Office of Transportation

and Air Quality

EPA420-R-04-007

May 2004

Final Regulatory Analysis:

Control of Emissions from

Nonroad Diesel Engines
EPA420-R-04-007

May 2004

Final Regulatory Impact Analysis:

Control of Emissions from

Nonroad Diesel Engines

Assessment and Standards Division

Office of Transportation and Air Quality

U.S. Environmental Protection Agency
CHAPTER 1: Industry Characterization

1.1 Characterization of Engine Manufacturers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.1.1 Engines Rated between 0-19 kW (0 and 25 hp) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.2 Engines Rated between 19 and 56 kW (25 and 75 hp) . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.3 Engines Rated between 56 and 130 kW (75 and 175 hp) . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.4 Engines Rated between 130 and 560 kW (175 and 750 hp) . . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.5 Engines Rated over 560 kW (750 hp) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

1.2 Characterization of Equipment Manufacturers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

1.2.1 Equipment Using Engines Rated under 19 kW (0 and 25 hp) . . . . . . . . . . . . . . . . . . . . 1-4

1.2.2 Equipment Using Engines Rated between 19 and 56 kW (25 and 75 hp) . . . . . . . . . . . 1-6

1.2.3 Equipment Using Engines Rated between 56kW and 130 kW (75 and 175 hp) . . . . . . 1-7

1.2.4 Equipment Using Engines Rated between 130 and 560 kW (175 and 750 hp) . . . . . . . 1-9

1.2.5 Equipment Using Engines Rated over 560 kW (750 hp) . . . . . . . . . . . . . . . . . . . . . . . 1-11

1.3 Refinery Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-12

1.3.1 The Supply-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-12

1.3.2 The Demand Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-19

1.3.3 Industry Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-26

1.3.4 Markets and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-30

1.4 Distribution and Storage Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-35

1.4.1 The Supply-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-35

1.4.2 The Demand-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-37

1.4.3 Industry Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-37

1.4.4 Markets and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-38

CHAPTER 2: Air Quality, Health, and Welfare Effects

2.1 Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3

2.1.1 Health Effects of Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

2.1.2 Attainment and Maintenance of the PM10 and PM2.5 NAAQS: Current and Future Air

Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

2.1.3 Environmental Effects of Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-38

2.2 Air Toxics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-55

2.2.1 Diesel Exhaust PM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-55

2.2.2 Gaseous Air Toxics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-75

2.3 Ozone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-88

2.3.1 Health Effects of Ozone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-89

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS . . . . . . . . . . 2-92

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS . . . . . . . . . . 2-93

2.3.3 Welfare Effects Associated with Ozone and its Precursors . . . . . . . . . . . . . . . . . . . . 2-118

2.4 Carbon Monoxide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-121

CHAPTER 3: Emission Inventory

3.1 Nonroad Diesel Baseline Emission Inventory Development . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.1.1 Land-Based Nonroad Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions . . . 3-2

3.1.2 Land-Based Nonroad Diesel Engines—Air Toxics Emissions . . . . . . . . . . . . . . . . . . . 3-15

3.1.3 Commercial Marine Vessels and Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-16

3.1.4 Recreational Marine Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-21

3.1.5 Fuel Consumption for Nonroad Diesel Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-24

3.2 Contribution of Nonroad Diesel Engines to National Emission Inventories . . . . . . . . . . . . . . 3-26

3.2.1 Baseline Emission Inventory Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-26

3.2.2 PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28

3.2.3 NOx Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28

3.2.4 SO2 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29
3.2.5 VOC Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.2.6 CO Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.3 Contribution of Nonroad Diesel Engines to Selected Local Emission Inventories . . . . . . . . . 3-37

3.3.1 PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-37

3.3.2 NOx Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-41

3.4 Nonroad Diesel Controlled Emission Inventory Development . . . . . . . . . . . . . . . . . . . . . . . . 3-43

3.4.1 Land-Based Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions . . . . . . . . . 3-43

3.4.2 Land-Based Diesel Engines—Air Toxics Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . 3-52

3.4.3 Commercial Marine Vessels and Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-53

3.4.4 Recreational Marine Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-55

3.5 Projected Emission Reductions from the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-58

3.5.1 PM2.5 Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-58

3.5.2 NOx Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-66

3.5.3 SO2 Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-68

3.5.4 VOC and Air Toxics Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-75

3.5.5 CO Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-78

3.5.6 PM2.5 and SO2 Reductions from the 15 ppm Locomotive and Marine (LM) Fuel Program

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-79

3.5.7 SO2 and Sulfate PM Reductions from Other Nonhighway Fuel . . . . . . . . . . . . . . . . . . 3-81

3.6 Emission Inventories Used for Air Quality Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-86

CHAPTER 4: Technologies and Test Procedures for Low-Emission Engines

4.1 Feasibility of Emission Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1.1 PM Control Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.1.2 NOx Control Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-19

4.1.3 Can These Technologies Be Applied to Nonroad Engines and Equipment? . . . . . . . . 4-70

4.1.4 Are the Standards for Engines >25 hp and <75 hp Feasible? . . . . . . . . . . . . . . . . . . . . 4-82

4.1.5 Are the Standards for Engines <25 hp Feasible? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-94

4.1.6 Meeting the Crankcase Emission Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-101

4.1.7 Why Do We Need 15 ppm Sulfur Diesel Fuel? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-101

4.2 Transient Emission Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-110

4.2.1 Background and Justification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-110

4.2.2 Data Collection and Cycle Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-113

4.2.3 Composite Cycle Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-126

4.2.4 Cycle Characterization Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-128

4.2.5 Cycle Normalization/Denormalization Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-129

4.2.6 Cycle Performance Regression Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-130

4.2.7 Constant-Speed, Variable-Load Equipment Considerations . . . . . . . . . . . . . . . . . . . 4-130

4.2.8 Cycle Harmonization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-134

4.2.9 Cold-Start Transient Test Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-146

4.2.10 Applicability of Component Cycles to Nonroad Diesel Market . . . . . . . . . . . . . . . . 4-148

4.2.11 Final Certification Cycle Selection Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-151

4.3 Steady-State Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-152

4.3.1 Ramped Modal Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-153

4.3.2 Transportation Refrigeration Unit Test Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-166

4.4 Not-to-Exceed Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-169

CHAPTER 5: Fuel Standard Feasibility

5.1 The Blendstocks and Properties of Non-Highway Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1.1 Blendstocks Comprising Non-highway Diesel Fuel and their Sulfur Levels . . . . . . . . 5-1

5.1.2 Current Levels of Other Fuel Parameters in Non-highway Distillate . . . . . . . . . . . . . . . 5-2

5.2 Evaluation of Diesel Fuel Desulfurization Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4
5.2.1 Introduction to Diesel Fuel Sulfur Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.2.2 Conventional Hydrotreating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.2.3 Process Dynamics Isotherming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-18

5.2.4 Phillips S-Zorb Sulfur Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-22

5.2.5 Chemical Oxidation and Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-23

5.3 Feasibility of Producing 500 ppm Sulfur NRLM Diesel Fuel in 2007 . . . . . . . . . . . . . . . . . . 5-25

5.3.1 Expected use of Desulfurization Technologies for 2007 . . . . . . . . . . . . . . . . . . . . . . . 5-25

5.3.2 Lead-time Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-26

5.4 Feasibility of Producing 15 ppm Sulfur NRLM in 2010 and 2012 . . . . . . . . . . . . . . . . . . . . . 5-34

5.4.1 Expected use of Desulfurization Technologies in 2010 and 2012 . . . . . . . . . . . . . . . . 5-34

5.4.2 Lead-time Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-37

5.5 Distribution Feasibility Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-38

5.5.1 Ability of Distribution System to Accommodate the Need for Additional Product

Segregations That Could Result from This Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-38

5.5.2 Limiting Sulfur Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-61

5.5.3 Handling Practices for Distillate Fuels that Become Mixed in the Pipeline Distribution

System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-63

5.6 Feasibility of the Use of a Marker in Heating Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-66

5.7 Impacts on the Engineering and Construction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-73

5.7.1 Design and Construction Resources Related to Desulfurization Equipment . . . . . . . . 5-74

5.7.2 Number and Timing of Revamped and New Desulfurization Units . . . . . . . . . . . . . . . 5-75

5.7.3 Timing of Desulfurization Projects Starting up in the Same Year . . . . . . . . . . . . . . . . 5-76

5.7.4 Timing of Design and Construction Resources Within a Project . . . . . . . . . . . . . . . . . 5-76

5.7.5 Projected Levels of Design and Construction Resources . . . . . . . . . . . . . . . . . . . . . . . 5-78

5.8 Supply of Nonroad, Locomotive, and Marine Diesel Fuel (NRLM) . . . . . . . . . . . . . . . . . . . 5-82

5.9 Desulfurization Effect on Other Non-Highway Diesel Fuel Properties . . . . . . . . . . . . . . . . . 5-90

5.9.1 Fuel Lubricity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-90

5.9.2 Volumetric Energy Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-93

5.9.3 Fuel Properties Related to Storage and Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-95

5.9.4 Cetane Index and Aromatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-95

5.9.5 Other Fuel Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-96

Appendix 5A: EPA’s Legal Authority for Adopting Nonroad, Locomotive, and Marine Diesel Fuel

Sulfur Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-99

CHAPTER 6: Estimated Engine and Equipment Costs

6.1 Methodology for Estimating Engine and Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2

6.2 Engine-Related Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.1 Engine Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.2 Engine Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-25

6.2.3 Engine Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-49

6.3 Equipment-Related Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-60

6.3.1 Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-61

6.3.2 Equipment Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-69

6.3.3 Potential Impact of the Transition Provisions for Equipment Manufacturers . . . . . . . 6-72

6.4 Summary of Engine and Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-74

6.4.1 Engine Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-74

6.4.2 Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-77

6.4.3 Engine and Equipment Costs on a Per Unit Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-78

6.5 Weighted Average Costs for Example Types of Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . 6-82

6.5.1 Summary of Costs for Some Example Types of Equipment . . . . . . . . . . . . . . . . . . . . 6-82

6.5.2 Method of Generating Costs for a Specific Piece of Equipment . . . . . . . . . . . . . . . . . 6-86
6.5.3 Costs for Specific Examples from the Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-89

6.6 Residual Value of Platinum Group Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-90

CHAPTER 7: Estimated Costs of Low-Sulfur Fuels

7.1 Production and Consumption of NRLM Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

7.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

7.1.2 Distillate Fuel Production and Demand in 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

7.1.3 Distillate Fuel Production and Demand in 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-18

7.1.4 Sensitivity Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-45

7.1.5 Methodology for Annual Distillate Fuel Demand: 1996 to 2040 . . . . . . . . . . . . . . . . . 7-62

7.1.6 Annual Distillate Fuel Demand and Sulfur Content . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-67

7.2 Refining Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-86

7.2.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-86

7.2.2 Refining Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-157

7.3 Cost of Lubricity Additives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-188

7.4 Cost of Distributing Non-Highway Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-189

7.4.1 New Production Segregation at Bulk Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-190

7.4.2 Reduction in Fuel Volumetric Energy Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-192

7.4.3 Handling of Distillate Fuel Produced from Pipeline Interface . . . . . . . . . . . . . . . . . . 7-194

7.4.4 Fuel Marker Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-200

7.4.5 Distribution and Marker Costs Under Alternative Sulfur Control Options . . . . . . . . 7-205

7.5 Total Cost of Supplying NRLM Fuel Under the Two-Step Program . . . . . . . . . . . . . . . . . . 7-206

7.6 Potential Fuel Price Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-208

CHAPTER 8: Estimated Aggregate Cost and Cost per Ton of Reduced Emissions

8.1 Projected Sales and Cost Allocations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-2

8.2 Aggregate Engine Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-3

8.2.1 Aggregate Engine Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-3

8.2.2 Aggregate Engine Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-7

8.3 Aggregate Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

8.3.1 Aggregate Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

8.3.2 Aggregate Equipment Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-13

8.4 Aggregate Fuel Costs and Other Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-15

8.4.1 Aggregate Fuel Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-16

8.4.2 Aggregate Oil-Change Maintenance Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18

8.4.3 Aggregate CDPF Maintenance, CDPF Regeneration, and CCV Maintenance Costs . . 8-20

8.4.4 Summary of Aggregate Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-22

8.4.5 Summary of Aggregate Operating Costs Associated with a Fuel-only Scenario . . . . . 8-24

8.5 Summary of Aggregate Costs of the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-26

8.6 Emission Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-29

8.7 Cost per Ton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-30

8.7.1 Cost per Ton for the NRT4 Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-30

8.7.2 Cost per Ton for the NRLM Fuel-only Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-34

8.7.3 Costs and Costs per Ton for Other Control Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . 8-37

8.7.4 Costs per Ton Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-63

Appendix 8A: Estimated Aggregate Cost and Cost per Ton of Sensitivity Analyses . . . . . . . . . . 8-65

Appendix 8B: Fuel Volumes used throughout Chapter 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-89

CHAPTER 9: Cost-Benefit Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-1

9.1 Time Path of Emission Changes for the Final Standards . . . . . . . . . . . . . . . . . . . . . . . 9-8

9.2 Development of Benefits Scaling Factors Based on Differences in Emission Impacts

Between the Final Standards and Modeled Preliminary Control Options . . . . . . . . 9-11

9.3 Summary of Modeled Benefits and Apportionment Method . . . . . . . . . . . . . . . . . . . 9-12
9.3.1 Overview of Analytical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-16

9.3.2 Air Quality Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-17

9.3.3 Health Impact Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-19

9.3.4 Economic Values for Health Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-23

9.3.5 Welfare Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-24

9.3.6 Treatment of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-28

9.3.7 Model Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-29

9.3.8 Apportionment of Benefits to NOx, SO2, and Direct PM Emissions Reductions9-39

9.4 Estimated Benefits of Final Nonroad Diesel Engine Standards in 2020 and 2030 . . 9-42

9.5 Development of Intertemporal Scaling Factors and Calculation of Benefits Over Time9-48

9.6 Comparison of Costs and Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-53

Appendix 9A: Benefits Analysis of Modeled Preliminary Control Option . . . . . . . . . . . 9-77

Appendix 9B: Supplemental Analyses Addressing Uncertainties in the ConcentrationResponse and Valuation Functions for Particulate Matter Health Effects . . . . . . . 9-205

Appendix 9C: Sensitivity Analyses of Key Parameters in the Benefits Analysis . . . . . 9-253

Appendix 9D: Visibility Benefits Estimates for Individual Class I Areas . . . . . . . . . . 9-271

CHAPTER 10: Economic Impact Analysis

10.1 Overview and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-1

10.1.1 What is an Economic Impact Analysis? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-1

10.1.2 What Methodology Did EPA Use in this Economic Impact Assessment? . . . . . . . . . 10-1

10.1.3 What are the key features of the NDEIM? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-4

10.1.4 Summary of Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-13

10.2 Economic Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-27

10.2.1 Behavioral Economic Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-27

10.2.2 Conceptual Economic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-28

10.2.3 Key Modeling Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-36

10.2.4 Estimation of Social Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-46

10.3 NDEIM Model Inputs and Solution Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-49

10.3.1 Description of Product Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-50

10.3.2 Market Linkages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-57

10.3.3 Baseline Economic Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-57

10.3.4 Calibrating the Fuel Spillover Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-66

10.3.5 Compliance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-66

10.3.6 Growth Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-79

10.3.7 Market Supply and Demand Elasticities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-79

10.3.8 Model Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-83

10.4 Estimating Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-86

Appendix 10A: Impacts on the Engine Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-92

Appendix 10B: Impacts on Equipment Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-101

Appendix 10C: Impacts on Application Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-152

Appendix 10D: Impacts on the Nonroad Fuel Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-158

Appendix 10E: Time Series of Social Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-163

Appendix 10F: Model Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-167

Appendix 10G: Elasticity Parameters for Economic Impact Modeling . . . . . . . . . . . . . . . . . . . 10-172

Appendix 10H: Derivation of Supply Elasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-188

Appendix 10I: Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-189

CHAPTER 11: Small-Business Flexibility Analysis

11.1 Overview of the Regulatory Flexibility Act . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-1

11.2 Need for the Rulemaking and Rulemaking Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-2
11.3 Issues Raised by Public Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-2

11.3.1 Comments Regarding Small Business Engine and Equipment Manufacturers . . . . . 11-3

11.3.2 Comments Regarding Small Fuel Refiners, Distributors, and Marketers . . . . . . . . . . 11-3

11.4 Description of Affected Entities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-6

11.4.1 Description of Nonroad Diesel Engine and Equipment Manufacturers . . . . . . . . . . . 11-7

11.4.2 Description of the Nonroad Diesel Fuel Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-9

11.5 Projected Reporting, Recordkeeping, and Other Compliance Requirements of the Regulation

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-10

11.6 Steps to Minimize Significant Economic Impact on Small Entities . . . . . . . . . . . . . . . . . . 11-11

11.6.1 Transition and Hardship Provisions for Small Engine Manufacturers . . . . . . . . . . . 11-12

11.6.2 Transition and Hardship Provisions for Nonroad Diesel Equipment Manufacturers 11-16

11.6.3 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Refiners . . . . . 11-20

11.6.4 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Distributors and

Marketers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-26

11.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-27

CHAPTER 12: Regulatory Alternatives

12.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-1

12.2 Description of Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-2

12.2.1 One-Step Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-3

12.2.2 Two-Step Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-7

List of Acronyms

ABT Averaging, Banking, and Trading 

AEO Annual Energy Outlook

AGME Above-ground mining equipment

APA Administrative Procedures Act

AT Aftertreatment

BSFC Brake Specific Fuel Consumption

CAA Clean Air Act

CCV Closed crankcase ventilation

CDPF Catalyzed diesel particulate filter

CFR Code of Federal Regulations

CI Compression-Ignition

CMV Commercial Marine Vessel

CO Carbon monoxide

DF Deterioration Factor

DI direct injection

DOC Diesel oxidation catalyst

EF Emission Factor

EGR Exhaust gas recirculation

EIA U. S. Energy Information Administration

EIA Economic Impact Analysis 

FR Federal Register

FTC Federal Trade Commission 

GPA Geographic Phase-In Area

GDP Gross domestic product

HC Hydrocarbons

HD2007 Heavy-duty 2007 refers to the final rule setting emission standards for 2007 and later engines

hp Horsepower

IDI Indirect injection

IRFA Initial Regulatory Flexibility Analysis

kW kilowatt

L&M Locomotive and marine

MPP marginal physical product

NAICS North American Industry Classification System

NDEIM Nonroad Diesel Economic Impact Model 

NMHC Non-methane hydrocarbons
NPV Net present value

NR Nonroad

NRLM Nonroad, Locomotive, and Marine diesel fuel 

O&M operating and maintenance 

OMB Office of Management and Budget 

PADD Petroleum Administration Districts for Defense

PM Particulate matter

ppm Parts per million

PSR Power Systems Research 

PTD Product Transfer Document

R&D Research and Development

RFA Regulatory Flexibility Act

RIA Regulatory Impact Analysis

SBA Small Business Administration 

SBAR Small Business Advocacy Review 

SBREFA Small Business Regulatory Enforcement Fairness Act 

SER Small Entity Representative

SIC Standard Industrial Classification 

stds standards

TAF Transient Adjustment Factor

TPEM Transition program for engine manufacturers (see 40 CFR 89.102 and the proposed 40 CFR

ULSD Ultra Low Sulfur Diesel

VMP value of marginal product 

VOC Volatile organic compounds

ZHL Zero-Hour Emission Level
Executive Summary

ES-1

Executive Summary

The Environmental Protection Agency (EPA) is adopting requirements to reduce emissions

of particulate matter (PM), oxides of nitrogen (NOX), and air toxics from nonroad diesel engines. 

This rule includes emission standards for new nonroad diesel engines. The rule also reduces the

level of sulfur for diesel fuels used in nonroad engines, locomotive engines, and marine engines. 

The reduction in sulfur for nonroad diesel fuel will enable the use of advanced emission-control

technology that new nonroad diesel engines will use to achieve the emission reductions called

for under the engine standards in this final rule. In addition, the reduction in sulfur will provide

important public health and welfare benefits by reducing emissions of PM and SO2 from

nonroad, locomotive and marine diesel engines.

This executive summary describes the relevant air-quality issues, highlights the new Tier 4

emission standards and fuel requirements, and gives an overview of the analyses in the rest of

this document.

Air Quality Background and Estimated Environmental Impact of the Final Rule

Emissions from nonroad, locomotive, and marine diesel engines contribute greatly to a

number of serious air pollution problems and would continue to do so in the future absent further

reduction measures. Such emissions lead to adverse health and welfare effects associated with

ozone, PM, NOX, SOx, and volatile organic compounds, including toxic compounds. In addition,

diesel exhaust is of specific concern because it is likely to be carcinogenic to humans by

inhalation, as well as posing a hazard from noncancer respiratory effects. Ozone, NOX, and PM

also cause significant public welfare harm, such as damage to crops, eutrophication, regional

haze, and soiling of building materials.

Millions of Americans continue to live in areas with unhealthy air quality that may endanger

public health and welfare. There are approximately 159 million people living in areas that either

do not meet the 8-hour ozone National Ambient Air Quality Standards (NAAQS) or contribute

to violations in other counties as noted in EPA’s recent nonattainment designations for part or all

of 474 counties. In addition, approximately 65 million people live in counties where air quality

measurements violate the PM2.5 NAAQS. These numbers do not include the tens of millions of

people living in areas where there is a significant future risk of failing to maintain or achieve the

ozone or PM2.5 NAAQS. Federal, state, and local governments are working to bring ozone and

PM levels into compliance with the NAAQS attainment and maintenance plans. The reductions

included in this final rule will play a critical part in these actions. Reducing regional emissions

of SOx is critical to this strategy for attaining the PM NAAQS and meeting regional haze goals in

our treasured national parks. SOx levels can themselves also pose a respiratory hazard.

In 1996, emissions from land-based nonroad diesel engines, locomotive engines, and marine
Final Regulatory Support Document

ES-2

diesel engines were estimated to be about 40 percent of the total mobile-source inventory of

PM2.5 (particulate matter less than 2.5 microns in diameter) and 25 percent of the NOX inventory. 

Absent this final rule, these contributions would be expected to grow to 44 percent and 47

percent by 2030 for PM2.5 and NOX, respectively. By themselves, land-based nonroad diesel

engines are a very large part of the mobile-source PM2.5 inventory for diesel engines,

contributing about 47 percent in 1996, and growing to 70 percent by 2020 without this final rule.

The requirements in this rule will result in substantial benefits to public health and welfare

and the environment through significant reductions in NOX and PM, as well as nonmethane

hydrocarbons (NMHC), carbon monoxide (CO), SOX and air toxics. By 2030, this program will

reduce annual emissions of NOX and PM by 738,000 and 129,000 tons, respectively. We

estimate these annual emission reductions will prevent 12,000 premature deaths, over 8,900

hospitalizations, 15,000 nonfatal heart attacks, and approximately 1 million days that people

miss work because of respiratory symptoms. The overall quantifiable benefits will total over $83

billion annually by 2030, with a 30-year net present value of $805 billion.

A comparison of the rule's quantified costs and quantified benefits indicates that estimated

benefits (approximately $80 billion per year) are much larger than estimated costs (roughly $2

billion per year). This favorable result was found to be robust in a variety of sensitivity and

uncertainty analyses. The favorable net benefits are particularly impressive since there are a

substantial number of health and environmental advantages of the rule that could not be

quantified. In the final Regulatory Impact Analysis, the Agency has done extensive analysis to

identify, describe and quantify the degree of uncertainty in the benefit estimates (see Chapter 9). 

This analysis suggests that the high end of the uncertainty range for this rule’s estimated benefits

could exceed the low end of the range by a factor of 20. In addition, illustrative calculations

indicate that the uncertainty range could span two orders of magnitude using the preliminary

results of an EPA-OMB collaborative study on expert judgment for the relative risk of mortality

from PM exposure. Despite the uncertainty inherent in the benefit-cost analysis for this rule, the

results strongly support a conclusion that the benefits will substantially exceed costs.

Engine Emission Standards

Tables 1 through 4 show the Tier 4 emission standards and when they apply. For most

engines, these standards are similar in stringency to the final standards included in the 2007

highway diesel program and are expected to require the use of high-efficiency aftertreatment

systems. As shown in the Table 2, we are phasing in many of the standards over time to address

considerations of lead time, workload, and overall feasibility. In addition, the final rule includes

other provisions designed to address the transition to meeting the long-term Tier 4 standards.
Executive Summary

ES-3

Table 1—Tier 4 PM Standards (g/bhp-hr) and Schedule

Engine Power

Model Year

2008 2009 2010 2011 2012 2013

hp < 25 (kW < 19) 0.30 a

25 # hp < 75 (19 # kW < 56) 0.22 b 0.02

75 # hp < 175 (56 # kW < 130) 0.01

175 # hp # 750 (130 # kW # 560) 0.01

hp > 750 (kW > 560) see Table 3

Notes:

a For air-cooled, hand-startable, direct injection engines under 11 hp, a manufacturer may instead delay

implementation until 2010 and demonstrate compliance with a less stringent PM standard of 0.45 g/bhp-hr,

subject also to additional provisions discussed in section II.A.3.a of the preamble. b

 A manufacturer has the option of skipping the 0.22 g/bhp-hr PM standard for all 50-75 hp engines. The 0.02

g/bhp-hr PM standard would then take effect one year earlier for all 50-75 hp engines, in 2012.

Table 2—Tier 4 NOx and NMHC Standards and Schedule

Engine Power

Standard (g/bhp-hr) Phase-in Schedulea (model year)

NOx NMHC 2011 2012 2013 2014

25 # hp < 75 (19 # kW < 56) 3.5 NMHC+NOx b 100%

75 # hp < 175 (56 # kW < 130) 0.30 0.14 50% c 50% c 100% c

175 # hp # 750 (130 # kW # 560) 0.30 0.14 50% 50% 50% 100%

hp > 750 (kW > 560) see Table 3

Notes:

a

 Percentages indicate production required to comply with the Tier 4 standards in the indicated model year. b

 This is the existing Tier 3 combined NMHC+NOx standard level for the 50-75 hp engines in this category. In

2013 it applies to the 25-50 hp engines as well.

c Manufacturers may use banked Tier 2 NMHC+NOx credits to demonstrate compliance with the 75-175 hp

engine NOx standard in this model year. Alternatively, manufacturers may forego this special banked credit

option and instead meet an alternative phase-in requirement of 25/25/25% in 2012, 2013, and 2014 through

December 30, with 100% compliance required beginning December 31, 2014. See sections III.A and II.A.2.b of

the preamble.
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Table 3 – Tier 4 Alternative NOx Phase-in Standards (g/bhp-hr)

Engine Power

 NOx Standard

(g/bhp-hr)

75 # hp < 175 (56 # kW < 130) 1.7 a

175 # hp # 750 (130 # kW # 560) 1.5

Notes:

a Under the option identified in footnote b of Table 2, by which manufacturers may meet an alternative phase-in

requirement of 25/25/25% in 2012, 2013, and 2014 through December 30, the corresponding alternative NOx

standard is 2.5 g/bhp-hr.

Table 4—Tier 4 Standards for Engines Over 750 hp (g/bhp-hr)

engines used in:

2011 2015

PM NOx NMHC PM NOx NMHC

generator sets #1200 hp 0.075 2.6 0.30 0.02 0.50 0.14

generator sets >1200 hp 0.075 0.50 0.30 0.02 no new 

standard

0.14

all other equipment 0.075 2.6 0.30 0.03 no new 

standard

0.14

 EPA has also taken steps to ensure that engines built to these standards achieve effective realworld emission control including the transient duty cycle (both cold-start and hot-start testing),

steady-state duty cycles, and Not-to-Exceed standards and test procedures. The Not-to-Exceed

provisions are modeled after the highway program, with which much of the industry has gained

some level of experience.

Feasibility of Meeting Tier 4 Emission Standards

For the past 30 or more years, emission-control development for gasoline vehicles and

engines has concentrated most aggressively on aftertreatment technologies (i.e., in-exhaust

catalyst technologies). These devices currently provide as much as or more than 95 percent of

the emission control on a gasoline vehicle. In contrast, the emission-control development work

for highway and nonroad diesel engines has concentrated on improvements to the engine itself to

limit the emissions formed in the engine (engine-out control technologies). 

During the past 15 years, however, more development effort has been put into catalytic 

exhaust emission-control devices for diesel engines, particularly in the area of particulate matter

(PM) control. Those developments, and recent developments in diesel NOx exhaust emissioncontrol devices, make the widespread commercial use of highly efficient diesel exhaust emission

controls feasible. EPA has recently set new emission standards for diesel engines installed in
Executive Summary

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highway vehicles based on the emission-reduction potential of these devices. These devices will

also make possible a level of emission control for nonroad diesel engines that is similar to that

attained by gasoline catalyst systems. However, without the same ultra-low-sulfur diesel fuel

that will be used by highway engines, these technologies cannot be implemented. 

The primary focus of the Tier 4 program is the transfer of catalyst based emission control

technologies developed for on-highway diesel engines to nonroad engines. This RIA

summarizes extensive analyses evaluating the effectiveness of these new emission control

technologies and the specific challenges to further develop these technologies for nonroad

applications. The RIA concludes that for a very significant fraction of nonroad diesel engines

and equipment, the application of advanced catalyst based emission control technology is

feasible in the Tier 4 timeframe given the availability of 15 ppm sulfur diesel fuel.

Although the primary focus of the Tier 4 emissions program and the majority of the analyses

contained in this RIA are directed at the application of catalytic emission control technologies

enabled by 15 ppm sulfur diesel fuel, there are also important elements of the program based

upon continuing improvements in engine-out emission controls. Like the advanced catalytic

based technologies, these engine-out emission solutions for nonroad diesel engines rely upon

technologies already applied to on-highway diesel engines. Additionally, these technologies

form the basis for the Tier 3 emission standards for some nonroad diesel engines in other size

categories. 

Controls on the Sulfur Content of Diesel Fuel

We are finalizing the a two-step sulfur standard for nonroad, locomotive and marine

(NRLM) diesel fuel that will achieve significant, cost-effective sulfate PM and SO2 emission

reductions. These emission reductions will, by themselves, provide dramatic environmental and

public health benefits which far outweigh the cost of meeting the standards necessary to achieve

them. In addition, the final sulfur standards for nonroad diesel fuel will enable advanced high

efficiency emission control technology to be applied to nonroad engines. As a result, these

nonroad fuel sulfur standards, coupled with our program for more stringent emission standards

for new nonroad engines and equipment, will also achieve dramatic NOx and PM emission

reductions. Sulfur significantly inhibits or impairs the function of the diesel exhaust emission

control devices which will generally be necessary for nonroad diesel engines to meet the

emission standards in this final rule. With the 15 ppm sulfur standard for nonroad diesel fuel, we

have concluded that this emission control technology will be available for model year 2011 and

later nonroad diesel engines to achieve the NOx and PM emission standards adopted in this final

rule. The benefits of this final rule also include the sulfate PM and SO2 reductions achieved by

establishing the same standard for the sulfur content of locomotive and marine diesel fuel.

The fuel sulfur requirements established under this final rule are similar to the sulfur limits

established for highway diesel fuel in prior rulemakings – 500 ppm in 1993 ( 55 FR 34120,

August 21, 1990) and 15 ppm in 2006 (66 FR 5002, January 18, 2001). Beginning June 1, 2007,

refiners will be required to produce NRLM diesel fuel with a maximum sulfur content of 500
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ppm. Then, beginning June 1, 2010, the sulfur content will be reduced for nonroad diesel fuel to

a maximum of 15 ppm. The sulfur content of locomotive and marine diesel fuel will be reduced

to 15 ppm beginning June 1, 2012. The program contains certain provisions to ease refiners'

transition to the lower sulfur standards and to enable the efficient distribution of all diesel fuels.

The final program also contains provisions to smooth the refining industry's transition to the

low sulfur fuel requirements, encourage earlier introduction of cleaner burning fuel, maintain the

fuel distribution system's flexibility to fungibly distribute similar products, and provide an outlet

for off-specification distillate product. These provisions, which will maintain, and even enhance,

the health and environmental benefits of this rule, include the 2012 date for locomotive and

marine diesel fuel, early credits for refiners and importers and special provisions for small

refiners, transmix processors, and entities in the fuel distribution system.

Feasibility of Meeting Diesel Fuel Sulfur Standards

We conclude that it is feasible for refiners to meet the 500 ppm and 15 ppm sulfur cap

standards for nonroad, locomotive and marine diesel fuel (NRLM). We project that refiners will

use conventional desulfurization technology for complying with the 500 ppm sulfur standard in

2007, which is the same technology used to produce 500 ppm sulfur highway diesel fuel today. 

Refiners complying with the 500 ppm sulfur NRLM diesel fuel standard will have about the

same amount of lead time refiners had in complying with the highway diesel fuel standard, when

it took affect in 1993, and they can draw on their experience gained from complying with the

1993 highway sulfur standard. Thus we conclude that refiners producing 500 ppm NRLM diesel

fuel will have sufficient leadtime. For complying with the 15 ppm sulfur cap standards

applicable to nonroad diesel fuel in 2010 and to locomotive and marine diesel fuel in 2012,

refiners will be able to use the experience gained from complying with the 15 ppm highway

diesel fuel standard which begins to take effect in 2006. Furthermore, refiners will have ample

lead time of at least six years before they will have to begin to produce 15 ppm sulfur nonroad

diesel fuel. For complying with both the 15 ppm sulfur standard for nonroad diesel fuel in 2010

and the locomotive and marine diesel fuel in 2012, we expect many refiners to utilize lower cost

advanced desulfurization technologies which have recently been commercialized. Others will

rely on extensions of conventional hydrotreating technology which most refiners are planning on

using to comply with the 15 ppm cap for highway diesel fuel in 2006. These technologies will

enable refiners to achieve the 15 ppm NRLM sulfur standards.

We do not expect any new significant issues regarding the feasibility of distributing

NRLM fuels that meet the sulfur standards in this rule. The highway diesel program

acknowledged that limiting sulfur contamination during the distribution of 15 ppm diesel fuel

would be a significant challenge to industry. Industry is already taking the necessary steps to

rise to this challenge to distribute highway diesel fuel meeting a 15 ppm sulfur standard by the

2006 implementation date for this standard. Thus, we believe that any issues regarding limiting

sulfur contamination during the distribution of 15 ppm sulfur nonroad, and locomotive/marine

diesel fuel will have been resolved a number of years before the implementation of the 15 ppm

sulfur standard for these fuels (in 2010 and 2012 respectively).
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The fuel program in this rule is structured in such a way to maximize fuel fungibility and

minimize the need for additional segregation of products in the fuel distribution system. Thus,

this rule will only result in the need for a limited number of additional storage tanks at terminals

and bulk plants in the interim, and in the long run will result in a simplified overall product slate

that needs to be distributed.

Estimated Costs and Cost-Effectiveness

There are approximately 600 nonroad equipment manufacturers using diesel engines in

several thousand different equipment models. There are more than 50 engine manufacturers

producing diesel engines for these applications. Fixed costs consider engine research and

development, engine tooling, engine certification, and equipment redesign. Variable costs

include estimates for new emission-control hardware. Near-term and long-term costs for some

example pieces of equipment are shown in Table 5. Also shown in Table 5 are typical prices for

each piece of equipment for reference. See Chapter 6 for detailed information related to our

engine and equipment cost analysis.

Table 5— Long-Term Costs for Several Example Pieces of Equipment ($2002)a

GenSet Skid/Steer

Loader

Backhoe Dozer Agricultural

Tractor

Dozer OffHighway

Truck

Horsepower 9 hp 33 hp 76 hp 175 hp 250 hp 503 hp 1000 hp

Displacement (L) 0.4 1.5 3.9 10.5 7.6 18 28

Incremental Engine &

Equipment Cost

 Long Term

 Near Term

$120

$180

$790

$1,160

$1,200

$1,700

$2,560

$3,770

$1,970

$3,020

$4,140

$6,320

$4,670

$8,610

Estimated Equipment

Priceb

$4,000 $20,000 $49,000 $238,000 $135,000 $618,000 $840,000

a

 Near-term costs include both variable costs and fixed costs; long-term costs include only variable costs and represent

those costs that remain following recovery of all fixed costs.

Our estimated costs related to changing to ultra-low-sulfur fuel take into account all of

the necessary changes in both refining and distribution practices. We have estimated the cost of

producing 500 ppm sulfur NRLM fuel to be, on average, 2.1 to 3.5 cents per gallon. Average

costs for 15 ppm sulfur NR fuel during the years 2010 through 2012 are estimated to be an

additional 2.5 cents per gallon for a combined cost of 5.8 cents per gallon. Average costs for 15

ppm sulfur NRLM fuel are estimated to be an additional 1.2 cents per gallon for a combined cost

of 7.0 cents per gallon for the years 2014 and beyond. All of these fuel costs are summarized in

Table 6. These ranges consider variations in regional issues in addition to factors that are

specific to individual refiners. In addition, engines running on low-sulfur fuel will have reduced

maintenance expenses that we estimate will be equivalent to reducing the cost of the fuel by 2.9
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to 3.2 cents per gallon.

Table 6—Increased Cost of Providing Nonroad, 

Locomotive and Marine Diesel Fuel (cents per gallon of affected fuel)

Specification Year Refining Costs

(c/gal)

Distribution &

Additive Costs (c/gal)

Total Costs

(c/gal)

500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm NRLM 2010-12 2.7 0.6 3.3

500 ppm NRLM 2012-14 2.9 0.6 3.5

15 ppm Nonroad 2010-12 5.0 0.8 5.8

15 ppm NRLM 2012-14 5.6 0.8 6.4

15 ppm NRLM 2014+ 5.8 1.2 7.0

Chapter 8 describes the analysis of aggregating the incremental fuel costs, operating

costs, and the costs for producing compliant engines and equipment, operating costs. Table 7

compares these aggregate costs with the corresponding estimated emission reductions to present

cost-per-ton figures for the various pollutants.

Table 7—Aggregate Cost per Ton for the Proposed Two-Step Fuel Program 

and Engine Program—2004-2036 Net Present Values at 3% Discount Rate ($2002)

Pollutant Aggregate Discounted Lifetime Cost per ton

NOx+NMHC $1,010

PM $11,200

SOx $690

Economic Impact Analysis

As described in Chapter 10, we prepared an Economic Impact Analysis (EIA) to estimate

the economic impacts of this rule on producers and consumers of nonroad engines and

equipment and fuels, and related industries. The EIA has two parts: a market analysis and a

welfare analysis. The market analysis explores the impacts of the proposed program on prices

and quantities of affected products. The welfare analysis focuses on changes in social welfare

and explores which entities will bear the burden of the proposed program. The EIA relies on the

Nonroad Diesel Economic Impact Model (NDEIM). The NDEIM uses a multi-market analysis

framework that considers interactions between 62 regulated markets and other markets to

estimate how compliance costs can be expected to ripple through these markets.

As shown in Table 8, the market impacts of this rule suggest that the overall economic
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impact on society is expected to be small, on average. According to this analysis, price increases

of goods and services produced using equipment and fuel affected by this rule (the application

marktets) are expected to average about 0.1 percent per year. Output decrease in the application

markets are expected to average less than 0.02 percent for all years. The price increases for

engines, equipment, and fuel are expected to be about 20 percent, 3 percent, and 7 percent,

respectively (total impact averaged over the relevant years). The number of engines and

equipment produced annually is expected to decrease by less than 250 units, and the amount of

fuel produced annually is expected to decrease by less than 4 million gallons. 

Table 8—Summary of Expected Market Impacts, 2013 and 2020

Market 2013 2036

Average

engineering

cost per unit

Price change Quantity

change

Average

engineering

cost per unit

Price change Quantity

change

Engines $1,052 21.4% -0.014% $931 18.2% -0.016%

Equipment $1,198 2.9% -0.017% $962 2.5% -0.018%

Application

marketsa

— 0.10% -0.015% — 0.10% -0.016%

Nonroad Fuel

Markets

$0.06 6.0% -0.019% $0.07 7.0% -0.022%

Loco/Marine

Transportation

— 0.01% -0.007 — 0.01% -0.008

a

Commodities in the application markets are normalized; only percentage changes are presented

The welfare analysis predicts that consumers and producers in the application markets are

expected to bear the burden of this proposed program. In 2013, the total social costs of the rule

are expected to be about $1.5 billion. About 83 percent of the total social costs is expected to be

borne by producers and consumers in the application markets, indicating that the majority of the

costs associated with the rule are expected to be passed on in the form of higher prices. When

these estimated impacts are broken down, 58.5 percent are expected to be borne by consumers in

the application markets and 41.5 percent are expected to be borne by producers in the application

markets. Equipment manufacturers are expected to bear about 9.5 percent of the total social

costs. These are primarily the costs associated with equipment redesign. Engine manufacturers

are expected to bear about 2.8 percent; this is primarily the fixed costs for R&D. Nonroad fuel

refiners are expected to bear about 0.5 percent of the total social costs. The remaining 4.2

percent is accounted for by locomotive and marine transportation services.

Total social costs continue to increase over time and are projected to be about $2.0 billion

by 2030 and $2.2 billion in 2036 ($2002). The increase is due to the projected annual growth in

the engine and equipment populations. Producers and consumers in the application markets are
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expected to bear an even larger portion of the costs, approximately 96 percent. This is consistent

with economic theory, which states that, in the long run, all costs are passed on to the consumers

of goods and services.

Impact on Small Businesses

Chapter 11 discusses our Final Regulatory Flexibility Analysis, which evaluates the

potential impacts of new engine standards and fuel controls on small entities. Before issuing our

proposal, we analyzed the potential impacts of this rule on small entities. As a part of this

analysis, we interacted with several small entities representing the various affected sectors and

convened a Small Business Advocacy Review Panel to gain feedback and advice from these

representatives. This feedback was used to develop regulatory alternatives to address the

impacts of the rule on small businesses. Small entities raised general concerns related to

potential difficulties and costs of meeting the upcoming standards.

The Panel consisted of members from EPA, the Office of Management and Budget, and

the Small Business Administration’s Office of Advocacy. We either proposed or requested

comment on the Panel’s recommendations. Chapter 11 discusses the options recommended in

the Panel Report, the regulatory alternatives we considered in the proposal, and the provisions

we are adopting in the final rule. We have adopted several provisions that give small engine and

equipment manufacturers and small refiners several compliance options aimed specifically at

educing the burden on these small entities. In general the options are similar to small entity

provisions adopted in prior rulemakings where EPA set standards for nonroad diesel engines and

controlled the level of sulfur in highway gasoline and diesel fuel. These provisions will reduce

the burden on small entities that must meet this rule’s requirements.

Alternative Program Options

In the course of developing our final program, we investigated several alternative

approaches to both the engine and fuel programs. These alternative program options included

variations in:

• The applicability of aftertreatment-based standards for different horsepower

categories

• The phase-in schedule for engine standards

• The start date for the diesel fuel sulfur standard

• The use of a single-step instead of a two-step approach to fuel sulfur standards

• The applicability of the very-low fuel sulfur standards to fuel used by locomotives

and marine engines

Chapter 12 includes a complete description of twelve alternative program options. The

draft RIA contained an assessment of technical feasibility, cost, cost-effectiveness, inventory

impact, and health and welfare benefits for each alternative. We refer the reader to the detailed

evaluations of the options presented in the Draft Regulatory Impact Analysis.
CHAPTER 1: Industry Characterization

1.1 Characterization of Engine Manufacturers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.1.1 Engines Rated between 0-19 kW (0 and 25 hp) . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.2 Engines Rated between 19 and 56 kW (25 and 75 hp) . . . . . . . . . . . . . . . . . . . . . 1-2

1.1.3 Engines Rated between 56 and 130 kW (75 and 175 hp) . . . . . . . . . . . . . . . . . . . 1-2

1.1.4 Engines Rated between 130 and 560 kW (175 and 750 hp) . . . . . . . . . . . . . . . . . 1-2

1.1.5 Engines Rated over 560 kW (750 hp) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

1.2 Characterization of Equipment Manufacturers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

1.2.1 Equipment Using Engines Rated under 19 kW (0 and 25 hp) . . . . . . . . . . . . . . . 1-4

1.2.2 Equipment Using Engines Rated between 19 and 56 kW (25 and 75 hp) . . . . . . 1-6

1.2.3 Equipment Using Engines Rated between 56kW and 130 kW (75 and 175 hp) . 1-7

1.2.4 Equipment Using Engines Rated between 130 and 560 kW (175 and 750 hp) . . 1-9

1.2.5 Equipment Using Engines Rated over 560 kW (750 hp) . . . . . . . . . . . . . . . . . . 1-11

1.3 Refinery Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-12

1.3.1 The Supply-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-12

1.3.2 The Demand Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-19

1.3.3 Industry Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-26

1.3.4 Markets and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-30

1.4 Distribution and Storage Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-35

1.4.1 The Supply-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-35

1.4.2 The Demand-Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-37

1.4.3 Industry Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-37

1.4.4 Markets and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-38
Industry Characterization

1-1

CHAPTER 1: Industry Characterization

In understanding the impact of emission standards on regulated industries, it is important to

assess the nature of the regulated and otherwise affected industries. The industries affected are

the nonroad diesel engine and equipment manufacturing, oil-refining, and fuel-distribution

industries. This chapter provides market share information for the above industries. This

information is provided for background purposes. The information presented in this chapter will

be most helpful for those unfamiliar with the engine/equipment industry and/or the oil refining

and fuel-distribution industries.

Nonroad engines are generally distinguished from highway engines in one of four ways: (1)

the engine is used in a piece of motive equipment that propels itself in addition to performing an

auxiliary function (such as a bulldozer grading a construction site); (2) the engine is used in a

piece of equipment that is intended to be propelled as it performs its function (such as a

lawnmower); (3) the engine is used in a piece of equipment that is stationary when in operation

but portable ( such as a generator or compressor) or (4) the engine is used in a piece of motive

equipment that propels itself, but is primarily used for off-road functions (such as an off-highway

truck).

The nonroad category is also different from other mobile source categories because: (1) it

applies to a wider range of engine sizes and power ratings; (2) the pieces of equipment in which

the engines are used are extremely diverse; and (3) the same engine can be used in widely

varying equipment applications (for example, the same engine used in a backhoe can also be

used in a drill rig or in an air compressor). 

A major consideration in regulating nonroad engines is the lack of vertical integration in this

field. Although some nonroad engine manufacturers also produce equipment that rely on their

own engines, most engines are sold to various equipment manufacturers over which the original

engine manufacturer has minimal control. A characterization of the industry affected by this

rulemaking must therefore include equipment manufacturers as well as engine manufacturers.

Sections 1.1 and 1.2 characterize the nonroad engine and equipment industries based on

different manufacturers and their products and the diversity of the manufacturer pool for the

various types of equipment. They describe the nonroad diesel engine market and related 

equipment markets by power category. Additional information related to engine/equipment

profiles, including employment figures, production costs, information on engine component

materials and firm characteristics, are available in the docket.1

1.1 Characterization of Engine Manufacturers

For purposes of discussion, the characterization of nonroad engine manufacturers is arranged

by the power categories used to define the new emission standards. The information detailed in

this section was derived from the Power Systems Research database and trade journals.2 We
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recognize that the PSR database is not comprehensive, but have not identified a better source to

provide consistent data for identifying additional companies. The sales figures presented in this

chapter pertain to both mobile and stationary nonroad equipment . The former forms the bases

for cost and other analyses such as included in Chapters 6 and 10.

1.1.1 Engines Rated between 0-19 kW (0 and 25 hp)

In year 2000, sales of engines in this category comprised 18 percent (approximately 135,828

units) of the nonroad market. The largest manufacturers of engines in this category are Kubota

(36,601 units) and Yanmar (32,126 units). Seventy three percent of Yanmar’s engines are fourcycle, water-cooled, indirect-injection models. A majority of Kubota’s engines are also fourcycle, water-cooled indirect-injection models. Another major manufacturer in this category is

Kukje with 21,216 units.

1.1.2 Engines Rated between 19 and 56 kW (25 and 75 hp)

This is the largest category, comprised of 38 percent of engines with approximately 281,157

units sold in year 2000. Direct-injection (DI) engines account for 59 percent of this category

with 165,427 units. Yanmar has approximately 19 percent of the DI market share, followed by

Deutz (16%), Kubota (13%), Hatz (12%), Isuzu(10%) ,Caterpillar/Perkins(10% ) and Deere

(8%). Kubota dominates the Indirect-injection (IDI) market with 51 percent of sales , followed

by Daewoo Heavy Industries (12%), Ihi-Shibaura (12%), Isuzu(8%) and Caterpillar/Perkins

(5%). Ag tractors, generator sets, skid-steer loaders and refrigeration and air conditioning units

are the largest selling engines in this power range. 

1.1.3 Engines Rated between 56 and 130 kW (75 and 175 hp)

In year 2000, manufacturers sold approximately 206,028 engines in this power range. This

represents the second-largest category of nonroad engines with 28 percent of the total market. 

Almost all of these engines are DI. The top three manufacturers are John Deere (28%),

Caterpillar/Perkins (20%) and Cummins (17%). Other manufacturers include Case/ New

Holland, Deutz, Hyundai Motor, Isuzu, Toyota and Komatsu. The engines in this power range

are used mostly in agricultural equipment such as ag tractors. The second-largest use for these

engines is in construction equipment such as tractor/loader/backhoes and skid-steer loaders.

1.1.4 Engines Rated between 130 and 560 kW (175 and 750 hp)

Engines in this power range rank fourth (15% of the total market) in nonroad diesel engines

sales with approximately 108,172 units sold in year 2000. Almost all of these are DI engines. 

Deere has approximately 32 percent of the DI market, followed by Caterpillar/Perkins (22%),

Cummins (21%), Case/New Holland (8%),Volvo (4%), and then by Komatsu and Detroit Diesel

(each 3%). The largest selling engines in this category are used in agricultural equipment (ag

tractors), followed by construction equipment (wheel loaders, bulldozers, and excavators). 
Industry Characterization

1-3

1.1.5 Engines Rated over 560 kW (750 hp)

This is the smallest nonroad category with approximately 5,633 engines comprising 1

percent of the total nonroad market and consist of all DI engines. Caterpillar is the largest

manufacturer (44%), followed by Cummins (19%), Komatsu (18%), and Detroit Diesel (11%). 

Power generation is the principal application in this range, followed by large off-highway trucks

and other types of construction equipment such as crawlers , wheel loaders and bulldozers.

1.2 Characterization of Equipment Manufacturers

Nonroad equipment can be grouped into several categories. This section considers the

following seven segments: agriculture, construction, general industrial, lawn and garden,

material handling, pumps and compressors, and welders and generator sets. Engines used in

locomotives, marine applications, aircraft, recreational vehicles, underground mining equipment,

and all spark-ignition engines within the above categories are not included in this rulemaking.

Table 1.2-1 has examples of the types of nonroad equipment that will be impacted by this

rulemaking, arranged by category.

Table 1.2-1

Sampling of Nonroad Equipment Applications

Segment Applications

Agriculture Ag Tractor

Baler

Combine

Sprayer 

Windrower

Other Ag Equipment

Construction Bore/drill Rig

Crawler

Excavator

Grader

Off-highway Tractor

Off-highway Truck

Paver

Plate Compactor

Roller

Wheel Loader/Dozer

Tamper/Rammer

Scraper

Skid-Steer Loader

Trencher

General Industrial Concrete/Ind. Saw

Crushing Equipment

Oil Field Equipment

Refrigeration/AC

Scrubber/sweeper

Rail Maintenance

Lawn and Garden Lawn and Garden

Tractor

Commercial Mower Trimmer/edger/cutter

Pumps and Compressors Air Compressor

Hydro Power Unit

Pressure Washer

Pump

Gas Compressor

Irrigation Set

Material Handling Aerial Lift

Crane

Forklift 

Terminal Tractor

Rough-Terrain Forklift

Welders and Generators Generator Set, Welder Lt Plant/Signal Board

Based on power rating rating of the engines, a fraction of applications such as air

compressors, generator sets, hydropower units, irrigation sets, pumps and welders is considered
Final Regulatory Support Document

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to be stationary and therefore not subject to EPA emission standards for nonroad engines. 

However, the tables in Sections 1.2.1 to 1.2.5 account for all equipment manufactured, whether

stationary or mobile within an engine power category.

For purposes of discussion, nonroad equipment is grouped into five power ranges similar to

those used for characterizing nonroad engines. This section explores the characteristics of

nonroad equipment applications and the companies involved in manufacturing these equipment. 

This analysis includes several numerical summaries of different categories.

1.2.1 Equipment Using Engines Rated under 19 kW (0 and 25 hp)

The applications with the most sales are ag tractors followed by generator sets. There are

about 29 total applications with engines rated under 19 kW. The six leading manufacturers

produce 46 percent of the equipment in this category. Their collective sales volume over five

years (1996 to 2000) was approximately 251,000 pieces of equipment in a market that has a 

five-year total sales volume of 551,000. These manufacturers and the major equipment types

manufactured by them are shown in Table 1.2-2.

Table 1.2-2

Characterization of the Top 6 Equipment 

Manufacturers for Engines Rated below 19 kW

Original Equipment

Manufacturer

Major Equipment Manufactured Average

Annual Sales

Percentage

of Market

Engine

Characterization*

Ingersoll-Rand Refrigeration/AC, Skid-steer loaders,

and Excavators

13,394 12% W,NA, I

Deere & Company Agricultural tractors, Commercial

mowers, Lawn & garden tractors

11,042 10% W,NA, I

Korean Gen-sets Generator Sets 9,970 9% W,NA, I

China Gen-sets Generator Sets 5,559 5% W,NA,D/ I

SDMO Generator Sets 5,191 5% W/A,NA, D/I

Kubota Corp. Ag tractors,Lawn & garden tractors

Commercial mowers

5,117 5% W,NA,I

*W=water-cooled, A=air-cooled,O=oil cooled;NA=naturally aspirated,T=turbocharged;I=indirect 

injection,D=direct injection.

Sales for these top six OEMs are typified by generator sets, skid-steer loaders, ag tractors,

commercial mowers, and refrigeration/air conditioning units. The sales of the equipment are

listed in Table 1.2-3. The top six manufacturers have equipment that are typical of the market.

Fifty-six OEMs produce 92 percent of the equipment in this power range. 
Industry Characterization

1-5

Table 1.2-3

Equipment Sales Distribution for Engines Rated below 19 kW

Application Description Five-year sales Volume 

(1996-2000)

Average Annual

Sales

Percentage of Total

Sales

Generator sets 171,435 34,287 31.1

Agricultural tractors 59,863 11,973 9.5

Commercial mowers 59,713 11,943 9.5

Refrigeration/AC 57,668 11,534 9.2

Welders 32,284 6,457 5.1

Light plants/Signal boards 28,239 5,648 4.5

Skid-steer loaders 23,685 4,737 3.8

Lawn & garden tractors 17,879 3,576 2.8

Pumps 16,262 3,252 2.6

Rollers 12,063 2,413 1.9

Pressure washers 11,959 2,392 1.9

Plate compactors 11,535 2,307 1.8

Utility vehicles 8,502 1,700 1.4

Aerial lifts 7,058 1,412 1.1

Excavators 6,118 1,224 1.0

Mixers 4,639 928 0.7

Scrubbers/sweepers 2,829 566 0.4

Commercial turf equipment 2,627 525 0.4

Finishing equipment 2,351 470 0.4

Other general industrial equipment 2,334 467 0.4

Tampers/rammers 2,156 431 0.3

Tractor/loader/backhoes 1,794 359 0.3

Dumpers/tenders 1,689 338 0.3

Air compressors 1,516 303 0.2

Hydraulic power units 797 159 0.1

Trenchers 776 155 0.1

Concrete/industrial saws 733 147 0.1

Irrigation sets 614 123 0.1

Wheel loaders/bulldozers 502 100 0.1

Other agricultural equipment 426 85 0.1

Surfacing equipment 362 72 0.1

Bore/drill rigs 275 55 0.0

Listed Total 110,137 91.4

Grand Total 110,289 100.0
Final Regulatory Support Document

1-6

1.2.2 Equipment Using Engines Rated between 19 and 56 kW (25 and 75 hp)

All market segments are represented within the 19 to 56 kW range. They are made up of 55

applications and about 17 percent of total sales are by Ingersoll- Rand. For the 19 to 56 kW range,

the equipment uses either direct-injection or indirect-injection engines that are water-cooled or oilcooled and are either naturally aspirated or turbocharged. The six leading manufacturers produce

53 percent of the equipment in this category. These manufacturers are listed in Table 1.2-4. They

manufacture equipment typical of the market, such as agricultural tractors, generator sets, skid-steer

loaders and refrigeration/AC. These top selling applications represent about 70 percent of the

market as seen in Table 1.2-5. The top 90 percent of the market is supplied by 60 different

companies.

Table 1.2-4

Characterization of the Top 6 Equipment 

Manufacturers for Engines Rated between 19 and 56 kW 

Original Equipment Manufacturer Major Equipment Manufactured Average

Annual Sales

Percentage of

Market

Engine

Characterization*

Ingersoll-Rand Refrigeration A/C, Skid-steer

loaders, Air compressors

40,199 17% W/O,NA/T,D/I

Case New Holland Agricultural tractors, Skid-steer

loaders

23,194 10% W/O,NA/T,D/I

Thermadyne Holdings Generator sets 19,090 8% A,NA,D

Deere & Company Agricultural tractors, Skid-steer

loaders, Commercial mowers

17,752 7% W,NA/T,D

Kubota Corp. Agricultural tractors, Excavators,

Wheel Loaders, Bulldozers

14,391 6% W,NA/T,D/I

United Technologies Co. Refrigeration/AC 12,484 5% W,NA,D/I

*W=water-cooled, A=air-cooled,O=oil cooled;NA=naturally aspirated, T=turbocharged, I=indirect injection,

D=direct injection.
Industry Characterization

1-7

Table 1.2-5

Equipment Sales Distribution across Applications between 19 and 56 kW

Application Description Five-year sales

Volume 

(1996-2000)

 Average Annual

Sales

Percentage of

Total Sales

Agricultural tractors 286,295 57,259 24%

Generator sets 223,960 44,792 19%

Skid-steer loaders 177,925 35,585 15%

Refrigeration/AC 142,865 28,573 12%

Welders 60,035 12,007 5.0%

Commercial mowers 47,735 9,547 3.9%

Air compressors 33,840 6,768 2.8%

Trenchers 26,465 5,293 2.2%

Aerial lifts 25,810 5,162 2.1%

Forklifts 23,480 4,696 1.9%

Rollers 18,010 3,602 1.5%

Excavators 16,485 3,297 1.4%

Rough terrain forklifts 13,530 2,706 1.1%

Scrubbers/sweepers 11,770 2,354 1.0%

Light plants/signal boards 11,720 2,344 1.00%

Pumps 9,290 1,858 0.77%

Bore/drill rigs 9,000 1,800 0.74%

Utility vehicles 8,460 1,692 0.70%

Wheel Loaders/bulldozers 6,985 1,397 0.58%

Pressure washers 6,700 1,340 0.55%

Pavers 6,395 1,279 0.53%

Commercial turf 5,760 1,152 0.48%

Tractor/loader/backhoes 5,115 1,023 0.42%

Irrigation sets 4,300 860 0.36%

Concrete/industrial saws 3,400 680 0.28%

Other general industrial 3,400 680 0.28%

Chippers/grinders 2,625 525 0.22%

Crushing/processing equipment 2,305 461 0.19%

Hydraulic power units 1,950 390 0.16%

Terminal tractors 1,765 353 0.15%

Surfacing equipment 1,490 298 0.12%

Dumpers/tenders 1,055 211 0.09%

Listed Total 239,984 99.3%

Grand Total 241,710 100.0%

1.2.3 Equipment Using Engines Rated between 56kW and 130 kW (75 and 175 hp)

Engines rated between 56 and 130 kW are all direct-injection engines that are either watercooled (94% ), oil-cooled (4%) or air-cooled (2%). The six leading manufacturers produce 49

percent of the equipment in this category. Their collective sales volume over five years (1996 to

2000) was approximately 440,000 pieces of equipment in a market that has a five-year total sales

volume of 905,000. These manufacturers are shown in Table 1.2-6.
Final Regulatory Support Document

1-8

Table 1.2-6

Characterization of the Top 6 Equipment 

Manufacturers for Engines Rated between 56kW and 130 kW (75 and 175 hp)

Original Equipment

Manufacturer

Major Equipment Manufactured Average

Annual Sales

Percentage of

Market

Engine

Characterization*

Case New Holland Ag Tractors, Combines, Crawlers, Skid-steer

loaders, Tractors/loaders/backhoes

26,717 15% W,T,D

Deere & Company Ag Tractors, Combines, Wheel

Loaders/Dozers

25,648 14% W,T,D

Caterpillar Generator Sets, Scrapers, Crawlers,

Excavators, Wheel loaders, bulldozers,

Graders, Rough terrain fork-lifts

13,670 8% W,T/N,D

Ingersoll-Rand Air compressors, Rollers, Bore/drill rigs 10,169 6% W,T,D

Agco Agricultural tractors, Combines, Sprayers 6,182 3% W/A,T,D

Landini Holding Agricultural tractors 5,467 3% W,T/N,D

*W=water-cooled, A=air-cooled,O=oil cooled;NA=naturally aspirated, T=turbocharged, I=indirect injection,

D=direct injection.

Sales of these top six OEMs are typified by agricultural tractors, tractors/loaders/backhoes,

generator sets, skid-steer loaders, rough terrain fork-lifts, excavators, air compressors and

crawlers. The sales of these equipment are listed in Table 1.2-7. The top six manufacturers have

engines that are typical of the market. Seventy-two OEMs produce 90 percent of the equipment

in this power range. 
Industry Characterization

1-9

Table 1.2-7

Equipment Sales Distribution across Applications between 56 and 130 kW

Application Description Five-yr sales Volume 

(1996-2000)

Average

Annual Sales

Percentage of

Total Sales

Agricultural tractors 185,315 37,063 20%

Tractor/loader/backhoes 106,780 21,356 12%

Generator sets 103,490 20,698 11%

Skid-steer loaders 74,040 14,808 8.2%

Rough terrain forklfts 56,770 11,354 6.3%

Excavators 50,140 10,028 5.5%

Air compressors 32,080 6,416 3.5%

Crawlers 30,260 6,052 3.3%

Forklifts 29,705 5,941 3.3%

Wheel Loaders/bulldozers 27,520 5,504 3.0%

Rollers 23,195 4,639 2.6%

Commercial turf equipment 17,425 3,485 1.9%

Other general industrial 16,580 3,316 1.8%

Scrubbers/sweepers 16,005 3,201 1.8%

Irrigation sets 15,745 3,149 1.7%

Windrowers 11,385 2,277 1.3%

Pumps 10,265 2,053 1.1%

Sprayers 8,830 1,766 1.0%

Listed Total 163,108 90.1%

Grand Total 181,094 100.0%

1.2.4 Equipment Using Engines Rated between 130 and 560 kW (175 and 750 hp) 

For the 130 to 560 kW range (where 560 kW is included in the range), most of the

equipment uses direct-injection engines that are water-cooled and turbocharged. A few are

naturally aspirated. The six leading manufacturers produce 56 percent of the equipment in this

category. These manufacturers are listed in Table 1.2-8. Their products have the following

applications : ag tractors, combines, generator sets, wheel loaders/bull dozers, which is typical of

the market.

The 130 to 560 kW range is characterized by applications as shown in Table 1.2-9. They

represent about 94 percent of the market. The top 90 percent of this market is supplied by 60

OEMs. 
Final Regulatory Support Document

1-10

Table 1.2-8

Characterization of the Top 6 Equipment Manufacturers

for Engines Rated between 130 and 560 kW

Original Equipment

Manufacturer

Major Equipment Manufactured Average

Annual Sales

Percentage

of Market

Engine

Characterization*

Deere & Company Ag Tractors, Combines, Wheel

Loaders/bulldozers

27,990 27% W,T,D

Case New Holland Ag Tractors, Combines, Crawlers, Generator

Sets, Scrapers, Crawlers,

14,778 14% W,T,D

Caterpillar Excavators,wheel loaders/dozers, graders 13,151 13% W,T/N,D

Komatsu Crawlers, Excavators,Graders, Wheel

Loaders/Dozers

4,941 5% W,T,D

Ingersoll-Rand Air Compressors, Rollers, Bore/Drill Rigs 3,683 4% W,T,D

Agco Ag Tractors, Combines, Sprayers 3,194 3% W/A,T,D

*W=water-cooled, A=air-cooled,O=oil cooled;NA=naturally aspirated, T=turbocharged, I=indirect injection,

D=direct injection.

Table 1.2-9

Equipment Sales Distribution across Applications between 130 and 560 kW

Application Description Five-yr sales Volume 

(1996-2000)

Average Annual

Sales

Percentage of

Total Sales

Agricultural tractors 149,589 29,918 29.0%

Generator sets 57,400 11,480 11.0%

Wheel loaders/bulldozers 43,475 8,695 8.3%

Combines 35,743 7,149 6.8%

Excavators 35,166 7,033 6.7%

Crawlers 28,478 5,696 5.4%

Air compressors 20,884 4,177 4.0%

Graders 14,814 2,963 2.8%

Sprayers 12,193 2,439 2.3%

Terminal ractors 12,141 2,428 2.3%

Forest equipment 12,101 2,420 2.3%

Pumps 9,901 1,980 1.9%

Off-highway trucks 9,377 1,875 1.8%

Cranes 9,356 1,871 1.8%

Scrapers 7,097 1,419 1.4%

Bore/drill rigs 7,047 1,409 1.3%

Irrigation sets 6,835 1,367 1.3%

Rollers 6,055 1,211 1.2%

Other agricultural equipment 5,935 1,187 1.1%

Chippers/grinders 4,669 934 0.9%

Other construction equipment 4,142 828 0.8%

Listed Total 98,480 94.0%

Grand Total 492,398 100.0%
Industry Characterization

1-11

1.2.5 Equipment Using Engines Rated over 560 kW (750 hp)

 The largest engines, those rated over 560 kW, are produced only for the nonroad market

segments of construction equipment and welders and generators. As much as 35 percent of the

equipment in this power range is manufactured by Caterpillar. Most equipment manufacturers

must buy engines from another company. For most power categories, the Power Systems

Research database estimates that between 5 and 25 percent of equipment sales are from

equipment manufacturers that also produce engines. Since vertically integrated manufacturers

are typically very large companies, such as John Deere and Caterpillar, the companies that make

up this fraction of the market are in a distinct minority.

As in the previous category, the equipment rated over 560 kW uses mostly turbocharged,

direct-injection engines that are water-cooled. The leading six manufacturers produce 81 percent

of the equipment in this power range. These manufacturers are shown in Table 1.2-10. 

Although generator sets make up the majority of equipment sold in this range, a fraction of them

are considered stationary and are therefore not impacted by this rulemaking. Off-highway trucks

, wheel loaders/dozers and crawlers also have significant sales (see Table 1.2-11).

Table 1.2-10

Characterization of the Top 6 Equipment Manufacturers for Engines Rated over 560 kW 

Original Equipment

Manufacturer

Major Equipment Manufactured Average

Annual Sales

Percentage of

Market

Engine

Characterization*

Caterpillar Generator Sets, Off-highway trucks,

crawler tractors

1,857 35% W,T,D

Komatsu Crawlers, Wheel Loaders/Dozers, OffHighway Trucks1,376 26% W,T,D

Multiquip Generator Sets 336 6% W,T,D

Kohler Generator Sets 335 6% W,T,D

Cummins Generator Sets 325 6% W,T,D

Onis Visa Generator Sets 107 2% W,T,D

*W=water-cooled, A=air-cooled,O=oil cooled;NA=naturally aspirated, T=turbocharged, I=indirect injection,

D=direct injection.
Final Regulatory Support Document

1-12

Table 1.2-11

Equipment Sales Distribution across Applications over 560 kW

Application Description Five-yr sales Volume 

(1996-2000)

Average Annual

Sales

Percentage of Total

Sales

Generator sets 14,237 2,847 54%

Off-highway trucks 4,048 810 15%

Crawlers 3,857 771 15%

Wheel loaders/bulldozers 2,567 513 9.8%

Off-highway tractors 542 108 2.1%

Excavators 371 74 1.4%

Oil field equipment 225 45 0.9%

Chippers/grinders 132 26 0.5%

Listed Total 5,196 99.1%

Grand Total 5,241 100.0%

Section 1.3 characterizes the U.S. petroleum refinery industry, market structure and trends

as it pertains to distillate fuels, including nonroad diesel fuel. In addition, it covers refinery

operations that are directly impacted by this final rule. Section 1.4 discusses distribution of

refined petroleum products through pipelines from refineries, as well as storage operations for

these products. Sections 1.3 and 1.4 are both are based on a report prepared by RTI under EPA

contract, which is available in the docket.3

1.3 Refinery Operations

1.3.1 The Supply-Side

This section describes the supply side of the petroleum refining industry, including the

current refinery production processes and raw materials used. It also discusses the need for

potential changes in refinery production created by this final rule. Finally, it describes the three

primary categories of petroleum products affected by the rule and the ultimate costs of

production currently faced by the refineries.

Refinery Production Processes/Technology. Petroleum refining is the thermal and

physical separation of crude oil into its major distillation fractions, followed by further

processing (through a series of separation and chemical conversion steps) into highly valued

finished petroleum products. Although refineries are extraordinarily complex and each site has a

unique configuration, we will describe a generic set of unit operations that are found in most

medium and large facilities. A detailed discussion of these processes can be found in EPA’s

sector notebook of the petroleum refining industry (EPA, 1995); simplified descriptions are

available on the web sites of several major petroleum producers (Flint Hills Resources, 2002;

Chevron, 2002). 
Industry Characterization

1-13

Figure 1.3-1 shows the unit operations and major product flows in a typical refinery. After

going through an initial desalting process to remove corrosive salts, crude oil is fed to an

atmospheric distillation column that separates the feed into several fractions. The lightest

boiling range fractions are processed through reforming and isomerization units into gasoline or

diverted to lower-value uses such as LPG and petrochemical feedstocks. The middle-boiling

fractions make up the bulk of the aviation and distillate fuels produced from the crude. In most

refineries, the undistilled liquid (called bottoms) is sent to a vacuum still to further fractionate

this heavier material. Bottoms from the vacuum distillation can be further processed into

low-value products such as residual fuel oil, asphalt, and petroleum coke.

A portion of the bottoms from the atmospheric distillation, along with distillate from the

vacuum still, are processed further in a catalytic cracking unit or in a hydrocracker. These

operations break large hydrocarbon molecules into smaller ones that can be converted to highvalue gasoline and middle distillate products. Bottoms from the vacuum still are increasingly

processed in a coker to produce saleable coke and gasoline and diesel fuel blendstocks. The

cracked molecules are processed further in combining operations (alkylation, for example),

which combine small molecules into larger, more useful entities, or in reforming, in which

petroleum molecules are reshaped into higher quality species. It is in the reforming operation

that the octane rating of gasoline is increased to the desired level for final sale. A purification

process called hydrotreating helps remove chemically bound sulfur from petroleum products and

is critically important for refineries to process their refinery streams into valuable products and

to achieve the low sulfur levels required under the regulation.

For each of the major products, several product streams from the refinery will be blended

into a finished mixture. For example, diesel fuel typically has a straight-run fraction from crude

distillation, distillate from the hydrocracker, light-cycle oil from the catalytic cracker, and

hydrotreated gas oil from the coker. Several auxiliary unit operations are also needed in the

refinery complex, including hydrogen generation, catalyst handing and regeneration, sulfur

recovery, wastewater treatment, and blending and storage tanks. Table 1.3-1 shows average

yields of major products from U.S. refineries.
Final Regulatory Support Document

1-14

Source: Chevron. 2002. Diesel Fuel Refining and Chemistry. As accessed on August 19, 2002. 

www.chevron.com/prodserv/fuels/bulletin/diesel/L2_4_2rf.htm. 
 Industry Characterization

1-15

Table 1.3-1

Yields of Major Petroleum Products from Refinery Operations

Product Gallons per Barrel of Crude Percentage of Total Feed*

Crude Feed 42.0 100.0%

Gasoline 19.4 46.0%

Highway diesel fuel 6.3 15.0%

Jet Fuel 4.3 10.0%

Petroleum Coke 2.0 5.0%

Residual Fuel Oil 1.9 4.5%

LP Gas 1.9 4.5%

Home heating oil 1.6 4.0%

Asphalt 1.4 3.0%

Nonroad diesel fuel 0.8 2.0%

Other Products 4.0 9.5%

Total 43.6 104.0%

*Note: Total exceeds 100 percent due to volume gain during refining.

Source: Calculated from EIA data in Petroleum Supply Annual 2001. U.S. Department of Energy, Energy

Information Administration (EIA). 2002a. Petroleum Supply Annual 2001, Tables 16, 17, and 20. 

Washington, DC. 

Potential Changes in Refining Technology Due to the Final Rule. Regulations requiring

much lower levels of sulfur for both gasoline and highway diesel fuel will come into effect over

the next few years. To meet these challenges, refineries are planning to add hydrotreater units to

their facilities, route more intermediate product fractions through existing hydrotreaters, and

operate these units under more severe conditions to reduce levels of chemically bound sulfur in

finished products. As has been documented in economic impact analyses for the gasoline and

highway diesel rules, these changes will require capital investments for equipment, new piping,

and in-process storage; increased use of catalyst and hydrogen; and modifications to current

operating strategies.

The addition of lower sulfur limits for nonroad diesel fuel will result in additional refinery

changes similar in nature to those required for highway diesel fuel. Product streams formerly

sent directly to blending tanks will need to be routed through the hydrotreating operation to

reduce their sulfur level. In addition, because an increasing fraction of the total volumetric

output of the facility must meet ultra-low sulfur requirements, flexibility will be somewhat

reduced. For example, it will become more difficult to sell off spec products if errors or

equipment failures occur during operation.

Types of Products. The major products made at petroleum refineries are unbranded

commodities, which must meet established specifications for fuel value, density, vapor pressure,
Draft Regulatory Support Document

1-16

sulfur content, and several other important characteristics. As Section 1.3.2 describes, they are

transported through a distribution network to wholesalers and retailers, who may attempt to

differentiate their fuel from competitors based on the inclusion of special additives or purely

through adroit marketing. Gasoline and highway diesel are taxed before final sale, whereas

nonroad fuel is not. To prevent accidental or deliberate misuse, nonroad diesel fuel must be

dyed before final sale.

A total of $158 billion of petroleum products were sold in the 1997 census year, accounting

for a nontrivial 0.4 percent of GDP. Table 1.3-2 lists the primary finished products produced; as

one might expect, the percentages are quite close to the generic refinery output shown in Table

1.3-1. Motor gasoline is the dominant product, both in terms of volume and value, with almost

three billion barrels produced in 1997. Distillate fuels accounted for less than half as much as

gasoline, with 1.3 billion barrels produced in the United States in the same year. Data from the

Energy Information Administration (EIA) suggest that 60 percent of that total is low-sulfur

highway diesel, with the remainder split between nonroad diesel and heating oil. Jet fuel, a

fraction slightly heavier than gasoline, is the third most important product, with a production

volume of almost 600 million barrels.

Table 1.3-2

Types of Petroleum Products Produced by U.S. Refineries

Products

Total Produced 

(thousand barrels) Percentage of Total

Liquified Refinery Gases 243,322 3.9%

Finished Motor Gasoline 2,928,050 46.4%

Finished Aviation 6,522 0.1%

Jet Fuel 558,319 8.8%

Kerosene 26,679 0.4%

Distillate Fuel Oil 1,348,525 21.4%

Residual Fuel Oil 263,017 4.2%

Naphtha for Feedstock 60,729 1.0%

Other Oils for Feedstock 61,677 1.0%

Special Naphthas 18,334 0.3%

Lubricants 63,961 1.0%

Waxes 6,523 0.1%

Petroleum Coke 280,077 4.4%

Asphalt and Road Oil 177,189 2.8%

Still Gas 244,432 3.9%

Miscellaneous 21,644 0.3%

Total 6,309,000 100.0%
 Industry Characterization

1-17

Primary Inputs. Crude oil is the dominant input in the manufacture of refined petroleum

products, accounting for 74 percent of material cost, or about $95 billion in 1997, according to

the latest Economic Census (U.S. Census Bureau, 1999). The census reported almost equal

proportions of imported and domestic crude in that year, with 2.5 billion barrels imported and

2.8 billion barrels originating from within the United States. More recent data published by the

EIA show a higher import dependence in the most recent year, with 3.4 billion barrels, or 61.7

percent, imported out of a total of 5.5 billion barrels used by refineries during 2001 (EIA,

2002a). 

Crude oil extracted in different regions of the world have quite different characteristics,

including the mixture of chemical species present, density and vapor pressure, and sulfur

content. The cost of production and the refined product output mix vary considerably depending

on the type of crude processed. A light, sweet crude oil, such as that found in Nigeria, will

process very differently from a heavy, sulfur-laden Alaska or Arabian crude. The ease of

processing any particular material is reflected in its purchase price, with sweet crudes selling at a

premium. The result of these variations is that refineries are frequently optimized to run only

certain types of crude; they may be unable or unwilling to switch to significantly different feed

materials.

In addition to crude oil, refineries may also feed to their refineries hydrocarbon by-products

purchased from chemical companies and other refineries and/or semiprocessed fuel oils imported

from overseas. In 1997, the Census reported that these facilities purchased $11 billion of

hydrocarbons and imported $2.4 billion of unfinished oils. Other significant raw materials

purchased include $600 million for precious metal catalysts and more than $800 million in

additives. 

Costs of Production. According to the latest Economic Census, there were 244 petroleum

refining establishments in the United States in 1997, owned by 123 companies and employing

64,789 workers. Data from EIA using a more stringent definition show 164 operable refineries

in 1997, a number that fell to 153 by January 1, 2002. As seen in Table 1.3-3, value of

shipments in 2000 was $216 billion, up from $158 billion in the 1997 census year. The costs of

refining are divided into the main input categories of labor, materials, and capital expenditures. 

Of these categories, the cost of materials represents about 80 percent of the total value of

shipments, as defined by the Census, varying from year to year as crude petroleum prices change

(see Table 1.3-4). Labor and capital expenditures tend to be more stable, each accounting for 2

to 4 percent of the value of shipments.

Table 1.3-3
Draft Regulatory Support Document

1-18

 Description of Petroleum Refineries—Census Bureau Data 

NAICS 324110—

Petroleum Refineries

Establishments Companies Employment Value of Shipments

($106

)

2000 (NA) (NA) 62229 $215,592

1999 (NA) (NA) 63619 $144,292

1998 (NA) (NA) 64920 $118,156

1997 244 123 64789 $157,935

1992 (reported as SIC 2911) 232 132 74800 $136,239

Sources: 

1992 data from U.S. Census Bureau. 1992 Census of Manufactures, Industry Series MC920I-29A. Table 1A. 

1997 data from U.S. Census Bureau, 1997 Economic Census - Manufacturing, Industry Series EC97M-3241A, Table 1. 

1998-2000 data from U.S. Census Bureau, Annual Survey of Manufactures-2000, 2000, Statistics for Industry Groups

and Industries M00(AS)-1, Table 2. 

Table 1.3-4

 Petroleum Refinery Costs of Production, 1997–2000

Petroleum Refinery 

Costs of Production 1997 1998 1999 2000

Cost of Materials (106

) $127,555 $92,212 $114,131 $178,631

 as percent of shipment

value

80.4% 78.0% 79.1% 82.9%

Cost of Labor (106) $3,885 $3,965 $3,983 $3,995

 as % of shipment value 2.4% 3.4% 2.8% 1.9%

Capital Expenditures (106) $4,244 $4,169 $3,943 $4,453

 as % of shipment value 2.7% 3.5% 2.7% 2.1%

Source: U.S. Census Bureau, Annual Survey of Manufactures. 2000. 2000 Statistics for Industry Groups

and Industries M00(AS)-1, Tables 2 and 5. 

Refinery Production Practices. Refining, like most continuous chemical processes, has

high fixed costs from the complex and expensive capital equipment installed. In addition,

shutdowns are very expensive, because they create large amounts of off-specification product

that must be recycled and reprocessed before sale. As a result, refineries attempt to operate 24

hours per day, 7 days per week, with only 2 to 3 weeks of downtime per year. Intense focus on

cost-cutting has led to large increases in capacity utilization over the past several years. A

Federal Trade Commission (FTC) investigation into the gasoline price spikes in the Midwest

during the summer of 2000 disclosed an average utilization rate of 94 percent during that year,

and EIA data from 2001 show that a 92.6 percent utilization rate was maintained in 2001 (FTC,

2001; EIA, 2002a).
 Industry Characterization

1-19

Because of long lead times in procuring and transporting crude petroleum and the need to

schedule pipeline shipments and downstream storage, refinery operating strategies are normally

set several weeks or months in advance. Once a strategy is established for the next continuous

run, it is difficult or impossible to change it. Exact proportions of final products can be altered

slightly, but at a cost of moving away from the optimal cost profile established initially. The

economic and logistical drivers combine to generate an extremely low supply elasticity. One

recent study estimated the supply elasticity for refinery products at 0.24 (Considine, 2002). The

FTC study discussed above concluded that refiners had little or no ability to respond to the

shortage of oxygenated gasoline in the Midwest in the summer of 2000, even with some advance

warning that this would occur.

1.3.2 The Demand Side

This section describes the demand side of the market for refined petroleum products, with a

focus on the distillate fuel oil industry. It discusses the primary consumer markets identified and

their distribution by end use and PADD. This section also considers substitution possibilities

available in each of these markets and the feasibility and costs of these substitutions. Figure

1.3-2 is a map of the five PADD regions.

Uses and Consumers. Gasoline, jet fuel, and distillate fuel oils account for almost 80

percent of the value of refinery product shipments, with gasoline making up about 51 percent

(U.S. Census Bureau, 1999). Actual and relative net production volumes of these three major

products, along with residual fuel oils, are shown in Table 1.3-5, broken out by PADD and for

the country as a whole. PADD III, comprising the states of Texas, Louisiana, Arkansas,

Alabama, Mississippi, and New Mexico, is a net exporter of refined products, shipping them

through pipelines to consumers on the East Coast and also to the Midwest. Compared with

gasoline production patterns, distillate production is slightly lower in PADD V (the West Coast)

and higher in PADD II (the Midwest). 

The primary end-use markets for distillate and residual fuel oils are divided by EIA as

follows:

C residential—primarily fuel oil for home (space) heating;

C commercial—high-sulfur diesel fuel, low-sulfur diesel fuel, and fuel oil for space

heating;

C industrial—low-sulfur diesel fuel for highway use, high-sulfur diesel fuel for nonroad

use, and residual fuel oil for operating steam boilers and turbines (power generation);

C oil companies—mostly fuel oil and some residual fuel for internal use;

C farm—almost exclusively high-sulfur diesel fuel;

C electric utility—residual fuel and distillate fuel oil for power generation;

C railroad—high-sulfur diesel fuel and low-sulfur diesel fuel used for locomotives;

C vessel bunking—combination of fuel oil and residual fuel for marine engines;

C on-highway diesel—low-sulfur diesel fuel for highway trucks and automobiles;

military—high-sulfur diesel fuel sales to the Armed Forces; and 

C off-highway diesel—high-sulfur diesel fuel and low-sulfur diesel fuel used in

construction and other industries.
Draft Regulatory Support Document

1-20

As Table 1.3-6 indicates, the highway diesel fuel usage of 33.1 billion gallons represents the

bulk of distillate fuel usage (58 percent) in 2000. Residential distillate fuel usage, which in the

majority is fuel oil, accounts for 11 percent of total usage in 2000. Nonroad diesel fuel is

primarily centered on industrial, farm, and off-highway diesel (construction) usage. In 2000,

these markets consumed about 13 percent of total U.S. distillate fuels.

To determine the regional consumption of distillate fuel usage, 2000 sales are categorized by

PADDs. As shown in Table 1.3-7, PADD I (the East Coast) consumes the greatest amount of

distillate fuel at 20.9 billion gallons. However, residential, locomotive, and vessel bunking

consumers account for 6.4 billion gallons of the distillate fuel consumed, which means that at

least one-third of the total consumed in PADD I is due to fuel oil and not to diesel fuel

consumption.
 Industry Characterization

1-21

Table 1.3-5

 Refinery Net Production of Gasoline and Fuel Oil Products by PADD

PADD

Motor Gasoline Distillate Fuel Oil Jet Fuel Residual Fuel Oil

Quantity

(1,000 bbl)

Percent

(%)

Quantity

(1,000 bbl)

Percent

(%)

Quantity

(1,000 bbl)

Percent

(%)

Quantity

(1,000 bbl)

Percent

(%)

I 369,750 12.6% 170,109 12.6% 30,831 5.5% 38,473 14.6%

II 641,720 21.9% 316,023 23.4% 80,182 14.4% 24,242 9.2%

III 1,306,448 44.6% 629,328 46.7% 288,749 51.7% 132,028 50.2%

IV 97,869 3.3% 54,698 4.1% 9,787 1.8% 4,151 1.6%

V 512,263 17.5% 178,367 13.2% 148,770 26.6% 64,123 24.4%

Total 2,928,050 100.0% 1,348,525 100.0% 558,319 100.0% 263,017 100.0%

Source: U.S. Department of Energy, Energy Information Administration (EIA). 2002a. Petroleum Supply Annual 2001,

Tables 16, 17, and 20. Washington, DC. Table 17.

Table 1.3-6

 Distillate Fuel Oil by End Use (2000)

End Use 2000 Usage (thousand gallons) Percentage Share (%)

Residential 6,204,449 10.8%

Commercial 3,372,596 5.9%

Industrial 2,149,386 3.8%

Oil Company 684,620 1.2%

Farm 3,168,409 5.5%

Electric Utility 793,162 1.4%

Railroad 3,070,766 5.4%

Vessel Bunking 2,080,599 3.6%

Highway Diesel 33,129,664 57.9%

Military 233,210 0.4%

Off-Highway Diesel 2,330,370 4.1%

Total 57,217,231 100.0%

Source: U.S. Department of Energy, Energy Information Administration (EIA). 2001b. Fuel Oil and Kerosene

Sales, 2000, Tables 7-12. Washington, DC. 
Draft Regulatory Support Document

1-22

Table 1.3-7

Distillate Fuel Oil by End Use and PADD

End Use

PADD (Thousand Gallons)

I II III IV V

Residential 5,399,194 628,414 1,117 38,761 136,962

Commercial 2,141,784 568,089 346,578 102,905 213,240

Industrial 649,726 600,800 420,400 241,146 237,313

Oil Company 19,101 41,727 560,905 29,245 33,643

Farm 432,535 1,611,956 552,104 220,437 351,377

Electric Utility 304,717 133,971 194,786 8,492 151,196

Railroad 499,787 1,232,993 686,342 344,586 307,059

Vessel Bunking 490,150 301,356 1,033,333 173 255,586

Highway Diesel 10,228,244 11,140,616 5,643,703 1,474,611 4,642,490

Military 70,801 36,100 9,250 4,163 112,895

Off-highway Diesel 669,923 608,307 516,989 180,094 355,056

Total 20,905,962 16,904,329 9,965,507 2,644,613 6,796,817

Table 1.3-8 presents a closer look at on-highway consumption of distillate fuel, which is

entirely low-sulfur diesel fuel. PADD I (the East Coast) and PADD II (the Midwest) consume

almost 65 percent of all U.S. distillate fuel sold for on-highway use.

Table 1.3-9 shows that residential consumption of distillate fuel (primarily fuel oil) is

centered in PADD I (the East Coast). Fuel-oil-fired furnaces and water heaters in New York and

New England consume most of this heating oil; in most of the rest of the country, residential

central heating is almost universally provided by natural gas furnaces or electric heat pumps. A

comparison of Tables 1.3-5 and 1.3-9 reveals that PADD I produces far less distillate fuel oil

than it consumes. The balance is made up by shipments from PADD III and imports from

abroad. 

Tables 1.3-10, 1.3-11, and 1.3-12 focus on diesel sales for industrial, agricultural, and

construction use. Industrial use of diesel fuel is fairly evenly spread across PADDs. PADD II

(the Midwest) has the highest percentage of diesel usage at 28 percent, while PADD V (the West

Coast) has the lowest percentage at 11 percent. In contrast, agricultural purchases of diesel are

in the great majority (51 percent) centered in PADD II (the Midwest). For construction only,

distillate fuel sales are available, but these sales are assumed to be principally diesel fuel. 

Construction usage of diesel fuel, as with industrial usage, is fairly evenly spread across PADDs,

with the exception of PADD IV. PADD IV represents only 8 percent of total construction usage.
 Industry Characterization

1-23

Table 1.3-8

Sales for Highway Use of Distillate Fuel by PADD (2000)

PADD

Distillate Usage

(Thousand Gallons)

Share of 

Distillate Fuel Used

I 10,228,244 30.9%

II 11,140,616 33.6%

III 5,643,703 17.0%

IV 1,474,611 4.5%

V 4,642,490 14.0%

Total 33,129,664 100.0%

Table 1.3-9

 Sales for Residential Use of Distillate Fuel by PADD (2000)

PADD

Distillate Usage

(Thousand Gallons)

Share of 

Distillate Fuel Used

I 5,399,194 87.0%

II 628,414 10.1%

III 1,117 0.0%

IV 38,761 0.6%

V 136,962 2.2%

Total 6,204,448 100.0%

Table 1.3-10

Industrial Use of Distillate Fuel by PADD (2000)

PADD

Distillate Usage

(Thousand Gallons)

Share of 

Distillate Fuel Used

I 649,726 30.2%

II 600,800 28.0%

III 420,400 19.6%

IV 241,146 11.2%

V 237,313 11.0%

Total 2,149,385 100.0%
Draft Regulatory Support Document

1-24

Table 1.3-11

Adjusted Sales for Farm Use of Distillate Fuel by PADD (2000)

PADD

Distillate Usage

(Thousand Gallons)

Share of 

Distillate Fuel Used

I 432,535 13.6%

II 1,611,956 50.9%

III 552,104 17.4%

IV 220,437 7.0%

V 351,377 11.1%

Total 3,168,409 100.0%

Table 1.3-12

Sales for Construction Use of Off-Highway Distillate Fuel by PADD (2000)

PADD

Distillate Usage

(Thousand Gallons)

Share of 

Distillate Fuel Used

I 510,876 26.9%

II 549,299 28.9%

III 394,367 20.8%

IV 150,060 7.9%

V 295,235 15.5%

Total 1,899,837 100.0%

Substitution Possibilities in Consumption. For engines and other combustion devices

designed to operate on gasoline, there are no practical substitutes, except among different grades

of the same fuel. Because EPA regulations apply equally to all gasoline octane grades, price

increases will not lead to substitution or misfueling. In the case of distillate fuels, it is currently

possible to substitute between low-sulfur diesel fuel, high-sulfur diesel fuel, and distillate fuel

oil, although higher sulfur levels are associated with increased maintenance and poorer

performance.

With the consideration of more stringent nonroad fuel and emission regulations, substitution

will become less likely. Switching from nonroad ultralow-sulfur diesel to highway ultralowsulfur diesel is not financially attractive, because of the taxes levied on the highway product. 

Misfueling with high-sulfur fuel oil will rapidly degrade the performance of the exhaust system

of the affected engine, with negative consequences for maintenance and repair costs.

1.3.3 Industry Organization

To determine the ultimate effects of the rule, it is important to have a good understanding of

the overall refinery industry structure. The degree of industry concentration, regional patterns of
 Industry Characterization

1-25

production and shipment, and the nature of the corporations involved are all important aspects of

this discussion. In this section, we look at market measures for the United States as a whole and

by PADD region.

Market Structure—Concentration. There is a great deal of concern among the public

about the nature and effectiveness of competition in the refining industry. Large price spikes

following supply disruptions and the tendency for prices to slowly fall back to more reasonable

levels have created suspicion of coordinated action or other market imperfections in certain

regions. The importance of distance in total delivered cost to various end-use markets also

means that refiners incur a wide range of costs in serving some markets; because the price is set

by the highest cost producer serving the market as long as supply and demand are in balance,

profits are made by the low-cost producers in those markets. 

Market concentration is measured in a variety of ways by antitrust regulators in the

Department of Justice (DOJ) and Federal Trade Commission (FTC), including four-firm

concentration ratios (CR4) and the Herfindahl-Hirschman Index (HHI). The CR4 is simply the

combined market share of the four largest sellers in a given market, a very intuitive

concentration measure. The HHI, which is currently used by the DOJ’s Antitrust Division and

the FTC, is constructed by summing up the squared market shares, in percentage terms, of all

competitors in the market. According to these agencies’ 1997 Horizontal Merger Guidelines, a

market with an HHI under 1,000 is considered “unconcentrated,” one with an HHI between

1,000 and 1,800 is “moderately concentrated,” and one with a measure over 1,800 is “highly

concentrated” (DOJ, 1997).

The merger guidelines assume that high concentration offers the potential for firms to

influence prices through coordinated action on prices. Still it is possible for highly concentrated

markets to behave competitively if firms are unwilling or unable to coordinate their actions or if

potential entry can serve to limit price increases. The RTI report presents the calculated HHI

values for diesel engine markets.

There is, however, no convincing evidence in the literature that markets should be modeled

as imperfectly competitive. The FTC study cited earlier concluded that the extremely low

supply and demand elasticities made large price movements likely and inevitable given

inadequate supply or unexpected increases in demand. Nevertheless, their economic analysis

found no evidence of collusion or other anticompetitive behavior in the summer of 2000. 

Furthermore, the industry is not highly concentrated on a nationwide level or within regions. 

The 1997 Economic Census presented the following national concentration information: 

four-firm concentration ratio (CR) of 28.5 percent, eight-firm concentration ratio of 48.6 percent,

and an HHI of 422. Merger guidelines followed by the FTC and Department of Justice consider

little potential for pricing power in an industry with an HHI below 1,000. 

Two additional considerations were important in making a determination as to whether we

can safely assume that refineries act as price-takers in their markets. First, with greater

concentration in regional or local markets than at the national level, as well as with significant
Draft Regulatory Support Document

1-26

transport costs, competition from across the country will not be effective in restraining prices. 

Secondly, several large mergers have occurred since the 1997 Economic Census was conducted,

all of which have prompted action by the FTC to ensure that effective competition was retained.

To investigate these issues, RTI estimated concentration measures that are not based on

refinery-specific production figures (which are not available), but rather on crude distillation

capacity, which is the industry’s standard measure of refinery size. We aggregated the total

capacity controlled by each corporate parent, both at the PADD level and nationwide, and then

calculated CR-4, CR-8, and HHI figures. The results are presented in Table 1.3-13. 

Table 1.3-13

2001 Concentration Measures for Refineries Based on Crude Capacity

PADD Quantity CR-4 CR-8 HHI

I 1,879,400 71.6% 91.3% 1,715

II 3,767,449 54.6% 78.2% 1,003

III 8,238,044 48.8% 68.0% 822

IV (current) 606,650 59.6% 90.1% 1,310

IV (future) 606,650 45.4% 80.5% 918

V 3,323,853 61.3% 90.9% 1,199

National 17,815,396 41.89% 65.50% 644

Note: Quantity is crude distillation capacity in thousands of barrels per stream day. 

Source:U.S. Department of Energy, Energy Information Administration (EIA). 2002b. Refinery Capacity Data

Annual. As accessed on September 23, 2002. http://www.eia.doe.gov/

oil_gas/petroleum/data_publications/ refinery_capacity_data/refcap02.dbf. Washington, DC. See text

discussion.

The data in this table provide several interesting conclusions: 

C The current and future state of PADD IV shows the impact of FTC oversight to

maintain competition. As part of approving the Phillips-Conoco merger, the FTC

ordered the merged company to divest two refineries in PADD IV—Commerce City,

Colorado, and Woods Cross, Utah. Once those divestitures take place, the

concentration levels will drop below 1,000, a level that is not generally of concern.

C The only region that is highly concentrated is PADD I, which is generally dominated

by two large refineries. In this case, however, imports of finished petroleum

products, along with shipments from PADD III, should prevent price-setting behavior

from emerging in this market. Table 1.3-14 shows imports of refined products for

PADD I and the entire country. About 90 percent of total U.S. imports of gasoline

and distillate fuels come into PADD I, aided by inexpensive ocean transport. It is

reasonable to assume that any attempts to set prices by the dominant refineries would

be defeated with increased imports.
 Industry Characterization

1-27

Table 1.3-14

PADD I and Total U.S. Imports of 

Gasoline and Fuel Oil Products by Top Five Countries of Origin

Top Five Countries of

Origin

Finished Motor Gasoline Distillate Fuel Oil Residual Fuel

PADD I

Import

Total U.S.

Import

PADD I

Import

Total U.S.

Import

PADD I

Import

Total U.S.

Import

Venezuela 21,017 21,257 16,530 16,530 17,667 18,341

Brazil 8,286 8,286 1,472 1,832 8,361 9,105

Canada 41,711 43,778 30,350 35,165 9,483 11,723

Russia 869 968 10,345 10,345 174 1,051

Virgin Islands (U.S.) 38,135 38,882 30,810 31,540 13,412 13,502

Sum of Top Five 110,018 113,171 89,507 95,412 49,097 53,722

Total 153,633 165,878 112,318 125,586 91,520 107,688

Percentage of Total

U.S. Imports

92.6% 89.4% 85.0%

Source: U.S. Department of Energy, Energy Information Administration (EIA). 2002a. Petroleum Supply Annual 2001. 

Tables 16, 17, and 20. Washington, DC. Table 20.

C Markets in PADDs II and III, which are not overly concentrated or geographically

isolated, should behave competitively, with little potential for price-setting among its

refineries. 

C The four large mergers (Exxon-Mobil, BP-Amoco, Chevron-Texaco, and

Phillips-Conoco) have not increased nationwide concentration to a level of concern

for competitive reasons.

Market Structure—Firms and Facilities. PADD III has the greatest number of refineries

affected by the final rule and will account for the largest volume of low-sulfur nonroad diesel

fuel. Tables 1.3-15 and 1.3-16 present the number of operating refineries and the number of

crude distillation units in each PADD; output volumes were presented in Table 1.3-5. PADD III

also accounts for 45 to 50 percent of U.S. refinery net production of finished motor gasoline,

distillate fuel oil, and residual fuel oil. Similarly, PADD IV has the fewest number of affected

facilities and accounts for the smallest share of distillate production. Still, because compliance

costs per unit of output are likely to depend on refinery scale, the small size and geographic

isolation of the PADD IV refineries suggest that the financial impact may be greatest on these

operations. 
Draft Regulatory Support Document

1-28

Table 1.3-15

Number of Petroleum Refineries by PADD

PADD Number of Facilities Percentage of Total

I 16 11.1%

II 28 19.4%

III 54 37.5%

IV 14 9.7%

V 32 22.2%

Total 144 100.0%

Table 1.3-16

Number of Crude Distillation Facilities by PADD

PADD Number of Facilities Percentage of Total

I 12 8.6%

II 26 18.7%

III 50 36.0%

IV 16 11.5%

V 35 25.2%

Total 139 100.0%

According to the EIA Petroleum Supply Annual 2001, the top three owners of crude

distillation facilities are ExxonMobil Corp. (11 percent of U.S. total), Phillips Petroleum Corp.

(10 percent), and BP PLC (9 percent). Table1.3-17 gives an overview of the top refineries in

each PADD, in descending order of total crude distillation capacity. As operating refineries

attempt to run at full utilization rates, this measure should correlate directly to total output. 

Information is not available on actual production of highway diesel, nonroad diesel, and other

distillate fuels for each refinery. Note that PADD III has more than 50 percent of the total crude

distillation capacity, as well as the three largest single facilities.

Firm Characteristics. Many of the large integrated refineries are owned by major

petroleum producers, which are among the largest corporations in the United States. According

to Fortune Magazine’s Fortune 500 list, ExxonMobil is the second largest corporation in the

world, as well as in the United States. Chevron Texaco ranks as the eighth largest U.S.

corporation, placing it fourteenth in the world. The newly merged Phillips and Conoco entity

will rank in the top 20 in the United States, and six more U.S. petroleum firms make the top 500. 

BP Amoco (fourth worldwide) and Royal Dutch Shell (eighth worldwide) are foreign-owned, as

is Citgo (owned by Petroleos de Venezuela).
 Industry Characterization

1-29

Many of the smallest refineries are small businesses. A total of 21 facilities owned by 13

different parent companies qualify or have applied for small business status (EPA, 2002). These

small refineries are concentrated in the Rocky Mountain and Great Plains region of PADD IV,

and their conversion to low-sulfur diesel fuel calls for significant flexibility.

1.3.4 Markets and Trends

There is considerable diversity in how different markets for distillate fuels have been

growing over the past several years. Table 1.3-18 shows that residential and commercial use of

fuel oil has been dropping steadily since 1984, while highway diesel use has nearly doubled over

the same period. Farm use of distillate has been flat over the 15-year period, while off-highway

use, mainly for construction, has increased by 40 percent.
Table 1.3-17

Top Refineries in Each PADD by Total Crude Distillation Capacity

Name 

of Company 

Location 

of Facilities

Crude Distillation

Capacity (barrels/day)

Percentage of Total

PADD Crude

Distillate Capacity

C

PADD I

Sunoco Inc. (R&M) Philadelphia PA 330,000 20.9% Phillips 66 Co. Linden NJ 250,000 15.9% Phillips 66 Co. Trainer PA 180,000 11.4% Motiva Enterprises LLC Delaware City DE 175,000 11.1% Sunoco Inc. Marcus Hook PA 175,000 11.1% TOTAL 1,576,600 100.0% 

PADD II

BP Products North America, Inc. Whiting IN 410,000 12.0% Phillips 66 Co. Wood River IL 288,300 8.4% Flint Hills Resources LP Saint Paul MN 265,000 7.7% ExxonMobil Refg & Supply Co. Joliet IL 235,500 6.9% Marathon Ashland Petro LLC Catlettsburg KY 222,000 6.5% Conoco Inc. Ponca City OK 194,000 5.7% Marathon Ashland Petro LLC Robinson IL 192,000 5.6% Williams Refining LLC Memphis TN 180,000 5.3% TOTAL 3,428,053 100.0% 
Table 1.3-17 (continued)

Top Refineries in Each PADD by Total Crude Distillation Capacity

Name 

of Company 

Location 

of Facilities

Crude Distillation

Capacity (barrels/day)

Percentage of Total

PADD Crude

Distillate Capacity

C

PADD III

ExxonMobil Refg & Supply Co. Baytown TX 516,500 6.8% ExxonMobil Refg & Supply Co. Baton Rouge LA 488,500 6.4% BP Products North America, Inc. Texas City TX 437,000 5.8% ExxonMobil Refg & Supply Co. Beaumont TX 348,500 4.6% Deer Park Refg Ltd Ptnrshp Deer Park TX 333,700 4.4% Citgo Petroleum Corp. Lake Charles LA 326,000 4.3% Chevron U.S.A. Inc. Pascagoula MS 295,000 3.9% Flint Hills Resources LP Corpus Christi TX 279,300 3.7% Lyondell Citgo Refining Co. Ltd. Houston TX 274,500 3.6% Premcor Refg Group Inc Port Arthur TX 255,000 3.4% Conoco Inc. Westlake LA 252,000 3.3% Phillips 66 Co. Belle Chasse LA 250,000 3.3% Motiva Enterprises LLC Port Arthur TX 245,000 3.2% Marathon Ashland Petro LLC Garyville LA 232,000 3.1% Motiva Enterprises LLC Norco LA 228,000 3.0% Motiva Enterprises LLC Convent LA 225,000 3.0% Phillips 66 Co. Sweeny TX 213,000 2.8% Valero Refining Co. Texas Texas City TX 204,000 2.7% Chalmette Refining LLC Chalmette LA 182,500 2.4% Atofina Petrochemicals Inc. Port Arthur TX 178,500 2.4% Total 7583080 100.0% 
Table 1.3-17 (continued)

Top Refineries in Each PADD by Total Crude Distillation Capacity

Name 

of Company 

Location 

of Facilities

Crude Distillation

Capacity (barrels/day)

Percentage of Total

PADD Crude

Distillate Capacity

PADD IV

Conoco Inc. Commerce City CO 62,000 2.0% Sinclair Oil Corp. Sinclair WY 62,000 2.0% Conoco Inc. Billings MO 60,000 1.9% TOTAL 567,370 18.4% 

PADD V

BP West Coast Products LLC Los Angeles CA 260,000 8.4% Chevron U.S.A. Inc. El Segundo CA 260,000 8.4% BP West Coast Products LLC Cherry Point WA 225,000 7.3% Chevron U.S.A. Inc. Richmond CA 225,000 7.3% Williams Alaska Petro Inc. North Pole AK 197,928 6.4% TOTAL 3,091,198 100.0% 

Total U.S. (excluding Virgin Islands) 16,246,301 

Source:U.S. Department of Energy, Energy Information Administration (EIA). 2002b. Refinery Capacity Data Annual. As accessed on Sep

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/refinery_capacity_data/refcap02.dbf. Washington, DC. 
Table 1.3-18

Sales of Distillate Fuel Oils to End Users 1984-1999 (thousands of barrels per day)

Year

Residential Com- mercial Indust- rial Oil Co. Farm Electric Utility Rail- road Vessel Bunkering Highway Diesel Military

Of

High

Die

1984 450 319 153 59 193 45 225 110 1,093 45 101985 471 294 169 57 216 34 209 124 1,127 50 101986 476 280 175 49 220 40 202 133 1,169 50 111987 484 279 190 58 211 42 205 145 1,185 58 111988 498 269 170 57 223 52 212 150 1,304 64 111989 489 252 167 55 209 70 213 154 1,378 61 101990 393 228 160 63 215 48 209 143 1,393 51 111991 391 226 152 59 214 39 197 141 1,336 54 111992 406 218 144 51 228 30 209 146 1,391 42 111993 429 218 128 50 211 38 190 133 1,485 31 121994 413 218 136 46 209 49 200 132 1,594 34 131995 416 216 132 36 211 39 208 129 1,668 24 121996 436 223 137 41 217 45 213 142 1,754 24 131997 423 210 141 41 216 42 200 137 1,867 22 131998 367 199 147 37 198 63 185 139 1,967 18 141999 381 196 142 38 189 60 182 135 2,091 19 14

Source: U.S. Department of Energy, Energy Information Administration (EIA). 2001a. Annual Energy Review, 2000, Table 5-13. Washing
Draft Regulatory Support Document

1-34

1.4 Distribution and Storage Operations

 Refined petroleum products, including gasoline, distillates, and jet fuel, are transported by

barge and truck and through pipelines from refineries to the wholesale and retail networks in the

major markets of the United States. The most important of these routes is the 86,500-mile

pipeline network, operated by nearly 200 separate companies (AOPL, 2000; FERC, 2002). 

Terminals and other storage facilities are located near refineries, along pipelines at breakout

stations, and at bulk plants near major consumer markets. There are currently more than 1,300

terminals for refined products in the United States (API, 2002).

1.4.1 The Supply-Side

Pipelines are constructed of large-diameter welded steel pipe and typically buried

underground. Pumps at the source provide motive force for the 3 to 8 miles per hour flow in the

piping network (API, 1998; AOPL, 2000). Periodically, the line pressure is boosted at

strategically placed pumping stations, which are often located at breakout points for intermediate

distribution of various components. The product is moved rapidly enough to ensure turbulent

flow, which prevents back-mixing of components. Figure 1.4-1 shows a typical configuration of

several refined components on the Colonial Pipeline, a major artery connecting East Texas

producing sites to Atlanta, Charlotte, Richmond, and New Jersey. 

The pipelines do not change the physical form of the petroleum products that they carry and

add value only by moving the products closer to markets. Operating costs of transporting

products in a pipeline are quite small, so most of the cost charged to customers represents

amortization of capital costs for construction. According to the 1997 Economic Census,

revenues for pipeline transportation, NIACS code 48691, were $2.5 billion, of which only $288

million represented wags and salaries (U.S. Census Bureau, 2000). Almost all pipeline

companies act as a common carrier (they do not take ownership of the products they transport),

so their revenues and economic value added are equivalent. Census data for storage operations

are not broken down in enough detail to permit estimation of revenues or value added. 
 Industry Characterization

1-35

Figure1.4-1

 Typical Sequence in which Products are Batched While in Transit on Colonial System

The most important impact of additional EPA regulation on the distribution network has been

to increase the number of different products handled by each pipeline. Although some concern

has been expressed by these firms in relation to the gasoline and highway diesel regulations, the

incremental effect of reducing sulfur content for nonroad diesel should be minor. The Colonial

Pipeline mentioned previously currently handles 38 grades of motor gasoline, 16 grades of

distillate products, 7 grades of kerosene-type fuels (including jet fuel), and an intermediate

refinery product, light cycle oil (Colonial, 2002).

As Figure1.4-1 shows, these pipelines are shipping low-sulfur gasoline, low-sulfur diesel

fuel, and high-sulfur nonroad fuel in the same pipeline. In most cases, the interface (mixing

zone) between products is degraded to the poorer quality material. When they begin handling

ultralow-sulfur diesel fuel and gasoline, they may be forced to downgrade more interface

material to nonroad or fuel oil and will need to carefully prevent contamination in storage tanks

and pumping stations. 

Importantly, changeover to ultralow-sulfur diesel fuel for nonroad applications will not add

additional complexity to their operations. We expect there to be no physical difference between

15 ppm diesel fuel destined for the highway market and 15 ppm diesel fuel destined for the offhighway market prior to the terminal level when dye must be added to off-highway diesel fuel to

denote its untaxed status. This will allow pipeline operators to ship such fuels in fungible

batches. Consequently, the introduction of 15 ppm off-highway diesel should not result in

increased difficulty in limiting sulfur contamination during the transportation of ultra-low sulfur

products. Pipeline operators will continue to have a market for the downgraded mixing zone
Draft Regulatory Support Document

1-36

material generated during the shipment of 15 ppm diesel fuel by pipeline. After the 15 ppm

standard for highway diesel fuel and the comparable fuel standards in this final rule take effect,

the pipelines that transport the majority of the nation’s diesel fuel are projected to continue to

carry high-sulfur diesel fuel and/or 500 ppm diesel fuel. These pipelines will blend their

downgraded 15 ppm diesel into the 500 ppm and/or high-sulfur diesel fuel that they ship. A

fraction of the pipelines are projected to carry only a single grade of diesel fuel (15 ppm fuel)

after the HD2007 rule takes effect. These pipelines currently carry only 500 ppm highway diesel

fuel. In the HD2007 rule, we projected that these pipelines will install an additional storage tank

to contain the relatively low volumes of downgraded 15 ppm diesel fuel generated during

pipeline transportation of the product. We projected that this downgraded material will be sold

into the off-highway diesel market. The new regulation of nonroad diesel fuel will not change

this practice. We expect these pipeline operators to continue finding a market for the

downgraded 15 ppm fuel, either as 500 ppm off-highway diesel fuel or for use in stationary

diesel engines.

1.4.2 The Demand-Side

Demand for distribution through pipelines (versus barge or truck movement) is driven by

cost differentials with these alternate means of transportation. The National Petroleum Council

estimated in a comprehensive 1989 report that water transport of a gallon of petroleum products

was about three times as expensive per mile as transport via pipeline, and truck transportation

was up to 25 times as expensive per mile (National Petroleum Council, 1989). A recent pipeline

industry publication shows that pipelines handle around 60 percent of refined petroleum product

movements, with 31 percent transported by water, 5.5 percent by truck, and 3.5 percent by rail

(AOPL, 2001).

Pipeline transport charges make up only a small portion of the delivered cost of fuels. 

Industry publications cite costs of about $1 per barrel, equal to 2.5 cents per gallon, for a 1600

mile transfer from Houston to New Jersey, and about 2 cents per gallon for a shipment of 1100

miles from Houston to Chicago (AOPL, 2002; Allegro, 2001). Although average hauls are

shorter and somewhat more expensive per mile, average transport rates are on the order of 0.06

to 0.18 cents per barrel per mile. 

1.4.3 Industry Organization

Just as it has with other transportation modes defined by site-specific assets and high fixed

costs, the federal government has traditionally regulated pipelines as common carriers. Unlike

railroad and long-haul trucking, however, pipeline transport was not deregulated during the

1980s, and the Federal Energy Regulatory Commission (FERC) still sets allowable tariffs for

pipeline movements. A majority of carriers, therefore, compete as regulated monopolies.

Most pipelines are permitted small annual increases in rates without regulatory approval,

typically limited to 1 percent less than the increase in the producer price index (PPI). If

regulatory changes caused significant cost increases, for instance from the addition of tankage to

handle two grades of nonroad diesel fuel, pipeline operators would have to engage in a rate case
 Industry Characterization

1-37

with FERC to pass their increased costs along to consumers. If they chose not to request rate

relief, the pipelines would absorb any costs above the allowable annual increases.

1.4.4 Markets and Trends

Pipeline firms have seen slowly rising demand for their services over the past several years. 

The latest available data, from the 1996 to 1999 period, are displayed in Table 1.4-1. Pipelines

have not only captured most of the overall increase in total product movements, they have also

taken some share away from water transport during the period. Railroad shipments have grown

as well, but from a very small base. 

Table 1.4-1

Trends in Transportation of Refined Petroleum Products

1996 1997 1998 1999

Percentage Change

1996-1999

Pipelines 280.9 279.1 285.7 296.6 5.6%

Water Carriers 154.1 148.3 147.1 147.5 –4.3%

Motor Carriers 28.0 26.0 26.7 27.6 –1.4%

Railroads 16.0 16.2 16.2 18.2 13.8%

Totals 479.0 469.6 475.7 489.9 2.2%

Note: All figures, except percentages, in billions of ton-miles.

Source: Association of Oil Pipe Lines (AOPL). 2001. Shifts in Petroleum Transportation. As accessed on

November 20, 2002. www.aopl.org/pubs/facts.html.
Draft Regulatory Support Document

1-38

1. RTI. (2003). Industry Profile for Nonroad Diesel Tier 4 Rule - Final Report. Prepared for the

U.S. Environmental Protection Agency. EPA Contract Number 68-D-99-024, April 2003. A

copy can be found in Docket A-2001-28, Document No. II-A-182.

2. Power Systems Research(PSR). 2002. OELink Sales Database.

3. RTI. (2003). Economic Impact Analysis for Nonroad Diesel Tier 4 Rule. Prepared for the

U.S. Environmental Protection Agency. EPA Contract No. 68-D-99-024, April 2003. A copy

can be found in Docket A-2001-28, Document II-A-115.

References to Chapter 1

Allegro Energy Group. 2001. How Pipelines Make the Oil Market Work—Their Networks,

Operations, and Regulations. New York: Allegro. A copy can also be found in Docket A2001-28, Document No. II-A-137.

American Petroleum Institute (API). 1998. “All About Petroleum.” As accessed on November

20, 2002. api-ec.api.org/filelibrary/AllAboutPetroleum.pdf. A copy can also be found in

Docket A-2001-28, Document No. II-A-172.

American Petroleum Institute (API). 2001. “Pipelines Need Operational Flexibility to Meet

America’s Energy Needs.” As accessed on November 20, 2002. apiep.api.org/industry/index.cfm. A copy can also be found in Docket A-2001-28, Document

No. II-A-173.

American Petroleum Institute (API). 2002. “Marketing Basic Facts.” As accessed on

September 25, 2002. www.api.org/industry/marketing/markbasic.htm.

Association of Oil Pipe Lines (AOPL). 2000. “Fact Sheet: U.S. Oil Pipe Line Industry.” As

accessed on November 20, 2002. www.aopl.org/pubs/pdf/fs2000.pdf.

Association of Oil Pipe Lines (AOPL). 2001. “Shifts in Petroleum Transportation.” As

accessed on November 20, 2002. www.aopl.org/pubs/facts.html.

Association of Oil Pipe Lines (AOPL). 2002. “Why Pipelines?” As accessed on November 20,

2002. www.aopl.org/about/pipelines.html.

Business & Company Resource Center. http://www.gale.com/servlet/Item

DetailServlet?region=9&imprint=000&titleCode=GAL49&type=1&id=115085. A copy of

information describing this database can be found in Docket A-2001-28, Document No.I IB-42. 
 Industry Characterization

1-39

Chevron. 2002. “Diesel Fuel Refining and Chemistry.” As accessed on August 19, 2002. 

www.chevron.com/prodserv/fuels/bulletin/diesel/L2_4_2rf.htm.

Colonial. 2002. “Frequently Asked Questions.” As accessed on September 24, 2002. 

www.colpipe.com/ab_faq.asp.

Considine, Timothy J. 2002. “Inventories and Market Power in the World Crude Oil Market.” 

As accessed on November 1, 2002. http://www.personal.psu.edu/faculty/ c/p/

cpw/resume/finvmarketpower.html.

Dun & Bradstreet. Million Dollar Directory. http://www.dnb.com/dbproducts/description/

0,2867,2-223-1012-0-223-142-177-1,00.html. 

Federal Energy Regulatory Commission (FERC). 2002. FERC Form No. 6, Annual Report of

Oil Pipelines. www.ferc.fed.us/oil/oil_list.htm. A copy of this webpage can be found in

Docket A-2001-28, Document No. II-B-43.

Flint Hills Resources. 2002. “Refining Overview.” As accessed on September 10, 2002. 

www.fhr.com/Refining101/default.asp.

Federal Trade Commission (FTC). Midwest Gasoline Price Investigation, March 29, 2001, p.7. 

As accessed September 25, 2002. www.ftc.gov/os/2001/03/mwgasrpt.htm. A copy can also

be found in Docket A-2001-28, Document No. II-A-23.

Freedonia Group. 2001. “Diesel Engines and Parts in the United States to 2005—Industry

Structure.” http://www.freedoniagroup.com/scripts/cgiip.exe/WService=freedonia

/abstract.html?ARTNUM=1153.

Hoover’s Online. http://www.hoovers.com/. 

National Petroleum Council. 1989. “Petroleum Storage and Transportation.” System

Dynamics. Volume II. Washington, DC: National Petroleum Council.

U.S. Department of Agriculture, National Agricultural Statistics Service (USDA-NASS). 2002. 

Agricultural Statistics 2002. See especially Tables 15-1, 15-2, 9-39, 9-40. Washington, DC: 

U.S. Department of Agriculture. This document can be accessed at

http://www.usda.gov/nass/pubs/agr02/acr02.htm. A copy of selected tables can be found in

Docket A-2001-28, Document No. II-A- 174.

U.S. Department of Energy, Energy Information Administration (EIA). 2001a. Annual Energy

Review, 2000. See especially Table 5.13. Washington, DC: Department of Energy. 

DOE/EIA-0384(2000), August 2001. This document can be found at

http://tonto.eia.doe.gov/FTPROOT/multifuel/038400.pdf. A copy of this document can also

be found in Docket A-2001-28, Document No. II-A-175.
Draft Regulatory Support Document

1-40

U.S. Department of Energy, Energy Information Administration (EIA). 2001b. Fuel Oil and

Kerosene Sales, 2000, Tables 7-12. Washington, DC: Department of Energy. DOE-EIA0535(00), Distribution Category UC-950, September 2001. A copy of this document can

also be found at

http://www.eia.doe.gov/pub/oil_gas/petroleum/data_publications/fuel_oil_and_kerosene

_sales/historical/2000/foks_2000.html. A copy can also be found in Docket A-2001-28,

Document No. II-A-176.

U.S. Department of Energy, Energy Information Administration (EIA). 2002a. Petroleum

Supply Annual 2001. Volumes 1 and 2. See especially Volume I, Table 16(page 48).

Washington, DC: Department of Energy. DOE/EIA-0340(01)/1 and DOE/EIA-0340(01)/2.

June 2002. A copy of these documents can also be found at

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/petroleum_supply_annual/psa_

volume1/psa_volume1.html and

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/petroleum_supply_annual/psa_

volume1/psa_volume2.html. A copy of these documents can also be found in Docket A2001-28, Documents No. II-A-165 and II-A-177. 

U.S. Department of Energy, Energy Information Administration (EIA). 2002b. Refinery

Capacity Data Annual. As accessed on September 23, 2002.

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/refinery_capacity_data/refcapa

city.html. Washington, DC: Department of Energy. A copy of this document is also

available in Docket A-2001-28, Document No. II-A-178.

U.S. Environmental Protection Agency. 1995a. EPA Office of Compliance Sector Notebook

Project: Profile of the Motor Vehicle Assembly Industry. EPA310-R-95-009. Washington,

DC: U.S. Environmental Protection Agency.

U.S. Environmental Protection Agency (EPA). 1995b. Profile of the Petroleum Refining

Industry. EPA Industry Sector Notebook Series. U.S. Environmental Protection Agency.

U.S. Environmental Protection Agency (EPA). 2000. Heavy-Duty Standards/Diesel Fuel RIA. 

EPA420-R-00-026. Washington, DC: U.S. Environmental Protection Agency.

U.S. Environmental Protection Agency (EPA). 2002. Highway Diesel Progress Review. 

EPA420-R-02-016. Washington, DC: EPA Office of Air and Radiation.

U.S. Census Bureau. 1992 Census of Manufactures, Industry Series, Petroleum and Coal

Products. MC92-I-29A. Table 1A. A copy of this document is available at

http://www.census.gov/prod/1/manmin/92mmi/mci29af.pdf. A copy can also be found in

Docket A-2001-28, Document No. II-A-179.

U.S. Census Bureau. 1997 Economic Census, Manufacturing, Industry Series, Petroleum

Refineries, EC97M-3241A, Table 1. A copy of this document can be found at
 Industry Characterization

1-41

http://www.census.gov/prod/ec97/97m3241a.pdf. A copy can also be found in Docket A2001-28, Document No. II-A-180.

U.S. Census Bureau, 2002 Annual Survey of Manufactures, Statistics for Industry Groups and

Industries M00(AS)-1, M00(AS)-1, Table 2. A copy of this document can be found at

http://www.census.gov/prod/2002pubs/m00as-1.pdf. A copy can also be found in Docket

A-2001-28, Document No. II-A-181.
CHAPTER 2: Air Quality, Health, and Welfare Effects

2.1 Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3

2.1.1 Health Effects of Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

2.1.2 Attainment and Maintenance of the PM10 and PM2.5 NAAQS: Current and Future

Air Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

2.1.2.1 Current PM Air Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

2.1.2.2 Risk of Future Violations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-26

2.1.3 Environmental Effects of Particulate Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-38

2.1.3.1 Visibility Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-39

2.1.3.2 Other Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-51

2.2 Air Toxics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-55

2.2.1 Diesel Exhaust PM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-55

2.2.1.1 Potential Cancer Effects of Diesel Exhaust . . . . . . . . . . . . . . . . . . . . . . . . 2-55

2.2.1.2 Other Health Effects of Diesel Exhaust . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-59

2.2.1.3 Diesel Exhaust PM Ambient Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-61

2.2.1.4 Diesel Exhaust PM Exposures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-71

2.2.2 Gaseous Air Toxics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-75

2.2.2.1 Benzene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-79

2.2.2.2 1,3-Butadiene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-82

2.2.2.4 Acetaldehyde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-85

2.2.2.6 Polycyclic Organic Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-87

2.2.2.7 Dioxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-88

2.3 Ozone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-88

2.3.1 Health Effects of Ozone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-89

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS . . . . . 2-92

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS . . . . . 2-93

2.3.2.1 1-Hour Ozone Nonattainment and Maintenance Areas and Concentration 2-95

2.3.2.2 8-Hour Ozone Levels: Current Nonattainment and Future Concentrations 2-97

2.3.2.3 Potentially Counterproductive Impacts on Ozone Concentrations from NOx

Emission Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-113

2.3.3 Welfare Effects Associated with Ozone and its Precursors . . . . . . . . . . . . . . . 2-118

2.4 Carbon Monoxide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-121

2.4.1 General Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-121

2.4.2 Health Effects of CO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-122

2.4.3 CO Nonattainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-122
Air Quality, Health, and Welfare Effects

2-1

CHAPTER 2: Air Quality, Health, and Welfare Effects

With this rulemaking, we are acting to extend highway types of emission controls to another

major source of diesel engine emissions: nonroad land-based diesel engines. This final rule sets

out emission standards for nonroad land-based diesel engines - engines used mainly in

construction, agricultural, industrial and mining operations - that will achieve reductions in

particulate matter (PM) and NOx standards in excess of 95 percent and 90 percent, respectively. 

This action also regulates nonroad diesel fuel for the first time by reducing sulfur levels in this

fuel more than 99 percent to 15 part per million (ppm). The diesel fuel sulfur requirements will

decrease PM and sulfur dioxide (SO2) emissions for land-based diesel engines, as well as for

three other nonroad source categories: commercial marine diesel vessels, locomotives, and

recreational marine diesel engines.

These sources are significant contributors to atmospheric pollution of (among other

pollutants) PM, ozone and a variety of toxic air pollutants. In 1996, emissions from these four

source categories were estimated to be 40 percent of the mobile source inventory for PM2.5 and

25 percent for NOx. Without further control beyond those we have already adopted, by the year

2030, these sources will emit 44 percent of PM2.5 from mobile sources, and 47 percent of NOx

emissions from mobile sources. Thus, reducing emissions from nonroad sources is critically

important to achieving the nation’s air quality goals.

In 2030, we estimate that this program will reduce over 129,000 tons PM2.5 and 738,000 tons

of NOx. It will also virtually eliminate nonroad diesel SO2 emissions, which amounted to

approximately 236,000 tons in 1996, and would otherwise grow to approximately 379,000 tons

by 2030.

These dramatic reductions in nonroad emissions are a critical part of the effort by Federal,

State, local and Tribal governments to reduce the health related impacts of air pollution and to

reach attainment of the National Ambient Air Quality Standard (NAAQS) for PM and ozone, as

well as to improve environmental effects such as visibility. These emission reductions will be

directly helpful to the 474 partial and full counties nationwide that have been recently designated

as nonattainment areas for the 8-hour ozone standard and the PM2.5 areas that will be designated

later this year. Based on the most recent monitoring data available for this rule, such problems

are widespread in the United States. There are almost 65 million people living in 120 counties

with PM2.5 levels exceeding the PM2.5 NAAQS (based on 2000-2002), and about 159 million

people living in 474 partial and full counties that are in nonattainment for either failing to meet 

the 8-hour ozone NAAQS or for contributing to poor air quality in a nearby area. Figure 2.-1

illustrates the widespread nature of these problems. Shown in this figure are counties exceeding

either or both of the PM2.5 NAAQS or designated 8-hour ozone nonattainment areas plus

mandatory Federal Class I areas, which have particular needs for reductions in haze.
Final Regulatory Impact Analysis

2-2

Figure I-1. Air Quality Problems are Widespread.

As described in Chapter 9, the air quality improvements expected from this rulemaking will

produce major benefits to human health and welfare, with a combined value in excess of three

quarters of a trillion dollars between 2007 and 2036. By the year 2030, we expect that this rule

will annually prevent approximately 12,000 premature deaths and 15,000 nonfatal heart attacks. 

By 2030, it will also prevent 13,000 annual acute bronchitis attacks in children, 280,000 upper

and lower respiratory symptoms in children, nearly 1 million lost work days among adults

because of their own symptoms, and 5.9 million days where adults have to restrict their activities

due to symptoms in 2030.

In this chapter and chapter 3, we describe in more detail the air pollution problems associated

with emissions from nonroad diesel engines and air quality information that we are relying upon

in this rulemaking. To meet these emission standards, engine manufacturers directly control

emissions of NOx, PM, non-methane hydrocarbons (NMHC), and to a lesser extent, carbon

monoxide (CO). Gaseous air toxics from nonroad diesel engines will also decrease as a

consequence of the new emission standards. In addition, there will be a substantial reduction in
Air Quality, Health, and Welfare Effects

AAmbient PM from nonroad diesel engine is associated with the direct emission of diesel PM

and sulfate PM, and with PM formed indirectly in the atmosphere by NOx and SO2 emissions

(and to a lesser extent NMHC emissions). Both NOx and NMHC can participate in the

atmospheric chemical reactions that produce ozone.

2-3

SO2 emissions resulting from the decreasing sulfur level in diesel fuel. SO2 is transformed in

the atmosphere to form PM (sulfate) and can also pose a public health hazard in the gas phase.

From a public health perspective, we are primarily concerned with nonroad engine

contributions to atmospheric levels of particulate matter in general (diesel PM in particular),

various gaseous air toxics emitted by diesel engines, and ozone.A We will first review important

public health effects caused by these pollutants, briefly describing the human health effects, and

we will then review the current and expected future ambient levels of directly or indirectly

caused pollution. Our presentation will show that substantial further reductions of these

pollutants, and the underlying emissions from nonroad diesel engines, will be needed to protect

public health.

Following discussion of health effects, we will discuss a number of welfare effects associated

with emissions from diesel engines. These effects include atmospheric visibility impairment,

ecological and property damage caused by acid deposition, eutrophication and nitrification of

surface waters, environmental threats posed by polycyclic organic matter (POM) deposition, and

plant and crop damage from ozone. Once again, the information available to us indicates a

continuing need for further nonroad emission reductions to bring about improvements in air

quality.

2.1 Particulate Matter

Particulate matter (PM) represents a broad class of chemically and physically diverse

substances. It can be principally characterized as discrete particles that exist in the condensed

(liquid or solid) phase spanning several orders of magnitude in size. PM10 refers to particles with

an aerodynamic diameter less than or equal to a nominal 10 micrometers. Fine particles refer to

those particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers

(also known as PM2.5), and coarse fraction particles are those particles with an aerodynamic

diameter greater than 2.5 microns, but less than or equal to a nominal 10 micrometers. Ultrafine

PM refers to particles with diameters of less than 100 nanometers (0.1 micrometers). The health

and environmental effects of PM are in some cases related to the size of the particles. 

Specifically, larger particles (greater than 10 micrometers) tend to be deposited nasally and in

the larger conducting airways, and they are removed by the respiratory clearance mechanisms

whereas smaller particles (PM10) are deposited deeper in the lungs. Also, fine particles scatter

light obstructing visibility.

In addition to directly emitted particles, nonroad diesel engines currently emit high levels of

NOx, which reacts in the atmosphere to form secondary PM2.5 (namely ammonium nitrate). 
Final Regulatory Impact Analysis

2-4

Nonroad diesel engines also emit SO2 and HC, which react in the atmosphere to form secondary

PM2.5 (namely sulfates and organic carbonaceous PM2.5). Both types of directly and indirectly

formed particles from nonroad engines are found principally in the fine fraction. Thus, this

discussion will focus on fine particles (PM2.5). Ambient fine particles are a complex mixture

generally composed of sulfate, nitrate, chloride, ammonium compounds, organic carbon,

elemental carbon, and metals. Fine particles can remain in the atmosphere for days to weeks and

travel through the atmosphere hundreds to thousands of kilometers, while coarse particles

generally tend to deposit to the earth within minutes to hours and within tens of kilometers from

the emission source. 

2.1.1 Health Effects of Particulate Matter

Scientific studies show ambient PM concentrations (which are attributable to a number of

sources including diesel) contribute to a series of adverse health effects. These health effects are

discussed in detail in the EPA Air Quality Criteria Document for PM (PM Criteria Document) as

well as the draft updates of this document released in the past year.1

 EPA’s Health Assessment

Document for Diesel Engine Exhaust (Diesel HAD) also reviewed health effects information

related to diesel exhaust as a whole including diesel PM, which is one component of ambient

PM.2 We are relying on the data and conclusions in these documents regarding the effects of

particulate matter. We also present additional recent studies. Taken together this information

supports the conclusion that PM-related emissions from nonroad diesel engines have been

associated with adverse health effects. 

We received a number of public comments on specific health studies, and we are relying on

the discussions and conclusions presented in the PM Criteria Document and Diesel HAD in

which EPA prepared detailed evaluations of the body of scientific information and subjected

those evaluations to extensive public and expert peer review. Additional information is

available in the Summary and Analysis of Public Comments that accompanies this final rule.

2.1.1.1 Short-Term Exposure-Mortality and Morbidity Studies

As detailed in the PM Criteria Document, health effects associated with short-term variation

in ambient PM have been indicated by numerous epidemiologic studies showing associations

between exposure and increased hospital admissions for ischemic heart disease,3

 heart failure,4

respiratory disease,5, 6, 7, 8 including chronic obstructive pulmonary disease (COPD) and

pneumonia.9, 10, 11 Short-term elevations in ambient PM have also been associated with increased

cough, lower respiratory symptoms, and decrements in lung function.12, 13, 14 Short-term

variations in ambient PM have also been associated with increases in total and cardiorespiratory

daily mortality in individual cities15, 16, 17, 18 and in multi-city studies.19, 20, 21

Several studies specifically address the contribution of PM from mobile sources in these

time-series studies. Analyses incorporating source apportionment by factor analysis with daily

time-series studies of daily death also established a specific influence of mobile source-related

PM2.5 on daily mortality22 and a concentration-response function for mobile source-associated

PM2.5 and daily mortality.23 Another recent study in 14 U.S. cities examined the effect of PM10
Air Quality, Health, and Welfare Effects

2-5

exposures on daily hospital admissions for cardiovascular disease (CVD). They found that the

effect of PM10 was significantly greater in areas with a larger proportion of PM10 coming from

motor vehicles, indicating that PM10 from these sources may have a greater effect on the toxicity

of ambient PM10 when compared with other sources.24

In 2002, questions were raised about the default convergence criteria and standard error

calculations made using generalized additive models (GAM), which has been the statistical

model of choice in many of the time-series epidemiologic studies. A number of time-series

studies were reanalyzed using alternative methods, typically GAM with more stringent

convergence criteria and an alternative model such as generalized linear models (GLM) with

natural smoothing splines. Since then, the Health Effects Institute convened an expert panel to

review the results of and the results of the reanalyses have been compiled and reviewed in a

recent HEI publication.25 In most, but not all, of the reanalyzed studies, it was found that risk

estimates were reduced and confidence intervals increased with the use of GAM with more

stringent convergence criteria or GLM analyses; however, the reanalyses generally did not

substantially change the findings of the original studies, and the changes in risk estimates with

alternative analysis methods were much smaller than the variation in effects across studies. The

HEI review committee concluded the following:

a. While the number of studies showing an association of PM with mortality was slightly

smaller, the PM association persisted in the majority of studies.

b. In some of the large number of studies in which the PM association persisted, the

estimates of PM effect were substantially smaller.

c. In the few studies in which investigators performed further sensitivity analyses, some

showed marked sensitivity of the PM effect estimate to the degree of smoothing and/or

the specification of weather. 

As discussed in Chapter 9, examination of the original studies used in our economic benefits

analysis found that the health endpoints that are potentially affected by the GAM issues include:

reduced hospital admissions, reduced lower respiratory symptoms, and reduced premature

mortality due to short-term PM exposures. It is important to note that the benefits estimates

derived from the long-term exposure studies, which account for a major share of the economic

benefits described in Chapter 9, are not affected. Similarly, the time-series studies and casecrossover studies employing generalized linear models or other parametric methods are not

affected. 

2.1.1.2 Long-Term Exposure Mortality and Morbidity Studies

Short-term studies provide one way of examining the effect of short-term variations in air

quality on morbidity and mortality. However, they do not allow for an evaluation of the effect of

long-term exposure to air pollution on human mortality and morbidty.26 Longitudinal cohort

studies allow for analysis of such effects. 

As discussed in the PM Criteria Document, the newer morbidity studies that combine the

features of cross-sectional and cohort studies provide the best evidence for chronic exposure
Final Regulatory Impact Analysis

2-6

effects. The Gauderman et al. studies both found significant decreases in lung function growth

among southern California school children to be related to PM2.5 and/or PM10 levels.27,

28

However, Peters et al. reported no relationship between respiratory symptoms and annual

average PM10 levels in 12 southern California communities.29 Long-term (months to years)

exposure to PM was linked with decreased lung function and increased incidence of respiratory

disease such as bronchitis (PM Criteria Document 1996, p. V-26, Abbey et al. 1995). The

results of studies using long-term and short-term PM exposure data were reported to be

consistent with one another. In addition, toxicology studies using surrogate particles or PM

components, generally at high concentrations, and autopsy studies of humans and animals

reported evidence of pulmonary effects, including morphological damage (e.g., changes in

cellular structure of the airways) and changes in resistance to infection. 

Additional data are available regarding long-term PM exposures and mortality. To date, four

major cohorts in the U.S. have examined mortality and long-term exposure to PM2.5. These

studies are described in detail in the PM Criteria Document and we are relying on the analyses

and conclusions in that document for these studies. Many of the issues raised in public comment

are addressed by the Criteria Document (as detailed in the Summary and Analysis of public

comments document.) In addition to the U.S. studies, there are additional data from Europe and

Canada. A cohort in the Netherlands evaluated exposure to mobile source-related pollutants.30

Another study examines exposure-mortality relationships with income in southern Ontario,

Canada.31

Two major U.S. cohort studies, the Harvard Six Cities and the American Cancer Society

studies, suggest an association between exposure to ambient PM2.5 measured in the city of

residence and premature mortality from cardiorespiratory causes.32, 33 As discussed in the PM

Criteria Document, these two prospective cohort studies tracked health outcomes in discrete

groups of people over time. Subsequent reanalysis of these studies have confirmed the findings

of these articles, and a recent extension of the ACS cohort study found statistically significant

increases in lung cancer mortality risk associated with ambient PM2.5.

34 This most recent finding

is of special interest in this rulemaking, because of the association of diesel exhaust and lung

cancer in occupational studies of varying design.

More recently, the Adventist Health Study on Smog (AHSMOG) in California indicated that

long-term exposure to PM10 resulted in a significant risk of premature mortality in men, although

risks were not elevated among women.35 In another AHSMOG analysis, ambient PM2.5 estimates

made from visibility data at an airport were used to compare the effects of PM10 and PM2.5 for the

cohort.36 No statistically significant increase in risk was observed with any component of PM. 

Among men, the PM2.5 coefficient on mortality from all natural causes was consistently larger

than the coarse fraction of PM10. Among women, no elevation in mortality risk was found for

any PM index. 

Another study evaluated in the PM Criteria Document examining long-term exposure to

ambient PM and mortality is the Electric Power Research Institute (EPRI)-Washington

University mortality study in American Veterans.37 The Veterans Study was originally designed

as a means of assessing the efficacy of anti-hypertensive drugs in reducing morbidity and
Air Quality, Health, and Welfare Effects

2-7

mortality in a population with pre-existing high blood pressure (in this case, male veterans)

(Lipfert et al., 2000). Unlike previous long-term analyses, this study found some associations

between premature mortality and ozone but found inconsistent results for PM indicators. A

variety of issues associated with the study design, including sample representativeness and loss

to follow up, make this cohort a poor choice for extrapolating to the general public. 

Furthermore, the selective nature of the population in the veteran’s cohort and methodological

weaknesses may have resulted in estimates of relative risk that are biased relative to a relative

risk for the general population.

The Hoek et al. (2002) study examines a cohort of residents of the Netherlands who were

recruited as part of the Netherlands Cohort study on Diet and Cancer (NLCS).38 Five thousand

study participants were selected at random from the larger cohort, which consisted of persons

aged 55 to 69 in 1986, with follow up until 1994. In 1986, all participants filled out

questionnaires on diet and other risk factors. All participants with full questionnaire data were

included in the study. Each participants’ home address was mapped by street address. 

Individual exposures to ambient pollutants were assigned by matching residential address to an

exposure metric via geographic information system (GIS). “Black smoke” – widely used in

Europe as a surrogate of particulate elemental carbon – and NO2 had been previously assessed as

a function of regional background, urban background, and contribution from local traffic based

on proximity to busy roads.39 Results of the survival analysis indicated that residential black

smoke predicted from regional, urban, and intra-urban variation was associated with a relative

risk (RR) of cardiopulmonary mortality per 10 ug/m3 of 1.71 (with a 95 percent confidence

interval (CI) of [1.10, 2.67]) and an RR for all-cause mortality of 1.31 [0.95, 1.80]. In a model

including background black smoke and proximity to a major roadway, the cardiopulmonary

mortality RR associated with living near a busy road was 1.95 [1.09, 3.51]. This study is of

particular interest in this rule, because of the strong focus on mobile source pollutants in the

exposure assessment portion of the study. This study also highlights the “near-roadway” health

concerns, discussed later.

The Six Cities, ACS, AHSMOG, Veterans, and NLCS Studies are discussed in detail in the

draft PM Criteria Document and revised Chapter 8. We are relying on the evaluations and

conclusions presented in those documents. The long-term exposure health effects of PM are

summarized in Table 2.1.1-1, which is taken directly from Table 9-11 of the draft Air Quality

Criteria Document referenced earlier that was released in 2003. This document is continuing to

undergo expert and public review. One study discussed below does not appear in the PM

Criteria Document because it was published after the date required for inclusion in the Criteria

Document.40

Finklestein et al. (2003) examined a cohort of 5,228 residents of the Hamilton-Burnling area

of southern Ontario, Canada who had been referred for lung function testing between 1985 and

1999. 41 The study was not a random sample of the population in the Hamilton-Burlington area.

Total non-accidental and cardiopulmonary mortalities between 1992 and 1999 were determined

based on the Ontario Mortality Registry. The subjects’ age, sex, postal code, body mass index,

and pulmonary function test results were matched with disease diagnosis via the Ontario Health

Insurance Plan. Canada’s health insurance system allowed the investigators to determine disease
Final Regulatory Impact Analysis

2-8

diagnoses during the follow-up period. Postal codes were used to assign “ecological” variables

of census-derived mean household income, 24-hour average total suspended particulate (TSP)

measured every 6 days, and SO2 measured continuously during the mid-1990's Air monitoring

data came from 9 TSP and 23 SO2 monitors, which were subject to spatial interpolation

techniques. Postal code-specific pollutant concentrations were assigned using GIS. Analysis of

the air quality data indicated that TSP and SO2 tended to be higher in low-income areas. The

study group was divided into higher and lower income and pollution strata, based on the median

income, and TSP and SO2 levels at the postal code level. Compared to the high-income, lowpollution group, all other groups had significantly elevated mortality relative risks with income,

and each pollutant (in one-pollutant models) was associated with increased risk. Age appeared

as an effect modifier, with attenuated effects at elevated age. 

The 1996 PM AQCD indicated that past epidemiologic studies of chronic PM exposures

collectively indicate increases in mortality to be associated with long-term exposure to airborne

particles of ambient origins. The PM effect size estimates for total mortality from these studies

also indicated that a substantial portion of these deaths reflected cumulative PM impacts above

and beyond those exerted by acute exposure events. 

Several advances have been made in terms of further analyses and/or reanalyses of several

studies of long-term PM exposure effects on total, cardiopulmonary, or lung cancer mortality. 

The Harvard Six Cities analyses (as confirmed by the HEI reanalyses) and the recent extension

of the ACS study by Pope et al. (2002) probably provide the most credible and precise estimates

of excess mortality risk associated with long-term PM2.5 exposures in the United States. 

2.1.1.3 Long-Term Exposures and Physiological Response in Individuals

Several studies examined in the PM Criteria Document have examined the effect of longterm exposure to air pollution on individual physiological and organ structure. These studies

provide insight into the biological pathways by which air pollution may act to produce adverse

health effects. The studies below provide examples of the types of studies examined in the PM

Criteria Document.

Studies in Vancouver, BC, and Mexico City, Mexico, have demonstrated increased retention

of PM2.5 in the lungs of residents of the more highly polluted Mexico City.42 More recently,

comparisons of non-smoking women in Mexico City and Vancouver have shown that particle

retention in the lungs of Mexico City women was associated with small airways remodeling.43

In another study, dogs autopsied in the Mexico City and other less-polluted areas showed that

dogs in more polluted areas showed greater respiratory and cardiac pathology indicative of longterm inflammatory stress.44,45

One recent study (not addressed in the PM Criteria Document) was conducted in Leicester,

UK studying lung cells (alveolar macrophages (AM)) obtained from children undergoing

elective surgery.46 The cells were examined by electron microscope, and the study reported that

in all children, some of the AMs contained particles, ranging from 1 to 16 percent of total AM

collected. Of particular note, the authors found that a significantly higher fraction of the AM
Air Quality, Health, and Welfare Effects

2-9

collected from children living on main roads contained particles as compared to children living

on quiet residential roads, and that these particles were composed of single and chain aggregates

of ultrafine carbon particles that appeared to be combustion-related. This study is of particular

relevance to this rule, given the evidence that exposure to mobile source PM results in greater

concentrations of PM in the lung. Given the elevated exposures to carbonaceous PM in

occupations that work with nonroad diesel engines (discussed below), this study provides a link

between nonroad PM exposure an potential lung and systemic health effects. 

2.1.1.4 Studies of Short-Term Exposures and Physiological Response in Individuals

A number of studies have investigated biological processes and physiological effects that

may underlie the epidemiologic findings of earlier studies. This research has found associations

between short-term changes in PM exposure with changes in heart beat, force, and rhythm,

including reduced heart rate variability (HRV), a measure of the autonomic nervous system’s

control of heart function.47, 48, 49, 50, 51, 52 The findings indicate associations between measures of

heart function and PM measured over the prior 3 to 24 hours or longer. Decreased HRV has

been shown to be associated with coronary heart disease and cardiovascular mortality in both

healthy and compromised populations.53, 54, 55, 56

Other studies have investigated the association between PM and such systemic factors such

as inflammation, blood coagulability and viscosity. It is hypothesized that PM-induced

inflammation in the lung may activate a “non-adaptive” response by the immune system,

resulting in increased markers of inflammation in the blood and tissues, heightened blood

coagulalability, and leukocyte count in the blood. A number of studies have found associations

between controlled exposure to either concentrated or ambient PM or diesel exhaust exposure

and pulmonary inflammation.57, 58, 59, 60 A number of studies have also shown evidence of

increased blood markers of inflammation, such as C-reactive protein, fibrinogen, and white

blood cell count associated with inter-day variability in ambient PM.61, 62, 63, 64 These blood

indices have been associated with coronary heart disease and cardiac events such as heart

attack.65, 66 Studies have also shown that repeated or chronic exposures to urban PM were

associated with increased severity of atherosclerosis, microthrombus formation, and other

indicators of cardiac risk.67, 68

The recent studies examining inflammation, heart rate and rhythm in relation to PM provide

some evidence into the mechanisms by which ambient PM may cause injury to the heart. New

epidemiologic data have indicated that short-term changes in ambient PM mass is associated

with adverse cardiac outcomes like myocardial infarction (MI) or ventricular arrythmia.69, 70

These studies provide additional evidence that ambient PM2.5 can cause both acute and chronic

cardiovascular injury, which can result in death or non-fatal effects.
Final Regulatory Impact Analysis

2-10

Table 2.1.1-1

Effect Estimates per Incrementsa in Long-term Mean Levels of 

Fine and Inhalable Particle Indicators From U.S. and Canadian Studies

Type of Health

Effect and Location Indicator

Change in Health Indicator per

Increment in PM*

Range of City 

PM Levels **

Means (μg/m3)

Increased Total Mortality in Adults Relative Risk (95% CI)

Six CityB PM15/10 (20 μg/m3

) 1.18 (1.06-1.32) 18-47

PM2.5 (10 μg/m3) 1.13 (1.04-1.23) 11-30

SO4

=

 (15 μg/m3) 1.46 (1.16-2.16) 5-13

ACS StudyC

(151 U.S. SMSA)

PM2.5 (10 μg/m3) 1.07 (1.04-1.10) 9-34

SO4

=

 (15 μg/m3) 1.10 (1.06-1.16) 4-24

Six City ReanalysisD PM15/10 (20 μg/m3) 1.19 (1.06-1.34) 18.2-46.5

PM2.5 (10 μg/m3

) 1.13 (1.04-1.23) 11.0-29.6

ACS Study ReanalysisD PM15/10 (20 μg/m3)

(dichot)

1.04 (1.01-1.07) 58.7 (34-101)

PM2.5 (10 μg/m3) 1.07 (1.04-1.10) 9.0-33.4

ACS Study Extended

AnalysesQ

PM2.5 (10 μg/m3) 1.04 (1.01-1.08) 21.1 (SD=4.6)

Southern CaliforniaE PM10 (20 μg/m3

) 1.091 (0.985-1.212) (males) 51 (±17)

PM10 (cutoff =

30 days/year

>100 μg/m3)

1.082 (1.008-1.162) (males)

PM10 (20 μg/m3) 0.950 (0.873-1.033) (females) 51 (±17)

PM10 (cutoff =

30 days/year

>100 μg/m3)

0.958 (0.899-1.021) (females)

Vetrans CohortR PM2.5 (10 μg/m3

) 0.90 (0.85, 0.954; males) 5.6-42.3

Increased Bronchitis in Children Odds Ratio (95% CI)

Six CityF PM15/10 (50 μg/m3

) 3.26 (1.13, 10.28) 20-59

Six CityG TSP (100 μg/m3) 2.80 (1.17, 7.03) 39-114

24 CityH H+ (100 nmol/m3) 2.65 (1.22, 5.74) 6.2-41.0

24 CityH SO4

=

 (15 μg/m3) 3.02 (1.28, 7.03) 18.1-67.3

24 CityH PM2.1 (25 μg/m3

) 1.97 (0.85, 4.51) 9.1-17.3

24 CityH PM10 (50 μg/m3) 3.29 (0.81, 13.62) 22.0-28.6

Southern CaliforniaI SO4

=

 (15 μg/m3) 1.39 (0.99, 1.92) —

12 Southern California

communitiesJ

(all children)

PM10 (25 μg/m3

)

Acid vapor (1.7 ppb)

0.94 (0.74, 1.19)

1.16 (0.79, 1.68)

28.0-84.9

0.9-3.2 ppb

12 Southern California

communitiesK

(children with asthma)

PM10 (19 μg/m3

)

PM2.5 (15 μg/m3)

Acid vapor (1.8 ppb)

1.4 (1.1, 1.8)

1.4 (0.9, 2.3)

1.1 (0.7, 1.6)

13.0-70.7

6.7-31.5

1.0-5.0 ppb
Type of Health

Effect and Location Indicator

Change in Health Indicator per

Increment in PM*

Range of City 

PM Levels **

Means (μg/m3

)

Increased Cough in Children Odds Ratio (95% CI)

12 Southern California

communitiesJ

(all children)

PM10 (20 μg/m3)

Acid vapor (1.7 ppb)

1.05 (0.94, 1.16)

1.13 (0.92, 1.38)

28.0-84.9

0.9-3.2 ppb

12 Southern California

communitiesK

(children with asthma)

PM10 (20 μg/m3

)

PM2.5 (10 μg/m3

)

Acid vapor (1.8 ppb)

1.1 (0.7, 1.8)

1.2 (0.8, 1.8)

1.4 (0.9, 2.1)

13.0-70.7

6.7-31.5

1.0-5.0 ppb

10 Canadian

Communitiess

PM10 (20 μg/m3) 1.19 (1.04,1.35) 13-23

Increased Wheeze in Children

10 Canadian

Communitiess

PM10 (20 μg/m3) 1.35 (1.10,1.64) 13-23

Increased Airway Obstruction in Adults

Southern CaliforniaL PM10 (20μg/m3

) 1.09 (0.92, 1.30) NR

Decreased Lung Function in Children

Six CityF PM15/10 (50 μg/m3

) NS Changes 20-59

Six CityG TSP (100 μg/m3

) NS Changes 39-114

24 CityM H+

 (52 nmoles/m3) !3.45% (-4.87, -2.01) FVC 6.2-41.0

24 CityM PM2.1 (15 μg/m3

) !3.21% (-4.98, -1.41) FVC 18.1-67.3

24 CityM SO4

=

 (7 μg/m3) !3.06% (-4.50, -1.60) FVC 9.1-17.3

24 CityM PM10 (17 μg/m3

) !2.42% (-4.30, -.0.51) FVC 22.0-28.6

12 Southern California

communitiesN

(all children)

PM10 (25 μg/m3

)

Acid vapor (1.7 ppb)

!24.9 (-47.2, -2.6) FVC

!24.9 (-65.08, 15.28) FVC

28.0-84.9

0.9-3.2 ppb

12 Southern California

communitiesN

(all children)

PM10 (25 μg/m3

)

Acid vapor (1.7 ppb)

!32.0 (-58.9, -5.1) MMEF

!7.9 (-60.43, 44.63) MMEF

28.0-84.9

0.9-3.2 ppb

12 Southern California

communitiesO

(4th grade cohort)

PM10 (51.5 μg/m3

)

PM2.5 (25.9 μg/m3

)

PM10-2.5 (25.6 μg/m3

)

Acid vapor (4.3 ppb)

!0.58 (-1.14, -0.02) FVC growth

!0.47 (-0.94, 0.01) FVC growth

!0.57 (-1.20, 0.06) FVC growth

!0.57 (-1.06, -0.07) FVC growth

NR

12 Southern California

communitiesO

(4th grade cohort)

PM10 (51.5 μg/m3)

PM2.5 (25.9 μg/m3

)

PM10-2.5 (25.6 μg/m3

)

Acid vapor (4.3 ppb)

!1.32 (-2.43, -0.20) MMEF growth

!1.03 (-1.95, -0.09) MMEF growth

!1.37 (-2.57, -0.15) MMEF growth

!1.03 (-2.09, 0.05) MMEF growth

NR
Type of Health

Effect and Location Indicator

Change in Health Indicator per

Increment in PM*

Range of City 

PM Levels **

Means (μg/m3

)

Lung Function Changes in Adults

Southern CaliforniaP

(% predicted FEV1,

females)

PM10 (cutoff of

54.2 days/year

>100 μg/m3

)

+0.9 % (-0.8, 2.5) FEV1 52.7 (21.3, 80.6)

Southern CaliforniaP

(% predicted FEV1, males)

PM10 (cutoff of

54.2 days/year

>100 μg/m3

)

+0.3 % (-2.2, 2.8) FEV1 54.1 (20.0, 80.6)

Southern CaliforniaP

(% predicted FEV1, males

whose parents had asthma,

bronchitis, emphysema)

PM10 (cutoff of

54.2 days/year

>100 μg/m3

)

!7.2 % (-11.5, -2.7) FEV1 54.1 (20.0, 80.6)

Southern CaliforniaP

(% predicted FEV1,

females)

SO4

=

 (1.6 μg/m3) Not reported 7.4 (2.7, 10.1)

Southern CaliforniaP

(% predicted FEV1, males)

SO4

=

 (1.6 μg/m3) !1.5 % (-2.9, -0.1) FEV1 7.3 (2.0, 10.1)

*Results calculated using PM increment between the high and low levels in cities, or other PM increments

given in parentheses; NS Changes = No significant changes.

**Range of mean PM levels given unless, as indicated, studies reported overall study mean (min, max), or

mean (±SD); NR=not reported.

*** Results only for smoking category subgroups.

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 Schwartz, J.; Dockery, D. W.; Neas, L. M. (1996) Is daily mortality associated specifically with fine particles? J. Air

Waste Manage. Assoc. 46: 927-939. b

 Ostro, B. D.; Broadwin, R.; Lipsett, M. J. (2000) Coarse and fine particles and daily mortality in the Coachella Valley,

California: a follow-up study. J. Exposure Anal. Environ. Epidemiol. 10: 412-419. c

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mortality and morbidity in urban populations. Cambridge, MA: Health Effects Institute; research report no. 95. d

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size-classified particulate matter. J. Air Waste Manage. Assoc.: 1501-1513. e

 Mar, T. F.; Norris, G. A.; Koenig, J. Q.; Larson, T. V. (2000) Associations between air pollution and mortality in

Phoenix, 1995-1997. Environ. Health Perspect. 108: 347-353. f

 Smith, R. L.; Spitzner, D.; Kim, Y.; Fuentes, M. (2000) Threshold dependence of mortality effects for fine and coarse

particles in Phoenix, Arizona. J. Air Waste Manage. Assoc. 50: 1367-1379. g

 Fairley, D. (1999) Daily mortality and air pollution in Santa Clara County, California: 1989-1996. Environ. Health

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 Burnett, R. T.; Brook, J.; Dann, T.; Delocla, C.; Philips, O.; Cakmak, S.; Vincent, R.; Goldberg, M. S.; Krewski, D.

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S

Howel et al. 2001

2.1.1.6 Roadway-Related Exposure and Health Studies

A recent body of studies has suggested a link between residential proximity to heavilytrafficked roadways (where diesel engines are operated) and adverse health effects. While many

of these studies did not measure PM specifically, they include potential exhaust exposures which

include mobile source PM because they employ exposure indices such as roadway proximity or

traffic volumes.

Based on extensive emission characterization studies and as reviewed in the EPA Diesel

HAD (Health Assessment Document for Diesel Exhaust), diesel PM is found principally in the

fine fraction (both primary and secondarily formed PM).71, 72 In addition, in the Diesel HAD, we

note that the particulate characteristics in the zone around nonroad diesel engines is likely to be

substantially the same as published air quality measurements made along busy roadways. This

conclusion supports the relevance of health effects associated with on-road diesel enginegenerated PM to nonroad applications. Thus, near roadway studies are relevant to understanding

potential health impacts of emissions from nonroad diesel engines. 

Specifically, in a recent body of studies, scientists have examined health effects associated

with living near major roads. As discussed above, a Dutch cohort study recently developed

estimates of the relative risk of cardiopulmonary and all-cause mortality associated with living

near a busy roadway.73 The study found a statistically significant excess risk of cardiopulmonary

mortality of 95 percent (i.e., a relative risk of 1.95, 95% CI: 1.09-3.52) associated with living

near a busy road. A recent British ecological study examined mortality attributable to stroke in

England and Wales.74 After adjusting for potential confounders, the study found a significantly

greater rate of mortality in men and women living within 200 meters of a busy road of 7 percent

[95% CI on RR: 1.04 to 1.09] and 4 percent [95% CI on RR: 1.02-1.06], respectively. Risks

decreased with increased distance from roadways. However, being an ecological study design, it

is impossible to rule out confounding variables.

Other studies relate the incidence or prevalence of respiratory health outcomes to roadway

proximity. Several studies have found positive associations between respiratory symptoms and

residential roadway proximity or traffic volume. Most recently, a study in U.S. veterans living
Final Regulatory Impact Analysis

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in southeastern Massachusetts found significant increases in self-reported respiratory symptoms

among subjects living within 50 meters of a major road.75 

A Dutch cohort study following infants from birth found that traffic-related pollutant

concentrations found positive associations with respiratory symptoms, several illnesses, and

physician-diagnosed asthma, the last of which was significant for diagnoses prior to 1 year of

age.76

In a case-control study of children under 14 years old in San Diego, CA, with asthma

diagnosis was confirmed by Medicaid claims, no associations between odds of physician

diagnosis of asthma and traffic was found.77 However, a case-based analysis of the data

associated traffic flows with an increased number of medical visits among children with asthma.

A case-control study of children aged 4 to 48 months diagnosed with wheezing bronchitis

included exposures predicted from traffic data, dispersion models of NO2 as a marker of mobile

source emissions, and included separate exposures for home and day care.78 Analyses found that

cases had significantly elevated NO2 exposures compared with controls, but only among girls. A

significant trend with NO2 was reported.

Two cross-sectional studies of self-reported wheezing and allergic rhinitis symptoms in

German aged 12 to 15 years found increased prevalence of wheezing and allergic rhinitis based

on subject-reported frequency of truck traffic.79,

80

A cross-sectional study in the Netherlands examined self-reported respiratory diagnoses,

allergies, and respiratory symptoms in association with annual truck and automobile density,

living within 100 meters of a freeway, and indoor measures of air pollution (black smoke,

NO2).81 The study found associations for truck traffic density with wheeze and asthma attacks

in girls but not boys. Associations among girls but not boys were also found for homes within

100 m of a freeway and chronic cough, wheeze, and rhinitis. Physician-diagnosed asthma was

not associated with traffic-related exposures. Physician-diagnosed allergy was inversely

associated with NO2 and black smoke.

A cross-sectional study in Surrey, England, compared city wards transected by freeways and

those not transected by freeways.82 Respiratory symptoms in the past year and self-reported

diagnosis of asthma by a physician was not associated with any respiratory metric.

A recent review of epidemiologic studies examining associations between asthma and

roadway proximity concluded that some coherence was evident in the literature, indicating that

asthma, lung function decrement, respiratory symptoms, and atopic illness appear to be higher

among people living near busy roads.83 Other studies have shown children living near roads with

high truck traffic density have decreased lung function and greater prevalence of lower

respiratory symptoms compared with children living on other roads.84 

Another recently published study from Los Angeles, CA, found that maternal residence near

heavy traffic during pregnancy is associated with adverse birth outcomes, such as preterm birth
Air Quality, Health, and Welfare Effects

2-15

and low birth weight.85 However, these studies are not specifically related to PM, but to fresh

emissions from mobile sources, which includes other components as well.

Other studies have shown that living near major roads results in substantially higher

exposures to ultrafine particles. A British study found that in the lungs of children living near

major roads in Leicester, UK, a significantly higher proportion of the alveolar macrophages

contained PM compared with children living on quiet streets.86 All particles observed in the

lungs of children were carbon particles under 0.1 um, which are known to be emitted from diesel

engines and other mobile sources. This study is consistent with recent studies of ultrafine

particle concentrations around major roads in Los Angeles, CA and Minnesota, which found that

concentrations of the smallest particles were substantially elevated near roadways with diesel

traffic.87, 88, 89

The particulate characteristics in the zone around nonroad diesel engines is not likely to

differ substantially from published air quality measurements made along busy roadways; thus,

these studies are relevant to the diesel exhaust emissions from nonroad diesel engines. While

these studies do not specifically examine nonroad diesel engines, several observations may be

drawn. First, nonroad diesel engine emissions are similar in their emission characteristics to onroad motor vehicles. Secondly, exposures from nonroad engines may actually negatively bias

these studies, because exposures from nonroad sources are not accounted for, and therefore

reduce the study’s statistical power. Third, certain populations that are exposed directly to fresh

nonroad diesel exhaust are exposed at greater concentrations than those found in studies among

the general population. These groups include workers in the construction, timber, mining, and

agriculture industries, and members of the general population that spend a large amount of time

near areas where diesel engine emissions are most densely clustered, such as residents in

buildings near large construction sites.

2.1.2 Attainment and Maintenance of the PM10 and PM2.5 NAAQS: Current and Future

Air Quality

2.1.2.1 Current PM Air Quality

There are NAAQS for both PM10 and PM2.5. Violations of the annual PM2.5 standard are

much more widespread than are violations of the PM10 standards. Emission reductions needed to

attain the PM2.5 standards will also assist in attaining and maintaining compliance with the PM10

standards. Thus, since most PM emitted by nonroad diesel engines is in the fine fraction of PM,

the emission controls resulting from this final rule will contribute to attainment and maintenance

of the existing PM NAAQS. More broadly, the new standards will benefit public health and

welfare through reductions in direct diesel PM and reductions of NOx, SOx, and HCs that

contribute to secondary formation of PM. As described above, diesel particles from nonroad

diesel engines are a component of both coarse and fine PM, but fall mainly in the fine (and even

ultrafine) size range. 
Final Regulatory Impact Analysis

B

On August 6, 2002, EPA finalized certain actions affecting the Searles Valley, California, PM10 nonattainment

area, which is located in the rural high desert and includes portions of Inyo, Kern, and San Bernardino Counties. The

action splits the Searles Valley nonattainment area into three separate areas: Coso Junction, Indian Wells Valley and

Trona. EPA's action also determines that the Trona area attained the PM-10 standards by December 31, 1994. On

May 7, 2003, EPA finalized approval of the Indian Wells Moderate Area and Maintenance Plan and redesignated the

area from nonattainment to attainment for particulate matter (PM-10).

Source: http://www.epa.gov/region9/air/searlespm/index.html

2-16

The emission reductions from this final rule will assist States as they work with EPA through

implementation of local controls including the development and adoption of additional controls

as needed to help their areas attain and maintain the standards.

2.1.2.1.1 PM10 Levels

The current NAAQS for PM10 were established in 1987. The primary (health-based) and

secondary (public welfare based) standards for PM10 include both short- and long-term NAAQS. 

The short-term (24-hour) standard of 150 :g/m3 is not to be exceeded more than once per year

on average over three years. The long-term standard specifies an expected annual arithmetic

mean not to exceed 50 :g/m3 averaged over three years.

Currently, 29.3 million people live in PM10 nonattainment areas, including moderate and

serious areas. There are presently 56 moderate PM10 nonattainment areas with a total population

of 6.6 million.90 The attainment date for the initial moderate PM10 nonattainment areas,

designated by law on November 15, 1990, was December 31, 1994. Several additional PM10

nonattainment areas were designated on January 21, 1994, and the attainment date for these areas

was December 31, 2000. 

There are 8 serious PM10 nonattainment areas with a total affected population of 22.7 million. 

According to the Act, serious PM10 nonattainment areas must attain the standards no later than

10 years after designation. The initial serious PM10 nonattainment areas were designated January

18, 1994 and had an attainment date set by the Act of December 31, 2001. The Act provides that

EPA may grant extensions of the serious area attainment dates of up to 5 years, provided that the

area requesting the extension meets the requirements of Section 188(e) of the Act. Five serious

PM10 nonattainment areas (Phoenix, Arizona; Clark County (Las Vegas), NV; Coachella Valley,

South Coast (Los Angeles), and Owens Valley, California) have received extensions of the

December 31, 2001 attainment date and thus have new attainment dates of December 31, 2006. 

Many PM10 nonattainment areas continue to experience exceedances. Of the 29.3 million

people living in designated PM10 nonattainment areas, approximately 24.5 million people are

living in nonattainment areas with measured air quality violating the PM10 NAAQS in 2000-

2002. Among these are 8 serious areas listed in Table 1.2-1 and 6 moderate areas: Nogales, AZ,

Imperial Valley, CA, Mono Basin, CA, Coso Junction, CA,B Ft. Hall, ID, and El Paso, TX.
Air Quality, Health, and Welfare Effects

2-17

 Table 1.2-1

Serious PM10 Nonattainment Areas

Area

Attainment 

Date

2000 

Population

2000-2002 Measured

Violation

Owens Valley, CA December 31, 2006 7,000 Yes

Phoenix, AZ December 31, 2006 3,111,876 Yes

Clark County, NV (Las Vegas) December 31, 2006 1,375,765 Yes

Coachella Valley, CA December 31, 2006 225,000 Yes

Los Angeles South Coast Air Basin, CA December 31, 2006 14,550,521 Yes

San Joaquin Valley, CA 2001 3,080,064 Yes

Walla Walla, WA 2001 10,000 No

Washoe County, NV (Reno) 2001 339,486 No

Total Population 22.7 million

In addition to these designated nonattainment areas, there are 16 unclassified areas, where

6.2 million live, for which States have reported PM10 monitoring data for 2000-2002 period

indicating a PM10 NAAQS violation. An official designation of PM10 nonattainment indicates

the existence of a confirmed PM10 problem that is more than a result of a one-time monitoring

upset or a result of PM10 exceedances attributable to natural events. We have not yet excluded

the possibility that one or the other of these is responsible for the monitored violations in 2000-

2002 in these 16 unclassified areas. We adopted a policy in 1996 that allows areas whose PM10

exceedances are attributable to natural events to remain unclassified if the State is taking all

reasonable measures to safeguard public health regardless of the sources of PM10 emissions. 

Areas that remain unclassified areas are not required to submit attainment plans, but we work

with each of these areas to understand the nature of the PM10 problem and to determine what best

can be done to reduce it.

2.1.2.1.2 PM2.5 Levels 

The need for reductions in the levels of PM2.5 is widespread. Figure 2.1.1-4 below shows

PM2.5 monitoring data highlighting locations measuring concentrations above the level of the

NAAQS. As can be seen from that figure, high ambient levels are widespread throughout the

country. In addition, there may be counties without monitors that exceed the level of the

standard. A listing of available measurements by county can be found in the air quality technical

support document (AQ TSD) for the rule.

The NAAQS for PM2.5 were established in 1997 (62 FR 38651, July 18, 1997). The short

term (24-hour) standard is set at a level of 65 μg/m3

 based on the 98th percentile concentration

averaged over three years. (The air quality statistic compared with the standard is referred to as
Final Regulatory Impact Analysis

2-18

the “design value.”) The long-term standard specifies an expected annual arithmetic mean not to

exceed 15 :g/m3

 averaged over three years. 

Current PM2.5 monitored values for 2000-2002 indicate that 120 counties in which almost 65

million people live have annual design values that violate the PM2.5 NAAQS. In total, this

represents 23 percent of the counties and 37 percent of the population with levels above the

NAAQS in the areas with monitors that met completeness criteria. An additional 32 million

people live in 91 counties that have air quality measurements within 10 percent of the level of

the standard. These areas, though not currently violating the standard, will also benefit from the

additional reductions from this rule in order to ensure long-term maintenance. There are another

204 counties where 21 million people live that had incomplete data.

Figure 2.1.2-1 is a map of currently available PM2.5 monitoring data, highlighting monitor

locations near or above the annual PM2.5 NAAQS. As can be seen from this figure, high ambient

levels are widespread throughout the East and California.
Air Quality, Health, and Welfare Effects

2-19

 Counties with at least 1 complete site w/ DV > 15.0 (violate the NAAQS) [120]

 Counties with at least 1 complete site w/ DV > 13.5 and < 15.0 (within 10% of the NAAQS) [91]

 Counties with at least 1 complete site w/ DV < 13.5 [313]

 Counties without a complete site [204]

PM2.5 County Design Values, 2000-2002 

Data from AQS 7/9/03

Figure 2.1.2-1
Final Regulatory Impact Analysis

2-20

Further insights into the need for reductions from this rule can be gained by evaluating

counties at various levels above the level of the NAAQS. As shown in Table 2.1.1-3 of the 64.9

million people currently living in counties with measurements above the NAAQS, 18.8 million

live in counties above 20 :g/m3

. In Section 2.1.2.2, we discuss that absent additional controls,

our modeling predicts there will continue to be large numbers of people living in counties with

PM levels above the standard.

Table 2.1.1-3

2000-2002 Monitored Populationa

 Living in Counties with Annual Averageb PM2.5

Concentrations Shown 

Measured 2000-2002

Annual Average PM2.5

Concentration

(:g/m3)

Number of Counties

Within The

Concentration

Range

2000 Population Living in

Monitored Counties

Within The Concentration

Range (Millions, 2000

Census Data)

>25 2 3.3

>20 <=25 6 15.5

>15 <=20 112 46.1

<=15 404 110.9

a

 Monitored population estimates represent populations living in counties with monitors producing data that meet the

NAAQS data completeness requirements for 2000 - 2002. This analysis excludes the 204 counties whose

monitoring data do not meet the completeness criteria. b

 Annual average represents the monitor reading with the highest average in each monitored county. c

 The monitored population is 175.7 million (or 62 percent of the U.S. Census total county-based 2000 population for the

U.S. of 281.4 million).

Chemical composition of ambient PM2.5 also underscores the contribution of emissions from

the engines subject to this rule and points to the need for reductions. Data on PM2.5 composition

are available from the EPA Speciation Trends Network and the IMPROVE Network for

September 2001 to August 2002 covering both urban and rural areas in numerous regions of the

United States. The relative contribution of various chemical components to PM2.5 varies by

region of the country. Figure 2.1.2-2 shows the levels and composition of ambient PM2.5 in some

urban areas. Figure 2.1.2-3 shows the levels and composition of PM2.5 in rural areas where the

total PM2.5 levels are generally lower. These data show that carbonaceous PM2.5 makes up the

major component for PM2.5 in both urban and rural areas in the Western United States. 

Carbonaceous PM2.5 includes both elemental and organic carbon. Nonroad engines, especially

nonroad diesel engines, contribute significantly to ambient PM2.5 levels, largely through

emissions of carbonaceous PM2.5. For the Eastern and middle United States, these data show that

carbonaceous PM2.5 is a major contributor to ambient PM2.5 both urban and rural areas. In some

eastern areas, carbonaceous PM2.5 is responsible for up to half of ambient PM2.5 concentrations. 
Sulfate

AmmoniumNitrateTCMCrustal

6.20 18.69 31.18

Figure 2.1.2-2

Annual Average PM2.5 Species and Concentrations in Selected 

 (September 2001- August 2002)
Sulfate

AmmoniumNitrateTCMCrustal

1.71 7.91 14.11

Figure 2.1.2-3

Annual Average PM2.5 Concentration and Species in Rural Areas

(September 2001 - August 2002) 
Air Quality, Health, and Welfare Effects

2-23

Another important component of PM in the West is nitrates, which are formed from NOx. 

Nitrates are especially prominent in the California area where it is responsible for about a quarter

of the ambient PM2.5 concentrations. Nonroad diesel engines also emit high levels of NOx,

which reacts in the atmosphere to form secondary PM2.5 (namely ammonium nitrate). Sulfate

plays a lesser role in these western regions by mass, but it remains important to visibility

impairment discussed below. Nonroad diesel engines also emit SO2 and HC, which react in the

atmosphere to form secondary PM2.5 (namely sulfates and organic carbonaceous PM2.5). Sulfate

is also a major contributor to ambient PM2.5 in the Eastern United States and in some areas make

greater contributions than carbonaceous PM2.5. 

From Figures 2.1.2-2 and 2.1.2-3, one can compare the levels and composition of PM2.5 in

various urban areas and a corresponding rural area. This comparison, in Figure 2.1.2-4, shows

that much of the excess PM2.5 in urban areas (annual average concentration at urban monitor

minus annual average concentration at corresponding rural monitor) is indeed from

carbonaceous PM.91, 92 See the AQ TSD for details.

The ambient PM monitoring networks account for both directly emitted PM as well as

secondarily formed PM. Emission inventories, which account for directly emitted PM and PM

precursors separately, also show that mobile source PM emissions, including that from nonroad

diesel engines, is a major contributor to total PM emissions. Nationally, this final rule will

significantly reduce emissions of carbonaceous PM. NOx emissions, a prerequisite for

formation of secondary nitrate aerosols, will also be reduced. Nonroad diesel engines are major

contributors to both of these pollutants. The new requirements in this rule will also reduce SOx

and HC. Nonroad diesel engines emissions also contribute to national SOx and HC emission

inventories, but to a lesser degree than for PM and NOx. The emission inventories are

discussed in detail in Chapter 3.

As discussed in Sections 2.2.2.6 and 2.1, diesel PM also contains small quantities of

numerous mutagenic and carcinogenic compounds associated with the particles (and also organic

gases). In addition, while toxic trace metals emitted by nonroad diesel engines represent a very

small portion of the national emissions of metals (less than one percent) and a small portion of

diesel PM (generally less than one percent of diesel PM), we note that several trace metals of

potential toxicological significance and persistence in the environment are emitted by diesel

engines. These trace metals include chromium, manganese, mercury and nickel. In addition,

small amounts of dioxins have been measured in highway engine diesel exhaust, some of which

may partition into the particulate phase; dioxins are a major health concern but diesel engines are

a minor contributor to overall dioxin emissions. Diesel engines also emit polycyclic organic

matter (POM), including polycyclic aromatic hydrocarbons (PAH), which can be present in both

gas and particle phases of diesel exhaust. Many PAH compounds are classified by EPA as

probable human carcinogens.
Fresno

Reno

Salt Lake City

St. Louis

Tulsa

Birmingham

Atlanta

Indianapolis

Cleveland

Charlot

Sulfate:

0.00 0.55 1.10

Est. Ammonium:

0.12 1.15 2.18

Nitrate:

0.37 3.63 6.88

TCM:

2.14 6.00 9.85

Crustal:

0.00 0.41 0.82

Figure 2.1.2-4

Composition of Urban Excess PM2.5 at Selected Sites (September 2001 - August 2002

(Source: U.S. EPA (2004) AQ TSD; Rao and Frank (2003))
Air Quality, Health, and Welfare Effects

C Given the potential impact of the final rule on secondarily formed particles it is important to employ a

Eulerian model such as REMSAD. The impact of secondarily formed pollutants typically involves primary

precursor emissions from a multitude of widely dispersed sources, and chemical and physical processes of pollutants

that are best addressed using an air quality model that employs an Eulerian grid model design. Thus, comments from

industry that EPA’s methodology form computing benefits over time is based on unsupportable assumptions such as

that there will be no interactions between precursors and directly emitted PM in the formation of secondary PM and

that EPA excludes consideration of non-linearities in its air quality modeling are incorrect. This air quality modeling

for 2020 and 2030 does incorporate the nonlinear interactions between NOx, SO2, and direct PM. 

2-25

2.1.2.2 Risk of Future Violations

2.1.2.2.1 PM Air Quality Modeling and Methods

In conjunction with this rulemaking, we performed a series of PM air quality modeling

simulations for the continental U.S. The model simulations were performed for five emission

scenarios: a 1996 baseline projection, a 2020 baseline projection and a 2020 projection with

nonroad controls, a 2030 baseline projection and a 2030 projection with nonroad controls. 

Further discussion of this modeling, including evaluations of model performance relative to

predicted future air quality, is provided in the AQ Modeling TSD.

The model outputs from the 1996, 2020 and 2030 baselines, combined with current air

quality data, were used to identify areas expected to exceed the PM2.5 NAAQS in 2020 and 2030. 

These areas became candidates for being determined to be residual exceedance areas that will

require additional emission reductions to attain and maintain the PM2.5 NAAQS. The impacts of

the nonroad controls were determined by comparing the model results in the future year control

runs against the baseline simulations of the same year. We note that there are significant SO2

benefits from sulfur reductions in home heating oil fuel that are not accounted for in our

modeling. This modeling supports the conclusion that there is a broad set of areas with predicted

PM2.5 concentrations at or above 15 :g/m3 between 1996 and 2030 in the baseline scenarios

without additional emission reductions.

The air quality modeling performed for this rule was based upon an improved version of the

modeling system used in the HD Engine/Diesel Fuel rule (to address peer-review comments)

with the addition of updated inventory estimates for 1996, 2020 and 2030. 

A national-scale version of the REgional Model System for Aerosols and Deposition

(REMSAD) was utilized to estimate base and future-year PM concentrations over the contiguous

United States for the various emission scenarios. Version 7 of REMSAD was used for this

rulemaking. REMSAD was designed to calculate the concentrations of both inert and

chemically reactive pollutants in the atmosphere that affect annual particulate concentrations and

deposition over large spatial scales.C Because it accounts for spatial and temporal variations as

well as differences in the reactivity of emissions, REMSAD is useful for evaluating the impacts

of the final rule on PM concentrations in the United States. The following sections provide an

overview of the PM modeling completed as part of this rulemaking. More detailed information

is included in the AQ Modeling TSD, which is located in the docket for this rule.
Final Regulatory Impact Analysis

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The PM air quality analyses employed the modeling domain used previously in support of

Clear Skies air quality assessment. The domain encompasses the lower 48 States and extends

from 126 degrees to 66 degrees west longitude and from 24 degrees to 52 degrees north latitude. 

The model contains horizontal grid-cells across the model domain of roughly 36 km by 36 km. 

There are 12 vertical layers of atmospheric conditions with the top of the modeling domain at

16,200 meters. 

The simulation periods modeled by REMSAD included separate full-year application for

each of the five emission scenarios (1996 base year, 2020 base, 2020 control, 2030 baseline,

2030 control) using the 1996 meteorological inputs described below. 

The meteorological data required for input into REMSAD (wind, temperature, surface

pressure, etc.) were obtained from a previously developed 1996 annual run of the FifthGeneration National Center for Atmospheric Research (NCAR) / Penn State Mesoscale Model

(MM5). A postprocessor called MM5- REMSAD was developed to convert the MM5 data into

the appropriate REMSAD grid coordinate systems and file formats. This postprocessor was used

to develop the hourly average meteorological input files from the MM5 output. Documentation

of the MM5REMSAD code and further details on the development of the input files is contained

in Mansell (2000).93 A more detailed description of the development of the meteorological input

data is provided in the AQ Modeling TSD, which is located in the docket for this rule.

The modeling specified initial species concentrations and lateral boundary conditions to

approximate background concentrations of the species; for the lateral boundaries the

concentrations varied (decreased parabolically) with height. These initial conditions reflect

relatively clean background concentration values. Terrain elevations and land use information

was obtained from the U.S. Geological Survey database at 10 km resolution and aggregated to

the roughly 36 km horizontal resolution used for this REMSAD application. The development

of model inputs is discussed in greater detail in the AQ Modeling TSD, which is available in the

docket for this rule.

2.1.2.2.2 Model Performance Evaluation

The purpose of the base year PM air quality modeling was to reproduce the atmospheric

processes resulting in formation and dispersion of fine particulate matter across the United

States. An operational model performance evaluation for PM2.5 and its related speciated

components (e.g., sulfate, nitrate, elemental carbon etc.) for 1996 was performed in order to

estimate the ability of the modeling system to replicate base year concentrations. 

This evaluation is comprised principally of statistical assessments of model versus observed

pairs. The robustness of any evaluation is directly proportional to the amount and quality of the

ambient data available for comparison. Unfortunately, for 1996 there were few PM2.5 monitoring

networks with available data for evaluation of the Nonroad PM modeling. Critical limitations of

the existing databases are a lack of urban monitoring sites with speciated measurements and poor

geographic representation of ambient concentration in the Eastern United States.
Air Quality, Health, and Welfare Effects

2-27

The largest available ambient database for 1996 comes from the IMPROVE network. 

IMPROVE is a cooperative visibility monitoring effort between EPA, federal land management

agencies, and state air agencies. Data are collected at Class I areas across the United States

mostly at national parks, national wilderness areas, and other protected pristine areas.94 There

were approximately 60 IMPROVE sites that had complete annual PM2.5 mass and/or PM2.5

species data for 1996. Using the 100th meridian to divide the Eastern and Western United States,

42 sites were located in the West and 18 sites were in the East.

The observed IMPROVE data used for the performance evaluation consisted of PM2.5 total

mass, sulfate ion, nitrate ion, elemental carbon, organic aerosols, and crustal material (soils). 

The REMSAD model output species were postprocessed in order to achieve compatibility with

the observation species. 

The principal evaluation statistic used to evaluate REMSAD performance is the “ratio of the

means.” It is defined as the ratio of the average predicted values over the average observed

values. The annual average ratio of the means was calculated for five individual PM2.5 species as

well as for total PM2.5 mass. The metrics were calculated for all IMPROVE sites across the

country as well as for the East and West individually. Table 2.1.2-1 shows the ratio of the

annual means. Numbers greater than 1 indicate overpredictions compared with ambient

observations (e.g. 1.23 is a 23 percent overprediction). Numbers less than 1 indicate

underpredictions. 

Table 2.1.2-1

Model Performance Statistics for REMSAD PM2.5 Species Predictions: 1996 Base Case

IMPROVE PM Species

Ratio of the Means (annual average concentrations)

Nationwide Eastern U.S. Western U.S.

PM2.5, total mass 0.68 0.85 0.51

Sulfate ion 0.81 0.9 0.61

Nitrate ion 1.05 1.82 0.45

Elemental carbon 1.01 1.23 0.8

Organic aerosols 0.55 0.58 0.53

Soil/Other 1.38 2.25 0.88

Note: The dividing line between the West and East was defined as the 100th meridian.

When considering annual average statistics (e.g., predicted versus observed), which are

computed and aggregated over all sites and all days, REMSAD underpredicts fine particulate

mass (PM2.5) by roughly 30 percent. PM2.5 in the Eastern United States is slightly

underpredicted, while PM2.5 in the West is underpredicted by about 50 percent. Eastern sulfate is

slightly underpredicted, elemental carbon is slightly overpredicted, while nitrate and crustal are
Final Regulatory Impact Analysis

2-28

largely overpredicted. This is balanced by an underprediction in organic aerosols. Overall the

PM2.5 performance in the East is relatively unbiased due to the dominance of sulfate in the

observations. Western predictions of sulfate, nitrate, elemental carbon, and organic aerosols are

all underpredicted. 

REMSAD performance is relatively good in the East. The model is overpredicting nitrate,

but less so than in previous model applications. The overpredictions in soil/other concentrations

in the East can largely be attributed to overestimates of fugitive dust emissions. The model is

performing well for sulfate, which is the dominant PM2.5 species in most of the East. Organic

aerosols are underpredicted in both the East and West. There is a large uncertainty in the current

primary organic inventory as well as the modeled production of secondary organic aerosols. 

REMSAD is underpredicting all species in the West. The dominant species in the West is

organic aerosols. Secondary formation of sulfate, nitrate, and organics appears to be

underestimated in the West. Additionally, the current modeling inventory does not contain

wildfires, which may be a significant source of primary organic carbon in the West.

It should be noted that PM2.5 modeling is an evolving science. There have been few regional

or national scale model applications for primary and secondary PM. Unlike ozone modeling,

there is essentially no database of past performance statistics against which to measure the

performance of this modeling. Given the state of the science relative to PM modeling, it is

inappropriate to judge PM model performance using criteria derived for other pollutants, like

ozone. Still, the performance of this air quality modeling is encouraging, especially considering

that the results are limited by our current knowledge of PM science and chemistry, and by the

emission inventories for primary PM and secondary PM precursor pollutants. EPA and others

are only beginning to understand the limitations and uncertainties in the current inventories and

modeling tools. Improvements to the tools are being made on a continuing basis.

2.1.2.2.3 Results with Areas at Risk of Future PM2.5 Violations

Our air quality modeling performed for this rulemaking also indicates that the present

widespread number of counties with annual averages above 15 :g/m3

 are likely to persist in the

future in the absence of additional controls. For example, in 2020 based on emission controls

currently adopted or expected to be in place, we project that 66 million people will live in 79

counties with average PM2.5 levels at and above 15 :g/m3

. In 2030, the number of people

projected to live in areas exceeding the PM2.5 standard is expected to increase to 85 million in

107 counties. An additional 24 million people are projected to live in counties with annual

averages within 10 percent of the standard in 2020, and 17 million people are projected to live in

counties with annual averages within 10 percent of the standard in 2030. The AQ Modeling

TSD lists the specifics.

Our modeling also indicates that the reductions from this final rule will make a substantial
Air Quality, Health, and Welfare Effects

DThe results illustrate the type of PM changes for the preliminary control option, as discussed in Section 3.6. 

The analysis differs from the modeled control case based on public comment and updated information; however, we

believe that the net results would approximate future emissions, though we anticipate the PM reductions might be

smaller. We also note that our modeling does not account for substantial reductions in SO2 associated with sulfur

reductions in home heating oil.

2-29

contribution to reducing these potential exposures.D In 2020, we estimate that the number of

people living in counties with PM2.5 levels above the NAAQS will be reduced from 66 million to

60 million living in 67 counties. That is a reduction of 9 percent in potentially exposed

population and 15 percent of the number of counties. In 2030, there will be an estimated

reduction from 85 million people to 71 million living in 84 counties. This represents an even

greater improvement than projected for 2020 because of the fleet turnover and corresponds to a

16 percent reduction in potentially exposed population and a 21 percent of the number of

counties. Furthermore, our modeling also shows that the emission reductions will assist areas

with future maintenance of the standards. 

Table 2.1.2-2 lists the counties with 2020 and 2030 projected annual PM2.5 design values that

violate the annual standard. Counties are marked with an “V” in the table if their projected

design values are greater than or equal to 15.05 :g/m3. The current 3-year average design values

of these counties are also listed. Recall that we project future design values only for counties

that have current design values, so this list is limited to those counties with 1999-2001 ambient

monitoring data sufficient to calculate current 3-year design values.
Final Regulatory Impact Analysis

2-30

Table 2.1.2-2

Counties with 2020 and 2030 Projected Annual PM2.5 

Design Values in Violation of the Annual PM2.5 Standard.a, b

State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000

Base Controla Base Controla

AL De Kalb 16.8 V V 64,452

AL Houston 16.3 V V V 88,787

AL Jefferson 21.6 V V V V 662,047

AL Mobile 15.3 V V 399,843

AL Montgomery 16.8 V V V V 223,510

AL Morgan 19.1 V V V V 111,064

AL Russell 18.4 V V V V 49,756

AL Shelby 17.2 V V V V 143,293

AL Talladega 17.8 V V V V 80,321

CA Fresno 24 V V V V 799,407

CA Imperial 15.7 V 142,361

CA Kern 23.7 V V V V 661,645

CA Los Angeles 25.9 V V V V 9,519,338

CA Merced 18.9 V V V V 210,554

CA Orange 22.4 V V V V 2,846,289

CA Riverside 29.8 V V V V 1,545,387

CA San Bernardino 25.8 V V V V 1,709,434

CA San Diego 17.1 V V V V 2,813,833

CA San Joaquin 16.4 V 563,598

CA Stanislaus 19.7 V V V V 446,997

CA Tulare 24.7 V V V V 368,021

CT New Haven 16.8 V V V V 824,008

DE New Castle 16.6 V V V V 500,265

DC Washington 16.6 V V V V 572,059

GA Bibb 17.6 V V V V 153,887

GA Chatham 16.5 V V V V 232,048

GA Clarke 18.6 V V V V 101,489

GA Clayton 19.2 V V V V 236,517

GA Cobb 18.6 V V V V 607,751

GA De Kalb 19.6 V V V V 665,865

GA Dougherty 16.6 V V V V 96,065

GA Floyd 18.5 V V V V 90,565

GA Fulton 21.2 V V V V 816,006

GA Hall 17.2 V V V 139,277

GA Muscogee 18 V V V V 186,291

GA Paulding 16.8 V V V V 81,678

GA Richmond 17.4 V V V V 199,775
State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000

Base Controla Base Controla

GA Washington 16.5 V V V V 21,176

GA Wilkinson 18.1 V V V V 10,220

IL Cook 18.8 V V V V 5,376,741

IL Du Page 15.4 V 904,161

IL Madison 17.3 V V V V 258,941

IL St Clair 17.4 V V V V 256,082

IL Will 15.9 V V V 502,266

IN Clark 17.3 V V V V 96,472

IN Lake 16.3 V V V V 484,564

IN Marion 17 V V V 860,454

IN Vanderburgh 16.9 V 171,922

KY Jefferson 17.1 V V V V 693,604

KY Kenton 15.9 V 151,464

LA East Baton Rouge 14.6 V V 412,852

LA West Baton Rouge 14.1 V 21,601

MD Baltimore 16 V 754,292

MD Prince Georges 17.3 V V V V 801,515

MD Baltimore City 17.8 V V V V 651,154

MA Suffolk 16.1 V V 689,807

MI Wayne 18.9 V V V V 2,061,162

MS Jones 16.6 V V V 64,958

MO St Louis City 16.3 V V V 348,189

MT Lincoln 16.4 V V V V 18,837

NJ Hudson 17.5 V V V V 608,975

NJ Union 16.3 V V 522,541

NY Bronx 16.4 V V V 1,332,650

NY New York 17.8 V V V V 1,537,195

NC Catawba 17.1 V V V 141,685

NC Davidson 17.3 V V V V 147,246

NC Durham 15.3 V 223,314

NC Forsyth 16.2 V V 306,067

NC Gaston 15.3 V 190,365

NC Guilford 16.3 V V V 421,048

NC McDowell 16.2 V 42,151

NC Mecklenburg 16.8 V V V V 695,454

NC Wake 15.3 V 627,846

OH Butler 17.4 V V V 332,807

OH Cuyahoga 20.3 V V V V 1,393,978

OH Franklin 18.1 V V V V 1,068,978

OH Hamilton 19.3 V V V V 845,303

OH Jefferson 18.9 V V V V 73,894

OH Lawrence 17.4 V V V V 62,319

OH Lucas 16.7 V V V V 455,054
State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000

Base Controla Base Controla

OH Mahoning 16.4 V 257,555

OH Montgomery 17.6 V V V V 559,062

OH Scioto 20 V V V V 79,195

OH Stark 18.3 V V V V 378,098

OH Summit 17.3 V V V V 542,899

OH Trumbull 16.2 V 225,116

PA Allegheny 21 V V V V 1,281,666

PA Delaware 15 V 550,864

PA Philadelphia 16.6 V V V V 1,517,550

PA York 16.3 V 381,751

SC Greenville 17 V V V V 379,616

SC Lexington 15.6 V 216,014

TN Davidson 17 V V 569,891

TN Hamilton 18.9 V V V V 307,896

TN Knox 20.4 V V V V 382,032

TN Shelby 15.6 V 897,472

TN Sullivan 17 V 153,048

TX Dallas 14.4 V 2,218,899

TX Harris 15.1 V V V V 3,400,578

UT Salt Lake 13.6 V 898,387

VA Richmond City 14.9 V 197,790

WV Brooke 17.4 V V V V 25,447

WV Cabell 17.8 V V V V 96,784

WV Hancock 17.4 V V V V 32,667

WV Kanawha 18.4 V V V V 200,073

WV Wood 17.6 V V V 87,986

WI Milwaukee 14.5 V 940,164

Number of Violating Counties b 79 67 107 84

Population of Violating Countiesc 65,821,000 60,453,500 85,525,600 71,375,600

a

 As described in Chapter 3, the final control case differs from the modeled control case based on public comment and

updated information; however, we believe that the net results would approximate future emissions, although we

anticipate the design value improvements would be smaller. In our modeling, we do not account for SO2 reductions

related to sulfur reductions in home heating oil. b

 Projections are made only for counties with monitored design values for 1999-2001. These were the most current data

at the time the analyses were performed. Counties with insufficient data or lacking monitors are excluded. c

 Populations are based on 2020 and 2030 estimates rounded to nearest hundred. See the AQ Modeling TSD for details.
Air Quality, Health, and Welfare Effects

2-33

Table 2.1.2-3 lists the counties with 2020 or 2030 projected annual PM2.5 design values that

do not violate the annual standard, but are within 10 percent of it. Counties are marked with an

“X” in the table if their projected design values are greater than or equal to13.55 :g/m3, but less

than 15.05 :g/m3

. Counties are marked with an “V” in the table if their projected design values

are greater than or equal to 15.05 :g/m3

. The 1999-2001 design values of these counties are also

listed. These are counties that are not projected to violate the standard, but to be close to it, so

the final rule will help ensure that these counties continue to meet the standard in either the base

or control case for at least one of the years analyzed.
Final Regulatory Impact Analysis

2-34

Table 2.1.2-3

Counties with 2020 and 2030 Projected Annual PM2.5 Design Values 

within Ten Percent of the Annual PM2.5 Standard.a, b

State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000 Base Controla Base Controla

AL Alabama 15.5 X X X X 14,254

AL De Kalb 16.8 X X V V 64,452

AL Houston 16.3 V X V V 88,787

AL Madison 15.5 X 276,700

AL Mobile 15.3 X X V V 399,843

AR Crittenden 15.3 X X X X 50,866

AR Pulaski 15.9 X X X X 361,474

CA Butte 15.4 X X 203,171

CA Imperial 15.7 X X V X 142,361

CA Kings 16.6 X X X 129,461

CA San Joaquin 16.4 X X V X 563,598

CA Ventura 14.5 X X X X 753,197

CT Fairfield 13.6 X 882,567

DE Sussex 14.5 X 156,638

GA Hall 17.2 V X V V 139,277

IL Du Page 15.4 X X V X 904,161

IL Macon 15.4 X X X X 114,706

IL Will 15.9 V X V V 502,266

IN Elkhart 15.1 X X X 182,791

IN Floyd 15.6 X X X X 70,823

IN Howard 15.4 X X X 84,964

IN Marion 17 V X V V 860,454

IN Porter 13.9 X 146,798

IN Tippecanoe 15.4 X X X 148,955

IN Vanderburgh 16.9 X X V X 171,922

KY Bell 16.8 X X X X 30,060

KY Boyd 15.5 X X X X 49,752

KY Bullitt 16 X 61,236

KY Campbell 15.5 X X X 88,616

KY Daviess 15.8 X X X 91,545

KY Fayette 16.8 X X X X 260,512

KY Kenton 15.9 X X V X 151,464

KY Pike 16.1 X X X X 68,736

LA Caddo 13.7 X X 252,161

LA Calcasieu 12.7 X 183,577

LA East Baton Rouge 14.6 X X V V 412,852

LA Iberville 13.9 X X X 33,320
State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000 Base Controla Base Controla

LA Jefferson 13.6 X X 455,466

LA Orleans 14.1 X X X 484,674

LA West Baton Rouge 14.1 X X V X 21,601

MD Baltimore 16 X X V X 754,292

MA Hampden 14.1 X 456,228

MA Suffolk 16.1 V X V X 689,807

MI Kalamazoo 15 X X X 238,603

MS Forrest 15.2 X X X X 72,604

MS Hinds 15.1 X X X 250,800

MS Jackson 13.8 X X 131,420

MS Jones 16.6 V X V V 64,958

MS Lauderdale 15.3 X X X X 78,161

MO Jackson 13.9 X 654,880

MO Jefferson 15 X X X X 198,099

MO St Charles 14.6 X X X 283,883

MO St Louis 14.1 X 1,016,315

MO St Louis City 16.3 V X V V 348,189

NJ Mercer 14.3 X X X 350,761

NJ Union 16.3 X X V V 522,541

NY Bronx 16.4 V X V V 1,332,650

NC Alamance 15.3 X X X X 130,800

NC Cabarrus 15.7 X X X X 131,063

NC Catawba 17.1 V X V V 141,685

NC Cumberland 15.4 X X X 302,963

NC Durham 15.3 X X V X 223,314

NC Forsyth 16.2 X X V V 306,067

NC Gaston 15.3 X X V X 190,365

NC Guilford 16.3 V X V V 421,048

NC Haywood 15.4 X X X 54,033

NC McDowell 16.2 X X V X 42,151

NC Mitchell 15.5 X X X 15,687

NC Orange 14.3 X 118,227

NC Wake 15.3 X X V X 627,846

NC Wayne 15.3 X 113,329

OH Butler 17.4 V X V V 332,807

OH Lorain 15.1 X X X 284,664

OH Mahoning 16.4 X X V X 257,555

OH Portage 15.3 X X X X 152,061

OH Trumbull 16.2 X X V X 225,116

PA Berks 15.6 X X X X 373,638

PA Cambria 15.3 X 152,598

PA Dauphin 15.5 X X X 251,798

PA Delaware 15 X X V X 550,864
State County

1999 - 2001

Design Value

(ug/m3

)

b

2020 2030 Population

in 2000 Base Controla Base Controla

PA Lancaster 16.9 X X X X 470,658

PA Washington 15.5 X 202,897

PA York 16.3 X X V X 381,751

SC Georgetown 13.9 X 55,797

SC Lexington 15.6 X X V X 216,014

SC Richland 15.4 X X X X 320,677

SC Spartanburg 15.4 X X X X 253,791

TN Davidson 17 X X V V 569,891

TN Roane 17 X X X X 51,910

TN Shelby 15.6 X X V X 897,472

TN Sullivan 17 X X V X 153,048

TN Sumner 15.7 X X X 130,449

TX Dallas 14.4 X X V X 2,218,899

UT Salt Lake 13.6 X V X 898,387

VA Bristol City 16 X X 17,367

VA Richmond City 14.9 X X V X 197,790

VA Roanoke City 15.2 X 94,911

VA Virginia Beach Cit 13.2 X 425,257

WV Berkeley 16 X X X X 75,905

WV Marshall 16.5 X X X X 35,519

WV Ohio 15.7 X X X 47,427

WV Wood 17.6 V X V V 87,986

WI Milwaukee 14.5 X X V X 940,164

WI Waukesha 14.1 X 360,767

Number of Counties within 10%b 70 62 64 70

Population of Counties within 10%c 23,836,400 24,151,800 16,870,300 24,839,600

a

 As described in Chapter 3, the final control case differs from the modeled control case based on public comment and

updated information; however, we believe that the net results would approximate future emissions, although we

anticipate the design value improvements would be smaller. In our modeling, we do not account for SO2

reductions related to sulfur reductions in home heating oil. b

 Projections are made only for counties with monitored design values for 1999-2001. These were the most current data

at the time the analyses were performed. Counties with insufficient data or lacking monitors are excluded. c

 Populations are based on 2020 and 2030 estimates rounded to nearest hundred. See the AQ Modeling TSD for details.

We estimate that the reduction of this final rule will produce nationwide air quality

improvements in PM levels. On a population-weighted basis, the average change in future-year

annual averages is projected to decrease by 0.42 :g/m3 in 2020, and 0.59 :g/m3 in 2030.

While the final implementation process for bringing the nation’s air into attainment with the

PM2.5 NAAQS is still being completed in a separate rulemaking action, the basic framework is

well defined by the statute. EPA has requested that States and Tribes submit their

recommendations by February 15, 2004. EPA’s current plans call for designating PM2.5

attainement and nonattainment areas in December 2004. Following designation, Section 172(b)

of the Clean Air Act allows states up to 3 years to submit a revision to their state implementation
Air Quality, Health, and Welfare Effects

2-37

plan (SIP) that provides for the attainment of the PM2.5 standard. Based on this provision, states

could submit these SIPs in late-2007. Section 172(a)(2) of the Clean Air Act requires that these

SIP revisions demonstrate that the nonattainment areas will attain the PM2.5 standard as

expeditiously as practicable but no later than 5 years from the date that the area was designated

nonattainment. However, based on the severity of the air quality problem and the availability

and feasibility of control measures, the Administrator may extend the attainment date “for a

period of no greater than 10 years from the date of designation as nonattainment.” Based on

section 172(a) provisions in the Act, we expect that areas will need to attain the PM2.5 NAAQS

in the 2010 (based on 2007 - 2009 air quality data) to 2015 (based on 2012 to 2014 air quality

data) time frame, and then be required to maintain the NAAQS thereafter.

Since the emission reductions from this final rule will begin in this same time frame, the

projected reductions in nonroad emissions will be used by states in meeting the PM2.5 NAAQS. 

States and state organizations have told EPA that they need nonroad diesel engine reductions in

order to be able to meet and maintain the PM2.5 NAAQS as well as visibility regulations,

especially in light of the otherwise increasing emissions from nonroad sources without more

stringent standards.95, 96, 97 The following are sample comments from states and state

associations on the proposed rule, which corroborate that this rule is a critical element in States’

NAAQS attainment efforts. Fuller information can be found in the Summary and Analysis of

Comments.

- “Unless emissions from nonroad diesels are sharply reduced, it is very likely that many

areas of the country will be unable to attain and maintain health-based NAAQS for ozone

and PM.” (STAPPA/ALAPCO)

- “Adoption of the proposed regulation ... is necessary for the protection of public health in

California and to comply with air quality standards.” (California Air Resources Board)

- “The EPA’s proposed regulation is necessary if the West is to make reasonable progress

towards improving visibility in our nation’s Class I areas.” (Western Regional Air

Partnership (WRAP))

- “Attainment of the NAAQS for ozone and PM2.5 is of immediate concern to the states in the

northeast region....Thus, programs ... such as the proposed rule for nonroad diesel engines are

essential.” (NESCAUM)

Furthermore, this rule ensures that nonroad diesel emissions will continue to decrease as the

fleet turns over in the years beyond 2014; these reductions will be important for maintenance of

the NAAQS following attainment. The future reductions are also important to achieve visibility

goals, as discussed below.

2.1.3 Environmental Effects of Particulate Matter

In this section, we discuss public welfare effects of PM and its precursors including visibility

impairment, acid deposition, eutrophication and nitrification, POM deposition, materials

damage, and soiling. 
Final Regulatory Impact Analysis

E

Visual range can be defined as the maximum distance at which one can identify a black object against the

horizon sky. It is typically described in miles or kilometers. Light extinction is the sum of light scattering and

absorption by particles and gases in the atmosphere. It is typically expressed in terms of inverse megameters (Mm-1),

with larger values representing worse visibility. The deciview metric describes perceived visual changes in a linear

fashion over its entire range, analogous to the decibel scale for sound. A deciview of 0 represents pristine

conditions. The higher the deciview value, the worse the visibility, and an improvement in visibility is a decrease in

deciview value. 

2-38

2.1.3.1 Visibility Degradation

Visibility can be defined as the degree to which the atmosphere is transparent to visible

light.98 Visibility impairment has been considered the “best understood and most easily

measured effect of air pollution.”99 Fine particles are the major cause of reduced visibility in

parts of the United States. Haze obscures the clarity, color, texture, and form of what we see. 

Visibility is an important effect because it has direct significance to people’s enjoyment of daily

activities in all parts of the country. Visibility is also highly valued in significant natural areas

such as national parks and wilderness areas, because of the special emphasis given to protecting

these lands now and for future generations.

Scattering and absorption by both gases and particles decrease light transmittance. Size and

chemical composition of particles strongly affects their ability to scatter or absorb light. The

same particles (sulfates, nitrates, organic carbon, smoke, and soil dust) comprising PM2.5, which

are linked to serious health effects and environmental effects (e.g., ecosystem damage), can also

significantly degrade visual air quality. (For data on chemical composition of particles in slected

urban and rural areas, see Figures 2.1.2-2 and 2.1.2-3 above.) Sulfates contribute to visibility

impairment especially on the haziest days, accounting in the rural Eastern United States for more

than 60 percent of annual average light extinction on the best days and up to 86 percent of

average light extinction on the haziest days. Nitrates and elemental carbon each typically

contribute 1 to 6 percent of average light extinction on haziest days in rural locations in the

Eastern United States.100

 To quantify changes in visibility, the analysis presented in this chapter computes a lightextinction coefficient, based on the work of Sisler, which shows the total fraction of light that is

decreased per unit distance.101 This coefficient accounts for the scattering and absorption of light

by both particles and gases, and accounts for the higher extinction efficiency of fine particles

compared with coarse particles. Visibility can be described in terms of visual range, light

extinction or deciview.E Visibility impairment also has a temporal dimension in that impairment

might relate to a short-term excursion or to longer periods (e.g., worst 20 percent of days or

annual average levels). More detailed discussions of visibility effects are contained in the EPA

Criteria Document for PM.102

Visibility effects are manifest in two principal ways: (1) as local impairment (e.g., localized

hazes and plumes) and (2) as regional haze. The emissions from engines covered by this rule

contribute to both types of visibility impairment. 
Air Quality, Health, and Welfare Effects

2-39

Local-scale visibility degradation is commonly in the form of either a plume resulting from

the emissions of a specific source or small group of sources, or it is in the form of a localized

haze such as an urban “brown cloud.” Plumes are comprised of smoke, dust, or colored gas that

obscure the sky or horizon relatively near sources. Impairment caused by a specific source or

small group of sources has been generally termed as “reasonably attributable.”

The second type of impairment, regional haze, results from pollutant emissions from a

multitude of sources located across a broad geographic region. It impairs visibility in every

direction over a large area, in some cases over multi-state regions. Regional haze masks objects

on the horizon and reduces the color and contrast of nearby objects.103

On an annual average basis, the concentrations of non-anthropogenic fine PM are generally

small when compared with concentrations of fine particles from anthropogenic sources.104

Anthropogenic contributions account for about one-third of the average extinction coefficient in

the rural West and more than 80 percent in the rural East.105 In the Eastern United States,

reduced visibility is mainly attributable to secondarily formed particles, particularly those less

than a few micrometers in diameter (e.g., sulfates). While secondarily formed particles still

account for a significant amount in the West, primary emissions contribute a larger percentage of

the total particulate load than in the East. Because of significant differences related to visibility

conditions in the Eastern and Western United States, we present information about visibility by

region. Furthermore, it is important to note that even in those areas with relatively low

concentrations of anthropogenic fine particles, such as the Colorado plateau, small increases in

anthropogenic fine particle concentrations can lead to significant decreases in visual range. This

is one of the reasons mandatory Federal Class I areas have been given special consideration

under the Clean Air Act. The 156 mandatory Federal Class I areas are displayed on the map in

Figure 2-1 above.

EPA determined that emissions from nonroad engines significantly contribute to air pollution

that may be reasonably anticipated to endanger public health and welfare for visibility effects in

particular (67 FR 68242, November 8, 2002). The primary and PM-precursor emissions from

nonroad diesel engines subject to this rule contribute to these effects. To demonstrate this, in

addition to the inventory information in Chapter 3, we present information about both general

visibility impairment related to ambient PM levels across the country, and we also analyze

visibility conditions in mandatory Federal Class I areas. Accordingly, in this section, for both

the nation and for mandatory Federal Class I areas, we discuss the types of effects, current and

future visibility conditions absent the projected emission reductions, and the changes we

anticipate from the projected emission reductions. We conclude that the projected emission

reductions will improve visibility conditions across the country and in particular in mandatory

Federal Class I areas.

2.1.3.1.1 Visibility Impairment Where People Live, Work and Recreate

Good visibility is valued by people throughout the country - in the places they live, work,

and enjoy recreational activities. However, unacceptable visibility impairment occurs in many

areas throughout the country. In this section, in order to estimate the magnitude of the visibility
Final Regulatory Impact Analysis

2-40

problem, we use monitored PM2.5 data and modeled air quality accounting for projected

emissions from nonroad diesel engines absent additional controls. The air quality modeling is

discussed in Section 2.1.2 above and in the AQ Modeling TSD.106 The engines covered by this

rule contribute to PM2.5 levels in areas across the country with significant visibility impairment.

The secondary PM NAAQS is designed to protect against adverse welfare effects such as

visibility impairment. In 1997, the secondary PM NAAQS was set as equal to the primary

(health-based) PM NAAQS (62 Federal Register No. 138, July 18, 1997). EPA concluded that

PM can and does produce adverse effects on visibility in various locations, depending on PM

concentrations and factors such as chemical composition and average relative humidity. In

1997, EPA demonstrated that visibility impairment is an important effect on public welfare and

that visibility impairment is experienced throughout the United States, in multi-state regions,

urban areas, and remote Federal Class I areas. 

The updated monitored data and air quality modeling presented below confirm that the

visibility situation identified during the NAAQS review in 1997 is still likely to exist. 

Specifically, there will still likely be a broad number of areas that are above the annual PM2.5

NAAQS in the Northeast, Midwest, Southeast and California , such that the determination in the

NAAQS rulemaking about broad visibility impairment and related benefits from NAAQS

compliance are still relevant. Thus, levels above the fine PM NAAQS cause adverse welfare

impacts, such as visibility impairment (both regional and localized impairment). EPA recently

confirmed this in our determination about nonroad engines significant contribution to

unacceptable visibility impairment (67 FR 68251, November 8, 2002).

In addition, in setting the PM NAAQS, EPA acknowledged that levels of fine particles below

the NAAQS may also contribute to unacceptable visibility impairment and regional haze

problems in some areas, and Clean Air Act Section 169 provides additional authorities to remedy

existing impairment and prevent future impairment in the 156 national parks, forests and

wilderness areas labeled as mandatory Federal Class I areas (62 FR at 38680-81, July 18, 1997). 

In making determinations about the level of protection afforded by the secondary PM

NAAQS, EPA considered how the Section 169 regional haze program and the secondary

NAAQS would function together.107 Regional strategies, such as this rule, are expected to

improve visibility in many urban and non-Class I areas as well. Visibility impairment in

mandatory Federal Class I areas is discussed in Section 2.1.4. 

2.1.3.1.1.1 Current Areas Affected by Visibility Impairment: Monitored Data

The need for reductions in the levels of PM2.5 is widespread, as discussed above and shown

in Figure 2-1. Currently, high ambient PM2.5 levels are measured throughout the country. Fine

particles may remain suspended for days or weeks and travel hundreds to thousands of

kilometers, and thus fine particles emitted or created in one county may contribute to ambient

concentrations in a neighboring region.108

Without the effects of pollution, a natural visual range is approximately 120 to 180 miles
Air Quality, Health, and Welfare Effects

2-41

(200 to 300 kilometers) in the West and 45 to 90 miles (75 to 150 kilometers) in the East.109

However, over the years, in many parts of the United States, fine particles have significantly

reduced the range that people can see. In the West, the visibility range is 33 to 90 miles (53 to

144 kilometers), and in the East, the current range is only 14 to 24 miles (22 to 38 kilometers).110

Current PM2.5 monitored values for 2000-2002 indicate that almost 65 million people in 120

counties live in areas where design values of PM2.5 annual levels are at or above the PM2.5

NAAQS. This represents 23 percent of the counties and 37 percent of the population in the areas

with monitoring data that met completeness requirements and had levels above the NAAQS. 

Thus, at least these populations (plus others who travel to these areas) would likely be

experiencing visibility impairment that is unacceptable. Emissions of PM and its precursors

from nonroad diesel engines contribute to this unacceptable impairment. 

An additional 32 million people live in 91 counties that have air quality measurements for

2000-2002 within 10 percent of the level of the PM standard. These areas, though not currently

violating the standard, will also benefit from the additional reductions from this final rule to

ensure long-term maintenance of the standard and to prevent deterioration in visibility

conditions.

Although we present the annual average to represent national visibility conditions, visibility

impairment can also occur on certain days or other shorter periods. As discussed below, the

Regional Haze program targets the worst 20 percent of days in a year. The projected emission

reductions from this rule are also needed to improve visibility on the worst days.

2.1.3.1.1.2 Areas Affected by Future Visibility Impairment

Because the chemical composition of PM and other atmospheric conditions affect visibility

impairment, we used the REMSAD air quality model to project visibility conditions in 2020 and

2030 to estimate visibility impairment directly as changes in deciview. One of the inputs to the

PM modeling described above is a projection of future emissions from nonroad diesel engines

absent additional controls. Thus, we are able to demonstrate that the nonroad diesel emissions

contribute to the projected visibility impairment and that there continues to be a need for

reductions from those engines.

As described above, based on this modeling and absent additional controls, we predicted that

in 2020, there will be 79 counties with a population of 66 million where annual PM2.5 levels are

above 15 μg/m3.111 In 2030, this number will rise to 107 counties with a population of 85 million

in the absence of additional controls. Section 2.1.2 and the AQ Modeling TSD provides

additional details.

Based upon the light-extinction coefficient, we also calculated a unitless visibility index or

deciview. As shown in Table 2.1.3-1, in 2030 we estimate visibility in the East to be about

20.54 deciviews (or visual range of 50 kilometers) on average, with poorer visibility in urban

areas, compared with the visibility conditions without man-made pollution of 9.5 deciviews (or

visual range of 150 kilometers). Likewise, we estimate visibility in the West to be about 8.83
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deciviews (or visual range of 162 kilometers) in 2030, compared with the visibility conditions

without anthropogenic pollution of 5.3 deciviews (or visual range of 230 kilometers). Thus, in

the future, a substantial percent of the population may experience unacceptable visibility

impairment in areas where they live, work and recreate. 

Table 2.1.3-1

Summary of Future National (48 state) Baseline Visibility 

Conditions Absent Additional Controls (Deciviews)

Regionsa

Predicted 2020 

Visibility

(annual average)

Predicted 2030

Visibility

(annual average)

Natural Background

Visibility

Eastern U.S. 20.27 20.54 9.5

Urban 21.61 21.94

Rural 19.73 19.98

Western U.S. 8.69 8.83 5.3

Urban 9.55 9.78

Rural 8.5 8.61

a

 Eastern and Western Regions are separated by 100 degrees north longitude. Background visibility conditions

differ by region.

The emissions from nonroad diesel engines contribute to this visibility impairment as

discussed in Chapter 3. Nonroad diesel engines emissions contribute a large portion of the total

PM emissions from mobile sources and anthropogenic sources, in general. These emissions

occur in and around areas with PM levels above the annual PM2.5 NAAQS. The nonroad

engines subject to this rule contribute to these effects as well as localized visibility impairment. 

Thus, the emissions from these sources contribute to the unacceptable current and anticipated

visibility impairment.

2.1.3.1.1.3 Future Improvements in Visibility from the Projected Emission Reductions

For this rule, we also modeled a preliminary control scenario that illustrates the likely

emission reductions. As public comment and additional data regarding technical feasibility and

other factors became available, our judgment about the controls that are feasible has evolved. 

Thus, the preliminary control option differs from what we are proposing, as summarized in

Section 3.6. It is important to note that these changes would not affect our estimates of the

baseline conditions without additional controls described above. In our air quality modeling, we

did not account for SO2 reductions from reductions in sulfur levels in home heating oil. We

anticipate that the nonroad diesel emission reductions from this final rule together with other

strategies would improve the projected visibility impairment, and we conclude that there

continues to be a need for reductions from those engines. 
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Based on our modeling, we predict that in 2020, there will be 12 counties with a population

of 6 million that come into attainment with the annual PM2.5 because of the improvements in air

quality from the emission reductions resulting from this final rule. In 2030, an estimated total of

24 counties (12 additional counties) with a population of 14 million (8 million additional people)

will come into attainment with the annual PM2.5 because of the improvements in air quality from

this final rule. There will also be emission reductions in counties with levels close to the air

quality standards that will improve visibility conditions and help them maintain the standards. 

All of these areas and their populations will experience improvements in visibility as well as

health effects, as described earlier.

We estimate that the emission reductions resulting from this final rule will produce

nationwide air quality improvements in PM levels. On a population-weighted basis, the average

change in future-year annual averages will be a decrease of 0.33 :g/m3 in 2020, and 0.46 :g/m3

in 2030. These reductions are discussed in more detail in Section 2.1.2 above.

We can also calculate these improvement in visibility as decreases in deciview value. As

shown in Table 2.1.3-2, in 2030 we estimate visibility in the East to be about 20.54 deciviews (or

visual range of 50 kilometers) on average, with poorer visibility in urban areas. Emission

reductions from this final rule in 2030 will improve visibility by an estimated 0.33 deciviews. 

Likewise, we estimate visibility in the West to be about 8.83 deciviews (or visual range of 162

kilometers) in 2030, and we estimate that emission reductions from this final rule in 2030 will

improve visibility by 0.25 deciviews. These improvements are needed in conjunction with other

sulfur reduction strategies in the East and a combination of strategies in the West to make

reasonable progress toward visibility goals.112 Thus, this final rule is an important part of

strategies to improve visibility in areas where they live, work and recreate.
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Table 2.1.3-2

Summary of Future National Visibility Improvements 

from Nonroad Diesel Emission Reductions (Annual Average Deciviews)

Regionsa

2020 2030

Predicted Baseline

2020 Visibility

Predicted 2020

Control Visibilityb

Predicted Baseline

2030 Visibility

Predicted 2030

Control Visibilityb

Eastern U.S. 20.27 20.03 20.54 20.21

Urban 21.61 21.37 21.94 21.61

Rural 19.73 19.49 19.98 19.65

Western U.S. 8.69 8.51 8.83 8.58

Urban 9.55 9.3 9.78 9.43

Rural 8.5 8.33 8.61 8.38

a

 Eastern and Western Regions are separated by 100 degrees north longitude. Background visibility conditions differ by

region. b

 The results illustrate the type of visibility improvements for the preliminary control option, as discussed in Section 3.6. 

The analysis in Chapter 3 differs based on updated information; however, we believe that the net results would

approximate future PM emissions, although we anticipate the annual average visibility improvements would be

smaller.

2.1.3.1.2 Visibility Impairment in Mandatory Federal Class I Areas 

Achieving the annual PM2.5 NAAQS will help improve visibility across the country, but it

will not be sufficient to meet the statutory goal of no manmade impairment in the mandatory

Federal Class I areas (64 FR 35722, July 1, 1999 and 62 FR 38680, July 18, 1997). In setting the

NAAQS, EPA discussed how the NAAQS in combination with the regional haze program, is

deemed to improve visibility consistent with the goals of the Act.113 In the East, there are and

will continue to be sizable areas above 15 :g/m3

 and where light extinction is significantly above

natural background. Thus, large areas of the Eastern United States have air pollution that is

causing and will continue to cause unacceptable visibility problems. In the West, scenic vistas

are especially important to public welfare. Although the annual PM2.5 NAAQS is met in most

areas outside of California, virtually the entire West is in close proximity to a scenic mandatory

Federal Class I area protected by 169A and 169B of the Act.

The 156 Mandatory Federal Class I areas are displayed on the map in Figure 2-1 above. 

These areas include many of our best known and most treasured natural areas, such as the Grand

Canyon, Yosemite, Yellowstone, Mount Rainier, Shenandoah, the Great Smokies, Acadia, and

the Everglades. More than 280 million visitors come to enjoy the scenic vistas and unique

natural features including the night sky in these and other park and wilderness areas each year.
Air Quality, Health, and Welfare Effects

F Although a recent court case, American Corn Growers Association v. EPA, 291F.3d 1(D.C .Cir 2002), vacated

the Best Available Retrofit Technology (BART) provisions of the Regional Haze rule, the court denied industry’s

challenge to EPA’s requirement that state’s SIPS provide for reasonable progress towards achieving natural visibility

conditions in national parks and wilderness areas and the “no degradation” requirement. Industry did not challenge

requirements to improve visibility on the haziest 20 percent of days. The court recognized that mobile source

emission reductions would need to be a part of a long-term emission strategy for reducing regional haze. A copy of

this decision can be found in Docket A-2000-01, Document IV- A-113.

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In the 1990 Clean Air Act amendments, Congress provided additional emphasis on regional

haze issues (see section 169B). In 1999 EPA finalized a rule that calls for States to establish

goals and emission reduction strategies for improving visibility in all 156 mandatory Class I

national parks and wilderness areas. In this rule, EPA established a “natural visibility” goal.114

In that rule, EPA also encouraged the States to work together in developing and implementing

their air quality plans. The regional haze program is focused on long-term emissions decreases

from the entire regional emission inventory comprised of major and minor stationary sources,

area sources and mobile sources. The regional haze program is designed to improve visibility

and air quality in our most treasured natural areas so that these areas may be preserved and

enjoyed by current and future generations. At the same time, control strategies designed to

improve visibility in the national parks and wilderness areas will improve visibility over broad

geographic areas, including other recreational sites, our cities and residences. In the PM

NAAQS rulemaking, EPA also anticipated the need in addition to the NAAQS and Section 169

regional haze program to continue to address localized impairment that may relate to unique

circumstances in some Western areas. For mobile sources, there may also be a need for a

Federal role in reduction of those emissions, in particular, because mobile source engines are

regulated primarily at the Federal level.

The regional haze program calls for states to establish goals for improving visibility in

national parks and wilderness areas to improve visibility on the haziest 20 percent of days and to

ensure that no degradation occurs on the clearest 20 percent of days (64 FR 35722. July 1,

1999). The rule requires states to develop long-term strategies including enforceable measures

designed to meet reasonable progress goals toward natural visibility conditions. Under the

regional haze program, States can take credit for improvements in air quality achieved as a result

of other Clean Air Act programs, including national mobile-source programs.F

 

2.1.3.1.2.1 Current Mandatory Federal Class I Areas Affected by Visibility Impairment:

Monitored Data

Detailed information about current and historical visibility conditions in mandatory Federal

Class I areas is summarized in the EPA Report to Congress and the recent EPA Trends Report.115

The conclusions draw upon the Interagency Monitoring of Protected Visual Environments

(IMPROVE) network data.116 The National Park Service report also describes the state of

national park visibility conditions and discusses the need for improvement.117

As described in the EPA Trends Report 1999, most of the IMPROVE sites in the

intermountain West and Colorado Plateau have annual average impairment of 12 deciviews or
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less, with the worst days ranging up to 17 deciviews (compared with 5.3 deciviews of natural

background visibility).118 Several other western IMPROVE sites in the Northwest and California

experience levels on the order of 16 to 23 deciviews on the haziest 20 percent of days. Many

rural locations in the East have annual average values exceeding 21 deciviews, with average

visibility levels on the haziest days up to 32 deciviews.

Although there have been general trends toward improved visibility, progress is still needed

on the haziest days. Specifically, as discussed in the EPA Trends Report, in the 10 Class I areas

in the Eastern United States, visibility on the haziest 20 percent of days remains significantly

impaired with a mean visual range of 23 kilometers for 1999, as compared with 84 kilometers for

the clearest days in 1999. In the 26 Class I reported areas in the Western United States, the

conditions for the haziest 20 percent of days degraded between 1997 and 1999 by 17 percent. 

However, visibility on the haziest 20 percent of days in the West remains relatively unchanged

over the 1990s with the mean visual range for 1990 (80 kilometers) nearly the same as the 1990

level (86 kilometers).

2.1.3.1.2.2 Mandatory Federal Class I Areas Affected by Future Visibility Impairment

As part of the PM air quality modeling described above, we modeled future visibility

conditions in the mandatory Federal Class I areas absent additional controls. The results by

region are summarized in Table 2.1.3-3. In Figure 2.1.3-1, we define the regions used in this

analysis.119 These air quality results show that visibility is impaired in most mandatory Federal

Class I areas and additional reductions from engines subject to this rule are needed to achieve the

goals of the Clean Air Act of preserving natural conditions in mandatory Federal Class I areas.
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Table 2.1.3-3

Summary of Future Baseline Visibility Conditions in Mandatory Federal Class I

Areas Absent Additional Emission Reductions (Annual Average Deciview)

Class I Regions a

Predicted 2020 Visibility Predicted 2030 Visibility Natural Background

Visibility 

Eastern 19.72 20.01

9.5

Southeast 21.31 21.62

Northeast/Midwest 18.30 18.56

Western 8.80 8.96

5.3

Southwest 6.87 7.03

California 9.33 9.56

Rocky Mountain 8.46 8.55

Northwest 12.05 12.18

National Class I Area

Average 

11.61 11.80

a

 Regions are depicted in Figure 1-5.1. Background visibility conditions differ by region based on differences in relative

humidity and other factors: Eastern natural background is 9.5 deciviews (or visual range of 150 kilometers) and in

the West natural background is 5.3 deciviews (or visual range of 230 kilometers).
 Nor thwest

 



  

 Roc ky M ountain





  

  

 Northeast/Midwes t







 Southeast





  





Southwest

 

 California

Study RegionTransfer Region

Figure 2.1.3-1

Visibility Regions for the Continental United States

Note: Study regions were represented in the Chestnut and Rowe (1990a, 1990b) studies used in evaluating the benefits of visibility impr
Air Quality, Health, and Welfare Effects

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2.1.3.1.2.3 Future Improvements in Mandatory Federal Class I Visibility from the

Projected Emission Reductions

The overall goal of the regional haze program is to prevent future and remedy existing

visibility impairment in mandatory Federal Class I areas. As shown by the future deciview

estimates in Table 2.1.3-4, additional emission reductions will be needed from the broad set of

sources that contribute, including the emissions from engines subject to this rule. The table also

presents the results from our modeling of a preliminary control scenario that illustrates the likely

reductions from the final rule. Emission reductions from nonroad diesel engines are needed to

achieve the goals of the Act of preserving natural conditions in mandatory Federal Class I areas. 

These reductions are a part of the overall strategy to achieve the visibility goals of the Act and

the regional haze program.

Table 2.1.3-4

Summary of Future Visibility Improvementsb in Mandatory Federal Class I Areas

from Nonroad Diesel Emission Reductions (Annual Average Deciviews)

Mandatory Federal

Class I Regionsa

2020 2030

Predicted Baseline

2020 Average

Visibility

Predicted 2020

Control Average

Visibilityb

Predicted Baseline

2030 Average

Visibility

Predicted 2030

Control Average

Visibilityb

Eastern 19.72 19.54 20.01 19.77

Southeast 21.31 21.13 21.62 21.38

Northeast/Midwest 18.30 18.12 18.56 18.32

Western 8.80 8.62 8.96 8.72

Southwest 6.87 6.71 7.03 6.82

California 9.33 9.12 9.56 9.26

Rocky Mountain 8.46 8.31 8.55 8.34

Northwest 12.05 11.87 12.18 11.94

National Class I Area

Average

11.61 11.43 11.80 11.56

a

 Regions are presented in Figure 2.1.3-1 based on Chestnut and Rowe (1990a, 1990b) study regions. b

 The results illustrate the type of visibility improvements for the preliminary control option, as discussed in Section 3.6. 

The final control scenario described in Chapter 3 differs from the modeled scenario based on public comment and

updated information; however, we believe that the net results would approximate future PM emissions, although we

anticipate the annual average visibility improvements would be smaller.
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2.1.3.2 Other Effects

2.1.3.2.1 Acid Deposition

Acid deposition, or acid rain as it is commonly known, occurs when SO2 and NOx react in

the atmosphere with water, oxygen, and oxidants to form various acidic compounds that later fall

to earth in the form of precipitation or dry deposition of acidic particles.120 It contributes to

damage of trees at high elevations and in extreme cases may cause lakes and streams to become

so acidic that they cannot support aquatic life. In addition, acid deposition accelerates the decay

of building materials and paints, including irreplaceable buildings, statues, and sculptures that

are part of our nation's cultural heritage. To reduce damage to automotive paint caused by acid

rain and acidic dry deposition, some manufacturers use acid-resistant paints, at an average cost

of $5 per vehicle—a total of near $80 million per year when applied to all new cars and trucks

sold in the United States each year.

Acid deposition primarily affects bodies of water that rest atop soil with a limited ability to

neutralize acidic compounds. The National Surface Water Survey (NSWS) investigated the

effects of acidic deposition in over 1,000 lakes larger than 10 acres and in thousands of miles of

streams. It found that acid deposition was the primary cause of acidity in 75 percent of the

acidic lakes and about 50 percent of the acidic streams, and that the areas most sensitive to acid

rain were the Adirondacks, the mid-Appalachian highlands, the upper Midwest and the high

elevation West. The NSWS found that approximately 580 streams in the Mid-Atlantic Coastal

Plain are acidic primarily due to acidic deposition. Hundreds of the lakes in the Adirondacks

surveyed in the NSWS have acidity levels incompatible with the survival of sensitive fish

species. Many of the over 1,350 acidic streams in the Mid-Atlantic Highlands (mid-Appalachia)

region have already experienced trout losses due to increased stream acidity. Emissions from

U.S. sources contribute to acidic deposition in Eastern Canada, where the Canadian government

has estimated that 14,000 lakes are acidic. Acid deposition also has been implicated in

contributing to degradation of high-elevation spruce forests that populate the ridges of the

Appalachian Mountains from Maine to Georgia. This area includes national parks such as the

Shenandoah and Great Smoky Mountain National Parks.

A study of emission trends and acidity of water bodies in the Eastern United States by the

General Accounting Office (GAO) found that from 1992 to 1999 sulfates declined in 92 percent

of a representative sample of lakes, and nitrate levels increased in 48 percent of the lakes

sampled.121 The decrease in sulfates is consistent with emission trends, but the increase in

nitrates is inconsistent with the stable levels of nitrogen emissions and deposition. The study

suggests that the vegetation and land surrounding these lakes have lost some of their previous

capacity to use nitrogen, thus allowing more of the nitrogen to flow into the lakes and increase

their acidity. Recovery of acidified lakes is expected to take a number of years, even where soil

and vegetation have not been “nitrogen saturated,” as EPA called the phenomenon in a 1995

study.122 This situation places a premium on reductions of SOx and especially NOx from all

sources, including nonroad diesel engines, in order to reduce the extent and severity of nitrogen

saturation and acidification of lakes in the Adirondacks and throughout the United States. 
Air Quality, Health, and Welfare Effects

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The SOx and NOx reductions from this rule will help reduce acid rain and acid deposition,

thereby helping to reduce acidity levels in lakes and streams throughout the country and help

accelerate the recovery of acidified lakes and streams and the revival of ecosystems adversely

affected by acid deposition. Reduced acid deposition levels will also help reduce stress on

forests, thereby accelerating reforestation efforts and improving timber production. 

Deterioration of our historic buildings and monuments, and of buildings, vehicles, and other

structures exposed to acid rain and dry acid deposition also will be reduced, and the costs borne

to prevent acid-related damage may also decline. While the reduction in sulfur and nitrogen acid

deposition will be roughly proportional to the reduction in SOx and NOx emissions,

respectively, the precise impact of this rule will differ across different areas. 

2.1.3.2.2 Eutrophication and Nitrification

Eutrophication is the accelerated production of organic matter, particularly algae, in a water

body. This increased growth can cause numerous adverse ecological effects and economic

impacts, including nuisance algal blooms, dieback of underwater plants due to reduced light

penetration, and toxic plankton blooms. Algal and plankton blooms can also reduce the level of

dissolved oxygen, which can also adversely affect fish and shellfish populations. 

In 1999, the National Oceanic and Atmospheric Administration (NOAA) published the

results of a five year national assessment of the severity and extent of estuarine eutrophication. 

An estuary is defined as the inland arm of the sea that meets the mouth of a river. The 138

estuaries characterized in the study represent more than 90 percent of total estuarine water

surface area and the total number of U.S. estuaries. The study found that estuaries with moderate

to high eutrophication conditions represented 65 percent of the estuarine surface area. 

Eutrophication is of particular concern in coastal areas with poor or stratified circulation

patterns, such as the Chesapeake Bay, Long Island Sound, or the Gulf of Mexico. In such areas,

the "overproduced" algae tends to sink to the bottom and decay, using all or most of the available

oxygen and thereby reducing or eliminating populations of bottom-feeder fish and shellfish,

distorting the normal population balance between different aquatic organisms, and in extreme

cases causing dramatic fish kills. 

Severe and persistent eutrophication often directly impacts human activities. For example,

losses in the nation’s fishery resources may be directly caused by fish kills associated with low

dissolved oxygen and toxic blooms. Declines in tourism occur when low dissolved oxygen

causes noxious smells and floating mats of algal blooms create unfavorable aesthetic conditions. 

Risks to human health increase when the toxins from algal blooms accumulate in edible fish and

shellfish, and when toxins become airborne, causing respiratory problems due to inhalation. 

According to the NOAA report, more than half of the nation’s estuaries have moderate to high

expressions of at least one of these symptoms – an indication that eutrophication is well

developed in more than half of U.S. estuaries. 

In recent decades, human activities have greatly accelerated nutrient inputs, such as nitrogen

and phosphorous, causing excessive growth of algae and leading to degraded water quality and

associated impairments of freshwater and estuarine resources for human uses.123 Since 1970,
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eutrophic conditions worsened in 48 estuaries and improved in 14. In 26 systems, there was no

trend in overall eutrophication conditions since 1970.124 On the New England coast, for

example, the number of red and brown tides and shellfish problems from nuisance and toxic

plankton blooms have increased over the past two decades, a development thought to be linked

to increased nitrogen loadings in coastal waters. Long-term monitoring in the United States,

Europe, and other developed regions of the world shows a substantial rise of nitrogen levels in

surface waters, which are highly correlated with human-generated inputs of nitrogen to their

watersheds. 

Between 1992 and 1997, experts surveyed by National Oceanic and Atmospheric

Administration (NOAA) most frequently recommended that control strategies be developed for

agriculture, wastewater treatment, urban runoff, and atmospheric deposition.125 In its Third

Report to Congress on the Great Waters, EPA reported that atmospheric deposition contributes

from 2 to 38 percent of the nitrogen load to certain coastal waters.126 A review of peer reviewed

literature in 1995 on the subject of air deposition suggests a typical contribution of 20 percent or

higher.127 Human-caused nitrogen loading to the Long Island Sound from the atmosphere was

estimated at 14 percent by a collaboration of federal and state air and water agencies in 1997.128

The National Exposure Research Laboratory, U.S. EPA, estimated based on prior studies that 20

to 35 percent of the nitrogen loading to the Chesapeake Bay is attributable to atmospheric

deposition.129 The mobile source portion of atmospheric NOx contribution to the Chesapeake

Bay was modeled at about 30 percent of total air deposition.130

Deposition of nitrogen from nonroad diesel engines contributes to elevated nitrogen levels in

waterbodies. The new emission standards for nonroad diesel engines will reduce total NOx

emissions by 738,000 tons in 2030. The NOx reductions will reduce the airborne nitrogen

deposition that contributes to eutrophication of watersheds, particularly in aquatic systems where

atmospheric deposition of nitrogen represents a significant portion of total nitrogen loadings. 

2.1.3.2.3 Polycyclic Organic Matter (POM) Deposition

EPA’s Great Waters Program has identified 15 pollutants whose deposition to water bodies

has contributed to the overall contamination loadings to the these Great Waters.131 One of these

15 compounds, a group known as polycyclic organic matter (POM), are compounds that are

mainly adhered to the particles emitted by mobile sources and later fall to earth in the form of

precipitation or dry deposition of particles. The mobile source contribution of the seven most

toxic POM is at least 62 tons/year and represents only those POM that are adhered to mobile

source particulate emissions.132 The majority of these emissions are produced by diesel engines.

POM is generally defined as a large class of chemicals consisting of organic compounds

having multiple benzene rings and a boiling point greater than 100° C. Polycyclic aromatic

hydrocarbons are a chemical class that is a subset of POM. POM are naturally occurring

substances that are byproducts of the incomplete combustion of fossil fuels and plant and animal

biomass (e.g., forest fires). Also, they occur as byproducts from steel and coke productions and

waste incineration.
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Evidence for potential human health effects associated with POM comes from studies in

animals (fish, amphibians, rats) and in human cells culture assays. Reproductive, developmental,

immunological, and endocrine (hormone) effects have been documented in these systems. Many

of the compounds included in the class of compounds known as POM are classified by EPA as

probable human carcinogens based on animal data.

The new emission standards will reduce not only the PM emissions from land-based nonroad

diesel engines, but also the deposition of the POM adhering to the particles, thereby reducing

health effects of POM in lakes and streams, accelerating the recovery of affected lakes and

streams, and reviving adversely affected ecosystems.

2.1.3.2.4 Materials Damage and Soiling

The deposition of airborne particles can also reduce the aesthetic appeal of buildings and

culturally important articles through soiling, and can contribute directly (or in conjunction with

other pollutants) to structural damage by means of corrosion or erosion. Particles affect materials

principally by promoting and accelerating the corrosion of metals, by degrading paints, and by

deteriorating building materials such as concrete and limestone. Particles contribute to these

effects because of their electrolytic, hygroscopic, and acidic properties, and their ability to sorb

corrosive gases (principally sulfur dioxide). The rate of metal corrosion depends on a number of

factors, including the deposition rate and nature of the pollutant; the influence of the metal

protective corrosion film; the amount of moisture present; variability in the electrochemical

reactions; the presence and concentration of other surface electrolytes; and the orientation of the

metal surface.

Paints undergo natural weathering processes from exposure to environmental factors such as

sunlight, moisture, fungi, and varying temperatures. In addition to the natural environmental

factors, studies show particulate matter exposure may give painted surfaces a dirty appearance. 

Several studies also suggest that particles serve as carriers of other more corrosive pollutants,

allowing the pollutants to reach the underlying surface or serve as concentration sites for other

pollutants. A number of studies have shown some correlation between particulate matter and

damage to automobile finishes. A number of studies also support the conclusion that gaseous

pollutants contribute to the erosion rates of exterior paints.

Damage to calcareous stones (i.e., limestone, marble and carbonated cemented stone) has

been attributed to deposition of acidic particles. Moisture and salts are considered the most

important factors in building material damage. However, many other factors (such as normal

weathering and microorganism damage) also seem to play a part in the deterioration of inorganic

building materials. The relative importance of biological, chemical, and physical mechanisms

has not been studied to date. Thus, the relative contribution of ambient pollutants to the damage

observed in various building stone is not well quantified. Under high wind conditions,

particulates result in slow erosion of the surfaces, similar to sandblasting.

Soiling is the accumulation of particles on the surface of an exposed material resulting in the

degradation of its appearance. When such accumulation produces sufficient changes in
Final Regulatory Impact Analysis

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reflection from opaque surfaces and reduces light transmission through transparent materials, the

surface will become perceptibly dirty to the human observer. Soiling can be remedied by

cleaning or washing, and depending on the soiled material, repainting. 

2.2 Air Toxics

2.2.1 Diesel Exhaust PM

A number of health studies have been conducted regarding diesel exhaust including

epidemiologic studies of lung cancer in groups of workers, and animal studies focusing on noncancer effects specific to diesel exhaust. Diesel exhaust PM (including the associated organic

compounds that are generally high molecular-weight hydrocarbon types, but not the more

volatile gaseous hydrocarbon compounds) is generally used as a surrogate measure for diesel

exhaust.

2.2.1.1 Potential Cancer Effects of Diesel Exhaust

In addition to its contribution to ambient PM inventories, diesel exhaust is of specific

concern because it has been judged to pose a lung cancer hazard for humans as well as a hazard

from noncancer respiratory effects such as pulmonary inflammation. 

In 2001, EPA completed a rulemaking on mobile source air toxics with a determination that

diesel particulate matter and diesel exhaust organic gases be identified as a Mobile Source Air

Toxic (MSAT).133 This determination was based on a draft of the Diesel HAD on which the

Clean Air Scientific Advisory Committee (CASAC) of the Science Advisory Board had reached

closure. Including both diesel PM and diesel exhaust organic gases in the determination was

made in order to be precise about the components of diesel exhaust expected to contribute to the

observed cancer and non-cancer health effects. Currently available science, while suggesting an

important role for the particulate phase component of diesel exhaust, does not attribute the likely

cancer and noncancer health effects independently to diesel particulate matter as distinct from

the gas phase components (EPA, 2001). The purpose of the MSAT list is to provide a screening

tool that identifies compounds emitted from motor vehicles or their fuels for which further

evaluation of emission controls is appropriate.

EPA released its final “Health Assessment Document for Diesel Engine Exhaust” (the EPA

Diesel HAD), referenced earlier. There, diesel exhaust was classified as likely to be

carcinogenic to humans by inhalation at environmental exposures, in accordance with the revised

draft 1996/1999 EPA cancer guidelines.134 In accordance with earlier EPA guidelines, diesel

exhaust would be similarly classified as a probable human carcinogen (Group B1).135, 136 A

number of other agencies (National Institute for Occupational Safety and Health, the

International Agency for Research on Cancer, the World Health Organization, California EPA,

and the U.S. Department of Health and Human Services) have made similar

classifications.137,138,139,140,141 The Health Effects Institute has also made numerous studies and

report on the potential carcinogenicity of diesel exhaust.142, 143, 144 Numerous animal and
Air Quality, Health, and Welfare Effects

2-55

bioassay/genotoxic tests have been done on diesel exhaust.145, 146 Also, case-control and cohort

studies have been conducted on railroad engine exposures147,148,149 in addition to studies on truck

workers.150, 151,152 Also, there are numerous other epidemiologic studies including some studying

mine workers and fire fighters.153, 154 

It should be noted that the conclusions in the EPA Diesel HAD were based on diesel engines

currently in use, including nonroad diesel engines such as those found in bulldozers, graders,

excavators, farm tractor drivers and heavy construction equipment. As new diesel engines with

significantly less PM exhaust emissions replace existing engines, the conclusions of the EPA

Diesel HAD will need to be reevaluated. 

More specifically, the EPA Diesel HAD states that the conclusions of the document apply to

diesel exhaust in use today including both highway and nonroad engines. The EPA Diesel HAD

acknowledges that the studies were done on engines with older technologies generally for

highway applications and that “there have been changes in the physical and chemical

composition of some DE [diesel exhaust] emissions (highway vehicle emissions) over time,

though there is no definitive information to show that the emission changes portend significant

toxicological changes.” The EPA Diesel HAD further concludes that “taken together, these

considerations have led to a judgment that the hazards identified from older-technology-based

exposures are applicable to current-day exposures.” The diesel technology used for nonroad

diesel engines typically lags that used for highway engines, which have been subject to PM

standards since 1988. Thus, the conclusions from the EPA Diesel HAD continue to be relevant

to current nonroad diesel engine emissions.

Some of the epidemiologic studies discussed in the EPA Diesel HAD were conducted

specifically on nonroad diesel engine emissions. In particular, one recent study examined

bulldozer operators, graders, excavators, and full-time farm tractor drivers finding increased

odds of lung cancer.155 Another cohort study of operators of heavy construction equipment also

showed increased lung cancer incidence for these workers.156

For the EPA Diesel HAD, EPA reviewed 22 epidemiologic studies in detail, finding

increased lung cancer risk in 8 out of 10 cohort studies and 10 out of 12 case-control studies. 

Relative risk for lung cancer associated with exposure range from 1.2 to 2.6. In addition, two

meta-analyses of occupational studies of diesel exhaust and lung cancer have estimated the

smoking-adjusted relative risk of 1.35 and 1.47, examining 23 and 30 studies, respectively.157,158

That is, these two studies show an overall increase in lung cancer for the exposed groups of 35

percent and 47 percent compared with the groups not exposed to diesel exhaust. In the EPA

Diesel HAD, EPA selected 1.4 as a reasonable estimate of occupational relative risk for further

analysis. 

EPA generally derives cancer unit risk estimates to calculate population risk more precisely

from exposure to carcinogens. In the simplest terms, the cancer unit risk is the increased risk

associated with average lifetime exposure of 1 :g/m3

. EPA concluded in the Diesel HAD that it

is not possible currently to calculate a cancer unit risk for diesel exhaust due to a variety of

factors that limit the current studies, such as a lack of standard exposure metric for diesel exhaust
Final Regulatory Impact Analysis

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and the absence of quantitative exposure characterization in retrospective studies.

However, in the absence of a cancer unit risk, the EPA Diesel HAD sought to provide

additional insight into the possible ranges of risk that might be present in the population. Such

insights, while not confident or definitive, nevertheless contribute to an understanding of the

possible public health significance of the lung cancer hazard. The possible risk range analysis

was developed by comparing a typical environmental exposure level to a selected range of

occupational exposure levels and then proportionally scaling the occupationally observed risks

according to the exposure ratio’s to obtain an estimate of the possible environmental risk. If the

occupational and environmental exposures are similar, the environmental risk would approach

the risk seen in the occupational studies whereas a much higher occupational exposure indicates

that the environmental risk is lower than the occupational risk. A comparison of environmental

and occupational exposures showed that for certain occupations the exposures are similar to

environmental exposures while, for others, they differ by a factor of about 200 or more. 

The first step in this process is to note that the occupational relative risk of 1.4, or a 40

percent from increased risk compared with the typical 5 percent lung cancer risk in the U.S.

population, translates to an increased risk of 2 percent (or 10-2) for these diesel exhaust exposed

workers. The Diesel HAD derived a typical nationwide average environmental exposure level of 

0.8 :g./m3 for diesel PM from highway sources for 1996. This estimate was based on national

exposure modeling; the derivation of this exposure is discussed in detail in the EPA Diesel HAD. 

Diesel PM is a surrogate for diesel exhaust and, as mentioned above, has been classified as a

carcinogen by some agencies. 

The possible environmental risk range was estimated by taking the relative risks in the

occupational setting, EPA selected 1.4 and converting this to absolute risk of 2% and then

ratioing this risk by differences in the occupational vs environmental exposures of interest. A

number of calculations are needed to accomplish this, and these can be seen in the EPA Diesel

HAD. The outcome was that environmental risks from diesel exhaust using higher estimates of

occupational exposure could range from a low of 10-4 to 10-5 or be as high as 10-3 if lower

estimates of occupational exposure were used. Note that the environmental exposure of interest

(0.8 :g/m3) remains constant in this analysis, while the occupational exposure is a variable. The

range of possible environmental risk is a reflection of the range of occupational exposures that

could be associated with the relative and related absolute risk levels observed in the occupational

studies. 

While these risk estimates are exploratory and not intended to provide a definitive

characterization of cancer risk, they are useful in gauging the possible range of risk based on

reasonable judgment. It is important to note that the possible risks could also be higher or lower

and a zero risk cannot be ruled out. Some individuals in the population may have a high

tolerance to exposure from diesel exhaust and low cancer susceptibility. Also, one cannot rule

out the possibility of a threshold of exposure below which there is no cancer risk, although

evidence has not been seen or substantiated on this point. 

Also, as discussed in the Diesel HAD, there is a relatively small difference between some
Air Quality, Health, and Welfare Effects

GIt should be note that, as with any modeling assessment, there are a number of significant limitations and

uncertainties in NATA. These uncertainties and limitations include use of default values to model local conditions,

limitations in emissions data, uncertainties in locating emissions spatially and temporally, and accounting for

atmospheric processes. NATA limitations and uncertainties are discussed at the following website: 

http://www.epa.gov/ttn/atw/nata/natsalim2.html

2-57

occupational settings where increased lung cancer risk is reported and ambient environmental

exposures. The potential for small exposure differences underscores the concerns about the

potential public hazard, since small differences suggest that environmental risk levels may be

close to those observed in the occupational setting.

EPA also assessed air toxic emissions and their associated risk (the National-Scale Air

Toxics Assessment or NATA for 1996), and we concluded that diesel exhaust ranks with other

substances that the national-scale assessment suggests pose the greatest relative risk.159 This

national assessment estimates average population inhalation exposures to diesel PM in 1996 for

nonroad as well as highway sources. These are the sum of ambient levels in various locations

weighted by the amount of time people spend in each of the locations. This analysis shows a

somewhat higher diesel exposure level than the 0.8 :g/m3

 used to develop the risk perspective in

the Diesel HAD. The average nationwide NATA mobile exposure levels are 1.44 :g/m3 total

with highway source contribution of 0.46 :g/m3 and a nonroad source contribution of 0.98

:g/m3

. The average urban exposure was 1.64 :g/m3 and the average rural exposure was 0.55

:g/m3

. In five percent of urban census tracts across the United States, average exposures were

above 4.33 :g/m3

. The EPA Diesel HAD states that use of the NATA exposure estimates

instead of the 0.8 :g/m3 estimate results in a similar risk perspective.G

In summary, even though EPA does not have a specific carcinogenic potency with which to

accurately estimate the carcinogenic impact of diesel exhaust, the likely hazard to humans

together with the potential for significant environmental risks leads us to conclude that diesel

exhaust emissions need to be reduced from nonroad engines in order to protect public health. 

The following factors lead to our determination.

1. EPA has officially designated diesel exhaust as a likely human carcinogen due to

inhalation at environmental exposure. Other organizations have made similar

determinations.

2. The entire U.S. population is exposed to various levels of diesel exhaust. The higher

exposures at environmental levels is comparable to some occupational exposure levels,

so that environmental risk could be the same as, or approach, the risk magnitudes

observed in the occupational epidemiologic studies.

3. The possible range of risk for the general U.S. population due to exposure to diesel

exhaust is 10-3 to 10-5 although the risk could be lower and a zero risk cannot be ruled

out.

Thus, the concern for a carcinogenicity hazard resulting from diesel exhaust exposures is

longstanding based on studies done over many years. This hazard may be widespread due to the
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ubiquitous nature of exposure to diesel exhaust.

2.2.1.2 Other Health Effects of Diesel Exhaust

The acute and chronic exposure-related effects of diesel exhaust emissions are also of

concern to the Agency. The Diesel HAD established an inhalation Reference Concentration

(RfC) specifically based on animal studies of diesel exhaust. An RfC is defined by EPA as “an

estimate of a continuous inhalation exposure to the human population, including sensitive

subgroups, with uncertainty spanning perhaps an order of magnitude, that is likely to be without

appreciable risks of deleterious noncancer effects during a lifetime.” EPA derived the RfC from

consideration of four well-conducted chronic rat inhalation studies showing adverse pulmonary

effects.160, 161, 162, 163 The diesel RfC is based on a “no observable adverse effect” level of 144

:g/m3

 that is further reduced by applying uncertainty factors of 3 for interspecies extrapolation

and 10 for human variations in sensitivity. The resulting RfC derived in the Diesel HAD is 5

:g/m3

 for diesel exhaust as measured by diesel PM. This RfC does not consider allergenic

effects such as those associated with asthma or immunologic effects. There is growing evidence

that diesel exhaust can exacerbate these effects, but the exposure-response data are presently

lacking to derive an RfC. 

While there have been relatively few human controlled exposure studies associated

specifically with the noncancer impact of diesel PM alone, diesel PM is frequently part of the

ambient particles studied in numerous epidemiologic studies. Conclusions that health effects

associated with ambient PM in general are relevant to diesel PM are supported by studies that

specifically associate observable human noncancer health effects with exposure to diesel PM. 

As described in the Diesel HAD, these studies include some of the same health effects reported

for ambient PM, such as respiratory symptoms (cough, labored breathing, chest tightness,

wheezing), and chronic respiratory disease (cough, phlegm, chronic bronchitis and suggestive

evidence for decreases in pulmonary function). Symptoms of immunological effects such as

wheezing and increased allergenicity are also seen. Studies in rodents, especially rats, show the

potential for human inflammatory effects in the lung and consequential lung tissue damage from

chronic diesel exhaust inhalation exposure. The Diesel HAD notes that acute or short-term

exposure to diesel exhaust can cause acute irritation (e.g., eye, throat, bronchial),

neurophysiological symptoms (e.g., lightheadedness, nausea), and respiratory symptoms (cough,

phlegm). There is also evidence for an immunologic effect such as the exacerbation of allergenic

responses to known allergens and asthma-like symptoms.164,165,166,167 The Diesel HAD lists

numerous other studies as well. Also, as discussed in more detail previously, in addition to its

contribution to ambient PM inventories, diesel PM is of special concern because it has been

associated with an increased risk of lung cancer.

The Diesel HAD also briefly summarizes health effects associated with ambient PM and the

EPA’s annual NAAQS of 15 :g/m3

. There is a much more extensive body of human data

showing a wide spectrum of adverse health effects associated with exposure to ambient PM, of

which diesel exhaust is an important component. The RfC is not meant to say that 5 :g/m3

provides adequate public health protection for ambient PM2.5. In fact, there may be benefits to
Air Quality, Health, and Welfare Effects

HIt should again be noted that recent epidemiologic studies of ambient PM2.5 do not indicate a threshold of

effects at low concentrations. For example, the authors of the Pope reanalysis note that, for the range of exposures

considered in their reanalysis, the slope of the concentration-response function appears to be monotonic and nearly

linear, although they cannot exclude the potential for a leveling off or steepening at higher exposure levels. The

EPA Science Advisory Board’s Advisory Council for Clean Air Compliance, which provides advice and review of

EPA’s methods for assessing the benefits and costs of the Clean Air Act under Section 812 of the Act, has advised

that there is currently no scientific basis for assuming any specific threshold for the PM-related health effects

considered in typical benefits analyses (EPA-SAB-Council-ADV-99-012, 1999). Also, the National Research

Council, in its own review of EPA’s approach to benefits analyses, has agreed with this advice. This advice is

supported by the recent literature on health effects of PM exposure (Daniels et al., 2000; Pope, 2000; Pope et al.,

2002, Rossi et al., 1999; Schwartz, 2000, Schwartz, Laden, and Zanobetti 2002 [Schwarz, J.; Laden, F.; and

Zanobetti, A. (2002) The Concentration-Response Relation between PM2.5 and Daily Deaths. Environ Health

Perspect 110(10): 1025-1029]) which generally finds no evidence of a non-linear concentration-response

relationship and, in particular, no evidence of a distinct threshold for health effects. The most recent draft of the

EPA Air Quality Criteria for Particulate Matter (U.S. EPA, 2002) reports only one study, analyzing data from

Phoenix, AZ, that reported even limited evidence suggestive of a possible threshold for PM2.5 (Smith et al., 2000).

2-59

reducing diesel PM below 5 :g/m3 since diesel PM is a major contributor to ambient PM2.5 .H

Also, as mentioned earlier in the health effects discussion for PM2.5, there are a number of

other health effects associated with PM in general—and motor vehicle exhaust, including that

from diesel engines in particular—that provide additional evidence for the need for significant

emission reductions from nonroad diesel sources. 

As indicated earlier, a number of recent studies have associated living near roadways with

adverse health effects. Two of the studies cited earlier will be mentioned again here as examples

of the type of work that has been done. A Dutch study (discussed earlier by G. Hoek et al.,

2002) of a population of people 55-69 years old found that there was an elevated risk of heart

and lung related mortality among populations living near high traffic roads. A review discussed

earlier of studies (by R. Delfino et al., 2002) of the respiratory health of people living near

roadways included a publication indicating that the risk of asthma and related respiratory

disease appeared elevated in people living near heavy traffic.168 These studies offer evidence

that people exposed most directly to emissions from mobile sources, including those from diesel

engines, face an elevated risk of illness or death.

All of these health effects plus the designation of diesel exhaust as a likely human carcinogen

provide ample health justification for control.

Public comments from the Building and Construction Trades Department, AFL-CIO, and

International Union of Operating Engineers supported the need to adopt the nonroad rule noting

that exposure to diesel emissions from nonroad diesel engine poses a great risk to workers in the

construction industry and other occupations, but are highest among construction workers because

they work in close proximity to the exposure source, and are exposed daily to the hazards of

nonroad diesel pollution. In their comments, BCTD noted that construction workers may be

exposed to hazards generated from work performed by other trades employed by other

contractors because sources of diesel exposure are scattered throughout the site. They noted

further that in an exposure study, railway workers, heavy equipment operators and miners had
Final Regulatory Impact Analysis

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higher mortality rates from lung cancer and all causes than workers without diesel exposure. 

Heavy equipment operators and miners had comparable relative risk for lung cancer, both of

which were over 2.5 times that of non-exposed workers (Boffetta, 1988).

2.2.1.3 Diesel Exhaust PM Ambient Levels

Because diesel PM is part of overall ambient PM and cannot be easily distinguished from

overall PM, we do not have direct measurements of diesel PM in the ambient air. Diesel PM

concentrations are estimated instead using one of three approaches: 1) ambient air quality

modeling based on diesel PM emission inventories; 2) using elemental carbon concentrations in

monitored data as surrogates; or 3) using the chemical mass balance (CMB) model in

conjunction with ambient PM measurements. (Also, in addition to CMB, UNMIX/PMF have

also been used). Estimates using these three approaches are described below. In addition,

estimates developed using the first two approaches above are subjected to a statistical

comparison to evaluate overall reasonableness of estimated concentrations from ambient air

quality modeling. It is important to note that, while there are inconsistencies in some of these

studies on the relative importance of gasoline and diesel PM, the studies discussed in the Diesel

HAD all show that diesel PM is a significant contributor to overall ambient PM. Some of the

studies differentiate nonroad from highway diesel PM.

2.2.1.3.1 Toxics Modeling and Methods 

In addition to the general ambient PM modeling conducted for this rulemaking, diesel PM

concentrations for 1996 were estimated as part of the National-Scale Air Toxics Assessment

(NATA; EPA, 2002). In this assessment, the PM inventory developed for the recent regulation

promulgating 2007 heavy duty vehicle standards was used (EPA, 2000). Note that the nonroad

inventory used in this modeling was based on an older version of the draft NONROAD Model

that showed higher diesel PM than the current version, so the ambient concentrations may be

biased high. Ambient impacts of mobile source emissions were predicted using the Assessment

System for Population Exposure Nationwide (ASPEN) dispersion model. 

From the NATA 1996 modeling, overall mean annual national ambient diesel PM levels of

2.06 :g/m3

 were calculated with a mean of 2.41 in urban counties and 0.74 in rural counties. 

Table 2.2.1-1 below summarizes the distribution of average ambient concentrations to diesel

PM at the national scale. Over half of the diesel PM can be attributed to nonroad diesel engines. 

A map of county median concentrations (median of census tract concentrations) from highway

and nonroad sources is provided in Figure 2.2.1-1. We have not generated a map depicting the

estimated geographic distribution of nonroad diesel PM alone. While the high median

concentrations are clustered in the Northeast, Great Lake States and California, areas of high

median concentrations are distributed throughout the United States.
Air Quality, Health, and Welfare Effects

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 Table 2.2.1-1

Distribution of Average Ambient Concentrations of 

Diesel PM at the National Scale in the 1996 NATA Assessment.

Nationwide (:g/m3) Urban (:g/m3) Rural (:g/m3)

5th Percentile 0.33 0.51 0.15

25th Percentile 0.85 1.17 0.42

Average 2.06 2.41 0.74

75th Percentile 2.45 2.7 0.97

95th Percentile 5.37 6.06 1.56

Onroad Contribution 

to Average

0.63 0.72 0.27

Nonroad Contribution 

to Average

1.43 1.69 0.47
Figure 2.2.1-1

Estimated County Median Concentrations of Diesel Particulate Matter

Source: EPA National-Scale Air Toxics Assessment for 1996. Results should not be used to draw conclusions abconcentrations. Results are most meaningful at the Regional or National level.
Air Quality, Health, and Welfare Effects

2-63
Final Regulatory Impact Analysis

2-64

Diesel PM concentrations were also recently modeled across a representative urban area,

Houston, Texas, for 1996, using the Industrial Source Complex Short Term (ISCST3) model.169

The methodology used to model diesel PM concentrations is the same as the methodology used

for benzene and other hazardous air pollutants, as described in a recent EPA technical report.170

For Harris County, which has the highest traffic density in Houston area, link-based diesel PM

emissions were estimated for highway mobile sources, using diesel PM emission rates developed

for the recent EPA 2007 heavy duty engine and highway diesel fuel sulfur control rule.171 This

link-based modeling approach is designed to specifically account for local traffic patterns within

the urban center, including diesel truck traffic along specific roadways. For other counties in the

Houston metropolitan area, county level emission estimates from highway vehicles were

allocated to one kilometer grid cells based on total roadway miles. Nonroad diesel emissions for

Houston area counties were obtained from the inventory done for the 2007 heavy duty rule, and

allocated to one kilometer grid cells using activity surrogates. The modeling in Houston suggests

strong spatial gradients (on the order of a factor of 2-3 across a modeling domain) for diesel PM

and indicates that “hotspot” concentrations can be very high. Values as high as 8 :g/m3 at were

estimated at a receptor versus a 3 :g/m3 average in Houston. Such “hot spot” concentrations

suggest both a high localized exposure plus higher estimated average annual exposure levels for

urban centers than what has been estimated in assessments such as NATA 1996, which are

designed to focus on regional and national scale averages. Figure 2.2.1-2 depicts the spatial

distribution of diesel PM concentrations in Houston.
Air Quality, Health, and Welfare Effects

2-65

Figure 2.2.1-2 

Annual Average Ambient Concentrations of Diesel PM in Houston, 1996, based on

Dispersion Modeling Using Industrial Source Complex Short Term (ISCST3) model.

2.2.1.3.2 Elemental Carbon Measurements

As shown in Figures 2.1.1-1 to 3, the carbonaceous component is significant in ambient PM. 

The carbonaceous component consists of organic carbon and elemental carbon. Monitoring data

on elemental carbon concentrations can be used as a surrogate to determine ambient diesel PM

concentrations. Elemental carbon is a major component of diesel exhaust, contributing to
Final Regulatory Impact Analysis

2-66

approximately 60-80 percent of diesel particulate mass, depending on engine technology, fuel

type, duty cycle, lube oil consumption, and state of engine maintenance. In most areas, diesel

engine emissions are major contributors to elemental carbon, with other potential sources

including gasoline exhaust, combustion of coal, oil, or wood, charbroiling, cigarette smoke, and

road dust. Because of the large portion of elemental carbon in diesel particulate matter, and the

fact that diesel exhaust is one of the major contributors to elemental carbon in most areas,

ambient diesel PM concentrations can be bounded using elemental carbon measurements. 

The measured mass of elemental carbon at a given site varies depending on the measurement

technique used. Moreover, to estimate diesel PM concentration based on elemental carbon level,

one must first estimate the percentage of PM attributable to diesel engines and the percentage of

elemental carbon in diesel PM. Thus, there are significant uncertainties in estimating diesel PM

concentrations using an elemental carbon surrogate. Also, there are issues with the measurement

methods used for elemental carbon. Many studies used thermal optimal transmission (TOT), the

NIOSH method developed at Sunset laboratories. Other studies used thermal optical reflectance

(TOR), a method developed by Desert Research Institute. EPA has developed multiplicative

conversion factors to estimate diesel PM concentrations based on elemental carbon levels.172

Results from several source apportionment studies were used to develop these factors.173, 174, 175,

176, 177, 178, 179 Average conversion factors were compiled together with lower and upper bound

values. Conversion factors (CFs) were calculated by dividing the diesel PM2.5 concentration

reported in these studies by the total organic carbon or elemental carbon concentrations also

reported in the studies. Table 2.2.1-2 presents the minimum, maximum, and average EC

conversion factors as a function of:

• Measurement technique

• Eastern or Western United States

• Season

• Urban or rural

The reported minimum, maximum, and average values in Table 2.2.1-2 are the minima, maxima,

and arithmetic means of the EC conversion factors across all sites (and seasons, where

applicable) in the given site subset. For the TOT data collected in the East, the minimum,

maximum, and average conversion factors are all equal. This is because these values were based

only on one study where the data were averaged over sites, by season.180 Depending on the

measurement technique used, and assumptions made in converting elemental carbon

concentration to diesel PM concentration, average nationwide concentrations for current years of

diesel PM estimated from elemental carbon data range from about 1.2 to 2.2 :g/m3. EPA has

compared these estimates based on elemental carbon measurements with modeled concentrations

in the NATA for 1996. Results of comparisons of mean percentage differences are presented in

Table 2.2.1-3. These results show that the two sets of data agree reasonably well, with estimates

for the majority of sites within a factor of 2, regardless of the measurement technique or

methodology for converting elemental carbon to diesel PM concentration. Agreement was better

when modeled concentrations were adjusted to reflect recent changes in the nonroad inventory. 

The best model performance based on the fraction of modeled values within 100 % of the

monitored value is for the DPM-maximum value, which reflects changes to the nonroad
Air Quality, Health, and Welfare Effects

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inventory model. The corresponding fractions of modeled values within 100 % of the monitored

value are 73 % for TOR sites, 80 % for TOT sites, and 92 % for TORX sites. All in all, this

performance compares favorably with the model to monitor results for other pollutants assessed

in NATA, with the exception of benzene, for which the performance of the NATA modeling was

better.

2.2.1.3.3 Chemical Mass Balance Receptor Modeling and Source Apportionment

The third approach for estimating ambient diesel PM concentrations uses the chemical mass

balance (CMB) model for source apportionment in conjunction with ambient PM measurements

and chemical source “fingerprints” to estimate ambient diesel PM concentrations. The CMB

model uses a statistical fitting technique to determine how much mass from each source would

be required to reproduce the chemical fingerprint of each speciated ambient monitor. Inputs to

the CMB model applied to ambient PM2.5 include measurements made at an air monitoring site

and measurements made of each of the source types suspected to affect the site. The CMB

model uses a statistical fitting technique (“effective variance weighted least squares”) to

determine how much mass from each source would be required to reproduce the chemical

fingerprint of each speciated ambient monitor. This calculation is based on optimizing the sum

of sources, so that the difference between the ambient monitor and the sum of sources is

minimized. The optimization technique employs “fitting species” that are related to the sources. 

The model assumes that source profiles are constant over time, that the sources do not interact or

react in the atmosphere, that uncertainties in the source fingerprints are well-represented, and

that all sources are represented in the model. 

This source apportionment technique presently does not distinguish between highway and

nonroad but, instead, gives diesel PM as a whole. One can allocate the diesel PM numbers based

on the inventory split between highway and nonroad diesel, although this allocation was not

done in the studies published to date. This source apportionment technique can though

distinguish between diesel and gasoline PM. Caution in interpreting CMB results is warranted,

as the use of fitting species that are not specific to the sources modeled can lead to misestimation

of source contributions. Ambient concentrations using this approach are generally about 1 :g/m3

annual average. UNMIX/PMF models show similar results.
Final Regulatory Impact Analysis

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Table 2.2.1-2

Summary of Calculated Elemental Carbon (EC) Conversion Factors 

(Conversion factors to convert total EC to diesel PM2.5 concentration)

Ambient

Measurement

Technique: TOT

or TOR

East or

West Season

Location

Type

General MINa MAXa AVERAGEa

Recommended

Conversion Factors

EAST WEST

TOT East Fall (Q4) Mixed 2.3 2.3 2.3 X

East Spring (Q2) Mixed 2.4 2.4 2.4 X

East

Summer

(Q3) Mixed 2.1 2.1 2.1

X

East Winter (Q1) Mixed 2.2 2.2 2.2 X

West Unknown Urban 1.2 2.4 1.6 X

TOT Total 1.2 2.4 2.0

TOR Winter Rural 0.6 1.0 0.8 X X

Winter Urban 0.5 1.0 0.7 X X

Winter Total 0.5 1.0 0.8

TOR Total 0.5 1.0 0.8

Grand Total 0.5 2.4 1.3

Source: ICF Consulting for EPA, 2002, Office of Transportation and Air Quality. Report No. EPA420-D-02-004. a

 Minimum, maximum, or average value across all sites of the estimated conversion factors.

TOT = thermal optimal transmission, the NIOSH method developed at Sunset laboratories. 

TOR = thermal optical reflectance, a method developed by Desert Research Institute.
Air Quality, Health, and Welfare Effects

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Table 2.2.1-3

Summary of Differences Between the Nearest Modeled Concentration 

of Diesel Pm from the National Scale Air Toxics Assessment and Monitored Values 

Based on Elemental Carbon Measurements (Diesel PM model-to-measurement comparison)

Modeled

Variablea

Monitored

Variableb N

Mean

Modeled

Value

Mean

Monitored

Value

Mean

Difference Mean 

%

Difference

Fraction of Modeled Values

Within

10% 25% 50% 100%

concnear TOR 15 1.56 0.94 0.63 100 0.07 0.13 0.53 0.53

concnear2 TOR 15 1.20 0.94 0.26 56 0.07 0.13 0.47 0.60

concnear TORH 15 1.56 1.16 0.40 62 0.00 0.07 0.40 0.60

concnear2 TORH 15 1.20 1.16 0.04 26 0.00 0.07 0.33 0.73

concnear TORL 15 1.56 0.64 0.92 190 0.13 0.40 0.47 0.53

concnear2 TORL 15 1.20 0.64 0.55 126 0.07 0.33 0.47 0.53

concnear TOT 95 2.61 1.73 0.88 80 0.12 0.21 0.45 0.68

concnear2 TOT 95 2.05 1.73 0.32 42 0.11 0.37 0.53 0.77

concnear TOTH 95 2.61 2.10 0.52 61 0.11 0.22 0.46 0.74

concnear2 TOTH 95 2.05 2.10 -0.05 27 0.11 0.35 0.53 0.80

concnear TOTL 95 2.61 1.52 1.09 101 0.09 0.17 0.43 0.63

concnear2 TOTL 95 2.05 1.52 0.52 58 0.09 0.32 0.52 0.72

concnear TORX 88 2.31 1.70 0.61 47 0.10 0.30 0.59 0.78

concnear2 TORX 88 1.81 1.70 0.11 15 0.17 0.30 0.59 0.85

concnear TORXH 88 2.31 2.23 0.08 13 0.11 0.26 0.60 0.84

concnear2 TORXH 88 1.81 2.23 -0.42 -12 0.08 0.22 0.52 0.92

concnear TORXL 88 2.31 1.19 1.12 110 0.10 0.26 0.41 0.65

concnear2 TORXL 88 1.81 1.19 0.62 65 0.14 0.31 0.52 0.74

Source: ICF Consulting for EPA, 2002, Office of Transportation and Air Quality. Report No. EPA420-D-02-004.

a

 Modeled variable:

concnear Nearest modeled DPM concentration from the 1996 NATA

concnear2 Nearest modeled DPM concentration with NATA concentrations adjusted to be consistent with

changes to the nonroad inventory model b

 Monitored variable:

TOR EC value multiplied by TOR average correction factor 

TORH EC value multiplied by TOR maximum correction factor

TORL EC value multiplied by TOR minimum correction factor

TOT EC value multiplied by TOT average correction factor

TOTH EC value multiplied by TOT maximum correction factor

TOTL EC value multiplied by TOR minimum correction factor

TORX TOR values plus the TOR equivalent values multiplied by TOR average correction factor

TORXH TOR values plus the TOR equivalent values multiplied by TOR maximum correction factor

TORXL TOR values plus the TOR equivalent values multiplied by TOR minimum correction factor

Because of the correlation of diesel and gasoline exhaust PM emissions in time and space,

chemical molecular species that provide markers for separation of these sources have been

sought. Recent advances in chemical analytical techniques have facilitated the development of

sophisticated molecular source profiles, including detailed speciation of organic compounds,

which allow the apportionment of particulate matter to gasoline and diesel sources with

increased certainty. As mentioned previously, however, caution in interpreting CMB results is

warranted. Markers that have been used in CMB receptor modeling have included elemental

carbon, polycyclic aromatic hydrocarbons (PAHs), organic acids, hopanes, and steranes.
Final Regulatory Impact Analysis

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It should be noted that since receptor modeling is based on the application of source profiles

to ambient measurements, this estimate of diesel PM concentrations includes the contribution

from on-highway and nonroad sources of diesel PM, although no study to date has included

source profiles from nonroad engines. Engine operations, fuel properties, regulations, and other

factors may distinguish nonroad diesel engines from their highway counterparts.

In addition, this model accounts for primary emissions of diesel PM only; the contribution of

secondary aerosols is not included. The role of secondarily formed organic PM in urban PM2.5

concentrations is not known, particularly from diesel engines. 

The first major application of organic tracer species in applying the CMB model evaluated

ambient PM2.0 in Los Angeles, CA sampled in 1982.181 This study was the first to distinguish

gasoline and diesel exhaust. CMB model application at four sites in the Los Angeles area

estimated ambient diesel PM2.0 concentrations to be 1.02-2.72 :g/m3

. Note that diesel PM

estimates are derived from source profiles measured on in-use diesel trucks.

Another major study examining diesel exhaust separately from gasoline exhaust and other

sources is the Northern Front Range Air Quality Study (NFRAQS).182 This study was conducted

in the metropolitan Denver, CO area during 1996-1997. The NFRAQS study employed a

different set of chemical species, including PAHs and other organics to produce source profiles

for a diverse range of mobile sources, including “normal emitting” gasoline vehicles, cold start

gasoline vehicles, high emitting gasoline vehicles, and diesel vehicles. Average source

contributions from diesel engines in NFRAQS were estimated to be 1.7 :g/m3 in an urban area,

and 1.2 :g/m3 in a rural area. Source profiles in this study were based on highway vehicles. 

The CMB model was applied in California’s San Joaquin Valley during winter 1995-1996.183

The study employed similar source tracers as the earlier study of Los Angeles PM2.0, in addition

to other more specific markers. Diesel PM source contribution estimates in Bakersfield, CA

were 3.92 and 5.32 during different measurement periods. Corresponding estimates in Fresno,

CA were 9.68 and 5.15 :g/m3. In the Kern Wildlife Refuge, diesel PM source contribution

estimates were 1.32 and 1.75 :g/m3 during the two periods.

The CMB model was applied in the Southeastern United States on data collected during the

Southeastern Aerosol Research and Characterization (SEARCH) study (Zheng et al., 2002). 

Modeling was conducted on data collected during April, July, and October 1999 and January

2000. Examining ambient monitors in urban, suburban, and rural areas, the modeled annual

average contribution of primary diesel emissions to ambient PM2.5 was 3.20-7.30 :g/m3 in

N. Birmingham, AL, 1.02-2.43 :g/m3 in Gulfport, MS, 3.29-5.56 :g/m3 in Atlanta, GA, and

1.91-3.07 :g/m3 in Pensacola, FL, which together represented the urban sites in the study. 

Suburban sites in the study were located outside Pensacola, FL (1.08-1.73 :g/m3

). Rural sites

were located in Centreville, AL (0.79-1.67 :g/m3), Oak Grove, MS (1.05-1.59 :g/m3), and

Yorkville, GA (1.07-2.02 :g/m3).

The CMB model was applied to ambient PM2.5 data collected during a severe photochemical

smog event during 1993 in Los Angeles using organic tracers.184 Modeled concentrations of
Air Quality, Health, and Welfare Effects

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diesel contributions to PM2.5 during this episode were conducted for Long Beach (8.33 :g/m3),

downtown Los Angeles (17.9 :g/m3

), Azusa (14.9 :g/m3), and Claremont, CA (7.63 :g/m3). 

While these studies provide an indication that diesel exhaust is a substantial contributor to

ambient PM2.5 mass, they should still be viewed with caution. CMB modeling depends on

ensuring the use of highly specific tracer species. If sources, such as nonroad diesel engines, are

chemically different from other sources, including highway diesel trucks, the CMB model can

misestimate source contributions. Nevertheless, these studies provide information that is

complementary to source-oriented air quality modeling (discussed above). From these studies, it

is apparent that diesel exhaust is a substantial contributor to ambient PM2.5, even in remote and

rural areas.

2.2.1.4 Diesel Exhaust PM Exposures 

Exposure of people to diesel exhaust depends on their various activities, the time spent in

those activities, the locations where these activities occur, and the levels of diesel exhaust

pollutants (such as PM) in those locations. While ambient levels are specific for a particular

location, exposure levels account for such factors as a person moving from location to location,

proximity to the emission source, and whether the exposure occurs in an enclosed environment.

2.2.1.4.1 Occupational Exposures 

Diesel particulate exposures have been measured for a number of occupational groups over

various years but generally for more recent years (1980s and later) rather than earlier years. 

Occupational exposures had a wide range varying from 2 to 1,280 :g/m3

 for a variety of

occupational groups including miners, railroad workers, firefighters, air port crew, public transit

workers, truck mechanics, utility linemen, utility winch truck operators, fork lift operators,

construction workers, truck dock workers, short-haul truck drivers, and long-haul truck drivers. 

These individual studies are discussed in the Diesel HAD.

The highest exposure to diesel PM is for workers in coal mines and noncoal mines, which are

as high a 1,280 :g/m3, as discussed in the Diesel HAD. The National Institute of Occupational

Safety and Health (NIOSH) has estimated a total of 1,400,000 workers are occupationally

exposed to diesel exhaust from on-road and nonroad equipment.

Many measured or estimated occupational exposures are for on-road diesel engines and some

are for school buses.185, 186, 187,188 Also, some (especially the higher ones) are for occupational

groups (fork lift operator, construction workers, or mine workers) who would be exposed to

nonroad diesel exhaust. Sometimes, as is the case for the nonroad engines, there are only

estimates of exposure based on the length of employment or similar factors rather than a :g/m3

level. Estimates for exposures to diesel PM for diesel fork lift operators have been made that

range from 7 to 403 :g/m3 as reported in the Diesel HAD. In addition, the Northeast States for

Coordinated Air Use Management (NESCAUM) measured occupational exposures to particulate

and elemental carbon near the operation of various diesel non-road equipment. Exposure groups

include agricultural farm operators, grounds maintenance personnel (lawn and garden
Final Regulatory Impact Analysis

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equipment), heavy equipment operators conducting multiple job tasks at a construction site, and

a saw mill crew at a lumber yard. Samples will be obtained in the breathing zone of workers. In

a recently released interim report on occupational health risks from diesel engine exposure,

pollution inside the cabs of heavy diesel equipment were shown to be up to 16 times higher than

federal health recommendations. The diesel PM was estimated to exist at levels that pose risk of

chronic inflammation and lung damage in exposed individuals (NESCAUM, 2003).

In public comments from the Building and Trade Department, AFL-CIO, they note their

research center, the Center to Protect Workers’ Rights, has sponsored research conducted by 

the Construction Occupational Health Program (COHP) at University of Massachusetts at

Lowell which documents diesel emissions exposure among a number of trades employed on a

major highway project underway in Boston, MA. Over 260 personal samples of diesel exposure

were collected among laborers (116); operating engineers (113) and other trades including

ironworkers (15), carpenters (9), piledrivers (5), boilermakers (1), plumbers (1) and surveyors

(1). Exposures associated with specific work processes were also documented. Using the

American Conference of Governmental Industrial Hygienists Threshold Limit Value (TLV) for

diesel exhaust as elemental carbon of 20 ug/m3 as proposed in 2002, the percentage of samples

exceeding the TLV overall was 14 percent (Woskie, 2002; ACGIH, 2002). It should be noted

that much of this project involves construction of underground tunnels. However, work in

enclosed and/or poorly ventilated work areas is common in construction.

One recent study found that construction workers in Ontario are exposed to elevated

concentrations of elemental carbon (EC) measured by thermal-optical transmission (TOT),

which the authors used as a surrogate for diesel exhaust.189 Task-based exposure measurements

were made corresponding to engine use. Demolition laborers were exposed to between 4.9

to146 ug/m3 of EC-TOT while operating compressors, performing excavation and cleanup, and

in tearing down structures. Construction equipment operating engineers were exposed to 4.3 to

7.8 ug/m3 EC-TOT while operating their machinery. Painters in new commercial construction

were exposed to between 3.6 to 9.0 ug/m3 EC-TOT, as a result of operating mixers. While these

concentrations are substantially higher than those seen in typical urban air, it is difficult to assign

these EC-TOT measurements to diesel engines, and the study authors did not indicate the fuel

source of the equipment used. However, it is likely that many of the engines in this study were

diesel engines.

2.2.1.4.2 Ambient Exposures in the General Population

Currently, personal exposure monitors for PM cannot differentiate diesel from other PM. 

Thus, we use modeling to estimate exposures. Specifically, exposures for the general population

are estimated by first conducting dispersion modeling of both highway and nonroad diesel

emissions, described above, and then by conducting exposure modeling. The most

comprehensive modeling for cumulative on-road and non-road exposures to diesel PM is the

NATA. This assessment calculates exposures of the national population as a whole to a variety

of air toxics, including diesel PM. As discussed previously, the ambient levels are calculated

using the ASPEN dispersion model. As discussed above, the preponderance of modeled diesel

PM concentrations are within a factor of 2 of diesel PM concentrations estimated from elemental
Air Quality, Health, and Welfare Effects

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carbon measurements.190 This comparison adds credence to the modeled ASPEN results and

associated exposure assessment. 

The modeled concentrations for calendar year 1996 are used as inputs into an exposure

model called the Hazardous Air Pollution Exposure Model (HAPEM4) to calculate exposure

levels. Average exposures calculated nationwide are 1.44 :g/m3

 with levels of 1.64 :g/m3 for

urban counties and 0.55 :g/m3

 for rural counties. Again, nonroad diesel emissions account for

over half of the this exposure. Table 2.2.1-4 summarizes the distribution of average exposure

concentrations to diesel PM at the national scale in the 1996 NATA assessment. Figure 2.2.1-3

presents a map of the distribution of median exposure concentrations for U.S. counties.

Table 2.2.1-4

Distribution of Average Exposure Concentrations to 

Diesel PM at the National Scale in the 1996 NATA Assessment.

Nationwide (:g/m3) Urban (:g/m3) Rural (:g/m3)

5th Percentile 0.16 0.29 0.07

25th Percentile 0.58 0.81 0.29

Average 1.44 1.64 0.55

75th Percentile 1.73 1.91 0.67

95th Percentile 3.68 4.33 1.08

Onroad Contribution to Average 0.46 0.52 0.21

Nonroad Contribution to Average 0.98 1.12 0.34
Figure 2.2.1-3

Estimated County Median Exposure Concentrations of Diesel Particulate Matter

Source: EPA National-Scale Air Toxics Assessment for 1996. Results should not be used to draw conclusions abconcentrations. Results are most meaningful at the Regional or National level.
Air Quality, Health, and Welfare Effects

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As explained earlier, the fact that these levels are below the 5 :g/m3 RfC (which is based on

limited animal studies on diesel PM) does not necessarily mean that there are no adverse health

implications from overall PM2.5 exposure. The health studies for the PM2.5 NAAQS are far more

encompassing than the limited animal studies used to develop the RfC for diesel exhaust, and,

also, the NAAQS applies to PM2.5 regardless of its composition. 

2.2.1.4.3 Ambient Exposures to Diesel Exhaust PM in Microenvironments 

One common microenvironment for ambient exposures to diesel exhaust PM is beside

freeways. Although freeway locations are associated mostly with highway rather than nonroad

diesel enignes, there are many similarities between highway and nonroad diesel emissions, as

discussed in the Diesel HAD. Also, similar spatial gradients in concentrations would be

expected where nonroad equipment is used. The California Air Resources Board (California

ARB) has measured elemental carbon near the Long Beach Freeway in 1993.191 Levels

measured ranged from 0.4 to 4.0 :g/m3 (with one value as high as 7.5 :g/m3) above background

levels. Microenvironments associated with nonroad engines would include construction zones. 

PM and elemental carbon samples are being collected by NESCAUM in the immediate area of

the nonroad engine operations (such as at the edge or fence line of the construction zone). 

Besides PM and elemental carbon levels, various toxics such as benzene, 1,3-butadiene,

formaldehyde, and acetaldehyde will be sampled. The results should be especially useful since

they focus on microenvironments affected by nonroad diesel engines.

Also, EPA is funding research in Fresno, California to measure indoor and outdoor PM

component concentrations in the homes of over 100 asthmatic children. Some of these homes

are located near agricultural, construction, and utility nonroad equipment operations. This work

will measure infiltration of elemental carbon and other PM components to indoor environments. 

The project also evaluates lung function changes in the asthmatic children during fluctuations in

exposure concentrations and compositions. This information may allow an evaluation of adverse

health effects associated with exposures to elemental carbon and other PM components from

on-road and nonroad sources.

2.2.2 Gaseous Air Toxics

Nonroad diesel engine emissions contain several substances known or suspected as human or

animal carcinogens, or have noncancer health effects. These other compounds include benzene,

1,3-butadiene, formaldehyde, acetaldehyde, acrolein, dioxin, and polycyclic organic matter

(POM). Mobile sources, including nonroad diesel engines, contribute significantly to total

emissions of these air toxics. All of these compounds were identified as national or regional

“risk” drivers in the 1996 NATA. That is, these compounds pose a significant portion of the

total inhalation cancer risk to a significant portion of the population. As discussed later in this

section, this final rule will significantly reduce these emissions.

Nonroad engines are major contributors to nationwide cancer risk from air toxic pollutants,

as indicated by the NATA 1996.192 In fact, this study and the National Toxics Inventory (NTI)

for 1996 are used throughout this section for toxics inventory information for nonroad sources.193
Final Regulatory Impact Analysis

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Also, a supplemental paper provides more detail on nonroad diesel exhaust.194 In addition, a

paper published by the Society of Automotive Engineers gives future projections to 2007 for

these air toxics.195 These references form the basis for much of what will be discussed in this

section.

Figure 2.2.2-1 summarizes the contribution of nonroad engines to average nationwide

lifetime upper bound cancer risk from outdoor sources in the 1996 NATA. These data do not

include the cancer risk from diesel PM since EPA does not presently have a potency for diesel

particulate/exhaust. Figure 2.2.2-2 depicts the nonroad engine contribution to average

nationwide inhalation exposure for benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and

acrolein. These compounds are all known or suspected human carcinogens, except for acrolein,

which has serious noncancer health effects. All of these compounds were identified as national

or regional risk drivers in the 1996 NATA, and mobile sources contribute significantly to total

emissions in NATA. As indicated previously, NATA exposure and risk estimates are based on

air dispersion modeling using the ASPEN model. Comparisons of the predicted concentrations

from the model to monitor data indicate good agreement for benzene, where the ratio of median

modeled concentrations to monitor values is 0.92, and results are within a factor of two at almost

90 percent of monitors.196 Comparisons with aldehydes indicate significantly lower modeled

concentrations than monitor values. Comparisons with 1,3-butadiene have not been done. 

Previously, extensive work was done on gaseous air toxic emissions including those from

nonroad diesel and reported in EPA’s 1993 Motor Vehicle-Related Air Toxics Study.197 This

final rule will reduce these emissions. Dioxin and some POM compounds have also been

identified as probable human carcinogens and are emitted by mobile sources, although nonroad

sources are less than 1% of total emissions for these compounds.
Air Quality, Health, and Welfare Effects

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Figure 2.2.2-1
0%

10%20%30%40%50%60%70%80%90%

100%

Benzene 1,3-Butadiene Form aldehyde Acetaldehyde Acrolein

Pollutant

Nationwide Average Contribution to Ambient Exposure

Expos ure All Sources = 1.40 

Expos ure All Sources = 0.06 

Expos ure All Sources= 0.96 

Expos ure All Sources = 0.71 

Expos ure All Sources = 0.10 

Figure 2.2.2-2

Contribution of Source Sectors to Average Annual Nationwide Inhalation Exposure to Air Toxic

Source: National Scale Air Toxics Assessment.
Air Quality, Health, and Welfare Effects

I

Leukemia is a blood disease in which the white blood cells are abnormal in type or number. Leukemia may be

divided into nonlymphocytic (granulocytic) leukemias and lymphocytic leukemias. Nonlymphocytic leukemia

generally involves the types of white blood cells (leukocytes) that are involved in engulfing, killing, and digesting

bacteria and other parasites (phagocytosis) as well as releasing chemicals involved in allergic and immune

responses. This type of leukemia may also involve erythroblastic cell types (immature red blood cells).

Lymphocytic leukemia involves the lymphocyte type of white bloods cell that are responsible for the immune

responses. Both nonlymphocytic and lymphocytic leukemia may, in turn, be separated into acute (rapid and fatal)

and chronic (lingering, lasting) forms. For example; in acute myeloid leukemia (AML) there is diminished

production of normal red blood cells (erythrocytes), granulocytes, and platelets (control clotting), which leads to

death by anemia, infection, or hemorrhage. These events can be rapid. In chronic myeloid leukemia (CML) the

leukemic cells retain the ability to differentiate (i.e., be responsive to stimulatory factors) and perform function; later

there is a loss of the ability to respond.

2-79

2.2.2.1 Benzene 

 Benzene is an aromatic hydrocarbon that is present as a gas in both exhaust and evaporative

emissions from mobile sources. Benzene accounts for one to two percent of the exhaust

hydrocarbons, expressed as a percentage of total organic gases (TOG), in diesel engines.198, 199

For gasoline-powered highway vehicles, the benzene fraction of TOG varies depending on

control technology (e.g., type of catalyst) and the levels of benzene and other aromatics in the

fuel, but is generally higher than for diesel engines, about three to five percent. The benzene

fraction of evaporative emissions from gasoline vehicles depends on control technology and fuel

composition and characteristics (e.g., benzene level and the evaporation rate) and is generally

about one percent.200

Nonroad engines account for 28 percent of nationwide emissions of benzene with nonroad

diesel accounting for about 3 percent in 1996. Mobile sources as a whole account for 78 percent

of the total benzene emissions in the nation. Nonroad sources as a whole account for an average

of about 17 percent of ambient benzene in urban areas and about 9 percent of ambient benzene in

rural areas across the U.S, in the 1996 NATA assessment. Of ambient benzene levels due to

mobile sources, 5 percent in urban and 3 percent in rural areas come from nonroad diesel engines

(see Figure 2.2.2-3).

The EPA’s IRIS database lists benzene as a known human carcinogen (causing leukemia) by

all routes of exposure.201 It is associated with additional health effects including chromosomal

changes in human and animal cells and increased proliferation of bone marrow cells in mice.202,

203 A number of adverse noncancer health effects including blood disorders, such as

preleukemia and aplastic anemia, have also been associated with long-term occupational

exposure to benzene.

Inhalation is the major source of human exposure to benzene in the occupational and nonoccupational setting. At least half of this exposure is attributable to gasoline vapors and

automotive emissions. Long-term inhalation occupational exposure to benzene has been shown

to cause cancer of the hematopoetic (blood cell) system. Among these are acute nonlymphocytic

leukemia,I

 chronic lymphocytic leukemia and possibly multiple myeloma 
Final Regulatory Impact Analysis

2-80

0 %

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Urban

Acrolein

Rural

Acrolein

Urban

Acetaldehyde

Rural

Acetaldehyde

Urban 

Benzene

Rural

Benzene

Urban

1,3-Butadiene

Rural

1,3-Butadiene

Urban

Diesel PM

Rural

Diesel PM

Urban

Formaldehyde

Rural

Formaldehyde

P o llu ta n t

L o c o m o tive s 9

C o m m e rcia l M a rin e 8

A irc ra ft7 

D ie s e l N o n ro a d E n g in e s 6 

4 -S tro k e G a s o lin e N o n ro a d 5

2 -S tro k e G a s o lin e N o n ro a d 4

H e a vy D u ty D ie s e l V e h ic le s 3

L ig h t D u ty D ie s e l2 

G a s o lin e h ig h w a y ve h ic le s 1

Figure 2.2.2-3

Contribution of Source Sectors to Total Average 

Nationwide Mobile Source Ambient Concentrations in 1996

(primary malignant tumors in the bone marrow), although the evidence for the latter has

decreased with more recent studies.204,205 Leukemias, lymphomas, and other tumor types have

been observed in experimental animals exposed to benzene by inhalation or oral administration. 

Exposure to benzene and/or its metabolites has also been linked with chromosomal changes in

humans and animals206 and increased proliferation of mouse bone marrow cells.207

The latest assessment by EPA places the excess risk of developing acute nonlymphocytic

leukemia at 2.2 × 10-6 to 7.8 × 10-6 per :g/m3

. In other words, there is a risk of about two to

eight excess leukemia cases in one million people exposed to 1 :g/m3 over a lifetime (70

years).208 This range of unit risks are the maximum likelihood estimate (MLE) calculated from

different exposure assumptions and dose-response models that are linear at low doses. It should

be noted that not enough information is known to determine the slope of the dose-response curve

at environmental levels of exposure and to provide a sound scientific basis to choose any

particular extrapolation model to estimate human cancer risk at low doses. In fact, recent data209

suggest that because genetic abnormalities occur at low exposure in humans, and the formation

of toxic metabolites plateaus above 25 ppm (80,000 :g/m3), the dose-response curve could be

supralinear below 25 ppm. Thus, EPA believes the use of a linear extrapolation model as a

default approach is appropriate. 
Air Quality, Health, and Welfare Effects

J

Pancytopenia is the reduction in the number of all three major types of blood cells

(erythrocytes, or red blood cells, thrombocytes, or platelets, and leukocytes, or white blood

cells). In adults, all three major types of blood cells are produced in the bone marrow of the

vertebra, sternum, ribs, and pelvis. The bone marrow contains immature cells, known as

multipotent myeloid stem cells, that later differentiate into the various mature blood cells. 

Pancytopenia results from a reduction in the ability of the red bone marrow to produce adequate

numbers of these mature blood cells.

KAplastic anemia is a more severe blood disease and occurs when the bone marrow ceases to

function, i.e.,these stem cells never reach maturity. The depression in bone marrow function

occurs in two stages - hyperplasia, or increased synthesis of blood cell elements, followed by

hypoplasia, or decreased synthesis. As the disease progresses, the bone marrow decreases

functioning. This myeloplastic dysplasia (formation of abnormal tissue) without acute leukemias

known as preleukemia. The aplastic anemia can progress to AML (acute mylogenous leukemia).

2-81

Based on average population exposures in the 1996 NATA Assessment, upper bound cancer

risk (using the upper end of the MLE range) from inhalation of benzene from ambient sources is

above 10 in a million across the entire United States. These results are best interpreted as upper

estimates of risks to typical individuals (provided exposure estimates are not underestimated). 

Thus most individuals are likely to have risks that are equal to or lower than these estimates, but

some individuals may have risks which are higher. EPA projects a median nationwide reduction

in ambient concentrations of benzene from mobile sources of about 46 percent between 1996 and

2007, as a result of current and planned control programs based on the analysis referenced earlier

examining these pollutants in the 1996 to 2007 time frame based on the analysis of hazardous air

pollutants in the 1996 to 2007 time frame referenced earlier.

A number of adverse noncancer health effects, blood disorders such as preleukemia and

aplastic anemia, have also been associated with long-term exposure to benzene.210, 211 People

with long-term occupational exposure to benzene have experienced harmful effects on the bloodforming tissues, especially in bone marrow. These effects can disrupt normal blood production

and suppress the production of important blood components, such as red and white blood cells

and blood platelets, leading to anemia (a reduction in the number of red blood cells), leukopenia

(a reduction in the number of white blood cells), or thrombocytopenia (a reduction in the number

of blood platelets, thus reducing the ability of blood to clot). Chronic inhalation exposure to

benzene in humans and animals results in pancytopenia,J a condition characterized by decreased

numbers of circulating erythrocytes (red blood cells), leukocytes (white blood cells), and

thrombocytes (blood platelets).212,213 Individuals that develop pancytopenia and have continued

exposure to benzene may develop aplastic anemia,K whereas others exhibit both pancytopenia

and bone marrow hyperplasia (excessive cell formation), a condition that may indicate a

preleukemic state.214, 215 It should be noted that these health effects occur in human and animal

studies at concentrations well above those typically found in the ambient environment. The most

sensitive noncancer effect observed in humans, based on current data, is the depression of the

absolute lymphocyte count in blood.216 EPA’s inhalation reference concentration (RfC, i.e., a

chronic exposure level presumed to be “without appreciable risk” for noncancer effects) for
Final Regulatory Impact Analysis

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benzene is 30 :g/m3, based on suppressed absolute lymphocyte counts as seen in humans under

occupational exposure conditions. 

The average inhalation exposure concentration to benzene from ambient sources in the 1996

NATA assessment is 1.4 :g/m3, and the 95th percentile exposure concentration is about twice as

high (U. S. EPA, 2002). However, the assessment does not account for localized hotspots. In

these hot spots, such as in close proximity to roadways, inhalation exposures from ambient

sources are likely to be much higher.217, 218, 219, 220, 221, 222 As mentioned above, nonroad diesel

engines are small but significant contributors to the ambient concentrations resulting in these

exposures.

2.2.2.2 1,3-Butadiene 

1,3-Butadiene is formed in engine exhaust by the incomplete combustion of fuel. It is not

present in engine evaporative emissions, because it is not present in any appreciable amount in

fuel. 1,3-butadiene accounts for less than one percent of total organic gas exhaust from mobile

sources.

Nonroad engines account for 18 percent of nationwide emissions of 1,3-butadiene in 1996

with nonroad diesel accounting for about 1.5 percent based on the NATA, NTI, and

supplemental information already discussed in the previous section. Mobile sources account for

63 percent of the total 1,3-butadiene emissions in the nation as a whole. Nonroad sources as a

whole account for an average of about 21 percent of ambient butadiene in urban areas and about

13 percent of ambient 1,3-butadiene in rural areas across the United States. Of ambient

butadiene levels due to mobile sources, 4 percent in urban and 2 percent in rural areas come from

nonroad diesel (see Figure 2.2.2-3). 

EPA earlier identified 1,3-butadiene as a probable human carcinogen in its IRIS database.223 

EPA characterized 1,3-butadiene as carcinogenic to humans by inhalation.224,225,226 The specific

mechanisms of 1,3-butadiene-induced carcinogenesis are not fully characterized. However, the

data strongly suggest that the carcinogenic effects are mediated by genotoxic metabolites of

1,3-butadiene. Animal data suggest that females may be more sensitive than males for cancer

effects; but more data are needed before reaching definitive conclusions on potentially sensitive

subpopulations. 

The cancer unit risk estimate is 0.08/ppm or 3×10-5 per :g/m3 (based primarily on linear

modeling and extrapolation of human data). In other words, it is estimated that approximately 30

persons in one million exposed to 1 :g/m3

 1,3-butadiene continuously for their lifetime (70

years) would develop cancer as a result of this exposure. The human incremental lifetime unit

cancer risk (incidence) estimate is based on extrapolation from leukemias observed in an

occupational epidemiologic study.227 This estimate includes a twofold adjustment to the

epidemiologic-based unit cancer risk applied to reflect evidence from the rodent bioassays

suggesting that the epidemiologic-based estimate may underestimate total cancer risk from

1,3-butadiene exposure in the general population. Based on average population exposure from

the 1996 NATA Assessment, upper bound lifetime cancer risk from inhalation of 1,3-butadiene
Air Quality, Health, and Welfare Effects

2-83

is above 10 in a million across the entire United States. Most individuals are likely to have risks

that are equal to or lower than these estimates, but some individuals may have risks which are

higher. EPA projects a median nationwide reduction in ambient concentrations of butadiene

from mobile sources of about 46 percent between 1996 and 2007, as a result of current and

planned control programs.

1,3-Butadiene also causes a variety of reproductive and developmental effects in mice; no

human data on these effects are available. The most sensitive effect was ovarian atrophy

observed in a lifetime bioassay of female mice.228 Based on this critical effect and the

benchmark concentration methodology, an RfC was calculated. This RfC for chronic health

effects was 0.9 ppb, or about 2 :g/m3. The average inhalation exposure from outdoor sources in

the 1996 NATA assessment was 0.08 :g/m3

, with a 95th percentile concentration of 0.2 :g/m3

(U. S. EPA, 2002). As is the case with benzene, in some hot spots, such as in close proximity to

roadways, inhalation exposures from ambient sources are likely to be much higher. As

mentioned above, nonroad diesel engines are small but significant contributors to the ambient

concentrations resulting in these exposures.

2.2.2.3 Formaldehyde 

Formaldehyde is the most prevalent aldehyde in engine exhaust. It is formed from

incomplete combustion of both gasoline and diesel fuel. In a recent test program that measured

toxic emissions from several nonroad diesel engines, ranging from 50 to 480 horsepower,

formaldehyde consistently accounted for well over 10 percent of total exhaust hydrocarbon

emissions.229 Formaldehyde accounts for far less of total exhaust hydrocarbon emissions from

gasoline engines, although the amount can vary substantially by duty cycle, emission control

system, and fuel composition. It is not found in evaporative emissions.

Nonroad engines account for 29 percent of nationwide emissions of formaldehyde in 1996,

with nonroad diesel accounting for about 22 percent based on the NATA, NTI, and supplemental

information already discussed. Mobile sources as a whole account for 56 percent of the total

formaldehyde emissions in the nation. Of ambient formaldehyde levels due to mobile sources,

37 percent in urban and 27 percent in rural areas come from nonroad diesel. Nonroad sources as

a whole account for an average of about 41 percent of ambient formaldehyde in urban areas and

about 10 percent of ambient formaldehyde in rural areas across the U.S, in the 1996 NATA

assessment. These figures are for tailpipe emissions of formaldehyde. Formaldehyde in the

ambient air comes not only from tailpipe (of direct) emissions but is also formed from

photochemical reactions of hydrocarbons. Mobile sources are responsible for well over 50

percent of total formaldehyde including both the direct emissions and photochemically formed

formaldehyde in the ambient air, according to the NATA for 1996. EPA projects a median

nationwide reduction in ambient concentrations of formaldehyde from mobile sources of about

43 percent between 1996 and 2007, as a result of current and planned control programs (Cook et

al., 2002).

EPA has classified formaldehyde as a probable human carcinogen based on limited evidence

for carcinogenicity in humans and sufficient evidence of carcinogenicity in animal studies, rats,
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mice, hamsters, and monkeys.230, 231 Epidemiological studies in occupationally exposed workers

suggest that long-term inhalation of formaldehyde may be associated with tumors of the

nasopharyngeal cavity (generally the area at the back of the mouth near the nose), nasal cavity,

and sinus.232 Studies in experimental animals provide sufficient evidence that long-term

inhalation exposure to formaldehyde causes an increase in the incidence of squamous (epithelial)

cell carcinomas (tumors) of the nasal cavity.233, 234, 235 The distribution of nasal tumors in rats

suggests that not only regional exposure but also local tissue susceptibility may be important for

the distribution of formaldehyde-induced tumors.236 Research has demonstrated that

formaldehyde produces mutagenic activity in cell cultures.237

The agency is currently conducting a reassessment of risk from inhalation exposure to

formaldehyde based on new information including a study by the CIIT Centers for Health

Research.238, 239 The CIIT information and other recent information, including recently published

epidemiological studies, are being reviewed and considered in the reassessment of the

formaldehyde unit risk estimate. The epidemiological studies examine the potential for

formaldehyde to cause cancer in organs other than those addressed by the CIIT model. We plan

to bring this reassessment to the Science Advisory Board in the summer of 2004.

Formaldehyde exposure also causes a range of noncancer health effects. At low

concentrations (e.g. 60 – 2500 :g/m3), irritation of the eyes (tearing of the eyes and increased

blinking) and mucous membranes is the principal effect observed in humans. At exposure to

1200-14,000 :g/m3, other human upper respiratory effects associated with acute formaldehyde

exposure include a dry or sore throat, and a tingling sensation of the nose. Sensitive individuals

may experience these effects at lower concentrations. Forty percent of formaldehyde-producing

factory workers reported nasal symptoms such as rhinitis (inflammation of the nasal membrane),

nasal obstruction, and nasal discharge following chronic exposure.240 In persons with bronchial

asthma, the upper respiratory irritation caused by formaldehyde can precipitate an acute

asthmatic attack, sometimes at concentrations below 6200 :g/m3.

241 Formaldehyde exposure

may also cause bronchial asthma-like symptoms in non-asthmatics.242, 243

Immune stimulation may occur following formaldehyde exposure, although conclusive

evidence is not available. Also, little is known about formaldehyde's effect on the central

nervous system. Several animal inhalation studies have been conducted to assess the

developmental toxicity of formaldehyde: The only exposure-related effect noted in these studies

was decreased maternal body weight gain at the high-exposure level. No adverse effects on

reproductive outcome of the fetuses that could be attributed to treatment were noted. An

inhalation reference concentration (RfC), below which long-term exposures would not pose

appreciable noncancer health risks, is not available for formaldehyde at this time. The Agency is

currently conducting a reassessment of risk from inhalation exposure to formaldehyde.

Average inhalation exposure from outdoor sources in the 1996 NATA assessment was 0.9

:g/m3

, with a 95th percentile concentration of 2.3 :g/m3.
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2.2.2.4 Acetaldehyde 

Acetaldehyde is a saturated aldehyde that is found in engine exhaust and is formed as a result

of incomplete combustion of both gasoline and diesel fuel. In a recent test program that

measured toxic emissions from several nonroad diesel engines, ranging from 50 to 480

horsepower, acetaldehyde consistently accounted for over 5 percent of total exhaust hydrocarbon

emissions (Southwest Research, 2002). Acetaldehyde accounts for far less of total exhaust

hydrocarbon emissions from gasoline engines, although the amount can vary substantially by

duty cycle, emission control system, and fuel composition. It is not a component of evaporative

emissions. 

Nonroad engines account for 43 percent of nationwide emissions of acetaldehyde with

nonroad diesel accounting for about 34 percent based on the NATA, NTI, and supplemental

information. Mobile sources as a whole account for 73 percent of the total acetaldehyde

emissions in the nation. Nonroad sources as a whole account for an average of about 36 percent

of ambient acetaldehyde in urban areas and about 21 percent of ambient acetaldehyde in rural

areas across the U.S, in the 1996 NATA assessment. Of ambient acetaldehyde levels due to

mobile sources, 24 percent in urban and 17 percent in rural areas come from nonroad diesel..

Also, acetaldehyde can be formed photochemically in the atmosphere. Counting both direct

emissions and photochemically formed acetaldehyde, mobile sources are responsible for the

major portion of acetaldehyde in the ambient air according to the NATA for 1996.

Based primarily on nonhuman animal model studies, acetaldehyde is classified by EPA as a

probable human carcinogen. Studies in experimental animals provide sufficient evidence that

long-term inhalation exposure to acetaldehyde causes an increase in the incidence of nasal

squamous cell carcinomas (epithelial tissue) and adenocarcinomas (glandular tissue).244, 245, 246, 247,

248 The upper confidence limit estimate of a lifetime extra cancer risk from continuous

acetaldehyde exposure is about 2.2 × 10-6 per :g/m3

. In other words, it is estimated that about 2

persons in one million exposed to 1 :g/m3 acetaldehyde continuously for their lifetime (70 years)

would develop cancer as a result of their exposure. The Agency is currently conducting a

reassessment of risk from inhalation exposure to acetaldehyde. Based on the current unit risk

and average population exposure from the 1996 NATA Assessment, upper bound cancer risk

from inhalation of acetaldehyde from ambient sources is above one in a million for more than

one hundred million Americans. Most individuals are likely to have risks that are equal to or

lower than these estimates, but some individuals may have risks which are higher. EPA projects

a median nationwide reduction in ambient concentrations of acetaldehyde from mobile sources

of about 36 percent between 1996 and 2007, as a result of current and planned control programs 

EPA’s IRIS database states that noncancer effects in studies with rats and mice showed

acetaldehyde to be moderately toxic by the inhalation, oral, and intravenous routes (EPA, 1988). 

Similar conclusions have been made by the California Air Resources Board.249 The primary

acute effect of exposure to acetaldehyde vapors is irritation of the eyes, skin, and respiratory

tract. At 

high concentrations, irritation and pulmonary effects can occur, which could facilitate the uptake

of other contaminants. Little research exists that addresses the effects of inhalation of
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acetaldehyde on reproductive and developmental effects. Long-term exposures should be kept

below the reference concentration of 9 :g/m3

 to avoid appreciable risk of these noncancer health

effects (EPA, 1988). The average inhalation exposure from outdoor sources in the 1996 NATA

assessment was 0.7 :g/m3

, with a 95th percentile concentration of 1.8 :g/m3 (U. S. EPA, 2002). 

As is the case with other air toxic compounds emitted by mobile sources, in some hot spots, such

as in close proximity to roadways, inhalation exposures are likely to be much higher. As

mentioned above, nonroad diesel engines are significant contributors to the ambient

concentrations resulting in these exposures.

Acetaldehyde has been associated with lung function decrements in asthmatics. In one

study, aerosolized acetaldehyde caused reductions in lung function and bronchoconstriction in

asthmatic subjects.250

2.2.2.5 Acrolein 

 In a recent test program that measured toxic emissions from several nonroad diesel engines,

ranging from 50 to 480 horsepower, acrolein accounted for about 0.5 to 2 percent of total

exhaust hydrocarbon emissions (Southwest Research, 2002). Acrolein accounts for far less of

total exhaust hydrocarbon emissions from gasoline engines, although the amount can vary

substantially by duty cycle, emission control system, and fuel composition. It is not a

component of evaporative emissions. 

Nonroad engines account for 25 percent of nationwide emissions of acrolein in 1996 with

nonroad diesel accounting for about 17.5 percent based on NATA, NTI, and the supplemental

information Mobile sources as a whole account for 43 percent of the total acrolein emissions in

the nation. Of ambient acrolein levels due to mobile sources, 28 percent in urban and 18 percent

in rural areas come form nonroad diesel according to NATA.

Acrolein is intensely irritating to humans when inhaled, with acute exposure resulting in 

substantial discomfort and sensory irritancy, mucus hypersecretion, and congestion. These

effects have been noted at acrolein levels ranging from 390 :g/m3

 to 990 :g/m3.

251 The intense

irritancy of this carbonyl has been demonstrated during controlled tests in human subjects who

suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure.252 The

irritant nature of acrolein provides the basis for the OSHA Permissible Exposure Limit (PEL) for

the workplace of 0.1 ppm (230 :g/m3) for an 8-hour exposure period. Acrolein has an odor

threshold of about 0.16 ppm (370 :g/m3),253 and acute inhalation exposure of humans to 10 ppm

(23,000 :g/m3) may result in death over a short period of time.254

Acrolein is an extremely volatile vapor, and it possesses considerable water solubility.255 As

such, it readily absorbs into airway fluids in the respiratory tract when inhaled. Lesions to the 

lungs and upper respiratory tract of rats, rabbits, and hamsters exposed to acrolein formed the

basis of the reference concentrations for inhalation (RfC) developed in 2003.256 The RfC of

acrolein is 0.02 :g/m3

. Average population inhalation exposures from the 1996 NATA

assessment are between 0.02 :g/m3 and 0.2 :g/m3. Thus, the hazard quotient (inhalation

exposure divided by the RfC) is greater than one for most of the U.S. population, indicating a
potential for adverse noncancer health effects.

The toxicological data base demonstrating the highly irritating nature of this vapor has been

consistent regardless of test species. Animal inhalation studies revealed early on that acrolein

induces damage throughout the respiratory tract at 0.7 ppm (1600 :g/m3) 257 in concordance with

data showing similar vapor uptake along isolated upper and lower lung regions of animals.258 At

levels that humans may encounter incidentally, acrolein has been shown to alter breathing

mechanics259, 260 and airway structure in animals261 as well as to interfere with macrophage

function and to alter microbial infectivity.262, 263, 264 As with many other irritants, acrolein has the

potential to induce adaptation to its own irritancy with repeated exposures to low concentrations

(1260 :g/m3)

265 -- a phenomenon consistent with the apparent human adaptation to the high

spikes of acrolein emanating in mainstream smoke from cigarettes.266 Hence, sensory awareness

of exposure to low levels of acrolein may diminish the apparent acute discomfort, while

exposure and the potential for longer term impacts persist. Prolonged exposure to acrolein has

been shown in animals to have an impact on pulmonary structure and function that can be

quantified.267 Over the range of 0.4 to 4.0 ppm (920 to 9200 :g/m3

) acrolein, distinct dosedependent changes in the degree of injury/disease are apparent, which have lung function

consequences. There are clear changes in the cell lining of the airways, including mucus cell

hyperplasia, as well as changes in the underlying supportive matrix of the airways. These

changes parallel changes in airway hyperreactivity (sometimes referred to as “twitchiness”). 

Such changes are similar to those observed with asthma. The structural changes in the larger

airways, likewise, are reminiscent of those associated with chronic exposure to tobacco smoke. 

Irritant effects in humans can be seen at levels encountered industrially that are below the

odor threshold and thus may be erroneously thought to be safe. Over time, these same

occupational levels of exposure in rats appear to alter airway structure and function. As those in

the workplace generally do not reflect the more sensitive groups of the public, the potential for

persistent, low level exposures eliciting health outcomes among susceptible groups, including

asthmatics who have sensitive airways is a concern.268

 EPA has concluded that the potential for carcinogenicity of acrolein cannot be determined

either for oral or inhalation routes of exposure.269

2.2.2.6 Polycyclic Organic Matter

POM is generally defined as a large class of chemicals consisting of organic compounds

having multiple benzene rings and a boiling point greater than 100 degrees C. Polycyclic

aromatic hydrocarbons (PAHs) are a chemical class that is a subset of POM. POM are naturally

occurring substances that are byproducts of the incomplete combustion of fossil fuels and plant

and animal biomass (e.g., forest fires). They occur as byproducts from steel and coke

productions and waste incineration. They also are a component of diesel PM emissions. As

mentioned in Section 2.1.2.1.2, many of the compounds included in the class of compounds

known as POM are classified by EPA as probable human carcinogens based on animal data. In

particular, EPA obtained data on 7 of the POM compounds, which we analyzed separately as a

class in the NATA for 1996. Nonroad engines account for only 1 percent of these 7 POM

compounds with total mobile sources responsible for only 4 percent of the total; most of the 7

POMs come from area sources. For total POM compounds, mobile sources as a whole are

responsible for only 1 percent. The mobile source emission numbers used to derive these
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inventories are based only on particulate-phase POM and do not include the semi-volatile phase

POM levels. Were those additional POMs included (which is now being done in the NATA for

1999), these inventory numbers would be substantially higher. A study of indoor PAH found that

concentrations of indoor PAHs followed the a similar trend as outdoor motor traffic, and that

motor vehicle traffic was the largest outdoor source of PAH.270

A recent study found that maternal exposures to polycyclic aromatic hydrocarbons (PAHs) in

a multiethnic population of pregnant women were associated with adverse birth outcomes,

including low birth weight, low birth length, and reduced head circumference.271

2.2.2.7 Dioxins

Exposure to dioxins are recognized by several authoritative bodies, including the

International Agency for Research on Cancer, the National Institute of Environmental Health

Sciences, the Agency for Toxic Substances and Disease Registry, EPA and some State health

and environmental agencies, to present a human health hazard for cancer and non-cancer effects. 

Recent studies have confirmed that very small amounts of dioxins are formed by and emitted

from diesel engines (both heavy-duty diesel trucks and nonroad diesel engines). In an inventory

for dioxin sources in 1995, such emissions accounted for only about 1 percent of total dioxin

emissions. These nonroad rules will have minimal impact on overall dioxin emissions since

these are a very small part of total emissions.

2.3 Ozone

This section reviews health and welfare effects of ozone and describes the air quality

information that forms the basis of our conclusion that ozone concentrations in many areas

across the country face a significant risk of exceeding the ozone standard into the year 2030. 

Information on air quality was gathered from a variety of sources, including monitored ozone

concentrations from 1999-2001, air quality modeling forecasts conducted for this rulemaking

and other state and local air quality information. 

Ground-level ozone, the main ingredient in smog, is formed by the reaction of volatile

organic compounds (VOCs) and nitrogen oxides (NOx) in the atmosphere in the presence of heat

and sunlight. These pollutants, often referred to as ozone precursors, are emitted by many types

of pollution sources, including highway and nonroad motor vehicles and engines, power plants,

chemical plants, refineries, makers of consumer and commercial products, industrial facilities,

and smaller “area” sources. VOCs are also emitted by natural sources such as vegetation. 

Oxides of nitrogen are emitted largely from motor vehicles, off-highway equipment, power

plants, and other sources of combustion. 

The science of ozone formation, transport, and accumulation is complex. Ground-level

ozone is produced and destroyed in a cyclical set of chemical reactions involving NOx, VOC,

heat, and sunlight. Many of the chemical reactions that are part of the ozone-forming cycle are

sensitive to temperature and sunlight. When ambient temperatures and sunlight levels remain
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high for several days and the air is relatively stagnant, ozone and its precursors can build up and

produce more ozone than typically would occur on a single high-temperature day. Further

complicating matters, ozone also can be transported into an area from pollution sources found

hundreds of miles upwind, resulting in elevated ozone levels even in areas with low VOC or

NOx emissions. As a result, differences in NOx and VOC emissions and weather patterns

contribute to daily, seasonal, and yearly differences in ozone concentrations and differences from

city to city. 

These complexities also have implications for programs to reduce ozone. For example,

relatively small amounts of NOx enable ozone to form rapidly when VOC levels are relatively

high, but ozone production is quickly limited by removal of the NOx. Under these conditions,

NOx reductions are highly effective in reducing ozone while VOC reductions have little effect. 

Such conditions are called “NOx-limited.” Because the contribution of VOC emissions from

biogenic (natural) sources to local ambient ozone concentrations can be significant, even some

areas where man-made VOC emissions are relatively low can be NOx-limited.

When NOx levels are relatively high and VOC levels relatively low, NOx forms inorganic

nitrates (i.e., particles) but relatively little ozone. Such conditions are called “VOC-limited.” 

Under these conditions, VOC reductions are effective in reducing ozone, but NOx reductions can

actually increase local ozone under certain circumstances. Even in VOC-limited urban areas,

NOx reductions are not expected to increase ozone levels if the NOx reductions are sufficiently

large. The highest levels of ozone are produced when both VOC and NOx emissions are present

in significant quantities on clear summer days.

Rural areas are almost always NOx-limited, due to the relatively large amounts of biogenic

VOC emissions in such areas. Urban areas can be either VOC- or NOx-limited, or a mixture of

both, in which ozone levels exhibit moderate sensitivity to changes in either pollutant.

Ozone concentrations in an area also can be lowered by the reaction of nitric oxide with

ozone, forming nitrogen dioxide (NO2); as the air moves downwind and the cycle continues, the

NO2 forms additional ozone. The importance of this reaction depends, in part, on the relative

concentrations of NOx, VOC, and ozone, all of which change with time and location. 

2.3.1 Health Effects of Ozone

Exposure to ambient ozone contributes to a wide range of adverse health effects, which are

discussed in detail in the EPA Air Quality Criteria Document for Ozone.272 Effects include lung

function decrements, respiratory symptoms, aggravation of asthma, increased hospital and

emergency room visits, increased medication usage, inflammation of the lungs, as well as a

variety of other respiratory effects. People who are particularly at risk for high ozone exposures

inclue healthy children and adults who are active outdoors. Susceptible subgroups include

children, people with respiratory disease, such as asthma, and people with unusual sensitivity to

ozone. More information on health effects of ozone is also available at 

http://www.epa.gov/ttn/naaqs/standards/ozone/s_03_index.html. 
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Based on a large number of scientific studies, EPA has identified several key health effects

caused when people are exposed to levels of ozone found today in many areas of the country. 

Short-term (1 to3 hours) and prolonged exposures (6 to 8 hours) to higher ambient ozone

concentrations have been linked to lung function decrements, respiratory symptoms, increased

hospital admissions and emergency room visits for respiratory problems.273, 274, 275, 276, 277, 278

Repeated exposure to ozone can make people more susceptible to respiratory infection and lung

inflammation and can aggravate preexisting respiratory diseases, such as asthma.279, 280, 281, 282, 283

It also can cause inflammation of the lung, impairment of lung defense mechanisms, and

possibly irreversible changes in lung structure, which over time could lead to premature aging of

the lungs and/or chronic respiratory illnesses, such as emphysema and chronic bronchitis.284, 285,

286, 287

Adults who are outdoors and active during the summer months, such as construction workers

and other outdoor workers, also are among those most at risk of elevated exposures.288 Thus, it

may be that children and outdoor workers are most at risk from ozone exposure because they

typically are active outside, playing and exercising, during the summer when ozone levels are

highest.289, 290 For example, summer camp studies in the Eastern United States and Southeastern

Canada have reported significant reductions in lung function in children who are active

outdoors.291, 292, 293, 294, 295, 296, 297, 298 Further, children are more at risk of experiencing health effects

than adults from ozone exposure because their respiratory systems are still developing. These

individuals, as well as people with respiratory illnesses such as asthma, especially asthmatic

children, can experience reduced lung function and increased respiratory symptoms, such as

chest pain and cough, when exposed to relatively low ozone levels during prolonged periods of

moderate exertion.299, 300, 301, 302 

The 8-hour NAAQS is based on well-documented science demonstrating that more people

are experiencing adverse health effects at lower levels of exertion, over longer periods, and at

lower ozone concentrations than addressed by the 1-hour ozone standard.303 Attaining the 8-hour

standard greatly limits ozone exposures of concern for the general population and populations

most at risk, including children active outdoors, outdoor workers, and individuals with preexisting respiratory disease, such as asthma.

There has been new research that suggests additional serious health effects beyond those that

had been know when the 8-hour ozone standard was set. Since 1997, over 1,700 new health and

welfare studies have been published in peer-reviewed journals.304 Many of these studies have

investigated the impact of ozone exposure on such health effects as changes in lung structure and

biochemistry, inflammation of the lungs, exacerbation and causation of asthma, respiratory

illness-related school absence, hospital and emergency room visits for asthma and other

respiratory causes, and premature mortality. EPA is currently in the process of evaluating these

and other studies as part of the ongoing review of the air quality criteria and NAAQS for ozone.

A revised Air Quality Criteria Document for Ozone and Other Photochemical Oxidants will be

prepared in consultation with the EPA’s Clean Air Scientific Advisory Committee (CASAC).

Key new health information falls into four general areas: development of new-onset asthma,

hospital admissions for young children, school absence rate, and premature mortality. Examples
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L

In communities with mean 8-hour ozone concentration of 59.6 ppb, the relative risk of developing asthma in

children playing three or more sports was 3.3. (95% CI 1.9 - 5.8) compared with children playing no sports.

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of new studies in these areas are briefly discussed below.

Aggravation of existing asthma resulting from short-term ambient ozone exposure was

reported prior to the 1997 decision and has been observed in studies published since.305, 306 More

recent studies now suggest a relationship between long-term ambient ozone concentrations and

the incidence of new-onset asthma. In particular, such a relationship in adult males (but not in

females) was reported by McDonnell et al. (1999).307 Subsequently, McConnell et al. (2002)

reported that incidence of new diagnoses of asthma in children is associated with heavy exercise

in communities with high concentrations (i.e., mean 8-hour concentration of 59.6 ppb) of

ozone.308 This relationship was documented in children who played 3 or more sports and was

not statistically significant for those children who played one or two sports.L The larger effect of

high activity sports than low activity sports and an independent effect of time spent outdoors also

in the higher ozone communities strengthened the inference that exposure to ozone may modify

the effect of sports on the development of asthma in some children.

Previous studies have shown relationships between ozone and hospital admissions in the

general population. A new study in Toronto reported a significant relationship between 1-hour

maximum ozone concentrations and respiratory hospital admissions in children under two.309

Given the relative vulnerability of children in this age category, we are particularly concerned

about the findings from the literature on ozone and hospital admissions.

Increased respiratory disease that are serious enough to cause school absences has been

associated with 1-hour daily maximum and 8-hour average ozone concentrations in studies

conducted in Nevada in kindergarten to 6th grade310 and in Southern California in grades 4 to 6.311

These studies suggest that higher ambient ozone levels may result in increased school

absenteeism.

The ambient air pollutant most clearly associated with premature mortality is PM, with

dozens of studies reporting such an association. However, repeated ozone exposure may be a

contributing factor for premature mortality, causing an inflammatory response in the lungs that

may predispose elderly and other sensitive individuals to become more susceptible to the adverse

health effects of other air pollutants, such as PM.312, 313 Although the findings in the past have

been mixed, the findings of three recent analyses suggests that ozone exposure is associated with

increased mortality. Although the National Morbidity, Mortality, and Air Pollution Study

(NMMAPS) did not find an effect of ozone on total mortality across the full year, Samet et al.

(2000), who conducted the NMMAPS study, did report an effect after limiting the analysis to

summer when ozone levels are highest.314 Similarly, Thurston and Ito (1999) have reported

associations between ozone and mortality.315 Toulomi et al., (1997) reported that 1-hour

maximum ozone levels were associated with daily numbers of deaths in 4 cities (London,

Athens, Barcelona, and Paris), and a quantitatively similar effect was found in a group of 4

additional cities (Amsterdam, Basel, Geneva, and Zurich).316
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As discussed in Section 2.1 with respect to PM studies, the Health Effects Institute (HEI)

reported findings by health researchers that have raised concerns about aspects of the statistical

methodology used in a number of older time-series studies of short-term exposures to air

pollution and health effects.317

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS

As shown earlier in Figure 2-1, unhealthy ozone concentrations (i.e., those exceeding the 8-

hour standard, which is requisite to protect public health with an adequate margin of safety)

occur over wide geographic areas, including most of the nation’s major population centers. 

These areas include much of the eastern half of the United States and large areas of California. 

Nonroad engines contribute a substantial fraction of ozone precursors in metropolitan areas. 

Emission reductions from this rule will assist nonattainment and maintenance areas in

reaching the standard by each area’s respective attainment date and help maintaining the

standard in the future. We discuss both the 1-hour and the 8-hour NAAQS, which are based on

air quality measurements, called design values and other factors.

An ozone design value is the concentration that determines whether a monitoring site meets

the NAAQS for ozone. Because of the way they are defined, design values are determined based

on 3 consecutive-year monitoring periods. For example, an 8-hour design value is the fourth

highest daily maximum 8-hour average ozone concentration measured over a three-year period at

a given monitor. The full details of these determinations (including accounting for missing

values and other complexities) are given in Appendices H and I of 40 CFR Part 50. As discussed

in these appendices, design values are truncated to whole part per billion (ppb). Due to the

precision with which the standards are expressed (0.08 parts per million (ppm) for the 8-hour), a

violation of the 8-hour standard is defined as a design value greater than or equal to 0.085 ppm. 

For a county, the design value is the highest design value from among all the monitors with

valid design values within that county. If a county does not contain an ozone monitor, it does

not have a design value. Thus, our analysis may underestimate the number of counties with

design values above the level of NAAQS. For the purposes of identifying areas likely to have an

ozone problem in the future, we used the 1999-2001 because these data were the most current at

the time we performed the modeling (i.e, 2003 data were not yet available). In the recent

designations, the 2001-2003 data were used. The 1999-2001, the 2000-2002, and the 2001-2003

sets of design values are listed in the AQ TSD, which is available in the docket to this rule.

A number of States and local areas in their public comments discussed their need for the rule

to reduce ozone levels. The California Air Resources Board noted, “Adoption of the proposed

regulations outlined in the NPRM by US EPA is necessary for the protection of public health in

California to comply with air quality standards.” In addition, the South Coast Air Quality

Management District (SCAQMD) requested more federal reductions, citing their need: “In 2010,

federal sources including non-road engines, ships, trains, aircraft, and 49-state vehicles would

contribute to 34% of the NOx emissions in the South Coast Air Basin (Basin). Of this amount,
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non-road engines account for 14% or 108 tons per day of NOx in the Basin. ... without

aggressive regulations which would achieve substantial reductions by 2010 for non-road engines,

as well as other sources under federal jurisdiction, attainment of the federal 1-hour ozone and

PM2.5 standards could be seriously jeopardized. ...Where EPA has exclusive or nearly exclusive

jurisdiction, EPA must achieve the maximum feasible reductions to enable states to attain federal

standards. Therefore, it is incumbent upon EPA to craft its proposed regulation in a manner that

would provide maximum emissions benefit in the near term as well as on a long-term basis.”

The City of Houston commented that as the largest city with a severe 1-hour ozone

nonattainment area and a near-nonattainment area for PM that they had a need for “huge

emission reductions from all sectors in the 8-county area to reach attainment... While diesel

engines constitute less than 25% of the city’s vehicle fleet, they account for over 40 percent of

our mobile source emissions and almost 35% of our overall emissions. The non-road portion of

our fleet alone produces 26% of our mobile source, and 21% of the city’s overall emissions.” 

Comments from Illinois Lieutenant Governor comments supported the need for reductions in

ozone: “Working to relieve the affects of asthma is of particular importance in Illinois where the

mortality rate is the highest in the country and is the number one reason for children missing

school.”

Similarly, New York State Department of Environmental Conservation “strongly supports

EPA’s proposed rule to control emissions of air pollution from nonroad diesel engines and fuels. 

We believe that these regulations, when fully implemented, will provide substantial

environmental and public health benefits. ..Nonroad diesel equipment is a major source of NOx,

SOx and PM emissions and this proposal will help the state of New York attain and maintain the

NAAQS for ozone and PM.” 

2.3.2 Attainment and Maintenance of the 1-Hour and 8-Hour Ozone NAAQS

As shown earlier in Figure 2-1, nonattainment with the ozone NAAQS occur over wide

geographic areas, including most of the nation’s major population centers. These areas include

much of the eastern half of the United States, industrial midwest, and large areas of California. 

Nonroad diesel engines contribute a substantial fraction of ozone precursors in metropolitan

areas. 

Emission reductions from this rule will assist nonattainment and maintenance areas in

reaching the standard by each area’s respective attainment date and help maintaining the

standard in the future. We discuss both the 1-hour, an exceedance-based standard, and the 8-

hour NAAQS, which is based on air quality measurements, called design values, as well as other

factors.

An ozone design value is a calculated ozone concentration that is used in determining

whether a monitoring site meets the NAAQS. Because of the way they are defined, design

values are determined based on 3 consecutive-year monitoring periods. For example, an 8-hour
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ozone design value is the average of the annual fourth highest daily maximum 8-hour average

ozone concentrations measured over a three-year period at a given monitor. Determination of

whether an area attains the 1-hour NAAQS is based on the number of “exceedances” of the

standard over a three year period. The full details of these determinations (including accounting

for missing values and other complexities) are given in Appendices H and I of 40 CFR Part 50.

As discussed in these appendices, design values are truncated to whole part per billion (ppb). 

Due to the precision with which the standards are expressed (0.08 parts per million (ppm) for the

8-hour), a violation of the 8-hour standard is defined as a design value greater than or equal to

0.085 ppm. 

For a county, the design value is the highest design value from among all the monitors with

valid design values within that county. A nonattainment area may contain counties both with

and without monitors. The highest design value of any county monitor representing the

nonattainment area would determine the design value for that nonattainment county. For the

purposes of identifying areas likely to have an ozone problem in the future, we performed

modeling and used the 1999-2001 air quality data as described below because these data were

the most current at the time we performed the modeling (i.e, 2003 data were not yet available). 

In the 8-hour designations and classifications, we used the 2001-2003 data in addition to

considering other factors. The 1999-2001, the 2000-2002, and the 2001-2003 sets of design

values are listed in the AQ TSD, which is available in the docket to this rule.

A number of States and local areas in their public comments discussed their need for the rule

to reduce ozone levels. For example, the California Air Resources Board noted, “Adoption of

the proposed regulations outlined in the NPRM by US EPA is necessary for the protection of

public health in California to comply with air quality standards.” In addition, the South Coast

Air Quality Management District (SCAQMD) requested more federal reductions, citing their

need: “In 2010, federal sources including non-road engines, ships, trains, aircraft, and 49-state

vehicles would contribute to 34% of the NOx emissions in the South Coast Air Basin (Basin). 

Of this amount, non-road engines account for 14% or 108 tons per day of NOx in the Basin. ...

without aggressive regulations which would achieve substantial reductions by 2010 for non-road

engines, as well as other sources under federal jurisdiction, attainment of the federal 1-hour

ozone and PM2.5 standards could be seriously jeopardized. ...Where EPA has exclusive or nearly

exclusive jurisdiction, EPA must achieve the maximum feasible reductions to enable states to

attain federal standards. Therefore, it is incumbent upon EPA to craft its proposed regulation in

a manner that would provide maximum emissions benefit in the near term as well as on a longterm basis.”

The City of Houston commented that as the largest city with a severe 1-hour ozone

nonattainment area and a near-nonattainment area for PM that they had a need for “huge

emission reductions from all sectors in the 8-county area to reach attainment... While diesel

engines constitute less than 25% of the city’s vehicle fleet, they account for over 40 percent of

our mobile source emissions and almost 35% of our overall emissions. The non-road portion of

our fleet alone produces 26% of our mobile source, and 21% of the city’s overall emissions.” 
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Comments from Illinois Lieutenant Governor comments supported the need for reductions in

ozone: “Working to relieve the effects of asthma is of particular importance in Illinois where the

mortality rate is the highest in the country and is the number one reason for children missing

school.”

Similarly, New York State Department of Environmental Conservation “strongly supports

EPA’s proposed rule to control emissions of air pollution from nonroad diesel engines and fuels. 

We believe that these regulations, when fully implemented, will provide substantial

environmental and public health benefits. ..Nonroad diesel equipment is a major source of NOx,

SOx and PM emissions and this proposal will help the state of New York attain and maintain the

NAAQS for ozone and PM.” 

2.3.2.1 1-Hour Ozone Nonattainment and Maintenance Areas and Concentrations

Currently, there are 110 million people living in 53 1-hour ozone nonattainment areas

covering 219 counties.318 Of these areas, there are one extreme and 13 severe 1-hour ozone

nonattainment areas with a total affected population of 74 million as shown in Table 2.3-1. We

focus on these classifications of designated areas because the timing of their attainment dates

relates to the timing of the new emission standards. Five severe 1-hour ozone nonattainment

areas have attainment dates of November 15, 2007. The Los Angeles South Coast Air Basin is

designated as an extreme nonattainment area and has a compliance date of November 15, 2010. 

While all of these areas are expected to be in attainment before the emission reductions from this

rule are fully realized, these reductions will be important to assist these areas in achieving the

health and welfare protections of the standards and maintaining compliance with air quality

standards. 
Final Regulatory Impact Analysis

MTypically, county design values (and thus exceedances) are consolidated where possible into design values for

consolidated metropolitan statistical areas (CMSA) or metropolitan statistical areas (MSA). Accordingly, the design

value for a metropolitan area is the highest design value among the included counties, and counties that are not in

metropolitan areas would be treated separately. However, for this section, we examined data on a county basis, not

consolidating into CMSA or MSA. Designated nonattainment areas may contain more than one county, and some of

these counties have experienced recent exceedances, as indicated in the table. Further, the analysis is limited to areas

with ozone monitors.

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 Table 2.3-1

1-Hour Ozone Extreme and Severe Nonattainment Areas

Nonattainment Area Attainment 

Date

2000 

Population

(millions)

2000-2002 

Measured 

Violation?

Los Angeles South Coast Air Basin,

CAa

November 15, 2010a 14.6 Yes

Chicago-Gary-Lake County, IL-IN November 15, 2007 8.8 Yes

Houston-Galveston-Brazoria, TX November 15, 2007 4.7 Yes

Milwaukee-Racine, WI November 15, 2007 1.8 Yes

New York-New Jersey-Long Island,

NY-NJ-CT

November 15, 2007 19.2 Yes

Southeast Desert Modified AQMA, CA November 15, 2007 1.0 Yes

Atlanta, GA 2005 3.7 Yes

Baltimore, MD 2005 0.8 Yes

Baton Rouge, LA 2005 0.6 Yes

Philadelphia-Wilmington-Trenton, PANJ-DE-MD2005 6.3 Yes

Sacramento, CA 2005 2.0 Yes

San Joaquin Valley, CA 2005 3.2 Yes

Ventura County, CA 2005 0.7 No

Washington, DC-MD-VA 2005 4.5 Yes

Total Population 74million

a

 Extreme 1-Hour nonattainment areas. All other areas are severe nonattainment areas.

Source: US EPA, Air Quality TSD 2004

Many 1-hour ozone nonattainment areas continue to experience exceedances. 

Approximately 53 million people are living in 73 counties with measured air quality violating

the 1-hour NAAQS in 2000-2002.M See the AQ TSD for more details about the counties and

populations experiencing various levels of measured 1-hour ozone concentrations.
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The ability of states to maintain the ozone NAAQS once attainment is reached has proved

challenging, and the recent recurrence of violations of the NAAQS in some other areas increases

the Agency’s concern about continuing maintenance of the standard. Recurrent nonattainment is

especially problematic for areas where high population growth rates lead to significant annual

increases in vehicle trips and VMT. Moreover, ozone modeling conducted for this rule predicted

exceedances in 2020 and 2030 (without additional controls), which adds to the Agency’s

uncertainty about the prospect of continued attainment for these areas. The reductions from this

final rule will help areas attain and maintain the 1-hour standards.

2.3.2.2 8-Hour Ozone Levels: Current Nonattainment and Future Concentrations

EPA has recently designated nonattainment areas for the 8-hour NAAQS by calculating air

quality design values (using 2001-2003 measurements) and considering other factors

(www.epa.gov/ozonedesignations). 

As described above in Section 2.3.1, the 8-hour NAAQS is based on well-documented

science demonstrating that more people are experiencing adverse health effects at lower levels of

exertion, over longer periods, and at lower ozone concentrations than addressed by the 1-hour

ozone standard.319 The 8-hour standard greatly limits ozone exposures of concern for the general

population and sensitive populations. This section describes the current nonattainment with the

8-hour ozone NAAQS and describes our modeling to predict future 8-hour ozone concentrations,

which demonstrate a need for reductions in emissions from this final rule.

2.3.2.2.1 Current 8-Hour Ozone Nonattainment

All or part of 474 counties are in nonattainment, as shown in Figure 2-1, for either failing to

meet the 8-hour ozone NAAQS or for contributing to poor air quality in a nearby area. About

159 million people live in the 126 areas that do not meet the 8-hour NAAQS. Based upon the

measured data from years 2001-2003 and other factors, these areas were recently designated and

classified by EPA. ). The nonattainment areas covered under subpart 1 will be required to attain

the standard no later than 5 years after designation and, in limited circumstances, they may

apply for an additional extension of up to 5 years (e.g., 2009 to 2014). The areas classified under

subpart 2 have attainment dates ranging from up to 3 years for marginal areas (2007) to up to 20

years for extreme areas (2024). . 

Table 2.3-2 presents the areas, their design values for the 8-hour and 1-hour standards and their

category or classification. The reductions from this rule will contribute to these areas’ overall

strategy to attain and maintain the standards.
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Table 2.3-2. 8-Hour Ozone Nonattainment Areas

EPA Design Value ppb (2001-2003 data)

RegionArea Name 8-Hr 1-Hr Category/Classification

2 Albany-Schenectady-Troy, NY 87 115 Subpart 1 

5 Allegan Co, MI 97 115 Subpart 1 

3 Allentown-Bethlehem-Easton, PA 91 114 Subpart 1 

3 Altoona, PA 85 107 Subpart 1 

9 Amador and Calaveras, CA(Central Mtn Co) 91 117 Subpart 1 

4 Atlanta, GA 91 125 Subpart 2 Marginal 

3 Baltimore, MD 103 143 Subpart 2 Moderate 

6 Baton Rouge, LA 86 131 Subpart 2 Marginal 

6 Beaumont-Port Arthur, TX 91 129 Subpart 2 Marginal 

5 Benton Harbor, MI 91 117 Subpart 1 

5 Benzie Co, MI 88 116 Subpart 1 

3 Berkeley and Jefferson Counties, WV 86 105 EAC Subpart 1 

4 Birmingham, AL 87 113 Subpart 1 

1 Boston-Lawrence-Worcester (E. MA), MA 95 124 Subpart 2 Moderate 

1 Boston-Manchester-Portsmouth(SE),NH* 95 124 Subpart 2 Moderate 

2 Buffalo-Niagara Falls, NY 99 116 Subpart 1 

5 Canton-Massillon, OH 90 109 Subpart 1 

5 Cass Co, MI 93 124 Subpart 2 Moderate 

3 Charleston, WV 86 107 Subpart 1 

4 Charlotte-Gastonia-Rock Hill, NC-SC 100 129 Subpart 2 Moderate 

4 Chattanooga, TN-GA 88 113 Subpart 1 

5 Chicago-Gary-Lake County, IL-IN 101 134 Subpart 2 Moderate 

9 Chico, CA 89 102 Subpart 1 

5,4 Cincinnati-Hamilton, OH-KY-IN 96 118 Subpart 1 

4 Clarksville-Hopkinsville, TN-KY 85 99 Subpart 1 

3 Clearfield and Indiana Cos, PA 90 106 Subpart 1 

5 Cleveland-Akron-Lorain, OH 103 128 Subpart 2 Moderate 

4 Columbia, SC 89 108 EAC Subpart 1 

5 Columbus, OH 95 117 Subpart 1 

6 Dallas-Fort Worth, TX 100 135 Subpart 2 Moderate 

5 Dayton-Springfield, OH 90 117 Subpart 1 

8 Denver-Boulder-Greeley-Ft Collins-Love., CO 87 114 EAC Subpart 1 

5 Detroit-Ann Arbor, MI 97 127 Subpart 2 Moderate 

5 Door Co, WI 94 113 Subpart 1 

3 Erie, PA 92 114 Subpart 1 

2 Essex Co (Whiteface Mtn) NY 91 113 Subpart 1 

5 Evansville, IN 85 106 Subpart 1 

4 Fayetteville, NC 87 108 EAC Subpart 1 

5 Flint, MI 90 103 Subpart 1 
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EPA Design Value ppb (2001-2003 data)

RegionArea Name 8-Hr 1-Hr Category/Classification

5 Fort Wayne, IN 88 106 Subpart 1 

3 Franklin Co, PA 93 114 Subpart 1 

3 Frederick Co, VA 85 106 EAC Subpart 1 

3 Fredericksburg, VA* 99 140 Subpart 2 Moderate 

5 Grand Rapids, MI 89 110 Subpart 1 

1 Greater Connecticut, CT 95 139 Subpart 2 Moderate 

5 Greene Co, IN 88 102 Subpart 1 

3 Greene Co, PA 89 107 Subpart 1 

4 Greensboro-Winston Salem-High Point, NC 93 121 EAC Subpart 2 Moderate 

4 Greenville-Spartanburg-Anderson, SC 87 114 EAC Subpart 1 

1 Hancock, Knox, Lincoln and Waldo Cos, ME 94 120 Subpart 1 

3 Harrisburg-Lebanon-Carlisle, PA 88 111 Subpart 1 

4 Haywood and Swain (Great Smoky NP), NC 85 104 Subpart 1 

4 Hickory-Morganton-Lenoir, NC 88 105 EAC Subpart 1 

6 Houston-Galveston-Brazoria, TX 102 175 Subpart 2 Moderate 

3,4 Huntington-Ashland, WV-KY 91 115 Subpart 1 

5 Huron Co, MI 87 109 Subpart 1 

9 Imperial Co, CA 87 142 Subpart 2 Marginal 

5 Indianapolis, IN 96 119 Subpart 1 

5 Jackson Co, IN 85 100 Subpart 1 

2 Jamestown, NY 94 115 Subpart 1 

2 Jefferson Co, NY 97 121 Subpart 2 Moderate 

4 Johnson City-Kingsport-Bristol, TN 86 110 EAC Subpart 1 

3 Johnstown, PA 87 106 Subpart 1 

5 Kalamazoo-Battle Creek, MI 86 102 Subpart 1 

3 Kent and Queen Anne’s Co, MD 95 122 Subpart 2 Moderate 

9 Kern Co (Eastern Kern), CA 98 118 Subpart 1 

5 Kewaunee Co, WI 93 110 Subpart 1 

4 Knoxville, TN 92 114 Subpart 1 

5 La Porte Co, IN 93 135 Subpart 2 Moderate 

3 Lancaster, PA 92 124 Subpart 2 Moderate 

5 Lansing-East Lansing, MI 86 102 Subpart 1 

9 Las Vegas, NV 86 107 Subpart 1 

5 Lima, OH 89 108 Subpart 1 

9 Los Angeles South Coast Air Basin, CA 131 180 Subpart 2 Severe 17 

9 Los Angeles-San Bernardino (W Mojave),CA 106 138 Subpart 2 Moderate 

4,5 Louisville, KY-IN 92 120 Subpart 1 

4 Macon, GA 86 113 Subpart 1 

3 Madison and Page Cos (Shenandoah NP), VA 87 104 Subpart 1 

5 Manitowoc Co, WI 90 110 Subpart 1 

9 Mariposa and Tuolumne Cos, CA (S. Mtn Cos) 91 113 Subpart 1 
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EPA Design Value ppb (2001-2003 data)

RegionArea Name 8-Hr 1-Hr Category/Classification

5 Mason Co, MI 89 114 Subpart 1 

4,6 Memphis, TN-AR 92 126 Subpart 2 Moderate 

5 Milwaukee-Racine, WI 101 134 Subpart 2 Moderate 

5 Muncie, IN 88 104 Subpart 1 

4 Murray Co (Chattahoochee Nat Forest), GA 85 103 Subpart 1 

5 Muskegon, MI 95 121 Subpart 2 Moderate

4 Nashville, TN 86 107 EAC Subpart 1 

9 Nevada Co, CA (Western Portion) 98 116 Subpart 1 

2,1 New York-N. N -Long Island,NY-NJ-CT 102 146 Subpart 2 Moderate 

3 Norfolk-Virginia Beach-Newport News,VA 90 121 Subpart 2 Marginal 

3,5 Parkersburg-Marietta, WV-OH 87 113 Subpart 1 

3,2 Philadelphia-Wilmin-Atl.City,PA-NJ-MD-DE 106 133 Subpart 2 Moderate 

9 Phoenix-Mesa, AZ 87 111 Subpart 1 

3 Pittsburgh-Beaver Valley, PA 94 120 Subpart 1 

1 Portland, ME 91 126 Subpart 2 Marginal 

2 Poughkeepsie, NY 94 126 Subpart 2 Moderate 

1 Providence (All RI), RI 95 130 Subpart 2 Moderate 

4 Raleigh-Durham-Chapel Hill, NC 94 118 Subpart 1 

3 Reading, PA 91 116 Subpart 1 

3 Richmond-Petersburg, VA 94 131 Subpart 2 Moderate 

9 Riverside Co, (Coachella Valley), CA 108 133 Subpart 2 Serious 

3 Roanoke, VA 85 107 EAC Subpart 1 

2 Rochester, NY 88 110 Subpart 1 

4 Rocky Mount, NC 89 106 Subpart 1 

9 Sacramento Metro, CA 107 143 Subpart 2 Serious 

6 San Antonio, TX 89 119 EAC Subpart 1 

9 San Diego, CA 93 118 Subpart 1 

9 San Francisco Bay Area, CA 86 123 Subpart 2 Marginal 

9 San Joaquin Valley, CA 115 151 Subpart 2 Serious 

3 Scranton-Wilkes-Barre, PA 86 108 Subpart 1 

5 Sheboygan, WI 100 124 Subpart 2 Moderate 

5 South Bend-Elkhart, IN 93 116 Subpart 1 

1 Springfield (Western MA), MA 94 132 Subpart 2 Moderate 

7,5 St Louis, MO-IL 92 122 Subpart 2 Moderate 

3 State College, PA 88 109 Subpart 1 

5,3 Steubenville-Weirton, OH-WV 86 113 Subpart 1 

9 Sutter Co, CA (Sutter Buttes) 88 113 Subpart 1 

5 Terre Haute, IN 87 108 Subpart 1 

3 Tioga Co, PA 86 102 Subpart 1 

5 Toledo, OH 93 112 Subpart 1 

9 Ventura Co, CA 95 124 Subpart 2 Moderate 
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EPA Design Value ppb (2001-2003 data)

RegionArea Name 8-Hr 1-Hr Category/Classification

3 Washington Co (Hagerstown), MD 86 109 EAC Subpart 1 

3 Washington, DC-MD-VA 99 140 Subpart 2 Moderate 

3,5 Wheeling, WV-OH 87 111 Subpart 1 

3 York, PA 89 114 Subpart 1 

5,3 Youngstown-Warren-Sharon, OH-PA 95 118 Subpart 1 

Boston-Manchester-Portsmouth(SE),NH has the same classification as Boston-LawrenceWorcester (E. MA), MA. Fredericksburg, VA has the same classification as Washington,

DC-MD-VA.

The level of the 8-hour ozone (O3) National Ambient Air Quality Standards (NAAQS) is 0.08

parts per million (ppm). The air quality design value for the 8-hour O3 NAAQS is the 3-year

average of the annual 4th highest daily maximum 8-hour average O3 concentration. The 8-hour

O3 NAAQS is not met when the 8-hour ozone design value is greater than 0.08 ppm (85 parts per

billion [ppb] rounds up). Therefore, an area with a design value of 85 ppb does not meet the

NAAQS. 

An area with a 1-hour design value of 120 ppb or lower is in a Subpart 1 category and must

attain the standard by up to 5 years after designation and they may apply for an extension of up

to 5 years. 

Areas classified under Subpart 2 must attain the standards by the following attainment dates: 

• Marginal up to 3 years, 

• Moderate up to 6 years, 

• Serious up to 9 years,

• Severe up to 15 or 17 years,

• Extreme up to 20 years.
Final Regulatory Impact Analysis

NBecause of the complexities and non-linear relationships in the air quality modeling, we are not attempting to

make any adjustments to the results. Instead, we are presenting the results for the preliminary control option with

information about how the emission changes relate to what was modeled.

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2.3.2.2.2 Risk of Future 8-Hour Ozone Violations

Our air quality modeling shows that there will continue to be a need for reductions in ozone

concentrations in the future without additional controls. In this section we describe the air

quality modeling including the non-emission inventory inputs. (See Chapter 3.6 summarizes the

emission inventory inputs.) We then discuss the results of the modeling for baseline conditions

absent additional control of nonroad diesel engines. 

We have also used our air quality modeling to estimate the change in future ozone levels that

would result from reductions in emissions from nonroad diesel engines. For this propose rule we

modeled a preliminary control scenario that illustrates the likely emission reductions. Because

of the substantial lead time to prepare the complex air quality modeling analyses, it was

necessary to develop a control options early in the proposal process based on our best judgment

at that time. Based on public comment and as additional data regarding technical feasibility and

other factors became available, our judgment about the controls that are feasible has evolved. 

Thus, the preliminary control option differs from what we are finalizing, as summarized in

Section 3.6 below.N It is important to note that these changes would not affect our estimates of

the baseline conditions without additional controls from nonroad diesel engines. This final rule

would produce nationwide air quality improvements in ozone levels, and we present the modeled

improvements in this section. Those interested in greater detail should review the AQ Modeling

TSD, which is available in the docket to this rule.

2.3.2.2.3 Ozone Modeling Methodology, Domains and Simulation Periods

In conjunction with this rulemaking, we performed a series of ozone air quality modeling

simulations for the Eastern and Western United States using Comprehensive Air Quality Model

with Extension (CAMx). The model simulations were performed for five emission scenarios: a

1996 baseline projection, a 2020 baseline projection and a 2020 projection with nonroad

controls, a 2030 baseline projection and a 2030 projection with nonroad controls. 

The model outputs from the 1996, 2020 and 2030 baselines, combined with current air

quality data, were used to identify areas expected to exceed the ozone NAAQS in 2020 and

2030. These areas became candidates for being determined to be residual exceedance areas that

will require additional emission reductions to attain and maintain the ozone NAAQS. The

impacts of the new emission standards were determined by comparing the model results in the

future year control runs against the baseline simulations of the same year. This modeling

supports the conclusion that there is a broad set of areas with predicted ozone concentrations at

or above 0.085 ppm between 1996 and 2030 in the baseline scenarios without additional

emission reductions.
The air quality modeling performed for this rule was based upon the same modeling system

as was used in the EPA’s air quality assessment of the Clear Skies legislation with the addition

of updated inventory estimates for 1996, 2020 and 2030. Further discussion of this modeling,

including evaluations of model performance relative to predicted future air quality, is provided in

the AQ Modeling TSD.

CAMx was utilized to estimate base and future-year ozone concentrations over the Eastern

and Western United States for the various emission scenarios. CAMx simulates the numerous

physical and chemical processes involved in the formation, transport, and destruction of ozone. 

CAMx is a photochemical grid model that numerically simulates the effects of emissions,

advection, diffusion, chemistry, and surface removal processes on pollutant concentrations

within a three-dimensional grid. This model is commonly used for purposes of determining

attainment/nonattainment as well as estimating the ozone reductions expected to occur from a

reduction in emitted pollutants. The following sections provide an overview of the ozone

modeling completed as part of this rulemaking. More detailed information is included in the AQ

Modeling TSD, which is located in the docket for this rule.

The regional ozone analyses used the modeling domains used previously for OTAG and the

highway passenger vehicle Tier 2 rulemaking. The Eastern modeling domain encompasses the

area from the East coast to mid-Texas and consists of two grids with differing resolutions. The

model resolution was 36 km over the outer portions of the domain and 12 km in the inner portion

of the grids. The vertical height of the eastern modeling domain is 4,000 meters above ground

level with 9 vertical layers. The western modeling domain encompasses the area west of the 99th

degree longitude (which runs through North and South Dakota, Nebraska, Kansas, Oklahoma,

and Texas) and also consists of two grids with differing resolutions. The vertical height of the

western modeling domains is 4,800 meters above ground level with 11 vertical layers. As for the

Eastern United States, the model resolution was 36 km over the outer portions of the domain and

12 km in the inner portion of the grids.

The simulation periods modeled by CAMx included several multi-day periods when ambient

measurements were representative of ozone episodes over the Eastern and Western United

States. A simulation period, or episode, consists of meteorological data characterized over a

block of days that are used as inputs to the air quality model. Three multi-day meteorological

scenarios during the summer of 1995 were used in the model simulations over the Eastern United

States: June 12-24, July 5-15, and August 7-21. Two multi-day meteorological scenarios during

the summer of 1996 were used in the model simulations over the Western United States: July 5-

15 and July 18-31. In general, these episodes do not represent extreme ozone events but, instead,

are generally representative of ozone levels near local design values. Each of the five emission

scenarios (1996 base year, 2020 base, 2020 control, 2030 baseline, 2030 control) were simulated

for the selected episodes. 

The meteorological data required for input into CAMx (wind, temperature, vertical mixing,

etc.) were developed by separate meteorological models. For the Eastern United States, the

gridded meteorological data for the three historical 1995 episodes were developed using the

Regional Atmospheric Modeling System (RAMS), version 3b. This model provided needed data

at every grid cell on an hourly basis. For the Western United States, the gridded meteorological

data for the two historical 1996 episodes were developed using the Fifth-Generation National

Center for Atmospheric Research (NCAR) / Penn State Mesoscale Model (MM5). These
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meteorological modeling results were evaluated against observed weather conditions before

being input into CAMx and it was concluded that the model fields were adequate representations

of the historical meteorology. A more detailed description of the settings and assorted input files

employed in these applications is provided in the AQ Modeling TSD, which is located in the

docket for this rule.

The modeling assumed background pollutant levels at the top and along the periphery of the

domain as in Tier 2. Additionally, initial conditions were assumed to be relatively clean as well. 

Given the ramp-up days and the expansive domains, it is expected that these assumptions will

not affect the modeling results, except in areas near the boundary (e.g., Dallas-Fort Worth TX). 

The other non-emission CAMx inputs (land use, photolysis rates, etc.) were developed using

procedures employed in the highway light duty Tier 2/OTAG regional modeling. The

development of model inputs is discussed in greater detail in the AQ Modeling TSD, which is

available in the docket for this rule.

2.3.2.2.4 Model Performance Evaluation

The purpose of the base year photochemical ozone modeling was to reproduce the

atmospheric processes resulting in the observed ozone concentrations over these domains and

episodes. One of the fundamental assumptions in air quality modeling is that a model that

adequately replicates observed pollutant concentrations in the base year can be used to assess the

effects of future-year emission controls.

A series of performance statistics was calculated for both model domains, the four quadrants

of the eastern domain, and multiple subregions in the eastern and western domains. Table 2.3-2

summarizes the performance statistics. The model performance evaluation consisted solely of

comparisons against ambient surface ozone data. There was insufficient data available in terms

of ozone precursors or ozone aloft to allow for a more complete assessment of model

performance. Three primary statistical metrics were used to assess the overall accuracy of the

base year modeling simulations. 

• Mean normalized bias is defined as the average difference between the hourly model

predictions and observations (paired in space and time) at each monitoring location,

normalized by the magnitude of the observations.

• Mean normalized gross error is defined as the average absolute difference between the

hourly model predictions and observations (paired in space and time) at each monitoring

location, normalized by the magnitude of the observations.

• Average accuracy of the peak is defined as the average difference between peak daily model

predictions and observations at each monitoring location, normalized by the magnitude of the

observations.
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In general, the model tends to underestimate observed ozone, especially in the modeling over

the Western United States, as shown in Table 2.3-3. When all hourly observed ozone values

greater than a 60 ppb threshold are compared with their model counterparts for the 30 episode

modeling days in the eastern domain, the mean normalized bias is -1.1 percent and the mean

normalized gross error is 20.5 percent. When the same statistics are calculated for the 19

episode days in the western domain, the bias is -21.4 percent and the error is 26.1 percent.

Table 2.3-3

Model Performance Statistics for the CAMx Ozone Predictions: Base Case

Region Episode

Average Accuracy 

of the Peak

Mean Normalized

Bias

Mean Normalized 

Gross Error

Eastern U.S.

June 1995 -7.3 -8.8 19.6

July 1995 -3.3 -5.0 19.1

August 1995 9.6 8.6 623.3

Western U.S. July 1996 -20.5 -21.4 26.1

At present, there are no guidance criteria by which one can determine if a regional ozone

modeling exercise is exhibiting adequate model performance. These base case simulations were

determined to be acceptable based on comparisons to previously completed model rulemaking

analyses (e.g., Ozone Transport Assessment Group (OTAG), the light-duty passenger vehicle

Tier-2 standards, and on highway Heavy-Duty Diesel Engine 2007 standards). The modeling

completed for this rule exhibits less bias and error than any past regional ozone modeling

application done by EPA. Thus, the model is considered appropriate for use in projecting

changes in future year ozone concentrations and the resultant health and economic benefits due

to the anticipated emission reductions.

2.3.2.2.5 Results of Photochemical Ozone Modeling: Areas at Risk of Future 8-Hour

Violations

This section summarizes the results of our modeling of ozone air quality impact in the future

of reductions in nonroad diesel emissions. Specifically, it provides information on our

calculations of the number of people estimated to live in counties in which ozone monitors are

predicted to exceed design values or to be within 10 percent of the design value in the future. 

We also provide specific information about the number of people who would repeatedly

experience levels of ozone of potential concern over prolonged periods, i.e., over 0.085 ppm

ozone 8-hour concentrations over a number of days.

The determination that an area is at risk of exceeding the ozone standard in the future was

made for all areas with current design values greater than or equal to 0.085 ppm (or within a 10

percent margin) and with modeling evidence that concentrations at and above this level will

persist into the future. The following sections provide background on methods for analysis of
OFor the one-hour NAAQS we used a cut-off of 80 ppb. Please see the Highway Passenger

Vehicle Tier 2 Air Quality Modeling TSD for more details (EPA 1999b).

attainment and maintenance. Those interested in greater detail should review the AQ TSD and

AQ Modeling TSD, both of which are available in the docket to this rule.

The relative reduction factor method was used for interpreting the future-year modeling

results to determine where nonattainment is expected to occur in the 2020 and 2030 control

cases. The CAMx simulations were completed for base cases in 1996, 2020, and 2030

considering growth and expected emission controls that will affect future air quality. The effects

of the nonroad engine reductions (control cases) were modeled for the two future years. As a

means of assessing the future levels of air quality with regard to the ozone NAAQS, future-year

estimates of ozone design values were calculated based on relative reduction factors (RRF)

between the various baselines and 1999-2001 ozone design values. The procedures for

determining the RRFs are similar to those in EPA’s draft guidance for modeling for an 8-hour

ozone standard.320 Hourly model predictions were processed to determine daily maximum 8-

hour concentrations for each grid cell for each non-ramp-up day modeled. The RRF for a

monitoring site was determined by first calculating the multi-day mean of the 8-hour daily

maximum predictions in the nine grid cells surrounding the site using only those predictions

greater than or equal to 70 ppb, as recommended in the guidance.O, 321 This calculation was

performed for the base year scenario and each of the future-year baselines. The RRF for a site is

the ratio of the mean prediction in the future-year scenario to the mean prediction in the base

year scenario. RRFs were calculated on a site-by-site basis. The future-year design value

projections were then calculated by county, based on the highest resultant design values for a site

within that county from the RRF application.

Based upon our air quality modeling for this rule, we anticipate that without emission

reductions beyond those already required under promulgated regulation and approved SIPs,

ozone nonattainment will likely persist into the future. With reductions from programs already

in place (but excluding the emission reductions from this rule), the number of counties violating

the ozone 8-hour standard is expected to decrease in 2020 to 30 counties where 43 million

people are projected to live.322 Thereafter, exposure to unhealthy levels of ozone is expected to

increase again. In 2030 the number of counties violating the ozone 8-hour NAAQS, without

considering the emission reductions from this rule, is projected to increase to 32 counties where

47 million people are projected to live.

EPA is still developing the implementation process for bringing the nation’s air into

attainment with the ozone 8-hour NAAQS (see proposal, 68 FR 32702, June 2, 2003, that was

recently finalized www.epa.gov/ozonedesignations) as described above. Since the VOC and

NOx emission reductions expected from this final rule will go into effect during the period when

areas will need to attain the 8-hour ozone NAAQS, the projected reductions in nonroad diesel

emissions are expected to assist States and local agencies in their effort to meet and maintain that

standard. Many states mentioned this need in their public comments. The following are sample

comments from states and state associations on the proposed rule, which corroborate that this

rule is a critical element in States’ NAAQS attainment efforts. Fuller information can be found

in the Summary and Analysis of Comments.
P

This is in spite of the fact that NOx reductions can at certain times in some areas cause ozone levels to

increase. Such “disbenefits” are observed in our modeling, but these results make clear that the overall effect of this

final rule is positive. 

- “Unless emissions from nonroad diesels are sharply reduced, it is very likely that many

areas of the country will be unable to attain and maintain health-based NAAQS for ozone

and PM.” (STAPPA/ALAPCO)

- “Adoption of the proposed regulation ... is necessary for the protection of public health in

California and to comply with air quality standards.” (California Air Resources Board)

- “Attainment of the NAAQS for ozone and PM2.5 is of immediate concern to the states in the

northeast region....Thus, programs ... such as the proposed rule for nonroad diesel engines are

essential.” (NESCAUM)

Furthermore, the inventories that underlie the ozone modeling conducted for this

rulemaking included emission reductions from all current or committed federal, State, and local

controls and, for the control case, including this rulemaking. There was no attempt to examine

the prospects of areas attaining or maintaining the ozone standard with possible future controls

(i.e., controls beyond current or committed federal, State, and local controls). Tables 2.2-4 and

2.2-5 below should therefore be interpreted as indicating what counties are at risk of ozone

violations in 2020 or 2030 without additional federal or State measures that may be adopted and

implemented after this rulemaking is finalized. We expect many of the areas listed in Table

2.2-4 to adopt additional emission reduction programs, but we are unable to quantify or rely

upon future reductions from additional State programs since they have not yet been adopted. 

Since the emission reductions expected from this final rule begin in the same time period in

which areas will need reductions to attain by their attainment dates, the projected reductions in

nonroad emissions will be extremely important to States in meeting the new NAAQS. In public

comment, many States and local agencies commented that they will be relying on such nonroad

reductions to help them attain and maintain the 8-hour NAAQS. Furthermore, since the nonroad

emission reductions will continue to grow in the years beyond 2014, they will also be important

for maintenance of the NAAQS for areas with attainment dates of 2014 and earlier.

On a population-weighted basis, the average change in future year design values would be a

decrease of 1.8 ppb in 2020, and 2.5 ppb in 2030. Within nonattainment areas, the populationweighted average decrease would be somewhat higher: 1.9 ppb in 2020 and 3 ppb in 2030.P

 In

terms of modeling accuracy, the count of modeled nonattaining counties is much less certain

than the average changes in air quality. For example, actions by states to meet their SIP

obligations would not be expected to significantly change the overall concentration changes

induced by this final rule, but they could substantially change the number of counties in or out of

attainment. If state actions resulted in an increase in the number of areas that are very close to,

but still above, the NAAQS, then this rule might bring many of those counties down sufficiently

to change their attainment status. On the other hand, if state actions brought several counties we

project to be very close to the standard in the future down sufficiently to reach attainment status,

then the air quality improvements from this rule might change the actual attainment status of

very few counties. Bearing this limitation in mind, our modeling indicates that the nonroad

diesel emission reductions will decrease the net number of nonattainment counties by 2 in 2020

and by 4 in 2030, without consideration of new state or local programs.
Final Regulatory Impact Analysis

QSince the air quality modeling and analyses performed at proposal used the 1999-2001 monitored data set, we

present these data rather than the 2000-2002 data for consistency.

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This air quality modeling suggests that without emission reductions beyond those already

required under promulgated regulations and approved SIPs, ozone nonattainment will likely

persist into the future. With reductions from programs already in place, the number of counties

violating the ozone 8-hour standard is expected to decrease from today’s levels to 30 counties in

2020 where 43 million people are projected to live.323 Thereafter, exposure to unhealthy levels

of ozone is expected to begin to increase again. In 2030 the number of counties violating the

ozone 8-hour NAAQS is projected to increase to 32 counties where 47 million people are

projected to live. In addition, in 2030, 82 counties where 44 million people are projected to live

will be within 10 percent of violating the ozone 8-hour NAAQS. Specifically, counties

presented in Table 2.3-3 and 2.3-4 have monitored 1999-2001 air quality dataQ and our modeling

predicts violations of the 8-hour ozone NAAQS, or predicts concentrations within 10 percent of

the standard, in 2020 or 2030. The base case indicates conditions predicted without the

reductions from this rule, and the control case represents a preliminary control option similar to

the final rule, as described in section 3.6 of the RIA. 

In Table 2.3-4 we list the counties with 2020 and 2030 projected 8-hour ozone design values

(4th maximum concentration) that violate the 8-hour standard. Counties are marked with an “V”

in the table if their projected design values are greater than or equal to 85 ppb. The 1999-2001

average design values of these counties are also listed. Recall that we project future design

values only for counties that have 1999-2001 design values, so this list is limited to those

counties with ambient monitoring data sufficient to calculate these design values.
Air Quality, Health, and Welfare Effects

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Table 2.3-4: Counties with 2020 and 2030 Projected Ozone Design Values 

in Violation of the 8-Hour Ozone Standard.a

State County

1999 - 2001

Design Value

(ppb)

2020 2030 Population

in 2000 Base Controla Base Controla

CA Fresno 108 V V V V 799,407

CA Kern 109 V V V V 661,645

CA Los Angeles 105 V V V V 9,519,338

CA Orange 77 V V V V 2,846,289

CA Riverside 111 V V V V 1,545,387

CA San Bernardino 129 V V V V 1,709,434

CA Ventura 101 V V V V 753,197

CT Fairfield 97 V V V V 882,567

CT Middlesex 99 V V V V 155,071

CT New Haven 97 V V V V 824,008

GA Bibb 98 V V 153,887

GA Fulton 107 V V V 816,006

GA Henry 107 V V 119,341

IL Cook 88 V V V V 5,376,741

IN Lake 90 V 484,564

MD Harford 104 V V 218,590

MI Macomb 88 V V 788,149

MI Wayne 88 V V V V 2,061,162

NJ Camden 103 V V V V 508,932

NJ Gloucester 101 V V V V 254,673

NJ Hudson 93 V V V V 608,975

NJ Hunterdon 100 V V V V 121,989

NJ Mercer 105 V V V V 350,761

NJ Middlesex 103 V V V V 750,162

NJ Ocean 109 VVVV 510,916

NY Bronx 83 V V 1,332,650

NY Richmond 98 V V V V 443,728

NY Westchester 92 V V V V 923,459

PA Bucks 105 V V V V 597,635

PA Montgomery 100 V V V V 750,097

TX Galveston 98 V V V V 250,158

TX Harris 110 V V V V 3,400,578

WI Kenosha 95 V V V V 149,577

Number of Violating Counties 30 28 32 28

Population of Violating Countiesb 42,930,060 43,532,490 46,998,413 46,038,489 a

 The projected emission reductions differ based on updated information (see Chapter 3.6); however, the base results

presented here would not change, but we anticipate the control case improvements would generally be smaller. b

 Populations are based on 2020 and 2030 estimates from the U.S. Census.
Final Regulatory Impact Analysis

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In Table 2.3-5 we present the counties with 1999-2001 design values and 2020 and 2030

projected 8-hour ozone design values that are within 10 percent of it in either base or control

scenarios. Counties are marked with an “X” in the table if their projected design values are

greater than or equal to 77 ppb, but less than 85 ppb. Counties are marked with a “V” in the

table if their projected design values are greater than or equal to 85 ppb. This list is limited to

those counties with ambient monitoring data sufficient to calculate these design values, and the

1999-2001 average design values of these counties are also presented. Most of these are

counties are not projected to violate the standard, but their future values are project to be close to

the standard. Thus, the final rule will help ensure that these counties continue to meet the

standard.

Table 2.3-5

Counties with 2020 and 2030 Projected Ozone Design Values 

within Ten Percent of the 8-Hour Ozone Standard.a

State County

1999 - 2001

Design Value

(ppb)

2020 2030 Population

in 2000 Base Controla Base Controla

AR Crittenden 92 X X X X 50,866

AZ Maricopa 85 X X X X 3,072,149

CA Kings 98 X X X X 129,461

CA Merced 101 X X X X 210,554

CA Tulare 104 X X X X 368,021

CO Jefferson 81 X X X X 527,056

CT New London 90 X X 259,088

DC Washington 94 X X X X 572,059

DE New Castle 97 X X X X 500,265

GA Bibb 98 V X V X 153,887

GA Coweta 96 X X X X 89,215

GA De Kalb 102 X X X X 665,865

GA Douglas 98 X X 92,174

GA Fayette 99 X X 91,263

GA Fulton 107 V V V X 816,006

GA Henry 107 V X V X 119,341

GA Rockdale 104 X X X X 70,111

IL McHenry 83 X X 260,077

IN Lake 90 X X V X 484,564

IN Porter 90 X X X X 146,798

LA Ascension 86 X X X X 76,627

LA Bossier 90 X X X X 98,310

LA Calcasieu 86 X X X X 183,577

LA East Baton Rouge 91 XXXX 412,852

LA Iberville 86 X X 33,320

LA Jefferson 89 X X X X 455,466
Air Quality, Health, and Welfare Effects

State County

1999 - 2001

Design Value

(ppb)

2020 2030 Population

in 2000 Base Controla Base Controla

2-111

LA Livingston 88 X X X X 91,814

LA St Charles 86 X X X X 48,072

LA St James 83 X 21,216

LA St John The Ba 86 X X X X 43,044

LA West Baton Rou 88 X X X X 21,601

MA Barnstable 96 X X 222,230

MA Bristol 93 X X 534,678

MD Anne Arundel 103 XXXX 489,656

MD Baltimore 93 XXXX 754,292

MD Cecil 106 X X X X 85,951

MD Harford 104 V X V X 218,590

MD Kent 100 X X 19,197

MD Prince Georges 97 X X X 801,515

MI Benzie 89 X X 15,998

MI Macomb 88 X X V V 788,149

MI Mason 91 X X 28,274

MI Muskegon 92 X X X 170,200

MI Oakland 84 X X X X 1,194,156

MI St Clair 85 X 164,235

MO St Charles 90 X 283,883

MO St Louis 88 X 1,016,315

MS Hancock 87 X X 42,967

MS Harrison 89 X X X X 189,601

MS Jackson 87 X X X X 131,420

NJ Cumberland 97 X X 146,438

NJ Monmouth 94 X X X X 615,301

NJ Morris 97 X X X X 470,212

NJ Passaic 89 X X X X 489,049

NY Bronx 83 X V X V 1,332,650

NY Erie 92 X X X X 950,265

NY Niagara 87 X X 219,846

NY Putnam 89 X X 95,745

NY Suffolk 91 X X X X 1,419,369

OH Geauga 93 X X 90,895

OH Lake 91 X X 227,511

PA Allegheny 92 X X 1,281,666

PA Delaware 94 X X X X 550,864

PA Lancaster 96 X X 470,658

PA Lehigh 96 X X X X 312,090

PA Northampton 97 X X X X 267,066
Final Regulatory Impact Analysis

State County

1999 - 2001

Design Value

(ppb)

2020 2030 Population

in 2000 Base Controla Base Controla

2-112

PA Philadelphia 88 X X X X 1,517,550

RI Kent 94 X X X 167,090

RI Washington 92 X X 123,546

TN Shelby 93 X X X X 897,472

TX Brazoria 91 X X X X 241,767

TX Collin 99 XXXX 491,675

TX Dallas 93 X X X X 2,218,899

TX Denton 101 X X X X 432,976

TX Jefferson 85 X X X X 252,051

TX Montgomery 91 X X X 293,768

TX Tarrant 97 X X X X 1,446,219

VA Alexandria City 88 X 128,283

VA Arlington 92 X X X X 189,453

VA Fairfax 95 X X X X 969,749

WI Door 93 X X X X 27,961

WI Kewaunee 89 X X 20,187

WI Manitowoc 92 X X X 82,887

WI Milwaukee 89 X X X X 940,164

WI Ozaukee 95 X X X X 82,317

WI Racine 87 X X 188,831

WI Sheboygan 95 XXXX 112,646

WI Waukesha 86 X X 360,767

Number of Counties within 10% 79 58 82 54

Population of Counties within 10%b 40,465,492 33,888,031 44,013,587 35,631,215

a

 The projected emission reductions differ based on updated information (see Section 3.6); however, the base results

presented here would not change, but we anticipate the control case improvements would generally be smaller. b

 Populations are based on 2020 and 2030 estimates from the U.S. Census.

Based on our modeling, we are also able to provide a quantitative prediction of the number of

people anticipated to reside in counties in which ozone concentrations are predicted to for 8-hour

periods in the range of 85 to 120 ppb and higher on multiple days. Our analysis relies on

projected county-level population from the U.S. Department of Census for the period

representing each year analyzed.324

For each of the counties analyzed, we determined the number of days for periods on which

the highest model-adjusted 8-hour concentration at any monitor in the county was predicted, for

example, to be equal to or above 85 ppb. We then grouped the counties that had days with ozone

in this range according to the number of days this was predicted to happen and summed their

projected populations. 
Air Quality, Health, and Welfare Effects

2-113

In the base case (i.e., before the application of emission reductions resulting from this rule),

we estimated in 2020 that 53 million people are predicted to live in counties with at least 2 days

with 8-hour average concentrations of 85 ppb or higher. This baseline will increase in 2030 to

56 million people are predicted to live in counties with at least 2 days with 8-hour average

concentrations of 85 ppb or higher. About 30 million people live in counties with at least 7 days

of 8-hour ozone concentrations at or above 85 ppb in 2020 and 2030 without additional controls.

Approximately 15 million people are predicted to live in counties with at least 20 days of 8-hour

ozone concentrations at or above 85 ppb in 2020 and 2030 without additional controls.325 Thus,

reductions in ozone precursors from nonroad diesel engines are needed to assist States in

meeting the ozone NAAQS and to reduce ozone exposures.

2.3.2.3 Potentially Counterproductive Impacts on Ozone Concentrations from NOx

Emission Reductions

While this final rule will reduce ozone levels generally and provide significant ozone-related

health benefits, this is not always the case at the local level. Due to the complex photochemistry

of ozone production, NOx emissions lead to both the formation and destruction of ozone,

depending on the relative quantities of NOx, VOC, and ozone catalysts such as the OH and HO2

radicals. In areas dominated by fresh emissions of NOx, ozone catalysts are removed via the

production of nitric acid, which slows the ozone formation rate. Because NOx is generally

depleted more rapidly than VOC, this effect is usually short-lived and the emitted NOx can lead

to ozone formation later and further downwind. The terms “NOx disbenefits” or “ozone

disbenefits” refer to the ozone increases that can result from NOx emission reductions in these

localized areas. According to the NARSTO Ozone Assessment, these disbenefits are generally

limited to small regions within specific urban cores and are surrounded by larger regions in

which NOx control is beneficial.326

In the context of ozone disbenefits, some have postulated that present-day weekend

conditions serve as a demonstration of the effects of future NOx reduction strategies because

NOx emissions decrease more than VOC emissions on weekends, due to a disproportionate

decrease in the activity of heavy-duty diesel trucks and other diesel equipment. Recent research

indicates that ambient ozone levels are higher in some metropolitan areas on weekends than

weekdays.327, 328 There are other hypotheses for the cause of the “weekend effect.”329 For

instance, the role of ozone and ozone precursor carryover from previous days is difficult to

evaluate because of limited ambient data, especially aloft. The role of the changed timing of

emissions is difficult to evaluate because of limited ambient and emission inventory information. 

It is also important to note that in many areas with “weekend effects” (e.g., Los Angeles and San

Francisco) significant ozone reductions have been observed over the past 20 years for all days of

the week, during a period in which both NOx and VOC emissions have been greatly reduced.

We received some public comments that in some cities, decreased motor vehicle traffic

(particularly diesels) results in a higher VOC/NOx ratio which, in airsheds that are VOC-limited,

can result in higher ozone concentrations. EPA’s air quality modeling predicts NOx disbenefits

in the areas identified by some studies as “VOC-limited” (e.g., Los Angeles). However, these
Final Regulatory Impact Analysis

2-114

areas represent a small minority of the area in the United States. While some empirical studies

to date point to a weekend ozone effect related to NOx reduction, modeling conducted for this

rule predicts that this rule will result in net gains in benefits as a result of reduced ozone and

PM2.5 related to NOx.

EPA maintains that the best available approach for determining the value of a particular

emission reduction strategy is the net air quality change projected to result from the rule,

evaluated on a nationwide basis and for all pollutants that are health and/or welfare concerns. 

The primary tool for assessing the net impacts of this rule are the air quality simulation

models.330 Model scenarios of 2020 and 2030 with and without the emission controls from this

rulemaking are compared to determine the expected changes in future pollutant levels resulting

from the rule. There are several factors related to the air quality modeling and inputs that should

be considered regarding the disbenefit issue. First, our future year modeling does not contain

any local governmental actions beyond the controls in this rule. It is possible that significant

local controls of VOC and/or NOx could modify the conclusions regarding ozone changes in

some areas. Second, the modeled NOx reductions are greater than those actually included in the

analysis to quantify the emission reductions resulting from the final rule (see Section 3.6 for

more detail). This could lead to an exaggeration of the benefits and disbenefits expected to

result from the rule. Also, recent work by California ARB has indicated that model limitations

and uncertainties may lead to overestimates of ozone disbenefits attributed to NOx emission

reductions. While EPA maintains that the air quality simulations conducted for the rule

represent state-of-the-science analyses, any changes to the underlying chemical mechanisms,

grid resolution, and emissions/meteorological inputs could result in revised conclusions

regarding the strength and frequency of ozone disbenefits.

A wide variety of ozone metrics were considered in assessing the emission reductions. Three

of the most important assessments are: 1) the effect of the rule on projected future-year ozone

violations, 2) the effect of the rule in assisting local areas in attainment and maintenance of the

NAAQS, and 3) an economic assessment of the rule benefits based on existing health studies. 

Additional metrics for assessing the air quality effects are discussed in the TSD for the modeling.

Based only on the reductions from this rule, our modeling predicts that periodic ozone

disbenefits will occur most frequently in New York City, Los Angeles, and Chicago. Smaller

and less frequent disbenefits also occur in Boston, Detroit, and San Francisco. As described

below, despite these localized increases, the net ozone impact of the rule nationally is positive

for the majority of the analysis metrics. Even within the few metropolitan areas that experience

periodic ozone increases, these disbenefits are infrequent relative to the benefits accrued at

ozone levels above the NAAQS. Furthermore, and most importantly, the overall air quality

impact of this final rule is projected to be strongly positive due to the expected reductions in fine

PM.

The projected net impact of the rule on 8-hour ozone violations in 2020 is that three counties

will no longer violate the NAAQS.331 Conversely, one county in the NewYork City CMSA

(Bronx County), which is currently not in violation of the NAAQS, is projected to violate the
Air Quality, Health, and Welfare Effects

2-115

standard in 2020 as a result of the rule. The net effect is a projected 1.4 percent increase in the

population living in violating counties. It is important to note that ozone nonattainment

designations are historically based on larger geographical areas than counties (e.g., see public

comments from New York Department of Environmental Conservation requesting that EPA use

metropolitan areas instead of counties for its analyses for this reason). Bronx County, NY is the

only county within the New York City CMSA in which increases are detected in 8-hour

violations in 2020. Considering a larger area, the modeling indicates that projected violations

over the entire New York City CMSA will be reduced by 6.8 percent. Upon full turnover of the

fleet in 2030, the net impact of the rule on projected 8-hour ozone violations is a 2.0 percent

decrease in the population living in violating counties as two additional counties are no longer

projected to violate the NAAQS. The net impact of the rule on projected 1-hour ozone

violations is to eradicate projected violations from four counties (in both 2020 and 2030),

resulting in a 10.5 percent decrease in the population living in violating counties.

Another way to assess the air quality impact of the rule is to calculate its effect on all

projected future year design values concentrations, as opposed to just those that cross the

threshold of the NAAQS. This metric helps assess the degree to which the rule will assist local

areas in attaining and/or maintaining the NAAQS. Future year design values were calculated for

every location for which complete ambient monitoring data existed for the period 1999-2001. 

These present-day design values were then projected by using the modeling projections (future

base vs. future control) in a relative sense. For the 1999-2001 monitoring period, there were

sites in 522 counties for which 8-hour design values could be calculated and sites in 510 counties

for which 1-hour design values could be calculated.

Table 2.3.2-1 shows the average change in future year eight-hour and one-hour ozone design

values. Average changes are shown 1) for all counties with design values in 2001, 2) for

counties with design values that did not meet the standard in 1999-2001 (“violating” counties),

and 3) for counties that met the standard, but were within 10 percent of it in 1999-2001. This

last category is intended to reflect counties that meet the standard, but will likely benefit from

help in maintaining that status in the face of growth. The average and population-weighted

average over all counties in Table 2.3.2-1 demonstrates a broad improvement in ozone air

quality. The average across violating counties shows that the rule will help bring these counties

into attainment. The average over counties within ten percent of the standard shows that the rule

will also help those counties to maintain the standard. All of these metrics show a decrease in

2020 and a larger decrease in 2030 (due to fleet turnover), indicating in four different ways the

overall improvement in ozone air quality as measured by attainment of the NAAQS.
Final Regulatory Impact Analysis

2-116

Table 2.3.2-1

Average Change in Projected Future-Year Ozone Design Valuef

Design Value Averagea

Number of

Counties

2020 Controlf

minus Base (ppb)

2030 Controlf

 minus

Base (ppb)

8-Hour All 522 -1.8 -2.8

All, population-weighted 522 -1.6 -2.6

Violating countiesb 289 -1.9 -3

Counties within 10

percent of the standardc

130 -1.7 -2.6

1-Hour All 510 -2.4 -3.8

All, population-weighted 510 -2.3 -3.6

Violating countiesd 73 -2.9 -4.5

Counties within 10

percent of the standarde

130 -2.4 -3.8

a

 Averages are over counties with 2001 design values.

b

 Counties whose present-day design values exceeded the 8-hour standard ($ 85 ppb). c

 Counties whose present-day design values were less than but within 10 percent of the 8-hour standard (77#DV<85 ppb). d

 Counties whose present-day design values exceeded the 1-hour standard ($ 125 ppb). e

 Counties whose present-day design values were less than but within 10 percent of the 1-hour standard

(112#DV<125 ppb) in 2001. f

 The analysis in Chapter 3 differs based on updated information; however, we believe that the net results would

approximate future emissions, although we anticipate the design value improvements would generally be slightly

smaller.

Table 2.3.2-2 presents counts of the same set of counties (those with 1999-2001 design

values) examined by the size and direction of their change in design value in 2020 and 2030. 

For the 8-hour design value, 96 percent of counties show a decrease in 2020, 97 percent in 2030. 

For the 1-hour design value, 97 percent of counties show a decrease in 2020, 98 percent in 2030.
Air Quality, Health, and Welfare Effects

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Table 2.3.2-2

Numbers of Counties Projected to Be in 

Different Design-Value Change Bins in 2020 and 2030 as a Result of the Rulea

Design value

change

2020 2030

8-Hour 1-Hour 8-Hour 1-Hour

$ 2ppb increase 1111

1 ppb increase 1532

No change 21 10 10 5

1 ppb decrease 140 69 42 22

2-3 ppb decrease 357 356 333 193

4 ppb decrease 2 69 133 287

Total 522 510 522 510

a

 The analysis in Chapter 3 differs based on updated information; however, we believe that the net results would

approximate future emissions, although we anticipate the design value improvements would generally be slightly

smaller.

A third way to assess the impacts of the rule is an economic consideration of the economic

benefits. Benefits related to changes in ambient ozone are expected to be positive for the nation

as a whole. However, for certain health endpoints associated with longer ozone-averaging times,

such as minor restricted activity days related to 24-hour average ozone, the national impact may

be small or even negative. This is due to the forecasted increases in ozone for certain hours of

the day in some urban areas. Many of the increases occur during hours when baseline ozone

levels are low, but the benefits estimates rely on the changes in ozone along the full distribution

of baseline ozone levels, rather than changes occurring only above a particular threshold. As

such, the benefits estimates are more sensitive to increases in ozone occurring due to the "NOx

disbenefits" effect described above. For more details on the economic effects of the rule, please

see Chapter 9: Public Health and Welfare Benefits.

Historically, NOx reductions have been very successful at reducing regional and national

ozone levels. Consistent with that fact, the photochemical modeling completed for this rule

indicates that the projected emission reductions will significantly assist in the attainment and

maintenance of the ozone NAAQS at the national level. Furthermore, NOx reductions also

result in reductions in PM and its associated health and welfare effects. This rule is one aspect

of overall emission reductions that States, local governments, and Tribes need to reach their

clean air goals. It is expected that future state, local and national controls that decrease VOC,

CO, and regional ozone will mitigate any localized disbenefits. EPA will continue to rely on

local attainment measures to ensure that the NAAQS are not violated in the future. Many

organizations with an interest in improved air quality have supported the rule because they

believe the resulting NOx reductions will reduce both ozone and PM.332 EPA believes that a
Final Regulatory Impact Analysis

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balanced air quality management approach that includes NOx emission reductions from nonroad

engines is needed as part of the nation’s progress toward clean air.

2.3.3 Welfare Effects Associated with Ozone and its Precursors

There are a number of significant welfare effects associated with the presence of ozone and

NOX in the ambient air.333 Because this rule will reduce ground-level ozone and nitrogen

deposition, benefits are expected to accrue to the welfare effects categories described in the

following paragraphs.

2.3.3.1 Ozone-related welfare effects.

The Ozone Criteria Document notes that “ozone affects vegetation throughout the United

States, impairing crops, native vegetation, and ecosystems more than any other air pollutant.”334

Like carbon dioxide (CO2) and other gaseous substances, ozone enters plant tissues primarily

through apertures (stomata) in leaves in a process called “uptake”. To a lesser extent, ozone can

also diffuse directly through surface layers to the plant's interior.335 Once ozone, a highly

reactive substance, reaches the interior of plant cells, it inhibits or damages essential cellular

components and functions, including enzyme activities, lipids, and cellular membranes,

disrupting the plant's osmotic (i.e., water) balance and energy utilization patterns.336, 337 This

damage is commonly manifested as visible foliar injury such as chlorotic or necrotic spots,

increased leaf senescence (accelerated leaf aging) and/or as reduced photosynthesis. All these

effects reduce a plant’s capacity to form carbohydrates, which are the primary form of energy

used by plants.338 With fewer resources available, the plant reallocates existing resources away

from root growth and storage, above ground growth or yield, and reproductive processes, toward

leaf repair and maintenance. Studies have shown that plants stressed in these ways may exhibit a

general loss of vigor, which can lead to secondary impacts that modify plants' responses to other

environmental factors. Specifically, plants may become more sensitive to other air pollutants,

more susceptible to disease, insect attack, harsh weather (e.g., drought, frost) and other

environmental stresses (e.g., increasing CO2 concentrations). Furthermore, there is considerable

evidence that ozone can interfere with the formation of mycorrhiza, essential symbiotic fungi

associated with the roots of most terrestrial plants, by reducing the amount of carbon available

for transfer from the host to the symbiont.339

Not all plants, however, are equally sensitive to ozone. Much of the variation in sensitivity

between individual plants or whole species is related to the plant’s ability to regulate the extent

of gas exchange via leaf stomata (e.g., avoidance of O3 uptake through closure of stomata).340, 341,

342 Other resistance mechanisms may involve the intercellular production of detoxifying

substances. Several biochemical substances capable of detoxifying ozone have been reported to

occur in plants including the antioxidants ascorbate and glutathione. After injuries have

occurred, plants may be capable of repairing the damage to a limited extent.343 Because of the

differing sensitivities among plants to ozone, ozone pollution can also exert a selective pressure

that leads to changes in plant community composition. Given the range of plant sensitivities and

the fact that numerous other environmental factors modify plant uptake and response to ozone, it
Air Quality, Health, and Welfare Effects

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is not possible to identify threshold values above which ozone is toxic for all plants. However,

in general, the science suggests that ozone concentrations of 0.10 ppm or greater can be

phytotoxic to a large number of plant species, and can produce acute foliar injury responses, crop

yield loss and reduced biomass production. Ozone concentrations below 0.10 ppm (0.05 to 0.09

ppm) can produce these effects in more sensitive plant species, and have the potential over a

longer duration of creating chronic stress on vegetation that can lead to effects of concern

associated with reduced carbohydrate production and decreased plant vigor. 

The economic value of some welfare losses due to ozone can be calculated, such as crop

yield loss from both reduced seed production (e.g., soybean) and visible injury to some leaf

crops (e.g., lettuce, spinach, tobacco) and visible injury to ornamental plants (i.e., grass, flowers,

shrubs), while other types of welfare loss may not be fully quantifiable in economic terms (e.g.,

reduced aesthetic value of trees growing in Class I areas).

Forests and Ecosystems. Ozone also has been shown conclusively to cause discernible

injury to forest trees.344, 345 In terms of forest productivity and ecosystem diversity, ozone may

be the pollutant with the greatest potential for regional-scale forest impacts.346 Studies have

demonstrated repeatedly that ozone concentrations commonly observed in polluted areas can

have substantial impacts on plant function.347, 348, 349

Because plants are at the center of the food web in many ecosystems, changes to the plant

community can affect associated organisms and ecosystems (including the suitability of habitats

that support threatened or endangered species and below ground organisms living in the root

zone). Ozone damages at the community and ecosystem-level vary widely depending upon

numerous factors, including concentration and temporal variation of tropospheric ozone, species

composition, soil properties and climatic factors.350 In most instances, responses to chronic or

recurrent exposure are subtle and not observable for many years. These injuries can cause standlevel forest decline in sensitive ecosystems.351, 352, 353 It is not yet possible to predict ecosystem

responses to ozone with much certainty; however, considerable knowledge of potential

ecosystem responses has been acquired through long-term observations in highly damaged

forests in the United States.

Given the scientific information establishing that ambient ozone levels cause visible injury to

foliage of some sensitive forest species,354 there is a corresponding loss of public welfare from

reduced aesthetic properties of forests.355 However, present analytic tools and resources preclude

EPA from quantifying the benefits of improved forest aesthetics.

Agriculture. Laboratory and field experiments have shown reductions in yields for

agronomic crops exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g.,

cotton and wheat). The most extensive field experiments, conducted under the National Crop

Loss Assessment Network (NCLAN) examined 15 species and numerous cultivars. The

NCLAN results show that “several economically important crop species are sensitive to ozone

levels typical of those found in the Unites States.”356 In addition, economic studies have shown a

relationship between observed ozone levels and crop yields.357 358 359
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Urban Ornamentals. Urban ornamentals represent an additional vegetation category likely

to experience some degree of negative effects associated with exposure to ambient ozone levels

and likely to impact large economic sectors. In the absence of adequate exposure-response

functions and economic damage functions for the potential range of effects relevant to these

types of vegetation, no direct quantitative analysis has been conducted. It is estimated that more

than $20 billion (1990 dollars) are spent annually on landscaping using ornamentals, both by

private property owners/tenants and by governmental units responsible for public areas.360 This

is therefore a potentially important environmental effect. However, methods are not available to

allow for plausible estimates of the percentage of these expenditures that may be related to

impacts associated with ozone exposure.

2.3.3.2 Nitrogen (NOX)-related welfare effects.

Agriculture. By reducing NOX emissions, this final rule will also reduce nitrogen deposition

on agricultural land and forests. There is some evidence that nitrogen deposition may have

positive effects on agricultural output through passive fertilization. Holding all other factors

constant, farmers’ and commercial tree growers use of purchased fertilizers or manure may

increase as deposited nitrogen is reduced. Estimates of the potential value of this possible

increase in the use of purchased fertilizers are not available, but it is likely that the overall value

is very small relative to other health and welfare effects. The share of nitrogen requirements

provided by this deposition is small, and the marginal cost of providing this nitrogen from

alternative sources is quite low. In some areas, agricultural lands suffer from nitrogen oversaturation due to an abundance of on-farm nitrogen production, primarily from animal manure. 

In these areas, reductions in atmospheric deposition of nitrogen represent additional agricultural

benefits.

Forests and Ecosystems. Information on the effects of changes in passive nitrogen

deposition on forests and other terrestrial ecosystems is very limited. The multiplicity of factors

affecting forests, including other potential stressors such as ozone, and limiting factors such as

moisture and other nutrients, confound assessments of marginal changes in any one stressor or

nutrient in forest ecosystems. However, reductions in nitrogen deposition can have negative

effects on forest and vegetation growth in ecosystems where nitrogen is a limiting factor.361

On the other hand, there is evidence that forest ecosystems in some areas of the United States

are already or are becoming nitrogen saturated.362 Once saturation is reached, adverse effects of

additional nitrogen begin to occur, such as soil acidification, which can lead to leaching of

nutrients needed for plant growth and mobilization of harmful elements such as aluminum,

leading to reductions in tree growth or forest decline. Increased soil acidification is also linked

to higher amounts of acidic runoff to streams and lakes and leaching of harmful elements into

aquatic ecosystems, harming fish and other aquatic life.363

The reductions in ground-level ozone and nitrogen deposition that will result from this rule

are expected to reduce the adverse impacts described above. In particular, it is expected that
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economic impacts, such as those related to reduced crop yields and forest productivity, will be

reduced. 

2.4 Carbon Monoxide

This final rule will reduce levels of other pollutants for which NAAQS have been

established: carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2). 

Currently every area in the United States has been designated to be in attainment with the NO2

NAAQS. As of August 27, 2003, there were 24 areas designated as nonattainment with the SO2

standard, and 11 designated CO nonattainment areas. The rest of this section describes issues

related to CO.

2.4.1 General Background

Unlike many gases, CO is odorless, colorless, tasteless, and nonirritating. Carbon monoxide

results from incomplete combustion of fuel and is emitted directly from vehicle tailpipes. 

Incomplete combustion is most likely to occur at low air-to-fuel ratios in the engine. These

conditions are common during vehicle starting when air supply is restricted (“choked”), when

vehicles are not tuned properly, and at high altitude, where “thin” air effectively reduces the

amount of oxygen available for combustion (except in engines that are designed or adjusted to

compensate for altitude). High concentrations of CO generally occur in areas with elevated

mobile-source emissions. Carbon monoxide emissions increase dramatically in cold weather. 

This is because engines need more fuel to start at cold temperatures and because some emission

control devices (such as oxygen sensors and catalytic converters) operate less efficiently when

they are cold. Also, nighttime inversion conditions are more frequent in the colder months of the

year. This is due to the enhanced stability in the atmospheric boundary layer, which inhibits

vertical mixing of emissions from the surface.

As described in Chapter 3, nonroad diesel engines currently account for about one percent of

the national mobile source CO inventory. EPA previously determined that the category of

nonroad diesel engines cause or contribute to ambient CO and ozone in more than one

nonattainment area (65 FR 76790, December 7, 2000). In that action, EPA found that engines

subject to this final rule contribute to CO nonattainment in areas such as Los Angeles, Phoenix,

Spokane, Anchorage, and Las Vegas. Nonroad land-based diesel engines emitted 1,004,600 tons

of CO in 1996 (1 percent of mobile source CO). Thus, nonroad diesel engines contribute to CO

nonattainment in more than one of these areas.

Although nonroad diesel engines have relatively low per-engine CO emissions, they can be a

significant source of ambient CO levels in CO nonattainment areas. Thus, the emission benefits

from this final rule will help areas to attain and maintain the CO NAAQS.
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2.4.2 Health Effects of CO

Carbon monoxide enters the bloodstream through the lungs and forms carboxyhemoglobin

(COHb), a compound that inhibits the blood’s capacity to carry oxygen to organs and tissues.364,

365 Carbon monoxide has long been known to have substantial adverse effects on human health,

including toxic effects on blood and tissues, and effects on organ functions. Although there are

effective compensatory increases in blood flow to the brain, at some concentrations of COHb,

somewhere above 20 percent, these compensations fail to maintain sufficient oxygen delivery,

and metabolism declines.366 The subsequent hypoxia in brain tissue then produces behavioral

effects, including decrements in continuous performance and reaction time.367

Carbon monoxide has been linked to increased risk for people with heart disease, reduced

visual perception, cognitive functions and aerobic capacity, and possible fetal effects.368 Persons

with heart disease are especially sensitive to carbon monoxide poisoning and may experience

chest pain if they breathe the gas while exercising.369 Infants, elderly persons, and individuals

with respiratory diseases are also particularly sensitive. Carbon monoxide can affect healthy

individuals, impairing exercise capacity, visual perception, manual dexterity, learning functions,

and ability to perform complex tasks.370

Several recent epidemiological studies have shown a link between CO and premature

morbidity (including angina, congestive heart failure, and other cardiovascular diseases. Several

studies in the United States and Canada have also reported an association of ambient CO

exposures with frequency of cardiovascular hospital admissions, especially for congestive heart

failure (CHF). An association of ambient CO exposure with mortality has also been reported in

epidemiological studies, though not as consistently or specifically as with CHF admissions. 

EPA reviewed these studies as part of the Criteria Document review process.371

2.4.3 CO Nonattainment

The current primary NAAQS for CO are 35 parts per million for the one-hour average and 9

parts per million for the eight-hour average. These values are not to be exceeded more than once

per year. Air quality carbon monoxide value is estimated using EPA guidance for calculating

design values. Over 19 million people currently live in the 11 nonattainment areas for the CO

NAAQS. 

Nationally, significant progress has been made over the last decade to reduce CO emissions

and ambient CO concentrations. Total CO emissions from all sources have decreased 16 percent

from 1989 to 1998, and ambient CO concentrations decreased by 39 percent. During that time,

while the mobile source CO contribution of the inventory remained steady at about 77 percent,

the highway portion decreased from 62 percent of total CO emissions to 56 percent while the

nonroad portion increased from 17 percent to 22 percent.372 Over the next decade, we expect

there to be a minor decreasing trend from the highway segment due primarily to the more

stringent standards for certain light-duty trucks and gasoline nonroad engines.373 CO standards
Air Quality, Health, and Welfare Effects

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for passenger cars and other light-duty trucks and heavy-duty vehicles did not change as a result

of other recent rulemakings.

 As noted above, CO has been linked to numerous health effects; however, we are unable to

quantify the CO-related health or environmental effects of the Nonroad Diesel Engine rule at this

time. However, nonroad diesel engines do contribute to nonattainment in some areas. Thus, the

emission benefits from this rule will help areas to attain and maintain the CO NAAQS.
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74.Maheswaran, R. and Elliott, P. (2003) Stroke mortality associated with living near main roads

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75.Garshick, E.; Laden, F.; Hart, J.E.; et al. (2003) Residence near a major road and respiratory

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76. Brauer, M; Hoek, G; Van Vliet, P.; et al. (2002) Air pollution from traffic and the

development of respiratory infections and asthmatic and allergic symptoms in children. Am J

Respir Crit Care Med 166(8):1092-8.

77.English, P.; Neutra, R.; Scalf, R.; et al. (1999). Examining associations between childhood

asthma and traffic flow using a geographic information system. Environ Health Perspect

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78.Pershagen, G.; Rylander, E.; Norberg, S.; et al. (1995) Air pollution involving nitrogen

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79.Weiland, S.K.; Mundt, K.A.; Ruckmann, A.; et al. (1994) Self-reported wheezing and allergic

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80.Duhme, H.; Weiland, S.K.; Keil, U.; et al. (1996) The association between self-reported

symptoms of asthma and allergic rhinitis and self-reported traffic density on street of residence

in adolescents. Epidemiology 7:578–582.

81.van Vliet, P.; Knape, M.; de Hartog, J; et al. (1997) Motor vehicle exhaust and chronic

respiratory symptoms in children living near freeways. Environ Res 74:122–132.

82.Waldron, G; Pottle, B; and Dod, J. (1995) Asthma and the motorways — one district’s

experience. J Public Health Med 17:85–89.

83. Delfino RJ. (2002). Epidemiologic evidence for asthma and exposure to air toxics: linkages

between occupational, indoor, and community air pollution research. Env Health Perspect Suppl

110(4): 573-589.

84. Brunekreef, B; Janssen NA; de Hartog, J; et al. (1997). Air pollution from traffic and lung

function in children living near motor ways. Epidemiology (8): 298-303.

85. Wilhelm, M. and Ritz, B. (2003) Residential proximity to traffic and adverse birth outcomes

in Los Angeles County, California, 1994-1996. Environ Health Perspect 111(2): 207-216.

86. Bunn, H.J.; Dinsdale, D.; Smith, T.; et al. (2001) Ultrafine particles in alveolar macrophages

from normal children. Thorax 56(12):932-4.

87. Zhu, Y.; Hinds, W.C.; Kim, S.; et al. (2002) Concentration and size distribution of ultrafine

particles near a major highway. J Air Waste Manage Assoc 52: 1032-1042.

88. Zhu, Y.; Hinds, W.C.; Kim, S.; et al. (2002) Study of ultafine particles near a major highway

with heavy-duty diesel traffic. Atmos Environ 36:4323-4335.

89. Kittleson, D.B.; Watts, W.F.; and Johnson, J.P. (2001) Fine particle (nanoparticle) emissions

on Minnesota highways. Minnesota Department of Transportation Report No. MN/RC-2001-12. 
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90. Koman memorandum to the Docket. One-hour Ozone and PM10 Nonattainment Status and

Air Quality Data Update. August 11, 2003.

91. Rao, Venkatesh; Frank, N.; Rush, A.; and Dimmick, F. (November 13-15, 2002). Chemical

speciation of PM2.5 in urban and rural areas (November 13-15, 2002) In the Proceedings of the

Air & Waste Management Association Symposium on Air Quality Measurement Methods and

Technology, San Francisco Meeting.

92. EPA (2002) Latest Finds on National Air Quality, EPA454-K-02-001.

93. Mansell (2000). User’s Instructions for the Phase 2 REMSAD Preprocessors, Environ

International. Novato, CA. 2000.

94. IMPROVE (2000). Spatial and Seasonal Patterns and Temporal Variability of Haze and its

Constitutents in the United States. Report III. Cooperative Institute for Research in the

Atmosphere, ISSN: 0737-5352-47.

95. California Air Resources Board and New York State Department of Environmental

Conservation (April 9, 2002). Letter to EPA Administrator Christine Todd Whitman. 

96. State and Territorial Air Pollution Program Administrators (STAPPA) and Association of

Local Air Pollution Control Officials (ALAPCO) (December 17, 2002). Letter to EPA Assistant

Administrator Jeffrey R. Holmstead. 

97. Western Regional Air Partnership (WRAP) January 28, 2003), Letter to Governor Christine

Todd Whitman. 

98.National Research Council, 1993. Protecting Visibility in National Parks and Wilderness

Areas. National Academy of Sciences Committee on Haze in National Parks and Wilderness

Areas. National Academy Press, Washington, DC. This document is available on the internet at

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EPA600-P-99-002a; Docket No. A-99-06. Document Nos. II-A-18 to 20. 

U.S. EPA (1996). Review of the National Ambient Air Quality Standards for Particulate Matter:

Policy Assessment of Scientific and Technical Information OAQPS Staff Paper. EPA452-R-96-

013, 1996. Docket Number A-99-06, Documents No. II-A-23. The particulate matter air quality

criteria documents are also available at http://www.epa.gov/ncea/partmatt.htm. Also, U.S. EPA. 

Review of the National Ambient Air Quality Standards for Particulate Matter: Policy

Assessment of Scientific and Technical Information, OAQPS Staff Paper. Preliminary Draft. 

June 2001. Docket A-2000-01, Document IV-A-199.

99. Council on Environmental Quality, 1978. Visibility Protection for Class I Areas, the

Technical Basis. Washington DC. Cited in U.S. EPA, Review of the National Ambient Air

Quality Standards for Particulate Matter: Policy Assessment of Scientific and Technical

Information. OAQPS Staff Paper. EPA452- R-96-013. This document is available in Docket
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A-99-06, Document II-A-23.

100.U.S. EPA Trends Report 2001. This document is available on the internet at

http://www.epa.gov/airtrends/. 

101. Sisler, James F. Spatial and Seasonal Patterns and Long Term Variability of the

Composition of Haze in the United States: An Analysis of Data from the IMPROVE Network. 

1996. A copy of the relevant pages of this document can be found in Docket A-99-06,

Document No. II-B-21.

102.U.S. EPA Criteria for Particulate Matter, 8-3; U.S. EPA Review of the National Ambient

Air Quality Standards for Particulate Matter: Policy Assessment of Scientific and Technical

Information OAQPS Staff Paper. EPA452-R-96-013. 1996. Docket Number A-99-06,

Documents Nos. II-A-18, 19, 20, and 23. The particulate matter air quality criteria documents

are also available at http://www.epa.gov/ncea/partmatt.htm. Also, U.S. EPA. Review of the

National Ambient Air Quality Standards for Particulate Matter: Policy Assessment of Scientific

and Technical Information, OAQPS Staff Paper. Preliminary Draft. June 2001. Docket A2000-01, Document IV-A-199.

103. National Research Council, 1993 (Ibid). This document is available on the internet at

http://www.nap.edu/books/0309048443/html/. 

104.National Research Council, 1993 (Ibid). This document is available on the internet at

http://www.nap.edu/books/0309048443/html/. 

105. National Acid Precipitation Assessment Program (NAPAP), 1991. Office of the Director. 

Acid Deposition: State of Science and Technology. Report 24, Visibility: Existing and

Historical Conditions - Causes and Effects. Washington, DC. Cited in U.S. EPA, Review of the

National Ambient Air Quality Standards for Particulate Matter: Policy Assessment of Scientific

and Technical Information. OAQPS Staff Paper. EPA452- R-96-013. This document is

available in Docket A-99-06, Document II-A-23. Also, U.S. EPA. Review of the National

Ambient Air Quality Standards for Particulate Matter: Policy Assessment of Scientific and

Technical Information, OAQPS Staff Paper. Preliminary Draft. June 2001. Docket A-2000-01,

Document IV-A-199.

106.U.S. EPA. (2003). Air Quality Technical Support Document for the proposed Nonroad

Diesel rulemaking. OAQPS. April 2003. 

107.U.S. EPA (1996). Review of the National Ambient Air Quality Standards for Particulate

Matter: Policy Assessment of Scientific and Technical Information OAQPS Staff Paper. 

EPA452-R-96-013. 1996. Docket Number A-99-06, Documents No. II-A-23. The particulate

matter air quality criteria documents are also available at http://www.epa.gov/ncea/partmatt.htm.

108. U.S. EPA (1996). Review of the National Ambient Air Quality Standards for Particulate

Matter: Policy Assessment for Scientific and Technical Information, OAQPS Staff Paper,
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EPA452-R-96-013, July, 1996, at IV-7. This document is available from Docket A-99-06,

Document II-A-23.

109.US EPA Trends Report 2002

110.See 64 FR 35722, July 1, 1999.

111. Technical Memorandum, EPA Air Docket A-99-06, Eric O. Ginsburg, Senior Program

Advisor, Emissions Monitoring and Analysis Division, OAQPS, Summary of Absolute Modeled

and Model-Adjusted Estimates of Fine Particulate Matter for Selected Years, December 6, 2000,

Table P-2. Docket Number 2000-01, Document Number II-B-14.

112.Western Regional Air Partnership (WRAP) letter dated Jan 28, 2003 to Administrator

Christine Todd Whitman. 

113. U.S. EPA. (1993). Effects of the 1990 Clean Air Act Amendments on Visibility in Class I

Areas: An EPA Report to Congress. EPA452-R-93-014, Docket A-2000-01, Document IV-A220. And see also 64 FR 35722, July 1, 1999.

114.This goal was recently upheld by the U.S. Court of Appeals. American Corn Growers

Association v. EPA, 291F.3d 1 (D.C .Cir 2002). A copy of this decision can be found in Docket

A-2000-01, Document IV-A-113.

115.U.S. EPA. (1993). Effects of the 1990 Clean Air Act Amendments on Visibility in Class I

Areas: An EPA Report to Congress. EPA452-R-93-014, Docket A-2000-01, Document IV-A20.U.S. EPA Trends Report 2002. 

116. For more information and the IMPROVE data, see

http://vista.cira.colostate.edu/improve/data/IMPROVE/improve_data.htm.

117.National Park Service. Air Quality in the National Parks, Second edition. NPS, Air

Resources Division. D 2266. September 2002.

118.U.S. EPA Trends Report 2002.

119. Chestnut, L.G., and R.D. Rowe. 1990a. Preservation for Visibility Protection at the

National Parks: Draft Final Report. Prepared for Office of Air Quality Planning and Standards,

U.S. Environmental Protection Agency, and Air Quality Management Division, National Park

Service; Chestnut, L.G., and R.D. This document is available from Docket A-97-10, Document

II-A-33 Rowe. 1990b. A New National Park Visibility Value Estimates. In Visibility and Fine

Particles, Transactions of an AWMA/EPA International Speciality Conference. C.V. Mathai,

ed., Air and Waste Management Association, Pittsburg. Docket A-2000-01, IV-A-2000.

120.Much of the information in this subsection was excerpted from the EPA document, Human

Health Benefits from Sulfate Reduction, written under Title IV of the 1990 Clean Air Act

Amendments, U.S. EPA, Office of Air and Radiation, Acid Rain Division, Washington, DC
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20460, November 1995.

121.Acid Rain: Emissions Trends and Effects in the Eastern United States, U.S. General

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122. Acid Deposition Standard Feasibility Study: Report to Congress, EPA430-R-95-001a,

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123. Deposition of Air Pollutants to the Great Waters, Third Report to Congress, June, 2000.

124.Deposition of Air Pollutants to the Great Waters, Third Report to Congress, June, 2000.

Great Waters are defined as the Great Lakes, the Chesapeake Bay, Lake Champlain, and coastal

waters. The first report to Congress was delivered in May, 1994; the second report to Congress

in June, 1997.

125. Bricker, Suzanne B., et al., National Estuarine Eutrophication Assessment, Effects of

Nutrient Enrichment in the Nation’s Estuaries, National Ocean Service, National Oceanic and

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126. Deposition of Air Pollutants to the Great Waters, Third Report to Congress, June, 2000.

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128. The Impact of Atmospheric Nitrogen Deposition on Long Island Sound, The Long Island

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129. Dennis, Robin L., Using the Regional Acid Deposition Model to Determine the Nitrogen

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1997.

130. Dennis, Robin L., Using the Regional Acid Deposition Model to Determine the Nitrogen

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131. Much of this information was taken from the following EPA document: Deposition of Air

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132. The 1996 National Toxics Inventory, Office of Air Quality Planning and Standards,

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133. U.S. EPA. Control of Emissions of Hazardous Air Pollutants from Mobile Sources; Final

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134. U.S. EPA. (1999). Guidelines for Carcinogen Risk Assessment. Review Draft.

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135. U.S. EPA. (1986) .Guidelines for carcinogen risk assessment. Federal Register

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185. Cal-EPA. (1998) Measuring concentrations of selected air pollutants inside California

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196. U.S. EPA. (2002). Comparison of ASPEN Modeling System Results to Monitored

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202. International Agency for Research on Cancer, IARC. (1982). Monographs on the

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attached. Docket No. A-2000-01. Document No. IV-A-145. 

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322.U.S. EPA (2003). Technical Support Document for Nonroad Diesel Proposed Rulemaking. 

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326. NARSTO Synthesis Team (2000). An Assessment of Tropospheric Ozone Pollution: A

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328. Marr, L.C. and R.A. Harley (2002). Modeling the Effect of Weekday-Weekend

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329. Larsen, L.C. (2003). The Ozone Weekend Effect in California: Evidence Supporting NOx

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330. U.S. EPA (2003). Air Quality Technical Support Document for the proposed Nonroad

Diesel rulemaking. 

331. Two counties in the Atlanta CMSA and one in the Baltimore-Washington CMSA.

332. For example, see letters in the Air Docket for this rule from American Lung Association,

Clean Air Trust, California Environmental Protection Agency, New York State Department of
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2-151

Environmental Conservation, Texas Commission on Environmental Quality (TCEQ, formerly

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333. U.S. Environmental Protection Agency, 1999. The Benefits and Costs of the Clean Air

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334. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

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335. Winner, W.E., and C.J. Atkinson. 1986. Absorption of air pollution by plants, and

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336. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

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337. Tingey, D.T., and Taylor, G.E. 1982. Variation in plant response to ozone: a conceptual

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338. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

339. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

340. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

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341. Ollinger, S.V., J.D. Aber and P.B. Reich. 1997. Simulating ozone effects on forest

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342. Winner, W.E., 1994. Mechanistic analysis of plant responses to air pollution. Ecological

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343. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

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344. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

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Final Regulatory Impact Analysis

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345. Fox, S., and R. A. Mickler, eds.. 1996. Impact of Air Pollutants on Southern Pine Forests.

Springer-Verlag, NY, Ecol. Studies, Vol. 118, 513 pp.

346. National Acid Precipitation Assessment Program (NAPAP), 1991. National Acid

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347. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

348. De Steiguer, J., J. Pye, C. Love. 1990. Air pollution Damage to U.S. forests. Journal of

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349. Pye, J.M. Impact of ozone on the growth and yield of trees: A review. Journal of

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350. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

351. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

352. McBride, J.R., P.R. Miller, and R.D. Laven. 1985. Effects of oxidant air pollutants on

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353. Miller, P.R., O.C. Taylor, R.G. Wilhour. 1982. Oxidant air pollution effects on a western

coniferous forest ecosystem. Corvallis, OR: U.S. Environmental Protection Agency,

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354. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

355. Hardner, J., A. VanGeel, K. Stockhammer, J. Neumann, and S. Ollinger. 1999. 

Characterizing the Commercial Timber Benefits from Tropospheric Ozone Reduction

Attributable to the 1990 Clean Air Act Amendments, 1990-2010. Prepared for Office of Air

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356. U.S. EPA (1996). Air Quality Criteria for Ozone and Related Photochemical Oxidants,

EPA600-P-93-004aF. Docket No. A-99-06. Document Nos. II-A-15 to 17.

357. Kopp, R. J.; Vaughn, W. J.; Hazilla, M.; Carson, R. 1985. Implications of environmental

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Air Quality, Health, and Welfare Effects

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358. Adams, R. M.; Hamilton, S. A.; McCarl, B. A. 1986. The benefits of pollution control: the

case of ozone and U.S. agriculture. Am. J. Agric. Econ. 34: 3-19.

359. Adams, R. M.; Glyer, J. D.; Johnson, S. L.; McCarl, B. A. 1989. A reassessment of the

economic effects of ozone on U.S. agriculture. JAPCA 39:960-968.

360. Abt Associates, Inc. 1995. Urban ornamental plants: sensitivity to ozone and potential

economic losses. U.S. EPA, Office of Air Quality Planning and Standards, Research Triangle

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361. U.S. EPA (1993). Air Quality Criteria for Oxides of Nitrogen, EPA600-8-91-049aF. 

Docket No. A-2000-01. Document Nos. II-A-89.

362. U.S. EPA (1993). Air Quality Criteria for Oxides of Nitrogen, EPA600-8-91-049aF. 

Docket No. A-2000-01. Document Nos. II-A-89.

363. Hardner, J., A. VanGeel, K. Stockhammer, J. Neumann, and S. Ollinger. 1999. 

Characterizing the Commercial Timber Benefits from Tropospheric Ozone Reduction

Attributable to the 1990 Clean Air Act Amendments, 1990-2010. Prepared for Office of Air

Quality Planning and Standards, U.S. Environmental Protection Agency. 

364. U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide. EPA600-P-99-001F. June 1,

2000. U.S. Environmental Protection Agency, Office of Research and Development, National

Center for Environmental Assessment, Washington, D.C. 

http://www.epa.gov/ncea/pdfs/coaqcd.pdf (Docket A-2000-01, Document II-A-29).

365. Coburn, R.F. (1979) Mechanisms of carbon monoxide toxicity. Prev. Med. 8:310-322.

366. Helfaer, M.A., and Traystman, R.J. (1996) Cerebrovascular effects of carbon monoxide. 

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367. Benignus, V.A. (1994) Behavioral effects of carbon monoxide: meta analyses and

extrapolations. J. Appl. Physiol. 76:1310-1316. Docket A-2000-01, Document IV-A-127.

368. U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide. EPA600-P-99-001F. June 1,

2000. U.S. Environmental Protection Agency, Office of Research and Development, National

Center for Environmental Assessment, Washington, D.C. 

http://www.epa.gov/ncea/pdfs/coaqcd.pdf (Docket A-2000-01, Document II-A-29).

369. U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide. EPA600-P-99-001F. June 1,

2000. U.S. Environmental Protection Agency, Office of Research and Development, National

Center for Environmental Assessment, Washington, DC. 

http://www.epa.gov/ncea/pdfs/coaqcd.pdf (Docket A-2000-01, Document II-A-29).

370. U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide. EPA600-P-99-001F. June 1,

2000. U.S. Environmental Protection Agency, Office of Research and Development, National
Final Regulatory Impact Analysis

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Center for Environmental Assessment, Washington, DC. 

http://www.epa.gov/ncea/pdfs/coaqcd.pdf (Docket A-2000-01, Document II-A-29).

371. U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide. EPA600-P-99-001F. June 1,

2000. U.S. Environmental Protection Agency, Office of Research and Development, National

Center for Environmental Assessment, Washington, DC. 

http://www.epa.gov/ncea/pdfs/coaqcd.pdf (Docket A-2000-01, Document II-A-29).

372. National Air Quality and Emissions Trends Report, 1998, March, 2000; this document is

available at http://www.epa.gov/oar/aqtrnd98 National Air Pollutant Emission Trends, 1900-

1998 (EPA454-R-00-002), March 2000. These documents are available at Docket No. A-2000-

01, Document No. II-A-72. See also Air Quality Criteria for Carbon Monoxide, U.S. EPA,

EPA600-P-99-001F, June 2000, at 3-10. Air Docket A-2001-11. This document is also

available at http://www.epa.gov/ncea/coabstract.htm.

373. Ref for Tier 2 and Large SI rules 
CHAPTER 3: Emission Inventory

3.1 Nonroad Diesel Baseline Emission Inventory Development . . . . . . . . . . . . . . . . . . . . 3-2

3.1.1 Land-Based Nonroad Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.1.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.1.1.2 NONROAD’s Major Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

3.1.1.3 Emission Estimation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-8

3.1.1.4 Estimation of VOC Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-9

3.1.1.5 Estimation of SO2 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-10

3.1.1.6 Estimation of PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-10

3.1.1.7 Estimation of Fuel Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11

3.1.1.8 Changes from Draft NONROAD2002 to Draft NONROAD2004 . . . . . . 3-11

3.1.1.9 Baseline Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-12

3.1.2 Land-Based Nonroad Diesel Engines—Air Toxics Emissions . . . . . . . . . . . . . 3-15

3.1.3 Commercial Marine Vessels and Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . 3-16

3.1.4 Recreational Marine Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-21

3.1.5 Fuel Consumption for Nonroad Diesel Engines . . . . . . . . . . . . . . . . . . . . . . . . . 3-24

3.2 Contribution of Nonroad Diesel Engines to National Emission Inventories . . . . . . . . 3-26

3.2.1 Baseline Emission Inventory Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-26

3.2.2 PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28

3.2.3 NOx Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28

3.2.4 SO2 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.2.5 VOC Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.2.6 CO Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.3 Contribution of Nonroad Diesel Engines to Selected Local Emission Inventories . . . 3-37

3.3.1 PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-37

3.3.2 NOx Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-41

3.4 Nonroad Diesel Controlled Emission Inventory Development . . . . . . . . . . . . . . . . . . 3-43

3.4.1 Land-Based Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions . . . . 3-43

3.4.1.1 Standards and Zero-Hour Emission Factors . . . . . . . . . . . . . . . . . . . . . . . 3-44

3.4.1.2 Transient Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-44

3.4.1.3 Deterioration Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

3.4.1.4 In-Use Sulfur Levels, Certification Sulfur Levels, and Sulfur Conversion

Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

3.4.1.5 Controlled Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-49

3.4.2 Land-Based Diesel Engines—Air Toxics Emissions . . . . . . . . . . . . . . . . . . . . . 3-52

3.4.3 Commercial Marine Vessels and Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . 3-53

3.4.4 Recreational Marine Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-55

3.5 Projected Emission Reductions from the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . 3-58

3.5.1 PM2.5 Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-58

3.5.2 NOx Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-66

3.5.3 SO2 Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-68

3.5.4 VOC and Air Toxics Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-75

3.5.5 CO Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-78

3.5.6 PM2.5 and SO2 Reductions from the 15 ppm Locomotive and Marine (LM) Fuel

Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-79

3.5.7 SO2 and Sulfate PM Reductions from Other Nonhighway Fuel . . . . . . . . . . . . . 3-81

3.6 Emission Inventories Used for Air Quality Modeling . . . . . . . . . . . . . . . . . . . . . . . . . 3-86
Final Regulatory Impact Analysis

3-2

CHAPTER 3: Emission Inventory

This chapter presents our analysis of the emission impact of the final rule for the four

categories of nonroad diesel engines affected: land-based diesel engines, commercial marine

diesel vessels, locomotives, and recreational marine diesel engines. New engine controls are

being adopted for the land-based diesel engine category. For the other three nonroad diesel

categories, the final rule includes no new engine controls; however, the diesel fuel sulfur

requirements will decrease emissions of particulate matter smaller than 2.5 microns (PM2.5) and

sulfur dioxide (SO2) for these categories.

Section 3.1 presents an overview of the methodology used to generate the baseline

inventories. The baseline inventories represent current and future emissions with only the

existing standards. Sections 3.2 and 3.3 then describe the contribution of nonroad diesel engines

to national and selected local baseline inventories, respectively. Section 3.4 describes the

development of the controlled inventories, specifically the changes made to the baseline inputs to

incorporate the new standards and fuel sulfur requirements. Section 3.5 follows with the

projected emission reductions resulting from the final rule. Section 3.6 concludes the chapter by

describing the changes in the inputs and resulting emission inventories between the preliminary

baseline and control scenarios used for the air quality modeling and the updated baseline and

control scenarios in this final rule.

The controlled inventory estimates do not include the potential uses of the averaging,

banking, and trading (ABT) program or the transition provisions for engine manufacturers, since

these are flexibilities that would be difficult to predict and model. More information regarding

these provisions can be found in Section III of the preamble.

The estimates of baseline emissions and emission reductions for nonroad land-based,

recreational marine, locomotive, and commercial marine vessel diesel engines are reported for

both 48-state and 50-state inventories. The 48-state inventories are used for the air quality

modeling that EPA uses to analyze regional ozone and PM air quality, of which Alaska and

Hawaii are not a part. In addition, 50-state emission estimates for other sources (such as

stationary and area sources) are not available. As a result, in cases where nonroad diesel sources

are compared with other emission sources, the 48-state emission inventory estimates are used.

Inventories are presented for the following pollutants: PM2.5, PM10, oxides of nitrogen (NOx),

SO2, volatile organic compounds (VOC), carbon monoxide (CO), and air toxics. The specific air

toxics are benzene, formaldeyde, acetaldehyde, 1,3-butadiene, and acrolein. The PM inventories

include directly emitted PM only, although secondary sulfates are taken into account in the air

quality modeling.
Emission Inventory

3-3

3.1 Nonroad Diesel Baseline Emission Inventory Development

This section describes how the baseline emission inventories were developed for the four

categories of nonroad diesel engines affected by this final rule: land-based diesel engines,

commercial marine diesel vessels, locomotives, and recreational marine diesel engines. For

land-based diesel engines, there is a section that discusses inventory development for PM2.5,

NOx, SO2, VOC, and CO, followed by a section for air toxics.

3.1.1 Land-Based Nonroad Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions

The baseline emission inventories for land-based diesel engines were generated using the

draft NONROAD2004 model. The baseline inventories account for the effect of existing federal

emission standards that establish three tiers of emission standards (Tier 1 through Tier 3). 

Section 3.1.1.1 provides an overview of the draft NONROAD2004 model and a description of

the methodology used in the model to estimate emissions. Details of the baseline modeling

inputs (e.g., populations, activity, and emission factors) for land-based diesel engines can be

found in the technical reports documenting the model. The single scenario option variable that

affects diesel emissions is the in-use fuel sulfur level. The in-use diesel fuel sulfur level inputs

used for the baseline scenarios are given in Section 3.1.1.2.3.

For the proposed rule, the draft NONROAD2002 model was used. Section 3.1.1.8 describes

the changes made to the model for the final rule.

3.1.1.1 Overview

The draft NONROAD2004 model estimates emission inventories of important air emissions

from diverse nonroad equipment. The model’s scope includes all nonroad sources with the

exception of locomotives, aircraft and commercial marine vessels. Users can construct

inventories for criteria pollutants including carbon monoxide (CO), oxides of nitrogen (NOx),

oxides of sulfur (SO2), and particulate matter (PM), as well as other emissions including total

hydrocarbon (THC) and carbon dioxide (CO2). As a related feature, the model estimates fuel

consumption. The model can distinguish emissions on the basis of equipment type, size and

technology group. A central feature of the model is projection of future or past emissions

between 1970 and 2050.

The draft NONROAD2004 model contains three major components: (1) the core model, a

FORTRAN program that performs model calculations, (2) the reporting utility, a Microsoft

Access application that compiles and presents results, and (3) the graphic user interface (GUI), a

Visual-Basic application that allows users to easily construct scenarios for submission to the core

model. The following discussion will describe processes performed by the core model in the

calculation of emission inventories.
Final Regulatory Impact Analysis

3-4

I E ALPN exh exh = ⋅⋅⋅⋅

This section describes how the draft NONROAD2004 model estimates emissions particularly

relevant to this analysis, including particulate matter (PM), oxides of nitrogen (NOx), oxides of

sulfur (SO2), carbon monoxide (CO) and volatile organic compounds (VOC). As appropriate,

we will focus on estimation of emissions of these pollutants by diesel engines. The model

estimates emissions from approximately 80 types of diesel equipment. As with other engine

classes, the model defines engine or equipment “size” in terms of the rated power (horsepower)

of the engine. For diesel engines, the regulations also classify engines on the basis of rated

power.

The first four chemical species are exhaust emissions, i.e., pollutants emitted directly as

exhaust from combustion of diesel fuel in the engine. However, the last emission, VOC, includes

both exhaust and evaporative components. The exhaust component represents hydrocarbons

emitted as products of combustion; the evaporative component includes compounds emitted

from unburned fuel during operation, i.e., “crankcase emissions.” For VOC, we will first

describe estimation of total hydrocarbon exhaust emissions, in conjunction with the description

for the other exhaust emissions. We discuss subsequent estimation of associated VOC emissions

in Section 3.1.1.4.

3.1.1.2 NONROAD’s Major Inputs

The draft NONROAD2004 model uses three major sets of inputs in estimation of exhaust

emission inventories: (1) emission calculation variables, (2) projection variables, and (3)

scenario option variables.

3.1.1.2.1 Emission Calculation Variables

The draft NONROAD2004 model estimates exhaust emissions using the equation

where each term is defined as follows:

Iexh = the exhaust emission inventory (gram/year, gram/day),

Eexh = exhaust emission factor (gram/hp-hr),

A = equipment activity (operating hours/year),

L = Load factor (average proportion of rated power used during operation (percent)),

P = average rated power (hp)

N = Equipment population (units).

Emissions are then converted and reported as tons/year or tons/day.

For diesel engines, each of the inputs applies to sub-populations of equipment, as classified

by type (dozer, tractor, backhoe, etc.), rated power class (50-100 hp, 100-300 hp, etc.) and

regulatory tier (tier 1, tier 2, etc.).
Emission Inventory

3-5

TAF

EF

EF

transient

steady state

= −

Exhaust Emission Factor. The emission factor in a given simulation year consists of three

components, a “zero-hour” emission level (ZHL) , a transient adjustment factor (TAF) and a

deterioration factor (DF). The ZHL represents the emission rate for recently manufactured

engines, i.e., engines with few operating hours, and is typically derived directly from laboratory

measurements on new or nearly new engines on several commonly used duty cycles, hence the

term “zero-hour.”

Because most emission data have been collected under steady-state conditions (constant

engine speed and load), and because most real-world operation involves transient conditions

(variable speed and load), we attempt to adjust for the difference between laboratory

measurements and real-world operation through the use of transient adjustment factors (TAFs).

The TAF is a ratio representing the difference in the emission rate between transient and steadystate operation. The TAFs are estimated by collecting emission measurements on specific

engines using both transient and steady-state cycles, and calculating the ratio

where EFtransient is the measurement for a given engine on a specific transient cycle, and EFsteady-state

is the corresponding measurement for the same engine on a selected steady-state cycle.

Data from seven transient cycles were used to develop seven TAFs for each of the four

pollutants. The seven cycle TAFs were then binned into two categories, based on the cycle load

factors. TAFs were then assigned to each equipment type represented in the model on the basis

of engineering judgment. If steady-state operation was typical of an equipment type, no

adjustment was made (i.e., TAF = 1.0).

Emission factors in the model input file represent the product (ZHL@TAF) for each

combination of equipment type, size class and regulatory tier represented by the model. We refer

to this product as the “baseline emission factor.” For more detail on the derivation and

application of EFs and TAFs, refer to the model documentation on diesel emission factors.1

During a model run, the model applies emission deterioration to the baseline emission factor,

based on the age distribution of the equipment type in the year simulated. Deterioration

expresses an assumption that emissions increase with equipment age and is expressed as a

multiplicative deterioration factor (DF). Thus, the final emission factor applied in the simulation

year is the product ZHL@TAF@DF. Deterioration factors vary from year to year; we describe their

calculation in more detail in Section 3.1.1.2.2 below.

The model estimates fuel consumption by substituting brake-specific fuel consumption

(BSFC, lb/hp-hr) for the emission factor in the equation above. We apply a TAF to the BSFC but

assume that BSFC does not deteriorate with equipment age.

In estimation of PM emissions, we apply an additional adjustment to the emission factor to

account for the in-use sulfur level of diesel fuel.1

 Based on user-specified diesel sulfur levels for
Final Regulatory Impact Analysis

3-6

S BSFC S S PMadj SO4,S PM,S base in use = ⋅ ⋅ ⋅⋅ − m m − 0 01 .( )

a given scenario, NONROAD adjusts the PM emission factor by the margin SPMadj (g/hp-hr)

calculated as 

where: BSFC = brake-specific fuel consumption (g fuel/hp-hr),

mSO4,S = a constant, representing the sulfate fraction of total particulate sulfur, equal to 7.0

g PM SO4/g PM S,

mPM,S = a constant, representing the fraction of fuel sulfur converted to particulate sulfur,

equal to 0.02247 g PM S/g fuel S,

0.01 = conversion factor from wt% to wt fraction

Sbase = base sulfur level in NONROAD (0.33 wt%, 3300 ppm for pre-control and Tier 1

engines; 0.20 wt%, 2000 ppm for Tier 2-3 engines),

Sin-use = in-use diesel sulfur level as specified by user (wt%).

Equipment Activity. Activity represents the usage of equipment, expressed in operating

hours per year. Activity estimates are specific to equipment types and remain constant in any

given simulation year. Activity estimates for diesel equipment have been adopted from the

Partslink model, a commercial source developed and maintained by Power Systems

Research/Compass International, Inc. For discussion of activity estimates for specific equipment

types, refer to the technical documentation for the model.2

Load Factor. This parameter represents the average fraction of rated power that equipment

uses during operation. Load factors are assigned by equipment type, and remain constant in any

simulation year. For use in draft NONROAD2004, we derived load factors from the results of a

project designed to develop transient engine test cycles. During the course of the project, seven

cycles were developed, designed to represent the operation of specific common equipment types.

Specific load factors for the cycles fell into two broad groups, which we designated as “high”

and “low.” We calculated an average for each group, with the high group containing four cycles

and the low group three; resulting load factors were 0.59 for the high group and 0.21 for the low

group. Then, we assigned one of these two factors to each equipment type for which we believed

engineering judgment was sufficient to make an assignment. For remaining equipment types, for

which we considered engineering judgment insufficient to make an assignment, we assigned a

‘steady-state’ load factor, calculated as the average of load factors for all seven transient cycles

(0.43). Of NONROAD’s 90 diesel applications, half were assigned ‘high’ or ‘low’ load factors,

with the remainder assigned ‘steady-state’ load factors. For more detail on the derivation of load

factors and assignment to specific equipment types, refer to the appropriate technical report2

.

Rated Power. This parameter represents the average rated power for equipment, as assigned

to each combination of equipment type and rated-power class represented by the model. Values

assigned to a given type/power combination represents the sales-weighted average of engines for

that equipment type in that rated-power class.3 Rated-power assignments remain constant in any

given simulation year. For use in draft NONROAD2004, we obtained estimates from the

Partslink database, maintained by Power Systems Research/Compass International, Inc. The
Emission Inventory

3-7

product of load factor and rated power (LP) represents actual power output during equipment

operation.

Equipment Population. As the name implies, this model input represents populations of

equipment pieces. For diesel engines, the model generates separate sub-populations for

individual combinations of equipment type and rated-power class. However, unlike activity and

load factor, populations do not remain constant from year to year. Projection of future or past

populations is the means through which the draft NONROAD2004 model projects future or past

emissions. As a reference point, the input file contains populations in the model’s base year 2000

(updated from 1998 in draft NONROAD2002). We generated populations in the base year using

a simple attrition model that calculated base-year populations as a function of equipment sales,

scrappage, activity and load factor. Equipment sales by model year were obtained from the

commercially available Partslink database, developed and maintained by Power Systems

Research/Compass International, Inc. (PSR). This database contains sales estimates for nonroad

equipment for model years 1973 through 2000. Base-year population development is discussed

in the technical documentation.3

3.1.1.2.2 Projection Variables

The model uses three variables to project emissions over time: the annual population growth

rate, the equipment median life, and the relative deterioration rate. Collectively, these variables

represent population growth, changes in the equipment age distribution, and emission

deterioration.

Annual Population Growth Rate (percent/year). The population growth rate represents the

percentage increase in the equipment population for a given equipment type over successive

years. The growth rate is linear for diesel equipment, and is applied to the entire population,

including all rated-power classes and tiers.4

 Diesel growth rates vary by sector (e.g.,

agricultural, construction).

Equipment Median Life (hours @ full load). This variable represents the period of time over

which 50 percent of the engines in a given “model-year cohort” are scrapped. A “model-year

cohort” represents a sub-population of engines represented as entering the population in a given

year. The input value assumes that (1) engines are run at full load until failure, and (2)

equipment scrappage follows the model’s scrappage curve. During a simulation, the model uses

the “annualized median life,” which represents the actual service life of equipment in years,

depending on how much and how hard the equipment is used. Annualized median life is

calculated as median life in hours (lh), divided by the product of activity and load factor (ly =

lh/AL). Engines persist in the equipment population over two median lives (2ly); during the first

median life, 50 percent of the engines are scrapped, and over the second, the remaining 50

percent are scrapped. For a more detailed description of median life, see the model

documentation.2
Final Regulatory Impact Analysis

3-8

DF age

pollutant,tier,year pollutant,tier

year

= +















 1 d ly

Relative Deterioration Rate (percent increase in emission factor/percent median life

expended). This variable plays a key role in calculation of the deterioration factor. Values of the

relative deterioration rate are assigned based on pollutant, rated-power class, and tier. Using the

relative deterioration rate (d), the annualized median life (ly) and the equipment age, draft

NONROAD2004 calculates the deterioration factor as

where:

DFpollutant,year = the deterioration factor for a given pollutant for a model-year cohort in the

simulation year

d = the relative deterioration rate for a given pollutant (percent increase in emission

factor /percent useful life expended) and regulatory tier

age = the age of a specific model-year group of engines in the simulation year

ly = the annualized median life of the given model-year cohort (years)

The deterioration factor adjusts the exhaust emission factor for engines in a given model-year

cohort in relation to the proportion of median life expended. The model calculates the

deterioration linearly over one median life for a given model-year cohort (represented as a

fraction of the entire population). Following the first median life, the deteriorated emission

factor is held constant over the remaining life for engines in the cohort. The model’s

deterioration calculations are discussed in greater detail in the technical documentation.1

3.1.1.2.3 Scenario Option Variables

These inputs apply to entire model runs or scenarios, rather than to equipment. Scenario

options describe fuel characteristics and ambient weather conditions. The option that applies to

inventories for diesel equipment is the in-use diesel sulfur level (wt%).

The in-use diesel fuel sulfur level inputs used for land-based diesel engines for the baseline

scenarios are provided in Table 3.1-1. The fuel sulfur levels account for spillover use of

highway fuel and are discussed in more detail in Chapter 7. The in-use sulfur levels in Table

3.1-1 used for modeling differ slightly from those presented in Chapter 7, since minor revisions

were made subsequent to the modeling.
Emission Inventory

3-9

N N ng year base = + ( ) 1

Table 3.1-1

Modeled Baseline In-Use Diesel Fuel Sulfur Content

for Land-Based Nonroad Diesel Engines

Calendar Year 48-State Fuel Sulfur

(ppm)

50-State Fuel Sulfur

(ppm)

through 2005 2283 2284

2006 2249 2242

2007-2009 2224 2212

2010 2167 2155

2011+ 2126 2114

3.1.1.3 Emission Estimation Process

To project emissions in a given year, the draft NONROAD2004 model performs a series of

steps (not necessarily in the order described).

Equipment Population. The model projects the equipment population for the user-specified

simulation year. The current year’s population (Nyear) is projected as a function of the base-year

population (Nbase) as

where g is the annual growth rate and n is the number of years between the simulation year and

the base year. For diesel equipment, population projection follows a linear trend as in the

equation above. Diesel growth rates in the model vary only by sector (e.g., agricultural,

construction). The sector-specific growth rates are applied to all equipment types and hp

categories within each sector.

Equipment Age Distribution. The model assigns an age distribution for each sub-population

calculated in the previous step. This calculation divides the total population into a series of

model-year cohorts of decreasing size, with the number of cohorts equal to twice the annualized

median life for the rated-power class under consideration (2ly). Each model-year cohort is

estimated as a fraction of the total population, using fractions derived from NONROAD’s

scrappage curve, scaled to the useful life of the given rated-power class, also equal to 2ly.

5

Emission and Deterioration Factors. Because the previous steps were performed for engines

of a given rated-power class, the model assigns emission factors to different model year cohorts

simply by relating equipment age to regulatory tier. Similarly, the model calculates deterioration

factors for each cohort. The algorithm identifies the appropriate relative deterioration rate in

relation to tier and rated-power class, calculates the age of the cohort, and supplies these inputs

to the deterioration factor equation.
Final Regulatory Impact Analysis

3-10

I E ALPN exh,poll exh,poll ( )

sum over all model-year cohorts

within a rated-power class

sum over all rated-power classes

within an equipment type 

sum over all equipment types

= ⋅⋅⋅⋅ 



 

































∑ ∑ ∑

6 7 4444 8 4444

6 7 44444 8 44444

6 7 444444 8 444444

VOC THC + (RCHO RCOH) (CH CH CH ) = + −+4 33

EF EF crank,HC,year exh,HC,year = ⋅ 0 02 .

Activity and Load Factor. The model obtains the appropriate activity, load factor and rated

power estimates. Activity and load factor are defined on the basis of equipment type alone; they

are constant for all model-year cohorts, and rated power is determined on the basis of equipment

type and rated power class.

Emission Calculation. For a given pollutant, the calculations described above are performed

and the resulting inputs multiplied in the exhaust emission equation. The steps are repeated for

each rated-power class within an equipment type to obtain total emissions for that type. The

resulting subtotals for equipment types are then summed to obtain total emissions from all

equipment types included in the simulation. These processes are repeated for each pollutant

requested for the simulation. Using summation notation, the process may be summarized as 

3.1.1.4 Estimation of VOC Emissions

Volatile organic compounds are a class of hydrocarbons considered to be of regulatory

interest. For purposes of inventory modeling, we define VOC as total hydrocarbon (THC) plus

reactive oxygenated species, represented by aldehydes (RCHO) and alcohols (RCOH), less

nonreactive species represented by methane and ethane (CH4 and CH3CH3), as follows:

The NONROAD model estimates VOC in relation to THC, where THC is defined as those

hydrocarbons measured by a flame ionization detector (FID) calibrated to propane. Total

hydrocarbon has exhaust and evaporative components, where the evaporative THC represents

‘crankcase emissions.’ Crankcase emissions are hydrocarbons that escape from the cylinder

through the piston rings into the crankcase. The draft NONROAD2004 model assumes that all

diesel engines have open crankcases, allowing that gases in the crankcase to escape to the

atmosphere.

For diesel engines, the emission factor for crankcase emissions (EFcrank) is estimated as a

fraction of the exhaust emission factor (EFexh), as
Emission Inventory

3-11

VOC THC VOC THC exh exh crank crank =⋅ =⋅ 1053 1053 ., .

EF BSFC EF S SO PM,S THC in use SO ,S 2 = ⋅− − ⋅ ⋅ [ ] − 2 ( ) 1 m m

Note that the model adjusts crankcase emissions for deterioration. In a given simulation year,

the crankcase emission factor is calculated from the deteriorated exhaust emission factor for that

year, i.e., EFexh,year = ZHL@TAF @DFyear.

The model estimates exhaust and crankcase VOC as a fraction of exhaust and crankcase

THC, respectively.

Note the fraction is greater than one, reflecting the addition of oxygenated species to THC. For

additional discussion of the model’s estimation of crankcase and VOC emissions, refer to the

model documentation.1, 6

3.1.1.5 Estimation of SO2 Emissions

To estimate SO2 emissions, the draft NONROAD2004 model does not use an explicit

emission factor. Rather, the model estimates a SO2 emission factor EFSO2 on the basis of brakespecific fuel consumption, the user-defined diesel sulfur level, and the emission factor for THC.

where:

BSFC = brake-specific fuel consumption (g/hp-hr),

mPM,S = a constant, representing the fraction of fuel sulfur converted to particulate sulfur,

equal to 0.02247 g PM S/g fuel S,

EFTHC = the in-use adjusted THC emission factor (g/hp-hr),

Sin-use = the user-specified scenario-specific sulfur content of diesel fuel (weight fraction),

and 

mSO2,S = a constant, representing fraction of fuel sulfur converted to SO2, equal to 2.0 g

SO2/g S.

This equation includes corrections for the fraction of sulfur that is converted to PM (mPM,S)

and for the sulfur remaining in the unburned fuel (EFTHC). The correction for unburned fuel, as

indicated by THC emissions, is more significant for gasoline emissions, but insubstantial for

diesel emissions.

Having estimated EFSO2, the model estimates SO2 emissions as it does other exhaust emissions.

3.1.1.6 Estimation of PM2.5 Emissions

The model estimates emissions of diesel PM2.5 as a multiple of PM10 emissions. PM2.5 is

estimated to compose 97 percent of PM10 emissions. This is an updated estimate, based on an

analysis of size distribution data for diesel engines.7
Final Regulatory Impact Analysis

3-12

F 

BSFC A L P N

D = ⋅⋅⋅⋅

3.1.1.7 Estimation of Fuel Consumption

The draft NONROAD2004 model estimates fuel consumption using the equation

where:

F = fuel consumption (gallons/year)

BSFC = brake-specific fuel consumption (lb/hp-hr)

A = equipment activity (operating hours/year)

L = load factor (average proportion of rated power used during operation (percent))

P = average rated power (hp)

N = equipment population (units)

D = fuel density (lb/gal); diesel fuel density = 7.1 lb/gal

The fuel consumption estimates for land-based diesel and recreational marine diesel engines

are given in Section 3.1.5.

3.1.1.8 Changes from Draft NONROAD2002 to Draft NONROAD2004

For the final rule, we have updated the model to incorporate the following changes:

1) Draft NONROAD2004 contains more horsepower bins in order to model the final standards. 

Specifically, the 50-100 hp bin was split into 50-75 hp and 75-100 hp bins. Also, the 1000-

1500 hp bin was split into 1000-1200 hp and 1200-1500 hp bins.

2) Draft NONROAD2004 eliminates the Tier 3 NOx and PM transient adjustment factors

(TAFs) for steady-state applications, which were mistakenly included in draft

NONROAD2002.

3) The base year populations in draft NONROAD2004 were updated from 1998 to 2000, based

on newer sales data.

4) The PM2.5 fraction of PM10 was revised from 0.92 to 0.97, based on an updated analysis of

size distribution data for diesel engines.

5) The recreational marine populations, median life, and deterioration factors for HC and NOx

were revised to match what was used in the 2002 final rulemaking that covers large spark

ignition engines (>25 hp), recreational equipment, and recreational marine diesel engines

(>50 hp).8

 The exhaust emission factors for these three categories were also revised in draft

NONROAD2004 to reflect the final standards.

6) The output label was changed from ‘SOx’ to ‘SO2' to avoid confusion, since SO2 emissions

are calculated by the model.
Emission Inventory

3-13

For land-based diesel nonroad engines, the net effect of these changes is generally within 3

percent, with the direction and variation of the change dependent on the calendar year and

pollutant of interest.

3.1.1.9 Baseline Inventory

Tables 3.1-2a and 3.1-2b present the PM10, PM2.5, NOx, SO2, VOC, and CO baseline

emissions for land-based nonroad engines in 1996 and 2000-2040, for the 48-state and 50-state

inventories, respectively.
Final Regulatory Impact Analysis

3-14

Table 3.1-2a

Baseline (48-State) Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 192,275 186,507 1,564,904 143,572 220,971 1,004,586

2000 176,056 170,774 1,550,355 161,977 199,887 916,507

2001 170,451 165,338 1,537,890 166,644 191,472 880,129

2002 165,017 160,067 1,526,119 171,309 183,525 845,435

2003 159,268 154,490 1,505,435 175,971 176,383 813,886

2004 153,932 149,314 1,486,335 180,630 169,873 787,559

2005 148,720 144,259 1,467,547 185,287 163,663 763,062

2006 143,840 139,525 1,435,181 187,085 156,952 741,436

2007 139,990 135,791 1,399,787 189,511 150,357 724,449

2008 137,366 133,245 1,359,661 194,019 143,306 710,202

2009 135,097 131,044 1,317,995 198,526 136,426 697,893

2010 132,712 128,730 1,278,038 197,829 129,711 687,234

2011 130,964 127,035 1,242,159 198,415 123,573 678,980

2012 130,091 126,189 1,211,982 202,740 118,363 674,285

2013 129,779 125,885 1,188,162 207,062 114,022 672,732

2014 129,700 125,809 1,168,310 211,382 110,284 672,819

2015 129,831 125,936 1,152,199 215,699 107,084 674,296

2016 130,128 126,224 1,139,969 219,971 104,426 677,095

2017 130,606 126,688 1,130,663 224,241 102,252 681,156

2018 131,211 127,275 1,124,057 228,510 100,383 685,866

2019 131,993 128,034 1,120,529 232,777 98,766 691,194

2020 133,049 129,058 1,119,481 237,044 97,513 697,630

2021 134,251 130,223 1,120,802 241,309 96,566 704,932

2022 135,491 131,426 1,124,159 245,573 95,837 712,591

2023 136,799 132,695 1,129,090 249,836 95,344 720,565

2024 138,136 133,992 1,135,338 254,099 95,061 729,001

2025 139,555 135,369 1,142,889 258,360 94,975 737,967

2026 141,007 136,777 1,151,480 262,591 95,043 747,219

2027 142,429 138,156 1,160,868 266,822 95,234 756,611

2028 143,901 139,584 1,170,868 271,052 95,529 766,274

2029 145,385 141,023 1,181,457 275,282 95,906 776,141

2030 146,891 142,484 1,192,833 279,511 96,374 786,181

2031 148,452 143,999 1,205,007 283,740 96,942 796,408

2032 150,035 145,534 1,217,535 287,969 97,568 806,761

2033 151,640 147,091 1,230,337 292,198 98,241 817,199

2034 153,253 148,655 1,243,467 296,426 98,967 827,712

2035 154,851 150,205 1,256,924 300,654 99,747 838,224

2036 156,499 151,804 1,270,722 304,882 100,591 848,884

2037 158,171 153,426 1,284,718 309,110 101,473 859,588

2038 160,204 155,398 1,299,415 313,337 102,472 870,258

2039 162,240 157,373 1,314,296 317,564 103,495 880,968

2040 164,275 159,346 1,329,330 321,792 104,543 891,684
Emission Inventory

3-15

Table 3.1-2b

Baseline (50-State) Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 193,166 187,371 1,573,083 144,409 222,084 1,009,804

2000 176,881 171,575 1,558,392 162,920 200,903 921,226

2001 171,256 166,118 1,545,852 167,615 192,447 884,645

2002 165,801 160,827 1,534,007 172,307 184,462 849,756

2003 160,030 155,229 1,513,203 176,996 177,287 818,037

2004 154,670 150,030 1,493,989 181,683 170,744 791,568

2005 149,434 144,951 1,475,092 186,368 164,505 766,944

2006 144,479 140,145 1,442,534 187,508 157,762 745,216

2007 140,579 136,362 1,406,936 189,505 151,134 728,159

2008 137,945 133,807 1,366,584 194,013 144,049 713,862

2009 135,668 131,598 1,324,685 198,521 137,135 701,516

2010 133,274 129,276 1,284,510 197,795 130,388 690,829

2011 131,521 127,576 1,248,440 198,360 124,220 682,563

2012 130,648 126,729 1,218,098 202,685 118,984 677,865

2013 130,337 126,426 1,194,153 207,006 114,621 676,320

2014 130,260 126,352 1,174,204 211,325 110,863 676,420

2015 130,394 126,482 1,158,023 215,641 107,647 677,918

2016 130,695 126,774 1,145,751 219,912 104,977 680,746

2017 131,178 127,243 1,136,425 224,181 102,793 684,843

2018 131,788 127,835 1,129,817 228,449 100,917 689,593

2019 132,575 128,598 1,126,301 232,716 99,294 694,964

2020 133,637 129,628 1,125,276 236,982 98,037 701,445

2021 134,844 130,799 1,126,633 241,246 97,086 708,795

2022 136,091 132,008 1,130,034 245,509 96,355 716,502

2023 137,406 133,284 1,135,015 249,772 95,860 724,528

2024 138,750 134,587 1,141,319 254,033 95,575 733,017

2025 140,177 135,972 1,148,929 258,294 95,490 742,039

2026 141,637 137,388 1,157,584 262,525 95,558 751,348

2027 143,067 138,775 1,167,040 266,754 95,752 760,798

2028 144,547 140,211 1,177,111 270,984 96,049 770,520

2029 146,038 141,657 1,187,773 275,213 96,429 780,446

2030 147,552 143,126 1,199,225 279,442 96,900 790,547

2031 149,123 144,649 1,211,478 283,670 97,472 800,835

2032 150,715 146,193 1,224,086 287,898 98,102 811,250

2033 152,329 147,759 1,236,969 292,126 98,779 821,751

2034 153,950 149,332 1,250,181 296,354 99,511 832,326

2035 155,557 150,891 1,263,722 300,581 100,296 842,901

2036 157,214 152,498 1,277,605 304,808 101,146 853,624

2037 158,896 154,129 1,291,688 309,035 102,033 864,392

2038 160,938 156,110 1,306,473 313,262 103,038 875,126

2039 162,984 158,095 1,321,443 317,489 104,068 885,901

2040 165,028 160,077 1,336,566 321,715 105,122 896,682
Final Regulatory Impact Analysis

3-16

3.1.2 Land-Based Nonroad Diesel Engines—Air Toxics Emissions

EPA focused on five major air toxics pollutants for this rule: benzene, formaldehyde,

acetaldehyde, 1,3-butadiene, and acrolein. These pollutants are VOCs and are included in the

total land-based nonroad diesel VOC emission estimate. EPA developed the baseline inventory

estimates for these pollutants by multiplying the baseline VOC emissions from the draft 

NONROAD2004 model for a given year by the constant fractional amount that each air toxic

pollutant contributes to VOC emissions. Table 3.1-3 shows the fractions that EPA used for each

air toxics pollutant. EPA developed these nonroad air toxics pollutant fractions for the National

Emission Inventory.9

Table 3.1-3

Air Toxics Fractions of VOC

Benzene Formaldehyde Acetaldehyde 1,3-Butadiene Acrolein

0.020 0.118 0.053 0.002 0.003

Tables 3.1-4a and 3.1-4b show our 48-state and 50-state estimates of national baseline

emissions for five selected major air toxic pollutants (benzene, formaldehyde, acetaldehyde,

1,3-butadiene, and acrolein) for 1996, as well as for selected years from 2005 to 2030, modeled

with the existing Tier 1-3 standards. Toxics emissions decrease over time until 2025 as engines

meeting the Tier 1-3 standards are introduced into the fleet. Beyond 2025, the growth in

population overtakes the effect of the existing emission standards. Chapter 2 discusses the

health effects of these pollutants.

Table 3.1-4a

Baseline (48-State) Air Toxics Emissions 

for Land-Based Nonroad Diesel Engines (short tons)

Year Benzene Formaldehyde Acetaldehyde 1,3-Butadiene Acrolein

1996 4,419 26,075 11,711 442 663

2000 3,998 23,587 10,594 400 600

2005 3,273 19,312 8,674 327 491

2007 3,007 17,742 7,969 301 451

2010 2,594 15,306 6,875 259 389

2015 2,142 12,636 5,675 214 321

2020 1,950 11,507 5,168 195 293

2025 1,900 11,207 5,034 190 285

2030 1,927 11,372 5,108 193 289
Emission Inventory

3-17

Table 3.1-4b

Baseline (50-State) Air Toxics Emissions 

for Land-Based Nonroad Diesel Engines (short tons)

Year Benzene Formaldehyde Acetaldehyde 1,3-Butadiene Acrolein

1996 4,442 26,206 11,770 444 666

2000 4,018 23,707 10,648 402 603

2005 3,290 19,412 8,719 329 494

2007 3,023 17,834 8,010 302 453

2010 2,608 15,386 6,911 261 391

2015 2,153 12,702 5,705 215 323

2020 1,961 11,568 5,196 196 294

2025 1,910 11,268 5,061 191 286

2030 1,938 11,434 5,136 194 291

3.1.3 Commercial Marine Vessels and Locomotives

Though no new engine controls are being proposed for diesel commercial marine and

locomotive engines, these engines use diesel fuel and the effects of the fuel changes in the final

rule need to be modeled. This section addresses the modeling of the baseline case for these

engines, which includes effects of certain other rules such as (a) the April 1998 final rule for

locomotives, (b) the December 1999 final rule for Category 1 and 2 commercial marine diesel

engines, (c) the January 2003 final rule for Category 3 commercial marine residual engines, and

(c) the January 2001 heavy duty highway diesel fuel rule that takes effect in June 2006.

Since the draft NONROAD2004 model does not generate emission estimates for these

applications, the emission inventories were calculated using the following methodology. VOC,

CO, and NOx emissions for 1996, 2020, and 2030 (the years chosen for air quality modeling) for

commercial marine diesel engines were taken from the rulemaking documentation. For

locomotives, the fuel-specific emission factors from the rulemaking documentation were

multiplied by the updated fuel consumption annual estimates described in Chapter 7 to obtain the

emission estimates. The VOC, CO, and NOx emission estimates for commercial marine diesel

engines and locomotives are presented in Table 3.1-5. VOC emissions were calculated by

multiplying THC emissions by a factor of 1.053, which is also the factor used for land-based

diesel engines.
Final Regulatory Impact Analysis

3-18

Table 3.1-5

Baseline (48-State) NOx, VOC, and CO Emissions 

for Locomotives and Commercial Marine Diesel Vessels (short tons)

Year NOx VOC CO

Locomotives CMV Locomotives CMV Locomotives CMV

1996 934,070 639,630 38,035 21,540 92,496 93,638

2020 508,084 587,115 30,125 24,005 99,227 114,397

2030 481,077 602,967 28,580 26,169 107,780 123,436

Tables 3.1-6a and 3.1-6b provide the 48-state and 50-state baseline fuel volumes, fuel sulfur

levels, PM sulfate, PM2.5, and SO2 emissions. The fuel sulfur levels account for "spillover" of

low-sulfur highway diesel fuel into use by nonroad applications. The slight decrease in average

sulfur level in 2006 is due to the introduction of highway diesel fuel meeting the 2007 15 ppm

standard, and the "spillover" of this highway fuel into the nonroad fuel pool. The derivation of

the fuel volumes and sulfur levels is discussed in more detail in Chapter 7. The marine fuel

volumes reported in Chapter 7 include both commercial and recreational marine usage. The fuel

consumption specific to commercial marine in Tables 3.1-6a and 3.1-6b was calculated by

subtracting the recreational marine fuel consumption as generated by the draft NONROAD2004

model.
3-19

Table 3.1-6a

Baseline (48-State) Fuel Sulfur Levels, SO2, Sulfate PM, and PM2.5 Emissions

 for Locomotives and Commercial Marine Diesel Vessels

Year

Locomotiv

e Usage

(109 gal/yr)

Commercial

Marine

Usage

(109 gal/yr)

Base 

Sulfur

Level

(ppm)

Base

SO2 Sulfate PM Total PM2.5

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr)

1996 3.065 1.644 2641 56,193 30,136 4,521 2,424 22,266 17,782

2000 2.687 1.556 2641 49,268 28,523 3,964 2,295 19,522 18,542

2001 2.772 1.533 2637 50,737 28,065 4,082 2,258 20,137 18,723

2002 2.692 1.493 2638 49,291 27,339 3,966 2,199 19,554 18,905

2003 2.722 1.507 2638 49,843 27,598 4,010 2,220 19,772 19,090

2004 2.741 1.518 2639 50,205 27,793 4,039 2,236 19,913 19,019

2005 2.762 1.522 2639 50,583 27,867 4,070 2,242 19,474 18,915

2006 2.818 1.556 2616 51,170 28,252 4,117 2,273 19,270 18,808

2007 2.868 1.575 2599 51,736 28,416 4,162 2,286 18,998 18,671

2008 2.900 1.594 2599 52,317 28,749 4,209 2,313 18,588 18,533

2009 2.939 1.609 2599 53,021 29,019 4,266 2,335 18,526 18,394

2010 2.986 1.625 2444 50,658 27,565 4,076 2,218 18,183 18,259

2011 3.043 1.646 2334 49,278 26,655 3,965 2,144 18,527 18,125

2012 3.073 1.663 2334 49,779 26,947 4,005 2,168 18,384 17,996

2013 3.097 1.674 2334 50,176 27,118 4,037 2,182 18,198 17,871

2014 3.121 1.691 2335 50,581 27,395 4,069 2,204 18,007 17,752

2015 3.148 1.706 2335 51,011 27,645 4,104 2,224 17,821 17,640

2016 3.181 1.718 2335 51,551 27,837 4,147 2,240 17,671 17,575

2017 3.210 1.733 2335 52,028 28,093 4,186 2,260 17,490 17,541

2018 3.234 1.757 2336 52,437 28,495 4,219 2,292 17,619 17,538

2019 3.266 1.786 2337 52,973 28,972 4,262 2,331 17,444 17,588

2020 3.288 1.804 2338 53,352 29,268 4,292 2,355 17,213 17,665

2021 3.305 1.823 2339 53,646 29,593 4,316 2,381 16,947 17,765

2022 3.335 1.852 2340 54,148 30,072 4,356 2,419 16,743 17,890

2023 3.364 1.870 2340 54,635 30,364 4,396 2,443 16,891 18,032

2024 3.393 1.893 2341 55,123 30,745 4,435 2,473 16,675 18,188

2025 3.426 1.912 2341 55,659 31,062 4,478 2,499 16,469 18,356

2026 3.455 1.935 2341 56,140 31,440 4,517 2,529 16,238 18,533

2027 3.483 1.958 2342 56,624 31,825 4,556 2,560 16,374 18,720

2028 3.513 1.981 2343 57,113 32,216 4,595 2,592 16,136 18,906

2029 3.542 2.005 2343 57,606 32,615 4,635 2,624 15,892 19,098

2030 3.572 2.030 2344 58,103 33,020 4,675 2,657 16,025 19,294

2031 3.602 2.055 2345 58,605 33,433 4,715 2,690 15,775 19,497

2032 3.632 2.080 2345 59,111 33,852 4,756 2,723 15,519 19,701

2033 3.662 2.106 2346 59,621 34,279 4,797 2,758 15,649 19,903

2034 3.693 2.132 2346 60,136 34,713 4,838 2,793 15,385 20,108

2035 3.724 2.158 2347 60,655 35,154 4,880 2,828 15,514 20,315

2036 3.755 2.185 2348 61,179 35,603 4,922 2,864 15,644 20,523

2037 3.786 2.213 2348 61,707 36,059 4,964 2,901 15,370 20,733

2038 3.818 2.240 2349 62,240 36,523 5,007 2,938 15,499 20,945

2039 3.850 2.269 2349 62,777 36,995 5,051 2,976 15,218 21,158

2040 3.882 2.298 2350 63,319 37,475 5,094 3,015 15,345 21,372
3-20

Table 3.1-6b

Baseline (50-State) Fuel Sulfur Levels, SO2, Sulfate PM, and PM2.5 Emissions 

for Locomotives and Commercial Marine Diesel Vessels

Year

Locomotiv

e Usage

(109 gal/yr)

Commercial

Marine

Usage

(109 gal/yr)

Base 

Sulfur

Level

(ppm)

Base

SO2 Sulfate PM Total PM2.5

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr)

1996 3.072 1.724 2640 56,287 31,587 4,528 2,541 22,319 18,717

2000 2.691 1.634 2640 49,305 29,926 3,967 2,408 19,551 19,518

2001 2.776 1.610 2635 50,778 29,454 4,085 2,370 20,167 19,708

2002 2.696 1.569 2637 49,330 28,702 3,969 2,309 19,583 19,900

2003 2.726 1.584 2637 49,882 28,978 4,013 2,331 19,801 20,095

2004 2.745 1.595 2637 50,244 29,186 4,042 2,348 19,943 20,020

2005 2.766 1.599 2637 50,622 29,269 4,073 2,355 19,502 19,911

2006 2.823 1.636 2588 50,693 29,374 4,078 2,363 19,298 19,798

2007 2.873 1.656 2552 50,877 29,330 4,093 2,360 19,026 19,653

2008 2.904 1.675 2552 51,447 29,676 4,139 2,388 18,616 19,508

2009 2.944 1.691 2552 52,140 29,958 4,195 2,410 18,553 19,363

2010 2.990 1.708 2400 49,822 28,464 4,008 2,290 18,210 19,220

2011 3.047 1.731 2292 48,471 27,529 3,900 2,215 18,554 19,079

2012 3.077 1.749 2292 48,962 27,832 3,939 2,239 18,411 18,943

2013 3.102 1.761 2292 49,351 28,012 3,970 2,254 18,225 18,811

2014 3.126 1.778 2293 49,748 28,299 4,002 2,277 18,034 18,686

2015 3.152 1.794 2293 50,169 28,559 4,036 2,298 17,847 18,568

2016 3.186 1.807 2293 50,701 28,761 4,079 2,314 17,697 18,500

2017 3.215 1.824 2293 51,170 29,028 4,117 2,335 17,516 18,464

2018 3.239 1.849 2294 51,567 29,442 4,149 2,369 17,645 18,461

2019 3.271 1.879 2295 52,091 29,934 4,191 2,408 17,469 18,514

2020 3.293 1.898 2295 52,462 30,240 4,221 2,433 17,238 18,595

2021 3.310 1.919 2296 52,747 30,576 4,244 2,460 16,972 18,700

2022 3.339 1.949 2297 53,236 31,069 4,283 2,500 16,767 18,831

2023 3.369 1.968 2297 53,714 31,372 4,321 2,524 16,916 18,981

2024 3.398 1.992 2298 54,191 31,766 4,360 2,556 16,699 19,146

2025 3.431 2.012 2298 54,717 32,095 4,402 2,582 16,493 19,322

2026 3.460 2.037 2298 55,187 32,486 4,440 2,614 16,262 19,509

2027 3.489 2.061 2299 55,661 32,884 4,478 2,646 16,398 19,705

2028 3.518 2.086 2299 56,139 33,288 4,517 2,678 16,159 19,901

2029 3.547 2.111 2300 56,621 33,699 4,555 2,711 15,916 20,104

2030 3.577 2.137 2300 57,107 34,118 4,594 2,745 16,049 20,309

2031 3.607 2.163 2301 57,597 34,543 4,634 2,779 15,798 20,523

2032 3.637 2.190 2301 58,092 34,976 4,674 2,814 15,542 20,738

2033 3.668 2.217 2302 58,591 35,416 4,714 2,849 15,672 20,951

2034 3.698 2.244 2302 59,094 35,864 4,754 2,885 15,408 21,166

2035 3.729 2.272 2303 59,601 36,319 4,795 2,922 15,537 21,384

2036 3.760 2.301 2303 60,113 36,782 4,836 2,959 15,667 21,603

2037 3.792 2.330 2304 60,629 37,252 4,878 2,997 15,393 21,825

2038 3.824 2.359 2304 61,150 37,731 4,920 3,036 15,522 22,047

2039 3.856 2.389 2305 61,675 38,217 4,962 3,075 15,240 22,271

2040 3.888 2.420 2305 62,205 38,711 5,005 3,114 15,368 22,497
Emission Inventory

3-21

Annual SO2 emission estimates for locomotives and commercial marine vessels were

calculated by multiplying the gallons of fuel use by the fuel density, the fuel sulfur content, and

the molecular weight ratio of SO2 to sulfur. This is then reduced by the fraction of fuel sulfur

that is converted to sulfate PM (2.247 percent on average for engines without aftertreatment).1 

Following is an example of the calculation for the case when fuel sulfur content is 2300 ppm.

SO2 tons = gallons × 7.1 lb/gallon × 0.0023 S wt. Fraction × (1-0.02247 S fraction converted to SO2) × 64/32

SO2 to S M.W. ratio / 2000 lb/ton 

Unlike the equation used in the draft NONROAD2004 model for land-based diesel and

recreational marine diesel engines (described in Section 3.1.1.5), this equation does not include a

correction for the sulfur remaining in the unburned fuel. The correction for unburned fuel, as

indicated by THC emissions is insubstantial for diesel emissions.

Annual sulfate PM emission estimates for locomotives and commercial marine vessels were

calculated by multiplying the gallons of fuel use by the fuel density, the fuel sulfur content, the

molecular weight ratio of hydrated sulfate to sulfur, and the fraction of fuel sulfur converted to

sulfate on average. Following is an example of the calculation for the case when fuel sulfur

content is 2300 ppm. 

Sulfate tons = gallons × 7.1 lb/gallon × 0.0023 S wt. Fraction × 0.02247 fraction of S converted

to sulfate × 224/32 sulfate to S M.W. ratio / 2000 lb/ton

The baseline sulfate PM estimates are not used to generate baseline PM10 emission estimates, but

are needed in order to calculate the PM benefits of reductions in fuel sulfur levels with the final

rule.

Annual total PM10 emission estimates for locomotives were calculated by multiplying the

gallons of fuel use by the gram per gallon PM emission factor from the 1998 locomotive final

rule Regulatory Support Document. Following is an example calculation:

PM10 tons = gallons × g/gal EF / 454g/lb / 2000 lbs/ton

Annual PM10 emission estimates for commercial marine vessels were derived from the

rulemaking documentation.

PM10 is assumed to be equivalent to total PM, and PM2.5 is estimated by multiplying PM10

emissions by a factor of 0.97. This is the factor used for all nonroad diesel engines; the basis is

described in Section 3.1.1.6.
Final Regulatory Impact Analysis

3-22

3.1.4 Recreational Marine Engines

Diesel recreational marine engines consist mainly of inboard engines used in larger power

boats and sailboats, but there are also a small number of outboard diesel engines in use. 

Emission estimates for this category were generated using the draft NONROAD2004 model. 

Details of the modeling inputs (e.g., populations, activity, and emission factors) for these engines

can be found in the technical reports documenting the draft NONROAD2004 model. The

emission inventory numbers presented here assume that recreational marine applications will use

diesel fuel with the same sulfur content and sulfur-to-sulfate conversion rate as locomotives and

commercial marine vessels.

It should be noted that, unlike the previous version of the NONROAD model, these

inventory values generated with the draft NONROAD2004 model now account for the newest

standards promulgated in September 2002, which take effect in 2006-2009, for diesel

recreational marine engines greater than 37 kw (50 hp). Although those standards provide

substantial benefits for the affected engines (e.g., 25 to 37 percent reductions of PM, NOx, and

HC in 2030), the impact of this on the total nonroad diesel inventory is quite small, representing

less than 1 percent of the baseline nonroad diesel inventory (without locomotives or commercial

marine) for PM, NOx, and HC in 2030.

Tables 3.1-7a and 3.1-7b present the PM10, PM2.5, NOx, SO2, VOC, and CO emissions for

recreational marine engines in 1996 and 2000-2040 for the 48-state and 50-state inventories,

respectively.
Emission Inventory

3-23

Table 3.1-7a

Baseline (48-State) Emissions for Recreational Marine Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 951 923 33,679 4,286 1,297 5,424

2000 1,070 1,038 37,943 4,831 1,455 6,098

2001 1,099 1,066 39,071 4,968 1,494 6,271

2002 1,130 1,096 40,198 5,114 1,533 6,444

2003 1,160 1,125 41,325 5,259 1,571 6,615

2004 1,190 1,154 42,452 5,406 1,609 6,787

2005 1,220 1,183 43,578 5,551 1,647 6,958

2006 1,233 1,196 44,105 5,647 1,657 7,128

2007 1,247 1,210 44,602 5,754 1,664 7,298

2008 1,262 1,225 45,066 5,897 1,670 7,467

2009 1,275 1,237 45,415 6,041 1,670 7,636

2010 1,257 1,219 45,729 5,816 1,668 7,804

2011 1,245 1,208 46,022 5,682 1,665 7,971

2012 1,254 1,216 46,282 5,811 1,660 8,137

2013 1,261 1,223 46,528 5,939 1,655 8,303

2014 1,269 1,230 46,765 6,070 1,649 8,469

2015 1,275 1,236 46,969 6,198 1,642 8,635

2016 1,280 1,242 47,168 6,327 1,634 8,802

2017 1,285 1,247 47,362 6,455 1,627 8,969

2018 1,290 1,251 47,525 6,587 1,618 9,137

2019 1,295 1,256 47,687 6,718 1,611 9,308

2020 1,300 1,261 47,847 6,850 1,604 9,482

2021 1,304 1,265 48,003 6,982 1,597 9,655

2022 1,309 1,270 48,182 7,114 1,592 9,829

2023 1,314 1,275 48,363 7,243 1,586 10,004

2024 1,320 1,281 48,593 7,375 1,583 10,178

2025 1,330 1,290 48,961 7,504 1,587 10,354

2026 1,344 1,303 49,501 7,633 1,599 10,529

2027 1,359 1,319 50,092 7,765 1,614 10,704

2028 1,376 1,335 50,716 7,897 1,630 10,880

2029 1,394 1,352 51,392 8,026 1,649 11,056

2030 1,413 1,371 52,085 8,158 1,669 11,232

2031 1,432 1,389 52,790 8,290 1,689 11,409

2032 1,451 1,408 53,510 8,419 1,710 11,585

2033 1,471 1,427 54,228 8,552 1,731 11,762

2034 1,491 1,446 54,959 8,681 1,753 11,938

2035 1,511 1,466 55,702 8,814 1,775 12,115

2036 1,531 1,485 56,444 8,946 1,798 12,292

2037 1,552 1,505 57,197 9,075 1,820 12,469

2038 1,573 1,526 57,963 9,208 1,844 12,646

2039 1,593 1,546 58,729 9,338 1,868 12,823

2040 1,615 1,566 59,506 9,471 1,892 13,001
Final Regulatory Impact Analysis

3-24

Table 3.1-7b

Baseline (50-State) Emissions for Recreational Marine Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 957 929 33,891 4,312 1,305 5,458

2000 1,076 1,044 38,182 4,859 1,464 6,137

2001 1,106 1,073 39,317 4,995 1,503 6,311

2002 1,137 1,103 40,452 5,145 1,542 6,484

2003 1,167 1,132 41,586 5,290 1,581 6,657

2004 1,197 1,161 42,719 5,436 1,619 6,829

2005 1,227 1,190 43,852 5,582 1,658 7,001

2006 1,236 1,199 44,383 5,622 1,667 7,173

2007 1,246 1,209 44,883 5,685 1,674 7,344

2008 1,262 1,224 45,350 5,827 1,680 7,514

2009 1,274 1,236 45,701 5,969 1,680 7,684

2010 1,256 1,219 46,018 5,747 1,678 7,853

2011 1,245 1,208 46,312 5,615 1,675 8,021

2012 1,253 1,215 46,573 5,742 1,671 8,189

2013 1,261 1,223 46,821 5,869 1,665 8,356

2014 1,268 1,230 47,060 5,998 1,660 8,523

2015 1,273 1,235 47,265 6,125 1,652 8,690

2016 1,279 1,241 47,465 6,252 1,645 8,857

2017 1,284 1,245 47,660 6,379 1,637 9,025

2018 1,288 1,250 47,825 6,509 1,629 9,195

2019 1,293 1,254 47,987 6,639 1,621 9,367

2020 1,298 1,259 48,148 6,766 1,614 9,541

2021 1,302 1,263 48,305 6,897 1,607 9,716

2022 1,307 1,268 48,485 7,027 1,602 9,891

2023 1,312 1,272 48,667 7,155 1,596 10,067

2024 1,317 1,278 48,899 7,285 1,593 10,243

2025 1,327 1,287 49,269 7,412 1,597 10,419

2026 1,341 1,301 49,813 7,540 1,609 10,595

2027 1,357 1,316 50,408 7,670 1,624 10,772

2028 1,373 1,332 51,036 7,797 1,640 10,949

2029 1,391 1,349 51,716 7,928 1,659 11,126

2030 1,410 1,367 52,413 8,055 1,679 11,303

2031 1,429 1,386 53,123 8,186 1,700 11,481

2032 1,448 1,404 53,847 8,313 1,721 11,658

2033 1,467 1,423 54,570 8,444 1,742 11,836

2034 1,487 1,442 55,305 8,572 1,764 12,013

2035 1,507 1,462 56,053 8,703 1,786 12,191

2036 1,527 1,481 56,799 8,830 1,809 12,369

2037 1,548 1,501 57,558 8,961 1,832 12,547

2038 1,568 1,521 58,329 9,089 1,856 12,726

2039 1,589 1,542 59,099 9,220 1,879 12,904

2040 1,610 1,562 59,881 9,348 1,904 13,082
Emission Inventory

3-25

3.1.5 Fuel Consumption for Nonroad Diesel Engines

Table 3.1-8 presents the fuel consumption estimates for the land-based, recreational marine,

locomotive, and commercial marine nonroad diesel categories. Fuel consumption estimates are

provided for 1996 and 2000-2040 for the 48-state and 50-state inventories.

The fuel consumption estimates for land-based diesel and recreational marine diesel engines

were obtained using the draft NONROAD2004 model. The methodology is described in Section

3.1.1.7. The derivation of the fuel consumption estimates for locomotives and commercial

marine vessels is described in Section 3.1.3.

For the final rule, the draft NONROAD2004 estimates for fuel consumption are the basis for

both inventory generation and for the cost analyses. The land-based diesel fuel estimates in

Chapter 7 differ from those presented in Table 3.1-8 by less than 1 percent, due to simple

rounding error.

Although the locomotive diesel demand volumes in this chapter are identical to those

described in Chapter 7, the marine diesel volumes are slightly different. In Chapter 7, the marine

end-use category is a combination of both commercial and recreational marine end uses. In this

chapter, recreational marine demand is estimated separately with the draft NONROAD2004

model for each calendar year, and subtracted from the respective combined marine end use

volume to produce the commercial marine estimate.
Final Regulatory Impact Analysis

3-26

Table 3.1-8

Fuel Consumption for Nonroad Diesel Engines

Year

Fuel Consumption (106

 gal/year)

Land-Based Diesel Recreational Marine Locomotives Commercial Marine

48-State 50-State 48-State 50-State 48-State 50-State 48-State 50-State

1996 9,120 9,169 234 236 3,065 3,072 1,644 1,724

2000 10,276 10,331 264 266 2,687 2,691 1,556 1,634

2001 10,568 10,625 272 274 2,772 2,776 1,533 1,610

2002 10,861 10,919 280 282 2,692 2,696 1,493 1,569

2003 11,153 11,213 288 289 2,722 2,726 1,507 1,584

2004 11,445 11,507 296 297 2,741 2,745 1,518 1,595

2005 11,737 11,801 303 305 2,762 2,766 1,522 1,599

2006 12,028 12,092 311 313 2,818 2,823 1,556 1,636

2007 12,318 12,384 319 321 2,868 2,873 1,575 1,656

2008 12,608 12,676 327 329 2,900 2,904 1,594 1,675

2009 12,898 12,968 335 337 2,939 2,944 1,609 1,691

2010 13,188 13,259 343 345 2,986 2,990 1,625 1,708

2011 13,480 13,553 351 353 3,043 3,047 1,646 1,731

2012 13,772 13,846 359 361 3,073 3,077 1,663 1,749

2013 14,063 14,139 367 369 3,097 3,102 1,674 1,761

2014 14,355 14,433 375 377 3,121 3,126 1,691 1,778

2015 14,647 14,726 383 385 3,148 3,152 1,706 1,794

2016 14,936 15,016 391 393 3,181 3,186 1,718 1,807

2017 15,224 15,307 399 401 3,210 3,215 1,733 1,824

2018 15,513 15,597 407 409 3,234 3,239 1,757 1,849

2019 15,802 15,887 415 417 3,266 3,271 1,786 1,879

2020 16,091 16,178 423 425 3,288 3,293 1,804 1,898

2021 16,380 16,468 431 433 3,305 3,310 1,823 1,919

2022 16,668 16,759 438 441 3,335 3,339 1,852 1,949

2023 16,957 17,049 446 449 3,364 3,369 1,870 1,968

2024 17,246 17,339 454 457 3,393 3,398 1,893 1,992

2025 17,535 17,630 462 465 3,426 3,431 1,912 2,012

2026 17,821 17,918 470 473 3,455 3,460 1,935 2,037

2027 18,108 18,206 478 481 3,483 3,489 1,958 2,061

2028 18,395 18,495 486 489 3,513 3,518 1,981 2,086

2029 18,682 18,783 494 497 3,542 3,547 2,005 2,111

2030 18,968 19,071 502 505 3,572 3,577 2,030 2,137

2031 19,255 19,360 510 513 3,602 3,607 2,055 2,163

2032 19,542 19,648 518 521 3,632 3,637 2,080 2,190

2033 19,829 19,936 526 529 3,662 3,668 2,106 2,217

2034 20,116 20,225 534 537 3,693 3,698 2,132 2,244

2035 20,402 20,513 542 545 3,724 3,729 2,158 2,272

2036 20,689 20,801 549 553 3,755 3,760 2,185 2,301

2037 20,976 21,090 557 561 3,786 3,792 2,213 2,330

2038 21,263 21,378 565 569 3,818 3,824 2,240 2,359

2039 21,549 21,666 573 577 3,850 3,856 2,269 2,389

2040 21,836 21,955 581 585 3,882 3,888 2,298 2,420
Emission Inventory

3-27

3.2 Contribution of Nonroad Diesel Engines to National Emission

Inventories

This section provides the contribution of nonroad diesel engines to national baseline

emission inventories in 1996, 2020, and 2030. The emission inventories are based on 48-state

inventories that exclude Alaska and Hawaii to be consistent with the air quality modeling region. 

The baseline cases represent current and future emissions only with the existing standards. For

the final rule, these baseline inventories now incorporate recent standards that cover large sparkignition engines (>25 hp), recreational equipment, and recreational marine diesel engines (>50

hp).10

The calendar years correspond to those chosen for the air quality modeling. Pollutants

discussed include PM2.5, NOx, SO2, VOC, and CO. VOC includes both exhaust and evaporative

emissions.

Of interest are the contributions of emissions from nonroad diesel sources affected by the

final rule. For PM2.5 and SO2, this includes emissions from all nonroad diesel sources. For NOx,

VOC, and CO, this includes emissions from land-based nonroad diesel engines. Contributions to

both total mobile source emissions and total emissions from all sources are presented. For PM2.5,

contributions of nonroad diesel engines to both total diesel PM2.5 and total manmade PM2.5 are

also presented.

The development of the 1996, 2020, and 2030 baseline emission inventories for the nonroad

sector and for the sectors not affected by this rule are briefly described, followed by discussions

for each pollutant of the contribution of nonroad diesel engines to national baseline inventories.

3.2.1 Baseline Emission Inventory Development

For 1996, 2020, and 2030, county-level emission estimates were developed by Pechan under

contract to EPA. These were used as input for the air quality modeling. These inventories

account for county-level differences in parameters such as fuel characteristics and temperature. 

The draft NONROAD2002 model was used to generate the county-level emission estimates for

all nonroad sources, with the exception of commercial marine engines, locomotives, and aircraft. 

The methodology has been documented elsewhere.11

The highway estimates are based on the MOBILE5b model, but with some further

adjustments to reflect MOBILE6 emission factors. The highway inventories are similar to those

prepared for HD2007 rulemaking, with the exception of adjustments to NOx and VOC for

California counties, based on county-level estimates from the California Air Resources Board.12

The stationary point and area source estimates are also based on the HD2007 rulemaking,

with the exception of adjustments to NOx and VOC for California counties, based on county-
Final Regulatory Impact Analysis

3-28

level estimates from the California Air Resources Board. There were also some stack parameter

corrections made to the point source estimates.

The inventories developed by Pechan were used in this section for the following categories:

recreational marine spark-ignition engines, commercial marine vessels fueled with gasoline and

coal, aircraft, and stationary point and area sources. For the remaining categories, updated

national estimates were substituted that reflect recent rulemakings and/or updated model inputs,

fuel parameters and usage. The basis for the updated estimates for the remaining categories is

described below.

The model inputs for the nonroad diesel sources have been described in detail in Section 3.1. 

The emission estimates for the land-based diesel and recreational marine diesel categories were

based on national level runs with the draft NONROAD2004 model. This was done for two

reasons. First, the baseline inventories for 2020 and 2030 were revised since the county-level

estimates were developed (specifically, PM2.5 and SO2 emissions were changed to reflect revised

diesel fuel sulfur inputs, standards affecting recreational marine diesel engines were

promulgated, and model inputs such as base year populations were updated). It was not possible

to develop revised county-level estimates for these categories due to resource and time

constraints. Second, county-level estimates were developed only for 2020 and 2030. Estimates

for interim years are also needed to fully evaluate the anticipated emission benefits of the final

rule. Interim year estimates are generated using national level model runs. To be consistent with

other sections of the Final RIA in which interim year estimates from 1996 to 2030 are presented,

the inventory estimates presented here for the land-based diesel and recreational marine diesel

categories are based on national level model runs. Model results for national level runs are

similar to those based on an aggregation of county-level runs.

For nonroad spark-ignition engines, the emission estimates were based on national level runs

with the draft NONROAD2004 model, in order to account for the recent rulemaking that affects

large spark-ignition engines. The draft NONROAD2004 model accounts for the exhaust

provisions of the rule. Additional adjustments were made to the VOC model output to account

for the evaporative provisions of the rule, since the draft NONROAD2004 model does not yet

incorporate the evaporative provisions of the rulemaking.

The commercial marine category has been divided into three subcategories: commercial

marine diesel, commercial marine residual, and commercial marine other. The commercial

marine diesel category includes compression-ignition engines using diesel fuel (generally

includes Category 1 and 2 engines). The commercial marine residual category includes

compression-ignition engines using residual fuel (includes Category 3 engines). The commercial

marine other category includes commercial marine engines using gasoline or coal. The emission

estimates for the commercial marine diesel and residual categories were updated to reflect the

1999 and 2003 rulemakings affecting commercial marine compression-ignition engines. In

addition, the SO2 estimates for commercial marine diesel vessels are based on the updated fuel

sulfur levels and fuel consumption estimates provided in Section 3.1.
Emission Inventory

3-29

Emission estimates for the locomotive category were revised to reflect the updated fuel sulfur

levels and fuel consumption estimates provided in Section 3.1. Finally, the motorcycle portions

of the highway estimates were revised to incorporate updated estimates contained in the recent

rulemaking affecting motorcycles.

3.2.2 PM2.5 Emissions

Table 3.2-1 provides the contribution of land-based diesel engines and other source

categories to total diesel PM2.5 emissions.

PM2.5 emissions from land-based nonroad diesel engines are 46 percent of the total diesel

PM2.5 emissions in 1996, and this percentage increases to 72 percent by 2030. Emissions from

land-based nonroad diesel engines actually decrease from 186,507 tons in 1996 to 129,058 tons

in 2020 due to the existing emission standards. From 2020 to 2030, however, emissions increase

to 142,484 tons, as growth in this sector offsets the effect of the existing emission standards.

PM2.5 emissions from recreational marine diesel engines, commercial marine diesel engines,

and locomotives will also be affected by this rule due to the fuel sulfur requirements. For all

nonroad diesel sources affected by this rule, the contribution to total diesel PM2.5 emissions

increases from 56 percent in 1996 to 91 percent in 2030.

Table 3.2-2 provides the contribution of land-based diesel engines and other source

categories to total manmade PM2.5 emissions. PM2.5 emissions from land-based nonroad diesel

engines are 8 percent of the total manmade PM2.5 emissions in 1996, and this percentage drops

slightly to 6 percent in 2020 and 2030. The contribution of land-based diesel engines to total

mobile source PM2.5 emissions is 33 percent in 1996, rising slightly to 35 percent by 2030. For

all nonroad diesel sources, the contribution to total manmade PM2.5 emissions is 10 percent in

1996, and this percentage drops slightly to 8 percent in 2020 and 2030.

3.2.3 NOx Emissions

Table 3.2-3 provides the contribution of land-based diesel engines and other source

categories to total NOx emissions.

NOx emissions from land-based nonroad diesel engines are 6 percent of the total emissions in

1996, and this percentage increases to 8 percent by 2030. The contribution of land-based diesel

engines to total mobile source NOx emissions is 12 percent in 1996, rising to 24 percent by 2030. 

Emissions from land-based nonroad diesel engines actually decrease from 1,564,904 tons in

1996 to 1,119,481 tons in 2020 due to the existing emission standards. From 2020 to 2030,

however, emissions increase to 1,192,833 tons, as growth in this sector offsets the effect of the

existing emission standards.
Final Regulatory Impact Analysis

3-30

NOx emissions from recreational marine diesel engines, commercial marine diesel engines,

and locomotives will not be affected by this rule. For these categories combined, the

contribution to total NOx emissions remains stable at 7-8 percent from 1996 to 2030.

3.2.4 SO2 Emissions

Table 3.2-4 provides the contribution of land-based diesel engines and other source

categories to total SO2 emissions.

SO2 emissions from land-based nonroad diesel engines are 1 percent of the total emissions in

1996, and this percentage increases to 2 percent by 2030. The contribution of land-based diesel

engines to total mobile source SO2 emissions is 20 percent in 1996, rising to 33 percent by 2030,

due to continued growth in this sector.

SO2 emissions from recreational marine diesel engines, commercial marine diesel engines,

and locomotives will also be affected by this rule due to the fuel sulfur requirements. For all

nonroad diesel sources affected by this rule, the contribution to total SO2 emissions remains

relatively stable at 1 percent.

3.2.5 VOC Emissions

Table 3.2-5 provides the contribution of land-based diesel engines and other source

categories to total VOC emissions. VOC includes both exhaust and evaporative emissions. 

VOC is an ozone precursor; therefore, VOC inventories are required for air quality modeling.

VOC emissions from land-based nonroad diesel engines are 1 percent of the total emissions

in 1996, and this percentage increases to 2 percent by 2030. The contribution of land-based

diesel engines to total mobile source VOC emissions is 3 percent in 1996, decreasing slightly to

2 percent by 2030. Emissions from land-based nonroad diesel engines actually decrease from

220,971 tons in 1996 to 97,513 tons in 2020 due to the existing emission standards. From 2020

to 2030, however, emissions increase to 96,374 tons, as growth in this sector offsets the effect of

the existing emission standards.

VOC emissions from recreational marine diesel engines, commercial marine diesel engines,

and locomotives will not be affected by this rule. For these categories combined, the

contribution to total VOC emissions is less than 1 percent.

3.2.6 CO Emissions

Table 3.2-6 provides the contribution of land-based diesel engines and other source

categories to total CO emissions.

CO emissions from land-based nonroad diesel engines are 1 percent of the total emissions in

1996, and this percentage remains stable at 1 percent by 2030. The contribution of land-based

diesel engines to total mobile source CO emissions is also 1 percent in 1996, remaining at 1
Emission Inventory

3-31

percent by 2030. Emissions from land-based nonroad diesel engines actually decrease from

1,004,586 tons in 1996 to 697,630 tons in 2020 due to the existing emission standards. From

2020 to 2030, however, emissions increase to 786,181 tons, as growth in this sector offsets the

effect of the existing emission standards.

CO emissions from recreational marine diesel engines, commercial marine diesel engines,

and locomotives will not be affected by this rule. For these categories combined, the

contribution to total CO emissions is less than 1 percent in 1996 and 2030.
Final Regulatory Impact Analysis

3-32

Table 3.2-1

Annual Diesel PM2.5 Baseline Emission Levels for Mobile and Other Source Categoriesa

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short

tons

% of

mobile

source

% of

total

short

tons

% of

mobile

source

% of

total

Land-Based Nonroad

Diesel

186,507 47.2% 45.8% 129,058 70.3% 68.8% 142,484 73.8% 72.2%

Recreational Marine

Diesel #50 hp

56 0.0% 0.0% 46 0.0% 0.0% 50 0.0% 0.0%

Recreational Marine

Diesel >50 hp

867 0.2% 0.2% 1,214 0.7% 0.6% 1,321 0.7% 0.7%

Commercial Marine

Diesel b

17,782 4.5% 4.4% 17,665 9.6% 9.4% 19,294 10.0% 9.8%

Locomotive 22,266 5.6% 5.5% 17,213 9.4% 9.2% 16,025 8.3% 8.1%

Total Nonroad Diesel 227,478 58% 56% 165,196 90% 88% 179,173 93% 91%

Total Highway Diesel 167,384 42% 41% 18,426 10% 10% 13,948 7% 7%

Total Mobile Source

Diesel

394,862 100% 97% 183,622 100% 98% 193,121 100% 98%

Stationary Point and

Area Source Diesel c

12,199 — 3% 4,010 — 2% 4,231 — 2%

Total Man-Made

Diesel Sources

407,061 — 187,632 — 197,352 —

Mobile Source

Percent of Total

97% — 98% — 98% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii. b

 This category includes compression-ignition (CI) vessels using diesel fuel. It does not include CI vessels using residual fuel. c This category includes point sources burning either diesel, distillate oil (diesel), or diesel/kerosene fuel.
Emission Inventory

3-33

Table 3.2-2

Annual PM2.5 Baseline Emission Levels for Mobile and Other Source Categories a,b

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

Land-Based Nonroad

Diesel

186,507 32.6% 8.4% 129,058 34.7% 6.2% 142,484 34.6% 6.4%

Recreational Marine

Diesel #50 hp

56 0.0% 0.0% 46 0.0% 0.0% 50 0.0% 0.0%

Recreational Marine

Diesel >50 hp

867 0.2% 0.0% 1,214 0.3% 0.1% 1,321 0.3% 0.1%

Recreational 

Marine SI

35,147 6.1% 1.6% 26,110 7.0% 1.3% 27,223 6.6% 1.2%

Nonroad SI #25 hp 24,309 4.2% 1.1% 30,151 8.1% 1.4% 34,598 8.4% 1.5%

Nonroad SI >25hp 1,374 0.2% 0.1% 2,302 0.6% 0.1% 2,692 0.7% 0.1%

Recreational SI 7,968 1.4% 0.4% 9,963 2.7% 0.5% 9,460 2.3% 0.4%

Commercial Marine

Diesel c

17,782 3.1% 0.8% 17,665 4.7% 0.8% 19,294 4.7% 0.9%

Commercial Marine

Residual c

16,126 2.8% 0.7% 34,532 9.3% 1.7% 51,026 12.4% 2.3%

Commercial Marine

Other c

1,370 0.2% 0.1% 1,326 0.4% 0.1% 1,427 0.3% 0.1%

Locomotive 22,266 3.9% 1.0% 17,213 4.6% 0.8% 16,025 3.9% 0.7%

Aircraft 27,891 4.9% 1.3% 30,024 8.1% 1.4% 30,606 7.4% 1.4%

Total Nonroad 341,663 60% 15% 299,603 81% 14% 336,206 82% 15%

Total Highway 230,684 40% 10% 72,377 19% 4% 75,825 18% 3%

Total Mobile Sources 572,346 100% 26% 371,980 100% 18% 412,030 100% 18%

Stationary Point and

Area Sources

1,653,392 — 74% 1,712,004 — 82% 1,824,609 — 82%

Total Man-Made

Sources

2,225,738 — 2,083,984 — 2,236,639 —

Mobile Source

Percent of Total

26% — 18% — 18% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii. b

 Excludes natural and miscellaneous sources.
Final Regulatory Impact Analysis

3-34

c Commercial marine diesel includes Category 1 and 2 compression-ignition (CI) engines using diesel fuel. The residual

category includes Category 3 CI engines using residual fuel. The other category includes engines using gasoline and

steamships fueled with coal.
Emission Inventory

3-35

Table 3.2-3

Annual NOx Baseline Emission Levels for Mobile and Other Source Categories a

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

Land-Based Nonroad

Diesel

1,564,904 12.1% 6.4% 1,119,481 22.2% 7.4% 1,192,833 24.3% 7.8%

Recreational Marine

Diesel #50 hp

438 0.0% 0.0% 491 0.0% 0.0% 554 0.0% 0.0%

Recreational Marine

Diesel >50 hp

33,241 0.3% 0.1% 47,356 0.9% 0.3% 51,531 1.0% 0.3%

Recreational 

Marine SI

33,304 0.3% 0.1% 61,749 1.2% 0.4% 67,893 1.4% 0.4%

Nonroad SI #25 hp 63,120 0.5% 0.3% 98,584 2.0% 0.7% 114,447 2.3% 0.8%

Nonroad SI >25hp 273,082 2.1% 1.1% 43,315 0.9% 0.3% 43,527 0.9% 0.3%

Recreational SI 4,297 0.0% 0.0% 17,129 0.3% 0.1% 19,389 0.4% 0.1%

Commercial Marine

Diesel b

639,630 4.9% 2.6% 587,115 11.6% 3.9% 602,967 12.3% 4.0%

Commercial Marine

Residual b

184,275 1.4% 0.8% 356,445 7.1% 2.4% 514,881 10.5% 3.4%

Commercial 

Marine Other b

5,979 0.0% 0.0% 4,207 0.1% 0.0% 4,020 0.1% 0.0%

Locomotive 934,070 7.2% 3.8% 508,084 10.1% 3.4% 481,077 9.8% 3.2%

Aircraft 165,018 1.3% 0.7% 228,851 4.5% 1.5% 258,102 5.2% 1.7%

Total Nonroad 3,901,357 30% 16% 3,072,808 61% 20% 3,351,220 68% 22%

Total Highway 9,060,923 70% 37% 1,975,312 39% 13% 1,566,902 32% 10%

Total Mobile

Sources

12,962,279 100% 53% 5,048,120 100% 33% 4,918,123 100% 32%

Stationary Point and

Area Sources c

11,449,752 — 47% 10,050,213 — 67% 10,320,361 — 68%

Total Man-Made

Sources

24,412,031 — 15,098,333 — 15,238,484 —

Mobile Source

Percent of Total

53% — 33% — 32% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii.
Final Regulatory Impact Analysis

3-36

b

 Commercial marine diesel includes Category 1 and 2 compression-ignition (CI) engines using diesel fuel. The residual

category includes Category 3 CI engines using residual fuel. The other category includes engines using gasoline and

steamships fueled with coal. c

 Does not include effects of the proposed Rule to Reduce Interstate Transport of Fine Particulate Matter and Ozone (Interstate

Air Quality Rule). 69 FR 4566 (January 30, 2004). See http://www.epa.gov/interstateairquality/rule.html.

Table 3.2-4

Annual SO2 Baseline Emission Levels for Mobile and Other Source Categories a

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

Land-Based Nonroad

Diesel

143,572 19.9% 0.8% 237,044 35.7% 1.6% 279,511 32.8% 1.8%

Recreational Marine

Diesel #50 hp

53 0.0% 0.0% 85 0.0% 0.0% 101 0.0% 0.0%

Recreational Marine

Diesel >50 hp

4,234 0.6% 0.0% 6,766 1.0% 0.0% 8,057 0.9% 0.1%

Recreational 

Marine SI

2,170 0.3% 0.0% 2,522 0.4% 0.0% 2,698 0.3% 0.0%

Nonroad SI #25 hp 6,803 0.9% 0.0% 8,623 1.3% 0.1% 10,007 1.2% 0.1%

Nonroad SI >25hp 890 0.1% 0.0% 879 0.1% 0.0% 998 0.1% 0.0%

Recreational SI 949 0.1% 0.0% 2,561 0.4% 0.0% 2,691 0.3% 0.0%

Commercial Marine

Diesel b

30,136 4.2% 0.2% 29,268 4.4% 0.2% 33,020 3.9% 0.2%

Commercial Marine

Residual b

151,559 21.0% 0.8% 263,076 39.6% 1.7% 387,754 45.6% 2.5%

Commercial 

Marine Other b

9,266 1.3% 0.1% 9,677 1.5% 0.1% 10,366 1.2% 0.1%

Locomotive 56,193 7.8% 0.3% 53,352 8.0% 0.4% 58,103 6.8% 0.4%

Aircraft 11,305 1.6% 0.1% 15,267 2.3% 0.1% 16,813 2.0% 0.1%

Total Nonroad 417,128 58% 2% 629,118 95% 4% 810,119 95% 5%

Total Highway 302,938 42% 2% 35,311 5% 0% 40,788 5% 0%

Total Mobile

Sources

720,066 100% 4% 664,429 100% 4% 850,907 100% 5%

Stationary Point and

Area Sources c

17,636,602 — 96% 14,510,426 — 96% 14,782,220 — 95%

Total Man-Made

Sources

18,356,668 — 15,174,855 — 15,633,127 —

Mobile Source

Percent of Total

4% — 4% — 5% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii.
Emission Inventory

3-37

b

 

c

 Commercial marine diesel includes Category 1 and 2 compression-ignition (CI) engines using diesel fuel. The residual

category includes Category 3 CI engines using residual fuel. The other category includes engines using gasoline and

steamships fueled with coal. c

 Does not include effects of the proposed Rule to Reduce Interstate Transport of Fine Particulate Matter and Ozone (Interstate

Air Quality Rule). 69 FR 4566 (January 30, 2004). See http://www.epa.gov/interstateairquality/rule.html.
Final Regulatory Impact Analysis

3-38

Table 3.2-5

Annual VOC Baseline Emission Levels for Mobile and Other Source Categories a

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

short tons % of

mobile

source

% of

total

Land-Based Nonroad

Diesel

220,971 2.7% 1.2% 97,513 2.5% 0.7% 96,374 2.3% 0.6%

Recreational Marine

Diesel #50 hp

106 0.0% 0.0% 52 0.0% 0.0% 50 0.0% 0.0%

Recreational Marine

Diesel >50 hp

1,191 0.0% 0.0% 1,552 0.0% 0.0% 1,619 0.0% 0.0%

Recreational 

Marine SI

804,488 9.7% 4.3% 380,891 9.8% 2.8% 372,970 8.8% 2.5%

Nonroad SI #25 hp 1,332,392 16.0% 7.2% 656,845 16.9% 4.9% 758,512 17.9% 5.1%

Nonroad SI >25hp 88,526 1.1% 0.5% 10,629 0.3% 0.1% 9,664 0.2% 0.1%

Recreational SI 322,766 3.9% 1.7% 345,649 8.9% 2.6% 327,403 7.7% 2.2%

Commercial Marine

Diesel b

21,540 0.3% 0.1% 24,005 0.6% 0.2% 26,169 0.6% 0.2%

Commercial Marine

Residual b

7,446 0.1% 0.0% 17,584 0.5% 0.1% 26,711 0.6% 0.2%

Commercial 

Marine Other b

892 0.0% 0.0% 925 0.0% 0.0% 1,001 0.0% 0.0%

Locomotive 38,035 0.5% 0.2% 30,125 0.8% 0.2% 28,580 0.7% 0.2%

Aircraft 176,394 2.1% 1.0% 239,654 6.2% 1.8% 265,561 6.3% 1.8%

Total Nonroad 3,014,747 36% 16% 1,805,424 47% 13% 1,914,614 45% 13%

Total Highway 5,291,388 64% 29% 2,071,456 53% 15% 2,312,561 55% 15%

Total Mobile

Sources

8,306,135 100% 45% 3,876,880 100% 29% 4,227,175 100% 28%

Stationary Point and

Area Sources

10,249,136 — 55% 9,648,376 — 71% 10,751,134 — 72%

Total Man-Made

Sources

18,555,271 — 13,525,256 — 14,978,309 —

Mobile Source

Percent of Total

45% — 29% — 28% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii. b

 Commercial marine diesel includes Category 1 and 2 compression-ignition (CI) engines using diesel fuel. The residual

category includes Category 3 CI engines using residual fuel. The other category includes engines using gasoline and

steamships fueled with coal.
Emission Inventory

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Table 3.2-6

Annual CO Baseline Emission Levels for Mobile and Other Source Categories a

Category

1996 2020 2030

short tons % of

mobile

source

% of

total

short tons % of

mobile

sources

% of

total

short tons % of

mobile

source

% of

total

Land-Based Nonroad

Diesel

1,004,586 1.3% 1.1% 697,630 0.9% 0.7% 786,181 0.8% 0.7%

Recreational Marine

Diesel #50 hp

304 0.0% 0.0% 243 0.0% 0.0% 259 0.0% 0.0%

Recreational Marine

Diesel >50 hp

5,120 0.0% 0.0% 9,239 0.0% 0.0% 10,973 0.0% 0.0%

Recreational 

Marine SI

1,995,907 2.5% 2.1% 1,977,403 2.4% 2.0% 2,075,666 2.2% 1.9%

Nonroad SI #25 hp 18,013,533 23.0% 19.0% 26,372,980 32.4% 27.2% 30,611,599 32.8% 27.9%

Nonroad SI >25hp 1,614,394 2.1% 1.7% 275,647 0.3% 0.3% 264,047 0.3% 0.2%

Recreational SI 921,345 1.2% 1.0% 1,820,865 2.2% 1.9% 1,836,350 2.0% 1.7%

Commercial Marine

Diesel b

93,638 0.1% 0.1% 114,397 0.1% 0.1% 123,436 0.1% 0.1%

Commercial Marine

Residual b

15,245 0.0% 0.0% 36,165 0.0% 0.0% 54,924 0.1% 0.1%

Commercial 

Marine Other b

5,869 0.0% 0.0% 6,542 0.0% 0.0% 7,058 0.0% 0.0%

Locomotive 92,496 0.1% 0.1% 99,227 0.1% 0.1% 107,780 0.1% 0.1%

Aircraft 949,313 1.2% 1.0% 1,387,178 1.7% 1.4% 1,502,265 1.6% 1.4%

Total Nonroad 24,711,750 32% 26% 32,797,515 40% 34% 37,380,538 40% 34%

Total Highway 53,685,026 68% 57% 48,529,203 60% 50% 55,847,203 60% 51%

Total Mobile

Sources

78,396,776 100% 83% 81,326,718 100% 84% 93,227,742 100% 85%

Stationary Point and

Area Sources

16,318,451 — 17% 15,648,555 — 16% 16,325,306 — 15%

Total Man-Made

Sources

94,715,227 — 96,975,273 — 109,553,048 —

Mobile Source

Percent of Total

83% — 84% — 85% —

a

 These are 48-state inventories. They do not include Alaska and Hawaii. b Commercial marine diesel includes Category 1 and 2 compression-ignition (CI) engines using diesel fuel. The residual

category includes Category 3 CI engines using residual fuel. The other category includes engines using gasoline and

steamships fueled with coal.
Final Regulatory Impact Analysis

A Construction, industrial, and commercial nonroad diesel equipment comprise most of the land-based nonroad emission

inventory. These types of equipment are more concentrated in urban areas where construction projects, manufacturing,

and commercial operations are prevalent.

3-40

3.3 Contribution of Nonroad Diesel Engines to Selected Local Emission

Inventories

The contribution of land-based nonroad compression-ignition (CI) engines to PM2.5 and NOx

emission inventories in many U.S. cities can be significantly greater than that reflected by

national average values.A This is not surprising given the high density of these engines one would

expect to be operating in urban areas. EPA selected a collection of typical cities spread across the

United States to compare projected urban inventories with national average ones for 1996, 2020,

and 2030. The results of this analysis are shown below.

3.3.1 PM2.5 Emissions

As illustrated in Tables 3.3-1, 3.3-2, and 3.3-3, EPA’s city-specific analysis of selected

metropolitan areas for 1996, 2020, and 2030 show that land-based nonroad diesel engine engines

are a significant contributor to total PM2.5 emissions from all man-made sources.
Emission Inventory

3-41

Table 3.3-1

Land-Based Nonroad Percent Contribution 

to PM2.5 Inventories in Selected Urban Areas in 1996a,b

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 1,650 7,308 22,190 7% 23%

Boston, MA 4,265 9,539 23,254 18% 45%

Chicago, IL 3,374 10,106 40,339 8% 33%

Dallas-Fort Worth, TX 1,826 5,606 13,667 13% 33%

Indianapolis, IN 1,040 3,126 7,083 15% 33%

Minneapolis, MN 1,484 4,238 15,499 10% 35%

New York, NY 2,991 6,757 23,380 13% 44%

Orlando, FL 764 2,559 5,436 14% 30%

Sacramento, CA 529 2,140 7,103 7% 25%

San Diego, CA 879 3,715 9,631 9% 24%

Denver, CO 1,125 3,199 10,107 11% 35%

El Paso, TX 252 822 1,637 15% 31%

Las Vegas, NV-AZ 1,155 2,700 7,511 15% 43%

Phoenix-Mesa, AZ 1,549 4,994 10,100 15% 31%

Seattle, WA 1,119 4,259 15,187 7% 26%

a

 Includes only direct exhaust emissions; see Chapter 2 for a discussion of secondary fine PM levels. b

 Based on inventories developed for the proposed rule.
Final Regulatory Impact Analysis

3-42

Table 3.3-2

Annual Land-Based Nonroad Diesel Contributions 

to PM2.5 Inventories in Selected Urban Areas in 2020a,b

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 1,429 4,506 22,846 6% 32%

Boston, MA 3,580 6,720 20,365 18% 53%

Chicago, IL 2,824 6,984 42,211 7% 40%

Dallas-Fort Worth, TX 1,499 3,544 15,202 10% 42%

Indianapolis, IN 794 1,779 6,238 13% 45%

Minneapolis, MN 1,188 2,509 15,096 8% 47%

New York, NY 2,573 4,549 21,566 12% 57%

Orlando, FL 652 1,743 5,627 12% 37%

Sacramento, CA 391 1,301 5,505 7% 30%

San Diego, CA 678 2,478 9,135 7% 27%

Denver, CO 923 2,149 10,954 8% 43%

El Paso, TX 212 478 1,140 19% 44%

Las Vegas, NV-AZ 961 2,080 7,804 12% 46%

Phoenix-Mesa, AZ 1,299 3,512 10,768 12% 37%

Seattle, WA 946 3,043 13,094 7% 31%

a

 Includes only direct exhaust emissions; see Chapter 2 for a discussion of secondary fine PM levels. b

 Based on inventories developed for the proposed rule.
Emission Inventory

3-43

Table 3.3-3

Land-Based Nonroad Percent Contribution 

to PM2.5 Inventories in Selected Urban Areas in 2030a,b

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 1,647 4,937 24,880 7% 33%

Boston, MA 4,132 7,529 21,846 19% 55%

Chicago, IL 3,236 7,735 45,975 7% 42%

Dallas-Fort Worth, TX 1,721 3,919 16,622 10% 44%

Indianapolis, IN 902 1,934 6,753 13% 47%

Minneapolis, MN 1,354 2,769 16,586 8% 49%

New York, NY 2,953 5,064 22,891 13% 58%

Orlando, FL 752 1,957 6,084 12% 38%

Sacramento, CA 447 1,445 5,890 8% 31%

San Diego, CA 777 2,770 10,096 8% 28%

Denver, CO 1,060 2,379 12,117 9% 45%

El Paso, TX 244 524 1,243 20% 47%

Las Vegas, NV-AZ 1,113 2,307 8,512 13% 48%

Phoenix-Mesa, AZ 1,499 3,870 11,989 13% 39%

Seattle, WA 1,084 3,357 14,148 8% 32%

a

 Includes only direct exhaust emissions; see Chapter 2 for a discussion of secondary fine PM levels. b

 Based on inventories developed for the proposed rule.
3.3.2 NOx Emissions

 As presented in Tables 3.3-4, 3.3-5, and 3.3-6, EPA’s city-specific analysis of selected

metropolitan areas for 1996, 2020, and 2030 show that land-based nonroad diesel engine engines

are a significant contributor to total NOx emissions from all man-made sources.

Table 3.3-4

Land-Based Nonroad Percent Contribution 

to NOx Inventories in Selected Urban Areas in 1996a

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 16,238 205,465 298,361 5% 8%

Boston, MA 43,362 232,444 311,045 14% 19%

Chicago, IL 32,276 296,710 509,853 6% 11%

Dallas-Fort Worth, TX 17,852 152,878 186.824 10% 12%

Indianapolis, IN 9,487 89,291 113,300 8% 11%

Minneapolis, MN 13,843 124,437 224,817 6% 11%

New York, NY 29,543 184,384 262,021 11% 16%

Orlando, FL 7,493 61,667 75,714 10% 12%

Sacramento, CA 5,666 55,144 58,757 10% 10%

San Diego, CA 9,460 99,325 107,024 9% 10%

Denver, CO 11,080 86,329 146,807 8% 13%

El Paso, TX 2,498 24,382 30,160 8% 10%

Las Vegas, NV-AZ 11,788 50,724 108,875 11% 23%

Phoenix-Mesa, AZ 15,145 115,544 161,606 9% 13%

Seattle, WA 11,227 115,264 133,840 8% 10%

a

 Based on inventories developed for the proposed rule.
3-45

Table 3.3-5

Annual Land-Based Nonroad Diesel Contributions 

to NOx Inventories in Selected Urban Areas in 2020a

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 12,650 69,816 193,456 7% 18%

Boston, MA 31,282 93,308 167,572 19% 34%

Chicago, IL 24,732 123,823 333,945 7% 20%

Dallas-Fort Worth, TX 13,334 60,745 101,453 13% 22%

Indianapolis, IN 6,982 36,283 60,059 12% 19%

Minneapolis, MN 10,376 47,375 165,775 6% 22%

New York, NY 22,456 67,083 112,960 20% 33%

Orlando, FL 5,837 28,653 45,362 13% 20%

Sacramento, CA 4,297 18,870 23,111 19% 23%

San Diego, CA 7,464 46,005 51,909 14% 16%

Denver, CO 8,251 38,435 103,533 8% 21%

El Paso, TX 1,847 10,105 12,452 15% 18%

Las Vegas, NV-AZ 8,501 26,840 72,829 12% 32%

Phoenix-Mesa, AZ 11,560 48,348 105,185 11% 24%

Seattle, WA 8,283 51,252 76,161 11% 16%

a

 Based on inventories developed for the proposed rule.
3-46

Table 3.3-6

Land-Based Nonroad Percent Contribution 

to NOx Inventories in Selected Urban Areas in 2030a

MSA, CMSA / State Land-Based

Diesel 

(short tons)

Mobile

Sources

(short tons)

Total ManMade Sources

(short tons)

Land-Based

Diesel as % of

Total

Land-Based

Diesel as % of

Mobile Sources

Atlanta, GA 14,190 65,746 191,932 7% 22%

Boston, MA 35,039 92,537 168,422 21% 38%

Chicago, IL 27,525 120,694 334,334 8% 23%

Dallas-Fort Worth, TX 14,839 56,907 100,721 15% 26%

Indianapolis, IN 7,641 34,442 58,793 13% 22%

Minneapolis, MN 11,444 45,326 167,154 7% 25%

New York, NY 25,064 67,163 108,215 23% 37%

Orlando, FL 6,551 28,365 45,267 14% 23%

Sacramento, CA 4,806 17,498 21,952 22% 27%

San Diego, CA 8,401 43,930 50,296 17% 19%

Denver, CO 9,185 37,105 104,217 9% 25%

El Paso, TX 2,062 9,422 11,905 17% 22%

Las Vegas, NV-AZ 9,544 26,349 72,926 13% 36%

Phoenix-Mesa, AZ 12,952 46,280 106,061 12% 28%

Seattle, WA 9,247 49,258 77,133 12% 19%

a

 Based on inventories developed for the proposed rule.

3.4 Nonroad Diesel Controlled Emission Inventory Development

This section describes how the controlled emission inventories were developed for the four

categories of nonroad diesel engines affected by this rule: land-based diesel engines, commercial

marine diesel vessels, locomotives, and recreational marine diesel engines. For land-based diesel

engines, there are separate sections for criteria (i.e., PM2.5, NOx, SO2, VOC, and CO) and air

toxics emission development.

3.4.1 Land-Based Diesel Engines—PM2.5, NOx, SO2, VOC, and CO Emissions

The emission inventory estimates used in this rule were generated using the draft

NONROAD2004 model with certain input modifications to account for the in-use diesel fuel

sulfur reductions and the engine controls associated with the new emission standards. This

section will describe only these modifications to the model inputs, since the other aspects of the

model, including inputs for earlier engines, are covered in detail in the technical reports that

document the draft NONROAD2004 model.
Emission Inventory

3-47

3.4.1.1 Standards and Zero-Hour Emission Factors

The new emission standards are summarized in Table 3.4-1. The modeled emission factors

corresponding to the new emission standards are shown in Table 3.4-2. These emission factors

are derived from the standards by applying an assumed 8 percent compliance margin to the

standard. This compliance margin was derived from data for highway diesel vehicles and used in

the HD2007 rulemaking.

Besides exhaust emissions, the final rule includes changes in crankcase hydrocarbon

emissions. Crankcase losses before Tier 4 have been modeled as 2.0 percent of exhaust HC, and

any crankcase emissions of other pollutants have been considered negligible. For all Tier 4

engines, including those using transitional controls without particulate traps, our modeling now

assumes zero crankcase emissions.

3.4.1.2 Transient Adjustment Factors

The supplemental nonroad transient test will apply to a nonroad diesel engine when that

engine must first show compliance with the Tier 4 PM and NOx+NMHC emissions standards

which are based on the performance of the advanced post-combustion emissions control systems

(e.g., catalyzed-diesel particulate filters and NOx adsorbers). This is 2011 for engines at or above

175 hp, 2012 for 75-175 hp engines, and 2013 for engines under 75 hp. Details regarding the

transient testing requirements and manufacturer options are provided in Section III of the

preamble. More broadly though, transient emissions control is expected to be an integral part of

all Tier 4 engine design considerations, including engines under 75 hp meeting either the 0.22

g/hp-hr or 0.30 g/hp-hr Tier 4 PM standards in 2008. Thus, there was no Transient Adjustment

Factor (TAF) applied to the emission factors for Tier 4 engines (i.e., the model applies a TAF of

1.0); the zero-hour emission factor was modeled simply as the value of the standard minus an

assumed 8 percent compliance margin.
Final Regulatory Impact Analysis

3-48

Table 3.4-1

Tier 4 Emission Standards Modeled

Engine 

Power

Emission Standard

(g/hp-hr) Model 

Year(s)

transitional

or final

PM NOx

a NMHC a CO d

kW < 19

(hp <25)

final 0.30 5.6 b,c 6.0/4.9 c 2008

19 # kW < 56

(25 # hp < 75)

transitional 0.22 5.6/3.5 b,c 4.1/3.7 c 2008-2012

final 0.02 3.5 b 4.1/3.7 c 2013

56 # kW < 130 

(75 # hp < 175)

transitional 0.01 0.30

(50%)

0.14

(50%)

3.7 c 2012-2013

final 0.01 0.30 0.14 3.7 c 2014

130 # kW < 560

(175 # hp < 750) 

transitional 0.01 0.30

(50%)

0.14

(50%)

2.6 c 2011-2013

final 0.01 0.30 0.14 2.6 c 2014

kW $ 560

(hp $ 750)

except Generator sets

transitional 0.075 2.6 0.30 2.6 c 2011-2014

final 0.03 2.6 0.14 2.6 c 2015

Generator sets

560 # kW # 895

(750 # hp # 1200)

transitional 0.075 2.6 0.30 2.6 c 2011-2014

final 0.02 0.50 0.14 2.6 c 2015

Generator sets

kW > 895

(hp > 1200)

transitional 0.075 0.50 0.30 2.6 c 2011-2014

final 0.02 0.50 0.14 2.6 c 2015

a

 Percentages are model year sales fractions required to comply with the indicated NOx and NMHC standards, for model

years where less than 100 percent is required. For a complete description of manufacturer options and alternative

standards, refer to Section II of the preamble.

b

 This is a combined NMHC + NOx standard. c

 This emission standard level is unchanged from the level that applies in the previous model year. For 25-75 hp engines,

the transitional NMHC + NOx standard is 5.6 g/hp-hr for engines below 50 hp and 3.5 g/hp-hr for engines at or above

50 hp. For engines under 75 hp, the CO standard is 6.0 g/hp-hr for engines below 11 hp, 4.9 g/hp-hr for engines 11 to

under 25 hp, 4.1 g/hp-hr for engines 25 to below 50 hp and 3.7 g/hp-hr for engines at or above 50 hp. d

 There are no Tier 4 CO standards. The CO emission standard level is unchanged from the level that applies in the

previous model year.
Emission Inventory

3-49

Table 3.4-2

NONROAD Model EF Inputs for Tier 4 Engines

Engine 

Power

Emission Factor Modeling Inputs, g/hp-hr a

Model

Type of Year(s)

standard

PM NOx

b,c THC c,d CO e

hp # 11 final 0.28 4.30 0.55 4.11 2008

11 < hp # 25 final 0.28 4.44 0.44 2.16 2008

25 < hp # 50

transitional 0.20 4.73 0.28 1.53 2008

final 0.018 3.0 0.13 0.15 2013

50 < hp # 75

transitional 0.20 3.0 0.18 2.4 2008

final 0.018 3.0 0.13 0.24 2013

75 < hp # 100

transitional 0.01 3.0 (50%) 0.28 (50%) 0.13 0.24 2012-2013

final 0.01 0.28 0.13 0.24 2014

100 < hp # 175

transitional 0.01 2.5 (75%) 0.28 (25%) 0.13 0.087 2012-2014

final 0.01 0.28 0.13 0.087 2015

175 < hp # 300

transitional 0.01 2.5 (50%) 0.28 (50%) 0.13 0.075 2011-2013

final 0.01 0.28 0.13 0.075 2014

300 < hp # 600

transitional 0.01 2.5 (50%) 0.28 (50%) 0.13 0.084 2011-2013

final 0.01 0.28 0.13 0.084 2014

600 < hp # 750

transitional 0.01 2.5 (50%) 0.28 (50%) 0.13 0.13 2011-2013

final 0.01 0.28 0.13 0.13 2014

hp > 750

except Generator

sets

transitional 0.069 2.39 0.28 0.076 2011-2014

final 0.028 2.39 0.13 0.076 2015

Generator sets

750 # hp # 1200

transitional 0.069 2.39 0.28 0.076 2011-2014

final 0.018 0.46 0.13 0.076 2015

Generator sets

hp > 1200

transitional 0.069 0.46 0.28 0.076 2011-2014

final 0.018 0.46 0.13 0.076 2015

a

 Transient emission control is assumed for Tier 4 engines, so Transient Adjustment Factors are not applied to the emission factors shown here. b

 Percentages are model-year sales fractions required to comply with the indicated standard. c

 NMHC + NOx is a combined standard, so for modeling purposes the NOx and HC are separated using a NOx/HC ratio that approximates the

results found in prior test programs, as described in technical report NR-009b. d

 HC Standards are in terms of NMHC, but the model expects inputs as THC, so a conversion factor of 1.02 is applied to the NMHC value to get

the THC model input.
Final Regulatory Impact Analysis

3-50

e

 CO emissions from Tier 4 engines are assumed to decrease by 90% from its prior levels in any cases where particulate traps are expected for PM

control.

3.4.1.3 Deterioration Rates

The deterioration rates (d) used for the modeling of Tier 4 engines are the same as used for

Tier 3 engines for all affected pollutants (PM, NOx, HC, and CO). These are listed in Table 3.4-3

below and are fully documented in technical report NR-009b.1

Table 3.4-3

Deterioration Rates for Nonroad Diesel Engines

Pollutant Relative Deterioration Rate (percent increase per percent useful life expended)a

Base/Tier 0 Tier 1 Tier 2 Tier 3 Tier 4

HC 0.047 0.036 0.034 0.027 0.027

CO 0.185 0.101 0.101 0.151 0.151

NOx 0.024 0.024 0.009 0.008 0.008

PM 0.473 0.473 0.473 0.473 0.473

a

 At the median life point, the Deterioration Factor = 1 + relative deterioration rate.

3.4.1.4 In-Use Sulfur Levels, Certification Sulfur Levels, and Sulfur Conversion Factors

Tables 3.4-4 and 3.4-5 show the certification and in-use fuel sulfur levels by calendar year

and engine power range that were assumed for modeling the engines regulated under this rule. 

The certification sulfur levels are the default fuel sulfur levels used to calculate the zero mile PM

and SO2 emission factors in the model (referred to as Sbase in Section 3.1.1.2.1). The in-use fuel

sulfur level is the episodic fuel sulfur level (referred to as Sin-use in Section 3.1.1.2.1). 

Adjustments to PM and SO2 for in-use fuel sulfur levels are made relative to the certification

sulfur levels in the model. As described above for the baseline inventory development, the in-use

fuel sulfur content, fuel consumption, sulfate conversion factor, and exhaust HC emission factor

(unburned fuel) determine the SO2 emissions, and a fraction of the fuel sulfur is also converted to

sulfate PM. The changes for modeling of the control case are (a) lower sulfur content for in-use

and certification fuel per this rule, and (b) the use of a higher sulfur-to-sulfate conversion factor

for engines that are expected to use a particulate trap/filter to achieve the PM standards of 0.01 or

0.02 g/hp-hr (30 percent conversion instead of 2.247 percent that is used for all earlier nontrapequipped engines).

The in-use sulfur levels account for the 500 ppm standard beginning in 2007, the 15 ppm

standard for land-based engines beginning in 2010, and the 15 ppm standard for marine engines
Emission Inventory

3-51

and locomotives beginning in 2012. The derivation of the annual fuel sulfur levels is described in

detail in Chapter 7. The in-use sulfur levels in Table 3.4-5 used for modeling differ slightly from

those presented in Chapter 7, since minor revisions were made subsequent to the modeling.

Table 3.4-4

Modeled Certification Diesel Fuel Sulfur Content

Engine 

Power Standards

Modeled Certification Fuel

Sulfur Content, PPM

Model 

Year(s)

kW < 56

(hp <75)

Tier 2 2000 through 2007

transitional 500 2008-2012

final 15 2013

56 # kW < 75 

(75 # hp < 100)

Tier 3 transitional a 500 2008-2011

final 15 2012

75 # kW < 130 

(100 # hp < 175)

Tier 3 2000 2007-2011

final 15 2012

130 # kW < 560

(175 # hp < 750) 

Tier 3 2000 2006-2010

final 15 2011

kW $ 560

 (hp $ 750)

Tier 2 2000 2006-2010

final 15 2011

a

 The emission standard here is still Tier 3 as in the Baseline case, but since the Tier 3 standard begins in 2008 for 50-100

hp engines it is assumed that this new technology introduction will allow manufacturers to take advantage of the

availability of 500 ppm fuel that year.
Final Regulatory Impact Analysis

3-52

Table 3.4-5

Modeled 48-State & 50-State In-Use Diesel Fuel Sulfur Content for Controlled Inventories

Applications Calendar 

Year(s)

Modeled In-Use Fuel Sulfur Content, ppm

48-State 50-State

Land-based, 

all power ranges

through 2005 2283 2284

2006 2249 2242

2007 1140 1139

2008-2009 348 351

2010 163 165

2011-2013 31 32

2014 19 20

2015+ 11 11

Recreational Marine,

Commercial Marine, and

Locomotives

through 2000 2641 2640

2001 2637 2635

2002-2003 2638 2637

2004-2005 2639 2637

2006 2616 2588

2007 1328 1332

2008-2009 408 435

2010 307 319

2011 234 236

2012 123 124

2013 43 44

2014 51 52

2015-2017 56 56

2018-2038 56 55

2039-2040 55 55

3.4.1.5 Controlled Inventory

Tables 3.4-6a and 3.4-6b present the PM10, PM2.5, NOx, SO2, VOC, and CO controlled

emissions for land-based nonroad diesel engines in 1996 and 2000-2040, for the 48-state and 50-

state inventories, respectively.
Emission Inventory

3-53

Table 3.4-6a

Controlled (48-State) Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 192,275 186,507 1,564,904 143,572 220,971 1,004,586

2000 176,056 170,774 1,550,355 161,977 199,887 916,507

2001 170,451 165,338 1,537,890 166,644 191,472 880,129

2002 165,017 160,067 1,526,119 171,309 183,525 845,435

2003 159,268 154,490 1,505,435 175,971 176,383 813,886

2004 153,932 149,314 1,486,335 180,630 169,873 787,559

2005 148,720 144,259 1,467,547 185,287 163,663 763,062

2006 143,840 139,525 1,435,181 187,085 156,952 741,436

2007 132,534 128,558 1,399,787 97,142 150,357 724,449

2008 123,646 119,936 1,359,631 30,359 143,138 707,098

2009 120,512 116,896 1,317,925 31,064 136,085 691,627

2010 116,263 112,775 1,277,888 14,881 129,186 677,599

2011 110,940 107,612 1,224,329 2,853 122,434 650,276

2012 104,319 101,189 1,165,155 2,850 115,877 609,685

2013 97,187 94,271 1,108,560 2,832 109,726 563,695

2014 89,522 86,837 1,031,680 1,724 104,160 518,729

2015 81,780 79,326 958,769 992 98,766 475,349

2016 74,718 72,476 890,935 987 93,976 435,137

2017 68,079 66,036 828,178 984 89,760 398,578

2018 61,986 60,127 772,291 983 85,896 365,813

2019 56,496 54,801 722,094 984 82,398 336,094

2020 51,613 50,065 677,420 986 79,372 309,593

2021 47,285 45,866 639,156 991 76,813 286,679

2022 43,376 42,074 606,068 996 74,680 266,071

2023 39,837 38,642 576,872 1,003 72,854 247,738

2024 36,548 35,452 551,570 1,011 71,291 231,324

2025 33,508 32,503 529,260 1,019 69,973 216,510

2026 30,735 29,813 510,126 1,028 68,878 203,435

2027 28,234 27,387 493,869 1,039 68,008 192,100

2028 26,125 25,341 479,930 1,050 67,319 182,716

2029 24,177 23,452 467,852 1,062 66,761 174,448

2030 22,369 21,698 458,649 1,074 66,344 167,014

2031 20,873 20,247 451,478 1,087 66,118 161,116

2032 19,492 18,907 445,218 1,100 65,979 155,882

2033 18,188 17,643 439,984 1,113 65,904 151,053

2034 16,970 16,461 435,620 1,126 65,909 146,747

2035 15,877 15,401 432,306 1,140 66,004 143,229

2036 14,930 14,482 429,867 1,155 66,186 140,378

2037 14,053 13,631 428,058 1,169 66,418 137,840

2038 13,577 13,169 427,438 1,183 66,781 135,517

2039 13,194 12,798 427,591 1,198 67,195 133,748

2040 12,852 12,467 428,084 1,213 67,645 132,256
Final Regulatory Impact Analysis

3-54

Table 3.4-6b

Controlled (50-State) Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 193,166 187,371 1,573,083 144,409 222,084 1,009,804

2000 176,881 171,575 1,558,392 162,920 200,903 921,226

2001 171,256 166,118 1,545,852 167,615 192,447 884,645

2002 165,801 160,827 1,534,007 172,307 184,462 849,756

2003 160,030 155,229 1,513,203 176,996 177,287 818,037

2004 154,670 150,030 1,493,989 181,683 170,744 791,568

2005 149,434 144,951 1,475,092 186,368 164,505 766,944

2006 144,479 140,145 1,442,534 187,508 157,762 745,216

2007 133,159 129,165 1,406,936 97,580 151,134 728,159

2008 124,257 120,529 1,366,553 30,786 143,880 710,743

2009 121,113 117,479 1,324,613 31,501 136,792 695,221

2010 116,841 113,336 1,284,357 15,145 129,859 681,150

2011 111,492 108,147 1,230,489 2,961 123,074 653,692

2012 104,846 101,700 1,170,969 2,957 116,483 612,882

2013 97,687 94,757 1,114,051 2,939 110,299 566,639

2014 89,993 87,293 1,036,731 1,825 104,704 521,423

2015 82,171 79,706 963,408 997 99,281 477,800

2016 75,070 72,818 895,198 992 94,464 437,357

2017 68,395 66,343 832,101 989 90,227 400,587

2018 62,269 60,401 775,920 988 86,343 367,637

2019 56,750 55,047 725,464 989 82,828 337,757

2020 51,840 50,285 680,563 991 79,786 311,112

2021 47,489 46,064 642,114 996 77,214 288,075

2022 43,560 42,254 608,874 1,001 75,070 267,360

2023 40,006 38,806 579,551 1,008 73,234 248,939

2024 36,703 35,602 554,147 1,016 71,662 232,449

2025 33,651 32,641 531,753 1,024 70,338 217,569

2026 30,866 29,940 512,553 1,034 69,237 204,437

2027 28,355 27,504 496,243 1,044 68,363 193,052

2028 26,237 25,450 482,261 1,056 67,671 183,622

2029 24,280 23,552 470,147 1,068 67,110 175,312

2030 22,464 21,790 460,918 1,080 66,690 167,841

2031 20,963 20,334 453,730 1,093 66,464 161,916

2032 19,577 18,990 447,458 1,106 66,324 156,659

2033 18,269 17,721 442,218 1,119 66,250 151,810

2034 17,047 16,536 437,851 1,133 66,256 147,486

2035 15,951 15,472 434,539 1,147 66,352 143,953

2036 15,000 14,550 432,104 1,161 66,535 141,089

2037 14,120 13,696 430,302 1,175 66,769 138,541

2038 13,642 13,233 429,692 1,190 67,135 136,210

2039 13,257 12,859 429,857 1,204 67,551 134,435

2040 12,915 12,527 430,365 1,219 68,004 132,940
Emission Inventory

3-55

3.4.2 Land-Based Diesel Engines—Air Toxics Emissions

Since air toxics emissions are part of the VOC emission inventory, NMHC standards in this

rule will also affect air toxics emissions. Tables 3.4-7a and 3.4-7b show 48-state and 50-state

estimated emissions for five major air toxics, benzene, formaldehyde, acetaldehyde,

1,3-butadiene, and acrolein, resulting from the final rule. EPA uses the same fractions used to

calculate the base air toxic emissions without the final rule (see Section 3.1.2), along with the

estimated VOC emissions resulting from the final rule, to calculate the air toxics emissions

resulting from the final rule.

Table 3.4-7a

Controlled (48-State) Air Toxic Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year Benzene Formaldehyde Acetaldehyde 1,3-butadiene Acrolein

2000 3,998 23,587 10,594 400 600

2005 3,273 19,312 8,674 327 491

2007 3,007 17,742 7,969 301 451

2010 2,584 15,244 6,847 258 388

2015 1,975 11,654 5,235 198 296

2020 1,587 9,366 4,207 159 238

2025 1,399 8,257 3,709 140 210

2030 1,327 7,829 3,516 133 199

Table 3.4-7b

Controlled (50-State) Air Toxic Emissions for Land-Based Nonroad Diesel Engines (short tons)

Year Benzene Formaldehyde Acetaldehyde 1,3-butadiene Acrolein

2000 4,018 23,707 10,648 402 603

2005 3,290 19,412 8,719 329 494

2007 3,023 17,834 8,010 302 453

2010 2,597 15,323 6,883 260 390

2015 1,986 11,715 5,262 199 298

2020 1,596 9,415 4,229 160 239

2025 1,407 8,300 3,728 141 211

2030 1,334 7,869 3,535 133 200
Final Regulatory Impact Analysis

3-56

3.4.3 Commercial Marine Vessels and Locomotives

The control case locomotive and commercial marine inventories for VOC, CO, and NOx are

identical to the base case inventories, since no new controls apply for these engines. However,

due to the new requirements to reduce sulfur levels in diesel fuel, decreases are expected in PM

and SO2 inventories for these engines. 

The method used for estimating PM and SO2 emissions in the control case is nearly almost

identical to that described in Section 3.1.3 for the base case, but the fuel sulfur levels in the

equations are changed to reflect the control case sulfur. The control case PM and SO2 emission

inventory estimates presented here assume that locomotive and commercial marine applications

will use diesel fuel meeting a 500 ppm sulfur standard beginning in June 2007 and a 15 ppm

sulfur standard beginning in June 2012. Additional sulfur adjustments were made to account for

the "spillover" of low-sulfur highway fuel meeting a 15 ppm standard in the applicable years

before the start of the 15 ppm nonroad fuel standard.

As in the base case, the same sulfur-to-sulfate conversion rate was used as for land-based

diesel applications before they started using aftertreatment technologies (2.247 percent). The

slight decrease in average sulfur level in 2006 is due to the introduction of highway diesel fuel

meeting the 2007 15 ppm standard, and the "spillover" of this highway fuel into the nonroad fuel

pool. Note that there are transition years in which the control sulfur level begins in June, in which

case the annual average sulfur level shown reflects an interpolation of five months at the higher

sulfur level of the prior year plus seven months at the new lower sulfur level. The derivation of

these sulfur levels are described in more detail in Chapter 7.

The control case locomotive and commercial marine PM inventories were calculated by

subtracting the sulfate PM benefits (from decreased fuel sulfur content) described above from the

base case locomotive and commercial marine PM inventories. The 48-state and 50-state control

case locomotive and commercial marine PM2.5 and SO2 inventories are given in Tables 3.4-8a and

3.4-8b, respectively.
Emission Inventory

3-57

Table 3.4-8a

Controlled (48-State) Fuel Sulfur Levels, SO2, 

Sulfate PM, and PM2.5 Emissions for Locomotives and Commercial Marine Vessels

Year

Control 

Sulfur Level

(ppm)

Control

SO2 Sulfate PM Total PM2.5

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr) Loco (tons/yr) CMV (tons/yr)

2007 1,328 26,430 14,517 2,126 1,168 17,023 17,586

2008 408 8,210 4,512 661 363 15,146 16,641

2009 408 8,321 4,554 669 366 15,038 16,485

2010 307 6,352 3,457 511 278 14,725 16,377

2011 234 4,944 2,675 398 215 15,067 16,254

2012 123 2,614 1,415 210 114 14,703 16,003

2013 43 921 498 74 40 14,354 15,793

2014 51 1,099 595 88 48 14,146 15,660

2015 56 1,231 667 99 54 13,936 15,534

2016 56 1,244 672 100 54 13,745 15,455

2017 56 1,255 678 101 55 13,527 15,402

2018 56 1,263 687 102 55 13,626 15,367

2019 56 1,274 697 103 56 13,409 15,382

2020 56 1,282 703 103 57 13,149 15,436

2021 56 1,288 710 104 57 12,861 15,511

2022 56 1,298 721 104 58 12,618 15,599

2023 56 1,309 727 105 59 12,729 15,719

2024 56 1,319 736 106 59 12,476 15,846

2025 56 1,332 743 107 60 12,229 15,990

2026 56 1,342 751 108 60 11,962 16,138

2027 56 1,352 760 109 61 12,060 16,295

2028 56 1,363 769 110 62 11,785 16,452

2029 56 1,373 777 110 63 11,504 16,614

2030 56 1,384 786 111 63 11,599 16,778

2031 56 1,394 795 112 64 11,310 16,950

2032 56 1,405 805 113 65 11,016 17,122

2033 56 1,416 814 114 65 11,107 17,292

2034 56 1,427 824 115 66 10,804 17,463

2035 56 1,438 833 116 67 10,893 17,636

2036 56 1,449 843 117 68 10,983 17,811

2037 56 1,460 853 117 69 10,669 17,986

2038 56 1,471 863 118 69 10,757 18,162

2039 55 1,482 874 119 70 10,434 18,339

2040 55 1,494 884 120 71 10,520 18,517
Final Regulatory Impact Analysis

3-58

Table 3.4-8b

Controlled (50-State) Fuel Sulfur Levels, SO2, 

Sulfate PM, and PM2.5 Emissions for Locomotives and Commercial Marine Vessels

Year

Control 

Sulfur Level

(ppm)

Control

SO2 Sulfate PM Total PM2.5

Loco

(tons/yr)

CMV

(tons/yr)

Loco

(tons/yr)

CMV

(tons/yr) Loco (tons/yr) CMV (tons/yr)

2007 1,332 26,548 15,305 2,136 1,231 17,127 18,559

2008 435 8,764 5,055 705 407 15,285 17,587

2009 435 8,881 5,103 715 411 15,177 17,423

2010 319 6,615 3,779 532 304 14,838 17,293

2011 236 4,990 2,834 401 228 15,161 17,152

2012 124 2,646 1,504 213 121 14,796 16,888

2013 44 943 535 76 43 14,447 16,667

2014 52 1,133 645 91 52 14,240 16,528

2015 56 1,215 692 98 56 14,027 16,393

2016 56 1,228 697 99 56 13,836 16,310

2017 56 1,239 703 100 57 13,619 16,254

2018 55 1,247 712 100 57 13,719 16,219

2019 55 1,258 723 101 58 13,502 16,234

2020 55 1,266 729 102 59 13,243 16,292

2021 55 1,271 737 102 59 12,955 16,372

2022 55 1,281 747 103 60 12,713 16,465

2023 55 1,291 754 104 61 12,825 16,591

2024 55 1,302 763 105 61 12,572 16,726

2025 55 1,314 771 106 62 12,326 16,878

2026 55 1,324 779 107 63 12,058 17,034

2027 55 1,334 788 107 63 12,158 17,200

2028 55 1,344 797 108 64 11,883 17,366

2029 55 1,355 806 109 65 11,603 17,537

2030 55 1,365 815 110 66 11,699 17,710

2031 55 1,375 825 111 66 11,411 17,892

2032 55 1,386 834 112 67 11,116 18,073

2033 55 1,397 844 112 68 11,208 18,253

2034 55 1,407 854 113 69 10,906 18,434

2035 55 1,418 864 114 70 10,996 18,617

2036 55 1,429 874 115 70 11,087 18,801

2037 55 1,440 885 116 71 10,774 18,987

2038 55 1,451 895 117 72 10,863 19,173

2039 55 1,462 906 118 73 10,541 19,359

2040 55 1,473 917 119 74 10,628 19,548

3.4.4 Recreational Marine Engines

Even though this final rule does not include any emission standards for marine engines, there

are PM and SO2 benefits associated with these engines due to the fuel sulfur standards. The

emission inventory estimates presented in Tables 3.4-9a and 3.4-9b assume that recreational
Emission Inventory

3-59

marine applications will use diesel fuel meeting the same standards as locomotive and

commercial marine diesel fuel, as shown in Table 3.4-5.

Table 3.4-9a

Controlled (48-State) Emissions for Recreational Marine Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 951 923 33,679 4,286 1,297 5,424

2000 1,070 1,038 37,943 4,831 1,455 6,098

2001 1,099 1,066 39,071 4,968 1,494 6,271

2002 1,130 1,096 40,198 5,114 1,533 6,444

2003 1,160 1,125 41,325 5,259 1,571 6,615

2004 1,190 1,154 42,452 5,406 1,609 6,787

2005 1,220 1,183 43,578 5,551 1,647 6,958

2006 1,233 1,196 44,105 5,647 1,657 7,128

2007 1,020 990 44,602 2,940 1,664 7,298

2008 862 836 45,066 926 1,670 7,467

2009 865 839 45,415 948 1,670 7,636

2010 847 822 45,729 731 1,668 7,804

2011 833 808 46,022 570 1,665 7,971

2012 810 786 46,282 306 1,660 8,137

2013 792 768 46,528 109 1,655 8,303

2014 790 767 46,765 133 1,649 8,469

2015 787 764 46,969 149 1,642 8,635

2016 783 759 47,168 152 1,634 8,802

2017 778 755 47,362 155 1,627 8,969

2018 772 749 47,525 158 1,618 9,137

2019 767 744 47,687 161 1,611 9,308

2020 761 738 47,847 164 1,604 9,482

2021 756 733 48,003 167 1,597 9,655

2022 750 728 48,182 170 1,592 9,829

2023 745 722 48,363 173 1,586 10,004

2024 740 718 48,593 176 1,583 10,178

2025 740 717 48,961 180 1,587 10,354

2026 744 721 49,501 183 1,599 10,529

2027 749 727 50,092 186 1,614 10,704

2028 756 733 50,716 189 1,630 10,880

2029 763 741 51,392 192 1,649 11,056

2030 772 749 52,085 195 1,669 11,232

2031 781 757 52,790 198 1,689 11,409

2032 790 766 53,510 201 1,710 11,585

2033 799 775 54,228 204 1,731 11,762

2034 808 784 54,959 207 1,753 11,938

2035 818 794 55,702 210 1,775 12,115

2036 828 803 56,444 213 1,798 12,292

2037 838 813 57,197 216 1,820 12,469

2038 849 823 57,963 220 1,844 12,646

2039 859 833 58,729 219 1,868 12,823

2040 870 844 59,506 222 1,892 13,001
Final Regulatory Impact Analysis

3-60

Table 3.4-9b

Controlled (50-State) Emissions for Recreational Marine Diesel Engines (short tons)

Year PM10 PM2.5 NOx SO2 VOC CO

1996 957 929 33,891 4,312 1,305 5,458

2000 1,076 1,044 38,182 4,859 1,464 6,137

2001 1,106 1,073 39,317 4,995 1,503 6,311

2002 1,137 1,103 40,452 5,145 1,542 6,484

2003 1,167 1,132 41,586 5,290 1,581 6,657

2004 1,197 1,161 42,719 5,436 1,619 6,829

2005 1,227 1,190 43,852 5,582 1,658 7,001

2006 1,236 1,199 44,383 5,622 1,667 7,173

2007 1,027 997 44,883 2,967 1,674 7,344

2008 872 846 45,350 993 1,680 7,514

2009 875 849 45,701 1,017 1,680 7,684

2010 855 829 46,018 764 1,678 7,853

2011 839 814 46,312 578 1,675 8,021

2012 816 791 46,573 311 1,671 8,189

2013 797 773 46,821 113 1,665 8,356

2014 795 772 47,060 136 1,660 8,523

2015 792 768 47,265 150 1,652 8,690

2016 788 764 47,465 153 1,645 8,857

2017 783 759 47,660 156 1,637 9,025

2018 777 753 47,825 156 1,629 9,195

2019 771 748 47,987 159 1,621 9,367

2020 766 743 48,148 162 1,614 9,541

2021 760 737 48,305 165 1,607 9,716

2022 755 732 48,485 168 1,602 9,891

2023 749 727 48,667 171 1,596 10,067

2024 745 722 48,899 174 1,593 10,243

2025 744 722 49,269 177 1,597 10,419

2026 748 726 49,813 180 1,609 10,595

2027 754 731 50,408 183 1,624 10,772

2028 760 737 51,036 187 1,640 10,949

2029 768 745 51,716 190 1,659 11,126

2030 776 753 52,413 193 1,679 11,303

2031 785 762 53,123 196 1,700 11,481

2032 794 771 53,847 199 1,721 11,658

2033 804 779 54,570 202 1,742 11,836

2034 813 789 55,305 205 1,764 12,013

2035 823 798 56,053 208 1,786 12,191

2036 833 808 56,799 211 1,809 12,369

2037 843 818 57,558 214 1,832 12,547

2038 854 828 58,329 217 1,856 12,726

2039 865 839 59,099 220 1,879 12,904

2040 876 849 59,881 223 1,904 13,082
Emission Inventory

3-61

3.5 Projected Emission Reductions from the Final Rule

Emissions from nonroad diesel engines will continue to be a significant part of the emission

inventory in the coming years. In the absence of new emission standards, we expect overall

emissions from nonroad diesel engines to generally decline across the nation for the next 10 to 15

years, depending on the pollutant. Although nonroad diesel engine emissions decline during this

period, this trend will not be enough to adequately reduce the large amount of emissions that

these engines contribute. In addition, after the 2010 to 2015 time period we project that this trend

reverses and emissions rise into the future in the absence of additional regulation of these engines. 

The initial downward trend occurs as the nonroad fleet becomes increasingly dominated over time

by engines that comply with existing emission regulations. The upturn in emissions beginning

around 2015 results as growth in the nonroad sector overtakes the effect of the existing emission

standards.

The engine and fuel standards in this rule will affect fine particulate matter (PM2.5), oxides of

nitrogen (NOx), sulfur oxides (SO2), volatile organic hydrocarbons (VOC), air toxics, and carbon

monoxide (CO). For engines used in locomotives, commercial marine vessels, and recreational

marine vessels, the requirements for low-sulfur fuel will affect PM2.5 and SO2.

This section discusses the projected emission reductions associated with this final rule. The

baseline case represents future emissions with current standards. The controlled case estimates

the future emissions of these engines based on the new emission standards and fuel requirements. 

Both 48-state and 50-state results are presented. Tables 3.5-1a and 3.5-1b present a summary of

the total 48-state and 50-state emission reductions for each pollutant.

3.5.1 PM2.5 Reductions

48-State and 50-state emissions of PM2.5 from land-based nonroad diesel engines are shown in

Tables 3.5-2a and 3.5-2b, respectively, along with estimates of the reductions from this final rule. 

PM2.5 will be reduced as a result of the new PM emission standards and changes in the sulfur level

in nonroad diesel fuel. The exhaust emission standards begin in 2008 for engines less than 75 hp,

and are completely phased in for all hp categories by 2015. Nonroad diesel fuel sulfur is reduced

to a 500 ppm standard in June of 2007, and further reduced to a 15 ppm standard (11 ppm in-use)

in June of 2010. The 15 ppm standard is fully phased in starting in 2011.

Tables 3.5-2a and 3.5-2b present results for five-year increments from 2000 to 2030. 

Individual years from 2007 to 2011 are also included, since fuel sulfur levels are changing during

this period. Emissions are projected to 2030 to reflect close to complete turnover of the fleet to

engines meeting the new emission standards. For comparison purposes, emission reductions are

also shown from reducing the diesel fuel sulfur level to 500 ppm in 2007 and to 15 ppm in 2010,

without any new emission standards.
Table 3.5-1a

Total Emission Reductions (48-State) from the Final Rule

Year PM2.5 NOx SO2 VOC CO Benzene Formaldehyde Acetaldehyde 1

2000 0 0 0 0 00 0 0 2005 0 0 0 0 00 0 0 2007 10,511 0 134,388 0 0 0 0 0 2008 19,031 30 236,976 168 3,104 3 20 9 2009 19,943 70 241,719 341 6,266 7 40 18 2010 21,692 149 256,447 525 9,634 11 62 28 2011 25,154 17,830 268,989 1,139 28,704 23 134 60 2012 31,103 46,827 278,092 2,486 64,599 50 293 132 2015 53,072 193,431 297,513 8,318 198,947 166 981 441 2020 85,808 442,061 323,378 18,141 388,037 363 2,141 961 2025 110,043 613,629 349,312 25,002 521,457 500 2,950 1,325 2030 128,350 734,184 375,354 30,030 619,167 601 3,544 1,592 

Table 3.5-1b

Total Emission Reductions (50-State) from the Final Rule

Year PM2.5 NOx SO2 VOC CO Benzene Formaldehyde Acetaldehyde 1

2000 0 0 0 0 00 0 0 2005 0 0 0 0 00 0 0 2007 10,403 0 132,998 0 0 0 0 0 2008 18,908 31 235,366 169 3,119 3 20 9 2009 19,821 72 240,084 343 6,296 7 41 18 2010 21,627 153 255,525 529 9,680 11 62 28 2011 25,142 17,951 268,613 1,146 28,871 23 135 61 2012 31,122 47,129 277,804 2,501 64,983 50 295 133 2015 53,238 194,615 297,440 8,367 200,118 167 987 443 2020 86,157 444,714 323,302 18,251 390,333 365 2,154 967 2025 110,508 617,176 349,233 25,152 524,471 503 2,968 1,333 2030 128,899 738,307 375,269 30,210 622,706 604 3,565 1,601 
Emission Inventory

3-63

Table 3.5-2a

Estimated National (48-State) PM2.5

Emissions and Reductions From Nonroad Land-Based Diesel Enginesa

Year

PM2.5 Emissions [short tons] PM2.5 Reductions [short tons]

Without 

Rule

With fuel

sulfur

reduced to

500 ppm in

2007;

No Tier 4

standards

With fuel

sulfur further

reduced to

15 ppm in

2010; No

Tier 4

standards

With Rule

(Fuel sulfur

reduced to 15

ppm in 2010;

Tier 4

standards)

With fuel

sulfur

reduced to

500 ppm in

2007;

No Tier 4

standards

With fuel

sulfur

further

reduced to

15 ppm in

2010; No

Tier 4

standards

With 

Rule

2000 170,774 170,774 170,774 170,774 0 0 0

2005 144,259 144,259 144,259 144,259 0 0 0

2007 135,791 128,558 128,558 128,558 7,232 7,232 7,232

2008 133,245 120,434 120,434 119,936 12,811 12,811 13,309

2009 131,044 117,938 117,938 116,896 13,106 13,106 14,148

2010 128,730 115,273 114,416 112,775 13,458 14,315 15,955

2011 127,035 113,243 111,739 107,612 13,792 15,296 19,423

2015 125,936 110,950 109,157 79,326 14,986 16,779 46,610

2020 129,058 112,595 110,625 50,065 16,463 18,433 78,993

2025 135,369 117,428 115,281 32,503 17,941 20,087 102,866

2030 142,484 123,076 120,754 21,698 19,408 21,730 120,786

a

 PM2.5 represents 97 percent of PM10 emissions.
Final Regulatory Impact Analysis

3-64

Table 3.5-2b

Estimated National (50-State) PM2.5

Emissions and Reductions From Nonroad Land-Based Diesel Enginesa

Year

PM2.5 Emissions [short tons] PM2.5 Reductions [short tons]

Without 

Rule

With fuel

sulfur

reduced to

500 ppm in

2007;

No Tier 4

standards

With fuel

sulfur further

reduced to

15 ppm in

2010; No

Tier 4

standards

With Rule

(Fuel sulfur

reduced to 15

ppm in 2010;

Tier 4

standards)

With fuel

sulfur

reduced to

500 ppm in

2007;

No Tier 4

standards

With fuel

sulfur

further

reduced to

15 ppm in

2010; No

Tier 4

standards

With 

Rule

2000 171,575 171,575 171,575 171,575 0 0 0

2005 144,951 144,951 144,951 144,951 0 0 0

2007 136,362 129,165 129,165 129,165 7,197 7,197 7,197

2008 133,807 121,030 121,030 120,529 12,777 12,777 13,277

2009 131,598 118,526 118,526 117,479 13,071 13,071 14,118

2010 129,276 115,846 114,984 113,336 13,430 14,292 15,940

2011 127,576 113,797 112,292 108,147 13,778 15,283 19,428

2015 126,482 111,511 109,708 79,706 14,971 16,774 46,777

2020 129,628 113,181 111,200 50,285 16,447 18,428 79,343

2025 135,972 118,049 115,891 32,641 17,923 20,081 103,331

2030 143,126 123,737 121,402 21,790 19,389 21,724 121,336

a

 PM2.5 represents 97 percent of PM10 emissions.

The benefits in the early years of the program (i.e., pre-2010) are primarily from reducing the

diesel fuel sulfur level to 500 ppm. As the standards phase in and fleet turnover occurs, PM2.5

emissions are impacted more significantly from the requirements of the final rule. PM2.5

emissions from land-based diesel engines are projected to decrease by roughly 120,000 tons by

2030 as a result of this rule.

Figure 3.5-1 shows EPA’s estimate of 50-state PM2.5 emissions from land-based diesel

engines for 2000 to 2030 with and without the new PM emission standards. We estimate that

PM2.5 emissions from this source would decrease by 85 percent in 2030.
Emission Inventory

3-65

Figure 3.5-1: Estimate d R e ductions in PM 2 .5 Emissions 

From Land-Base d N onroad Engine s (tons/ye ar)

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

200,000

2000 2005 2010 2015 2020 2025 2030

Base 50-State

C ontrol 50-State

Nonroad diesel engines used in locomotives, commercial marine vessels, and recreational

marine vessels are not affected by the emission standards in this rule. PM2.5 emissions from these

engines will be reduced as a result of the lower fuel sulfur levels from a current in-use average of

about 2640 ppm to about 55 ppm by 2015. The estimated 48-state and 50-state reductions in

PM2.5 emissions from these engines based on the diesel fuel-sulfur requirements are given in

Tables 3.5-3a and 3.5-3b, respectively. Total PM2.5 reductions reach roughly 7,500 tons in 2030

for these engine categories.

Tables 3.5-4a and 3.5-4b present the PM2.5 emissions and reductions for all nonroad diesel

categories combined. The 50-state results are also presented graphically in Figure 3.5-2. For all

nonroad diesel categories combined, the estimated reductions in PM2.5 emissions are 86,000 tons

in 2020, increasing to 128,000 tons in 2030. Simply reducing the fuel sulfur level to 500 ppm in

2007 will lead to projected PM2.5 reductions of 23,000 tons in 2020 and 26,000 tons in 2030. 

Reducing the fuel sulfur level further to 15 ppm (in 2010 for land-based diesel engines and in

2012 for marine engines and locomotives) in the absence of Tier 4 standards (i.e., a fuel only

program) will lead to projected PM2.5 reductions of 25,000 tons in 2020 and 29,000 tons in 2030.
Final Regulatory Impact Analysis

3-66

Table 3.5-3a

Estimated National (48-State) PM2.5 Reductions

From Locomotives, Commercial Marine, and Recreational Marine Diesel Engines

Year

PM2.5 Reductions with Rule [short tons]

Locomotives Commerical 

Marine Diesel

Recreational

Marine Diesel

Total PM2.5

Reductions

2000 0 0 0 0

2005 0 0 0 0

2007 1,975 1,085 220 3,279

2008 3,442 1,891 389 5,722

2009 3,488 1,909 398 5,796

2010 3,458 1,882 397 5,737

2011 3,460 1,871 400 5,731

2015 3,885 2,105 473 6,463

2020 4,063 2,229 522 6,815

2025 4,240 2,366 572 7,178

2030 4,426 2,516 622 7,564

Table 3.5-3b

Estimated National (50-State) PM2.5 Reductions

From Locomotives, Commercial Marine, and Recreational Marine Diesel Engines

Year

PM2.5 Reductions with Rule [short tons]

Locomotives Commerical 

Marine Diesel

Recreational

Marine Diesel

Total PM2.5

Reductions

2000 0 0 0 0

2005 0 0 0 0

2007 1,899 1,095 212 3,206

2008 3,331 1,921 378 5,630

2009 3,376 1,940 387 5,702

2010 3,372 1,927 390 5,689

2011 3,393 1,927 394 5,714

2015 3,820 2,175 467 6,462

2020 3,995 2,303 516 6,814

2025 4,168 2,445 565 7,177

2030 4,350 2,599 614 7,563
Emission Inventory

3-67

Table 3.5-4a

Estimated National (48-State) PM2.5 Emissions and Reductions from 

Land-Based Nonroad, Locomotive, Commercial Marine, and Recreational Marine Vessels

Year

PM2.5 Emissions [short tons] PM2.5 Reductions [short tons]

Without 

Rule

With fuel

sulfur

reduced to

500 ppm in

2007; No

Tier 4

standards

With fuel

sulfur further

reduced to

15 ppm in

2010/2012;

No Tier 4

standards

With Rule

(Fuel sulfur

further

reduced to 15

ppm in

2010/2012;

Tier 4

standards)

With fuel

sulfur

reduced to

500 ppm in

2007; No

Tier 4

standards

With fuel

sulfur

further

reduced to

15 ppm in

2010/2012;

No Tier 4

standards

With Rule

(Fuel sulfur

further

reduced to 15

ppm in

2010/2012;

Tier 4

standards)

2000 209,876 209,876 209,876 209,876 0 0 0

2005 183,831 183,831 183,831 183,831 0 0 0

2007 174,668 164,157 164,157 164,157 10,511 10,511 10,511

2008 171,591 153,058 153,058 152,560 18,533 18,533 19,031

2009 169,201 150,300 150,300 149,258 18,901 18,901 19,943

2010 166,391 147,235 146,340 144,699 19,156 20,051 21,692

2011 164,894 145,438 143,868 139,741 19,457 21,027 25,154

2012 163,784 143,965 142,054 132,681 19,819 21,730 31,103

2015 162,633 141,757 139,391 109,560 20,876 23,241 53,072

2020 165,196 142,522 139,948 79,388 22,674 25,248 85,808

2025 171,484 147,002 144,219 61,440 24,482 27,265 110,043

2030 179,173 152,873 149,880 50,824 26,300 29,293 128,350
Final Regulatory Impact Analysis

3-68

Table 3.5-4b

Estimated National (50-State) PM2.5 Emissions and Reductions from 

Land-Based Nonroad, Locomotive, Commercial Marine, and Recreational Marine Vessels

Year

PM2.5 Emissions [short tons] PM2.5 Reductions [short tons]

Without 

Rule

With fuel

sulfur

reduced to

500 ppm in

2007; No

Tier 4

standards

With fuel

sulfur further

reduced to

15 ppm in

2010/2012;

No Tier 4

standards

With Rule

(Fuel sulfur

further

reduced to 15

ppm in

2010/2012;

Tier 4

standards)

With fuel

sulfur

reduced to

500 ppm in

2007; No

Tier 4

standards

With fuel

sulfur

further

reduced to

15 ppm in

2010/2012;

No Tier 4

standards

With Rule

(Fuel sulfur

further

reduced to 15

ppm in

2010/2012;

Tier 4

standards)

2000 211,688 211,688 211,688 211,688 0 0 0

2005 185,555 185,555 185,555 185,555 0 0 0

2007 176,250 165,847 165,847 165,847 10,403 10,403 10,403

2008 173,154 154,747 154,747 154,247 18,407 18,407 18,908

2009 170,750 151,976 151,976 150,929 18,774 18,774 19,821

2010 167,923 148,844 147,944 146,296 19,079 19,979 21,627

2011 166,416 146,990 145,419 141,274 19,426 20,997 25,142

2012 165,298 145,510 143,591 134,176 19,788 21,707 31,122

2015 164,133 143,289 140,897 110,894 20,843 23,236 53,238

2020 166,719 144,080 141,477 80,562 22,639 25,242 86,157

2025 173,075 148,630 145,816 62,567 24,445 27,259 110,508

2030 180,851 154,591 151,565 51,953 26,260 29,287 128,899
Emission Inventory

3-69

Figure 3.5-2: Estimated Reductions in PM2.5 

Emissions From Land-Based Nonroad Engines, 

CMVs, RMVs, and Locomotives (tons/year)

0

50,000

100,000

150,000

200,000

250,000

2000 2005 2010 2015 2020 2025 2030

Base 50-State

Control 50-State

3.5.2 NOx Reductions

Tables 3.5-5a and 3.5-5b show the estimated 48-state and 50-state NOx emissions in five-year

increments from 2000 to 2030 with and without this rule. The 50-state results are shown

graphically in Figure 3.5-3. We estimate that NOx emissions from these engines will be reduced

by 62 percent in 2030.

We note that the magnitude of NOx reductions determined in the final rule analysis is

somewhat less than what was reported in the proposal's draft RIA, especially in the later years

when the fleet has mostly turned over to Tier 4 designs. The greater part of this is due to the fact

that we have deferred setting a long-term NOx standard for mobile machinery over 750 hp to a

later action. When this future action is completed, we would expect roughly equivalent

reductions between the proposal and the overall final program, though there are some other

effects reflected in the differing NOx reductions as well, due to updated modeling assumptions

and the adjusted NOx standards levels for engines over 750 hp. Preamble Section II.A.4 contains

a detailed discussion of the NOx standards we are adopting for engines over 750 hp, and the basis

for those standards.

NOx emissions from locomotives, commercial marine diesel vessels, and recreational marine

diesel vessels are not affected by this rule.
Final Regulatory Impact Analysis

3-70

Table 3.5-5a

Estimated National (48-State) NOx Emissions 

and Reductions From Nonroad Land-Based Diesel Engines

Year NOx Emissions Without

Rule [short tons]

NOx Emissions With

Rule

NOx Reductions With

Rule

2000 1,550,355 1,550,355 0

2005 1,467,547 1,467,547 0

2010 1,278,038 1,277,888 149

2015 1,152,199 958,769 193,431

2020 1,119,481 677,420 442,061

2030 1,192,833 458,649 734,184

Table 3.5-5b

Estimated National (50-State) NOx Emissions 

and Reductions From Nonroad Land-Based Diesel Engines

Year NOx Emissions Without

Rule [short tons]

NOx Emissions With

Rule

NOx Reductions With

Rule

2000 1,558,392 1,558,392 0

2005 1,475,092 1,475,092 0

2010 1,284,510 1,284,357 153

2015 1,158,023 963,408 194,615

2020 1,125,276 680,563 444,714

2030 1,199,225 460,918 738,307
Emission Inventory

3-71

Figure 3.5-3: Estimated Reductions in NOx Emissions 

From Land-Based Nonroad Engines (tons/year)

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2000 2005 2010 2015 2020 2025 2030

Base 50-State

Control 50-State

3.5.3 SO2 Reductions

As part of this final rule, sulfur levels in fuel will be significantly reduced, leading to large

reductions in nonroad diesel SO2 emissions. By 2007, the sulfur in diesel fuel used by all nonroad

diesel engines will be reduced to 500 ppm. By 2010, the sulfur in diesel fuel used by nonroad

land-based engines will be further reduced to 15 ppm. By 2012, the sulfur in diesel fuel used by

marine engines and locomotives will also be reduced to 15 ppm.

48-State and 50-state emissions of SO2 from land-based nonroad diesel engines are shown in

Tables 3.5-6a and 3.5-6b, respectively, along with estimates of the emission reductions resulting

from this final rule. Results are presented for five-year increments from 2000 to 2030. Individual

years from 2007 to 2011 are also included, since fuel sulfur levels are changing during this

period. SO2 will be reduced due to the changes in the sulfur level in nonroad diesel fuel. For

comparison purposes, emission reductions are also shown from reducing the diesel fuel sulfur

level to 500 ppm beginning in June of 2007, without any new emission standards or any

additional sulfur level reductions.
Final Regulatory Impact Analysis

3-72

Table 3.5-6a

Estimated National (48-State) SO2

Emissions and Reductions From Nonroad Land-Based Diesel Engines

Year

SO2 Emissions [short tons] SO2 Reductions [short tons]

Without 

Rule

With fuel sulfur

reduced to 500 ppm in

2007

With Rule

(Fuel sulfur reduced

to 15 ppm in 2010)

With fuel sulfur

reduced to 500 ppm in

2007

With 

Rule

2000 161,977 161,977 161,977 0 0

2005 185,287 185,287 185,287 0 0

2007 189,511 97,142 97,142 92,370 92,370

2008 194,019 30,359 30,359 163,660 163,660

2009 198,526 31,064 31,064 167,462 167,461

2010 197,829 25,835 14,881 171,993 182,948

2011 198,415 22,119 2,853 176,296 195,562

2015 215,699 24,045 992 191,654 214,707

2020 237,044 26,425 986 210,619 236,057

2025 258,360 28,801 1,019 229,559 257,341

2030 279,511 31,159 1,074 248,352 278,437
Emission Inventory

3-73

Table 3.5-6b

Estimated National (50-State) SO2

Emissions and Reductions From Nonroad Land-Based Diesel Engines

Year

SO2 Emissions [short tons] SO2 Reductions [short tons]

Without 

Rule

With fuel sulfur

reduced to 500 ppm in

2007

With Rule

(Fuel sulfur reduced

to 15 ppm in 2010)

With fuel sulfur

reduced to 500 ppm in

2007

With 

Rule

2000 162,920 162,920 162,920 0 0

2005 186,368 186,368 186,368 0 0

2007 189,505 97,580 97,580 91,926 91,926

2008 194,013 30,786 30,786 163,227 163,227

2009 198,521 31,501 31,501 167,019 167,019

2010 197,795 26,159 15,145 171,637 182,651

2011 198,360 22,238 2,961 176,122 195,400

2015 215,641 24,175 997 191,466 214,644

2020 236,982 26,568 991 210,414 235,990

2025 258,294 28,957 1,024 229,337 257,270

2030 279,442 31,328 1,080 248,114 278,362

The benefits in the early years of the program (i.e., pre-2010) are from reducing the diesel fuel

sulfur level to 500 ppm. Reducing the diesel fuel sulfur level to 15 ppm in June of 2010

proportionately reduces SO2 further. Total 50-state SO2 emissions are projected to decrease by

278,000 tons in 2030 as a result of this final rule. Note that SO2 emissions continue to increase

over time due to the growth in the nonroad sector.

Nonroad diesel engines used in locomotives, commercial marine vessels, and recreational

marine vessels are also affected by the new fuel sulfur requirements. The estimated 48-state and

50-state reductions in SO2 emissions from these engines based on the new requirements for diesel

fuel are given in Tables 3.5-7a and 3.5-7b, respectively. Total 50-state SO2 reductions reach

96,000 tons in 2030 for these nonroad diesel engine categories.

Tables 3.5-8a and 3.5-8b present the SO2 emissions and reductions for all nonroad diesel

categories combined. The 50-state results are also presented graphically in Figure 3.5-4. For all

nonroad diesel categories combined, the estimated 50-state reductions in SO2 emissions resulting

from the final rule are 323,000 tons in 2020, increasing to 375,000 tons in 2030. Simply reducing

the fuel sulfur level to 500 ppm in 2007 will result in SO2 reductions of 289,000 tons in 2020 and

336,000 tons in 2030.
Final Regulatory Impact Analysis

3-74

Table 3.5-7a

Estimated National (48-State) SO2 Reductions

From Locomotives, Commercial Marine, and Recreational Marine Diesel Engines

Year

SO2 Reductions with Rule [short tons]

Locomotives Commerical Marine

Diesel Vessels

Recreational

Marine Diesel

Vessels

Total SO2

Reductions

2000 0 0 0 0

2005 0 0 0 0

2007 25,305 13,899 2,814 42,018

2008 44,107 24,238 4,972 73,316

2009 44,700 24,465 5,093 74,257

2010 44,306 24,108 5,085 73,499

2011 44,334 23,980 5,112 73,426

2015 49,779 26,977 6,049 82,806

2020 52,070 28,564 6,686 87,320

2025 54,328 30,319 7,324 91,971

2030 56,720 32,234 7,963 96,917
Emission Inventory

3-75

Table 3.5-7b

Estimated National (50-State) SO2 Reductions

From Locomotives, Commercial Marine, and Recreational Marine Diesel Engines

Year

SO2 Reductions with Rule [short tons]

Locomotives Commerical Marine

Diesel Vessels

Recreational

Marine Diesel

Vessels

Total SO2

Reductions

2000 0 0 0 0

2005 0 0 0 0

2007 24,329 14,025 2,718 41,072

2008 42,683 24,621 4,834 72,139

2009 43,258 24,855 4,952 73,065

2010 43,207 24,685 4,983 72,875

2011 43,481 24,695 5,037 73,213

2015 48,954 27,867 5,975 82,797

2020 51,196 29,511 6,604 87,311

2025 53,404 31,325 7,235 91,963

2030 55,742 33,302 7,863 96,907
Final Regulatory Impact Analysis

3-76

Table 3.5-8a

Estimated National (48-State) SO2 Emissions and Reductions from 

Land-Based Nonroad, Locomotive, Commercial Marine, and Recreational Marine Vessels

Year

SO2 Emissions [short tons] SO2 Reductions [short tons]

Without 

Rule

With fuel sulfur

reduced to 500

ppm in 2007

With fuel sulfur

further reduced to 15

ppm in 2010/2012

With fuel sulfur

reduced to 500

ppm in 2007

With fuel sulfur

further reduced to 15

ppm in 2010/2012

2000 244,599 244,599 244,599 0 0

2005 269,288 269,288 269,288 0 0

2007 275,416 141,029 141,029 134,388 134,388

2008 280,983 44,007 44,007 236,976 236,976

2009 286,606 44,887 44,888 241,719 241,719

2010 281,867 36,860 25,420 245,007 256,447

2011 280,031 31,152 11,041 248,879 268,989

2012 285,277 31,735 7,185 253,542 278,092

2015 300,552 33,434 3,039 267,118 297,513

2020 326,514 36,322 3,136 290,192 323,378

2025 352,585 39,218 3,273 313,367 349,312

2030 378,793 42,128 3,439 336,665 375,354
Emission Inventory

3-77

Table 3.5-8b

Estimated National (50-State) SO2 Emissions and Reductions from 

Land-Based Nonroad, Locomotive, Commercial Marine, and Recreational Marine Vessels

Year

SO2 Emissions [short tons] SO2 Reductions [short tons]

Without 

Rule

With fuel sulfur

reduced to 500

ppm in 2007

With fuel sulfur

further reduced to 15

ppm in 2010/2012

With fuel sulfur

reduced to 500

ppm in 2007

With fuel sulfur

further reduced to 15

ppm in 2010/2012

2000 247,010 247,010 247,010 0 0

2005 271,841 271,841 271,841 0 0

2007 275,397 142,399 142,399 132,998 132,998

2008 280,964 45,598 45,598 235,366 235,366

2009 286,588 46,503 46,503 240,085 240,084

2010 281,828 37,802 26,303 244,026 255,525

2011 279,976 31,486 11,363 248,490 268,613

2012 285,221 32,075 7,418 253,147 277,804

2015 300,494 33,788 3,054 266,706 297,440

2020 326,450 36,701 3,149 289,749 323,302

2025 352,519 39,625 3,286 312,894 349,233

2030 378,722 42,565 3,453 336,157 375,269
Final Regulatory Impact Analysis

3-78

Figure 3.5-4: Estimated Reductions in SO2 Benefits 

From Reducing Fuel Sulfur for Land-Based Nonroad 

Engines, CMVs, RMVs, and Locomotives (tons/year)

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

2000 2005 2010 2015 2020 2025 2030

Base 50-State

Control 50-State

3.5.4 VOC and Air Toxics Reductions

Tables 3.5-9a and 3.5-9b show our projection of the 48-state and 50-state reductions in VOC

emissions expected from implementing the new NMHC emission standards.

Although this final rule does not include specific standards for air toxics, these pollutants

decrease as manufacturers take steps to meet the NMHC emission standards. Tables 3.5-10a and

3.5-10b show our estimate of reduced emissions of benzene, formaldehyde, acetaldehyde,

1,3-butadiene, and acrolein. We base these numbers on the assumption that air toxic emissions

are a constant fraction of hydrocarbon exhaust emissions.
Emission Inventory

3-79

Table 3.5-9a

VOC Reductions (48-State) from Land-Based Nonroad Diesel Engines

Calendar Year VOC 

Without Rule 

[short tons]

VOC 

With Rule 

[short tons]

VOC Reductions 

With Rule 

[short tons]

2000 199,887 199,887 0

2005 163,663 163,663 0

2010 129,711 129,186 525

2015 107,084 98,766 8,318

2020 97,513 79,372 18,141

2025 94,975 69,973 25,002

2030 96,374 66,344 30,030

Table 3.5-9b

VOC Reductions (50-State) from Land-Based Nonroad Diesel Engines

Calendar Year VOC 

Without Rule 

[short tons]

VOC 

With Rule 

[short tons]

VOC Reductions 

With Rule 

[short tons]

2000 200,903 200,903 0

2005 164,505 164,505 0

2010 130,388 129,859 529

2015 107,647 99,281 8,367

2020 98,037 79,786 18,251

2025 95,490 70,338 25,152

2030 96,900 66,690 30,210
Final Regulatory Impact Analysis

3-80

Table 3.5-10a

Air Toxic Reductions (48-State) (tons/year)

Year Benzene Formaldehyde Acetaldehyde 1,3-butadiene Acrolein

2000 Base

Control

Reduction

3,998

3,998

0

23,587

23,587

0

10,594

10,594

0

400

400

0

600

600

0

2005 Base

Control

Reduction

3,273

3,273

0

19,312

19,312

0

8,674

8,674

0

327

327

0

491

491

0

2007 Base

Control

Reduction

3,007

3,007

0

17,742

17,742

0

7,969

7,969

0

301

301

0

451

451

0

2010 Base

Control

Reduction

2,594

2,584

11

15,306

15,244

62

6,875

6,847

28

259

258

1

389

388

2

2015 Base

Control

Reduction

2,142

1,975

166

12,636

11,654

981

5,675

5,235

441

214

198

17

321

296

25

2020 Base

Control

Reduction

1,950

1,587

363

11,507

9,366

2,141

5,168

4,207

961

195

159

36

293

238

54

2025 Base

Control

Reduction

1,900

1,399

500

11,207

8,257

2,950

5,034

3,709

1,325

190

140

50

285

210

75

2030 Base

Control

Reduction

1,927

1,327

601

11,372

7,829

3,544

5,108

3,516

1,592

193

133

60

289

199

90
Emission Inventory

3-81

Table 3.5-10b

Air Toxic Reductions (50-State) (tons/year)

Year Benzene Formaldehyde Acetaldehyde 1,3-butadiene Acrolein

2000 Base

Control

Reduction

4,018

4,018

0

23,707

23,707

0

10,648

10,648

0

402

402

0

603

603

0

2005 Base

Control

Reduction

3,290

3,290

0

19,412

19,412

0

8,719

8,719

0

329

329

0

494

494

0

2007 Base

Control

Reduction

3,023

3,023

0

17,834

17,834

0

8,010

8,010

0

302

302

0

453

453

0

2010 Base

Control

Reduction

2,608

2,597

11

15,386

15,323

62

6,911

6,883

28

261

260

1

391

390

2

2015 Base

Control

Reduction

2,153

1,986

167

12,702

11,715

987

5,705

5,262

443

215

199

17

323

298

25

2020 Base

Control

Reduction

1,961

1,596

365

11,568

9,415

2,154

5,196

4,229

967

196

160

37

294

239

55

2025 Base

Control

Reduction

1,910

1,407

503

11,268

8,300

2,968

5,061

3,728

1,333

191

141

50

286

211

75

2030 Base

Control

Reduction

1,938

1,334

604

11,434

7,869

3,565

5,136

3,535

1,601

194

133

60

291

200

91

3.5.5 CO Reductions

Tables 3.5-11a and 3.5-11b show the estimated 48-state and 50-state emissions of CO from

land-based diesel engines in five-year increments from 2000 to 2030 with and without the final

rule. Although there are no Tier 4 CO standards, CO is estimated to decrease by 90 percent with

the advent of trap-equipped engines (corresponding to the start of 0.02 or 0.01 g/hp-hr PM

standards). We estimate that 50-state CO emissions from these engines will decrease by 623,000

tons in 2030.

CO emissions from locomotives, commercial marine diesel vessels, and recreational marine

diesel vessels are not affected by this rule.
Final Regulatory Impact Analysis

3-82

Table 3.5-11a

Estimated National (48-State) CO 

Emissions and Reductions From Nonroad Land-Based Diesel Engines

Year

CO Emissions 

Without Rule 

[short tons]

CO Emissions 

With Rule

[short tons]

CO Reductions 

With Rule 

[short tons]

2000 916,507 916,507 0

2005 763,062 763,062 0

2010 687,234 677,599 9,634

2015 674,296 475,349 198,947

2020 697,630 309,593 388,037

2030 786,181 167,014 619,167

Table 3.5-11b

Estimated National (50-State) CO 

Emissions and Reductions From Nonroad Land-Based Diesel Engines

Year

CO Emissions 

Without Rule 

[short tons]

CO Emissions 

With Rule

[short tons]

CO Reductions 

With Rule 

[short tons]

2000 921,226 921,226 0

2005 766,944 766,944 0

2010 690,829 681,150 9,680

2015 677,918 477,800 200,118

2020 701,445 311,112 390,333

2030 790,547 167,841 622,706

3.5.6 PM2.5 and SO2 Reductions from the 15 ppm Locomotive and Marine (LM) Fuel

Program

Tables 3.5-12a and 3.5-12b provide the 48-state and 50-state PM2.5 and SO2 emissions and

reductions from reducing locomotive and marine fuel sulfur from 500 ppm to 15 ppm in 2012. 

This is referred to as the 15 ppm LM fuel program. The reductions are shown relative to the full

engine and fuel program for land-based diesel engines, and locomotive and marine fuel sulfur

control to 500 ppm starting in 2007. To model the reductions for this program, the in-use fuel

sulfur levels in Chapter 7 were used. The 15 ppm LM fuel program provides additional PM2.5

reductions of approximately 400 tons by 2030, and additional SO2 reductions of approximately

5,300 tons by 2030.
Emission Inventory

3-83

Table 3.5-12a

Estimated National (48-State) PM2.5 and SO2 Emissions and Reductions 

from a 15 ppm Locomotive and Marine (LM) Fuel Program

Year

Emissions (short tons) Reductions (short tons)

Land-based full engine and fuel

program; LM fuel sulfur reduced

to 500 ppm in 2007

Land-based full engine and fuel

program; LM fuel sulfur further

reduced to 15 ppm in 2012

LM fuel sulfur reduced from 

500 ppm to 15 ppm in 2012

PM2.5 SO2 PM2.5 SO2 PM2.5 SO2

2000 209,876 244,599 209,876 244,599 0 0

2005 183,831 269,288 183,831 269,288 0 0

2010 144,667 24,864 144,667 24,864 0 0

2012 133,144 11,639 132,755 7,269 389 4,370

2015 110,027 8,285 109,613 2,977 414 5,308

2020 79,870 8,517 79,450 3,139 420 5,378

2030 51,296 8,925 50,882 3,621 414 5,304

Table 3.5-12b

Estimated National (50-State) PM2.5 and SO2 Emissions and Reductions 

from a 15 ppm Locomotive and Marine (LM) Fuel Program

Year

Emissions (short tons) Reductions (short tons)

Land-based full engine and fuel

program; LM fuel sulfur reduced

to 500 ppm in 2007

Land-based full engine and fuel

program; LM fuel sulfur further

reduced to 15 ppm in 2012

LM fuel sulfur reduced from 

500 ppm to 15 ppm in 2012

PM2.5 SO2 PM2.5 SO2 PM2.5 SO2

2000 211,688 247,010 211,688 247,010 0 0

2005 185,555 271,841 185,555 271,841 0 0

2010 146,152 25,793 146,152 25,793 0 0

2012 134,509 11,871 134,137 7,567 372 4,305

2015 111,240 8,308 110,825 2,989 415 5,319

2020 80,915 8,537 80,495 3,153 420 5,385

2030 52,279 8,935 51,866 3,640 413 5,294
Final Regulatory Impact Analysis

3-84

3.5.7 SO2 and Sulfate PM Reductions from Other Nonhighway Fuel

The fuel sulfur requirements in this rule are also expected to indirectly affect diesel fuel for

other nonhighway end uses. This includes any application other than land-based nonroad

engines, locomotives, or marine vessels. Tables 3.5-13a and 3.5-13b provide the 48-state and 50-

state estimates of fuel volumes, fuel sulfur levels, and SO2 emissions and reductions for diesel

fuel for other nonhighway end uses. Tables 3.5-14a and 3.5-14b provide similar information for

sulfate PM emissions and reductions. Details regarding the estimated volumes and fuel sulfur

levels can be found in Chapter 7.

The tables show the incremental reductions from controlling fuel sulfur: 1) to 500 ppm in

2007 for land-based, locomotive, and marine use (the 500 ppm NRLM fuel program), 2) further

control to 15 ppm in 2010 for land-based use only, and 3) further control to 15 ppm in 2010 for

locomotive and marine use (the 15 ppm LM fuel program).

SO2 emissions are calculated similarly to the commercial marine and locomotive categories,

as described in Section 3.1.3. We estimate that 99 percent of the sulfur in other nonhighway fuel

is emitted in the form of SO2 and 1 percent in the form of sulfate PM.13

For the incremental step of reducing LM fuel sulfur from 500 ppm to 15 ppm, heating oil

related benefits dominate those related to the LM fuel itself. This occurs because the final rule

prohibits the use of downgraded distillate in NRLM fuel starting in mid-2010 in the

Northeast/Mid-Atlantic area, while this fuel would be able to be used in LM fuel in this area

under a 500 ppm cap. When this downgraded distillate cannot be used in LM fuel, it will shift to

the heating oil market. The downgrade contains between 31 (highway-based) and 435 ppm (jetbased) sulfur, well below that of heating oil. Thus, the sulfur content of heating oil decreases

significantly in the Northeast/Mid-Atlantic area with a 15 ppm cap on LM fuel.

Chapter 8 provides details regarding the estimated number of gallons of downgrade shifted to

the heating oil market and the corresponding sulfur content of this downgrade. The resulting SO2

and sulfate PM emission reductions for the 15 ppm LM program given in Chapter 8 are

reproduced here. The 48-state and 50-state reductions for the 15 ppm LM program are the same,

since the benefits only occur in the Northeast/Mid-Atlantic area, which does not include Alaska

or Hawaii.

Total SO2 reductions in 2030 for other nonhighway uses are estimated to be 19,000 tons with

the full fuel program. Of that, approximately 6,300 tons are due to the 500 ppm NRLM fuel

program and 12,000 tons are due to the 15 ppm LM fuel program. Total sulfate PM reductions in

2030 are estimated to be 670 tons with the full fuel program. Of that, approximately 220 tons are

due to the 500 ppm NRLM fuel program and 420 tons are due to the 15 ppm LM fuel program. 

These reductions are not included in Tables 3.5-1a and 3.5-1b.
Table 3.5-13a

Estimated National (48-State) SO2 Emissions and Reductions from Other Nonhighway Fue

Year

Volume

(106 gals)

Sulfur (ppm) SO2 Emissions (tons/year) Incremental 

Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012) Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012)

500 ppm

NRLM

Fuel

Program

50

N

Pr

an

onl

p

2

2000 10,471 2,871 2,871 2,871 2,871 211,286 211,286 211,286 211,286 0 2005 10,174 2,871 2,871 2,871 2,871 205,291 205,291 205,291 205,291 0 2007 10,058 2,858 2,671 2,671 2,671 202,026 188,820 188,820 188,820 13,206 2008 10,000 2,858 2,534 2,534 2,534 200,866 178,086 178,086 178,086 22,780 2009 9,943 2,858 2,534 2,534 2,534 199,713 177,064 177,064 177,064 22,649 2010 9,886 2,724 2,530 2,530 2,530 189,258 175,775 175,773 175,773 13,483 2011 9,829 2,628 2,527 2,527 2,527 181,561 174,572 174,568 174,568 6,989 2012 9,772 2,628 2,527 2,527 -- 180,519 173,570 173,566 168,683 6,949 2015 9,605 2,628 2,527 2,515 -- 177,429 170,599 169,830 160,886 6,830 2020 9,333 2,628 2,527 2,515 -- 172,394 165,758 165,012 155,190 6,636 2025 9,068 2,628 2,527 2,515 -- 167,503 161,055 160,330 149,494 6,448 2030 8,811 2,628 2,527 2,515 -- 162,751 156,486 155,781 143,852 6,265 

a NRLM refers to land-based diesel engines, locomotives, and recreational and commercial marine vessels.

NR refers to land-based diesel nonroad engines.LM refers to locomotives, recreational and commercial marine vessels.
Table 3.5-13b

Estimated National (50-State) SO2 Emissions and Reductions from Other Nonhighway Fue

Year

Volume

(106 gals)

Sulfur (ppm) SO2 Emissions (tons/year) Incremental 

Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012) Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012)

500 ppm

NRLM

Fuel

Program

50

N

Pr

an

onl

p

2

2000 10,819 2,859 2,859 2,859 2,859 217,431 217,431 217,431 217,431 0 2005 10,512 2,859 2,859 2,859 2,859 211,262 211,262 211,262 211,262 0 2007 10,392 2,846 2,666 2,666 2,666 207,911 194,712 194,712 194,712 13,199 2008 10,332 2,846 2,533 2,533 2,533 206,717 183,944 183,944 183,944 22,773 2009 10,273 2,846 2,533 2,533 2,533 205,531 182,889 182,889 182,889 22,642 2010 10,214 2,717 2,529 2,529 2,529 195,041 181,561 181,559 181,559 13,481 2011 10,155 2,624 2,526 2,526 2,526 187,310 180,321 180,317 180,317 6,989 2012 10,097 2,624 2,526 2,526 -- 186,235 179,286 179,282 174,399 6,949 2015 9,924 2,624 2,526 2,515 -- 183,047 176,217 175,448 166,504 6,830 2020 9,643 2,624 2,526 2,515 -- 177,853 171,217 170,471 160,649 6,636 2025 9,369 2,624 2,526 2,515 -- 172,807 166,359 165,634 154,798 6,448 2030 9,103 2,624 2,526 2,515 -- 167,904 161,639 160,934 149,006 6,265 

a NRLM refers to land-based diesel engines, locomotives, and recreational and commercial marine vessels.

NR refers to land-based diesel nonroad engines.LM refers to locomotives, recreational and commercial marine vessels.
Table 3.5-14a

Estimated National (48-State) Sulfate Emissions and Reductions from Other Nonhighway Fu

Year

Volume

(106 gals)

Sulfur (ppm) Sulfate Emissions (tons/year) Incremental S

Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012) Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012)

500 ppm

NRLM

Fuel

Program

50

N

Pr

an

onl

p

2

2000 10,471 2,871 2,871 2,871 2,871 7,470 7,470 7,470 7,470 0 2005 10,174 2,871 2,871 2,871 2,871 7,258 7,258 7,258 7,258 0 2007 10,058 2,858 2,671 2,671 2,671 7,142 6,675 6,675 6,675 467 2008 10,000 2,858 2,534 2,534 2,534 7,101 6,296 6,296 6,296 805 2009 9,943 2,858 2,534 2,534 2,534 7,061 6,260 6,260 6,260 801 2010 9,886 2,724 2,530 2,530 2,530 6,691 6,214 6,214 6,214 477 2011 9,829 2,628 2,527 2,527 2,527 6,419 6,172 6,172 6,172 247 2012 9,772 2,628 2,527 2,527 -- 6,382 6,136 6,136 5,964 246 2015 9,605 2,628 2,527 2,515 -- 6,273 6,031 6,004 5,688 241 2020 9,333 2,628 2,527 2,515 -- 6,095 5,860 5,834 5,487 235 2025 9,068 2,628 2,527 2,515 -- 5,922 5,694 5,668 5,285 228 2030 8,811 2,628 2,527 2,515 -- 5,754 5,532 5,507 5,086 221 

a NRLM refers to land-based diesel engines, locomotives, and recreational and commercial marine vessels.

NR refers to land-based diesel nonroad engines.LM refers to locomotives, recreational and commercial marine vessels.
Table 3.5-14b

Estimated National (50-State) Sulfate Emissions and Reductions from Other Nonhighway Fu

Year

Volume

(106 gals)

Sulfur (ppm) Sulfate Emissions (tons/year) Incremental S

Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012) Base

500 ppm

NRLM

Fuel

Program

(Control

to 500

ppm in

2007)

500 ppm

NRLM

Fuel

Program

and NR

only to 15

ppm in

2010

Full Fuel

Program

(NR

Control to

15 ppm in

2010; LM

in 2012)

500 ppm

NRLM

Fuel

Program

50

N

Pr

an

onl

p

2

2000 10,819 2,859 2,859 2,859 2,859 7,687 7,687 7,687 7,687 0 2005 10,512 2,859 2,859 2,859 2,859 7,469 7,469 7,469 7,469 0 2007 10,392 2,846 2,666 2,666 2,666 7,350 6,884 6,884 6,884 467 2008 10,332 2,846 2,533 2,533 2,533 7,308 6,503 6,503 6,503 805 2009 10,273 2,846 2,533 2,533 2,533 7,266 6,466 6,466 6,466 800 2010 10,214 2,717 2,529 2,529 2,529 6,895 6,419 6,419 6,419 477 2011 10,155 2,624 2,526 2,526 2,526 6,622 6,375 6,375 6,375 247 2012 10,097 2,624 2,526 2,526 -- 6,584 6,338 6,338 6,166 246 2015 9,924 2,624 2,526 2,515 -- 6,471 6,230 6,203 5,887 241 2020 9,643 2,624 2,526 2,515 -- 6,288 6,053 6,027 5,680 235 2025 9,369 2,624 2,526 2,515 -- 6,109 5,881 5,856 5,473 228 2030 9,103 2,624 2,526 2,515 -- 5,936 5,715 5,690 5,268 221 

a NRLM refers to land-based diesel engines, locomotives, and recreational and commercial marine vessels.

NR refers to land-based diesel nonroad engines.LM refers to locomotives, recreational and commercial marine vessels.
Emission Inventory

3-89

3.6 Emission Inventories Used for Air Quality Modeling

The emission inputs for the air quality modeling are required early in the analytical process to

conduct the air quality modeling and present the results. The air quality modeling was based on a

preliminary control scenario. Since the preliminary control scenario was developed, we have

gathered more information regarding the technical feasibility of the standards (see Section III of

the preamble for the final rule and Chapter 4 of the Final RIA). As a result, we have revised the

Tier 4 emission standards for land-based diesel engines. We have also made changes to the fuel

provisions of the rule for locomotives and diesel marine vessels. This section describes the

changes in the inputs and resulting emission inventories between the preliminary baseline and

control scenarios used for the air quality modeling and the updated baseline and control scenarios

in this final rule. This section will focus on the four nonroad diesel categories that are affected by

the new emission standards and/or the fuel sulfur requirements: land-based diesel engines,

recreational marine diesel engines, commercial marine diesel engines, and locomotives.

The methodology used to develop the emission inventories for the air quality modeling is first

briefly described, followed by comparisons of the preliminary and final baseline and control

inventories.

3.6.1 Methodology for Emission Inventory Preparation

Air quality modeling was performed for calendar years 1996, 2020, and 2030. For these

years, county-level emission estimates were developed by Pechan under contract to EPA. These

inventories account for county-level differences in fuel characteristics and temperature. The

NONROAD model was used to generate the county-level emission estimates for all nonroad

sources, with the exception of commercial marine engines, locomotives, and aircraft. The

methodology has been documented in detail.10

For the nonroad diesel categories affected by the final rule, the only fuel characteristic that

affects emissions is the fuel sulfur level. The specific pollutants affected by fuel sulfur level are

PM and SO2. To develop the county-level emission estimates for each baseline and control

inventory, one diesel fuel sulfur level was used to characterize all counties outside California. A

separate diesel fuel sulfur level was used to characterize all counties within California. Diesel

emissions as modeled are not affected by ambient temperature.

3.6.2 Baseline Inventories

Table 3.6-1 presents the preliminary 48-state baseline inventories used for the air quality

modeling. These are an aggregation of the county-level results. Results expressed as short tons

are presented for 1996, 2020, and 2030 for the land-based diesel, recreational marine diesel,

commercial marine diesel, and locomotive categories. The pollutants include PM2.5, NOx, SO2,

VOC, and CO. VOC includes both exhaust and crankcase emissions.
Final Regulatory Impact Analysis

3-90

Table 3.6-1

Modeled 48-State Baseline Emissions

Preliminary Baseline Used for Air Quality Modeling

Applications Year NOx

[short tons]

PM2.5

[short tons]

SO2

[short tons]

VOC

[short tons]

CO

[short tons]

Land-Based Diesel

Engines

1996 1,583,641 178,500 172,175 221,398 1,010,501

2020 1,144,686 127,755 308,075 97,113 702,145

2030 1,231,981 143,185 360,933 97,345 793,899

Recreational Marine

Diesel Engines

1996 19,438 511 2,535 803 3,215

2020 34,814 876 4,562 1,327 5,537

2030 41,246 1,021 5,418 1,528 6,464

Commercial Marine

Diesel Engines a

1996 960,153 37,203 37,252 31,613 126,523

2020 819,544 42,054 43,028 37,362 160,061

2030 815,162 46,185 48,308 41,433 176,708

Locomotives 1996 921,556 22,396 57,979 48,381 112,171

2020 612,722 17,683 62,843 36,546 119,302

2030 534,520 16,988 70,436 31,644 119,302

a

 Includes emissions from vessels using both diesel and residual fuel, with the exception of SO2. For the pollutants other

than SO2, it was not possible to separate emissions from diesel-fueled and residual-fueled vessels.

For the final baseline inventories, we have made minor changes to the diesel fuel sulfur levels. 

The diesel fuel sulfur inputs used for the preliminary and final baseline inventories are provided

in Table 3.6-2. The diesel fuel sulfur level for land-based diesel engines is now reduced from

2500ppm to roughly 2200ppm, beginning in 2006. Both the preliminary and final sulfur levels

account for spillover of highway fuel, but the preliminary sulfur levels did not properly account

for the 15ppm highway fuel sulfur content control phase-in beginning in 2006. The diesel fuel

sulfur levels for marine engines and locomotives are now higher prior to 2009 and lower

beginning in 2010.
Emission Inventory

3-91

Table 3.6-2

Modeled Baseline In-Use Diesel Fuel Sulfur Content

Final Baseline vs. Preliminary Baseline Used for Air Quality Modeling

Applications

Final Baseline Preliminary Baseline

Fuel Sulfur

ppm

Calendar Year Fuel Sulfur

ppm

Calendar Year

Land-Based Diesel Engines

2283 through 2005

2500a all years

2249 2006

2224 2007-2009

2167 2010

2126 2011+

Commercial and Recreational Marine

Engines and Locomotives

2637-2641 through 2005

2500a all years

2616 2006

2599 2007-2009

2444 2010

2334-2350 2011

a

 2500ppm is the 48-state average diesel fuel sulfur level, based on 2700ppm in 47 states and 120ppm in California.

For the nonroad land-based diesel category, the preliminary inventories were generated with

the draft NONROAD2002 model. For the final inventory, the draft NONROAD2004 model was

used. The changes from draft NONROAD2002 to draft NONROAD2004 are described in

Section 3.1.1.8. The net difference in land-based diesel emissions with the two model versions is

generally within 3 percent, with the direction and variation of the change dependent on the

calendar year and pollutant of interest. Apart from the model changes, the lower fuel sulfur levels

will serve to reduce the PM and SO2 baseline inventories in 2020 and 2030. Table 3.6-3

compares the preliminary and final 48-state baseline scenario inventories for land-based diesel

engines, as well as recreational marine diesel engines, commercial marine diesel engines, and

locomotives.

For recreational marine diesel engines, the preliminary inventories were generated with the

draft NONROAD2002 model. For the final inventory, the draft NONROAD2004 model was

used. The changes from draft NONROAD2002 to draft NONROAD2004 are more substantial for

this category. The recreational marine populations, median life, and deterioration factors for HC

and NOx were revised to match what was used in the 2002 final rulemaking that covers large

spark ignition engines (>25 hp), recreational equipment, and recreational marine diesel engines

(>50 hp). The exhaust emission factors for HC, NOx, and PM were also revised in draft

NONROAD2004 to reflect the final standards.
Final Regulatory Impact Analysis

3-92

For locomotives, there have been reductions to the fuel volume estimates used to calculate

emissions for this category. For the preliminary inventory development, railroad distillate values

were taken from the EIA Fuel and Kerosene Supply 2000 report. Fuel consumption specific to

locomotives was calculated by subtracting the rail maintenance fuel consumption as generated by

the draft NONROAD2002 model from the EIA railroad distillate estimates.

For the final inventory, the EIA railroad distillate estimates were taken from the EIA Fuel and

Kerosene Supply 2001 report. The estimates were first adjusted to estimate the fraction of

distillate that is diesel fuel. The diesel fraction used was 0.95 for railroad distillate. Fuel

consumption estimates from rail maintenance were then subtracted. The estimate of rail

maintenance fuel consumption was also revised by assuming these engines consume one percent

of the total railroad diesel fuel estimate, rather than using the estimate derived from draft

NONROAD2002. The revised estimate of rail maintenance fuel consumption is roughly half of

the NONROAD-derived estimate; however, the rail maintenance portion of the total railroad

diesel fuel consumption is small, so this change alone does not significantly affect the resulting

locomotive estimate. The derivation of diesel fractions and the revised estimate of rail

maintenance fuel consumption is documented in Chapter 7.

There have also been reductions to the fuel volumes assigned to commercial marine vessels. 

For the preliminary inventory development, vessel bunkering distillate values were taken from the

EIA Fuel and Kerosene Supply 2000 report. Fuel consumption specific to commercial marine

vessels was calculated by subtracting the recreational marine fuel consumption as generated by

the draft NONROAD2002 model from the EIA vessel bunkering estimates.

For the final inventory, the EIA vessel bunkering distillate estimates were taken from the EIA

Fuel and Kerosene Supply 2001 report. The vessel bunkering distillate estimates were first

adjusted to estimate the fraction of distillate that is diesel fuel. The diesel fraction used was 0.90

for vessel bunkering distillate. Fuel consumption estimates from recreational marine engines

were then subtracted. The estimate of recreational marine fuel consumption was that generated

by the draft NONROAD2004 model. These revised fuel volumes were used to generate SO2 and

sulfate PM estimates for commercial marine diesel engines in the final inventory. Emission

estimates for other pollutants emitted by commercial marine vessels were also revised in the final

inventory to reflect the January 2003 final rule for Category 3 commercial marine residual

engines.

As a result, differences in total emissions between the final and preliminary baseline scenarios

are generally within 10 percent. Exceptions include PM2.5 and SO2. Total PM2.5 emissions are

higher with the final baseline scenario, in part due to the upward revision of the PM2.5 fraction of

total PM.from 92 to 97 percent. Total SO2 emissions are lower, due to reductions in fuel volumes

for some categories and reductions in fuel sulfur levels.
Table 3.6-3

Modeled 48-State Emission Impact Due to Changes in Baseline

Applications Year

NOx [short tons] VOC Emissions [short tons] CO 

Final Preliminary Difference Final Preliminary Difference Final Prel

Land-BasedDiesel Engines

1996 1,564,904 1,583,641 -18,737

(-1.2%)

220,971 221,398 -427

(0.0%)

1,004,586 1,0

2020 1,119,481 1,144,686 -25,205

(-2.2%)

97,513 97,113 400

(0.4%)

697,630 70

2030 1,192,833 1,231,981 -39,148

(-3.2%)

96,374 97,345 -971

(1.0%)

786,181 79

RecreationalMarine DieselEngines

1996 33,679 19,438 14,241

(73.3%)

1,297 803 494

(61.5%)

5,424 3

2020 47,847 34,814 13,033

(37.4%)

1,604 1,327 277

(20.9%)

9,482 5

2030 52,085 41,246 10,839

(26.3%)

1,669 1,528 141

(9.2%)

11,232 6

CommercialMarine DieselEnginesa

1996 823,905 960,153 -136,248

(-14.2%)

28,986 31,613 -2,627

(-9.1%)

108,883 12

2020 943,560 819,544 124,016

(15.1%)

41,588 37,362 4,226

(11.3%)

150,562 16

2030 1,117,848 815,162 302,686

(37.1%)

52,880 41,433 11,447

(27.6%)

178,360 17

Locomotives 1996 934,070 921,556 12,514

(1.4%)

38,035 48,381 -10,346

(-21.4%)

92,496 11

2020 508,084 612,722 -104,638

(-17.1%)

30,125 36,546 -6,421

(-17.6%)

99,227 11

2030 481,077 534,520 -53,443

(-10.0%)

28,580 31,644 -3,064

(-9.7%)

107,780 11

Total 1996 3,356,558 3,484,788 -128,230

(-3.7%)

289,289 302,195 -12,906

(-4.3%)

1,211,389 1,2

2020 2,618,972 2,611,766 7,206

(0.3%)

170,830 172,348 -1,518

(0.9%)

956,901 98

2030 2,843,843 2,622,909 220,934

(8.4%)

179,503 171,950 7,553

(4.4%)

1,083,553 1,0

a To provide direct comparisons, for pollutants other than SO2, emissions include vessels using both diesel and residual fuels.
Final Regulatory Impact Analysis

3-94

Table 3.6-3 (cont.)

Modeled 48-State Emission Impact Due to Changes in Baseline

Applications Year

PM2.5 Emissions [short tons] SO2 [short tons]

Final Preliminary Difference Final Preliminary Difference

Land-Based

Diesel Engines

1996 186,507 178,500 8,007

(4.5%)

143,572 172,175 -28,603

(-16.6%)

2020 129,058 127,755 1,303

(1.0%)

237,044 308,075 -71,031

(-23.1%)

2030 142,484 143,185 -701

(-0.5%)

279,511 360,933 -81,422

(-22.6%)

Recreational

Marine Diesel

Engines

1996 923 511 412

(80.6%)

4,286 2,535 1,751

(69.1%)

2020 1,261 876 385

(43.9%)

6,850 4,562 2,288

(50.2%)

2030 1,371 1,021 350

(34.3%)

8,158 5,418 2,740

(50.6%)

Commercial

Marine Diesel

Engines a

1996 33,908 37,203 -3,295

(-8.9%)

30,136 37,252 -7,116

(-19.1%)

2020 52,197 42,054 10,143

(24.1%)

29,268 43,028 -13,760

(-32.0%)

2030 70,319 46,185 24,134

(52.3%)

33,020 48,308 -15,288

(-31.6%)

Locomotives 1996 22,266 22,396 -130

(-0.6%)

56,193 57,979 -1,786

(-3.1%)

2020 17,213 17,683 -470

(-2.7%)

53,352 62,843 -9,491

(-15.1%)

2030 16,025 16,988 -963

(-5.7%)

58,103 70,436 -12,333

(-17.5%)

Total 1996 243,604 238,610 4,994

(2.1%)

234,187 269,941 -35,754

(-13.2%)

2020 199,729 188,368 11,361

(6.0%)

326,514 418,508 -91,994

(-22.0%)

2030 230,199 207,379 22,820

(11.0%)

378,792 485,095 -106,303

(-21.9%)

a

 To provide direct comparisons, for pollutants other than SO2, emissions include vessels using both diesel and residual

fuels.
Emission Inventory

3-95

3.6.3 Control Inventories

Table 3.6-4 presents the preliminary 48-state control inventories used for the air quality

modeling. These are an aggregation of the county-level results. Results expressed as short tons

are presented for 2020 and 2030 for the land-based diesel, recreational marine diesel, commercial

marine diesel, and locomotive categories. Results are not presented for 1996, since controls will

affect only future-year emission estimates.

Table 3.6-4

Modeled 48-State Controlled Emissions

Preliminary Control Scenario Used for Air Quality Modeling

Applications Year NOx

[short tons]

PM2.5

[short tons]

SO2

[short tons]

VOC

[short tons]

CO

[short tons]

Land-Based Diesel

Engines

2020 481,068 36,477 1,040 73,941 249,734

2030 222,237 14,112 1,159 63,285 133,604

Recreational Marine

Diesel Engines

2020 34,814 552 20 1,327 5,537

2030 41,246 636 24 1,528 6,464

Commercial Marine

Diesel Engines

2020 819,544 38,882 184 37,362 160,061

2030 815,162 42,625 206 41,433 176,708

Locomotives 2020 612,722 13,051 272 36,546 119,302

2030 534,520 11,798 305 31,644 119,302

The certification standards used for the preliminary and final control scenarios are provided in

Tables 3.6-5 and 3.6-6, respectively. In general, the preliminary control scenario is more

stringent in terms of levels and effective model years for PM and NOx than the final control

scenario for all horsepower categories. The NMHC standard is 0.14 g/hp-hr with both scenarios

for <750 hp engines, although the phase-in of this standard is later in the final control scenario. 

The final control scenario also has a transitional NMHC standard of 0.30 g/hp-hr for engines over

750 hp. There are no Tier 4 CO standards in both control scenarios, although CO is assumed to

be reduced 90 percent in both scenarios with the advent of trap-equipped engines (corresponding

to the start of 0.02 or 0.01 g/hp-hr PM standards). As a result, the final standards will increase the

emissions of PM, NOx, NMHC, and CO in 2020 and 2030 relative to the preliminary standards.
Final Regulatory Impact Analysis

3-96

Table 3.6-5

Preliminary Tier 4 Emission Standards Used for Air Quality Modeling

Engine Power

Emission Standards 

g/hp-hr Model Year

transitional or

final

PM NOx NMHC CO

hp <25 transitional 0.01 5.6 a,b 6.0/4.9 b 2010

final 0.01 0.30 0.14 6.0/4.9 b 2012

25 # hp < 50 transitional 0.01 5.6 a,b 4.1 b 2010

final 0.01 0.30 0.14 4.1 b 2012

50 # hp < 100 transitional 0.01 3.5 a,b 3.7 b 2010

final 0.01 0.30 0.14 3.7 b 2012

100 # hp < 175 transitional 0.01 3.0 a,b 3.7 b 2010

final 0.01 0.30 0.14 3.7 b 2012

175 # hp < 750 transitional 0.01 3.0 a,b 2.6 b 2009

final 0.01 0.30 0.14 2.6 b 2011

hp $ 750 transitional 0.01 4.8 a,b 2.6 b 2009

final 0.01 0.30 0.14 2.6 b 2011

a

 This is a combined NMHC + NOx standard. b

 This emission standard is unchanged from the level that applies in the previous model year. For engines below 25 hp, the

CO standard is 6.0 g/hp-hr for engines below 11 hp and 4.9 g/hp-hr for engines at or above 11 hp. There are no Tier 4

CO standards.
Emission Inventory

3-97

Table 3.6-6

Tier 4 Emission Standards

Engine 

Power

Emission Standard

(g/hp-hr) Model 

Year(s)

transitional

or final

PM NOx

a NMHC a CO d

hp <25 final 0.30 5.6 b,c 6.0/4.9 c 2008

25 # hp < 75

transitional 0.22 5.6/3.5 b,c 4.1/3.7 c 2008-2012

final 0.02 3.5 b 4.1/3.7 c 2013

75 # hp < 175

transitional 0.01 0.30

(50%)

0.14

(50%)

3.7 c 2012-2013

final 0.01 0.30 0.14 3.7 c 2014

175 # hp < 750

transitional 0.01 0.30

(50%)

0.14

(50%)

2.6 c 2011-2013

final 0.01 0.30 0.14 2.6 c 2014

hp $ 750

except Generator sets

transitional 0.075 2.6 0.30 2.6 c 2011-2014

final 0.03 2.6 0.14 2.6 c 2015

Generator sets

750 # hp # 1200

transitional 0.075 2.6 0.30 2.6 c 2011-2014

final 0.02 0.50 0.14 2.6 c 2015

Generator sets

hp > 1200

transitional 0.075 0.50 0.30 2.6 c 2011-2014

final 0.02 0.50 0.14 2.6 c 2015

a

 Percentages are model year sales fractions required to comply with the indicated NOx and NMHC standards, for model

years where less than 100 percent is required. For a complete description of manufacturer options and alternative

standards, refer to Section II of the preamble.

b

 This is a combined NMHC + NOx standard. c

 This emission standard level is unchanged from the level that applies in the previous model year. For 25-75 hp engines,

the transitional NMHC + NOx standard is 5.6 g/hp-hr for engines below 50 hp and 3.5 g/hp-hr for engines at or above

50 hp. For engines under 75 hp, the CO standard is 6.0 g/hp-hr for engines below 11 hp, 4.9 g/hp-hr for engines 11 to

under 25 hp, 4.1 g/hp-hr for engines 25 to below 50 hp and 3.7 g/hp-hr for engines at or above 50 hp. d

 There are no Tier 4 CO standards. The CO emission standard level is unchanged from the level that applies in the

previous model year.
Final Regulatory Impact Analysis

3-98

The diesel fuel sulfur inputs used for the preliminary and final control scenarios are provided

in Tables 3.6-7 and 3.6-8, respectively. For land-based diesel engines, the modeled in-use diesel

fuel sulfur content is 11 ppm in 2020 and 2030 for both scenarios. For recreational marine

engines, commercial marine engines and locomotives, the modeled in-use diesel fuel sulfur

content is 11 ppm in 2020 and 2030 for the preliminary control scenario, but 55 ppm in 2020 and

2030 for the final control scenario. As a result, the fuel sulfur levels required by the final rule

will serve to increase the PM and SO2 control inventories for the recreational marine, commercial

marine, and locomotive categories in 2020 and 2030. This will be offset slightly by the reduced

fuel volumes assigned to the commercial marine and locomotive categories.

Table 3.6-7

Modeled 48-State In-Use Diesel Fuel Sulfur Content Used for Air Quality Modeling

Applications Standards

Modeled In-Use Fuel Sulfur

Content, ppm

Calendar 

Year

All Diesel Categories

Baseline + hwy 500 ppm

"spillover"

2500 through 2005

Baseline + hwy 15 ppm

"spillover"

2400 2006-2007

June intro of 15 ppm 1006 2008

Final 15 ppm standard 11 2009
Emission Inventory

3-99

Table 3.6-8

Modeled 48-State In-Use Diesel Fuel Sulfur Content

Applications Calendar Year(s)

Modeled In-Use Fuel Sulfur

Content, ppm

Land-based, 

all power ranges

through 2005 2283

2006 2249

2007 1140

2008-2009 348

2010 163

2011-2013 31

2014 19

2015+ 11

Recreational and

Commercial Marine Diesel

Engines and Locomotives

through 2000 2641

2001 2637

2002-2003 2638

2004-2005 2639

2006 2616

2007 1328

2008-2009 408

2010 307

2011 234

2012 123

2013 43

2014 51

2015-2017 56

2018-2038 56

2039-2040 55

To adjust PM emissions for these in-use fuel sulfur levels, the adjustment is made relative to

the certification diesel fuel sulfur levels in the model. The modeled certification diesel fuel sulfur

inputs used for the preliminary and final control scenarios are provided in Tables 3.6-9 and 3.6-
Final Regulatory Impact Analysis

3-100

10, respectively. For 2020 and 2030, the certification diesel fuel sulfur levels are the same for

both the preliminary and final control scenarios.

Table 3.6-11 compares the preliminary and final 48-state control scenario inventories for

land-based diesel engines, recreational marine diesel engines, commercial marine diesel engines,

and locomotives. Results are presented for PM2.5, NOx, SO2, VOC, and CO emissions.

For land-based diesel engines, emissions of PM2.5, NOx, VOC, and CO emissions are higher

for the final control scenario. This is due to the less stringent emission standards. There were no

differences in either the in-use or certification diesel fuel sulfur levels in 2020 and 2030 for this

category. The minor difference in SO2 emissions between the preliminary and final scenarios is

attributed to differences in the version of the NONROAD model used and aggregation of countylevel runs for the preliminary scenario compared with using one national level run for the final

control scenario.

The recreational marine, commercial marine, and locomotive categories are controlled in both 

scenarios; however, the in-use fuel sulfur level is 11 ppm for the preliminary control scenario and

56 ppm for the final control scenario. This directly affects the SO2 emissions. Accordingly, the

SO2 emissions for these categories are higher for the final control scenario.

For the recreational marine category, differences are also attributed to the version of the

NONROAD model used. For the commercial marine category, the final control scenario now

accounts for the latest rulemaking inventories, as well as updated fuel volumes. For locomotives,

the final control scenario incorporates updated fuel volume estimates.

Table 3.6-9

Modeled Certification Diesel Fuel Sulfur Content Used for Air Quality Modeling

Engine Power Standards Modeled Certification Fuel

Sulfur Content, PPM

Model 

Year

hp <50

Tier 2 2000 through 2009

Tier 4a 15 2010

50 # hp < 175

Tier 3 2000 through 2009

Tier 4a 15 2010

175 # hp < 750 

Tier 3 2000 through 2008

Tier 4a 15 2009

hp $ 750

Tier 2 2000 through 2008

Tier 4a 15 2009

a

 Tier 4 refers to both transitional and final standards.
Emission Inventory

3-101

Table 3.6-10

Modeled Certification Diesel Fuel Sulfur Content

Engine Power Standards

Modeled Certification Fuel

Sulfur Content, PPM

Model 

Year

hp <75

Tier 2 2000 through 2007

transitional 500 2008

final 15 2013

75 # hp < 100

Tier 3 transitionala 500 2008-2011

final 15 2012

100 # hp < 175

Tier 3 2000 2007-2011

final 15 2012

175 # hp < 750 

Tier 3 2000 2006-2010

final 15 2011

hp $ 750

Tier 2 2000 2006-2010

final 15 2011

a

 The emission standard here is still Tier 3 as in the Baseline case, but since the Tier 3 standard begins in 2008 for 50-

100 hp engines it is assumed that this new technology introduction will allow manufacturers to take advantage of the

availability of 500 ppm fuel that year.
Table 3.6-11

Modeled 48-State Emission Impact Due to Changes in Control Scenario

Applications Year NOx [short tons] PM2.5 [short tons] 

Final Preliminary Difference Final Preliminary Difference Final 

Land-Based DieselEngines

2020 677,420 481,068 196,352

(40.8%)

50,065 36,477 13,588

(37.3%)

986 

2030 458,649 222,237 236,412

(106%)

21,698 14,112 7,586

(53.8%)

1,074 

Recreational MarineDiesel Engines

2020 47,847 34,814 13,033

(37.4%)

738 552 186

(33.7%)

164 

2030 52,085 41,246 10,839

(26.3%)

749 636 113

(17.8%)

195 

Commercial MarineDiesel Engines a

2020 943,560 819,544 124,016

(15.1%)

49,968 38,882 11,086

(28.5%)

703 

2030 1,117,848 815,162 302686

(37.1%)

67,804 42,625 25,179

(59.1%)

786 

Locomotives 2020 508,084 612,722 -104,638

(-17.1%)

13,149 13,051 98

(0.8%)

1,282 

2030 481,077 534,520 -53,443

(-10.0%)

11,599 11,798 -199

(-1.7%)

1,384 

a To provide direct comparisons, for pollutants other than SO2, emissions include vessels using both diesel and residual fuels.
Emission Inventory

3-103

Table 3.6-11, continued

Applications Year VOC [short tons] CO [short tons]

Final Preliminary Difference Final Preliminary Difference

Land-Based Diesel

Engines

2020 79,372 73,941 5,431

(7.3%)

309,593 249,734 59,859

(24.0%)

2030 66,344 63,285 3,059

(4.8%)

167,014 133,604 33,410

(25.0%)

Recreational Marine

Diesel Engines

2020 1,604 1,327 277

(20.9%)

9,482 5,537 3,945

(71.2%)

2030 1,669 1,528 141

(9.2%)

11,232 6,464 4,768

(73.8%)

Commercial Marine

Diesel Engines a

2020 41,589 37,362 4,227

(11.3%)

150,562 160,061 -9,499

(-5.9%)

2030 52,880 41,433 11,447

(27.6%)

178,360 176,708 1,652

(0.9%)

Locomotives 2020 30,125 36,546 -6,421

(-17.6%)

99,227 119,302 -20,075

(-16.8%)

2030 28,580 31,644 -3,064

(-9.7%)

107,780 119,312 -11,532

(-9.7%)

a

 To provide direct comparisons, for pollutants other than SO2, emissions include vessels using both diesel and residual

fuels.
Final Regulatory Impact Analysis

3-104

1. U.S. Environmental Protection Agency. Exhaust and Crankcase Emission Factors for

Nonroad Engine Modeling: Compression Ignition. NR-009b. Assessment & Standards Division,

Office of Transportation & Air Quality. Ann Arbor, MI. November, 2002. (Docket A-2001-28,

Document II-A-29)

2. U.S. Environmental Protection Agency. Median Life, Annual Activity, and Load Factor

Values for Nonroad Engine Emissions Modeling. NR-005b. Assessment & Standards Division,

Office of Transportation & Air Quality. Ann Arbor, MI. May, 2002. (Docket A-2001-28,

Document II-A-30)

3. U.S. Environmental Protection Agency. Nonroad Engine Population Estimates. NR-006b.

Assessment & Standards Division, Office of Transportation & Air Quality. Ann Arbor, MI. July,

2002. (Docket A-2001-28, Document II-A-31)

4. U.S. Environmental Protection Agency. Nonroad Engine Growth Estimates. NR-008b.

Assessment & Standards Division, Office of Transportation & Air Quality. Ann Arbor, MI. May,

2002. (Docket A-2001-28, Document II-A-32)

5. U.S. Environmental Protection Agency. Calculation of Age Distributions in the Nonroad

Model: Growth and Scrappage. NR-007a Assessment & Standards Division, Office of

Transportation & Air Quality. Ann Arbor, MI. June, 2002. (Docket A-2001-28, Document II-A33)

6. U.S. Environmental Protection Agency. Conversion Factors for Hydrocarbon Emission

Components. NR-002. Assessment and Standards Division, Office of Transportation & Air

Quality. November, 2002. (Docket A-2001-28, Document II-A-34)

7. U.S. Environmental Protection Agency. Recommended revision of the fraction of diesel

particulate emissions mass less than 2.5 microns in size. Memo to the docket from Bruce

Cantrell. October 17, 2003. (Docket A-2001-28, Document IV-B-21)

8.U.S. Environmental Protection Agency. Control of Emissions From Nonroad Large SparkIgnition Engines, and Recreational Engines (Marine and Land-Based); Final Rule. 67 FR

68241-68290. November 8, 2002. (Docket Number A-2001-01, Document V-B-05)

9. U.S. Environmental Protection Agency. Documentation For Aircraft, Commercial Marine

Vessel, Locomotive, and Other Nonroad Components of the National Emissions Inventory,

Volume I - Methodology. Emission Factor and Inventory Group, Emissions Monitoring and

Analysis Division. November 11, 2002. 

(ftp://ftp.epa.gov/EmisInventory/draftnei99ver3/haps/documentation/nonroad/)

10. U.S. Environmental Protection Agency. Control of Emissions From Nonroad Large SparkIgnition Engines, and Recreational Engines (Marine and Land-Based); Final Rule. 67 FR

68241-68290. November 8, 2002. (Docket Number A-2001-01, Document V-B-05)

Chapter 3 References
Emission Inventory

3-105

11. E. H. Pechan & Associates, Inc. Procedures for Developing Base Year and Future Year

Mass Emission Inventories for the Nonroad Diesel Engine Rulemaking. Prepared for U.S.

Environmental Protection Agency, Office of Air Quality Planning and Standards. February,

2003.

12. U.S. Environmental Protection Agency. Control of Emissions of Air Pollution from 2004 and

Later Heavy-Duty Highway Engines and Vehicles. Office of Air and Radiation. July, 2000.

(Docket Number A-99-06, Document IV-A-01)

13. John E. Batey and Roger McDonald. Advantages of Low Sulfur Home Heating Oil. Interim

Report of Compiled Research, Studies, and Data Resources. National Oilheat Research Alliance

and U.S. Department of Energy. December, 2002. (E-Docket Number OAR-2003-0012-0933)
CHAPTER 4: Technologies and Test Procedures for Low-Emission Engines

4.1 Feasibility of Emission Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1.1 PM Control Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.1.1.1 In-Cylinder PM Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3

4.1.1.2 Diesel Oxidation Catalyst (DOC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5

4.1.1.3 Catalyzed Diesel Particulate Filter (CDPF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

4.1.2 NOx Control Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-19

4.1.2.1 In-Cylinder NOx Control Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-19

4.1.2.2 Lean-NOx Catalyst Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-20

4.1.2.3 NOx Adsorber Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-21

4.1.2.4 Selective Catalytic Reduction (SCR) Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-69

4.1.3 Can These Technologies Be Applied to Nonroad Engines and Equipment? . . . . . . . . . . . . . . . . . . . . . 4-70

4.1.3.1 Nonroad Operating Conditions and Exhaust Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-71

4.1.3.2 Durability and Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-80

4.1.4 Are the Standards for Engines >25 hp and <75 hp Feasible? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-82

4.1.4.1 What makes the 25 - 75 hp category unique? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-83

4.1.4.2 What engine technology is used currently, and will be used for Tier 2 and Tier 3, in the 25-75hp

range? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-85

4.1.4.3 Are the standards for 25 -75 hp engines technologically feasible? . . . . . . . . . . . . . . . . . . . . . . . 4-86

4.1.5 Are the Standards for Engines <25 hp Feasible? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-94

4.1.5.1 What makes the < 25 hp category unique? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-94

4.1.5.2 What engine technology is currently used in the <25 hp category? . . . . . . . . . . . . . . . . . . . . . . 4-95

4.1.5.3 What data support the feasibility of the new standards? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-95

4.1.6 Meeting the Crankcase Emission Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-101

4.1.7 Why Do We Need 15 ppm Sulfur Diesel Fuel? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-101

4.1.7.1 Catalyzed Diesel Particulate Filters and the Need for Low-Sulfur Fuel . . . . . . . . . . . . . . . . . . 4-102

4.1.7.2 Diesel NOx Catalysts and the Need for Low-Sulfur Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-108

4.2 Transient Emission Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-110

4.2.1 Background and Justification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-110

4.2.1.1 Microtrip-Based Duty Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-112

4.2.1.2 "Day-in-the-Life"-Based Duty Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-112

4.2.2 Data Collection and Cycle Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-113

4.2.2.1 Test Site Descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-113

4.2.2.2 Engine and Equipment Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-115

4.2.2.3 Data Collection Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-118

4.2.2.4 Cycle Creation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-119

4.2.3 Composite Cycle Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-126

4.2.4 Cycle Characterization Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-128

4.2.5 Cycle Normalization/Denormalization Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-129

4.2.6 Cycle Performance Regression Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-130

4.2.7 Constant-Speed, Variable-Load Equipment Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-130

4.2.7.1. Background on Cycle Considered . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-131

4.2.7.2. Follow-on Constant-Speed Engine Testing and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-132

4.2.8 Cycle Harmonization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-134

4.2.8.1 Technical Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-134

4.2.8.2 Global Harmonization Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-136

4.2.9 Cold-Start Transient Test Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-144

4.2.10 Applicability of Component Cycles to Nonroad Diesel Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-146

4.2.10.1 Market Representation of Component Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-147

4.2.10.2 Inventory Impact of Equipment Component Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-147

4.2.10.3 Power and Sales Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-148

4.2.10.4 Broad Application Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-148

4.2.11 Final Certification Cycle Selection Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-149

4.3 Steady-State Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-150

4.3.1 Ramped Modal Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-151

4.3.1.1 Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-151

4.3.1.2 Comparison of Steady-State vs. RMC Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-154

4.3.2 Transportation Refrigeration Unit Test Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-164

4.4 Not-to-Exceed Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-167
Technologies and Test Procedures for Low-Emission Engines

4-1

CHAPTER 4: Technologies and Test Procedures for LowEmission Engines

The new emission standards will require both new engine technologies and new

measurement procedures. Section 4.1 documents the technical analysis supporting the feasibility

of meeting the Tier 4 emission standards for nonroad diesel engines, including the not-to-exceed

standards. Section 4.2 describes the development and characteristics of the new transient duty

cycles and Section 4.3 describes issues related to steady-state duty cycles, including the

development of new ramped-modal duty cycles and new cycles for transportation refrigeration

units.

4.1 Feasibility of Emission Standards

A description of the new emission standards and our reasons for setting those standards can

be found in Section II of the preamble to the final rule. This chapter documents the analysis we

completed to inform the decisions described in the preamble regarding new emission standards

for nonroad diesel engines. This analysis incorporates recent Agency analyses of emissioncontrol technologies for highway diesel engines and expands those analyses with more recent

data and additional analysis specific to the application of technology to nonroad diesel

engines.1,2,3

This section is organized into subsections describing diesel emission-control technologies,

issues specific to the application of these technologies to new nonroad engines, specific analyses

for engines within distinct power categories (<25 hp and 25-75 hp) and an analysis of the need

for low-sulfur diesel fuel (15 ppm sulfur) to enable these emission-control technologies. 

For the past 30 or more years, emission-control development for gasoline vehicles and

engines has concentrated most aggressively on exhaust emission-control devices. These devices

currently provide as much as or more than 95 percent of the emission control on a gasoline

vehicle. In contrast, the emission-control development work for highway and nonroad diesel

engines has concentrated on improvements to the engine itself to limit the emissions leaving the

combustion chamber. 

During the past 15 years, however, more development effort has been put into catalytic 

exhaust emission-control devices for diesel engines, particularly in the area of particulate matter

(PM) control. Those developments, and recent developments in diesel NOx exhaust emissioncontrol devices, make the widespread commercial use of diesel exhaust emission controls

feasible. EPA has recently set new emission standards for diesel engines installed in highway

vehicles based on the emission-reduction potential of these devices. We believe these devices

will make possible a level of emission control for nonroad diesel engines that is similar to that
Regulatory Impact Analysis

4-2

attained by gasoline three-way-catalyst applications. However, without low-sulfur diesel fuel,

these technologies cannot be implemented. 

Although the primary focus of the Tier 4 emissions program and the majority of the analysis

contained in this RIA is directed at the application of catalytic emission control technologies

enabled by 15 ppm sulfur diesel fuel, there are also important elements of the program based

upon continuing improvements in engine-out emission controls. Like the advanced catalytic

based technologies, these engine-out emission solutions for nonroad diesel engines rely upon

technologies already applied to on-highway diesel engines. Additionally, these technologies

form the basis for the Tier 3 emission standards for some nonroad diesel engines in other size

categories. Extensive analysis and discussion of these engine-out emission control technologies

can be found in the RIAs associated with the On-Highway Heavy-Duty 2004 emission standards

and the Nonroad Tier 2 and Tier 3 emission standards.4,5,6,7 Those detailed analyses are not

repeated here but are a fundamental underpinning of EPA’s understanding of engine-out

emission controls for diesel engines and the feasibility of applying those controls to nonroad

diesel engines in the Tier 4 timeframe.

4.1.1 PM Control Technologies

Particulate matter from diesel engines is made of four components;

- solid carbon soot,

- volatile and semi-volatile organic matter

- inorganic solids (ash) , and

- sulfate.

The formation of the solid carbon soot portion of PM is inherent in diesel engines due to the

heterogenous distribution of fuel and air in a diesel combustion system. Diesel combustion is

designed to allow for overall lean (excess oxygen) combustion giving good efficiencies and low

CO and HC emissions with a small region of rich (excess fuel) combustion within the fuelinjection plume. It is within this excess fuel region of the combustion that PM is formed when

high temperatures and a lack of oxygen cause the fuel to pyrolize, forming soot. Much of the

soot formed in the engine is burned during the combustion process as the soot is mixed with

oxygen in the cylinder at high temperatures. Any soot that is not fully burned before the exhaust

valve is opened will be emitted from the engine as diesel PM. 

The volatile and semi-volatile organic material in diesel PM is often simply referred to as the

soluble organic fraction (SOF) in reference to a test method used to measure its level. SOF is

primarily composed of engine oil that passes through the engine with no oxidation or only partial

oxidation and condenses in the atmosphere to form PM. The SOF portion of diesel PM can be

reduced through reductions in engine oil consumption and through oxidation of the SOF

catalytically in the exhaust.

The inorganic solids (ash) in diesel PM comes primarily from metals found in engine oil and

to certain extent from engine wear. Ash makes up a very small portion of total PM such that it is

often not listed as a PM component and has no impact on compliance with PM emission
Technologies and Test Procedures for Low-Emission Engines

4-3

standards. However, it does impact maintenance of PM filter technologies, as discussed later,

because in aggregate over a very long period of time ash accumulation in the PM filter can reach

a level such that it must be cleaned from the filter (see section 4.1.1.3.4 below).

The sulfate portion of diesel PM is formed from sulfur present in diesel fuel and engine

lubricating oil that oxidizes to form sulfuric acid (H2SO4) and then condenses in the atmosphere

to form sulfate PM. Approximately two percent of the sulfur that enters a diesel engine from the

fuel is emitted directly from the engine as sulfate PM.8 The balance of the sulfur content is

emitted from the engine as SO2. Oxidation catalyst technologies applied to control the SOF and

soot portions of diesel PM can inadvertently oxidize SO2 in the exhaust to form sulfate PM. The

oxidation of SO2 by oxidation catalysts to form sulfate PM is often called sulfate make. Without

low-sulfur diesel fuel, oxidation catalyst technology to control diesel PM is limited by the

formation of sulfate PM in the exhaust as discussed in more detail in the discussion below of the

need for low-sulfur fuel.

4.1.1.1 In-Cylinder PM Control

The soot portion of PM emissions can be reduced by increasing the availability of oxygen

within the cylinder for soot oxidation during combustion. Oxygen can be made more available

by either increasing the oxygen content in-cylinder or by increasing the mixing of the fuel and

oxygen in-cylinder. Several current technologies can influence oxygen content and in-cylinder

mixing, including improved fuel-injection systems, air management systems, and combustion

system designs. Many of these PM-reducing technologies offer better control of combustion in

general, and better utilization of fuel allowing for improvements in fuel efficiency concurrent

with reductions in PM emissions. Improvements in combustion technologies and refinements of

these systems is an ongoing effort for highway engines and for some nonroad engines where

emission standards or high fuel use encourage their introduction. The application of better

combustion system technologies across the broad range of nonroad engines for meeting the new

emission standards offers an opportunity for significant reductions in engine-out PM emissions

and possibly for reductions in fuel consumption.

In general, the application of these in-cylinder emission control solutions for PM are more

successful (reduce PM to a lower level) as engine size increases. This occurs for three reasons:

1) larger engines have a higher volume to surface area within the cylinder reducing the

proportion of the in-cylinder volume near a cooler cylinder wall and thus decreasing PM

formation in these cool regions; 2) larger engines operate over a narrow engine speed range

allowing for better matching of turbomachinery to the engine (i.e., higher boost and more

oxygen); and 3) larger engines operate at lower engine speeds reducing oil consumption which

contributes to SOF and providing longer residence time for combustion to complete (i.e., at

slower speeds the combustion event measured in time is longer). In the Tier 4 program, we are

setting an emission standard of 0.075 g/bhp-hr for some nonroad diesel engines >750 hp

beginning in 2011. This emission level is approximately 25 percent lower than the level for
Regulatory Impact Analysis

A On-highway diesel engines used in urban buses must meet an even lower PM standard of 0.05 g/bhp-hr.

4-4

most current on-highway diesel engines (using 500 ppm sulfur fuel).A We are projecting that incylinder PM emission control technologies along with 15 ppm sulfur diesel fuel will allow these

very large nonroad diesel engines to meet this emission standard. Given the inherent PM control

advantage that these larger diesel engines enjoy when compared to the smaller on-highway

counterparts and the use of lower sulfur diesel fuel which lowers sulfate PM, we can conclude

that the 0.075 g/bhp-hr emission standard is clearly feasible for these engines in 2011.

Another means to reduce the soot portion of engine-out PM emissions from diesel

(compression-ignited) engines is to operate the engine with a homogenous method of operation,

rather than the typical heterogeneous operation. In homogenous diesel combustion, also called

premixed diesel combustion, the fuel is dispersed evenly with the air throughout the combustion

system. This means there are no fuel-rich/oxygen-deprived regions of the system where fuel can

be pyrolized rather than burned. Rather, combustion occurs globally initiating at an

indeterminate number of locations. Because there are no fuel-rich/oxygen deprived regions in

homogenous combustion, the carbon (soot) PM emissions are eliminated. The resulting PM

emissions are very low, consisting primarily of SOF and sulfate.

Homogenous diesel combustion has been under development for more than twenty years, yet

it is still unable to overcome a number of developmental issues.9,10 Fundamental among these

issues is the ability to control the start of combustion.11 Conventional diesel engines control the

start of combustion by controlling the start of fuel injection: injection-timing control. 

Homogenous diesel combustion systems cannot readily use fuel-injection timing to control the

start of combustion because it is difficult to inject fuel into the engine without initiating

combustion. If combustion is initiated while the fuel is being injected, the engine will operate

under heterogenous combustion resulting in high PM emissions. Techniques used to delay the

start of combustion such as decreasing intake air temperatures or reducing the engines

compression ratio can lead to misfire, a failure to ignited the fuel at all. Engine misfire results in

no engine power and high hydrocarbon (raw fuel) emissions. Conversely, techniques to advance

the start of combustion such as increasing intake air temperatures or increasing the engine

compression ratio can lead to premature uncontrolled combustion called engine knock. Engine

knock causes exceedingly high in-cylinder pressure spikes that can irreversibly damage a diesel

engine at all but low-load conditions.

Controlled homogenous combustion is possible with a diesel engine under certain

circumstances, and is used in limited portions of engine operation by some engine

manufacturers. Nissan, a passenger car manufacturer, has developed a modified version of

premixed combustion that they call modulated-kinetics, or MK, combustion.12,13 When operated

under MK combustion the PM and NOx emissions of the engine are dramatically decreased. 

Unfortunately, the range of engine operation for which the MK combustion process can function

is limited to low-load conditions. At higher engine loads the combustion process is not stable

and the engine reverts to operation with conventional diesel combustion. This dual mode

operation allows the engine to benefit from the homogenous combustion approach when
Technologies and Test Procedures for Low-Emission Engines

4-5

possible, while still providing the full range of engine operation. Other approaches that are

similarly limited to low-load engine operation have been proposed to produce a dual combustion

mode engine.14, 15, 16

4.1.1.2 Diesel Oxidation Catalyst (DOC)

Diesel oxidation catalyst (DOCs) are the most common form of diesel aftertreatment

technology today and have been used for compliance with the PM standards for some highway

engines since the early 1990s. DOCs reduce diesel PM by oxidizing a small fraction of the soot

emissions and a significant portion of the SOF emissions. Total DOC effectiveness to reduce

PM emissions is normally limited to approximately 30 percent because the SOF portion of diesel

PM for modern diesel engines is typically less than 30 percent and because the DOC increases

sulfate emissions, reducing the overall effectiveness of the catalyst. Limiting fuel sulfur levels to

15ppm allows DOCs to be designed for maximum effectiveness (nearly 100% control of SOF

with highly active catalyst technologies) since their control effectiveness is not reduced by

sulfate make (i.e., their sulfate make rate is high but because the sulfur level in the fuel is low the

resulting PM emissions are well controlled). 

DOC effectiveness to control HC and CO emissions are directly related to the “activity” of

the catalyst material used in DOC washcoating. Highly active (hence effective) DOCs can

reduce HC emissions by 97 percent while low activity catalysts realize approximately 50 percent

HC control.17 Today, highly active DOC formulations cannot be used for NMHC and CO

control because the sulfur in current diesel fuel leads to unacceptable sulfate PM emissions, as

discussed later in this section. However, with the low sulfur diesel fuel that will be available

under this program, DOCs will be able to provide substantial control of these pollutants. We

have projected the use of DOCs as part of an overall compliance strategy for engines meeting the

interim PM standards in 2008. For those engines, DOC would also provide significant

reductions in CO and HC including over the various emission test cycles for these engines. 

Oxidation catalyst technologies generally (i.e., DOCs and CDPFs) will be an effective tool to

ensuring compliance over the NTE provisions of the Tier 4 program and to ensuring compliance

with the CO standards under the new test cycles.

Data presented by one engine manufacturer regarding the existing Tier 2 PM standard show

that while a DOC can be used to reduce PM emissions when tested on 2,000 ppm sulfur fuel,

lowering the fuel sulfur level to 380 ppm enabled the DOC to reduce PM by 50 percent from the

2,000 ppm sulfur fuel.18 Without the availability of 500 ppm sulfur fuel in 2008, DOCs would be

of limited use for nonroad engine manufacturers and would not provide the emission-control

necessary for most engine manufacturers to meet the 2008 interim Tier 4 standards. With the

availability of 500 ppm sulfur fuel, DOCs can be designed to provide PM reductions on the order

of 20 to 50%, while suppressing particulate sulfate reduction.19 These levels of reductions have

been seen on transient duty cycles as well as on highway and nonroad steady-state duty cycles.

DOCs are also very effective at reducing the air toxic emissions from diesel engines. Test

data show that emissions of toxics such as polycyclic aromatic hydrocarbons (PAHs) can be

reduced by more than 80 percent with a DOC.20
Regulatory Impact Analysis

B

 There are a number of different ways to measure mechanical strength and toughness. One metric for

comparison is tensile strength. Comparing the tensile strength of fiber based filter technologies (approximately

1,000 MPa) to a ceramic filter technology such as Silicon Nitride (5.1 MPa) is illustrative of the higher strength of

the fiber based technology.

4-6

DOCs are less effective at controlling the solid carbon soot portion of PM. The solid (soot)

typically constitutes 60 to 90 percent of the total diesel PM. Even with 15 ppm sulfur fuel,

DOCs would therefore not be able to achieve the level of PM control needed to meet the PM

filter based PM emission standards (i.e., PM standards at or below 0.03 g/bhp-hr). As noted

above however, DOCs can be effective tools to accomplish emission reductions on the order of

20 to 50 percent even when operated on 500 ppm sulfur diesel fuel and thus may be used by

some manufacturers as a means to reduce emissions in order to comply with the 2008 interim

Tier 4 standards for engines <75 hp.

4.1.1.3 Catalyzed Diesel Particulate Filter (CDPF)

4.1.1.3.1 CDPF PM and HC Control Effectiveness

Emission levels from a catalyzed diesel particulate filter (CDPF) are determined by several

factors. Filtering efficiencies for solid particle emissions like soot are determined by the

characteristics of the PM filter, including wall thickness and pore size. Some of these

characteristics represent a tradeoff between mechanical strength, weight, size and filtering

efficiency. Filtering efficiencies for ceramic based diesel soot filters can be as high as 99

percent with the appropriate filter design.21 Given an appropriate PM filter design, the

contribution of the soot portion of PM to the total PM emissions can be negligible (less than

0.001 g/hp-hr). For some wire mesh or ceramic fiber filter technologies the filtering efficiency is

lower, around 70 percent, but the mechanical strength (resistance to thermal and mechanical

stress) especially for very large filter sizes is improved.B,22,23 The level of soot emission control

is much less dependent on engine test cycle or operating conditions due to the mechanical

filtration characteristics of the particulate filter. 

Control of the SOF portion of diesel soot is accomplished on a CDPF through catalytic

oxidation. At the elevated temperature of diesel exhaust, the SOF portion of diesel PM consists

primarily of gas-phase hydrocarbons which later form particulate matter in the environment

when the SOF condenses. Catalytic materials applied to CDPFs can oxidize a substantial

fraction of the SOF in diesel PM just as the SOF portion is oxidized by a DOC. However, we

believe that for engines with very high SOF emissions the emission rate may be higher than can

be handled by a conventionally sized catalyst resulting in higher than zero SOF emissions. If a

manufacturer’s base engine technology has high oil consumption rates, and therefore high

engine-out SOF emissions (i.e., higher than 0.04 g/hp-hr), compliance with the 0.01 g/hp-hr
Technologies and Test Procedures for Low-Emission Engines

C

 SOF oxidation efficiency is typically better than 80 percent and can be better than 90 percent. Given a base

engine SOF rate of 0.04 g/hp-hr and an 80 percent SOF reduction a tailpipe emission of 0.008 can be estimated from

SOF alone. This level may be too high to comply with a 0.01 g/hp-hr standard once the other constituents of diesel

PM (soot and sulfate) are added. In this case, engine-out SOF emissions will need to be reduced or the CDPF will

need to reduce SOF emissions by more than 90 percent.

4-7

emission standard may require additional technology beyond the application of a CDPF system

alone.C 

Modern highway diesel engines have controlled SOF emission rates to comply with the

existing 0.1 g/hp-hr emission standards. Typically the SOF portion of PM from a modern

highway diesel engine contributes less than 0.02 g/hp-hr to the total PM emissions. This level of

SOF control is accomplished by controlling oil consumption through the use of engine

modifications (e.g., piston ring design, the use of 4-valve heads, the use of valve stem seals,

etc.).24 Nonroad diesel engines may similarly need to control engine-out SOF emissions to

comply with the new emission standards. The means to control engine-out SOF emissions are

well known and have additional benefits, as they decrease oil consumption reducing operating

costs. With good control of engine-out SOF emissions (i.e., engine-out SOF < 0.02 g/hp-hr) and

the application of catalytic material to the DPF, SOF emissions from CDPF equipped nonroad

engines will contribute only a very small fraction of the total tailpipe PM emissions (less than

0.004 g/hp-hr). Alternatively, it may be less expensive or more practical for some applications

to ensure that the SOF control realized by the CDPF is in excess of 90 percent, thereby allowing

for higher engine-out SOF emission levels.

The catalytic materials used on a CDPF to promote soot regeneration and to control SOF

emissions are also effective to control NMHC emissions including toxic hydrocarbon emissions. 

CDPFs designed for operation on low-sulfur diesel fuel (i.e., with highly active catalyst

technologies) can reduce total hydrocarbon emissions by more than 90 percent.25 Toxic

hydrocarbon emissions are typically reduced in proportion to total hydrocarbon emissions. 

Table 4.1-1 shows hydrocarbon compound reduction data for two different CDPF technologies.26
Regulatory Impact Analysis

4-8

Compound Baseline DPF-A DPF-B %Red DPF-A %Red DPF-B

Napthalene 295 50 0 83% 100%

2-Methylnapthalene 635 108 68 83% 89%

Acenapthalene 40 0.8 1 98% 98%

Acenapthene 46 6.7 11 85% 76%

Fluorene 72 29 12 60% 83%

Phenanthrene 169 33 26 81% 85%

Anthracene 10 1 1 90% 90%

Fluoranthene 7.7 0 2 100% 74%

Pyrene 14 0 2 100% 86%

Benzo(a)anthracene 0.22 0 0.01 100% 95%

Chrysene 0.51 0 0 100% 100%

Benzo(b)fluoranthene 0.26 0 0 100% 100%

Benzo(k)fluoranthene 0.15 0 0 100% 100%

Benzo(e)pyrene 0.26 0 0 100% 100%

Perylene 0.01 0 0 100% 100%

Indeno(123-cd)pyrene 0.13 0 0 100% 100%

Dibenz(ah)anthracene 0.01 0 0 100% 100%

Benzo(ghi)perylene 0.32 0 0 100% 100%

Polyaromatic Hydrocarbon Reductions with Catalyzed Diesel Particulate Filters

Table 4.1-1 Polyaromatic Hydrocarbon Reductions with a CDPF

The best means to reduce sulfate emissions from diesel engines is by reducing the sulfur

content of diesel fuel and lubricating oils. This is one of the reasons that we are limiting sulfur

levels in nonroad diesel fuel to 15ppm or less. The catalytic material on the CDPF is crucial to

ensuring robust regeneration and high SOF oxidation; however, it can also oxidize the sulfate in

the exhaust with high efficiency. The result is that the predominant form of PM emissions from

CDPF equipped diesel engines is sulfate PM. Even with 15ppm sulfur diesel fuel a CDPF

equipped diesel engine can have total PM emissions including sulfate emissions as high as 0.009

g/hp-hr over some representative operating cycles using conventional diesel engine oils. This

level of emissions will meet the new PM emission standard of 0.01 g/hp-hr for engines between

75 hp and 750 hp. We further believe there is room for reductions from this level to provide

engine manufacturers with additional compliance margin. Our recently released Highway Diesel

Progress Review Report 2 documents progress by a consortium of engine manufacturers, oil

companies and other stakeholders to develop a new engine oil formulation with reduced Sulfur,

Ash, and Phosphorous (SAP) content for diesel engines. The new engine oil formulation is

expected to be ready in 2006. Any reduction in the sulfur level of engine lubricating oils will be

beneficial. Similarly, as discussed above, we expect engine manufacturers to reduce engine oil

consumption to reduce SOF emissions and secondarily to reduce sulfate PM emissions. While

we believe sulfate PM emissions will be the single largest source of the total PM from diesel

engines, we believe that with the combination of technology, and the appropriate control of

engine-out PM emissions, sulfate and total PM emissions will be low enough to allow
Technologies and Test Procedures for Low-Emission Engines

D We have also set slightly higher PM standards for >750 hp engines predicated on the use of alternative PM

filter technologies. These higher levels (standards of 0.02 g/bhp-hr for gensets, and 0.03 g/bhp-hr for mobile

machines) are not based on higher sulfate emission rates, as for the <75 hp engines, but instead on slightly less

effective PM filtration efficiencies and differing engine out emission rates.

4-9

compliance with a 0.01 g/hp-hr standard, except in the case of small engines with higher fuel

consumption rates, as described later in this section.D

CDPFs have been shown to be very effective at reducing PM mass by reducing dramatically

the soot and SOF portions of diesel PM. In addition, recent data show that they are also very

effective at reducing the overall number of emitted particles when operated on low-sulfur fuel. 

Hawker, et al, found that a CDPF reduced particle count by over 95 percent, including some of

the smallest measurable particles (< 50 nm), at most of the tested conditions. The lowest

observed efficiency in reducing particle number was 86 percent. No generation of particles by

the CDPF was observed under any tested conditions.27 Kittelson, et al, confirmed that ultrafine

particles can be reduced by a factor of ten by oxidizing volatile organics, and by an additional

factor of ten by reducing sulfur in the fuel. Catalyzed PM traps efficiently oxidize nearly all of

the volatile organic PM precursors (SOF), and the reduction of diesel fuel sulfur levels to 15ppm

or less will substantially reduce the number of ultrafine PM emitted from diesel engines. The

combination of CDPFs with low-sulfur fuel is expected to result in very large reductions in both

PM mass and the number of ultrafine particles.

Engine operating conditions have little impact on the particulate trapping efficiency of

carbon particles by CDPFs, so the greater than 90 percent efficiency for elemental carbon

particulate matter will apply to engine operation within the NTE zone and over the regulated

transient cycles, as well as to the test modes that comprise the steady-state test procedures such

as the ISO C1. However, engine operation will affect the CDPF regeneration and oxidation of

SO2 to sulfate PM (i.e., “sulfate-make”). Sulfate-make will reduce the measured PM removal

efficiency at some NTE operating conditions and some steady-state modes, even at the 15 ppm

fuel sulfur cap. This increased sensitivity to fuel sulfur is caused by the higher temperatures that

are found at some of the steady-state modes. High exhaust temperatures promote the oxidation

of SO2 to SO3 (which then combines with water in the exhaust, forming a hydrated sulfate)

across the precious metals found in CDPFs. The sulfate emissions condense in the atmosphere

(as well as in the CFR mandated dilution tunnel used for PM testing) forming PM.

Under contract from the California Air Resources Board, two nonroad diesel engines were

recently tested for control of PM emissions with the application of a CDPF over several transient

and steady-state test cycles.28 The first engine was a 1999 Caterpillar 3408 (480 hp, 18 liter

displacement) nonroad diesel engine certified to the Tier 1 standards. The engine was tested

with and without a CDPF on 12 ppm sulfur diesel fuel. The transient emission results for this

engine are summarized in Table 4.1-2. The steady-state emission results are summarized in

Table 4.1-3. The test results confirm the excellent PM control performance realized by a CDPF

with low-sulfur diesel fuel across a wide range of nonroad operating cycles in spite of the

relatively high engine-out PM emissions from this Tier 1 engine. We expect engine-out PM

emissions to be lower for production engines meeting Tier 3 standards, which will form the
Regulatory Impact Analysis

4-10

technology baseline for the Tier 4 engines. The engine demonstrated PM emissions of 0.009

g/hp-hr on the Nonroad Transient Cycle (NRTC) from an engine-out emission level of 0.256

g/hp-hr, a reduction of 0.247 g/hp-hr (a greater than 96% reduction). The engine also

demonstrated excellent PM performance on the existing steady-state ISO C1 cycle with PM

emissions of 0.010 g/hp-hr from an engine-out emission level of 0.127, a reduction of 0.107

g/hp-hr. Thus, this engine would meet the new emission standards for 75-750 hp variable-speed

nonroad engines.

Reduction

Test Cycle Engine Out w/ CDPF %

Proposed Nonroad TransientCycle (NRTC) 0.256 0.009 96%

Proposed Constant Speed Variable Load Cycle (CSVL) 0.407 0.016 96%

On-Highway U.S. FTP Transient Cycle (FTP) 0.239 0.019 92%

Agricultural Tractor Cycle (AGT) 0.181 0.009 95%

Backhoe Loader Cycle (BHL) 0.372 0.022 94%

Crawler Tractor Dozer Cycle (CRT) 0.160 0.014 91%

Composite Excavator Duty Cycle (CEX) 0.079 0.009 88%

Skid Steer Loader Typical No. 1 (SST) 0.307 0.016 95%

Skid Steer Loader Typical No. 2 (SS2) 0.242 0.013 95%

Skid Steer Loader Highly Transient Speed (SSS) 0.242 0.008 97%

Skid Steer Loader Highly Transient Torque (SSQ) 0.351 0.004 99%

Arc Welder Typical No.1 (AWT) 0.510 0.018 96%

Arc Welder Typical No.2 (AW2) 0.589 0.031 95%

Arc Welder Highly Transient Speed (AWS) 0.424 0.019 96%

Rubber-Tired Loader Typical No.1 (RTL) 0.233 0.010 96%

Rubber-Tired Loader Typical No.2 (RT2) 0.236 0.011 96%

Rubber-Tired Loader Highly Transient Speed (RTS) 0.255 0.008 97%

Rubber-Tired Loader Highly Transient Torque (RTQ) 0.294 0.009 97%

PM [g/bhp-hr]

1999 (Tier 1) Caterpillar 3408 (480hp, 18l)

Table 4.1-2 Transient PM Emissions for a Tier 1 NR Diesel Engine with a CDPF

Table 4.1-2 also shows results over a large number of additional test cycles developed from

real-world in-use test data to represent typical operating cycles for different nonroad equipment

applications (see Section 4.2 for information on these test cycles). The results show that the

CDPF technology is highly effective to control in-use PM emissions over any number of

disparate operating conditions. Remembering that the base Tier 1 engine was not designed to

meet a transient PM standard, the CDPF emissions demonstrated here show that very low

emission levels are possible even when engine-out emissions are exceedingly high (e.g., a

reduction of 0.558 g/hp-hr is demonstrated on the AW2 cycle).

The results summarized in the two tables support the feasibility of the NTE provisions in this

rulemaking. In spite of the Tier 1 baseline of this engine, there are only three test results with

emissions higher than the permissible limit for the NTE standards. The first, in Table 4.1-2,

shows PM emissions of 0.031 over the AW2 cycle, but from a very high baseline level of nearly

0.6 g/hp-hr. We believe that simple improvements to the engine-out PM emissions as needed to

comply with the Tier 2 emission standard would reduce these emission below the 0.02 level

required by the NTE standard. There are two other test points in Table 4.1-3 that are above the
Technologies and Test Procedures for Low-Emission Engines

E

 The rounding procedures in ASTM E29-90 are applied to the emission standard. The emission results are

therefore rounded to the same number of significant digits as the specified standard, i.e., 0.014 g/hp-hr is rounded to

0.01 g/hp-hr, while 0.015 g/hp-hr would be rounded to 0.02 g/hp-hr.

4-11

NTE standard, both at 10 percent engine load. However, both test points are outside the NTE

zone, which excludes emissions for engine loads below 30 percent. It is important to note that,

although the engine would not be constrained to meet NTE standards under these conditions, the

resulting reductions at both points are still substantially greater than 96 percent.

Engine Speed Engine Load Reduction

% % Engine Out w/ CDPF %

100 100 0.059 0.010 83%

100 75 0.103 0.009 91%

100 50 0.247 0.012 95%

100 25 0.247 0.000 100%

100 10 0.925 0.031 97%

60 100 0.028 0.011 61%

60 75 0.138 0.009 93%

60 50 0.180 0.010 95%

60 25 0.370 0.007 98%

60 10 0.801 0.018 98%

91 82 0.091 0.006 93%

80 63 0.195 0.008 96%

63 40 0.240 0.008 97%

0 0 -- -- --

ISO C1 Composite 0.127 0.011 91%

PM ([g/bhp-hr]

1999 (Tier 1) Caterpillar 3408 (480hp, 18l)

Table 4.1-3 Steady-State PM Emissions from a Tier 1 NR Diesel Engine w/ CDPF

The second engine tested was a prototype engine developed at Southwest Research Institute

(SwRI) under contract to EPA.29 The engine, dubbed Deere Development Engine 4045 (DDE4045) because the prototype engine was based on a John Deere 4045 production engine, was also

tested with a CDPF from a different manufacturer on the same 12 ppm diesel fuel. The engine is

very much a prototype and experienced a number of part failures during testing, including to the

turbocharger actuator. Nevertheless, the transient emission results summarized in Table 4.1-4

and the steady-state results summarized in Table 4.1-5 show that substantial PM reductions are

realized on this engine as well. The emission levels on the NRTC and the ISO C1 duty cycles

would meet the PM standard of 0.01 g/hp-hr once the appropriate rounding convention is

applied.E Note also that measured emissions over the transient highway FTP cycle are higher

than for either of the new nonroad transient duty cycles. This suggests that developing PMcompliant engines on the new nonroad transient cycles may not be substantially different from

developing compliant technologies for highway engines.
Regulatory Impact Analysis

4-12

Reduction

Test Cycle Engine Out w/ CDPF %

Proposed Nonroad TransientCycle (NRTC) 0.143 0.013 91%

Proposed Constant Speed Variable Load Cycle (CSVL) 0.218 0.018 92%

On-Highway U.S. FTP Transient Cycle (FTP) 0.185 0.023 88%

Agricultural Tractor Cycle (AGT) 0.134 0.008 94%

Backhoe Loader Cycle (BHL) 0.396 0.021 95%

Crawler Tractor Dozer Cycle (CRT) 0.314 0.008 97%

Composite Excavator Duty Cycle (CEX) 0.176 0.009 95%

Skid Steer Loader Typical No. 1 (SST) 0.288 0.012 96%

Skid Steer Loader Typical No. 2 (SS2) 0.641 0.013 98%

Skid Steer Loader Highly Transient Speed (SSS) 0.298 0.011 96%

Skid Steer Loader Highly Transient Torque (SSQ) 0.536 0.014 97%

Arc Welder Typical No.1 (AWT) 0.290 0.018 94%

Arc Welder Typical No.2 (AW2) 0.349 0.019 95%

Arc Welder Highly Transient Speed (AWS) 0.274 0.019 93%

Rubber-Tired Loader Typical No.1 (RTL) 0.761 0.014 98%

Rubber-Tired Loader Typical No.2 (RT2) 0.603 0.012 98%

Rubber-Tired Loader Highly Transient Speed (RTS) 0.721 0.010 99%

Rubber-Tired Loader Highly Transient Torque (RTQ) 0.725 0.009 99%

EPA Prototype Tier 3 DDE-4045 (108hp, 4.5l)

PM [g/bhp-hr]

Table 4.1-4 Transient PM Emissions for a Prototype NR Diesel Engine with a CDPF

As with the results from the Caterpillar engine, the two low-load (10 percent load) steadystate emission points (see Table 4.1-5) have some of the highest brake specific emission rates. 

However, these rates are not high enough to preclude compliance with the steady-state emission

cycle. The test points are also not within the NTE zone and still show substantial levels of PM

reduction.

Engine Speed Engine Load Reduction

% % Engine Out w/ CDPF %

100 100 0.178 0.012 93%

100 75 0.116 0.006 95%

100 50 0.126 0.006 96%

100 25 0.218 0.013 94%

100 10 0.470 0.029 94%

60 100 0.045 0.007 84%

60 75 0.062 0.014 78%

60 50 0.090 0.009 90%

60 25 0.146 0.019 87%

60 10 0.258 0.046 82%

91 82 0.094 0.004 95%

80 63 0.099 0.006 94%

63 40 0.136 0.011 92%

0 0 -- -- --

ISO C1 Composite 0.129 0.010 92%

EPA Prototype Tier 3 DDE-4045 (108hp, 4.5l)

PM [g/bhp-hr]

Table 4.1-5 Steady-State PM Emissions for a Prototype NR Diesel Engine w/CDPF
Technologies and Test Procedures for Low-Emission Engines

4-13

The new NTE requirement, unlike the nonroad transient cycle (NRTC) or the existing ISO

C1 cycle, is not a composite test. In fact, several of the individual modes within the C1 cycle

test fall within the NTE zone. As discussed above, CDPFs are very efficient at capturing

elemental carbon PM (up to 99 percent), but sulfate-make under certain operating conditions

may exceed the standard of 0.01 g/hp-hr over the NRTC or C1 duty cycles, which is part of the

reason the NTE standard for PM is greater than the PM standards that apply for testing over the

NRTC and C1 duty cycles.

In this rulemaking, we are making changes to the test procedures for nonroad CI engines. 

The switch to the test procedures specified in part 1065 and part 86 (from those specified in part

89) will generally improve the repeatability of emission measurements. These changes do not

change our analysis of the feasibility to comply with the Tier 4 standards as they are designed to

improve accuracy and repeatability and as such do not adversely impact stringency. Also, as

described in section III.G.3 of the preamble, we are considering in a separate proceeding

additional changes to the part 1065 regulations to further improve the test procedures. Like the

changes finalized in this rulemaking, these planned changes will not impact stringency only

accuracy and repeatability, and thus, will not impact feasibility.

The new NTE requirements apply not only during standard laboratory conditions, but also

during the expanded ambient temperature, humidity, and altitude limits defined in the

regulations. We believe the new NTE PM standard is technologically feasible across this range

of ambient conditions. As discussed above, CDPFs are mechanical filtration devices, and

ambient temperature changes will have minimal effect on CDPF performance. Ambient altitude

will also have minimal, if any, effects on CDPF filtration efficiencies, and ambient humidity

should have no effect on CDPF performance. As discussed above, particulate sulfate make is

sensitive to high exhaust gas temperatures; however, at sea-level conditions, the NTE

requirements apply up to ambient temperatures that are only 14/F greater than standard test cell

conditions (100/F under the NTE standards, versus 86/F for C1 laboratory conditions). At an

altitude of 5,500 feet above sea level, the NTE standards apply only up to an ambient

temperature within the range of standard laboratory conditions (i.e., 86/F). These small or nonexistent differences in ambient temperature should have little effect on the sulfate make of

CDPFs, and as can be seen in Tables 4.1-3 and 4.1-5 above, even when tested at an engine

operating test mode representative of the highest particulate sulfate generating conditions (peaktorque operation) with 12 ppm sulfur diesel fuel, the results show the engine would easily meet

the NTE PM standard. Based on the available test data and the expected impact of the expanded,

but constrained, ambient conditions under which engines must comply with the NTE standards,

we conclude that the NTE PM standard for engines > 75 hp is technologically feasible (including

engines >750 hp), provided low-sulfur diesel fuel (15 ppm or lower) is available. Although we

do not have data available specific to the application of wire or fiber mesh filter technologies on

diesel engines >750 hp, the same filtration principles and control mechanisms apply to this

technology as to the ceramic technology described here. A discussion of the technical feasibility

for engines with rated power lower than 75 hp is given in Sections 4.1.4 and 4.1.5.
Regulatory Impact Analysis

F

 With regard to gaseous emissions such as NMHCs and CO, the CDPF works in the same manner with similar

effectiveness as the DOC (i.e., NMHC and CO emissions are reduced by more than 80 percent).

G If the question was asked, “without 15 ppm sulfur fuel and the best catalyst technology, are the exhaust

temperatures high enough on aggregate to oxidize the engine-out PM emission rate?” the answer would be no, for all

but a very few highway or nonroad diesel engines.

4-14

4.1.1.3.2 CDPF Regeneration

Diesel particulate filters (DPFs) control diesel PM by capturing the soot portion of PM in a

filter media, typically a ceramic wall flow substrate, and then by oxidizing (burning) it in the

oxygen-rich atmosphere of diesel exhaust. The SOF portion of diesel PM can be controlled

through the addition of catalytic materials to the DPF to form a catalyzed diesel particulate filter

(CDPF).F

 The catalytic material is also very effective to promote soot burning. This burning off

of collected PM is referred to as “regeneration.” In aggregate over an extended period of

operation, the PM must be regenerated at a rate equal to or greater that its accumulation rate, or

the DPF will clog. 

For a non-catalyzed DPF the soot can regenerate only at very high temperatures, in excess of

600/C, a temperature range that occurs infrequently in normal diesel engine operation (exhaust

temperatures for many engines might never reach 600/C). With the addition of a catalytic

coating to make a CDPF, the temperature necessary to ensure regeneration is decreased

significantly to approximately 250/C, a temperature within the normal operating range for most

diesel engines.30 

The catalytic materials that most effectively promote soot and SOF oxidation, however, are

significantly impacted by sulfur in diesel fuel. Sulfur both degrades catalyst oxidation efficiency

(i.e., poisons the catalyst) and forms sulfate PM. Both catalyst poisoning by sulfur and increases

in PM emissions due to sulfate make influence our decision to limit the sulfur level of diesel fuel

to 15 ppm as discussed in greater detail in the discussion below of the need for low-sulfur diesel

fuel. 

Filter regeneration is affected by catalytic materials used to promote oxidation, sulfur in

diesel fuel, engine-out soot rates, and exhaust temperatures. At higher exhaust temperatures,

soot oxidation occurs at a higher rate. Catalytic materials accelerate soot oxidation at a single

exhaust temperature compared with non-catalyst DPFs, but even with catalytic materials

increasing the exhaust temperature further accelerates soot oxidation.

Having applied 15 ppm sulfur diesel fuel and the best catalyst technology to promote lowtemperature oxidation (regeneration), the regeneration balance of soot oxidation equal to or

greater than soot accumulation over aggregate operation simplifies to the following question: are

the exhaust temperatures high enough on aggregate to oxidize the engine-out PM emission rate?G

The answer is yes, for most highway applications and many nonroad applications, as

demonstrated by the widespread success of retrofit CDPF systems for nonroad equipment and

the use of both retrofit and original equipment CDPF systems for highway vehicles.31,32,33
Technologies and Test Procedures for Low-Emission Engines

H EC-D is a diesel fuel developed recently by ARCO (Atlantic Richfield Company) from typical crude oil using

a conventional refining process and having a fuel sulfur content less than 15 ppm.

4-15

However, it is possible that for some nonroad applications the engine-out PM emission rate may

exceed the soot oxidation rate even with low-sulfur diesel fuel and the best catalyst technologies. 

Should this occur, successful regeneration requires that either engine-out PM emission rates be

decreased or exhaust temperatures be increased, both feasible strategies. In fact, we expect both

to occur as highway-based technologies are transferred to nonroad engines. As discussed earlier,

engine technologies to lower PM emissions while improving fuel consumption are continuously

being developed and refined. As these technologies are applied to nonroad engines driven by

both new emission standards and market pressures for better products, engine-out PM emissions

will decrease. Similarly, techniques to raise exhaust temperatures periodically for initiating soot

oxidation in a PM filter have been developed for highway diesel vehicles as typified by the PSA

system used on more than 400,000 vehicles in Europe.34 

During our 2002 Highway Diesel Progress Review, we investigated the plans of highway

engine manufacturers to use CDPF systems to comply with the HD2007 emission standards for

PM. We learned that all diesel engine manufacturers intend to comply through the application of

CDPF system technology. We also learned that the manufacturers are developing means to raise

the exhaust temperature, if necessary, to ensure that CDPF regeneration occurs.35 These

technologies include modifications to fuel-injection strategies, modifications to EGR strategies,

and modifications to turbocharger control strategies. These systems are based upon the

technologies used by the engine manufacturers to comply with the 2004 highway emission

standards. In general, the systems anticipated to be used by highway manufacturers to meet the

2004 emission standards are the same technologies that engine manufacturers have indicated to

EPA that they will use to comply with the Tier 3 nonroad regulations (e.g., electronic fuel

systems).36 In a manner similar to highway engine manufacturers, we expect nonroad engine

manufacturers to adapt their Tier 3 emission-control technologies to provide back-up

regeneration systems for CDPF technologies to comply with the new emission standards. We

have estimated costs for such systems in our cost analysis.

4.1.1.3.3 Current Status of CDPF Technology

More than one emission control manufacturer is developing CDPFs. In field trials, they have

demonstrated highly efficient PM control and promising durability. A recent publication

documents results from a sample of these field test engines after years of use in real-world

applications.37 The sampled CDPFs had on average four years of use covering more than

225,000 miles in applications ranging from city buses to garbage trucks to intercity trains, with

some units accumulating more than 360,000 miles. When tested on the highway FTP cycle, they

continued to demonstrate PM reductions in excess of 90 percent. 

Another program evaluating CDPFs in the field is the ARCO Emission Control Diesel (ECD) program.H In that program, a technology validation is being run to evaluate EC-D and

CDPFs using diesel vehicles operating in southern California. The fuel’s performance, impact
Regulatory Impact Analysis

I

 We are defining backup regeneration to include any number of methods for raising exhaust temperatures in

order to promote PM filter regeneration. These could include changes to engine management to change engine

operation and raise exhaust temperature, any external mechanism to add heat into the exhaust, or a combination of

engine management to increase hydrocarbon (fuel) emissions from the engine in order to oxidize those emissions

across a diesel oxidation catalyst (DOC) and thus raise exhaust temperatures.

4-16

on engine durability and vehicle performance, and emission characteristics are being evaluated

in several fleets in various applications. The program is still ongoing, but interim results have

been made available.38 These interim results have shown that vehicles retrofitted with CDPFs

and fueled with EC-D (7.4 ppm sulfur) emitted 91 percent to 99 percent less PM compared with

the vehicles fueled with California diesel fuel (121 ppm sulfur) having no exhaust filter

equipment. Further, the test vehicles equipped with the CDPFs and fueled with EC-D have

operated reliably during the program start-up period and no significant maintenance issues have

been reported for the school bus, tanker truck and grocery truck fleets that have been operating

for over six months (approximately 50,000 miles).39 These results from on-highway diesel

engines are significant because in form and function the engines are virtually the same as those

used for nonroad diesel applications. In fact, in many cases on-highway diesel engines have

directed nonroad counterparts that are virtually identical. Further, even for nonroad engines

which may differ in physical size or horsepower range, the underlying chemistry and filtration

efficiency of CDPFs is the same.

Even with the relatively mature state of the CDPF technology, progress is still being made to

improve catalytic-based soot regeneration technologies and to develop system solutions to

ensure that even under the most extreme conditions soot regeneration can be ensured. 

Improvements in catalytic soot oxidation are important because more active soot oxidation can

help to improve fuel economy and to ensure robust soot regeneration. A PM filter with a more

effective soot oxidation catalyst would be expected to have a lower average soot loading and

therefore would be less restrictive to exhaust flow, thus decreasing the pressure drop across the

PM filter and leading to better fuel economy. Improved effectiveness in oxidizing soot will also

further ensure that excessive soot loading that might lead to PM filter failure will not occur.

A paper presented at a recent conference of the Society of Automotive Engineers (SAE)

documented design improvements in catalyzed diesel particulate filters with improved soot

oxidation effectiveness. The paper showed that changes in where catalytic materials were coated

within a PM filter system (on an upfront flow-through catalyst, on the surface of the PM filter or

a combination of both) influenced the effectiveness of the catalyst material to promote soot

oxidation.40 This kind of system analysis suggests that there remain opportunities to further

improve how diesel particulate filters are designed to promote soot oxidation and that different

solutions may be chosen dependent upon expected nonroad equipment operation (expected

exhaust temperature history), packaging constraints and cost. 

Alhough highly effective catalytic soot oxidation, enabled by clean diesel fuel (15 ppm S),

suggests that PM filters will regenerate passively for most vehicle and many nonroad equipment

applications, there remains the possibility that for some conditions active regeneration systems

(backup systems) may be desirable.I For this reason, some vehicle manufacturers have
Technologies and Test Procedures for Low-Emission Engines

4-17

developed systems to help ensure that PM soot regeneration can occur under all conditions. One

example of this is a current production product sold in Europe by PSA/Peugeot. On diesel

powered Peugeot 607 passenger cars (a Ford Taurus-sized passenger car) a PM filter system is

installed that includes mechanisms for engine-promoted soot oxidation. The vehicle estimates

soot loading from several parameters, including exhaust backpressure and can periodically

promote more rapid soot oxidation by injecting additional fuel late in the combustion cycle. This

fuel is injected so late in the cycle that it does not contribute to engine power but instead is

combusted (oxidized) across an oxidation catalyst in front of the PM filter. The combustion of

the fuel across the catalyst increases the exhaust temperature substantially, encouraging rapid

soot oxidation. Peugeot has sold more than 400,000 passenger cars with this technology and

expects to expand the use of the system across all of its diesel vehicle lines.41 Other European

vehicle manufacturers indicated to EPA during our progress review, that they intend to introduce

similar technologies in the near future. They noted that this was not driven by regulation but by

customer demand for clean diesel technologies. The fact that manufacturers are introducing PM

filter technologies in advance of mandatory regulations suggests that the technology is well

developed and mature.

The potential for synergistic benefits to the application of both PM filters and NOx adsorbers

was highlighted in the HD2007 Regulatory Impact Analysis, but at that time little was known as

to the extent of these synergistic benefits.42 Toyota has developed a combined diesel particulate

filter and NOx adsorber technology dubbed DPNR (Diesel Particulate NOx Reduction). The

mechanism for synergistic PM soot regeneration with programmed NOx regeneration was

recently documented by Toyota in a SAE publication. The paper showed that active oxygen

molecules created both under lean conditions as part of the NOx storage function and under rich

conditions created by the NOx regeneration function were effective at promoting soot oxidation

at low temperatures.43 This suggests that the combination of a NOx adsorber catalyst function

with a diesel particulate filter can provide a more robust soot regeneration system than a PM

filter-only technology.

4.1.1.3.4 CDPF Maintenance

Inorganic solid particles present in diesel exhaust can be captured by diesel particulate filters. 

Typically these inorganic materials are metals derived from engine oil, diesel fuel or even engine

wear. Without a PM filter these materials are normally exhausted from the engine as diesel PM. 

While the PM filter is effective at capturing inorganic materials it is not typically effective at

removing them, since they do not tend to be oxidized into a gaseous state (carbon soot is

oxidized to CO2 which can easily pass through the PM filter walls). Because these inorganic

materials are not typically combusted and remain after the bulk of the PM is oxidized from the

filter they are typically referred to as ash. While filtering metallic ash from the exhaust is an

environmental benefit of the PM filter technology it also creates a maintenance need for the PM

filter to remove the ash from the filter periodically. 

The maintenance function for the removal of ash is relatively straightforward, and itself does

not present a technical challenge for the industry. We have estimated cost for ash removal as

one of the costs of this rule (see RIA Chapter 6). However, both the industry and EPA would
Regulatory Impact Analysis

4-18

like to see ash-related PM filter maintenance reduced as much as possible. EPA has specific

guidelines for acceptable maintenance intervals for nonroad diesel engines with CDPFs intended

to ensure robust emission-control technologies (3,000hrs for engines <175 hp and 4,500hrs for

engines $175hp). Nonroad engine manufacturers are similarly motivated to improve reliability

to minimize end-user maintenance costs. The issue of ash accumulation was raised consistently

during our progress review visits with the industry. The industry is investigating several ways to

address this issue including means to improve ash tolerance and to reduce the amount of ash

present in diesel exhaust.

For most current PM filter designs ash accumulates at the end of the inlet passages of the PM

filter. As more ash is accumulated, the effective filter size is reduced because the ash fills the

end of the passage shortening the effective filter length. Increasing PM filter size to tolerate

higher levels of ash accumulation is one simple approach to address ash. This approach, though

effective, is undesirable due to the added cost and size of the resulting PM filter. Several

companies are investigating means to develop PM filter mechanisms that are more ash-tolerant. 

These approaches include concepts to increase storage area within the filter itself and concepts

that promote self-cleaning of the filter, perhaps driven by engine and vehicle vibrations during

normal vehicle operation. Our recent Highway Diesel Progress Review Report 2 described two

such systems recently introduced for on-highway applications. For light-duty vehicle

applications the technologies are described as fit for life, meaning that ash cleaning maintenance

will not be necessary over the life of a light-duty diesel vehicle. For heavy-duty diesel engines

(and for nonroad diesel engines >250 hp) the technologies are expected to increase the interval

between ash cleaning by 50 percent.

In addition to concepts to improve ash handling, possibilities exist to decrease the amount of

ash present in diesel exhaust. The predominant source of ash in diesel exhaust is inorganic

materials contained in engine oil (oil ash). A significant fraction of the ash in engine oil is from

additives necessary to control acidification of engine oil due in part to sulfuric acid derived from

sulfur in diesel fuel. As the sulfur content of diesel fuel is decreased, the need for additives to

neutralize the acids in engine oil should also decrease. The concept of an engine oil with less

ash content is often referred to as “low-ash oil.” Several technical programs are ongoing to

determine the impact of changes in oil ash content and other characteristics of engine oil on

exhaust emission-control technologies and engine wear and performance. Historically, as engine

technologies have changed (often due to changes in emission regulations) engine oil

formulations have also changed. These changes have been accomplished through industry

consensus on oil specifications based on defined test protocols. This process of consensus

definition has begun to develop engine oils specifications for highway diesel engines for the

2007 model year. This engine oil will also be appropriate for application to nonroad diesel

engine designed with the same technologies (i.e., an engine oil specification designed for

highway HD2007 engines would also be appropriate for use with Tier 4 engines).

It may also be possible to reduce the ash level in diesel exhaust by reducing oil consumption

from diesel engines. Diesel engine manufacturers over the years have reduced engine oil

consumption to reduce PM emissions and to reduce operating costs for engine owners. Further

improvements in oil consumption may be possible to reduce ash accumulation rates in PM
Technologies and Test Procedures for Low-Emission Engines

4-19

filters. If oil accumulation rates could be halved and engine oil ash content similarly decreased,

the PM filter maintenance interval would be increased four-fold. Current retrofit PM filter ash

maintenance intervals can range from 50k miles to more than 200k miles.44

4.1.2 NOx Control Technologies

Oxides of nitrogen (NO and NO2, collectively called NOx) are formed at high temperatures

during the diesel combustion process from nitrogen and oxygen present in the intake air. The

NOx formation rate is exponentially related to peak cylinder temperatures and is also strongly

related to nitrogen and oxygen content (partial pressures). NOx control technologies for diesel

engines have focused on reducing emissions by lowering the peak cylinder temperatures and by

decreasing the oxygen content of the intake air. 

4.1.2.1 In-Cylinder NOx Control Technologies

Several technologies have been developed to accomplish these objectives, including fuelinjection timing retard, fuel-injection rate control, charge air cooling, exhaust gas recirculation

(EGR) and cooled EGR. The use of these technologies can result in significant reductions in

NOx emissions, but are limited due to practical and physical constraints of heterogeneous diesel

combustion.45

Our recent Highway Diesel Progress Review Report 2, investigated the extent to which incylinder NOx control technologies had advanced. The report noted that a number of diesel

engine manufacturers introduced cooled EGR systems on their heavy-duty diesel engines in

2002 compliant with the 2004 emission standards for NOx and NMHC of 2.5 g/bhp-hr. The

engines circulate a portion of the exhaust gases through a heat exchanger cooling the exhaust

before reintroducing the gases into the engine intake manifold. The systems control NOx

emissions by providing a diluent (spent exhaust gases) reducing the oxygen content of the intake

air and recirculated exhaust mixture. Engine manufacturers have now demonstrated that these

systems can be further refined to allow NOx emissions compliant with the 2007 NOx averaging

level of approximately 1.2 g/bhp-hr. To reduce NOx emissions below 1.2 g/bhp-hr engine

manufacturers will likely need to increase EGR rates (use higher levels of EGR), thus we are

referring to such refinements for on-highway 2007 diesel engines as high flow EGR. Although

there are nonroad specific challenges to applying similar technologies to nonroad diesel engines

(most notably the lack of ram-air for cooling), the fundamental NOx control technologies are

applicable to all diesel engines. We are confident based on the continuing development of onhighway technologies for in-cylinder NOx control using cooled EGR or ACERTTM that nonroad

diesel engines between 25 and 75 hp and mobile machine nonroad engines >750 hp will be able

to comply with their respective Tier 4 standards (i.e., 3.5 g/bhp-hr NOx+NMHC for 25-50 hp

engines, the same standard certified using the NRTC and NTE for 50-75 hp engines, and 2.6

g/bhp-hr NOx for >750 hp engines), including the NRTC (with cold-start) and the NTE

standards all of which are similar in difficulty to the heavy-duty FTP (with cold-start) and the

NTE standards for on-highway engines. For additional discussion of these emission control

technologies and the impact of the NTE and cold-start, see the RIA for the on-highway HD 2004

emission standards and the RIA for the Tier 2/3 emission standards.46,47
Regulatory Impact Analysis

4-20

A new form of diesel engine combustion, commonly referred to as homogenous diesel

combustion or premixed diesel combustion, can give very low NOx emissions over a limited

range of diesel engine operation. In the regions of diesel engine operation over which this

combustion technology is feasible (light-load conditions), NOx emissions can be reduced enough

to comply with the 0.3 g/hp-hr NOx emission standard.48 Some engine manufacturers are

already producing engines that utilize this technology over a narrow range of engine operation.49

Unfortunately, it is not possible today to apply this technology over the full range of diesel

engine operation. We believe that more engine manufacturers will utilize this alternative

combustion approach in the limited range over which it is effective, but will have to rely on

conventional heterogenous diesel combustion for the bulk of engine operation. See Section

4.1.1.1 for additional discussion of homogenous diesel combustion and PM emission control.

4.1.2.2 Lean-NOx Catalyst Technology

Lean-NOx catalysts have been under development for some time, and two methods have

been developed for using a lean NOx catalyst depending on the level of NOx reduction desired

though neither method can produce more than a 30 percent NOx reduction. The “active” leanNOx catalyst injects a reductant that serves to reduce NOx to N2 and O2 (typically diesel fuel is

used as the reductant). The reductant is introduced upstream of, or into, the catalyst. The

presence of the reductant provides locally oxygen-poor conditions that allow the NOx emissions

to be reduced by the catalyst. 

The lean-NOx catalyst washcoat incorporates a zeolite catalyst that acts to adsorb

hydrocarbons from the exhaust stream. Once adsorbed on the zeolite, the hydrocarbons will

oxidize and create a locally oxygen-poor region that is more conducive to reducing NOx. To

promote hydrocarbon oxidation at lower temperatures, the washcoat can incorporate platinum or

other precious metals. The platinum also helps to eliminate the emission of unburned

hydrocarbons that can occur if too much reductant is injected, referred to as “hydrocarbon slip.” 

With platinum, the NOx conversion can take place at the low exhaust temperatures that are

typical of diesel engines. However, the presence of the precious metals can lead to production of

sulfate PM, as already discussed for PM control technologies.

Active lean-NOx catalysts have been shown to provide up to 30 percent NOx reduction

under limited steady-state conditions. However, this NOx control is achieved with a fuel

economy penalty upwards of 7 percent due to the need to inject fuel into the exhaust stream.50

NOx reductions over the transient highway FTP cycle are only on the order of 12 percent due to

excursions outside the optimum NOx reduction efficiency temperature range for these devices.51

Consequently, the active lean-NOx catalyst does not appear to be capable of enabling the

significantly lower NOx emissions required by the Tier 4 NOx standards.

 The “passive” lean-NOx catalyst uses no reductant injection. The passive lean-NOx

catalyst is therefore even more limited in its ability to reduce NOx because the exhaust gases

normally contain very few hydrocarbons. For that reason, today’s passive lean-NOx catalyst is

capable of best steady-state NOx reductions of less than 10 percent. Neither approach to lean-
Technologies and Test Procedures for Low-Emission Engines

J

 NOx adsorber catalysts are also called, NOx storage catalysts (NSCs), NOx storage and reduction catalysts

(NSRs), and NOx traps.

4-21

NOx catalysis listed here can provide the significant NOx reductions necessary to meet the Tier

4 standards.

4.1.2.3 NOx Adsorber Technology

NOx emissions from gasoline-powered vehicles are controlled to extremely low levels

through the use of the three-way catalyst technology first introduced in the 1970s. Three-waycatalyst technology is very efficient in the stochiometric conditions found in the exhaust of

properly controlled gasoline-powered vehicles. Today, an advancement upon this welldeveloped three-way catalyst technology, the NOx adsorber, has shown that it too can make

possible extremely low NOx emissions from lean-burn engines such as diesel engines.J

 The

potential of the NOx adsorber catalyst is limited only by its need for careful integration with the

engine and engine control system (as was done for three-way catalyst equipped passenger cars in

the 1980s and 1990s) and by poisoning of the catalyst from sulfur in the fuel. The Agency set

stringent new NOx standards for highway diesel engines beginning in 2007 predicated upon the

use of the NOx adsorber catalyst enabled by significant reductions in fuel sulfur levels (15 ppm

sulfur or less). The final rule includes similarly stringent NOx emission standards for nonroad

engines from 75-750 hp and for certain engines >750 hp, again based on using technology

enabled by a reduction in fuel sulfur levels. 

NOx adsorbers work to control NOx emissions by storing NOx on the surface of the catalyst

during the lean engine operation typical of diesel engines. The adsorber then undergoes

subsequent brief rich regeneration events where the NOx is released and reduced across

precious-metal catalysts. The NOx storage period can be as short as 15 seconds and as along as

10 minutes depending upon engine-out NOx emission rates and exhaust temperature. Several

methods have been developed to accomplish the necessary brief rich exhaust conditions

necessary to regenerate the NOx adsorber technology including late-cycle fuel injection, also

called post injection, in exhaust fuel injection, and dual bed technologies with off-line

regeneration.52,53,54 This method for NOx control has been shown to be highly effective when

applied to diesel engines but has some technical challenges associated with it. Primary among

these is sulfur poisoning of the catalyst, as described in Section 4.1.2.3.4.2 below.

4.1.2.3.1 How do NOx Adsorbers Work?

As noted, the NOx adsorber catalyst is a further development of the three-way catalyst

technology developed for gasoline powered vehicles more than twenty years ago. The NOx

adsorber enhances the three-way catalyst function through the addition of storage materials on

the catalyst surface that can adsorb NOx under oxygen-rich conditions. This enhancement

means that a NOx adsorber can allow for control of NOx emissions under lean-burn (oxygenrich) operating conditions typical of diesel engines.
Regulatory Impact Analysis

4-22

Three-way catalysts reduce NOx emissions as well as HC and CO emissions (hence the name

three-way) by promoting oxidation of HC and CO to water and CO2 using the oxidation potential

of the NOx pollutant, and, in the process, reducing the NOx emissions to atomic nitrogen, N2. 

Said another way, three-way catalysts work with exhaust conditions where the net oxidizing and

reducing chemistry of the exhaust is approximately equal, allowing the catalyst to promote

complete oxidation/reduction reactions to the desired exhaust components, carbon dioxide

(CO2), water (H2O) and nitrogen (N2). The oxidizing potential in the exhaust comes from NOx

emissions and from oxygen (O2) that is not consumed during combustion. The reducing

potential in the exhaust comes from HC and CO emissions, which are products of incomplete

combustion. Operation of the engine to ensure that the oxidizing and reducing potential of the

combustion and exhaust conditions is precisely balanced is referred to as stoichiometric engine

operation. 

If the exhaust chemistry varies from stoichiometric conditions emission control is decreased. 

If the exhaust chemistry is net “fuel-rich,” meaning there is an excess of HC and CO emissions

in comparison to the oxidation potential of the NOx and O2 present in the exhaust, the excess HC

and CO pollutants are emitted from the engine. Conversely, if the exhaust chemistry is net

“oxygen-rich” (lean-burn), meaning there is an excess of NOx and O2 in comparison to the

reducing potential of the HC and CO present in the exhaust, the excess NOx pollutants are

emitted from the engine. It is this oxygen-rich operating condition that typifies diesel engine

operation. Because of this, diesel engines equipped with three-way catalysts (or simpler

oxidation catalysts) have very low HC and CO emissions while NOx (and O2) emissions remain

almost unchanged from the high engine-out emission levels. For this reason, when diesel

engines are equipped with catalysts (diesel oxidation catalysts (DOCs)) they have HC and CO

emissions that are typically lower, but have NOx emissions that are an order of magnitude

higher, than for gasoline engines equipped with three-way catalysts.

The NOx adsorber catalyst works to overcome this situation by storing NOx emissions when

the exhaust conditions are oxygen-rich. Unfortunately the storage capacity of the NOx adsorber

is limited, requiring that the stored NOx be periodically purged from the storage component. If

the exhaust chemistry is controlled such that when the stored NOx emissions are released the net

exhaust chemistry is at stoichiometric or net fuel-rich conditions, then the three-way catalyst

portion of the catalyst can reduce the NOx emissions in the same way as for a gasoline three-way

catalyst equipped engine. Simply put, the NOx adsorber works to control NOx emissions by

storing NOx on the catalyst surface under lean-burn conditions typical of diesel engines and then

by reducing the NOx emissions with a three-way catalyst function by periodically operating

under stoichiometric or fuel-rich conditions.

The NOx storage process can be further broken down into two steps. First the NO in the

exhaust is oxidized to NO2 across an oxidation promoting catalyst, typically platinum. Then the

NO2 is further oxidized and stored on the surface of the catalyst as a metallic nitrate (MNO3). 

The storage components are typically alkali or alkaline earth metals that can form stable metallic

nitrates. The most common storage component is barium carbonate (BaCO3), which can store

NO2 as barium nitrate (Ba(NO3)2) while releasing CO2. For the NOx storage function to work,

the NOx must be oxidized to NO2 prior to storage and a storage site must be available (the
Technologies and Test Procedures for Low-Emission Engines

4-23

device cannot be “full”). During this oxygen-rich portion of operation, NOx is stored while HC

and CO emissions are oxidized across the three-way catalyst components by oxygen in the

exhaust. This can result in near zero emissions of NOx, HCs, and CO under the net oxygen-rich

operating conditions typical of diesel engines.

The NOx adsorber releases and reduces NOx emissions under fuel-rich operating conditions

through a similar two step process, referred to here as NOx adsorber regeneration. The metallic

nitrate becomes unstable under net fuel-rich operating conditions, decomposing and releasing the

stored NOx. Then the NOx is reduced by reducing agents in the exhaust (CO and HCs) across a

three-way catalyst system, typically containing platinum and rhodium. Typically, this NOx

regeneration step occurs at a significantly faster rate than the period of lean-NOx storage such

that the fuel-rich operation constitutes only a small fraction of the total operating time. Since

this release and reduction step, NOx adsorber regeneration, occurs under net fuel-rich operating

conditions, NOx emissions can be almost completely eliminated. But for some of the HC and

CO emissions, “slip”(failure to remove all of the HC and CO) may occur during this process. 

The HC and CO slip can be controlled with a downstream “clean-up” catalyst that promotes their

oxidation or potentially by controlling the exhaust constituents such that the excess amount of

the HC and CO pollutants at the fuel-rich operating condition is as low as possible, that is, as

close to stoichiometric conditions as possible.

The difference between stoichiometric three-way catalyst function and the newly developed

NOx adsorber technology can be summarized as follows. Stoichiometric three-way catalysts

work to reduce NOx, HCs and CO by maintaining a careful balance between oxidizing (NOx and

O2) and reducing (HCs and CO) constituents and then promoting their mutual destruction across

the catalyst on a continuous basis. The newly developed NOx adsorber technology works to

reduce the pollutants by balancing the oxidation and reduction chemistry on a discontinuous

basis, alternating between net oxygen-rich and net fuel-rich operation to control the pollutants. 

This approach allows lean-burn engines (oxygen-rich operating), like diesel engines, to operate

under their normal operating mode most of the time, provided that they can periodically switch

and operate such that the exhaust conditions are net fuel-rich for brief periods. If the

engine/emission-control system can be made to operate in this manner, NOx adsorbers offer the

potential to employ the highly effective three-way catalyst chemistry to lean-burn engines.

4.1.2.3.2 NOx Adsorber Regeneration Mechanisms

NOx adsorbers work to control NOx emissions by storing the NOx pollutants on the catalyst

surface during oxygen-rich engine operation (lean-burn engine operation) and then by

periodically releasing and reducing the NOx emissions under fuel-rich exhaust conditions. This

approach to controlling NOx emissions can work for a diesel engine provided that the engine and

emission-control system can be designed to work in concert, with relatively long periods of

oxygen-rich operation (typical diesel engine operation) followed by brief periods of fuel-rich

exhaust operation. The ability to control the NOx emissions in this manner is the production

basis for lean-burn NOx emission control in stationary power systems and for lean-burn gasoline

engines. As outlined below, we believe there are several approaches to accomplish the required

periodic operation on a diesel engine.
Regulatory Impact Analysis

4-24

The most frequently mentioned approach for controlling the exhaust chemistry of a diesel

engine is through in-cylinder changes to the combustion process. This approach roughly mimics

the way in which lean-burn gasoline engines function with NOx adsorbers. That is, the engine

itself changes in operation periodically between “normal” lean-burn (oxygen-rich) combustion

and stoichiometric or even fuel-rich combustion to promote NOx control with the NOx adsorber

catalyst. For diesel engines this approach typically requires the use of common rail fuel systems,

which allow for multiple fuel-injection events, along with an air handling system that includes

exhaust gas recirculation (EGR).

The normal lean-burn engine operation can last from as little time as 15 seconds to more than

three minutes as the exhaust NOx emissions are stored on the surface of the NOx adsorber

catalyst. The period of fuel-lean, oxygen-rich, operation is determined by the NOx emission rate

from the engine and the storage capacity of the NOx adsorber. Once the NOx adsorber catalyst

is full (once an unacceptable amount of NOx is slipping through the catalyst without storage) the

engine must switch to fuel-rich operation to regenerate the NOx adsorber.

The engine typically changes to fuel-rich operation by increasing the EGR rate, by throttling

the fresh air intake, and by introducing an additional fuel-injection event late in the combustion

cycle. The increased EGR rate works to decrease the oxygen content of the intake air by

displacing fresh air that has a high oxygen content with exhaust gases that have a much lower

oxygen content. Intake air throttling further decreases the amount of fresh air in the intake gases

again lowering the amount of oxygen entering the combustion chamber. The combination of

these first two steps serves to lower the oxygen concentration in the combustion chamber,

decreasing the amount of fuel required to reach a fuel-rich condition. The fuel is metered then

into the combustion chamber in two steps under this mode of operation. The first, or primary,

injection event meters a precise amount of fuel to deliver the amount of torque (energy) required

by the operator demand (accelerator pedal input). The second injection event is designed to

meter the amount of fuel necessary to achieve a net fuel-rich operating condition. That is, the

primary plus secondary injection events introduce an excess of fuel when compared with the

amount of oxygen in the combustion chamber. The secondary injection event occurs very late in

the combustion cycle, so it does not generate additional torque. This is necessary so the

switching between the normal lean-burn operation and this periodic fuel-rich operation is

transparent to the user.

Additional ECM capability will be necessary to monitor the NOx adsorber and determine

when the NOx regeneration events are necessary. This can be done in a variety of ways, though

they fall into two general categories: predictive and reactive. First, the predictive method

estimates or measures the NOx flow into the adsorber in conjunction with the predicted adsorber

performance to determine when the adsorber is near capacity. Then, upon entering optimal

engine operating conditions, the system performs a NOx regeneration. This particular step is

similar to an on-board diagnostic (OBD) algorithm waiting for proper conditions to perform a

functionality check. During the NOx regeneration, sensors determine how accurately the

predictive algorithm performed, and adjust it accordingly. Second, the reactive method is

envisioned to monitor NOx downstream of the NOx adsorber and detection of NOx slippage

triggers a regeneration event. This method is dependent on good NOx-sensor technology. This
Technologies and Test Procedures for Low-Emission Engines

K A condition of 8 = 1 means that there are precisely the needed quantity of reactants for complete reaction at

equilibrium. 8 < 1 means that there is insufficient oxygen, 8 > 1 means that there is excess oxygen.

4-25

method also depends on the ability to regenerate under any given engine operating condition,

since the algorithm reacts to indications that the adsorber had reached its NOx storage capacity. 

In either case, we believe these algorithms are not far removed from the systems that will be

used by nonroad manufacturers to meet Tier 3 emission standards and will be virtually identical

to the systems used by highway engine manufacturers to comply with the HD2007 emission

regulations. When used in combination with the sophisticated control systems that will be

available, we expect that NOx regeneration events can be seamlessly integrated into engine

operation such that the operator may not be aware that the events are taking place.

Using this approach of periodic switching between normal lean-burn operation and brief

periods of fuel-rich operation all accomplished within the combustion chamber of a diesel engine

is one way in which an emission-control system for a diesel engine can be optimized to work

with the NOx adsorber catalyst. This approach requires no new engine hardware beyond the air

handling and advanced common rail fuel systems that many advanced diesel engines will have

already applied to meet the Tier 3 NOx standard. For this reason an in-cylinder approach is

likely to appeal to engine manufacturers for product lines where initial purchase cost or package

size is the most important factor in determining engine purchases. 

Another approach to accomplish the NOx adsorber regeneration is through the use of a socalled “dual-bed” or “multiple-bed” NOx adsorber catalyst system. Such a system is designed so

the exhaust flow can be partitioned and routed through two or more catalyst “beds” operating in

parallel. Multiple-bed NOx adsorber catalysts restrict exhaust flow to part of the catalyst during

its regeneration. By doing so, only a portion of the exhaust flow need be made rich, reducing

dramatically the amount of oxygen needing to be depleted and thus the fuel required to be

injected to generate a rich exhaust stream. One simple example of a multiple bed NOx adsorber

is the dual-bed system in Figure 4.1-1. In this example, the top half of the adsorption catalyst

system is regenerating under a low exhaust flow condition (exhaust control valve nearly closed),

while the remainder of the exhaust flow is bypassed to a lower half of the system. A system of

this type has the following characteristics:

• Half of the system operates with a major flow in an “adsorption mode,” where most of

the exhaust is well lean of stoichiometric (8 > 1 or >>1, typical diesel exhaust), NO is

converted to NO2 over a Pt-catalyst, and stored as a metallic nitrate within the NOx

adsorbent material.K

• The other half of the system has its exhaust flow restricted to just a small fraction (~5

percent) of the total flow and operates in a regeneration mode.

- While the flow is restricted for regeneration, a small quantity of fuel is sprayed into

the regenerating exhaust flow at the beginning of the regeneration event. 

- The fuel is oxidized by the oxygen in the exhaust until sufficient oxygen is depleted

for the stored NOx to be released. This occurs at exhaust conditions of 8 # 1.
Regulatory Impact Analysis

4-26

- At these conditions, NOx can also be very efficiently reduced to N2 and O2 over a

precious-metal catalyst.

• At the completion of regeneration, the majority of the flow can then be reintroduced into

the regenerated half of the system by opening the flow control valve.

• Simultaneously, flow is restricted to the other half of the system to allow it to regenerate.

NOx

Adsorber

Secondary 

Fuel Injector

(off)

Flow

NOx

Adsorber

Secondary

Fuel Injector

(on)

Flow

Partially Closed 

Exhaust-flow 

Control Valve

Fully Open 

Exhaust-flow 

Control Valve

Exhaust Flow

Diesel Engine

NOx

Adsorber

Secondary 

Fuel Injector

(off)

Flow

NOx

Adsorber

Secondary

Fuel Injector

(on)

Flow

Partially Closed 

Exhaust-flow 

Control Valve

Fully Open 

Exhaust-flow 

Control Valve

Exhaust Flow

Diesel Engine

Figure 4.1-1

Schematic Representation of the Operation of a Dual-Bed NOx Adsorption Catalyst

Although the schematic shows two separate systems, the diversion of exhaust flow can occur

within a single catalyst housing, and with a single catalyst monolith. There may also be

advantages to using more than one partition for the NOx adsorber system such as the use of

multiple beds allows desulfation of one bed while normal NOx adsorption and regeneration

events occur in other beds.

The NOx adsorber performance can be enhanced by incorporating a catalyzed diesel

particulate filter (CDPF) into the system. A number of synergies exist between NOx adsorber

systems and CDPFs. Both systems rely on conversion of NO to NO2 over a Pt catalyst for part

of their functioning. Partial oxidation reforming of diesel fuel to hydrogen and CO over a Ptcatalyst has been demonstrated for fuel-cell applications. A similar reaction to reform the fuel

upstream of the NOx adsorber during regeneration provides a more reactive reductant for

desorption and reduction of NOx. Heavier fuel hydrocarbons are known to inhibit NOx

reduction on the NOx adsorption catalyst since competitive adsorption by hydrocarbons on the

precious-metal sites inhibits NOx reduction during adsorber regeneration.55 Partial oxidation of

the secondary fuel injected into the exhaust during regeneration could lead to sooting of the fuel. 

Using a CDPF upstream of the NOx adsorber, but downstream of the secondary fuel injection,

allows partial oxidation of the fuel hydrocarbons to occur over the Pt catalyst on the surface of
Technologies and Test Procedures for Low-Emission Engines

4-27

the CDPF. The wall-flow design of the CDPF efficiently captures any soot formed during partial

oxidation of the fuel injected into the exhaust, preventing any increase in soot emissions. The

partial oxidation reaction over the CDPF is exothermic, which can be used increase the rate of

temperature rise for the NOx adsorber catalyst after cold starts, similar to the use of light-off

catalysts with cascade three-way catalyst systems.56

4.1.2.3.3 How Efficient are Diesel NOx Adsorbers?

Research into applying the NOx adsorber catalyst to diesel exhaust is only a few years old

but benefits from the larger body of experience with stationary power sources and with lean-burn

gasoline systems. In simplest terms the question is how well does the NOx adsorber store NOx

under normal lean-burn diesel engine operation, and then how well does the control system

perform the NOx regeneration function. Both of these functions are affected by the temperature

of the exhaust and of the catalyst surface. For this reason efficiency is often discussed as a

function of exhaust temperature under steady-state conditions. This is the approach used in this

section and is extended in Section 4.1.3.1.2 below to predict the effectiveness of the NOx

adsorber technology when engines operate over the new transient duty cycles. The potential for

both NOx storage and reduction to operate at very high efficiencies can be realized through

careful emission-control system design, as described below.

The NOx storage function consists of oxidation of NO to NO2 and then storage of the NOx as

a metallic nitrate on the catalyst surface. The effectiveness of the catalyst at accomplishing these

tasks is dependent upon exhaust temperature, catalyst temperature, precious-metal dispersion,

NO storage volume, and transport time (mass flow rates through the catalyst). Taken as a whole,

these factors determine how effectively a NOx adsorber-based control system can store NOx

under lean-burn diesel engine operation.

Catalyst and exhaust temperature are important because the rate at which the desirable

chemical reactions occur is a function of the local temperature where the reaction occurs. The

reaction rate for NO to NO2 oxidation and for NOx storage increases with increasing

temperature. Beginning at temperatures as low as 100/C NO oxidation to NO2 can be promoted

across a platinum catalyst at a rate high enough to allow for NOx storage to occur. Below 100/C

the reaction can still occur (as it does in the atmosphere); however, the reaction rate is so slow as

to make NOx storage ineffective below this temperature in a mobile source application. At

higher exhaust temperatures, above 400/C, two additional mechanisms affect the ability of the

NOx adsorber to store NOx. First the NO to NO2 reaction products are determined by an

equilibrium reaction that favors NO rather than NO2. That is across the oxidation catalyst, NO is

oxidizing to form NO2 and NO2 is decaying to form NO at a rate that favors a larger fraction of

the gas being NO rather than NO2. As this is an equilibrium reaction when the NO2 is removed

from the gas stream by storage on the catalyst surface, the NOx gases quickly “re-equilibrate”

forming more NO2. This removal of NO2 from the gas stream and the rapid oxidation of NO to

NO2 means that in spite of the NO2 fraction of the NOx gases in the catalyst being low at

elevated conditions (30 percent at 400/C) the storage of NOx can continue to occur with high

efficiencies, near 100 percent.
Regulatory Impact Analysis

4-28

Unfortunately, the other limitation of high-temperature operation is not so easily overcome. 

The metallic nitrates that are formed on the catalyst surface and that serve to store the NOx

emissions under fuel-lean operating conditions can become unstable at elevated temperatures. 

That is, the metallic nitrates thermally decompose releasing the stored NOx under lean operating

conditions allowing the NOx to exit the exhaust system “untreated.” The temperature at which

the storage metals begin to thermally release the stored NOx emissions varies dependent upon

the storage metal or metals used, the relative ratio of the storage metals, and the washcoat

design. Changes to catalyst formulations can change the upper temperature threshold for thermal

NOx desorption by as much as 100/C.57 Thermal stability is the primary factor determining the

NOx control efficiency of the NOx adsorber at temperatures higher than 400-500/C. NOx

adsorber catalyst developers are continuing to work to improve this aspect of NOx adsorber

performance, and as documented in EPA’s 2002 Highway Progress Review improving

temperature performance is being realized.

The NOx adsorber catalyst releases stored NOx emissions under fuel-rich operating

conditions and then reduces the NOx over a three-way catalyst function. While the NOx storage

function determines the NOx control efficiency during lean operation, it is the NOx release and

reduction function that determines the NOx control efficiency during NOx regeneration. Since

NOx storage can approach near 100 percent effectiveness for much of the temperature range of

the diesel engine, the NOx reduction function often determines the overall NOx control

efficiency.

NOx release can occur under relatively cool exhaust temperatures even below 200/C for

current NOx adsorber formulations. Unfortunately, the three-way NOx reduction function is not

operative at such cool exhaust temperatures. The lowest temperature at which a chemical

reaction is promoted at a defined efficiency (often 50 percent) is referred to as the “light-off”

temperature. The 80 percent light-off temperature for the three-way catalytic NOx reduction

function of current NOx adsorbers is between 200/C and 250/C. Even though NOx storage and

release can occur at cooler temperatures, NOx control is therefore limited under steady-state

conditions to temperatures greater than this light-off temperature.

Under transient operation, however, NOx control can be accomplished at temperatures below

this NOx reduction light-off temperature provided that the period of operation at the lower

temperature is preceded by operation at higher temperatures and provided that the lowtemperature operation does not continue for an extended period. This NOx control is possible

due to two characteristics of the system specific to transient operation. First, NOx control can be

continued below the light-off temperature because storage can continue below that temperature. 

If the exhaust temperature again rises above the NOx reduction light-off temperature before the

NOx adsorber storage function is full, the NOx reduction can then precede at high efficiency. 

Said another way, if the excursions to very low temperatures are brief enough, NOx storage can

proceed under this mode of operation, followed by NOx reduction when the exhaust

temperatures are above the light-off temperature. Although this sounds like a limited benefit

because NOx storage volume is limited, in fact it can be significant, because the NOx emission

rate from the engine is low at low temperatures. While the NOx storage rate may be limited such

that at high-load conditions the lean-NOx storage period is as short as 30 seconds, at the very
Technologies and Test Procedures for Low-Emission Engines

4-29

low NOx rates typical of low-temperature operation (operation below the NOx reduction lightoff temperature) this storage period can increase dramatically. This is due to the NOx mass flow

rate from the engine changing dramatically between idle conditions and full load conditions. 

The period of lean-NOx storage is expected to increase in inverse proportion to the NOx

emission rate from the engine. The period of NOx storage under light load conditions therefore

can likewise be expected to increase dramatically.

Transient operation can further allow for NOx control below the NOx reduction light-off

temperature due to the thermal inertia of the emission-control system itself. The thermal inertia

of the emission-control system can work to warm the exhaust gases to a local temperature high

enough to promote the NOx reduction reaction even though the inlet exhaust temperatures are

below the light-off temperature for the catalyst. 

The combination of these two effects was observed during testing of NOx adsorbers at the

National Vehicle and Fuel Emissions Laboratory (NVFEL), especially regarding NOx control

under idle conditions. It was observed that when idle conditions followed loaded operation, for

example when cooling the engine down after a completing an emission test, that the NOx

emissions were effectively zero (below background levels) for extended periods of idle operation

(for more than 10 minutes). It was also discovered that the stored NOx can be released and

reduced in this operating mode, even though the exhaust temperatures were well below 250/C,

provided that the regeneration event was triggered within the first 10 minutes of idle operation

(before the catalyst temperature decreased significantly). However, if the idle mode was

continued for extended periods (longer than 15 minutes) NOx control eventually diminished. 

The loss of NOx control at extended idle conditions appeared to be due to the inability to reduce

the stored NOx leading to high NOx emissions during NOx regeneration cycles.

NOx control efficiency with the NOx adsorber technology under steady-state operating

conditions can be seen to be limited by the light-off temperature threshold of the three-way

catalyst NOx reduction function. Further, a mechanism for extending control below this

temperature is described for transient operation and is observed in testing of NOx adsorber-based

catalyst systems. In addition, as described later in this section, new combustion strategies such

as Toyota’s low-temperature combustion technology can raise exhaust temperatures at low loads

to promote improved NOx performance with a NOx adsorber catalyst.

Overall, NOx adsorber efficiency reflects the composite effectiveness of the NOx adsorber in

storing, releasing and reducing NOx over repeated lean/rich cycles. As detailed above, exhaust

temperatures play a critical role in determining the relative effectiveness of each of these catalyst

functions. These limits on the individual catalyst functions can explain the observed overall

NOx control efficiency of the NOx adsorber, and can be used to guide future research to improve

overall NOx adsorber efficiency and the design of an integrated NOx emission-control system.

At low exhaust temperatures overall NOx control is limited by the light-off temperature

threshold of the three-way NOx reduction function in the range from 200/C to 250/C. At high

temperatures (above 400/ to 500/C) overall NOx control is limited by the thermal stability of the
Regulatory Impact Analysis

4-30

NOx storage function. For exhaust temperatures between these two extremes NOx control can

occur at virtually 100 percent effectiveness. 

The ability of the complete system, including the engine and the emission-control system, to

control NOx emissions consistently (well in excess of 90 percent) is therefore dependent upon

the careful management of temperatures within the system. Figure 4.1-2 provides a pictoral

representation of these constraints and indicates how well a diesel engine can match the

capabilities of a NOx adsorber-based NOx control system. The figure shows accumulated NOx

emissions (grams) over the highway FTP cycle for both a light heavy-duty and a heavy heavyduty engine. The engine-out NOx emissions are shown as the dark bars on the graphs. The

accumulated NOx emissions shown here, divided by the integrated work over the test cycle gives

a NOx emission rate of 4 g/hp-hr (the 1998 emission standard for highway heavy-duty diesel

engines) for each of these engines. Also shown on the graph as a solid line is the steady-state

NOx conversion efficiency for a NOx adsorber, MECA “B”, used in testing at NVFEL (see

Section 4.1.2.3.5.2 below for more details on testing at NVFEL). The line has been annotated to

show the constraint under low-temperature operation (three-way catalyst light-off). The white

bars on the graph represent an estimate of the tailpipe NOx emissions that can be realized from

the application of the NOx adsorber based upon the steady-state efficiency curve for adsorber

MECA “B”. These estimated tailpipe emissions are highest in the temperature range below

250/C even though the engine-out NOx emissions are the lowest in this region. This is due to

the light-off temperature threshold for the NOx three-way reduction function. 
Technologies and Test Procedures for Low-Emission Engines

4-31

100 150 200 250 300 350 400 450 500

0

10

20

30

40

50

60

70

80

90

100

Catalyst Inlet Temperature ( oC)

Steady State NOx Adsorber Conversion Efficiency (%)

HHD Diesel Estimated NOx Adsorber Effectiveness over HD FTP

MECA "B" NOx Adsorber (%) 

Engine Out NOx FTP (4g NOx Engine)

Projected FTP Tailpipe NOx 

2

4

6

8

10

0

Accumulated NOx Emissions over HD FTP Cycle (grams)

100 150 200 250 300 350 400 450 500

0

10

20

30

40

50

60

70

80

90

100

Catalyst Inlet Temperature ( oC)

Steady State NOx Adsorber Conversion Efficiency (%)

LHD Diesel Estimated NOx Adsorber Effectiveness over HD FTP

MECA "B" NOx Adsorber (%) 

Engine Out NOx FTP (4g NOx Engine)

Projected FTP Tailpipe NOx 

Accumulated NOx Emissions over HD FTP Cycle (grams)

1

2

3

0

three-way catalyst “lightoff”

three-way catalyst “lightoff”

Figure 4.1-2

NOx Adsorber Efficiency Characteristics versus Exhaust Temperature
Regulatory Impact Analysis

4-32

Since the conversion efficiencies are based upon steady-state operation, it is likely that the

low-temperature performance can be better than estimated here due to a catalyst’s ability to store

the NOx emissions at these low temperatures and then to reduce them when transient operation

raises the exhaust temperatures above the three-way light-off temperature. This assertion

provides one explanation for differences noted between this approximation of the NOx

efficiency over the highway FTP cycle for the light heavy-duty engine shown in Figure 4.1-2 and

actual NOx adsorber efficiency demonstrated with this engine in the NVFEL test program. 

Based upon the figure above (using the steady-state conversion estimate) the NOx adsorber

catalyst should have provided less than an 84 percent reduction in NOx emissions over the

highway FTP cycle. However, testing at NVFEL (detailed in Section 4.1.2.3.5) has

demonstrated a greater than 90 percent reduction in NOx emissions with this same engine and

catalyst pair without significant optimization of the system. Clearly then, steady-state NOx

adsorber performance estimates can underestimate the real NOx reductions realized in transient

vehicle operation. Nevertheless, we have used this approach as a screening analysis to predict

performance for nonroad engines equipped with NOx adsorber catalysts in Section 4.1.3.1.2

below.

The tailpipe NOx emissions are the lowest in the range from 250/C to 450/C, even though

this is where the majority of the engine-out NOx emissions are created, because of the high

overall NOx reduction efficiency of the NOx adsorber system under these conditions. At

temperatures above 500/C the NOx conversion efficiency of the NOx adsorber can be seen to

decrease. 

Figure 4.1-2 shows that the temperature window of a current technology NOx adsorber

catalyst is well matched to the exhaust temperature profiles of a light heavy-duty and a heavy

heavy-duty diesel engine operated over the highway FTP cycle. The discussion in Section

4.1.3.1.2 below shows similarly that the nonroad transient cycle (NRTC) is also well matched to

the performance of the NOx adsorber catalyst. Testing at NVFEL on the same engine operated

over a wide range of steady-state points, shows that even for extended high-load operation, as

typified by the 100 percent load test points in the test, NOx conversion efficiencies remained

near or above 90 percent (see discussion of the NVFEL test program in Section 4.1.2.3.5 below). 

The discussion above makes it clear that when the engine and NOx adsorber-based emissioncontrol system are well matched, NOx reductions can be far in excess of 90 percent. Conversely,

it can be inferred that if exhaust temperatures are well in excess of 500/C or well below 200/C

for significant periods of engine operation then NOx control efficiency may be reduced. 

Researchers are developing and testing new NOx adsorber formulations designed to increase the

high temperature stability of the NOx adsorber and to therefore widen this window of

operation.58 

How effective are NOx adsorbers for cold-start emissions?

In addition to broadening the catalyst temperature window, the exhaust temperature from the

diesel engine can be managed to align with the temperature window of the catalyst. 
Technologies and Test Procedures for Low-Emission Engines

4-33

The steady-state analysis discussed above is based on steady-state emission results (i.e., after

exhaust temperatures have stabilized), but the NRTC also includes a cold-start test where the

catalyst initial temperature will be at ambient conditions (see Section 4.2). The NRTC emission

level for the engine is determined by weighting the cold-start emissions by 1/20 (5 percent), and

weighting the hot-start emission results by 19/20 (95 percent). Historically, for highway heavyduty diesel engines that are similar to current technology nonroad diesel engines not equipped

with an exhaust emission-control device, the cold-start and hot-start emissions have been nearly

identical. However, with the application of emission-control devices which have optimal

temperature operating windows, such as a NOx adsorber, the cold-start test will become a design

challenge for highway diesel engine manufacturers and for nonroad diesel engine manufacturers,

just as it has been a design challenge for light-duty gasoline vehicle manufacturers for more than

20 years. 

Manufacturers have several available tools to overcome this challenge:

• The volume, shape, and substrate material have a significant effect on the warm-up time

of a NOx adsorber (just as they do for light-duty three-way catalysts). Manufactures will

optimize the make-up of the adsorber for best light-off characteristics, such as the thinwalled ceramic monolith catalysts typical of modern low-emission light-duty gasoline

applications.

• The packaging of the exhaust emission-control devices, including the use of insulating

material and air-gap exhaust systems, will also decrease light-off time, and we expect

manufacturers to explore those opportunities.

• The location of the adsorber, with respect to it’s proximity to the exhaust manifold, will

have a significant impact on the light-off characteristics.

• As discussed above, NOx adsorbers have the ability to store NOx at temperatures much

less than the three-way catalyst function temperature operating window, on the order of

100/C. This is unlike the performance of catalysts for light-duty gasoline engines, and it

allows the NOx adsorber to store NOx for some period of time before the light-off time

of the three-way function of its catalyst, resulting in an overall lower effective

temperature for the device.

These first four tools available to manufacturers all deal with system design opportunities to

improve the cold-start performance of the NOx adsorber system. In addition, manufacturers

have several active tools that can be used to enhance the cold-start performance of the system, all

based on technologies that may be used to comply with the Tier 3 emission standards (i.e.,

technologies that will form the baseline for most engines meeting the Tier 4 standards). These

include the use of engine start-up routines that have a primary purpose of adding heat to the

exhaust to enhance NOx adsorber light-off. For example:

• retarded injection timing;
Regulatory Impact Analysis

4-34

• intake air throttling;

• post-injection addition of fuel; or

• or increasing back-pressure with an exhaust brake or a VGT system. 

We anticipate manufacturers will explore all these tools to choose the best combination

necessary to minimize light-off time and improve the cold-start NRTC performance. Highway

manufacturers must overcome this same challenge to comply with the HD2007 emission

standards some number of years before these nonroad emission standards go into effect. 

Additionally, highway manufacturers must do this with a higher cold-start weighting of 1/7,

rather than 1/20 we are adopting for nonroad diesel engines. This means that highway engine

manufacturers must have lower cold-start emissions relative to their hot-start emissions than will

nonroad engine manufacturers meeting the Tier 4 standards. We therefore believe that

manufacturers of nonroad diesel engines will be able to use the technologies described above to

comply with the Tier 4 standards over the NRTC, including the cold-start test.

One light-duty passenger car manufacturer, Toyota, has already demonstrated such an

approach to comply with light-duty cold-start requirements. Toyota has shown with its lowtemperature combustion technology one mechanism for raising exhaust temperatures even at

extremely low-load conditions. The approach, called Low Temperature Combustion (LTC),

increases exhaust temperatures at low-load conditions by more than 50/C while decreasing

engine-out NOx emissions.59 As a result, exhaust temperature are increased into the region for

effective NOx adsorber operation even at light loads. The technologies that Toyota uses to

accomplish LTC, cooled EGR and advanced common rail fuel systems, are similar to the

systems that we expect many nonroad engine manufacturers will use to comply with the Tier 3

standards.

Another example of system integration approaches for diesel engines designed to allow

compliance with transient emission control standards including hot and cold emissions can be

seen in recent work by the Department of Energy and contractors under the Advanced Petroleum

Based Fuels Program - Diesel Emission Control (APBF-DEC). This work documented in a

recent SAE paper and in EPA’s Highway Diesel Progress Review Report 2, shows that NOx

emission can be reduced adequately on a combined hot and cold start FTP test procedure to

demonstrate emissions below 0.3 g/bhp-hr.60,61 The work illustrates both the ability to control

NOx emissions under cold-start conditions using rapid warm-up procedures and the ability to

reduce NOx emissions below the regulated standards under hot-start conditions to compensate

for the slightly elevated emissions levels experienced under cold-start conditions.

How effective are NOx adsorbers over the NTE zone?

We are adopting an NTE standard for nonroad Tier 4 engines that replicates the provisions

for highway diesel trucks. A complete discussion of the NTE provisions can be found in Section

III.J of the preamble to the final rule. In short, we are setting an NTE emission limit, over a

broad range of engine operating conditions, that is 1.5 times the limit that applies for testing over
Technologies and Test Procedures for Low-Emission Engines

4-35

the NRTC and over the steady-state tests. As discussed below, a 90 percent NOx reduction is

technologically feasible across the range of engine operating conditions and ambient conditions

subject to the NTE standards. Also, as discussed below, some modifications to the NTE

provisions to address technical issues that result from the application of advanced NOx catalyst

systems were included in the HD2007 standards and are carried over into this final rule.

Section 4.1.2.3.5.2 contains a description of the ongoing NOx adsorber evaluation test

program run by our EPA laboratory. Included in that section are test data on four different NOx

adsorbers for which extensive steady-state mapping was performed to calculate various steadystate emission levels (See Figures 4.1-10 through 4.1-13). Several of the test modes presented in

these figure are not within the NTE zone for NOx, and so would not be subject to the NTE

standard. The following modes listed in these four figures are within the NTE zone for NOx: 

EPA modes 6 - 13, 15, 17, 19, 20. For all of the adsorbers, efficiencies of 90 percent or greater

were achieved across the majority of the NTE zone. The region of the NTE zone for which

efficiencies less than 90 percent were achieved were concentrated on or near the torque curve

(EPA modes 8, 9, 15 and 17), with the exception of Adsorber D, for which EPA modes 6 and 7

achieved 87 percent and 89 percent NOx reduction, respectively. However, Adsorber D was

able to achieve NOx reductions greater than 90 percent along the torque curve. The test modes

along the torque curve represent the highest exhaust gas temperature conditions for this test

engine, on the order of 500/C. Exhaust temperatures of 500/C are near the current upper

temperature limit of the peak NOx reduction efficiency range for NOx adsorbers. It is therefore

not unexpected that the NOx reductions along the torque curve for the test engine are not as high

as in other regions of the NTE zone. We expect manufacturers to choose a NOx adsorber

formulation that matches the operating range of exhaust gas temperatures for the engine. In

addition, the steady-state mode data in Figures 4.1-10 through 4.1-13 were collected under

stabilized conditions. In reality, actual in-use operation of a heavy-duty diesel vehicle likely

does not experience periods of sustained operation along the torque curve, which diminishes the

likelihood that the NOx adsorber bed itself will achieve temperatures in excess of 500/C. 

Regardless, as observed in our ongoing diesel progress review and documented in the 2002

diesel progress report, catalyst developers are realizing incremental improvements in the hightemperature NOx reduction capabilities of NOx adsorbers through improvements in NOx

adsorber formulations.62,63,64 As discussed above, only small improvements in the current

characteristics are necessary to achieve 90 percent NOx reductions or greater across the NTE

zone.

As discussed above, the use of advanced NOx adsorber-based catalyst systems will present

cold-start challenges for highway heavy-duty diesel engines, and for nonroad diesel engines,

under our Tier 4 program, similar to what light-duty gasoline manufacturers have faced in the

past, due to the light-off characteristics of the NOx adsorber. We have previously discussed the

tools available to engine manufacturers to overcome these challenges to achieve the NOx

standard. The majority of engine operation within the NTE zone will occur at exhaust gas

temperatures well above the light-off requirement of the NOx adsorbers. Figures 4.1-10 through

4.1-13 below show that all test modes within the NTE zone have exhaust gas temperatures

greater than 300/C, which is well within the peak NOx reduction efficiency range of current

generation NOx adsorbers. However, although NTE testing does not include engine start-up
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conditions, a diesel engine that has not been warmed up could conceivably be started and very

quickly be operated under conditions that are subject to NTE testing; for example, within a

minute or less of vehicle operation after the vehicle has left an idle state. The final rule specifies

a minimum emission sampling period of 30 seconds for NTE testing. Conceivably, vehicle

emissions could be measured against the NTE standards during that first minute of operation,

and in all likelihood it would not meet the NTE NOx standard. Given that the NRTC standards

will require control of cold-start emissions, manufacturers will be required to pay close attention

to cold start to comply with the NRTC. As discussed above, engine operation during NTE

testing will be at exhaust gas temperatures within the optimum NOx reduction operating window

of the NOx adsorbers. In addition, the NOx adsorber is capable of adsorbing NOx at

temperatures on the order of 100/C. Figures 4.1-10 through 4.1-13 all show NOx emission

reductions on the order of 70 - 80 percent are achieved at temperatures as low as 250/C. We are

therefore setting a threshold for exhaust gas temperatures of 250/C, below which the specified

NTE requirements do not apply; we also adopted this provision for the same reason for highway

engines in our HD2007 program.

The NTE requirements apply not only during laboratory conditions applicable to the transient

test, but also under the wider range of ambient conditions for altitude, temperature and humidity

specified in the regulations. These expanded conditions will have minimal impact on the

emission-control systems expected to be used to meet the NTE NOx standard. In general, it can

be said that the performance of the NOx adsorbers are only affected by the exhaust gas stream to

which the adsorbers are exposed. The impact of ambient humidity, temperature, and altitude will

therefore affect the performance of the adsorber only to the extent these ambient conditions

change the exhaust gas conditions (i.e., exhaust gas temperature and gas constituents). The

ambient humidity conditions subject to the NTE requirement will have minimal, if any, impact

on the performance of the NOx adsorbers. The exhaust gas itself, independent of the ambient

humidity, contains a very high concentration of water vapor, and the impact of the ambient

humidity on top of the products of dry air and fuel combustion are minimal. The effect of

altitude on NOx adsorber performance should also be minimal or negligible. NTE testing is

limited to altitudes below 5,500 feet above sea level. The decrease in atmospheric pressure at

5,500 feet should have minimal impact on the NOx adsorber performance. Increasing altitude

can decrease the air-fuel ratio for diesel engines, which can in turn increase exhaust gas

temperatures. However, as discussed in the final rule for the highway 2004 standards (Phase 1),

highway engines with Phase 1 technology (and thus the similar Tier 3 nonroad diesel engines)

can be designed to target air-fuel ratios at altitude that will maintain appropriate exhaust gas

temperatures within the ambient conditions specified by the highway NTE test procedure and

thus the similar NTE procedure for Tier 4 engines. This approach also allows manufacturers to

maintain engine-out PM emission levels near the 0.1 g/hp-hr level. Finally, the NTE regulations

specify ambient temperatures that are broader than the NRTC temperature range of 68-86/F. 

The NTE test procedure specifies no lower ambient temperature bounds. However, as discussed

above, we limit NTE requirements on NOx (and NMHC) for engines equipped with NOx (and/or

NMHC) catalysts to include only engine operation with exhaust gas temperatures greater than

250/C. Low ambient temperatures will therefore not present any difficulties for NTE NOx

compliance. NTE standards also apply under ambient temperatures that are higher than the

laboratory conditions. The NTE standards apply up to a temperature of 100/F at sea level, and
Technologies and Test Procedures for Low-Emission Engines

4-37

up to 86/F at 5,500 feet above sea level. At altitudes in between, the upper NTE ambient

temperature requirement is a linear fit between these two conditions. At 5,500 feet, the NTE

ambient temperature requirement is the same as the upper end of the temperature range (86/F)

for testing with prescribed duty cycles, and will therefore have no impact on the performance of

the NOx adsorbers, considering that majority of the test data described throughout this chapter

were collected under laboratory conditions. The NTE upper temperature limits at sea level is

100/F, which is 14/F (7.7/C) greater than the NRTC range. This increase is relatively minor, and

while it will increase the exhaust gas temperature; in practice the increase should be passed

through the engine to the exhaust gas, and the exhaust gas would be on the order of 8/C higher. 

Within the exhaust gas temperature range for a diesel engine during NTE operation, an 8/C

increase is very small. As discussed above, we expect manufacturers to choose an adsorber

formulation matched to a particular engine design and we expect the small increase in exhaust

gas temperature that can occur from the expanded ambient temperature requirements for the

NTE to be taken into account by manufacturers when designing the complete emission-control

system.

To summarize, based on the information presented in this chapter, and the analysis and

discussion presented in this section, we conclude the NTE NOx requirement (1.5 × NRTC/C1

standard) contained in this final rule will be feasible.

Further discussion of feasibility of the NOx requirement under transient testing conditions

can be found in Section 4.1.3.1.2.

4.1.2.3.4 Are Diesel NOx Adsorbers Durable?

The considerable success in demonstrating NOx adsorbers makes us confident that the

technology is capable of providing the level of conversion efficiency needed to meet the Tier 4

NOx standard. However, there are several engineering challenges that will need to be addressed

in going from this level of demonstration to implementation of durable and effective emissioncontrol systems on nonroad equipment. In addition to the generic need to optimize engine

operation to match the NOx adsorber performance, engine and catalyst manufacturers will

further need to address issues of system and catalyst durability. The nature of these issues are

well understood. The hurdles that must be overcome have direct analogues in technology issues

that have been addressed previously in automotive applications and are expected to be overcome

with many of the same solutions. With the transfer of highway technologies to nonroad engines

anticipated in this rulemaking, we believe we have already addressed the issues highlighted in

this section for highway engines well before the start of this nonroad program.

 In this section, we will describe the major technical hurdles that must be addressed to ensure

that the significant emission reductions from NOx adsorbers occur throughout the life of nonroad

diesel engines. This section is organized into separate durability discussions for the system

components (hardware) and various near-term and long-term durability issues for the NOx

adsorber catalyst itself.

4.1.2.3.4.1 NOx Adsorber Regeneration Hardware Durability
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The system we have described in Figure 4.1-1 represents but one possible approach for

generating the necessary exhaust conditions to allow for NOx adsorber regeneration and

desulfation. The system consists of three catalyst substrates (for a CDPF/Low Temperature NOx

Adsorber, a High Temperature NOx Adsorber and an Oxidation Catalyst), a support can that

partitions the exhaust flow through the first two catalyst elements, three fuel injectors, and a

means to divert exhaust flow through one or more of the catalyst partitions. Though not shown

in the figure, a NOx /O2 sensor is also likely to be needed for control feedback and on-board

diagnostics (OBD). All of these elements have already been applied in one form or another to

either diesel or gasoline engines in high volume long life applications.

The NOx adsorber system we described earlier borrows several components from the

gasoline three-way catalyst systems and benefits from the years of development on three way

catalysts. The catalyst substrates (the ceramic support elements on which a catalyst coating is

applied) have developed through the years to address concerns with cracking due to thermal

cycling and abrasive damage from vehicle vibration. The substrates applied for diesel NOx

adsorbers will be virtually identical to the ones used for today’s passenger cars in every way but

size. They are expected to be equally durable when applied to diesel applications as has already

been shown in the successful application of diesel oxidation catalysts (DOCs) on some diesel

engines over the last 15 years. Retrofit catalyst-based systems have similarly been applied to

nonroad diesel engines with good durability, as described in Section 4.1.3.2 below.

The NOx/O2 sensor needed for regeneration control and OBD is another component

originally designed and developed for gasoline powered vehicles (in this case lean-burn gasoline

vehicles) that are already well developed and can be applied with confidence in long life for

NOx adsorber-based diesel emission control. The NOx/O2 sensor is an evolutionary technology

based largely on the current Oxygen (O2) sensor technology developed for gasoline three-way

catalyst-based systems. Oxygen sensors have proven to be extremely reliable and long lived in

passenger car applications, which see significantly higher temperatures than are normally

encountered on a diesel engine.65,66 Diesel engines do have one characteristic that makes the

application of NOx/O2 sensors more difficult. Soot in diesel exhaust can cause fouling of the

NOx/O2 sensor damaging its performance. However this issue can be addressed through the

application of a catalyzed diesel particulate filter (CDPF) in front of the sensor. (See Section

4.1.2.3.2 above, noting synergies that can result from use in tandem of NOx adsorbers and

CDPFs.) The CDPF then provides a protection for the sensor from PM while not hindering its

operation. Since the NOx adsorber will likely be located downstream of a CDPF in each of the

potential technology scenarios we have considered this solution to the issue of PM sooting is

readily addressed.

Fuel is metered into a modern gasoline engine with relatively low pressure pulse-widthmodulated fuel-injection valves. These valves are designed to cycle well over a million times

over the life of a vehicle while continuing to accurately meter fuel. Applying this technology to

provide diesel fuel as a reductant for a NOx adsorber system is a relatively straightforward

extension of the technology. A NOx adsorber system cycles far fewer times over its life when

compared with the current long life of gasoline injectors. However, these gasoline fuel injectors
Technologies and Test Procedures for Low-Emission Engines

4-39

designed to meter fuel into the relatively cool intake of a car cannot be directly applied to the

exhaust of a diesel engine. In the testing done at NVFEL, a similar valve design was used that

had been modified in material properties to allow application in the exhaust of an engine. While

benefitting from the extensive experience with gasoline-based injectors a designer can therefore,

in a relatively straightforward manner, improve the characteristics of the injector to allow

application for exhaust reductant regeneration. Toyota has shown with its Avensis DPNR diesel

passenger car how to use a gasoline direct injection (GDI)-based fuel injector to inject diesel fuel

in the exhaust manifold of a diesel engine to allow for NOx adsorber regeneration and

desulfation.67

The NOx adsorber system we describe in Figure 4.1-1 requires a means to partition the

exhaust during regeneration and to control the relative amounts of exhaust flow between two or

more regions of the exhaust system. Modern diesel engines already employ a valve designed to

carry out this very task. Most modern turbochargers employ a wastegate valve that allows some

amount of the exhaust flow to bypass the exhaust turbine to control maximum engine boost and

limit turbocharger speed. These valves can be designed to be proportional, bypassing a specific

fraction of the exhaust flow to track a specified boost pressure for the system. Turbocharger

wastegate valves applied to heavy-duty diesel engines typically last the life of the engine in spite

of the extremely harsh environment within the turbocharger. This same valve approach can be

applied to accomplish the flow diversion required for diesel NOx adsorber regeneration and

desulfation. Since temperatures will typically be cooler at the NOx adsorber compared with the

inlet to the exhaust turbine on a turbocharger, the control valve should be equally reliable in this

application.

4.1.2.3.4.2 NOx Adsorber Catalyst Durability

In many ways a NOx adsorber, like other engine catalysts, acts like a small chemical process

plant. It has specific chemical processes that it promotes under specific conditions with different

elements of the catalyst materials. There is often an important sequence to the needed reactions

and a need to match process rates to keep this sequence of reactions going. Because of this need

to promote specific reactions under the right conditions early catalysts were often easily

damaged. This damage prevents or slows one or more the reactions causing a loss in emission

control. For example, contaminants from engine oil, like phosphorous or zinc, can attach to

catalysts sites partially blocking the site from the exhaust constituents and slowing reactions. 

Similarly, lead added to gasoline to increase octane levels bonds to the catalyst sites, causing

poisoning as well. Likewise, sulfur, which occurs naturally in petroleum products like gasoline

and diesel fuel, can poison many catalyst functions preventing or slowing the desired reactions. 

High exhaust temperatures experienced under some conditions can cause the catalyst materials to

sinter (thermally degrade) decreasing the surface area available for reactions to decrease. 

All of these problems have been addressed over time for the gasoline three-way catalysts,

resulting in the high efficiency and long life durability now typical of modern vehicles. To

accomplish this, changes were made to fuels and oils used in vehicles (e.g., lead additives

banned from gasoline, sulfur levels reduced in gasoline distillates, specific oil formulations for
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4-40

aftertreatment equipped cars), and advances in catalysts designs were needed to promote

sintering-resistant catalyst formulations with high precious-metal dispersion.

The wealth of experience gained and technological advancements made over the last 30 years

of gasoline catalyst development can now be applied to the development of the NOx adsorber

catalyst. The NOx adsorber is itself an incremental advancement from current three-way catalyst

technology. It adds one important additional component not currently used on three-way

catalysts, NOx storage catalyst sites. The NOx storage sites (normally alkali or alkaline earth

metals) allow the catalyst to store NOx emissions with extremely high efficiency under the leanburn conditions typical of the diesel exhaust. It also adds a new durability concern due to sulfur

storage on the catalyst. 

This section will explore the durability issues of the NOx adsorber catalyst applied to diesel

engines. It describes the effect of sulfur in diesel fuel on catalyst performance, the methods to

remove the sulfur from the catalyst through active control processes, and the implications for

durability of these methods. It then discusses these durability issues relative to similar issues for

existing gasoline three-way catalysts and the engineering paths to solve these issues. This

discussion shows that the NOx adsorber is an incremental improvement upon the existing threeway catalyst, with many of the same solutions for the expected durability issues.

Sulfur Poisoning of the NOx Storage Sites

The NOx adsorber technology is extremely efficient at storing NOx as a nitrate on the

surface of the catalyst, or adsorber (storage) bed, during lean operation. Because of the

similarities in chemical properties of SOx and NOx, the SO2 present in the exhaust is also stored

on the catalyst surface as a sulfate. The sulfate compound that is formed is significantly more

stable than the nitrate compound and is typically not released during the NOx release and

reduction step (NOx regeneration step) (i.e., it is stored preferentially to NOx). Since the NOx

adsorber is virtually 100 percent effective at capturing SO2 in the adsorber bed, sulfate

compounds quickly occupy the NOx storage sites on the catalyst thereby reducing and

eventually rendering the catalyst ineffective for NOx reduction (poisoning the catalyst).

Figure 4.1-3 shows the effect of sulfur poisoning of a NOx adsorber catalyst as reported by

the DOE DECSE program. The graph shows the NOx adsorber efficiency versus exhaust inlet

temperature under steady-state conditions for a diesel engine-based system. The three dashed

lines that overlap each other show the NOx conversion efficiency of the catalyst when sulfur has

been removed from the catalyst. The three solid lines show the effect of sulfur poisoning on the

catalyst at three different fuel sulfur levels over different periods of extended aging (up to 250

hours). From the figure, it can be seen that even with three ppm sulfur fuel a significant loss in

NOx efficiency can occur in as little as 250 hours. Further, it can be seen that quite severe sulfur

poisoning can occur with elevated fuel sulfur levels. Catalyst performance was degraded by

more than 70 percent over only 150 hours of operation when 30 ppm sulfur fuel was used.68
Technologies and Test Procedures for Low-Emission Engines

4-41

0

20

40

60

80

100

250 300 350 400 450 500

Catalyst Inlet Temperature [C]

NOx Conversion Efficiency [%]

DECSE II after desulfation (3-ppm) DECSE II before desulfation (3-ppm, 250 hrs aging)

DECSE II after desulfation (16-ppm) DECSE II before desulfation (16-ppm, 200 hrs aging)

DECSE II after desulfation (30-ppm) DECSE II before desulfation (30-ppm, 150 hrs aging)

Figure 4.1-3

Comparison of NOx Conversion Efficiency before and after Desulfation

The DECSE researchers drew three important conclusions from Figure 4.1-3: 

• Fuel sulfur, even at very low levels like three ppm, can limit the performance of the NOx

adsorber catalyst significantly.

• Higher fuel sulfur levels, like 30 ppm, dramatically increase the poisoning rate, further

limiting NOx adsorber performance. 

• Most importantly though, the figure shows that if the sulfur can be removed from the

catalyst through a desulfation (or desulfurization) event, the NOx adsorber can provide

high NOx control even after exposure to sulfur in diesel fuel. This is evidenced by the

sequence of the data presented in the figure. The three high conversion efficiency lines

show the NOx conversion efficiencies after a desulfation event that was preceded by the

sulfur poisoning and degradation shown in the solid lines.
Regulatory Impact Analysis

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It is clear from this data that higher fuel sulfur levels dramatically reduce the efficiency of

NOx adsorber catalysts. Sulfur accumulates in the NOx storage sites preventing their use for

NOx storage. In other words, they decrease the storage volume of the catalyst. The rate at

which sulfur fills NOx storage sites is expected to be directly proportional to the amount of

sulfur that enters the catalyst. A doubling in fuel-sulfur levels should therefore correspond to a

doubling in the SOx poisoning rate.

The design of a NOx adsorber will need to address accommodating an expected volume of

sulfur before experiencing unacceptable penalties in either lost NOx control efficiency or

increased fuel consumption due to more frequent NOx regenerations. The amount of operation

allowed before that limit is realized for a specific adsorber design will be inversely proportional

to fuel sulfur quantity. In the theoretical case of zero sulfur, the period of time before the sulfur

poisoning degraded performance excessively would be infinite. For a more practical fuel sulfur

level like the 10 ppm average expected with a 15 ppm fuel sulfur cap, the period of operation

before unacceptable poisoning levels have been reached is expected to be less than 40 hours

(with today’s NOx adsorber formulations).69

Future improvements in the NOx adsorber technology are expected due to its relatively early

state of development. Some of these improvements are likely to include improvements in the

kinds of materials used in NOx adsorbers to increase the means and ease of removing stored

sulfur from the catalyst bed. However, because the stored sulfate species are inherently more

stable than the stored nitrate compounds (from stored NOx emissions), we expect that future

NOx adsorbers will continue to be poisoned by sulfur in the exhaust. A separate sulfur release

and reduction cycle (desulfation cycle) will therefore always be needed to remove the stored

sulfur.

NOx Adsorber Desulfation

Numerous test programs have shown that sulfur can be removed from the catalyst surface

through a sulfur regeneration step (desulfation step) not dissimilar from the NOx regeneration

function.70,71,72,73,74,75 The stored sulfur compounds are removed by exposing the catalyst to hot

and rich (air-fuel ratio below the stoichiometric ratio of 14.5 to 1) conditions for a brief period. 

Under these conditions, the stored sulfate is released and reduced in the catalyst. This sulfur

removal process, called desulfation or desulfurization in this document, can restore the

performance of the NOx adsorber to near new operation.

Most of the information in the public domain on NOx adsorber desulfation is based upon

research done either in controlled bench reactors using synthetic gas compositions or on

advanced lean-burn gasoline engine vehicles. As outlined above, these programs have shown

that desulfation of NOx adsorber catalysts can be accomplished under certain conditions but the

work does not directly answer whether NOx adsorber desulfation is practical for diesel engine

exhaust conditions. The DECSE Phase II program answers that question. 

Phase II of the DECSE program developed and demonstrated a desulfurization (desulfation)

process to restore NOx conversion efficiency lost to sulfur contamination. The engine used in
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4-43

the testing was a high-speed direct-injection diesel selected to provide a representative source of

diesel exhaust and various exhaust temperature profiles to challenge the emission-control

devices. The desulfation process developed in the DECSE Phase II program controlled the airfuel ratio and catalyst inlet temperatures to achieve the high temperatures required to release the

sulfur from the device. Air-fuel ratio control was accomplished in the program with exhaust gas

recirculation (EGR) and a post-injection of fuel to provide additional reductants. Using this

approach the researchers showed that a desulfation procedure can be developed for a diesel

engine with the potential to meet in-service engine operating conditions and acceptable levels of

torque fluctuation. The NOx efficiency recovery accomplished in DECSE Phase II using this

approach is shown in Figure 4.1-3, above.

The effectiveness of NOx adsorber desulfation appears to be closely related to the

temperature of the exhaust gases during desulfation, the exhaust chemistry (relative air-fuel

ratio), and to the NOx adsorber catalyst formulation.76, 77 Lower air-fuel ratios (more available

reductant) works to promote the release of sulfur from the surface, promoting faster and more

effective desulfation. Figure 4.1-4 shows results from Ford testing on NOx adsorber conversion

efficiency with periodic aging and desulfation events in a control flow reactor test.78 The control

flow reactor test uses controlled gas constituents that are meant to represent the potential exhaust

gas constituents from a lean-burn engine. The solid line with the open triangles labeled “w/o

regen” shows the loss of NOx control over thirteen hours of testing without a desulfation event

and with eight ppm sulfur in the test gas (this is roughly equivalent to 240 ppm fuel sulfur,

assuming an air-fuel ratio for diesel engines of 30:1).79 From the figure it can be seen that

without a desulfation event, sulfur rapidly degrades the performance of the NOx adsorber

catalyst. The remaining two lines show the NOx adsorber performance with periodic sulfur

regeneration events timed at one-hour intervals and lasting for 10 minutes (a one-hour increment

on 240 ppm fuel sulfur is approximately equivalent to 34 hours of operation on 7 ppm fuel). The

desulfation events were identical to the NOx regeneration events, except that the desulfation

events occurred at elevated temperatures. The base NOx regeneration temperature for the testing

was 350/C. The sulfur regeneration, or desulfation, event was conducted at two different gas

temperatures of 550/C and 600/C to show the effect of exhaust gas temperature on desulfation

effectiveness, and thus NOx adsorber efficiency. From Figure 4.1-4 it can be seen that, for this

NOx adsorber formulation, the NOx recovery after desulfation is higher for the desulfation event

at 600/C than at 550/C.
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60%

65%

70%

75%

80%

85%

90%

95%

1 2 3 4 5 6 7 8 9 10 11 12 13 14

# of SOx and DeSOx events (1hr periods)

%NOx Efficiency

Tr = 600° C

Tr = 550° C

w/o regen

Figure 4.1-4

Flow Reactor Testing of a NOx Adsorber with Periodic Desulfations

As suggested by Figure 4.1-4, it is well known that the rate of sulfur release (also called

sulfur decomposition) in a NOx adsorber increases with temperature.80,81 However, while

elevated temperatures directionally promote more rapid sulfur release, they also can directionally

promote sintering of the precious metals in the NOx adsorber washcoat. The loss of conversion

efficiency due to exposure of the catalyst to elevated temperatures is referred to as thermal

degradation in this document.

Thermal Degradation

The catalytic metals that make up most exhaust emission-control technologies, including

NOx adsorbers, are designed to be dispersed throughout the catalyst into as many small catalyst

“sites” as possible. By spreading the catalytic metals into many small catalyst sites, rather than

into a fewer number large sites, catalyst efficiency is improved. This is because smaller catalyst

sites have more surface area per mass, or volume, of catalyst when compared with larger catalyst

sites. Since most of the reactions being promoted by the catalyst occur on the surface, increasing

surface area increases catalyst availability and thus conversion efficiency. While high dispersion

(many small catalyst sites) is in general good for most catalysts, it is even more beneficial to the

NOx adsorber catalyst because of the need for the catalytic metal sites to perform multiple tasks. 

NOx adsorber catalysts typically rely on platinum to oxidize NO to NO2 prior to adsorption of
Technologies and Test Procedures for Low-Emission Engines

4-45

the NO2 on an adjacent NOx storage site. Under rich operating conditions, the NOx is released

from the adsorption site, and the adjacent platinum (or platinum + rhodium) catalyst site can

serve to reduce the NOx emissions into N2 and O2. High dispersion, combined with NO

oxidation, NOx storage and NOx reduction catalyst sites being located in close proximity,

provide the ideal catalyst design for a NOx adsorber catalyst. But high temperatures, especially

under oxidizing conditions, can promote sintering of the platinum and other PGM catalyst sites,

permanently decreasing NOx adsorber performance.

Catalyst sintering is a process by which adjacent catalyst sites can “melt” and regrow into a

single larger catalyst site (crystal growth). The single larger catalyst site has less surface area

available to promote catalytic activity than the original two or more catalyst sites that were

sintered to form it. This loss in surface area decreases the efficiency of the catalyst.82 High

temperatures, promote sintering of platinum catalysts especially under oxidizing conditions.83 It

is therefore important to limit the exposure of platinum-based catalysts to high exhaust

temperatures especially during periods of lean operation. Consequently, the desire to promote

rapid desulfation of the NOx adsorber catalyst technology by maximizing the desulfation

temperature and the need to limit the exposure of the catalyst to the high temperatures that

promote catalyst sintering must be carefully balanced. An example of this tradeoff can be seen

in Figure 4.1-5, which shows the NOx conversion efficiency of three NOx adsorber catalysts

evaluated after extended periods of sulfur poisoning followed by sulfur regeneration periods.84

The three catalysts (labeled A, B, and C) are identical in formulation and size but were located at

three different positions in the exhaust system of the gasoline direct injection engine used for this

testing. Catalyst A was located 1.2 meters from the exhaust manifold, catalyst B 1.8 meters from

the exhaust manifold and catalyst C was located 2.5 meters from the exhaust manifold. Locating

the catalysts further from the engine lowered the maximum exhaust temperature and thus catalyst

bed temperature experienced during the programmed sulfur regeneration cycle. Catalyst A

experienced the highest catalyst bed temperature of 800/C, while catalyst C experienced the

lowest catalyst bed temperature of 650/C. Catalyst B experienced a maximum catalyst bed

temperature of 730/C. Figure 4.1-5 shows that there is an optimum desulfation temperature that

balances the tradeoffs between rapid sulfur regeneration and thermal degradation (thermal

sintering) at high temperatures. 
Regulatory Impact Analysis

4-46

Influence of Maximum Temperature in Durability Cycle on Engine Bench

0%

20%

40%

60%

80%

100%

600 650 700 750 800 850

Maximum Catalyst Bed Temperature (°C) in Durability Cycle

From SAE 1999-01-3501 Figure 7 

NOx Conversion (%) at 350°C

Aging Time:

100 hours

C

A

B Lower Temperatures Decrease

Sulfur Deconposition Rates and

the Effective Period of Desulfation

High Temperatures Promote

Sulfate Decomposition but 

Increase Precious Metal Sintering

Figure 4.1-5

Influence of Maximum Catalyst Bed Temperature During Desulfation

The DECSE Phase II program, in addition to investigating the ability of a diesel engine /

NOx adsorber-based emission-control system to desulfate, provides a preliminary assessment of

catalyst durability when exposed to repeated aging and desulfurization cycles. Two sets of tests

were completed using two different fuel sulfur levels (three ppm and 78 ppm) to investigate

these durability aspects. The first involved a series of aging, performance mapping,

desulfurization and performance mapping cycles. An example of this testing is shown in Figure

4.1-6. The graph shows a characteristic “sawtooth” pattern of gradual sulfur poisoning followed

by an abrupt improvement in performance after desulfation. The results shown in Figure 4.1-6

are for two identical catalysts one operated on 3 ppm sulfur fuel (catalyst S5) and the other

operated on 78 ppm sulfur fuel (catalyst S7). For the catalyst operated on 3 ppm sulfur fuel the

loss in performance over the ten hours of poisoning is noted to be very gradual. There appears to

be little need to desulfate that catalyst at the ten-hour interval set in the experiment. In fact it can

be seen that in several cases the performance after desulfation is worse than prior to desulfation. 

This suggests, as discussed above, that the desulfation cycle can itself be damaging to the

catalyst. In actual use, we would expect an engine operating on 3 ppm sulfur fuel not to

desulfate until well beyond a ten-hour interval and be engineered to better withstand the damage

caused by desulfation, as discussed later in this section. For the catalyst operated on 78 ppm

sulfur fuel the loss in performance over the ten-hour poisoning period is dramatic. To ensure

continued high performance when operating on 78 ppm sulfur fuel, the catalyst requires frequent
Technologies and Test Procedures for Low-Emission Engines

4-47

desulfations. From the figure it can be inferred that the desulfation events need to be spaced at

intervals as short as one to two hours to maintain acceptable performance.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50

Time (hours) cycle of 10 hrs Sulfur Aging / 6 min Desulfation

NOx Reduction (%) 

DECSE Catalyst S7

- Aged on 78 ppm S

DECSE Catalyst S5

- Aged on 3 ppm S

Aging 10 hrs

of 78 ppm fuel

Desulfation

Aging Aging Aging Aging Desulfation Desulfation Desulfation

Aging 10 hrs

of 3 ppm fuel

Figure 4.1-6

Integrated NOx Conversion Efficiency following Aging and Desulfation

As a follow on to the work shown in Figure 4.1-6, the desulfation events were repeated an

additional 60 times without sulfur aging between desulfation events. This was done to

investigate the possibility of deleterious affects from the desulfation event itself even without

additional sulfur poisoning. As can be seen in Figure 4.1-7, the investigation did reveal that

repeated desulfation events even without additional sulfur aging can cause catalyst deterioration. 

As described previously, high temperatures can lead to a loss in catalyst efficiency due to

thermal degradation (sintering of the catalytic metals). This appears to be the most likely

explanation for the loss in catalyst efficiency shown here. For this testing, the catalyst inlet

temperature was controlled to approximately 700/C; however, the catalyst bed temperatures may

have been higher.85

Based on the work in DECSE Phase II, the researchers concluded that:

• The desulfurization procedure developed has the potential to meet in-service engine

operating conditions and to provide acceptable driveability conditions.
Regulatory Impact Analysis

4-48

• Although aging with 78 ppm sulfur fuel reduced NOx conversion efficiency more than

aging with three ppm sulfur fuel as a result of sulfur contamination, the desulfurization

events restored the conversion efficiency to nearly the same level of performance. However,

repeatedly exposing the catalyst to the desulfurization procedure developed in the program

caused a continued decline in the catalyst’s desulfated performance.

• The rate of sulfur contamination during aging with 78 ppm sulfur fuel increased with

repeated aging / desulfurization cycles (from 10 percent per ten hours to 18 percent per ten

hours). This was not observed with the three ppm sulfur fuel, where the rate of decline

during aging was fairly constant at approximately two percent per ten hours. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70

Desulfation Events (# of desulfation cycles)

NOx Efficiency after Desulfation 

(%NOx Reduction)

DECSE Catalyst S7

DECSE Catalyst S8

Figure 4.1-7

Integrated NOx Conversion Efficiency after Repeated Desulfation

Currently available data on NOx adsorber formulations show clearly that sulfur can be

removed from the surface of the NOx adsorber catalyst. The initial high performance after a

desulfation event is then degraded over time by the presence of sulfur until the next desulfation

event. The resulting characteristic NOx adsorber performance level over time exhibits a sawtooth pattern with declining performance followed by rapid recovery of performance following

desulfation. The rate of this decline increases substantially with higher fuel sulfur levels. Tto

ensure a gradual and controllable decline in performance, fuel sulfur levels must be minimized. 
Technologies and Test Procedures for Low-Emission Engines

4-49

However, even given very low fuel sulfur levels, gradual decline in performance must be

periodically overcome. The development experience so far shows that diesel engines can

accomplish the required desulfation event. The circumstances that effectively promote rapid

desulfation also promote thermal degradation. It will therefore be important to limit thermal

degradation. 

Limiting Thermal Degradation

The issue of thermal degradation of NOx adsorber catalyst components is similar to the

thermal sintering issues faced by light-duty three-way catalysts for vehicles developed to meet

current California LEV and future Federal Tier 2 standards using platinum+rhodium (Pt+Rh)

catalysts. Initial designs were marked by unacceptable levels of platinum sintering that limited

the effectiveness of Pt+Rh catalysts. This problem has been overcome through modifications to

the catalyst supports and surface structures that stabilize the precious metals at high temperatures

(>900 /C). Stabilization of ceria components using Zirconium (Zr) has pushed the upper

temperature limits of ceria migration to well over 1000 /C.86, 87 Stabilization components can

function in different ways. Some are used to “fill” structural vacancies, for example “open”

locations within a crystalline lattice, thus strengthening the lattice structure. Such strengthening

of crystalline lattice structures is particularly important at high temperatures. Other types of

stabilizing components can act as obstructions within a matrix to prevent migration of

components, or can enhance the mobility of other molecules or atoms, such as oxygen. An

approach stabilizing NOx adsorber catalyst components similar to the approaches taken with

LEV three-way catalyst designs should help to minimize thermal sintering of components during

desulfation.

In many ways, limiting the thermal degradation of the NOx adsorber catalyst should be easier

than for the gasoline three-way catalyst. Typical exhaust gas temperatures for a heavy light-duty

gasoline truck (e.g., a Ford Expedition) commonly range from 450/C to more than 800/C during

normal operation.88 A heavy-duty diesel engine in contrast rarely has exhaust gas temperatures

in excess of 500/C. Further, even during the desulfation event, exhaust temperatures are

expected to be controlled below 700/C. The NOx adsorber applied to diesel engines is therefore

expected to see both lower average temperatures and lower peak temperatures when compared

with an equivalent gasoline engine. Once thermal degradation improvements are made to NOx

adsorber catalysts, thermal degradation will reasonably be expected to be less than the level

predicted for future Tier 2 gasoline applications.

In addition to the means to improve the thermal stability of the NOx adsorber by applying

many of the same techniques being perfected for the Tier 2 gasoline three-way catalyst

applications, an additional possibility exists that the desulfation process itself can be improved to

give both high sulfur removal and to limit thermal degradation. The means to do this might

include careful control of the maximum temperature during desulfation to limit the exposure to

high temperatures. Also, improvements in how the regeneration process occurs may provide

avenues for improvement. Low air-fuel ratios (high levels of reductant) are known to improve

the desulfation process. The high level of reductant may also help to suppress oxygen content in

the exhaust to further limit thermal degradation.
Regulatory Impact Analysis

4-50

Researchers at Ford Scientific Research Labs have investigated NOx adsorber catalyst

desulfation (called DeSOx in their work) to answer the question: “if a regeneration process

(sulfur regeneration) is required periodically, will the high temperatures required for the

regeneration have deleterious, irreversible effects on NOx efficiency?” To explore the issue of

NOx adsorber durability after repeated desulfation events, Ford conducted repeated sequential

sulfur poisoning and desulfation cycles with a NOx adsorber catalyst. The results of their

experiment are shown in Figure 4.1-8.89 As shown in Figure 4.1-8, the NOx adsorber sample

underwent more than 90 poisoning and desulfation cycles with 12 hours occurring between the

end of one desulfation to the end of the next desulfation without a measurable loss in postdesulfation performance. This testing was done using a laboratory tool called a pulsator, used to

study ceramic monolith catalyst samples. The ceramic test samples were heated to between

700/C and 750/C. These results indicate that for some combinations of temperatures and

reductant chemistries the NOx adsorber can be repeatedly desulfated without a significant loss in

NOx reduction efficiency. This work indicates that it is possible to optimize the desulfation

process to allow for adequate sulfur removal without a significant decrease in NOx reduction

efficiency.

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90

DeSOx event

% NOx sorption

Figure 4.1-8

Repeated Sulfur Poisoning and Desulfation on a Bench Pulsator

These results indicate that, with further improvements to the NOx adsorber catalyst design

incorporating the experience gained on gasoline three-way catalysts and continuing

improvements in the control of the desulfation, degradation of the NOx adsorber catalyst with

each desulfation event can be limited. However, the expectation remains that there will be some
Technologies and Test Procedures for Low-Emission Engines

4-51

level of deterioration with desulfation that must be managed to ensure long-term high efficiency

of the NOx adsorber. This means that the number and frequency of desulfation events must be

kept to a minimum. The key to this is to limit the amount of sulfur to which the catalyst is

exposed over its life. In this way, the deterioration in performance between desulfation events is

controlled at a gradual rate and the period between desulfations can be maximized to limit

thermal degradation. 

Overall System Durability

NOx emission control with a NOx adsorber catalyst-based systems is an extension of the

very successful three-way catalyst technology. NOx adsorber technology is most accurately

described as incremental and evolutionary with system components that are straightforward

extensions of existing technologies. The technology therefore benefits substantially from the

considerable experience gained over the past 30 years with the today’s highly reliable and

durable three-way catalyst systems.

The following observations can be made from the data provided in the preceding sections on

NOx adsorber durability:

• NOx adsorber catalysts are poisoned by sulfur in diesel fuel, even at fuel sulfur levels as

low as three ppm.

• A sulfur regeneration event (desulfation) can restore NOx adsorber performance.

• A diesel engine can produce exhaust conditions that are conducive to desulfation.

• Desulfation events, which require high catalyst temperatures, can cause sintering of the

catalytic metals in the NOx adsorber, thereby reducing NOx-control efficiency.

• The means exist from the development of gasoline three-way catalysts to improve the

NOx adsorber’s thermal durability.

• In carefully controlled experiments, NOx adsorbers can be desulfated repeatedly without

an unacceptable loss in performance.

• The number and frequency of desulfation events must be limited to ensure any gradual

thermal degradation over time does not excessively deteriorate the catalyst.

Based on these observations, we are confident that NOx adsorber technology for HD2007

and later engines will be durable over the life of heavy-duty diesel vehicles, provided that the

engines use fuel with a 15 ppm sulfur cap and that the technology will prove to be similarly

durable when applied some years later to nonroad diesel engines to comply with the Tier 4

emission standards. Without the use of this low-sulfur fuel, we can no longer be confident that

the increased number of desulfation cycles that will be required to address the impact of sulfur

on efficiency can be accomplished without unrecoverable thermal degradation and thus loss of
Regulatory Impact Analysis

L

 Toyota requires that their lean-burn gasoline engines equipped with NOx adsorbers are fueled on premium

gasoline in Japan, which has an average sulfur content of six ppm.

4-52

NOx adsorber efficiency. Limiting the number and frequency of these deleterious desulfation

events through the use of diesel fuel with sulfur content less than 15 ppm allows us to conclude

with confidence that NOx adsorber catalysts will be developed that are durable throughout the

life of a nonroad diesel engine.

4.1.2.3.5 Current Status of NOx Adsorber Development

NOx adsorber catalysts were first introduced in the power generation market less than five

years ago. Since then, NOx adsorber systems in stationary source applications have enjoyed

considerable success. In 1997, the South Coast Air Quality Management District of California

determined that a NOx adsorber system provided the “Best Available Control Technology” NOx

limit for gas turbine power systems.90 Average NOx control for these power generation facilities

is in excess of 92 percent.91 A NOx adsorber catalyst applied to a natural gas fired powerplant

has demonstrated better than 99 percent reliability for more than 21,000 hours of operation while

controlling NOx by more than 90 percent.92 The experience with NOx adsorbers in these

stationary power applications shows that NOx adsorbers can be highly effective for controlling

NOx emissions for extended periods of operation with high reliability.

4.1.2.3.5.1 Lean-Burn Gasoline Engines

The NOx adsorber’s ability to control NOx under oxygen-rich (fuel-lean) operating

conditions has led industry to begin applying NOx adsorber technology to lean-burn engines in

mobile source applications. NOx adsorber catalysts have been developed and are now in

production for lean-burn gasoline vehicles in Japan, including several vehicle models sold by

Toyota Motor Corporation.L

 The 2000 model year saw the first application of this technology in

the United States with the introduction of the Honda Insight, certified to the California LEV-I

ULEV category standard. Table 4.1-6 lists some of the 2002 European lean-burn direct-injection

gasoline vehicles that use NOx adsorber catalyst technology.93 These lean-burn gasoline

applications are of particular interest because they are similar to diesel vehicle applications in

terms of lean-NOx storage and the need for periodic NOx regeneration under transient driving

conditions. The fact that they have been successfully applied to these mobile source applications

shows clearly that NOx adsorbers can work under transient conditions provided that engineering

solutions can be found to periodically cause normally lean-burn exhaust conditions to operate in

a rich regeneration mode.
Technologies and Test Procedures for Low-Emission Engines

4-53

Model Displacement(liter) Power(KW/PS)

Audi A2 FSI 1.6 81/110

Audi A4 FSI 2 110/150

BMW 760 iL 6 ca. 300/408

Citroen C5 HPI 2 103/140

Mercedes CLK 200 CGI 1.8 125/170

Mercedes C 200 CGI 1.8 125/170

Mitsubishi Carisma GDI 1.8 90/122

Mitsubishi Space Star GDI 1.8 90/122

Mitsubishi Space Wagon 2.4 GDI 2.4 108/147

Mitsubishi Space Runner 2.4 GDI 2.4 110/150

Mitsubishi Galant 2.4 GDI 2.4 106/144

Mitsubishi Pajero Pinin 2.0 GDI 2 90/122

Mitsubishi Pajero 3.2 V6 GDI 3.5 149/202

Peugeot 406 HPI 2 103/140

VW Lupo FSI 1.4 77/105

VW Polo FSI 1.4 63/85

VW Golf FSI 1.6 81/110

VW Bora FSI 1.6 81/110

Volvo S40 1.8 1.6 90/122

Table 4.1-6 2002 European Lean-Burn Gasoline Direct-Injection Engines 

4.1.2.3.5.2 EPA National Vehicle and Fuel Emissions Laboratory

As part of an ongoing effort to evaluate the rapidly developing state of this technology, the

Manufacturers of Emission Control Association (MECA) have provided numerous NOx

adsorber catalyst formulations to EPA for evaluation. Testing of some of these catalysts at

NVFEL revealed that formulations were capable of reducing NOx emissions by more than 90

percent over the broad range of operation in the highway steady-state SET procedure (sometimes

called the EURO 4 test). At operating conditions representative of “road-load” operation for a

highway trucks, the catalysts showed NOx reductions as high as 99 percent resulting in NOx

emissions well below 0.1 g/hp-hr from an engine-out level of nearly 5 g/hp-hr. Figure 4.1-9

shows an engine torque vs. speed map with the various steady-state test modes used in this

testing as well as the 8 modes of the ISO-C1 cycle used for nonroad certification. Though not

included in the test results shown in Figures 4.1-10 through 4.1-12, the ISO-C1 modes are

closely approximated by some other test modes, as can be seen in Figure 4.1-9. We therefore

expect similarly good performance on the ISO-C1 test modes. Testing on the highway transient

test procedure has shown similarly good results, with hot-start NOx emissions over the highway

FTP cycle reduced by more than 90 percent. These results demonstrate that significant NOx

reductions are possible over a broad range of operating conditions with current NOx adsorber

technology, as typified by the highway FTP cycle and the SET procedure. 

The test program at NVFEL can be divided into phases. The first phase began with an

adsorber screening process using a single leg of the planned dual-leg system. The goals of this

screening process, a description of the test approach, and the results are described below. The
Regulatory Impact Analysis

4-54

next phase of the test program consisted of testing the dual-leg system on a more advanced Tier

3 like diesel engine (i.e., with common rail fuel system and cooled EGR) using a NOx adsorber

chosen during the first phase in each of two legs. The current ongoing phase is working on

improved systems approaches including a demonstration of an improved package four “leg”

system.

Testing Goals—Single-Leg NOx Adsorber System

The goal of the NOx adsorber screening process was to evaluate available NOx adsorber

formulations from different manufacturers with the objective of choosing an adsorber with 90

percent or better NOx reduction for continued evaluation. To this end, four different adsorber

formulations were provided from three different suppliers. Since this was a screening process

and since a large number of each adsorber formulation would be required for a full dual-leg

system, it was decided to run half of a dual-leg system (a single-leg system) and mathematically

correct the emissions and fuel economy impact to reflect a full dual-leg system. The trade-off

was that the single-leg system would be able to run only steady-state modes, as the emissions

could not be corrected over a transient cycle. The configuration used for this test was similar to

that shown in Figure 4.1-1, but with a catalyst installed only on one side of the system.

Test Approach—Single-Leg NOx Adsorber System

The single-leg system consisted of an exhaust brake, a fuel injector, CDPF, and a NOx

adsorber in one test leg. The other leg, the “bypass leg,” consisted of an exhaust brake that

opened when the test-leg brake was closed; this vented the remainder of the exhaust out of the

test cell. Under this setup, the test leg, i.e., the leg with the adsorber, was directed into the

dilution tunnel where the emissions were measured and then compensated to account for

emissions from the bypass leg. The restriction in the bypass leg was set to duplicate the

backpressure of the test leg so that, while bypassing the test leg to conduct a NOx regeneration,

the backpressure of the bypass leg simulated the presence of a NOx adsorber system. A clean-up

diesel oxidation catalyst (DOC) downstream of the NOx adsorber was not used for this testing.

The measured emissions had to be adjusted to account for the lack of any NOx adsorber in

the bypass leg. For this correction, it was assumed that the bypass leg’s missing (virtual)

adsorber would adsorb only while the actual leg was regenerating. It was also assumed the

virtual adsorber would have regeneration fuel requirements in proportion to its adsorbing time. 

The emission-control performance of the virtual adsorber was assumed to be the same as the

performance of the actual adsorber. With these assumptions, the gaseous emissions could be

adjusted.94

Test Results—Single-Leg NOx Adsorber System
Technologies and Test Procedures for Low-Emission Engines

M The AVL 8 mode test procedure is a steady-state test procedure developed by Anstalt für

Verbrennungskraftmaschinen, Prof. Dr. Hans List (or Institute for Internal Combustion Engines) to approximate

emission levels that would occur while operating the engine over the transient highway FTP cycle.

4-55

Two sets of steady-state modes were run with each adsorber formulation. These modes

consisted of the SET modes and the AVL 8 mode composite FTP prediction.M The modes are

illustrated in Figure 4.1-9 and are numbered sequentially one through 20 to include both the

eight AVL modes and the 13 SET modes (the idle mode is repeated in both tests). The mode

numbers shown in the figure are denoted as “EPA” modes in the subsequent tables to

differentiate between the AVL and SET modes that have duplicate mode numbers. The highway

NTE zone (which is the same as the nonroad NTE zone) is also shown in Figure 4.1-9 to show

that these two sets of modes give comprehensive coverage of the NTE zone. The ISO C1

steady-state modes used for nonroad engines are closely represented by the test modes shown

here. The only C1 mode not well represented is the 10 percent load point (ISO Mode 5), which

is outside of the nonroad NTE zone. The modes were run with varying levels of automation,

with the general strategy being to inject sufficient fuel during regeneration to obtain a lambda at

or slightly fuel-rich of stoichiometric (8 #1). The NOx regenerations were then timed to achieve

the desired NOx reduction performance. The adsorber formulations were identified as A, B, D,

and E. Prior to testing, each set of adsorbers were aged at 2500 rpm, 150 lb-ft for 40 minutes,

then 2500 rpm full load for 20 minutes, repeated for a total of 10 hours.

0

100

200

300

400

500

600

700

800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800

Speed (rpm)

Torque (lb-ft)

Torque

NOx NTE

PM NTE

AVL Modes

SET modes

ISO C-1 Modes

1

2

3

4

9

13

12

14 16

15

11

10

17

8

19

20

18

7

5

6

ISO Mode 11

ISO Mode 6

ISO Mode 7

ISO Mode 8

ISO Mode 1

ISO Mode 2

ISO Mode 3

ISO Mode 5

Figure 4.1-9 Steady-State Test Modes from NVFEL Testing and ISO C-1 Modes
Regulatory Impact Analysis

4-56

The SET and AVL Composite emission results, along with the NOx reduction performance

vs. adsorber inlet temperature, are shown in Figures 4.1-10 through 4.1-13 for each of the tested

NOx adsorber formulations. The SET composites for all four adsorber formulations had NOx

reductions in excess of 90 percent with under a three percent impact on fuel economy. The HC

emissions varied most widely, most likely due to differences in regeneration strategies, and to

some extent, adsorber formulation. The HC emissions with the exception of adsorber “A” were

very good, less than 0.1 g/hp-hr over the SET and less than 0.2 g/hp-hr over the AVL composite. 

Note that no DOC was used to clean up the HC emissions.

Another point to note is that the EPA mode 1 (ISO-C1 Mode 11) data for each composite is

the same. This is because EPA mode 1, low idle, is too cold for effective steady-state

regeneration, but efficient NOx adsorption can occur for extended periods of time. (Note that the

exhaust temperature at idle is well below the NTE threshold of 250/C discussed earlier.) For

either of these composite tests, a regeneration would not be needed under such conditions. EPA

mode 1 has very little impact on either composite in any case because of the low power and

emission rate. EPA mode 2 also had very low steady-state temperatures, and the difficulty

regenerating at this mode can be seen in the impacts on HC emissions and on fuel economy. 

But, like EPA mode 1, the engine would adsorb during EPA mode 2 for extended periods

without needing regeneration. None of the ISO-C1 modes, other than the idle mode, are similar

to EPA mode 2. Further, no attempt was made to apply new combustion approaches such as the

Toyota low-temperature combustion technology to raise exhaust temperatures at these operating

modes.

The AVL composite showed greater differences between the adsorber formulations than the

SET. Three of the adsorbers achieved greater than 90 percent NOx reduction over the AVL

composites with the other adsorber at 84 percent NOx reduction. The greater spread in NOx

reduction performance was, in part, due to this composite’s emphasis on EPA mode 8, which

was at the upper end of the NOx reduction efficiency temperature window. Adsorber E had an

EPA mode 8 NOx reduction of 66 percent, and the NOx reduction efficiency vs. inlet

temperature graph clearly shows that this formulation’s performance falls off quickly above

450/C. In contrast, the other formulations do not show such an early, steep loss in performance. 

The fuel economy impacts vary more widely also, partly due to the test engineers’ regeneration

strategies, particularly with the low-temperature modes, and to the general inability to regenerate

at very low-temperature modes at steady-state. Note also that none of the regeneration strategies

here can be considered fully optimized, as they reflect the product of trial and error

experimentation by the test engineers. With further testing and understanding of the technology

a more systematic means for optimization should be possible. In spite of the trial and error

approach the results shown here are quite promising.

The AVL composite was developed as a steady-state test that would predict engine-out

emission levels over the transient highway FTP cycle. As discussed in 4.1.3.1.2 below, NOx

adsorber control effectiveness is projected to be more effective over the NRTC than over the

highway FTP cycle. The AVL cycle loses some accuracy when testing engines with NOx

adsorbers, since regeneration does not occur at the low-temperature modes (EPA modes 1, 2, 5). 

In real-world conditions, diesel engines do not come to steady-state temperatures at any of these
Technologies and Test Procedures for Low-Emission Engines

4-57

modes, and the adsorber temperatures will be higher at EPA modes 1, 2, and 5 than the stabilized

steady-state values used for this modal testing. Consequently, the actual performance over a

transient duty cycle should be much better than the composites would suggest (see the discussion

of transient testing below).

Based on the composite data and the temperature performance charts, amongst other factors,

adsorber formulation B was chosen for further dual-leg performance work. Both composites for

this formulation were well above 90 percent. The NOx vs. temperature graph, Figure 4.1-11,

also shows that this formulation was a very good match for this engine.
Regulatory Impact Analysis

4-58

Base

EPA SET SET Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 15% Idle 0 13.0 144 0.16 100% 0.00 0.0%

9 2 8% 1619 630 4.6 461 0.11 98% 0.92 2.4%

10 3 10% 1947 328 4.7 357 0.07 98% 1.02 2.0%

11 4 10% 1947 493 5.0 411 0.06 99% 1.35 2.6%

12 5 5% 1619 332 5.0 384 0.13 97% 0.11 1.3%

13 6 5% 1619 498 5.0 427 0.24 95% 0.81 1.6%

14 7 5% 1619 166 5.5 287 0.25 95% 1.39 3.3%

15 8 9% 1947 630 4.0 498 0.89 78% 0.36 1.9%

16 9 10% 1947 164 5.0 293 0.14 97% 1.88 4.1%

17 10 8% 2275 599 4.0 515 0.48 88% 1.12 3.8%

18 11 5% 2275 150 4.8 282 0.42 91% 0.68 3.5%

19 12 5% 2275 450 5.0 404 0.08 98% 0.62 3.0%

20 13 5% 2275 300 4.8 357 0.14 97% 0.70 2.8%

Composite Results 4.6 0.31 93% 0.91 * 2.6% *

Adsorber

Base

EPA AVL AVL Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 42% Idle 0 13.00 144 0.16 100% 0.00 0.0%

2 2 8% 987 86 8.80 172 0.83 91% 0.75 7.7%

3 3 3% 1157 261 8.40 346 0.36 96% 1.10 3.1%

4 4 4% 1344 435 5.90 430 0.20 97% 2.16 3.0%

5 5 10% 2500 94 5.50 286 0.37 93% 4.93 3.6%

6 6 12% 2415 228 4.60 325 0.08 98% 2.30 3.6%

7 7 12% 2415 394 4.90 386 0.10 98% 2.38 3.1%

8 8 9% 2313 567 4.10 505 1.06 74% 0.03 1.9%

Composite Results 4.9 0.44 91% 1.69 * 2.9% *

* HC results & FE Impacts do not reflect future potential as they are derived using a 5 g NOx engine which requires more frequent NOx regens 

than would result using a 2.5 g engine and the tested system was not a fully optimized engine & emission control system.

Adsorber

0%

20%

40%

60%

80%

100%

200 250 300 350 400 450 500 550

Adsorber Inlet Temperature (C)

NOx Reduction Efficiency (%)

Figure 4.1-10. SET & AVL Composites, and Temperature vs.

NOx Chart for Adsorber A
Technologies and Test Procedures for Low-Emission Engines

4-59

Base

EPA SET SET Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 15% Idle 0 13.0 144 0.16 100% 0.00 0.0%

9 2 8% 1619 630 4.6 498 0.18 96% 0.01 1.2%

10 3 10% 1947 328 4.7 366 0.07 98% 0.04 0.5%

11 4 10% 1947 493 5.0 446 0.14 97% 0.01 1.5%

12 5 5% 1619 332 5.0 375 0.06 99% 0.08 0.7%

13 6 5% 1619 498 5.0 420 0.07 98% 0.10 2.3%

14 7 5% 1619 166 5.5 296 0.18 97% 0.10 0.3%

15 8 9% 1947 630 4.0 524 0.46 89% 0.01 3.2%

16 9 10% 1947 164 5.0 293 0.36 93% 0.05 0.4%

17 10 8% 2275 599 4.0 537 0.56 86% 0.04 4.3%

18 11 5% 2275 150 4.8 280 0.29 94% 0.03 0.4%

19 12 5% 2275 450 5.0 426 0.24 95% 0.04 4.3%

20 13 5% 2275 300 4.8 357 0.11 98% 0.02 0.9%

Composite Results 4.6 0.27 94% 0.03 * 2.2% *

Adsorber

Base

EPA AVL AVL Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 42% Idle 0 13.00 144 0.16 100% 0.00 0.0%

2 2 8% 987 86 8.80 162 0.56 94% 2.11 1.8%

3 3 3% 1157 261 8.40 355 0.30 96% 0.16 0.3%

4 4 4% 1344 435 5.90 446 0.09 98% 0.23 0.9%

5 5 10% 2500 94 5.50 263 0.66 88% 0.25 1.6%

6 6 12% 2415 228 4.60 346 0.11 98% 0.03 0.4%

7 7 12% 2415 394 4.90 403 0.05 99% 0.02 1.4%

8 8 9% 2313 567 4.10 544 0.73 82% 0.35 4.0%

Composite Results 4.9 0.33 93% 0.19 * 2% *

* HC results & FE Impacts do not reflect future potential as they are derived using a 5 g NOx engine which requires more frequent NOx regens 

than would result using a 2.5 g engine and the tested system was not a fully optimized engine & emission control system.

Adsorber

0%

20%

40%

60%

80%

100%

200 250 300 350 400 450 500 550

Adsorber Inlet Temperature (C)

NOx Reduction Efficiency (%)

Figure 4.1-11. SET & AVL Composites, and Temperature vs.

NOx Chart for Adsorber B
Regulatory Impact Analysis

4-60

Base

EPA SET SET Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 15% Idle 0 13.00 144 0.16 100% 0.00 0.0%

9 2 8% 1619 630 4.60 451 0.18 96% 0.07 1.3%

10 3 10% 1947 328 4.70 356 0.14 97% 0.15 1.7%

11 4 10% 1947 493 5.00 400 0.09 98% 0.05 1.6%

12 5 5% 1619 332 5.00 377 0.07 99% 0.01 1.2%

13 6 5% 1619 498 5.00 431 0.11 98% 0.02 1.6%

14 7 5% 1619 166 5.50 305 0.23 96% 0.14 2.3%

15 8 9% 1947 630 4.00 501 0.16 96% 0.04 2.1%

16 9 10% 1947 164 5.00 303 0.15 97% 0.14 3.1%

17 10 8% 2275 599 4.00 489 0.93 93% 0.09 1.7%

18 11 5% 2275 150 4.80 278 0.57 88% 0.18 3.5%

19 12 5% 2275 450 5.00 391 0.12 98% 0.10 1.8%

20 13 5% 2275 300 4.80 330 0.21 96% 0.09 2.9%

Composite Results 4.6 0.28 94% 0.08 * 1.9% *

Adsorber

Base

EPA AVL AVL Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 42% Idle 0 13.00 144 0.16 100% 0.00 0.0%

2 2 8% 987 86 8.80 162 0.56 94% 2.11 1.8%

3 3 3% 1157 261 8.40 359 0.08 99% 0.30 3.1%

4 4 4% 1344 435 5.90 427 0.14 98% 0.19 1.7%

5 5 10% 2500 94 5.50 273 1.25 77% 0.26 6.4%

6 6 12% 2415 228 4.60 301 0.52 89% 0.13 1.9%

7 7 12% 2415 394 4.90 363 0.66 87% 0.04 1.4%

8 8 9% 2313 567 4.10 493 0.31 92% 0.08 1.6%

Composite Results 4.9 0.51 90% 0.14 * 1.9% *

* HC results & FE Impacts do not reflect future potential as they are derived using a 5 g NOx engine which requires more frequent NOx regens 

than would result using a 2.5 g engine and the tested system was not a fully optimized engine & emission control system.

Adsorber

0%

20%

40%

60%

80%

100%

200 250 300 350 400 450 500 550

Adsorber Inlet Temperature (C)

NOx Reduction Efficiency (%)

Figure 4.1-12. SET & AVL Composites, and Temperature vs.

NOx Chart for Adsorber D
Technologies and Test Procedures for Low-Emission Engines

4-61

Base

EPA SET SET Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 15% Idle 0 13.00 144 0.16 100% 0.00 0.0%

9 2 8% 1619 630 4.60 455 0.47 89% 0.02 2.1%

10 3 10% 1947 328 4.70 343 0.07 98% 0.05 0.9%

11 4 10% 1947 493 5.00 442 0.36 93% 0.07 9.0%

12 5 5% 1619 332 5.00 377 0.08 98% 0.01 1.5%

13 6 5% 1619 498 5.00 419 0.29 94% 0.03 1.6%

14 7 5% 1619 166 5.50 412 0.14 98% 0.05 1.7%

15 8 9% 1947 630 4.00 392 0.05 99% 0.02 2.1%

16 9 10% 1947 164 5.00 294 0.09 98% 0.26 4.4%

17 10 8% 2275 599 4.00 492 0.95 76% 0.03 2.0%

18 11 5% 2275 150 4.80 388 0.11 98% 0.03 2.4%

19 12 5% 2275 450 5.00 391 0.12 98% 0.10 1.8%**

20 13 5% 2275 300 4.80 327 0.22 95% 0.02 1.4%

** Md 19 data from Adsorber D

Composite Results 4.6 0.33 93% 0.05 * 2.9% *

Adsorber

Base

EPA AVL AVL Speed Torque BSNOx Inlet T BSNOx NOx Red HC * FE Impact

Mode Mode Weighting (rpm) (lb-ft) (g/hp-hr) (C) (g/hp-hr) (g/hp-hr) *

1 1 42% Idle 0 13.00 144 0.16 100% 0.00 0.0%

2 2 8% 987 86 8.80 166 7.39 16% 1.02 71.9%

3 3 3% 1157 261 8.40 339 0.09 99% 0.05 2.3%

4 4 4% 1344 435 5.90 449 0.65 89% 0.01 2.1%

5 5 10% 2500 94 5.50 256 1.36 75% 0.91 15.8%

6 6 12% 2415 228 4.60 313 0.35 92% 0.21 5.6%

7 7 12% 2415 394 4.90 372 0.12 97% 0.10 2.6%

8 8 9% 2313 567 4.10 508 1.39 66% 0.04 3.3%

Composite Results 4.9 0.80 84% 0.16 * 5.4% *

* HC results & FE Impacts do not reflect future potential as they are derived using a 5 g NOx engine which requires more frequent NOx regens 

than would result using a 2.5 g engine and the tested system was not a fully optimized engine & emission control system.

Adsorber

0%

20%

40%

60%

80%

100%

200 250 300 350 400 450 500 550

Adsorber Inlet Temperature (C)

NOx Reduction Efficiency (%)

Figure 4.1-13. SET & AVL Composites, and Temperature vs.

NOx Chart for Adsorber E
Regulatory Impact Analysis

4-62

Testing Goals—Dual-Leg NOx Adsorber System

After completing the screening process and selecting NOx adsorber “B,” the dual-leg system

was developed. The dual-leg system was first tested on the same ISB engine as was used for the

single-leg testing. The results from that portion of the testing were similar to the single-leg

results (i.e., >90 percent NOx reductions for most test modes) and were reported in the HD2007

Regulatory Impact Analysis.95 Subsequent testing of the NOx adsorber system was made at

NVFEL but with a new ISB engine that had been upgraded to include nonroad Tier 3 type

technologies, such as common rail fuel injection and cooled EGR. The change in engine

technology led to significantly lower engine-out emissions (similar to the levels expected for

2004 highway engines Tier 3 nonroad engines) and to different exhaust gas temperature

characteristics. As a result of the engine changes, the overall system performance was improved

on both the steady-state test points and on the transient highway FTP cycle.96 As discussed

further in Section 4.1.3.1.2 below, performance over the NRTC is projected to be better than for

the highway FTP cycle. Also, as can be seen in Figure 4.1-9 above, the SET steady-state test

points are not significantly different from the ISO C1 test points (to which nonroad engines

would be subject). Emission reductions are therefore expected to be similar. 

Testing Approach—Dual-Leg NOx Adsorber System

The steady-state SET testing was conducted in a manner similar to that used in the screening

process described above. The modes were run with varying levels of automation, with the

general strategy being to inject sufficient fuel during regeneration to obtain a lambda at or

slightly fuel-rich of stoichiometric (8 #1). The NOx regenerations were then timed to achieve

the targeted 90 percent NOx reduction. The regeneration control and optimization strategies are

described in more detail in an SAE paper included in the docket for this rule.97

Transient regeneration control over the highway FTP cycle was accomplished using a timebased regeneration schedule. This control regenerated on a prescribed schedule of time and fuel

quantities, so regenerations occurred at predetermined engine conditions during the transient

cycle. 

The emission results presented here are only for hot-start portions of the highway FTP cycle. 

The adsorber system was not optimized for cold-start performance and does not provide a

meaningful assessment of adsorber warmup performance. To better simulate the “cold-soakhot” procedure called for in highway FTP cycle, a preconditioning mode was chosen to provide

adsorber temperatures at the start of the “hot” cycle similar to those found following the “coldsoak” portion of the test. The mode chosen was EPA mode 10 (1947 rpm, 328 lb-ft), which

resulted in adsorber inlet temperatures (i.e., at the outlet of the CDPF) at the start of the hot cycle

of about 280/C. Another purpose for the preconditioning was to ensure the adsorbers were in the

same condition at the start of each test. Given that our regeneration control system did not

automatically take into account the starting condition of the NOx adsorbers, this preconditioning

was necessary to provide repeatable transient test results. 
Technologies and Test Procedures for Low-Emission Engines

4-63

Test Results—Dual-Leg NOx Adsorber System

The highway SET is made up of the 13 Euro III modes. Several modes were run twice by

different engineers, and the best calibration was chosen for the SET composite. Table 4.1-7

shows the SET composite test results. These data show that 90 percent NOx reductions were

possible over the SET composite, with a modal NOx reduction range from 89 percent to nearly

100 percent. The adsorber NOx and HC reduction performance varied primarily as a function of

exhaust temperature. 

 Modal and composite SET NOx and HC emissions results for the Modified Cummins ISB engine. 

Modified Cummins ISB 

(HPCR, cooled EGR) 

Modified Cummins ISB 

(Baseline + CDPF and NOx adsorber catalysts)

SET 

Mode 

SET 

Weighting 

Speed 

(rpm) 

Torque 

(lb-ft) 

BSNOx 

(g/hp-hr) 

BSHC 

(g/hp-hr) 

Outlet T 

(°C) 

BSNOx 

(g/hp-hr) 

NOx (%-

Reduction) 

BSHC 

(g/hp-hr) 

Reductant FE 

Impact (%)* 

1 15% Idle 0 6.95 6.77 144 0.16 100% 0.00 0.0% 

2 8% 1649 633 3.10 0.08 529 0.33 89% 0.03 1.6% 

3 10% 1951 324 1.79 0.21 403 0.06 96% 0.01 1.0% 

4 10% 1953 490 1.98 0.12 486 0.07 96% 0.02 1.3% 

5 5% 1631 328 1.90 0.22 403 0.10 95% 0.01 0.9% 

6 5% 1626 496 2.35 0.09 504 0.07 97% 0.02 1.6% 

7 5% 1623 161 2.05 0.56 313 0.02 99% 0.03 0.9% 

8 9% 1979 609 2.09 0.08 524 0.19 91% 0.03 1.7% 

9 10% 1951 159 1.68 0.49 323 0.01 100% 0.02 0.8% 

10 8% 2348 560 1.95 0.11 524 0.10 95% 0.04 2.3% 

11 5% 2279 145 1.66 0.57 306 0.01 99% 0.02 0.7% 

12 5% 2275 447 1.84 0.14 465 0.10 95% 0.01 0.9% 

13 5% 2274 296 1.76 0.25 400 0.03 98% 0.01 0.9% 

SET Weighted Composite Results: 2.10 0.17 0.12 94% 0.03 1.4%** 

Notes: 

* Fuel economy impact of fuel-reductant addition for NOx adsorber regeneration. 

** Increased exhaust restriction from the wall-flow and flow through monoliths results in a further FE impact of approximately 1-2% over 

the SET composite. 

Table 4.1-7 SET Results for Dual-Leg System at NVFEL

The fuel economy impact was defined as the percent increase in fuel consumption caused by

the adsorber regeneration fuel, or the mass of fuel used for regeneration, divided by the mass of

fuel consumed by the engine during one regeneration and adsorption cycle. The fuel economy

impact varied from virtually zero to 2.3 percent depending on the mode with a composite fuel

economy impact of 1.4 percent. We anticipate significant improvements in regeneration

strategies are possible with different system configurations. Also, changes in engine operation

designed to increase exhaust temperatures, not attempted in this work, can provide substantial

improvements in catalyst performance and potentially a lower fuel economy impact.

Test Results over the Highway FTP Cycle

As with the steady-state test results, the test results over the hot-start portion of the highway

FTP cycle showed NOx and PM emission reductions greater than 90 percent. The baseline

(without the catalyst system) NOx emissions of 2.7 g/hp-hr were reduced to 0.1 g/hp-hr with the

addition of the catalyst system, a better than 95 percent reduction in NOx emissions. Similarly,
Regulatory Impact Analysis

4-64

the PM emissions were reduced to below 0.003 g/hp-hr from a baseline level of approximately

0.1 g/hp-hr, a reduction of more than 95 percent. The fuel economy impact associated with

regeneration of the NOx adsorber system was measured as 1.5 percent over the highway FTP

cycle. The fuel economy impact associated with increased exhaust restriction from the CDPF

was less than the measurement variability for the test cycle (i.e., less than 0.5 percent).98

Durability Baseline NOx Adsorber Catalyst Testing

Additional testing was conducted at NVFEL to provide baseline performance data to gauge

improvements in NOx adsorber durability performance in support of the HD2007 technology

reviews. The data provide a look at the state of adsorber technology in 2001, with a glimpse of

improvements that will be made in the future and is documented in a SAE paper.99 It is clear

from the analysis that there were vast differences in the durability performance of the

formulations over these short tests. Adsorber suppliers were early on in their development and

rapid improvements were being made. Two adsorbers representing one company’s progress over

two years showed significantly better aging performance (i.e., less degradation over time). This

performance was evidenced by its NOx adsorbing and regeneration performance after 100

hours.100 In support of the U.S. EPA’s continuing effort to monitor NOx adsorber progress, new

formulations are continuing to be evaluated.

Development of a Four “Leg” System Design

At NVFEL, developments have continued on methods and system designs for NOx adsorber

catalyst technologies. A novel four-leg NOx adsorber/PM trap system was developed as an

evolution of the proof-of-concept two-leg system that was used for previous testing at NVFEL

(the system used in the test results reported here). The four-leg system has a catalyst volume that

is less than half of the volume of the two-leg system. This allows the four-leg system to be

packaged in a volume not much larger than a muffler for a medium heavy duty truck application

as can be seen in Figure 4.1-14. Efforts have also been made to reduce the cost of the system by

using simpler injectors and valve actuators.
Technologies and Test Procedures for Low-Emission Engines

4-65

Figure 4.1 -14 Prototype 4-leg System Compared with a Truck Muffler

Initial testing indicates that the four-leg system at least matches the previous two-leg systems

NOx reduction efficiency with similar fuel consumption as can be seen in Figure 4.1-15. Note

that the results shown in the figure are based upon the NOx sensor data used in the control

system. Work is underway to confirm these steady-state results and to demonstrate the

performance over transient cycles.

93%

94%

95%

96%

97%

98%

99%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 CR

SET Mode

NOx Reduction Efficiency (%)

3.4

3.4

3.7 3.6

4.8

3.3

3.5

3.8

3.4

2.0

1.6

2.2

4.4

0

Mode FE Penalty

Figure 4.1-15 Preliminary Results for Prototype Four-Leg System
Regulatory Impact Analysis

4-66

4.1.2.3.5.3 Department of Energy (DOE) Test Programs

The U.S. Department of Energy (DOE) has funded several test programs at national

laboratories and in partnership with industry to investigate the NOx adsorber technology. Most

of these test programs are part of the Advanced Petroleum Based Fuel (APBF) program of

DOE’s Office of Transportation Technology (OTT). The initial phases of the programs are often

referred to as the Diesel Emission Control Sulfur Effects (DECSE) program, which are part of

the APBF programs. Five reports documenting the DECSE program are available from the DOE

OTT website (www.ott.doe.gov/decse) and were used extensively throughout our

analysis.101,102,103 104,105

In the DECSE program, an advanced diesel engine equipped with common rail fuel injection

and exhaust gas recirculation (EGR) was combined with a NOx adsorber catalyst to control NOx

emissions. The system used an in-cylinder control approach. Rich regeneration conditions are

created for the NOx adsorber catalyst regeneration through increased EGR rates and a secondary

injection event designed to occur late enough in the engine cycle so as not to change engine

torque output. Using this approach, the DECSE program has shown NOx conversion

efficiencies exceeding 90 percent over a catalyst inlet operating temperature window of 300/C to

450/C. This performance level was achieved while staying within the four percent fuel economy

penalty target defined for regeneration calibration.106

Subsequent work organized under the APBF program is commonly referred to as the APBFDiesel Emission Control program, or APBF-DEC. The ongoing APBF-DEC work includes

additional phases to develop prototype CDPF/NOx adsorber systems for a heavy-duty truck, a

large sport utility vehicle and a passenger car. The program is looking at all important issues

related to the technology including, packaging systems, effective regeneration, emission

performance and durability.107 

4.1.2.3.5.4 Heavy-Duty Engine Manufacturers

Heavy-duty diesel engine manufacturers (highway manufacturers) are currently developing

systems to comply with the HD2007 emission standards including the NOx adsorber technology. 

As noted in EPA’s Highway Diesel Progress Review Report 2, which documents in more detail

progress by the highway diesel engine industry to develop CDPF and NOx adsorber technology,

the progress to develop these emission-control systems is progressing rapidly. Although much

of the work being done is protected as confidential business information, a recent public

presentation by Daimler Chrysler Powersystems is illustrative some of the work that has been

done prior to 2003.108 The presentation reviews three possible system configurations for a

combined CDPF / NOx adsorber system and compares the trade-offs among the approaches. 

Similar to the results shown in Section 4.1.2.3.5.3 by EPA, a dual-leg system demonstrated 90

percent or higher NOx emission control over a wide range of operation.

Two Japanese truck manufacturers, Toyota and Hino have recently introduced light heavyduty diesel trucks in Japan using the Toyota developed Diesel Particulate NOx Reduction
Technologies and Test Procedures for Low-Emission Engines

4-67

(DPNR) catalyst system. The DPNR system described in a light-duty application in our 2002

Highway Diesel Progress Review, consists of a diesel particulate filter with NOx storage catalyst

coated onto the PM filter substrate. In some applications, the system can be further enhanced

with the addition of an oxidation catalyst and an additional NOx adsorber catalyst applied to a

conventional flow through catalyst substrate. The new trucks introduced in Japan, the Toyota

Dyna and the Hino Dutro are commonly used as urban delivery vehicles and as refuse hauling

vehicles.

In July 2003, EPA engineers visited Toyota’s Higashifuji Technical Center in Japan to

participate in testing of the engine and DPNR catalyst system being introduced later in the year

as the Toyota Dyna product. EPA participated in several days of testing and reviewed detailed

technical information regarding the emission control system and its potential for further

development. The information shared with EPA in that test program was designated as

confidential business information by Toyota. However, Toyota has published a relatively

detailed SAE paper in Japan describing the system and its performance.109 The paper

summarizes the demonstrated emission reduction of the vehicle as aged to an estimated 250,000

kilometers with NOx emissions controlled below 0.5 g/bhp-hr and PM emissions controlled

below 0.01 g/bhp-hr.

4.1.2.3.5.5 Light-Duty Diesel Vehicle Manufacturers

Diesel passenger car manufacturers are developing emission-control systems using NOx

adsorbers and PM filters in a combined control strategy to meet upcoming Euro IV emission

standards for larger passenger cars and sedans in Europe and the light-duty Tier 2 emission

standards in the United States. EPA has tested five prototype diesel passenger cars with these

technologies over the last year and a half. The results shown in Figure 4.1-16 demonstrate the

potential for substantial reductions with NOx adsorber and PM filter technologies when tested

with low-sulfur diesel fuel. All five vehicles demonstrated substantial reductions in NOx and

PM emissions when compared with a current relatively clean (compared with only a few years

ago) diesel passenger cars as represented by the solid black diamond and solid black square in

Figure 4.1-16.110
Regulatory Impact Analysis

4-68

Toyota Avensis D-CAT Station Wagon

VW Golf TDI Station Wagon

Mercedes E320 Sedan

Mercedes E320 Sedan

APBF-DEC Audi A4 Station Wagon

Vehicle “E”

Tier 1 VW Beetle TDI

Tier 2 Bin 10 VW Jetta Wagon TDI

95% Confidence Interval 

FTP Results

Toyota Avensis D-CAT Station Wagon

VW Golf TDI Station Wagon

Mercedes E320 Sedan

Mercedes E320 Sedan

APBF-DEC Audi A4 Station Wagon

Vehicle “E”

Tier 1 VW Beetle TDI

Tier 2 Bin 10 VW Jetta Wagon TDI

95% Confidence Interval 

FTP Results

Figure 4.1-16 Tier 2 Passenger Car Prototypes Tested at NVFEL on the FTP75 Cycle

One vehicle in the test program, the Mercedes E320, was tested with both new catalyst

hardware and aged catalyst hardware. The aged catalyst had experienced the equivalent of the

100,000 km of aging. The aged test results show that the aged catalyst system has lost some

amount of NOx storage volume, causing the NOx emissions to breakthrough as the catalyst fills

with NOx prior to the periodic NOx regenerations. In this testing, the NOx regeneration period

was fixed for the new and aged catalyst at the same interval. It appears from the data that the

regeneration interval for the fresh catalyst was too infrequent for the aged catalyst, which had a

reduced NOx-storage volume. At the very low NOx emission levels shown in the figure, it takes

only a very small breakthrough in NOx emissions to significantly increase the emissions over the

lowest control levels. Manufacturers are currently working to keep the number of regeneration

episodes to the minimum number to minimize stress on catalyst materials (i.e., limit thermal

degradation as discussed in Section 4.2 above). We believe manufacturers are continuing to

develop more heat-resistant materials that will reduce overall aging of the catalyst. If such

materials had been available at this time, we believe the NOx results for the aged vehicle would

have been better. Note however, that the PM emissions show no deterioration for the aged

system compared with the new system.

The most recently tested vehicle, vehicle “E” was tested after aging of the catalyst system to

the equivalent of 50,000 miles of vehicle operation. The emissions results even after this

extended aging where very good demonstrating NOx emission levels below 0.07 g/mile and PM
Technologies and Test Procedures for Low-Emission Engines

4-69

emissions below 0.01 g/mile. Relative to vehicle “D” this demonstrates substantial progress by

manufacturers to improve the overall durability of NOx adsorber catalysts.

4.1.2.4 Selective Catalytic Reduction (SCR) Technology

Another NOx catalyst-based emission-control technology is selective catalytic reduction

(SCR). SCR catalysts require a reductant, ammonia, to reduce NOx emissions. Because of the

significant safety concerns with handling and storing ammonia, most SCR systems make

ammonia within the catalyst system from urea. Such systems are commonly called urea SCR

systems. Throughout this document, the term SCR and urea SCR may be used interchangeably

and should be considered as referring to the same urea-based catalyst system. With the

appropriate control system to meter urea in proportion to engine-out NOx emissions, urea SCR

catalysts can reduce NOx emissions by over 90 percent for a significant fraction of the diesel

engine operating range.111 Although EPA has not done an extensive analysis to evaluate its

effectiveness, we believe it may be possible to reduce NOx emissions with a urea SCR catalyst

to levels consistent with compliance with Tier 4 NOx standards.

We have significant concerns regarding a technology that requires extensive user

intervention to function properly and the lack of the urea delivery infrastructure necessary to

support this technology. Urea SCR systems consume urea in proportion to the engine-out NOx

rate. The urea consumption rate can be on the order of five percent of the engine fuel

consumption rate. Unless the urea tank is prohibitively large, the urea must therefore be

replenished frequently. Most urea systems are designed to be replenished every time fuel is

added or at most every few times that fuel is added. There is not a system in place today to

deliver or dispense automotive-grade urea to diesel fueling stations. One study conducted for the

National Renewable Energy Laboratory (NREL), estimated that if urea were to be distributed to

every diesel fuel station in the United States, the cost would be more than $30 per gallon.112

We are not aware of a proven mechanism that ensures that the user will replenish the urea

supply as necessary to maintain emission-control performance. Further, we believe that, given

the additional cost for urea, there will be significant disincentives for the end-user to replenish

the urea because the cost of urea can be avoided without equipment performance loss. See

NRDC v. EPA, 655 F. 2d 318, 332 (D.C. Cir. 1981) (referring to “behavioral barriers to periodic

restoration of a filter by a [vehicle] owner” as a valid basis for EPA considering a technology

unavailable). Due to the lack of an infrastructure to deliver the needed urea, and the lack of a

track record of successful ways to ensure urea use, we have concluded that the urea SCR

technology is not likely to be available for general use in the time frame of the Tier 4 standards. 

We have therefore not based the feasibility or cost analysis of this emission-control program on

the use or availability of the urea SCR technology. However, we do not preclude its use for

compliance with the emission standards, provided that a manufacturer can demonstrate

satisfactorily that the engine will use urea under all conditions. We believe that consistent use of

urea can only be ensured only for a few unique installations and therefore believe it is

inappropriate to base a national emission-control program on a technology that can effectively

serve only in a few niche applications.
Regulatory Impact Analysis

4-70

This section has described several technologies that can reduce emissions from diesel

engines. The following section describes the challenges to applying these diesel engine

technologies to engines and equipment designed for nonroad applications. 

4.1.3 Can These Technologies Be Applied to Nonroad Engines and Equipment?

The emission standards and the introduction dates for those standards, as described earlier in

Section III of the preamble, are premised on the transfer of diesel engine technologies being, or

already developed, to meet light-duty and heavy-duty vehicle standards that begin in 2007. The

Tier 4 aftertreatment based standards for engines from 75-750 hp will begin to go into effect four

years later. This time lag between equivalent highway and nonroad diesel engine standards is

necessary to allow time for engine and equipment manufacturers to further develop these

highway engine technologies for nonroad engines and to align this program with nonroad Tier 3

emission standards that begin to go into effect in 2006.

The test procedures and regulations for the HD2007 highway engines include a transient test

procedure, a broad steady-state procedure and NTE provisions that require compliant engines to

emit at or below 1.5 times the regulated emission levels under virtually all conditions. An

engine designed to comply with the HD2007 emission standards will meet the Tier 4 standards if

it is tested over the transient and steady-state duty cycles specified in the final rule, which cover

the same regions and types of engine operation. Said in another way, a highway diesel engine

produced in 2007 may be certified in compliance with the transient and steady-state standards in

this final rule for nonroad diesel engines several years in advance of the date when these

standards are scheduled to go into effect. However, that engine, while compliant with certain of

the nonroad emission standards, would not necessarily be designed to address the various

durability and performance requirements of many nonroad equipment manufacturers. We expect

that the engine manufacturers will need additional time to further develop the necessary

emission-control systems to address some of the nonroad issues described below as well as to

develop the appropriate calibrations for engine rated speed and torque characteristics required by

the diverse range of nonroad equipment. Furthermore, not all nonroad engine manufacturers

produce highway diesel engines or produce nonroad engines that are developed from highway

products. There is therefore a need for lead time between the Tier 3 emission standards, which

go into effect in 2006-2008, and the Tier 4 emission standards. We believe the technologies

developed to comply with the Tier 3 emission standards such as improved air handling systems

and electronic fuel systems will form an essential technology baseline that manufacturers will

need to initiate and control the various regeneration functions required of the catalyst-based

technologies for Tier 4. The Agency has given consideration to all these issues in setting the

levels and timing of the Tier 4 emission standards.

This section presents some of the challenges of applying advanced emission-control

technologies to nonroad engines and equipment and describes why we believe technologies

developed for highway diesel engines can be further refined to address these issues in a timely

manner for nonroad engines consistent with the Tier 4 emission standards.
Technologies and Test Procedures for Low-Emission Engines

4-71

4.1.3.1 Nonroad Operating Conditions and Exhaust Temperatures

Nonroad equipment is highly diverse in design, application, and typical operating conditions. 

This variety of operating conditions affects emission-control systems through the resulting

variation in the torque and speed demands (i.e., power demands). This wide range in what

constitutes typical nonroad operation makes the design and implementation of advanced

emission-control technologies more difficult. The primary concern for catalyst-based emissioncontrol technologies is exhaust temperature. In general, exhaust temperature increases with

engine power and can vary dramatically as engine power demands vary.

For most catalytic emission-control technologies there is a minimum temperature below

which the chemical reactions necessary for emission control do not occur. The temperature

above which substantial catalytic activities is realized is often called the light-off temperature. 

For gasoline engines, the light-off temperature is typically important only in determining coldstart emissions. Once gasoline vehicle exhaust temperatures exceed the light-off temperature,

the catalyst is “lit-off” and remains fully functional under all operating conditions. Diesel

exhaust is significantly cooler than gasoline exhaust due to the diesel engine’s higher thermal

efficiency and its operation under predominantly lean conditions. Absent control action taken by

an electronic engine control system, diesel exhaust may fall below the light-off temperature of

catalyst technology even when the engine is fully warmed up.

The relationship between the exhaust temperature of a nonroad diesel engine and light-off

temperature is an important factor for both CDPF and NOx adsorber technologies. For the

CDPF technology, exhaust temperature determines the rate of filter regeneration and if too low

causes a need for supplemental means to ensure proper filter regeneration. In the case of the

CDPF, it is the aggregate soot regeneration rate that is important, not the regeneration rate at any

particular moment in time. A CDPF controls PM emissions under all conditions and can

function properly (i.e., not plug) even when exhaust temperatures are low for an extended time

and the regeneration rate is lower than the soot accumulation rate, provided that occasionally

exhaust temperatures and thus the soot regeneration rate are increased enough to regenerate the

CDPF. A CDPF can passively (without supplemental heat addition) regenerate if exhaust

temperatures remain above 250/C for more than 40 percent of engine operation.113 Similarly

(and as discussed in more detail earlier), there is a minimum temperature (e.g., 200/C) for NOx

adsorbers below which NOx regeneration is not readily possible and a maximum temperature

(e.g., 500/C) above which NOx adsorbers are unable to effectively store NOx. These minimum

and maximum temperatures define a characteristic temperature window of the NOx adsorber

catalyst. When the exhaust temperature is within the temperature window (above the minimum

and below the maximum) the catalyst is highly effective. When exhaust temperatures fall

outside this window of operation, NOx adsorber effectiveness is diminished. There is therefore a

need to match diesel exhaust temperatures to conditions for effective catalyst operation under the

various operating conditions of nonroad engines.

Although the range of products for highway vehicles is not as diverse as for nonroad

equipment, the need to match exhaust temperatures to catalyst characteristics is still present. 

This is a significant concern for highway engine manufacturers and has been a focus of our
Regulatory Impact Analysis

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ongoing diesel engine progress review. There we have learned that substantial progress is being

made to broaden the operating temperature window of catalyst technologies, while at the same

time, engine systems are being designed to better control exhaust temperatures. Highway diesel

engine manufacturers are working to address this need through modifications to engine design,

modifications to engine control strategies and modifications to exhaust system designs. Engine

design changes including the ability for multiple late fuel injections and the ability to control

total air flow into the engine give controls engineers additional flexibility to change exhaust

temperature characteristics. Modifications to the exhaust system, including the use of insulated

exhaust manifolds and exhaust tubing, can help to preserve the temperature of the exhaust gases. 

New engine control strategies designed to take advantage of engine and exhaust system

modifications can then be used to manage exhaust temperatures across a broad range of engine

operation. The technology solutions being developed for highway engines to better manage

exhaust temperature are built upon the same emission-control technologies (i.e., advanced air

handling systems and electronic fuel-injection systems) that we expect nonroad engine

manufacturers to use for meeting the Tier 3 emission standards.

4.1.3.1.1 CDPFS and Nonroad Operating Temperatures

EPA has conducted a screening analysis to better understand the effect of engine operating

cycles and engine power density on exhaust temperatures, specifically to see if passive CDPF

regeneration can be expected under all conditions for nonroad engine applications. Our

approach for assessing the likelihood of passive regeneration by a CDPF is based on what we

learned from the literature as well as information submitted by various catalyst manufacturers for

product verification to our voluntary diesel retrofit program.

For this analysis three representative nonroad engines were tested. The engines are

described in Table 4.1-8. In the case of the Cummins engine, the testing was done at three

different engine ratings (250hp, 169hp, and 124hp) to evaluate the effect of engine power density

on expected exhaust temperatures and therefore the likelihood of passive PM filter regeneration.

Table 4.1-8

Engines Tested to Evaluate PM Filter Regeneration

Engine Model Model

Year

Displacement

(L)

Cylinder

Number

Rated

Power (hp) Air Induction EngineType

Lombardini

LDW1003-FOCS 2001 1.0 3 26 naturallyaspirated IDI

Kubota V2203-E 1999 2.2 4 50 naturally

aspirated

IDI

Cummins ISB 2000 5.9 6 260 turbocharged

intercooled DI

As described in 4.1.1.3 above, passive filter regeneration occurs when the exhaust

temperatures are high enough that on aggregate the PM accumulation rate on the filter is less
Technologies and Test Procedures for Low-Emission Engines

4-73

than the PM oxidation rate on the filter over an extended time period. During that time period

there can be periods of low-temperature operation where the PM accumulation rate is higher than

the oxidation rates, provided that there are other periods of higher temperature operation where

the PM oxidation rate is significantly higher than the accumulation rate. CDPF manufacturers

provide guidelines for CDPF applications where passive regeneration is necessary (i.e., no

provision for occasional active regeneration is provided). These guidelines are based on the

cumulative amount of typical engine operation above and below a particular exhaust

temperature. One CDPF manufacturer has stated that passive regeneration will occur if

temperatures exceed 250o

C for more than 30 percent of engine operation.114 Another CDPF

manufacturer has stated that catalyzed diesel particulate filters will work properly in the field if

the engine exhaust temperature is at least 250-275oC for about 40-50 percent of the duty cycle.115

EPA used the more restrictive of these guidelines to evaluate the likelihood that passive

regeneration will during typical nonroad operating cycles. To do this, the exhaust temperatures

collected from testing each engine on various nonroad transient duty cycles were sorted in an

ascending order. Upon sorting, we identified the 50th and 60th percentile mark of the temperature

obtained for a transient cycle run, which lasted anywhere between 8 to 20 minutes for an entire

cycle duration. The temperatures associated with the 50th and 60th percentile mark correspond to

the minimum temperatures for 50 and 40 percent of the duty cycle, respectively. In addition, we

also calculated the average temperature obtained throughout a given cycle.

 Tables 4.1-9, 4.1-10, and 4.1-11 show the 50th and 60th percentile temperatures representing

the minimum temperatures for 50% and 40% of the duty cycle, respectively. The tables show

that the 60th percentile temperature exceeded 250/C for most of the engine tests on all three

engines. The runs that did not result in at least 250/C for 40% of the duty cycle were from the

highway FTP cycle for the two small engines, and from the backhoe cycle for the lowest power

rating, i.e., 124 hp, on the Cummins ISB engine. 
Regulatory Impact Analysis

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Table 4.1-9

Engine-out Exhaust Gas Temperature Data - 124, 163, 260 hp Cummins ISB

Cycle Average

T (o

C)

50th %tile

T (o

C)

60th %tile

T (o

C)

Operation at

 T m 275oC

Agricultural Tractor 260 hp (test #1454)

 124 hp (test #1518)

418

319

444

336

452

339

92%

89%

Wheel Loader 260 hp (test #1449)

 169 hp (test #1530)

 124 hp (test #1526)

295

264

221

323

277

222

295

311

258

57%

50%

29%

Backhoe 260 hp (test #1455)

 169 hp (test #1528) 

 124 hp (test #1523) 

261

236

185

280

238

194

303

254

201

52%

24%

 0%

JRC Composite 260 hp (test #1660)

 260 hp (test #1661)

 169 hp (test #1529)

 124 hp (test #1525)

311

317

289

252

323

326

290

243

337

339

304

265

75%

78%

61%

37%

Table 4.1-10

Engine-out Exhaust Gas Temperature Data - 50 hp Kubota V2203E

Cycle Average 

T (o

C)

50th %tile

T (o

C) 

60th %tile

T (o

C) 

Operation at

T m 275oC

Agricultural Tractor 518 544 561 96%

Nonroad Composite 289 286 310 56%

Skid Steer Loader 259 257 268 34%

Federal Test Procedure 232 210 238 30%

Table 4.1-11

Engine-out Exhaust Gas Temperature Data - 26 hp Lombardini LDW1003

Cycle Average

T (oC)

50th %tile

T (oC)

60th %tile

T (oC) 

Operation at

T m 275oC

Arc Welder 262 257 263 26%

Nonroad Composite 274 271 290 48% 

Skid Steer Loader 243 239 252 24% 

Federal Test Procedure 177 148 175 15%

Agricultural Tractor 516 548 554 97%

The results shown here lead us to conclude that, for a significant fraction of nonroad diesel

engine operation, exhaust temperatures are likely to be high enough to ensure passive

regeneration of CDPFs. However, the results also indicate that for some operating conditions it
Technologies and Test Procedures for Low-Emission Engines

4-75

may be that passive filter regeneration is not realized. In the case of those operating conditions,

we believe that active backup regeneration systems (systems designed to increase exhaust

temperature periodically to initiate filter regeneration) can be used to ensure CDPF regeneration. 

Additional data regarding in-use temperature operation are contained in a recent report from the

Engine Manufacturers Association (EMA) and the European Association of Internal Combustion

Engine Manufacturers (Euromot).116 This report contains data from a range of applications and

power categories. Similar to the data presented above, the EMA/Euromot data indicate that,

while several nonroad applications generate temperatures high enough to passively regenerate a

filter, there are also some applications that require active regeneration.

We have assumed in our cost analysis that all nonroad engines complying with a PM

standard of 0.03 g/hp-hr or lower (those engines that we are projecting will use a CDPF) will

have an active means to control temperature (i.e., we have costed a backup active regeneration

system, though some applications may not need one). We have made this assumption believing

that manufacturers will not be able to predict, accurately, in-use conditions for every piece of

equipment and will thus choose to provide the technologies on a back-up basis. As explained

earlier, the technologies necessary to accomplish this temperature management are

enhancements of the Tier 3 emission-control technologies that will form the baseline for Tier 4

engines, and the control strategies being developed for highway diesel engines. We believe there

are no nonroad engine applications above 25 hp for which these highway engine approaches will

not work. However, given the diversity in nonroad equipment design and application, we

believe that additional time will be needed to match the engine performance characteristics to the

full range of nonroad equipment.

Matching the operating temperature window of the broad range of nonroad equipment may

be somewhat more challenging for nonroad engines than for many highway diesel engines

simply because of the diversity in equipment design and equipment use. Nonetheless, the

problem has been successfully solved in highway applications facing low-temperature

performance situations as difficult to address as any encountered faced by nonroad applications. 

The most challenging temperature regime for highway engines are encountered at very lightloads as typified by congested urban driving. Under congested urban driving conditions exhaust

temperatures may be too low for effective NOx reduction with a NOx adsorber catalyst. 

Similarly, exhaust temperatures may be too low to ensure passive CDPF regeneration. To

address these concerns, light-duty diesel engine manufacturers have developed active

temperature management strategies that provide effective emissioncontrol even under these

difficult light-load conditions. Toyota has shown with their prototype DPNR vehicles that

changes to EGR and fuel-injection strategies can realize an increase in exhaust temperatures of

more than 50/C under even very light-load conditions allowing the NOx adsorber catalyst to

function under these normally cold exhaust conditions.117 Similarly, PSA has demonstrated

effective CDPF regeneration under demanding light-load taxi cab conditions with current

production technologies.118 Both of these are examples of technology paths available to nonroad

engine manufacturers to increase temperatures under light-load conditions. 

 We are not aware of any in-use operating cycles for nonroad equipment that are more

demanding of low-temperature performance than highway urban driving. Both the Toyota and
Regulatory Impact Analysis

N There is one important distinction between the current PSA system and the kind of system that we project

industry will use to comply with the Tier 4 standards: the PSA system incorporates a cerium fuel additive to help

promote soot oxidation. The additive serves a similar function to a catalyst to promote soot oxidation at lower

temperatures. Even with the use of the fuel additive, passive regeneration is not realized on the PSA system and an

active regeneration is conducted periodically involving late cycle fuel injection and oxidation of the fuel on an

up-front diesel oxidation catalyst to raise exhaust temperatures. This form of supplemental heating to ensure

infrequent but periodic PM filter regeneration has proven to be robust and reliable for more than 500,000 PSA

vehicles. Our 2002 progress review found that other manufacturers will be introducing similar systems in the next

few years without the use of a fuel additive. One vehicle manufacturer, Renault has recently announced that they

will introduce this year a CDPF system on a diesel passenger car that does not rely on an additive to help ensure that

regeneration occurs.

4-76

PSA systems are designed to function even with extended-idle operation typical of a taxi waiting

to pick up a fare.N By actively managing exhaust temperatures engine manufacturers can ensure

highly effective catalyst-based emission-control performance (i.e., compliance with the emission

standards) and reliable filter regeneration (failsafe operation) across a wide range of engine

operation typical of the broad range of nonroad engine operation in use and the new nonroad

transient duty cycle.

The systems described here from Toyota and PSA are examples of highly integrated engine

and exhaust emission-control systems based upon active engine management designed to

facilitate catalyst function. Because these systems are based upon the same engine control

technologies likely to be used to comply with the Tier 3 standards and because they allow great

flexibility to trade-off engine control and catalyst control approaches depending on operating

mode and need, we believe most nonroad engine manufacturers will use similar approaches to

comply with the Tier 4 emission standards. However, there are other technologies available that

are designed to be added to existing engines without the need for extensive integration and

engine management strategies. One example of such a system is an active DPF system

developed by Deutz for use on a wide range on nonroad equipment. The Deutz system has been

sold as an OEM retrofit technology that does not require changes to the base engine technology. 

The system is electronically controlled and uses supplemental in-exhaust fuel injection to raise

exhaust temperatures periodically to regenerate the DPF. Deutz has sold over 2,000 of these

units and reports that the systems have been reliable and effective. Some manufacturers may

choose to use this approach for compliance with the Tier 4 PM standard, especially in the case of

engines that may be able to meet the NOx standards with engine-out emission-control

technologies (i.e., engines rated between 25 and 75 hp and mobile machines >750 hp).

We believe that, given the timing of the Tier 4 emission standards and the availability and

continuing development of technologies to address temperature management for highway

engines (whose technologies are transferrable to all nonroad engines with greater than 25 hp

power rating), nonroad engines can be designed to meet the emission standards adopted in this

final rule in a timely manner.
Technologies and Test Procedures for Low-Emission Engines

4-77

4.1.3.1.2 NOx Adsorbers and Nonroad Operating Temperatures

Section 4.1.2.3.3 above describes a method to directionally evaluate the match between the

operating temperature characteristics of a diesel engine in typical use and the range of

temperatures over which a NOx adsorber catalyst is highly effective, the operating window of

the NOx adsorber catalyst technology. The analysis is not effective to accurately predict exact

emission results as it does not account for the thermal inertia of the catalyst technologies nor the

ability of the NOx adsorber to store NOx at lower temperatures as discussed in more fully in

Section 4.1.2.3.3. Nevertheless, this analysis approach can be used to compare predicted

performance of an engine with a NOx adsorber catalyst on various test cycles and with various

engine configurations.

In this case, we have used this analysis approach to better understand the characteristics of

the NRTC and the C1 composite cycle relative to the highway FTP cycle. We have extensive

experience testing NOx adsorber catalyst systems on the highway FTP cycle (see discussion

above in Section 4.2) showing that NOx reductions in excess of 90% can be expected. Here, we

are trying to understand if the NOx performance on the NRTC and the C1 composite cycle

should be expected to be better or worse than the highway FTP cycle. To accomplish that, we

tested a Cummins ISB (see Table 4.1-8) engine at three different power ratings representative of

the range of engine power density currently seen for nonroad diesel engines (250hp, 169hp, and

124hp). Following the technique described in Section 4.1.2.3.3, we estimated a notional NOx

adsorber efficiency for the various test cycles and engine power ratings described here. Further,

we performed this analysis for several different NOx adsorber mounting locations (i.e., we

measured exhaust temperatures at several locations in the exhaust system, a catalyst is not

actually installed for this testing). By measuring temperature at several locations, we could

further understand the impact of heat loss in the exhaust system on NOx adsorber performance. 

The results of this testing and analysis are presented in Tables 4.1-12, 4.1-13 and 4.1-14.

Table 4.1-12

Estimated NOx Adsorber Efficiency on Cummins ISB ISO-C1 Compositea

Engine Power

(hp)

6" from turbo

outlet (%)

25" from turbo

outlet (%)

4' from turbo

outlet (%)

6' 7" from turbo

outlet (%)

124 90.5 90.7 90.6 89.8

169 86.2 87.1 88.7 90.8

250 79.5 84.2 85.2 87.9

a

 The estimates are based on the absorber B curve shown in Figure 4.1-11.
Regulatory Impact Analysis

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Table 4.1-13

Estimated NOx Adsorber Efficiency on Cummins ISB - NRTC Cyclea

Engine Power

(hp)

6" from turbo

outlet (%)

25" from turbo

outlet (%)

4' from turbo

outlet (%)

6' 7" from turbo

outlet (%)

124 85.6 83.9 81.7 77.4

169 93.0 92.2 91.1 88.6

250 91.6 92.9 93.6 93.5 

a

 The estimates are based on the absorber B curve shown in Figure 4.1-11.

Table 4.1-14

Estimated NOx Adsorber Efficiency on Cummins ISB - Highway FTP Cyclea

Engine Power (hp) 6" from turbo outlet (%)

124 60.3 

169 72.4

250 83.0

a

 The estimates are based on the absorber B curve shown in Figure 4.1-11.

Results of the analysis show that for many nonroad engines, the expected exhaust

temperatures are well matched for NOx adsorber control giving high NOx conversion

efficiencies with today’s NOx adsorber technology. The NOx-reduction potential by these

devices was higher over nonroad cycles when compared with that achieved from the highway

FTP cycle. This higher efficiency obtained from the engine testing results was due to

comparatively higher engine-out exhaust temperatures obtained from running on various

nonroad transient cycles compared with the highway FTP cycle, thus indicating that the transfer

of highway engine technologies developed for the HD2007 emission standards will be able to

provide similar or better control for nonroad diesel engines designed to comply with the Tier 4

standards.

4.1.3.1.3 Power Density Trends in Nonroad

An analysis of power density trends in nonroad diesel engines was undertaken to understand

what levels of power density to expect in the future for nonroad diesel engines. This analysis

included consideration of data from the Power Systems Research 2002 database (PSR). The

PSR data includes estimates of nonroad diesel engine model specifications and sales going back

at least 20 years. This data set represents the most comprehensive nonroad engine database of

this nature available. 

This analysis specifically examined trends in power density within various power categories

from 1985 to 2000. The PSR database reports both rated power and engine displacement, from
Technologies and Test Procedures for Low-Emission Engines

O Power density is equal to the engine’s rated power divided by the engines total displacement. The data in this

memorandum is presented in terms of horsepower per liter.

4-79

which power was calculated.O The data were divided into 5 power categories: 70-100 hp; 100 -

175hp; 175 - 300hp, 300 - 600hp, and >600hp. For each power category, a sales-weighted

average of power density was calculated for each year. Table 4.1-15 shows the resulting data, as

well as the percent change from 1985 to 2000. Figure 4.1-17 is a graphical representation of the

data in Table 4.1-15.

Table 4.1-15

Sales-Weighted Power Density by Power Category (hp/liter), 1985 - 2000

Year 50-100hp 100-175hp 175-300hp 300-600hp 600hp+

1985 20.5 24.0 25.2 30.2 27.5

1986 20.5 23.4 25.9 30.1 27.6

1987 20.9 23.3 25.9 30.6 27.9

1988 21.1 23.6 26.3 29.8 28.1

1989 20.7 24.2 27.8 31.8 31.9

1990 21.2 24.8 28.3 30.5 32.7

1991 21.5 25.2 28.7 30.6 33.4

1992 21.9 25.6 29.1 30.2 35.0

1993 22.3 25.5 29.6 30.0 33.9

1994 22.3 25.6 30.2 30.7 34.7

1995 22.0 25.8 30.1 32.7 35.2

1996 22.2 25.7 30.1 35.1 35.5

1997 22.1 25.9 30.0 35.4 35.4

1998 22.6 26.3 30.0 35.1 35.3

1999 23.1 26.4 30.1 35.5 34.9

2000 22.9 26.4 30.4 35.6 34.9

% Change

1985 - 2000 11% 9% 17% 15% 21%

Figure 4.1-7 shows reasonably steady increase in power density for engines all power

categories from 1985 until approximately 1994/1995, though the rate of increase varies between

the power categories. From 1994/95 until 2000 most power categories saw either no change or a

slight increase in power density, with the exception of the >600hp category, which saw a small

decrease. Power density increases by engine rated power, with the 70-100hp category showing

the lowest values, with year 2000 being 22.9 hp/liter, and the 300-600hp and 600+hp categories

have sales-weighted power densities on the order of 35 hp/liter.
Regulatory Impact Analysis

4-80

1985 - 2000, >50 horsepower engines

15

20

25

30

35

40

1985 1987 1989 1991 1993 1995 1997 1999

Year

Sales Weighted Power Density (hp/L)

50-100hp 100-175hp 175-300hp 300-600hp 600hp+

Figure 4.1-17 Power Density Trends for Nonroad Diesel Engines

4.1.3.2 Durability and Design

Nonroad equipment is designed to be used in a wide range of tasks in some of the harshest

operating environments imaginable, from mining equipment to crop cultivation and harvesting to

excavation and loading. In the normal course of equipment operation the engine and its

associated hardware will experience levels of vibration, impacts, and dust that may exceed

conditions typical of highway diesel vehicles. Failing to consider differences in operating

conditions in engine and equipment design would be expected to lead to eventual failure of the

equipment.

Specific efforts to design for the nonroad operating conditions will be required to ensure that

the benefits of these new emission-control technologies are realized for the life of nonroad

equipment. Much of the engineering knowledge and experience to address these issues already

exists with the nonroad equipment manufacturers. Vibration and impact issues are

fundamentally mechanical durability concerns (rather than issues of technical feasibility of

achieving emission reductions) for any component mounted on a piece of equipment (e.g., an

engine coolant overflow tank). Equipment manufacturers must design mounting hardware such

as flanges, brackets, and bolts to support the new component without failure. Further, the

catalyst substrate material itself must be able to withstand the conditions encountered on nonroad

equipment without itself cracking or failing. There is a large body of real-world testing with

retrofit emission-control technologies that demonstrates the durability of the catalyst components

themselves even in the harshest of nonroad equipment applications.
Technologies and Test Procedures for Low-Emission Engines

4-81

Deutz, a nonroad engine manufacturer, sold approximately 2,000 diesel particulate filter

systems for nonroad equipment in the period from 1994 through 2000. The very largest of these

systems were limited to engine sizes below 850 hp. The majority of these systems were sold into

significantly smaller applications. Many of these systems were sold for use in mining

equipment. No other applications are likely to be more demanding than this. Mining equipment

is exposed to extraordinarily high levels of vibration, experiences impacts with the mine walls

and face, and high levels of dust. Yet in meetings with the Agency, Deutz shared their

experience that no system had failed due to mechanical failure of the catalyst or catalyst

housing.119 The Deutz system utilized a conventional cordierite PM filter substrate as is

commonly used for heavy-duty highway truck CDPF systems. The canning and mounting of the

system was a Deutz design. Deutz was able to design the catalyst housing and mounting in such

a way as to protect the catalyst from the harsh environment as evidenced by its excellent record

of reliable function. 

 Other nonroad equipment manufacturers have also offered OEM diesel particulate filter

systems to comply with requirements of some mining and tunneling worksite standards. 

Liebherr, a nonroad engine and equipment manufacturer, offers diesel particulater filter systems

as an OEM option on 340 different nonroad equipment models.120 We believe this experience

shows that appropriate design considerations, as are necessary with any component on a piece of

nonroad equipment, will be adequate to address concerns with the vibration and impact

conditions that can occur in some nonroad applications. This experience applies equally well to

the NOx adsorber catalyst technologies, as the mechanical properties of DOCs, CDPFs, and NOx

adsorbers are all similar. We believe that no new or fundamentally different solutions are

needed to address the vibration and impact constraints for nonroad equipment below 750 hp. 

Engines above 750 hp are fundamentally similar to smaller engines with the most obvious

difference being their larger size. Their larger size does create some additional issues regarding

the size and physical strength of emission control technologies. While we believe that it may be

possible to address these concerns using the same technologies as for engines <750 hp, we

recognize that today we have limited evidence to draw that conclusion definitively. As

described in Preamble Section II, we have therefore made some revisions to the proposed

emission standards for engines >750 hp reflecting technologies (e.g., wire or fiber mesh PM

filters) that we can say with confidence will be appropriate and available in the timeframe of this

rulemaking.

Certain nonroad applications, including some forms of harvesting equipment and mining

equipment, may have specific limits on maximum surface temperature for equipment

components to ensure that the components do not serve as ignition sources for flammable dust

particles (e.g. coal dust or fine crop dust). Some have suggested that these design constraints

might limit the equipment manufacturers ability to install advanced diesel catalyst technologies

such as NOx adsorbers and CDPFs. This concern seems to be largely based upon anecdotal

experience with gasoline catalyst technologies where, under certain circumstances, catalyst

temperatures can exceed 1,000/C and, without appropriate design considerations, could

conceivably serve as an ignition source. We do not believe these concerns are justified in the

case of either the NOx adsorber catalyst or the CDPF technology. Catalyst temperatures for

NOx adsorbers and CDPFs should not exceed the maximum exhaust manifold temperatures
Regulatory Impact Analysis

P

 The hottest surface on a diesel engine is typically the exhaust manifold, which connects the engines exhaust

ports to the inlet of the turbocharger. The hot exhaust gases leave the engine at a very high temperature (800/C at

high power conditions) and then pass through the turbo where the gases expand driving the turbocharger providing

work and are cooled in the process. The exhaust leaving the turbocharger and entering the catalyst and the

remaining pieces of the exhaust system is normally at least 100/C cooler than in the exhaust manifold.

4-82

already commonly experienced by diesel engines (i.e., catalyst temperatures are expected to be

below 800/C).P

 CDPF temperatures are not expected to exceed approximately 700/C in normal

use and are expected to reach the 650/C temperature only during periods of active regeneration. 

Similarly, NOx adsorber catalyst temperatures are not expected to exceed 700/C and again only

during periods of active sulfur regeneration, as described in Section 4.1.7 below. Under

conditions where diesel exhaust temperatures are naturally as high as 650/C, no supplemental

heat addition from the emission-control system will be necessary and therefore exhaust

temperatures will not exceed their natural level. When natural exhaust temperatures are too low

for effective functioning of the emission-control system, then supplemental heating (as described

earlier) may be necessary, but this is not expected to produce temperatures higher than the

maximum levels normally encountered in diesel exhaust. Furthermore, even if it were necessary

to raise exhaust temperatures to a higher level to promote effective emission control, there are

technologies available to isolate the higher exhaust temperatures from flammable materials such

as dust. One approach is the use of air-gapped exhaust systems (i.e., an exhaust pipe inside

another concentric exhaust pipe separated by an air-gap) that serve to insulate the inner hightemperature surface from the outer surface, which could come into contact with the dust. The

use of such a system may be additionally desirable to maintain higher exhaust temperatures

inside the catalyst to promote better catalyst function. Another technology to control surface

temperature already used by some nonroad equipment manufacturers is water cooled exhaust

systems.121 This approach is similar to the air-gapped system but uses engine coolant water to

actively cool the exhaust system. Flammable dust concerns should not prevent the use of either

a NOx adsorber or a CDPF, because catalyst temperatures are not expected to be unacceptably

high and because remediation technologies exist to address these concerns. In fact, exhaust

emission-control technologies (i.e., aftertreatment) have already been applied on both an OEM

basis and for retrofit to nonroad equipment for use in potentially explosive environments. Many

of these applications must undergo Underwriters Laboratory (UL) approval before they can be

used.122

We agree that nonroad equipment must be designed to address durable performance for a

wide range of operating conditions and applications that are not commonly experienced by

highway vehicles. We believe further, as demonstrated by retrofit experiences around the world,

that there are technical solutions that allow catalyst-based emission-control technologies to be

applied to nonroad equipment. 

4.1.4 Are the Standards for Engines >25 hp and <75 hp Feasible?

As discussed in Section II of the preamble, the emission standards for engines between 25

and 75 hp consist of a 2008 transitional standard and long-term 2013 standards. The transitional

standard is a 0.22 g/hp-hr PM standard. The 2013 standards consist of a 0.02 g/hp-hr PM
Technologies and Test Procedures for Low-Emission Engines

Q Data in Table 4.1-16 are derived from a combination of the publically available certification data for model

year 2001 engines, as well as the manufacturers reported estimates of 2001 production targets, which is not public

information.

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standard and a 3.5 g/hp-hr NMHC+NOx standard. The transitional standard is optional for 50-

75 hp engines, as the 2008 implementation date is the same as the effective date of the Tier 3

standards. Manufactures may decide, at their option, not to undertake the 2008 transitional PM

standard, in which case their implementation date for the 0.02 g/hp-hr PM standard begins in

2012. 

The remainder of this section discusses (1) what makes the 25-75 hp category unique, (2)

which engine technology is used currently, (3) which engine technology will be used for

applicable Tier 2 and Tier 3 standards, and (4) why the Tier 4 standards are technologically

feasible.

4.1.4.1 What makes the 25 - 75 hp category unique?

Many of the nonroad diesel engines $75 hp are either a direct derivative of highway heavyduty diesel engines, or share some common traits with highway diesel engines. These include

similarities in displacement, aspiration, fuel systems, and electronic controls. At the time of the

proposal, we summarized some of the key engine parameter using data from the 2001 engines

certified for sale in the United States. For this final rule, we have also added to this data set by

including the 2004 engines certified for sale in the U.S. A comparison of these two data sets

show a number of important trends, as discussed below.

Table 4.1-16 contains a summary of some key engine parameters from the 2001 engines

certified for sale in the United States, and Table 4.1-17 is a summary of the 2004 engines.Q

Table 4.1-16

Summary of Model Year 2001 Key Engine Parameters by Power Category

Engine Parameter

Percent of 2001 U.S. Productiona

0-25 hp 25-75 hp 75-100 hp >100 hp

IDI Fuel System 83% 47% 4% <0.1%

DI Fuel System 17% 53% 96% >99%

Turbocharged 0% 7% 62% 91%

1 or 2 Cylinder Engines 47% 3% 0% 0%

Electronic fuel systems 0% 0% 0% 14%

a

 Based on sales weighting of 2001 engine certification data.
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Table 4.1-17

Summary of Model Year 2004 Key Engine Parameters by Power Category

Engine Parameter

Percent of 2004 U.S. Productiona

0-25 hp 25-75 hp 75-100 hp >100 hp

IDI Fuel System 85% 54% 6% 0.0%

DI Fuel System 15% 46% 94% 100.0%

Turbocharged 0% 22% 78% 99.9%

1 or 2 Cylinder Engines 18% <1% 0% 0%

Electronic fuel systems 0% 0% 18% 61%

a

 Based on sales weighting of 2004 engine certification data.

As can be seen in Table 4.1-16 & 4.1-17, the engines in the 25-75 hp category have some

important technology differences from the larger engines. These include a higher percentage of

indirect-injection fuel systems, and a lower fraction of turbocharged engines. (The distinction in

the <25 hp category is even more different, with no turbocharged engines, a large number of the

engines have two cylinders or less, and a significant majority of the engines have indirectinjection fuel systems.) 

The distinction is particularly marked with respect to electronically controlled fuel systems. 

These are commonly available in the $ 75 hp power categories (see Table 4.1.17 above showing

that the technology is already migrating in significant amounts even into the 75-100 hp power

band), but, based on the available certification data as well as our discussions with engine

manufacturers, we believe there are very limited, if any in the 25-75 hp category (and no

electronic fuel systems in the less than 25 hp category) at this time. The research and

development work currently being performed for the heavy-duty highway market is targeted at

turbocharged and electronically controlled, direct-injection engines with at least four cylinders

and per-cylinder displacements greater than 0.5 liters. As discussed in more detail below (and in

the preamble), as well as in Section 4.1.5.1 (regarding the <25 hp category), these engine

distinctions are important from a technology perspective and warrant a different set of standards

and implementation time-frame for the 25-75 hp category (as well as for the <25 hp category).

At the same time, the data in Tables 4.1-16 and 4.1-17 shows that engine technology is

steadily progressing in the nonroad diesel engine market, and the penetration of that technology

has increased in the past few years, i.e., from 2001 to 2004. In 2001, only engines in the 300-

600hp range were required to comply with Tier 2. Today, in 2004, all engines in the 25-750hp

range must comply with the Tier 2 emission standards. As a result of the inherent benefits of

electronically controlled fuel systems and turbocharging, and as a response to the Tier 2

emission standards, the penetration of these engine technologies in the past few years has been

dramatic. Nearly all engines >100 hp are turbocharged and have direct injection fuel systems. 

In addition, more than 60 percent of the engines > 100 hp now have electronically controlled fuel

systems (up from 14% in 2001). In the 75-100hp range, turbocharging has increased from 62 to
Technologies and Test Procedures for Low-Emission Engines

4-85

78 percent, and electronically controlled fuel systems have increased from 0 percent in 2001 to

18 percent in 2004. The certification data shows that these electronically controlled fuel systems

are available across the full 75-100 hp range, with some engines which use these fuel systems

having a rated power of 75 hp and others having a rated power of 99 hp. The data also indicate

that the engines in the 75-100 hp range with electronically controlled fuel systems are designed

for use in nonroad equipment such as agricultural tractors, mobile cranes, dozers, loaders, fork

lifts, and a range of other nonroad equipment. Even in the 25-75 hp range, turbocharging has

increased by a factor of 3, from 7 to 21 percent. We expect all of these trends to continue as Tier

2 is fully implemented by 2006, and as the Tier 3 standards are phased-in from 2006 to 2008. 

Another reason we expect that the trend will continue is because of the inherent benefits for the

end-user which result from the use of electronically controlled fuel systems and turbocharging.

4.1.4.2 What engine technology is used currently, and will be used for Tier 2 and Tier 3,

in the 25-75hp range?

In the 1998 nonroad diesel rulemaking, we established Tier 1 and Tier 2 standards for

engines in the 25-50 hp category. Tier 1 standards were implemented in 1999, and the Tier 2

standards take effect in 2004. The 1998 rule also established Tier 2 and Tier 3 standards for

engines between 50 and 75 hp. The Tier 2 standards take effect in 2004, and the Tier 3 standards

take effect in 2008. The Tier 1 standards for engines between 50 and 75 hp took effect in 1998. 

All engines in the 25-75 hp range were first required to meet Tier 2 standards in the 2004 model

year, and the MY 2004 data presented in Table 4.1-17 represent Tier 2 technology for this power

range.

Engines in the 25-75 hp category use either indirect injection (IDI) or direct injection (DI)

fuel systems. The IDI system injects fuel into a pre-chamber rather than directly into the

combustion chamber as in the DI system.123 This difference in fuel systems results in

substantially different emission characteristics, as well as several important operating

parameters. In general, the IDI engine has lower engine-out PM and NOx emissions, while the

DI engine has better fuel efficiency and lower heat rejection.124

We expect a significant shift in the engine technology that will be used in this power

category as a result of the upcoming Tier 2 and Tier 3 standards, in particular for the 50-75 hp

engines. In the 50-75 hp category, the 2008 Tier 3 standards will likely result in the significant

use of turbocharging and electronic fuel systems, as well as the introduction of both cooled and

uncooled exhaust gas recirculation by some engine manufacturers and possibly the use of

charge-air-cooling.125 To some extent this has already begun to occur as a result of the Tier 2

standards, as discussed above in relation to Tables 4.1-16 and 4.1-17. In addition, we have heard

from some engine manufacturers that the engine technology used to meet Tier 3 for engines in

the 50-75 hp range will also be made available on those engines in the 25-50 hp range that are

built on the same engine platform. For the Tier 2 standards for the 25-50 hp products, a large

number of engines already meet these standards; we therefore expect to see more moderate

changes in these engines, including an increased penetration of turbocharging.126 
Regulatory Impact Analysis

R

 The Tier 1 standards for this power category must be demonstrated on one of a variety of different engine

test cycles. The appropriate test cycle is selected by the engine manufacturer based on the intended in-use

application of the engine.

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4.1.4.3 Are the standards for 25 -75 hp engines technologically feasible?

This section discusses the feasibility of both the interim 2008 PM standard and the long-term

2013 standards.

4.1.4.3.1 2008 PM Standards

As just discussed in Section 4.1.4.2, engines in the 25-50 hp category must already meet Tier

1 NMHC+NOx and PM standards. We have examined the model year 2002 engine certification

data for engines in the 25-50 hp category.127 We have also examined the model year 2004 

certification data for engines in the 25-50hp category. For the model year 2002 data, there is no

Tier 1 PM standard for engines in the 50-75 hp range, and engine manufacturers are therefore

not required to report PM emission levels until Tier 2 starts in 2004, so there is no 2002 data to

summarize for the 50-75hp range.

Summary of 2002 Model Year Certification Data for 25-50 hp

A summary of the 2002 model year certification data for the 25-50 hp engines is presented in

Table 4.1-18, and Figure 4.1-18 is a graph of the HC+NOx and PM results from these same

engines. These data indicate that over 10 percent of the engine families already meet the 2008

0.22 g/hp-hr PM standard and 5.6 g/hp-hr NMHC+NOx standard (unchanged from Tier 2 in

2008). These include a variety of engine families using a mix of engine technologies (IDI and

DI, turbocharged and naturally aspirated) tested on a variety of certification test cycles.R Five

engine families are more than 20 percent below the 0.22 g/hp-hr PM standard; an additional 24

engine families that already meet the 2008 NMHC+NOx standards will require no more than a

30 percent PM reduction to meet the 2008 PM standards. Unfortunately, similar data do not

exist for engines between 50 and 75 hp for the 2002 model year.
Technologies and Test Procedures for Low-Emission Engines

4-87

Table 4.1-18

2002 Model Year Certification Data for 25-50 hp Nonroad Diesel Engines

PM Emissions Relative to the 0.22

g/hp-hr Standard

IDI Engines DI Engines

Totals

5-mode/

NA

8-mode/

NA

5-mode/

TC

8-mode/

TC

5-mode/

NA

8-mode/

NA

8-mode/

TC

0 - 5 % below T4a 0 0 0 0 0 1 01

5 - 20 % below T4a 1 5 1 2 0 0 09

>20 % below T4a 2 1 0 1 0 1 05

require #30% PM 

reduction to meet T4a

3 15 0 4 0 2 0 24

requires >30%PM reduction

and/or

2 17 1 3 8 40 8 79

Total # of Engine Families 8 38 2 10 8 44 8 118

a

 Engine also meets 2008 NMHC+NOx

The model year 2002 engines in this power range use well known engine-out emissioncontrol technologies, such as optimized combustion chamber design and fuel-injection timing

control strategies, to comply with the existing standards. These data have a two-fold

significance. First, they indicate that some engines in this power range can already achieve the

2008 standard for PM using only engine-out technology, and that other engines should be able to

achieve the standard making improvements just to engine-out performance. 
Regulatory Impact Analysis

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0

1

2

3

4

5

6

7

8

0.0 0.1 0.2 0.3 0.4 0.5 0.6

PM (g/bhp-hr)

HC+NOx (g/bhp-hr)

All IDI & other DI engines Naturally Aspirated DI/8-mode cycle engines

Figure 4.1-18 Emission Certification Data for 25-50 HP Model Year 2002 Engines

Summary of 2004 Model Year Certification Data for 25-75 hp

Table 4.1-19 contains a summary of the model year 2004 certification data for PM and

NMHC+NOx as it relates to the 2008 Tier 4 emission standards for engines in the 25-75hp

range. The data represented in Table 4.1-19 is also shown graphically in Figure 4.1-19. As can

be seen, the 2004 data shows 35 percent of the engine families in the 25-50hp range already meet

the 2008 0.22 g/hp-hr PM standard and a 5.6 g/hp-hr NMHC+NOx standard (which standard is

unchanged from Tier 2 in 2008). In the 50-75 hp range, the data shows 7 percent of the families

can meet the 2008 Tier 4 standards (0.22 g/bhp-hr PM and 3.5 g/bhp-hr NMHC+NOx). The

relatively low percentage of engines in the 50-75 hp category which meet the Tier 4 standards

today is largely a result of the stringency of the Tier 3 NMHC+NOx emission standards, which

are required for this power category in 2008. As discussed in our Tier 3 Staff Technical Paper

which reviewed the feasibility of the Tier 3 standards, we believe in-cylinder technologies such

as cooled EGR will be necessary to comply with the Tier 3 emission standards (and we included

the cost of such systems in our assessment of costs for the Tier 3 rule). Technologies such as

cooled EGR and advanced fuel systems have been shown to be capable of reducing NOx
Technologies and Test Procedures for Low-Emission Engines

4-89

emissions by 50 percent or more without increasing PM emissions. As can be seen by the data in

Figure 4.1-19, more than 70 percent of the engines in the 50-75 hp range are below the 0.22

g/bhp-hr PM level, and a NOx reduction of 50 percent would easily bring these engines into

compliance with the Tier 3 NMHC+NOx standards. Finally, when considered as a whole, nearly

one-quarter of the model year 2004 engine families in the 25-75 hp range could comply with the

Tier 4 2008 PM and NMHC+NOx requirements today. 

Table 4.1-19

2004 Model Year Certification Data for 25-75hp Nonroad Diesel Engines

Power Catergory

PM Emissions < 0.22 g/bhp-hr and 

2008 NMHC+NOx standards?

 Naturally Aspirated Turbocharged Grand 

Total

DI IDI NA DI IDI TC

25-50 hp, 

# of Engine Families

 No 23 35 58 6 4 10 68

 Yes 12 17 29 2 5 7 36

Total 35 52 87 8 9 17 104

50-75 hp,

 # of Engine Families

 No 22 11 33 15 9 24 57

 Yes 0 4 4 0 0 0 4

Total 22 15 37 15 9 24 61

Power Catergory

PM Emissions < 0.22 g/bhp-hr and

2008 NMHC+NOx standards?

Naturally Aspirated Turbocharged

Grand 

Total

DI IDI NA

Total

DI IDI TC

Total

25-50 hp,

% of Engine Families

No 66% 67% 67% 75% 44% 59% 65%

Yes 34% 33% 33% 25% 56% 41% 35%

50-75 hp,

% of Engine Families

No 100% 73% 89% 100% 100% 100% 93%

Yes 0% 27% 11% 0% 0% 0% 72%

25-75hp,

% of Engine Families

No 79% 69% 73% 91% 72% 83% 76%

Yes 21% 31% 27% 9% 28% 17% 24%
Regulatory Impact Analysis

4-90

0

1

2

3

4

5

6

7

8

0.0 0.1 0.2 0.3 0.4 0.5 0.6

PM Emissions (g/bhp-hr)

NMHC+NOx Emissions (g/bhp-hr)

25-50 hp Engines 50-75 hp Engines

2008 Tier 4 PM Standard

2008 NMHC+NOx Standard, 25-50hp

2008 NMHC+NOx Standard, 50-75hp

Figure 4.1-19 Emissions Certification Data for 25-75 HP Model Year 2004 Engines

Discussion of Certification Data and 2008 Feasibility

Despite the fact that the certification data from recent model years indicates that engine-out

techniques are capable of meeting the Tier 4 2008 PM standards for some engines, we are not

basing the feasibility of the 2008 PM standard on engine-out techniques alone, as discussed

below.

As can be seen from the 2002 model year data in Figure 4.1-18, while the engines are all

certified to the same emission standard (Tier 1) with similar engine technology, the emission

levels from these engines vary widely. The same can be seen for the 2004 model year data

shown in Figure 4.1-19, in particular for the 25-50hp engines. Figure 4.1-18 highlights a

specific example of this wide range: engines using naturally aspirated DI technology and tested

on the 8-mode test cycle. Even for this subset of DI engines achieving approximately the same

HC+NOx level of ~6.5 g/hp-hr, the PM rates vary from approximately 0.2 to more than 0.5 g/hphr. There is limited information available to indicate why for these small diesel engines with

similar technology operating at approximately the same HC+NOx level the PM emission rates

cover such a broad range. We are therefore not predicating the 2008 PM standard on the lowest

engine-out emissions being achieved today, because it is uncertain whether or not additional
Technologies and Test Procedures for Low-Emission Engines

4-91

engine-out improvements will lower all engines to the 2008 PM standard. Instead, we believe

there are two likely means by which companies can comply with the 2008 PM standard. First,

some engine manufacturers can comply with this standard using known engine-out techniques

(e.g., optimizing combustion chamber designs, fuel-injection strategies). However, based on the

available data as shown in Figure 4.1-18 and 4.1-19, it is unclear whether engine-out techniques

will work in all cases. We therefore believe some engine companies will choose to use a

combination of engine-out techniques and diesel oxidation catalysts, as discussed below.

Emission Reductions from Engine-out Techniques

For some of the engines not already meeting the 2008 Tier 4 PM standard, engine-out

techniques may bring the engines into compliance with the 2008 standards. In our recent Staff

Technical Paper on the feasibility of the Tier 2 and Tier 3 standards, we projected that engines

greater than 50 hp will rely on some combination of technologies—including electronic fuel

systems such as electronic rotary pumps or common-rail fuel systems—to comply with the Tier

3 NMHC+NOx standards.128 In addition to enabling the Tier 3 NMHC+NOx standards,

electronic fuel systems with high injection pressure and the capability to perform pilot-injection

and rate-shaping, have the potential to substantially reduce PM emissions.129 Even for

mechanical fuel systems, increased injection pressures can reduce PM emissions substantially.130

As discussed above, we are projecting that the Tier 3 engine technologies used in engines

between 50 and 75 hp, such as turbocharging and electronic fuel systems, will make their way

into engines in the 25-50 hp range. However, we do not believe this technology will be required

to achieve the Tier 4 2008 PM standard. As demonstrated by the 2002 and 2004 certification

data, engine-out techniques such as optimized combustion chamber design, fuel-injection

pressure increases and fuel-injection timing can be used to achieve the 2008 Tier 4 standards for

many of the engines in the 25-75 hp category without the need to add turbocharging or electronic

fuel systems.

Emission Reductions from Diesel Oxidation Catalysts

For those engines not able to achieve the Tier 4 standards with known engine-out techniques,

we project that these engines can meet the standards with diesel oxidation catalysts. DOCs are

passive flow-through emission-control devices that are typically coated with a precious metal or

a base-metal washcoat. DOCs have been proven to be durable in use on both light-duty and

heavy-duty diesel applications. In addition, DOCs have already been used to control PM or

carbon monoxide on some nonroad applications.131

Certain DOC formulations can be sensitive to diesel fuel sulfur levels, and depending on the

level of emission reduction necessary, sulfur in diesel fuel can be an impediment to PM

reductions. Precious-metal oxidation catalysts can oxidize the sulfur in the fuel and form

particulate sulfates. However, even with current high-sulfur nonroad fuel, some manufacturers

have demonstrated that a properly formulated DOC can be used in combination with other

technologies to achieve the existing Tier 2 PM standards for larger engines (i.e., the 0.15 g/hp-hr

standard).132 However, given the high level of sulfur in current nonroad fuel, the use of DOCs as

a PM-reduction technology is severely limited. Data presented by one engine manufacturer
Regulatory Impact Analysis

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regarding the existing Tier 2 PM standard show that, while a DOC can be used to meet the

current standard even when tested on 2,000 ppm sulfur fuel, lowering the fuel sulfur level to 380

ppm enabled the DOC to reduce PM by 50 percent from the 2,000 ppm sulfur fuel.133 Without

the availability of 500 ppm sulfur fuel in 2008, DOCs would be of limited use for nonroad

engine manufacturers and would not provide the emission-control necessary for most

manufacturers to meet the Tier 4 standards. With the availability of 500 ppm sulfur fuel, DOCs

can be designed to provide PM reductions on the order of 20 to 50%, while suppressing

particulate sulfate reduction.134 These levels of reductions have been seen on transient duty

cycles as well as highway and nonroad steady-state duty cycles. As discussed above, 24 engine

families in the 25-50 hp range are within 30 percent of the 2008 PM standard and are at or below

the 2008 NMHC+NOx standard for this power range, indicating that use of DOCs should

achieve the incremental improvement necessary to meet the 2008 PM standard. However, we

also do not believe that an emission level lower than 0.22 g/bhp-hr will be generally feasible in

2008 due to the diesel fuel sulfur level of 500 ppm and consequent potential for sulfate PM

formation.

4.1.4.3.2 2013 Standards

For engines in the 25-50 range, we are adopting standards starting in 2013 of 3.5 g/hp-hr for 

NMHC+NOx and 0.02 g/hp-hr for PM. Additionally, compliance with the existing CO emission

standards will need to be demonstrated over new test cycles including the NRTC with cold-start,

and NTE. For the 50-75 hp engines, we are adopting a 0.02 g/hp-hr PM standard that will be

implemented in 2013, and for those manufacturers who choose to pull-ahead the standard oneyear, 2012 (manufacturers who choose to pull-ahead the 2013 standard for engine in the 50-75

range do not need to comply with the transitional 2008 PM standard). 

4.1.4.3.2.1 PM Standard

Sections 4.1.1 through 4.1.3 have already discussed catalyzed diesel particulate filters,

including explanations of how CDPFs reduce PM emissions, and how to apply CDPFs to

nonroad engines. We concluded there that CDPFs can be used to achieve the Tier 4 PM

standard for engines $75 hp. Specifically we discussed the ability of ceramic based filter

technologies to meet the 0.01 g/bhp-hr standard for engines from 75-750 hp and the ability of

alternate depth filter technologies to meet a slightly less stringent standard of 0.02 g/bhp-hr

standard (0.03 for mobile machines) for engines > 750 hp. As also discussed in Section 4.1.3,

PM filters may require active back-up regeneration systems for many nonroad applications. 

Secondary technologies will likely be needed in addition to enable proper regeneration, possibly

including electronic fuel systems such as common rail, which makes possible multiple postinjections for raising exhaust gas temperatures to aid in filter regeneration.

Particulate filter technology, with the requisite trap regeneration technology, can also be

applied to engines in the 25 to 75 hp range. The fundamentals of how a filter is able to reduce

PM emissions, as described in Section 4.1.1, are not a function of engine power, and CDPFs are

just as effective at capturing soot emissions and oxidizing SOF on smaller engines as on larger

engines. As discussed in more detail below, particulate sulfate generation rates are slightly
Technologies and Test Procedures for Low-Emission Engines

4-93

higher for the smaller engines; however, we have addressed this issue in the final rule. The PM

filter regeneration systems described in Sections 4.1.1 and 4.1.3 are also applicable to engines in

this size range and are therefore likewise feasible. Engine manufacturers may prefer some

specific trap-regeneration technologies over others in the 25-75 hp category. Specifically, an

electronically controlled secondary fuel-injection system (i.e., a system that injects fuel into the

exhaust upstream of a PM filter). Such a system has been commercially used successfully by at

least one nonroad engine manufacturer, and other systems have been tested by technology

companies.135

We are, however, adopting a slightly higher PM standard (0.02 g/hp-hr rather than 0.01) for

these engines. As discussed in Section 4.1.1, with the use of a CDPF, the PM emissions emitted

by the filter are primarily derived from the fuel sulfur. The smaller power category engines tend

to have higher fuel consumption than larger engines. This occurs for a number of reasons. First,

the lower power categories include a high fraction of IDI engines, which by their nature consume

approximately 15 percent more fuel than a DI engine. Second, as engine displacements get

smaller, the engine’s combustion chamber surface-to-volume ratio increases. This leads to

higher heat-transfer losses and therefor lower efficiency and higher fuel consumption. In

addition, frictional losses are a higher percentage of total power for the smaller displacement

engines, which also contributes to higher fuel consumption. Because of the higher fuel

consumption rate, we expect a higher particulate sulfate level, and are therefore adopting a 0.02

g/hp-hr standard.

Test data confirm that this standard, as well as the NTE of 1.5 times the standard, is

achievable. In 2001, EPA completed a test program on two small nonroad diesel engines (a 25

hp IDI engine and a 50 hp IDI engine) that demonstrated the 0.02 g/hp-hr standard can be

achieved with the use of a CDPF.136 This test program included testing on the existing 8-mode

steady-state duty cycle as well as the new nonroad transient cycle. The 0.02g/hp-hr level was

achieved on each engine over both test cycles. In addition, the 0.02 g/hp-hr level was achieved

on a variety of nonroad test cycles that are intended to represent several specific applications,

such as skid-steer loaders, arc-welders, and agricultural tractors. We believe these data indicate

the robust emission-reduction capability of particulate filters and demonstrate that the NTE

standard of 1.5 × 0.02 g/hp-hr standard (0.03 g/hp-hr) can be achieved under the NTE test

requirements, because the data was generated over a number of test cycles which are intended to

represent real in-use operation, such as we would expect the NTE to represent. This test

program also demonstrates why we have adopted a slightly higher PM standard for the 25 - 75

hp category (0.02 g/hp-hr vs. 0.01). The data from the test program described above showed fuel

consumption rates over the 8-mode test procedure between 0.4 and 0.5 lbs/bhp-hr, while typical

values for a modern turbocharged DI engine with 4-valves per cylinder in the $75 hp categories

are on the order of 0.3 to 0.35 lbs/hp-hr. 

The CDPF technology applied to meet the PM standard will also serve to ensure compliance

with the existing CO emission standards over the new test procedures. CDPFs can reduce CO

emissions by more than 80 percent, a level of control that will more than offset any increase in

CO emission due to the new test cycles.
Regulatory Impact Analysis

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4.1.4.3.2.2 NMHC+NOx Standard

We are adopting a 3.5 g/hp-hr NMHC+NOx standard for engines in the 25 - 50 hp range

starting in 2013. This will align the NMHC+NOx standard for engines in this power range with

the Tier 3 standard for engines in the 50 - 75 hp range, which starts in 2008. EPA’s recent Staff

Technical paper, which reviewed the technological feasibility of the Tier 3 standards, contains a

detailed discussion of a variety of technologies capable of achieving a 3.5 g/hp-hr standard. 

These include cooled EGR, uncooled EGR, as well as advanced in-cylinder technologies relying

on electronic fuel systems and turbocharging.137 These technologies are capable of reducing

NOx emission by more than 50 percent including when measured over transient test cycles

including cold-start.138 Given the Tier 2 NMHC+NOx standard of 5.6 g/hp-hr, a 50 percent

reduction will allow a Tier 2 engine to comply with the 3.5 g/hp-hr NMHC+NOx standard. In

addition, because this NMHC+NOx standard is concurrent with the 0.02 g/hp-hr PM standards,

which we project will be achievable with particulate filters, engine designers will have

significant additional flexibility in reducing NOx because the PM filter will eliminate the

traditional concerns with the engine-out NOx vs. PM trade-off. Further, the CDPF technology

will substantially reduce NMHC emissions (by more than 80 percent) providing additional

control effective to help meet the NOx+NMHC emission standards.

4.1.5 Are the Standards for Engines <25 hp Feasible?

As discussed in Section III of the preamble, there is a new PM standard of 0.30 g/hp-hr for

engines less than 25 hp beginning in 2008. As discussed below, the NMHC+NOx and CO levels

for this power category is unchanged from Tier 2 levels although compliance will need to be

demonstrated over additional test cycles beginning in 2013. This section describes (1) what

makes the <25 hp category unique, (2) which engine technologies are currently used in the <25

hp category, and (3) data showing that the new emission standards are technologically feasible.

4.1.5.1 What makes the < 25 hp category unique?

Nonroad engines less than 25 hp are the least sophisticated nonroad diesel engines from a

technological perspective. All of the engines currently sold in this power category lack

electronic fuel systems and turbochargers (see Table 4.1-17). Nearly 20 percent of the products

have two-cylinders or less, and 14 percent of the engines sold in this category are single-cylinder

products, several of these have no batteries and are crank-start machines, much like a simple

walk-behind lawnmower. In addition, given the available data and taking into account the Tier 2

standards that have not yet been implemented, we are not projecting any significant penetration

of advanced engine technology, such as electronically controlled fuel systems, into this category

in the next five to ten years.

4.1.5.2 What engine technology is currently used in the <25 hp category?

In the 1998 nonroad diesel rulemaking we established Tier 1 and Tier 2 standards for these

products. Tier 1 was implemented in model year 2000, and Tier 2 will be implemented in model

year 2005. As discussed in EPA’s recent Staff Technical Paper, we project the Tier 2 standards
Technologies and Test Procedures for Low-Emission Engines

S

 The Tier 1 and Tier 2 standards for this power category must be demonstrated on one of a variety of different

engine test cycles. The appropriate test cycle is selected by the engine manufacturer based on the intended in-use

applications(s) of the engine.

4-95

will be met by basic engine-out emission-optimization strategies.139 We are not predicting that

Tier 2 will require electronic fuel systems, EGR, or turbocharging. As discussed in Section

4.1.5.3 of this RIA and in the Staff Technical Paper, a large number of engines in this power

category already meet the Tier 2 standards by a wide margin.140

Two basic types of engine fuel-injection technologies are currently present in the less than 25

hp category, mechanical indirect injection (IDI) and mechanical direct injection (DI). The IDI

system injects fuel into a pre-chamber rather than directly into the combustion chamber as in the

DI system. This difference in fuel systems results in substantially different emission

characteristics, as well as several important operating parameters. In general, as noted earlier,

the IDI engine has lower engine-out PM and NOx emissions, while the DI engine has better fuel

efficiency and lower heat rejection.

4.1.5.3 What data support the feasibility of the new standards?

We project that the Tier 4 PM standard can be met by 2008 based on: 

—the existence of a large number of engine families already meeting the standards,

—the use of engine-out reduction techniques and

—the use of diesel oxidation catalysts.

We have examined model year 2002 and 2004 engine certification data for nonroad diesel

engines less than 25 hp category.141 Tier 2 does not begin for these engines until model year

2005, and thus all of the data we examined are certified to the Tier 1 emission standards. As

described below, there is little difference between these data sets, and it is likely that many of the

2004 model year engine families are carry overs from the model year 2002.

Summary of 2002 Model Year Certification Data for Engines <25 hp

A summary of the model year 2002 certification data for engines <25hp is presented in Table

4.1-20. The data is also shown in graphical form in Figure 4.1-20. These data indicate that

some engine families already meet the Tier 4 PM standard (and the 2008 NMHC+NOx standard,

unchanged from Tier 2). The current data indicate that approximately 28% of the engine

families are already at or below the Tier 4 PM standard, while meeting the 2008 NMHC+NOx

standard. These data reflect a range of certification test cycles, and include both IDI and DI

engines.S Many of the engine families are certified well below the Tier 4 standard while meeting

the 2008 NMHC+NOx level. Specifically, 15 percent of the engine families are more than 20

percent below the Tier 4 PM standard. An additional 15 percent of the engine families already

meeting 2008 NMHC+NOx standards will require no more than a 30 percent PM reduction to

meet the 2008 PM standards. The public certification data indicate that these engines do not use

turbocharging, electronic fuel systems, exhaust gas recirculation, or aftertreatment technologies.
Regulatory Impact Analysis

4-96

Table 4.1-20 

2002 Model Year Certification Data for <25 hp Nonroad Diesel Engines

PM Emissions Relative 

to the 0.30 g/hp-hr Standard

IDI Engines DI Engines

Totals

5-mode 6-mode 8-mode 5-mode 6-mode 8-mode

0-5% below T4a 1 0 1 0 0 02

5-20% below T4a 4 6 1 0 0 0 11

>20% below T4a 1 9 5 0 1 0 16

require #30% PM 

reduction to meet T4a

5 4 4 0 2 0 15

requires >30%PM reduction and/or

> 2008 NMHC+NOx std.

7 8 4 18 18 3 58

Total # of Engine Families 18 27 15 18 21 3 102

a

 Engine also meets the 2008 NMHC+NOx standard.

0

1

2

3

4

5

6

7

8

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

PM Emissions (g/bhp-hr)

HC+NOx Emissions (g/bhp-hr)

Other IDI & DI IDI 6-mode data

Figure 4.1-20 Emission Certification Data for <25 HP Model Year 2002 Engines
Technologies and Test Procedures for Low-Emission Engines

4-97

Summary of 2004 Model Year Certification Data for 25-50 hp

The certification data for model year 2004 engines is summarized in Table 4.1.-21. In

general, this data is similar to the 2002 data shown in Table 4.1-20. The data shows that 31% of

the certified engines are below the 2008 Tier 4 standards, as compared to 28% in the 2002 data. 

However, one of the differences is a higher number of 2004 direct-injection engines are below

the Tier 4 levels in 2004 (5 out of 48) as compared to 2002 (1 out of 42). This data is also shown

in Figure 4.1-21.

Table 4.1-21

2004 Model Year Certification Data for <25hp Nonroad Diesel Engines

PM Emissions

Below 0.30 g/bhphr?

Direct Injection

Fuel System

Indirect Injection

Fuel System Totals

Engine Family

Count

No 43 38 81

Yesa 5 32 37

Total 48 70 118

% of Engine

Families

No 90% 54% 69%

Yesa 10% 46% 31%

a

 Engine also meets the 2008 NMHC+NOx standard.
Regulatory Impact Analysis

4-98

0

1

2

3

4

5

6

7

8

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

PM Emissions (g/bhp-hr)

NMHC+NOx Emissions (g/bhp-hr)

2008 NMHC+NOx Standard

2008 Tier 4 PM Standard

Figure 4.1-21 Emissions Certification Data for <25 HP Model Year 2004 Engines

Discussion of Certification Data and 2008 Feasibility

These model year 2002 and 2004 engines use well known engine-out emission-control

technologies, such as combustion chamber design and fuel-injection timing control strategies, to

comply with the existing standards (Tier 1 in both cases). As with 25-75 hp engines, these data

have a two-fold significance. First, they indicate that some engines in this power category can

already achieve the 2008 PM standard using only engine-out technology, and that other engines

should be able to achieve the standard making improvements just to engine-out performance. 

However, the data does not indicate that all engines could comply with the 2008 PM standard

using engine-out techniques alone. Despite being certified to the same emission standards with

similar engine technology, the emission levels from these engines vary widely. As can be seen

in the Figure 4.1-20, the emission levels cover a wide range. Figure 4.1-20 highlights a specific

example of this wide range: engines using naturally aspirated IDI technology and tested on the

6-mode test cycle. Even for this subset of IDI engines achieving approximately the same

HC+NOx level of~4.5 g/hp-hr, the PM rates vary from approximately 0.15 to 0.5 g/hp-hr. There

is limited information available to indicate why for these small diesel engines with similar

technology operating at approximately the same HC+NOx level the PM emission rates cover

such a broad range. The model year 2004 data in Figure 4.1-21 shows a similarly large spread in

PM emissions. We are therefore not predicating the 2008 PM standard on the combination of
Technologies and Test Procedures for Low-Emission Engines

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diesel oxidation catalysts and the lowest engine-out emissions in the final rule, because it is

uncertain whether or not additional engine-out improvements would lower all engines to the

2008 PM standard. Instead, we believe there are two likely means by which companies can

comply with the 2008 PM standard. First, some engine manufacturers can comply with this

standard using known engine-out techniques (e.g., optimizing combustion chamber designs, fuelinjection strategies). However, based on the available data, it is unclear whether engine-out

techniques will work in all cases. We therefore believe some engine companies will choose to

use a combination of engine-out techniques and diesel oxidation catalysts, as discussed below.

Emission Reductions from Engine-out Techniques

PM emissions can be reduced through in-cylinder techniques for small nonroad diesel

engines using similar techniques as used in larger nonroad and highway engines. As discussed

in Section 4.1.1 there several technologies that can influence oxygen content and in-cylinder

mixing (and thus lower PM emissions) including improved fuel-injection systems and

combustion system designs. For example, increased injection pressure can reduce PM emissions

substantially.142 The wide-range of emission characteristics present in the existing engine

certification data likely result from differences in fuel systems and combustion chamber designs. 

For many of the engines with higher emission levels, further optimization of the fuel system and

combustion chamber can provide additional PM reductions.

Emission Reductions from Diesel Oxidation Catalysts

Diesel oxidation catalysts (DOCs) also offer the opportunity to reduce PM emissions from

the engines in this power category. As explained earlier, DOCs are passive flow-through

emission-control devices that are typically coated with a precious metal or a base-metal washcoat. DOCs have been proven to be durable in-use on both light-duty and heavy-duty diesel

applications. In addition, DOCs have already been used to control either PM or in some cases

carbon monoxide on some nonroad applications.143 However, as discussed in Section 4.1.1,

certain DOC formulations can be sensitive to diesel fuel sulfur level. Specifically, preciousmetal oxidation catalysts (which have the greatest potential for reducing PM) can oxidize the

sulfur in the fuel and form particulate sulfates. Given the high level of sulfur in current nonroad

fuel, the use of DOCs as a PM reduction technology is severely limited. Data presented by one

engine manufacturer regarding the existing Tier 2 PM standard show that while a DOC can be

used to meet the current standard when tested on 2,000 ppm sulfur fuel, lowering the fuel sulfur

level to 380 ppm enabled the DOC to reduce PM by 50 percent from the 2,000 ppm sulfur

fuel.144 Without the availability of 500 ppm sulfur fuel in 2008, DOCs would be of limited use

for nonroad engine manufacturers and would not provide the emission-control necessary for

most engine manufacturers to meet the Tier 4 standards. With the availability of 500 ppm sulfur

fuel, DOCs can be designed to provide PM reductions on the order of 20 to 50%, while

suppressing particulate sulfate reduction.145 These levels of reductions have been seen on

transient duty cycles as well as on highway and nonroad steady-state duty cycles.

DOCs are also effective to control HC and CO emissions. The application of DOC as a

means to comply with the PM standard in 2008 will also provide an effective means to meet the
Regulatory Impact Analysis

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existing standards for NOx+NMHC and CO over the new test cycles in 2013. The increase in

NOx emissions over transient test conditions with typical in-cylinder controls are very small as

indicated by the transient adjustment factors estimated in the NONROAD model. HC emissions

may increase during transient testing conditions, however the ability of a DOC to reduce HC

emissions in excess of 80 percent would more than offset any increase in NOx+NMHC

emissions observed over the new test cycles. Similarly for CO, the additional CO control

allowed by the use of the DOC will more than offset any increase in CO emissions as measured

over the new test cycles. For purposes of our cost analysis contained in Chapter 6, we have

assumed that all engines certifying to the 2008 interim PM standards will use DOCs for

compliance.
Technologies and Test Procedures for Low-Emission Engines

4-101

4.1.6 Meeting the Crankcase Emission Requirements

The most common way to eliminate crankcase emissions has been to vent the blow-by gases

into the engine air intake system, so the gases can be recombusted. Prior to the HD2007

rulemaking, we have required that crankcase emissions be controlled only on naturally aspirated

diesel engines. We had made an exception for turbocharged diesel engines (both highway and

nonroad) because of concerns in the past about fouling that could occur by routing the diesel

particulates (including engine oil) into the turbocharger and aftercooler. However, this is an

environmentally significant exception since most nonroad equipment over 75hp use

turbocharged engines, and a single engine can emit over 100 pounds of NOx, NMHC, and PM

from the crankcase over its lifetime.

Given the available means to control crankcase emissions, we are eliminating this exception

for nonroad diesel engines, as we did for highway engines in 2007. We anticipate that the diesel

engine manufacturers will be able to control crankcase emissions through the use of closed

crankcase filtration systems or by routing unfiltered blow-by gases directly into the exhaust

system upstream of the emission-control equipment. However, the crankcase provision has been

written such that if adequate control can be had without “closing” the crankcase, then the

crankcase vent to the atmosphere. Manufacturers show that they meet this requirement by

adding the emissions from the crankcase ventilation system to the emissions from the engine’s

exhaust system, either by measuring them separately and adding together mathematically or by

routing crankcase emissions into the exhaust stream before sampling for emission measurement.

We expect that manufacturers will have to utilize closed crankcase approaches, as described

here to meet the stringent tailpipe emission standards in this final rule. Closed crankcase

filtration systems work by separating oil and particulate matter from the blow-by gases through

single or dual stage filtration approaches, routing the blow-by gases into the engine’s intake

manifold and returning the filtered oil to the oil sump. Oil separation efficiencies in excess of 90

percent have been demonstrated with production ready prototypes of two stage filtration

systems.146 By eliminating 90 percent of the oil that would otherwise be vented to the

atmosphere, the system works to reduce oil consumption and to eliminate concerns over fouling

of the intake system when the gases are routed through the turbocharger. Hatz, a nonroad engine

manufacturer, currently has closed crankcase systems on many of its turbocharged engines.

4.1.7 Why Do We Need 15 ppm Sulfur Diesel Fuel?

As stated earlier, we strongly believe that fuel sulfur control is critical to ensuring the

success of NOx and PM aftertreatment technologies. To evaluate the effect of sulfur on diesel

exhaust control technologies, we used three key factors for categorizing the impact of sulfur in

fuel on emission-control function. These factors were efficiency, reliability, and fuel economy. 

Taken together, these three factors support the position that the Tier 4 standards are feasible only

with diesel fuel sulfur levels of 15 ppm or lower. Brief summaries of these factors are provided

below. 
Regulatory Impact Analysis

4-102

The efficiency of emission-control technologies to reduce harmful pollutants is directly

affected by sulfur in diesel fuel. Initial and long-term conversion efficiencies for NOx, NMHC,

CO and diesel PM emissions are significantly reduced by catalyst poisoning and catalyst

inhibition due to sulfur. NOx conversion efficiencies with the NOx adsorber technology in

particular are dramatically reduced in a very short time due to sulfur poisoning of the NOx

storage bed. In addition, total PM control efficiency is negatively impacted by the formation of

sulfate PM. As explained in the following sections, the CDPF, NOx adsorber, and urea SCR

catalyst technologies described here have the potential to make significant amounts of sulfate

PM under operating conditions typical of many nonroad engines. We believe that the formation

of sulfate PM will be in excess of the total PM standard, unless diesel fuel sulfur levels are at or

below 15 ppm. Based on the strong negative impact of sulfur on emission-control efficiencies

for all of the technologies evaluated, we believe that 15 ppm represents an upper threshold of

acceptable diesel fuel sulfur levels.

Reliability refers to the expectation that emission-control technologies must continue to

function as required under all operating conditions for the life of the engine. As discussed in the

following sections, sulfur in diesel fuel can prevent proper operation of both NOx and PM

control technologies. This can lead to permanent loss in emission-control effectiveness and even

catastrophic failure of the systems. Sulfur in diesel fuel impacts reliability by decreasing catalyst

efficiency (poisoning of the catalyst), increasing diesel particulate filter loading, and negatively

impacting system regeneration functions. Among the most serious reliability concerns with

sulfur levels greater than 15 ppm are those associated with failure to properly regenerate. In the

case of the NOx adsorber, failure to regenerate the stored sulfur (desulfate) will lead to rapid loss

of NOx emission control as a result of sulfur poisoning of the NOx adsorber bed. In the case of

the diesel particulate filter, sulfur in the fuel reduces the reliability of the regeneration function. 

If regeneration does not occur, catastrophic failure of the filter could occur. It is only by the

availability of low-sulfur diesel fuels that these technologies become feasible. 

Fuel economy impacts due to sulfur in diesel fuel affect both NOx and PM control

technologies. The NOx adsorber sulfur regeneration cycle (desulfation cycle) can consume

significant amounts of fuel unless fuel sulfur levels are very low. The larger the amount of

sulfur in diesel fuel, the greater the adverse effect on fuel economy. As sulfur levels increase

above 15 ppm, the adverse effect on fuel economy becomes more significant, increasing above

one percent and doubling with each doubling of fuel sulfur level. Likewise, PM trap

regeneration is inhibited by sulfur in diesel fuel. This leads to increased PM loading in the diesel

particulate filter and increased work to pump exhaust across this restriction. With low-sulfur

diesel fuel, diesel particulate filter regeneration can be optimized to give a lower (on average)

exhaust backpressure and thus better fuel economy. As a result, for both NOx and PM

technologies, reducing the fuel sulfur level decreases the operating costs of the vehicle.

4.1.7.1 Catalyzed Diesel Particulate Filters and the Need for Low-Sulfur Fuel

CDPFs function to control diesel PM through mechanical filtration of the solid PM (soot)

from the diesel exhaust stream and then oxidation of the stored soot (trap regeneration) and

oxidation of the SOF. Through oxidation in the catalyzed diesel particulate filter the stored PM
Technologies and Test Procedures for Low-Emission Engines

4-103

is converted to CO2 and released into the atmosphere. Failure to oxidize the stored PM leads to

accumulation in the trap, eventually causing the trap to become so full that it severely restricts

exhaust flow through the device, leading to trap or vehicle failure. 

Uncatalyzed diesel particulate filters require exhaust temperatures in excess of 650/C in

order for the collected PM to be oxidized by the oxygen available in diesel exhaust. That

temperature threshold for oxidation of PM by exhaust oxygen can be decreased to 450/C through

the use of base metal catalytic technologies. For a broad range of operating conditions typical of

in-use diesel engine operation, diesel exhaust can be significantly cooler than 400/C. If

oxidation of the trapped PM would occur only at exhaust temperatures lower than 300/C, then

diesel particulate filters would be more robust for most applications and operating regimes. 

Oxidation of PM (regeneration of the trap) at such low exhaust temperatures can occur by using

oxidants that are more readily reduced than oxygen. One such oxidant is NO2.

NO2 can be produced in diesel exhaust through the oxidation of the nitrogen monoxide (NO),

created in the engine combustion process, across a catalyst. The resulting NO2-rich exhaust is

highly oxidizing in nature and can oxidize trapped diesel PM at temperatures as cool as 250/C.147

Some platinum group metals are known to be good catalysts to promote the oxidation of NO to

NO2. To promote more effective passive regeneration of the diesel particulate filters, significant

amounts of platinum group metals (primarily platinum) are therefore being used in the wash-coat

formulations of advanced CDPFs. The use of platinum to promote the oxidation of NO to NO2

introduces several system vulnerabilities affecting both the durability and the effectiveness of the

CDPF when sulfur is present in diesel exhaust. (In essence, diesel engine exhaust temperatures

are in a range necessitating use of precious-metal catalysts to adequately regenerate the PM

filter, but precious-metal catalysts are in turn highly sensitive to sulfur in diesel fuel.) The two

primary mechanisms by which sulfur in diesel fuel limits the robustness and effectiveness of

CDPFs are inhibition of trap regeneration, through inhibition of the oxidation of NO to NO2, and

a dramatic loss in total PM control effectiveness due to the formation of sulfate PM. 

Unfortunately, these two mechanisms trade-off against one another in the design of CDPFs. 

Changes to improve the reliability of regeneration by increasing catalyst loadings lead to

increased sulfate emissions and, thus, loss of PM control effectiveness. Conversely, changes to

improve PM control by reducing the use of platinum group metals and, therefore, limiting

“sulfate make” leads to less reliable regeneration. We believe the best means of achieving good

PM emission control and reliable operation is to reduce sulfur in diesel fuel, as shown in the

following subsections.

4.1.7.1.1 Inhibition of Trap Regeneration Due to Sulfur

The CDPF technology relies on the generation of a very strong oxidant, NO2, to ensure that

the carbon captured by the PM trap’s filtering media is oxidized under the exhaust temperature

range of normal operating conditions. This prevents plugging and failure of the PM trap. NO2 is

produced through the oxidation of NO in the exhaust across a platinum catalyst. This oxidation

is inhibited by sulfur poisoning of the catalyst surface.148 This inhibition limits the total amount

of NO2 available for oxidation of the trapped diesel PM, thereby raising the minimum exhaust

temperature required to ensure trap regeneration. Without sufficient NO2, the amount of PM
Regulatory Impact Analysis

T

 Through tax incentives 50 ppm cap sulfur fuel is widely available in the United Kingdom and 10 ppm sulfur

fuel is available in Sweden and in certain European city centers.

4-104

trapped in the diesel particulate filter will continue to increase and can lead to excessive exhaust

back pressure and low engine power.

The failure mechanisms experienced by diesel particulate filters due to low NO2 availability

vary significantly in severity and long-term consequences. In the most fundamental sense, the

failure is defined as an inability to oxidize the stored particulate at a rate fast enough to prevent

net particulate accumulation over time. The excessive accumulation of PM over time blocks the

passages through the filtering media, making it more restrictive to exhaust flow. To continue to

force the exhaust through the now more restrictive filter, the exhaust pressure upstream of the

filter must increase. This increase in exhaust pressure is commonly referred to as increasing

“exhaust backpressure” on the engine.

The increase in exhaust backpressure represents increased work being done by the engine to

force the exhaust gas through the increasingly restrictive particulate filter. Unless the filter is

frequently cleansed of the trapped PM, this increased work can lead to reductions in engine

performance and increases in fuel consumption. This loss in performance may be noted by the

equipment operator in terms of sluggish engine response.

Full field test evaluations and retrofit applications of these catalytic trap technologies are

occurring in parts of the United States and Europe where low-sulfur diesel fuel is already

available.T

 The experience gained in these field tests helps to clarify the need for low-sulfur

diesel fuel. In Sweden and some European city centers where 10 ppm diesel fuel sulfur is

readily available, more than 3,000 catalyzed diesel particulate filters have been introduced into

retrofit applications without a single failure. Given the large number of vehicles participating in

these test programs, the diversity of the vehicle applications, and the extended time periods of

operation, there is a strong indication of the robustness of this technology on 10 ppm low-sulfur

diesel fuel.149 Vehicle applications included intercity trains, airport buses, mail trucks, city buses

and garbage trucks. Some vehicles have been operating with traps for more than 5 years and in

excess of 300,000 miles. The field experience in areas where sulfur is capped at 50 ppm has

been less definitive. In regions without extended periods of cold ambient conditions, such as the

United Kingdom, field tests on 50 ppm cap low-sulfur fuel have also been positive, matching the

durability at 10 ppm, though sulfate PM emissions are much higher. However, field tests on 50

ppm fuel in Finland, where colder winter conditions are sometimes encountered (similar to many

parts of the United States), showed a significant number of failures (~10 percent) due to trap

plugging. This 10 percent failure rate has been attributed to insufficient trap regeneration due to

fuel sulfur in combination with low ambient temperatures.150 Other possible reasons for the high

failure rate in Finland when contrasted with the Swedish experience appear to be unlikely. The

Finnish and Swedish fleets were substantially similar, with both fleets consisting of transit buses

powered by Volvo and Scania engines in the 10 to 11 liter range. Further, the buses were

operated in city areas and none of the vehicles were operated in northern extremes such as north

of the Arctic Circle.151 Given that the fleets in Sweden and Finland were substantially similar,
Technologies and Test Procedures for Low-Emission Engines

U The average temperature in Helsinki, Finland, for the month of January is 21/F. The average temperature in

Stockholm, Sweden, for the month of January is 26/F. The average temperature at the University of Michigan in

Ann Arbor, Michigan, for the month of January is 24/F. The temperatures reported here are from

www.worldclimate.com based upon the Global Historical Climatology Network (GHCN) produced jointly by the

National Climatic Data Center and Carbon Dioxide Information Analysis Center at Oak Ridge National Laboratory

(ORNL).

4-105

and given that ambient conditions in Sweden are expected to be similar to those in Finland, we

believe that the increased failure rates noted here are due to the higher fuel sulfur level in a 50

ppm cap fuel versus a 10 ppm cap fuel.U 

 Testing on an even higher fuel sulfur level of 200 ppm was conducted in Denmark on a fleet

of 9 vehicles. In less than six months all of the vehicles in the Danish fleet had failed due to trap

plugging.152 The failure of some fraction of the traps to regenerate when operated on fuel with

sulfur caps of 50 ppm and 200 ppm is believed to be primarily due to inhibition of the NO to

NO2 conversion, as described here. Similarly the increasing frequency of failure with higher fuel

sulfur levels is believed to be due to the further suppression of NO2 formation when higher sulfur

level diesel fuel is used. Since this loss in regeneration effectiveness is due to sulfur poisoning

of the catalyst this real-world experience is expected to apply equally well to nonroad engines

(i.e., operation on lower-sulfur diesel fuel, 15 ppm versus 50 ppm, will increase regeneration

robustness).

As shown above, sulfur in diesel fuel inhibits NO oxidation leading to increased exhaust

backpressure and reduced fuel economy. We therefore believe that sulfur levels in nonroad

diesel fuel must be at or below 15 ppm to ensure reliable and economical operation over the wide

range of expected operating conditions.

4.1.7.1.2 Loss of PM Control Effectiveness

In addition to inhibiting the oxidation of NO to NO2, the sulfur dioxide (SO2) in the exhaust

stream is itself oxidized to sulfur trioxide (SO3) at very high conversion efficiencies by the

precious metals in the catalyzed particulate filters. The SO3 serves as a precursor to the

formation of hydrated sulfuric acid (H2SO4+H2O), or sulfate PM, as the exhaust leaves the

vehicle tailpipe. Virtually all of the SO3 is converted to sulfate under dilute exhaust conditions

in the atmosphere as well in the dilution tunnel used in heavy-duty engine testing. Since

virtually all sulfur present in diesel fuel is converted to SO2, the precursor to SO3, as part of the

combustion process, the total sulfate PM is directly proportional to the amount of sulfur present

in diesel fuel. Therefore, even though diesel particulate filters are very effective at trapping the

carbon and the SOF portions of the total PM, the overall PM reduction efficiency of catalyzed

diesel particulate filters drops off rapidly with increasing sulfur levels due to the formation of

sulfate PM downstream of the CDPF.

SO2 oxidation is promoted across a catalyst in a manner very similar to the oxidation of NO,

except it is converted at higher rates, with peak conversion rates in excess of 50 percent. The

SO2 oxidation rate for a platinum-based oxidation catalyst typical of the type that might be used
Regulatory Impact Analysis

V Note that direct emissions are those pollutants emitted directly from the engine or from the tailpipe depending

on the context in which the term is used, and indirect emissions are those pollutants formed in the atmosphere

through chemical reactions between direct emissions and other atmospheric constituents.

4-106

in conjunction with, or as a washcoat on, a CDPF can vary significantly with exhaust

temperature. At the low temperatures the oxidation rate is relatively low, perhaps no higher than

ten percent. However at the higher temperatures that might be more typical of agricultural

tractor use pulling a plow and the highway Supplemental Emission Test (also called the EURO 4

or 13 mode test), the oxidation rate may increase to 50 percent or more. These high levels of

sulfate make across the catalyst are in contrast to the very low SO2 oxidation rate typical of

diesel exhaust (typically less than 2 percent). This variation in expected diesel exhaust

temperatures means that there will be a corresponding range of sulfate production expected

across a CDPF.

The U.S. Department of Energy in cooperation with industry conducted a study entitled

DECSE to provide insight into the relationship between advanced emission-control technologies

and diesel fuel sulfur levels. Interim report number four of this program gives the total

particulate matter emissions from a heavy-duty diesel engine operated with a diesel particulate

filter on several different fuel sulfur levels. A straight line fit through this data is presented in

Table 4.1-19 showing the expected total direct PM emissions from a diesel engine on the

supplemental emission test cycle.V The SET test cycle, a 13 mode steady-state cycle that these

data were developed on, is similar to the C1 eight mode steady-state nonroad test cycle. Both

cycles include operation at full and intermediate load points at approximately rated-speed

conditions and torque peak-speed conditions. As a result, the sulfate make rate for the C1 cycle

and the SET cycle are expected to be similar. The data can be used to estimate the PM emissions

from diesel engines operated on fuels with average fuel sulfur levels in this range.

Table 4.1-19

Estimated PM Emissions from a Diesel Engine at the Indicated Fuel Sulfur Levels

Fuel Sulfur

 [ppm]

Steady-State Emission-Control Performancea

Tailpipe PMb

 [g/hp-hr]

PM Increase

Relative to 3 ppm Sulfur 

3 0.003 --

7a 0.006 100%

15a 0.009 200%

30 0.017 470%

150 0.071 2300%

a

 The PM emissions at these sulfur levels are based on a straight-line fit to the DECSE data; PM emissions

at other sulfur levels are actual DECSE data. (Diesel Emission Control Sulfur Effects (DECSE)

Program - Phase II Interim Data Report No. 4, Diesel Particulate Filters-Final Report, January 2000. 

Table C1.) Although DECSE tested diesel particulate filters at these fuel sulfur levels, they do not

conclude that the technology is feasible at all levels, but they do note that testing at 150 ppm is a moot

point as the emission levels exceed the engine’s baseline emission level. b

 Total exhaust PM (soot, SOF, sulfate).
Technologies and Test Procedures for Low-Emission Engines

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Table 4.1-19 makes it clear that there are significant PM emission reductions possible with

the application of catalyzed diesel particulate filters and low-sulfur diesel fuel. At the observed

sulfate PM conversion rates, the DECSE program results show that the 0.01 g/hp-hr total PM

standard is feasible for CDPF equipped engines operated on fuel with a sulfur level at or below

15 ppm. The results also show that diesel particulate filter control effectiveness is rapidly

degraded at higher diesel fuel sulfur levels due to the high sulfate PM make observed with this

technology. It is clear that PM reduction efficiencies are limited by sulfur in diesel fuel and that,

to realize the PM emission benefits sought in this rule, diesel fuel sulfur levels must be at or

below 15 ppm. 

4.1.7.1.3 Increased Maintenance Cost for Diesel Particulate Filters Due to Sulfur

In addition to the direct performance and durability concerns caused by sulfur in diesel fuel,

it is also known that sulfur can lead to increased maintenance costs, shortened maintenance

intervals, and poorer fuel economy for CDPFs. CDPFs are highly effective at capturing the

inorganic ash produced from metallic additives in engine oil. This ash is accumulated in the

filter and is not removed through oxidation, unlike the trapped soot PM. Periodically the ash

must be removed by mechanical cleaning of the filter with compressed air or water. This

maintenance step is anticipated to occur on intervals of well over 1,500 hours (depending on

engine size). However, sulfur in diesel fuel increases this ash accumulation rate through the

formation of metallic sulfates in the filter, which increases both the size and mass of the trapped

ash. By increasing the ash accumulation rate, the sulfur shortens the time interval between the

required maintenance of the filter and negatively impacts fuel economy. 

4.1.7.2 Diesel NOx Catalysts and the Need for Low-Sulfur Fuel

NOx adsorbers are damaged by sulfur in diesel fuel because the adsorption function itself is

poisoned by the presence of sulfur. The resulting need to remove the stored sulfur (desulfate)

leads to a need for extended high temperature operation that can deteriorate the NOx adsorber. 

These limitations due to sulfur in the fuel affect the overall performance and feasibility of the

NOx adsorber technology.

4.1.7.2.1 Sulfur Poisoning (Sulfate Storage) on NOx Adsorbers

The NOx adsorber technology relies on the ability of the catalyst to store NOx as a metallic

nitrate (MNO3) on the surface of the catalyst, or adsorber (storage) bed, during lean operation. 

Because of the similarities in chemical properties of SOx and NOx, the SO2 present in the

exhaust is also stored by the catalyst surface as a sulfate (MSO4). The sulfate compound that is

formed is significantly more stable than the nitrate compound and is not released and reduced

during the NOx release and reduction step (NOx regeneration step). Since the NOx adsorber is

essentially 100 percent effective at capturing SO2 in the adsorber bed, the sulfur build up on the

adsorber bed occurs rapidly. As a result, sulfate compounds quickly occupy all of the NOx

storage sites on the catalyst thereby rendering the catalyst ineffective for NOx storage and

subsequent NOx reduction (poisoning the catalyst).
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The stored sulfur compounds can be removed by exposing the catalyst to hot (over 650/C)

and rich (air-fuel ratio below the stoichiometric ratio of 14.5 to 1) conditions for a brief period.153

Under these conditions, the stored sulfate is released and reduced in the catalyst.154 While

research to date on this procedure has been very favorable regarding sulfur removal from the

catalyst, it has revealed a related vulnerability of the NOx adsorber catalyst. Under the high

temperatures used for desulfation, the metals that make up the storage bed can change in

physical structure. This leads to lower precious-metal dispersion, or “metal sintering,” (a less

even distribution of the catalyst sites) reducing the effectiveness of the catalyst.155 This

degradation of catalyst efficiency due to high temperatures is often referred to as thermal

degradation. Thermal degradation is known to be a cumulative effect. That is, with each

excursion to high temperature operation, some additional degradation of the catalyst occurs. 

One of the best ways to limit thermal degradation is by limiting the accumulated number of

desulfation events over the life of the engine. Since the period of time between desulfation

events will likely be determined by the amount of sulfur accumulated on the catalyst (the higher

the sulfur accumulation rate, the shorter the period between desulfation events), the desulfation

frequency should be proportional to the fuel sulfur level. In other words, for each doubling in

the average fuel sulfur level, the frequency and accumulated number of desulfation events are

expected to double. We concluded in the HD2007 rulemaking, that this thermal degradation

would be unacceptable high for fuel sulfur levels greater than 15 ppm. Some commenters to the

HD2007 rule suggested that the NOx adsorber technology can meet the HD2007 NOx standard

using diesel fuel with a 30 ppm average sulfur level. This implies that NOx adsorbers can

tolerate as much as a four-fold increase in desulfation frequency (when compared with an

expected seven to 10 ppm average) without any increase in thermal degradation. That

conclusion was inconsistent with our understanding of the technology at the time of the HD2007

rulemaking and remains inconsistent with our understanding of progress made by industry since

that time. Diesel fuel sulfur levels must be at or below 15 ppm to limit the number and

frequency of desulfation events. Limiting the number and frequency of desulfation events will

limit thermal degradation and thus enable the NOx adsorber technology to meet the NOx

standard.

 

 This conclusion remains true for the highway NOx adsorber catalyst technology and

will be equally true for nonroad engines applying the NOx adsorber technology to comply with

the Tier 4 standards. 

Nonroad and highway diesel engines are similarly durable, so they consume a similar amount

of diesel fuel their lifetimes. This means that both nonroad and highway diesel engines will have

the same exposure to sulfur in diesel fuel and will therefore require the same number of

desulfation cycles over their lifetimes. This is true independent of the test cycle or in-use

operation of the nonroad engine.

Sulfur in diesel fuel for NOx adsorber equipped engines will also have an adverse effect on

fuel economy. The desulfation event requires controlled operation under hot and net fuel-rich

exhaust conditions. These conditions, which are not part of a normal diesel engine operating
Technologies and Test Procedures for Low-Emission Engines

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cycle, can be created through the addition of excess fuel to the exhaust. This addition of excess

fuel causes an increase in fuel consumption. 

Future improvements in the NOx adsorber technology, as we have observed in our ongoing

diesel progress reviews, are expected and needed to meet the Tier 4 NOx standards. Some of

these improvements are likely to include improvements in the means and ease of removing

stored sulfur from the catalyst bed. However because the stored sulfate species are inherently

more stable than the stored nitrate compounds (from stored NOx emissions) and so will always

be stored preferentially to NOx on the adsorber storage sites, we expect that a separate release

and reduction cycle (desulfation cycle) will always be needed to remove the stored sulfur. We

therefore believe that fuel with a sulfur level at or below 15 ppm sulfur will be necessary to

control thermal degradation of the NOx adsorber catalyst and to limit the fuel economy impact of

sulfur in diesel fuel.

4.1.7.2.2 Sulfate Particulate Production and Sulfur Impacts on Effectiveness of NOx Control

Technologies

 The NOx adsorber technology relies on a platinum-based oxidation function to ensure high

NOx-control efficiencies. As discussed more fully in Section 4.F.1, platinum-based oxidation

catalysts form sulfate PM from sulfur in the exhaust gases significantly increasing PM emissions

when sulfur is present in the exhaust stream. The NOx adsorber technology relies on the

oxidation function to convert NO to NO2 over the catalyst bed. For the NOx adsorber this is a

fundamental step prior to the storage of NO2 in the catalyst bed as a nitrate. Without this

oxidation function the catalyst will trap only that small portion of NOx emissions from a diesel

engine that is NO2. This would reduce the NOx adsorber effectiveness for NOx reduction from

in excess of 90 percent to something well below 20 percent. The NOx adsorber relies on

platinum to provide this oxidation function due to the need for high NO oxidation rates under the

relatively cool exhaust temperatures typical of diesel engines. Because of this fundamental need

for a precious-metal catalytic oxidation function, the NOx adsorber inherently forms sulfate PM

when sulfur is present in diesel fuel, since sulfur in fuel invariably leads to sulfur in the exhaust

stream.

The Compact-SCR technology, like the NOx adsorber technology, uses an oxidation catalyst

to promote the oxidation of NO to NO2 at the low temperatures typical of much of diesel engine

operation. By converting a portion of the NOx emissions to NO2 upstream of the ammonia SCR

reduction catalyst, the overall NOx reductions are improved significantly at low temperatures. 

Without this oxidation function, low-temperature SCR NOx effectiveness is dramatically

reduced, making compliance with the NOx standard impossible. Future Compact-SCR systems

therefore need to rely on a platinum oxidation catalyst to provide the required control of NOx

emissions. This use of an oxidation catalyst to enable good NOx control means that CompactSCR systems will produce significant amounts of sulfate PM when operated on anything but the

lowest fuel sulfur levels due to the oxidation of SO2 to sulfate PM promoted by the oxidation

catalyst.
Without conversion of NO to NO2 promoted by oxidation catalysts, neither of these control

technologies can meet the Tier 4 NOx standard. Each of these technologies will therefore

require low-sulfur diesel fuel to control the sulfate PM emissions inherent in the use of highly

active oxidation catalysts. The NOx adsorber technology may be able to limit its impact on

sulfate PM emissions by releasing stored sulfur as SO2 under rich operating conditions. The

Compact-SCR technology, on the other hand, has no means to limit sulfate emissions other than

through lower catalytic function or lowering sulfur in diesel fuel. The degree to which the NOx

emission-control technologies increase the production of sulfate PM through oxidation of SO2 to

SO3 varies somewhat from technology to technology, but it is expected to be similar in

magnitude and environmental impact to that for the PM control technologies discussed

previously, since both the NOx and the PM control catalysts rely on precious metals to achieve

the required NO to NO2 oxidation reaction. 

At fuel sulfur levels below 15 ppm this sulfate PM concern is greatly diminished. Without

this low-sulfur fuel, the NOx control technologies are expected to create PM emissions well in

excess of the PM standard regardless of the engine-out PM levels. We therefore believe that

diesel fuel sulfur levels will need to be at or below 15 ppm to apply the NOx control technology.

4.2 Transient Emission Testing

4.2.1 Background and Justification

In the 1998 Rulemaking for Nonroad Compression Ignition Engines, we acknowledged that

effective in-use control of emissions from nonroad sources would be positively impacted by

having a duty cycle that more accurately characterized the transient nature of nonroad activity. 

While no certification cycle may guarantee complete in-use emission control, a cycle that

appropriately characterizes the activity of the subject equipment achieves a greater level of

control. The basics of any nonroad transient duty cycle should fulfill the following goals:

C Represent nonroad activity broadly, with a basis in real-world activities through diverse

data segments;

C Exercise the engine over its operating range; cycle not limited to a specific speed or load,

but traverses the operating range over the engine's full power range;

C Measure particulate matter (PM) on a transient basis;

C Capture the basic characteristics of PM, as currently defined, including:

- organic and inorganic carbon fractions

- volatile fraction

- sulfate fraction

- ash, etc., and

C Ensure that measures developed to control emissions over the cycle encourage and afford

greater assurance of adequate control of emissions in-use.

Since that rulemaking, we have embarked on a strategy for cataloging operational data,

generating a duty cycle from those data sets, and compiling a transient composite duty cycle that

represents a broad range of activity for nonroad diesel equipment. Working cooperatively with

the Engine Manufacturers Association (EMA) and through contract with the Southwest Research

Institute (SwRI), we created a set of duty cycles based on the following nonroad applications:
Technologies and Test Procedures for Low-Emission Engines

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- Agricultural Tractor

- Backhoe Loader

- Crawler Tractor

- Arc Welder

- Skid Steer Loader

- Wheel Loader

- Excavator

These application duty cycles were created from actual speed and load data recorded in-use

on each of these pieces of equipment. The strategy for generating the duty cycles and the base

data sets differed slightly. However, combining these two strategies has ensured that the

strengths of both approaches are integrated into the resultant composite duty cycle. Each of the

pieces of equipment represented the top tier of nonroad equipment as defined by their

contribution to nonroad diesel inventory as defined by the 1991 Nonroad Engine and Vehicles

Emissions Study (NEVES). The pieces of equipment selected have retained their historical

significance even today as they appear to match fairly well with EPA modeling data for the

impacts of those applications.

The existing steady-state duty cycle affords good coverage of the range of activity seen by

nonroad diesel applications; however, it is incomplete. The range of nonroad activity is much

broader and much more varied than can be captured by a set of steady-state points (see Figure

4.2-1). No single transient cycle, of reasonable length, could capture the full body of nonroad

diesel activity from the various equipment applications. However, it is possible to capture

typical operation of nonroad equipment and to extrapolate the applicability of available data to

the remainder of nonroad equipment for purposes of certification and modeling. This can’t

replace an in-use characterization, but it does drive development of engine design strategies to

focus emission-control and performance parameters on a broader set of activity that is much

more likely to be seen in use.

A much broader set of data from the nonroad duty cycle generation may be found in

Memorandum from Cleophas Jackson to EPA Air Docket A-2001-28. This operational and

cycle data demonstrate the amount of nonroad activity that can occur outside the modes of the

ISO C1 duty cycle.

4.2.1.1 Microtrip-Based Duty Cycles

The microtrip-based cycles were created based on a range of activity the equipment is likely

to see in use. The weighting of each microtrip impacted the duration of each segment within the

resulting duty cycle. Each microtrip was extracted from a full set of data with the equipment

being operated within the targeted implement application. The data from the extracted segment

were compared with the full body of data for the targeted implement application based on a chi

square analysis, with a 95% confidence level, of the nature of the operation. This included a

characterization of the speeds, loads, velocities, and accelerations over the full operating map,

for the given piece of equipment. Experienced operators conducting actual work operated each

unit. The projects ranged from an actual farmer plowing to a backhoe digging a trench for a
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municipal works project to a wheel loader in a rock quarry loading a truck to a skid steer loader

preparing plots in a subdivision under construction. The microtrip-based application duty cycles

were the Agricultural Tractor cycle, the Backhoe Loader cycle and the Crawler/Dozer cycle.

4.2.1.2 "Day-in-the-Life"-Based Duty Cycles

In attempting to address real-world activity, another strategy was employed for the second

set of nonroad duty cycles. This approach was termed the “day-in-the-life” strategy. It could be

said that this approach yielded only a single or perhaps two microtrips per piece of equipment. 

This approach was employed to capture data for work that would have otherwise have been done

regardless of EPA data collection needs. With these pieces, the data recorded was simply data

generated as selected pieces of equipment were used by contractors or construction personnel

during their normal operation versus being asked to do certain types of operation. The day-inthe-life duty cycles consisted of the Skidsteer Loader cycle, the Arc Welder cycle, the Rubber

Tire Loader cycle, and the Excavator cycle. The Excavator Cycle is in fact a composite duty

cycle assembled from three equal time segments of operating data from two different excavators.
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0

10

20

30

40

50

60

70

80

90

100

-20 0 20 40 60 80 100

Torque (%)

Speed (%)

Crawler Tractor Cycle Data(with ISO C-1 Weightings)

0

10

20

30

40

50

60

70

80

90

100

-20 0 20 40 60 80 100

Torque (%)

Speed (%)

Backhoe\Loader Cycle Data (with ISO C-1 Weightings)

Figure 4.2-1

Backhoe Loader and Crawler Tractor Cycle Data versus the ISO 8178-4 C1 Cycle

4.2.2 Data Collection and Cycle Generation

4.2.2.1 Test Site Descriptions

Operators were instructed to complete a job commensurate with the functionality of the

vehicle and at their customary pace. Experienced operators conducted their normal work with a

given piece of nonroad equipment. The work conducted by the equipment during the data

collection was actual work and not artificial scenarios, which ensured the accuracy of the data.

4.2.2.1.1 Agricultural Tractor Cycle Operation 

The John Deere agricultural tractor was operated by an experienced farmer on his farm. The

farmer was asked to conduct the following activities as he normally would on any given work

day. This activity formed the basis for the microtrips for the agricultural tractor duty cycle. The

microtrip activity segments included: planter, tandem offset discing (35 foot), bedder, cultivator,

ripper (10 row), folding chisel plow, and turnaround. The work was conducted during spring

planting season in Hamlin, Texas, using an actual in-use field being prepared for cultivation. 

The tractor was used to make passes with each selected implement. The normal load operation

retained for inclusion in the cycle generation was the “normal” operation with each implement. 

The data from the intentionally, highly loaded pass were not included in the eventual

Agricultural Tractor cycle.
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4.2.2.1.2 Backhoe Loader Cycle Operation

The Caterpillar backhoe loader was utilized on a site by the City of Houston, Utility

Maintenance Division, Fleet Management Department to conduct the following activities:

roading, trenching, loading and grade and level. The operation was conducted by a municipal

employee experienced in the operation of the backhoe conducting that activity. Engine data

were collected during the repair of a collapsed city sewage line in a residential neighborhood. 

The activity included demolishing the road over the sewage line, trenching to reach the pipe,

craning to remove the old pipe and install the new pipe, backfilling, loading, spreading gravel,

and finish-grading the site. 

4.2.2.1.3 Crawler Tractor Cycle Operation

The Caterpillar D4 Tractor was used to conduct the following activity on the grounds of

Southwest Research Institute by an experienced operator. The microtrips included road bed

preparation, clearing activity, and pit activity. The operation was examined at three independent

sites. Site 1 included clearing trees and brush for a construction site. At Site 2 the equipment

dug and prepared a road bed. At Site 3 V-trench and pit operations were examined. This

activity was similar to preparing a site for a small building foundation. 

4.2.2.1.4 Wheel Loader Operation

The Caterpillar 988F Wheel Loader was operated at Redland Stone Products Company

(quarry) in San Antonio, Texas. Data were collected between June 8 and June 10, 1998. The

equipment was operated from morning until midnight, working to fill construction and mining

trucks, open-topped trailers of Class-8 highway trucks, and rail cars.156 The material being

moved was typical for a quarry application, including aggregate of various densities, such as

crushed stone, gravel, and sand. Twenty-six hours of data were gathered at the quarry for the

wheel loader.

4.2.2.1.5 Skid Steer Loader Operation

The Daewoo skid steer loader was operated at a construction site for a new complex of

townhouses in the San Antonio, Texas, area by a commercial site preparation company. The

equipment was used to create drives for individual homes. Specifically, the skid steer loader was

used to haul and position aggregate foundation material to prepare the driveway and sidewalk

areas prior to laying asphalt. Over twelve hours of data were gathered over three work days for

the skid steer loader. The implement used by the skid steer loader during this operation was its

bucket. 

4.2.2.1.6 Arc Welder Operation

The Lincoln Electric 250-amp arc welder was operated at Redland Stone Products Company

(quarry) in San Antonio, Texas. Data were collected over a single work day. The equipment
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was used to perform repairs on a large, mobile steel crusher tower by a private contract firm,

Holt. Eight hours of data were gathered at the quarry for the arc welder.

4.2.2.1.7 Excavator Operations

The Hitachi EX300LC excavator was operated at 3 different sites over 7 days in the greater

San Antonio metropolitan area. Data were collected during Winter 1998 and Spring 1999. The

equipment was used to level ground at a building site, to load aggregate materials into trucks at a

quarry and to dig trenches and transport pipes for a sewer project. Almost thirty-nine hours of

data were gathered for this excavator.

The Caterpillar 320BL excavator was operated at 4 different sites over 6 days in the greater

San Antonio metropolitan area. Data were collected during Winter 1998 and Spring 1999. The

equipment was used to perform digging, trenching, pipe transport and placement and backfilling

associated with an on-going sewer project. More than thirty-eight hours of data were gathered

for this excavator.

4.2.2.2 Engine and Equipment Description

In generating the microtrip-based and the day-in-the-life duty cycles, the equipment selected

were based on the highest sales volume applications and the contribution of those applications to

the ambient inventories for NOx and PM. Those cycles were created based on a John Deere

4960 Agricultural Tractor, Caterpillar 446B Backhoe Loader, and a Caterpillar D4H Crawler

Tractor. The detailed description of the engines may be seen in Table 4.2-1 through Table 4.2-

3.157

Table 4.2-1

Agricultural Tractor—John Deere 4960

Engine Characteristic Value

Rated Speed (rpm) 2200

Peak Torque (Nm) 970

Peak Power (kW) 189.2

Low Idle Speed (rpm) 850

Operating Range (rpm) 850-2400

Other Engine Descriptors 7.6L displacement, electronic controls
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Table 4.2-2

Backhoe Loader—Caterpillar 446B

Engine Characteristic Value

Rated Speed (rpm) 2200

Peak Torque (Nm) 405

Peak Power (kW) 76.8

Low Idle Speed (rpm) 800

Operating Range (rpm) 800-2300

Other Engine Descriptors CAT 3114-D17 engine

Table 4.2-3

Crawler Tractor—Caterpillar D4H

Engine Characteristic Value

Rated Speed (rpm) 2200

Peak Torque (Nm) 442

Peak Power (kW) 85

Low Idle Speed (rpm) 800

Other Engine Descriptors 3204-D17 engine

The engines used for data generation for the day-in-the-life approach were from a skid steer

loader, an arc welder, and a wheel loader. The engine parameters of the Caterpillar 988F Series

II rubber tire loader, the Lincoln arc welder and the Daewoo skidsteer loader are listed in Table

4.2-4 through Table 4.2-6.
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Table 4.2-4

Rubber Tired Loader—1997 Caterpillar 988F Series II

Engine Characteristic Value

Rated Speed (rpm) 2080

Peak Torque (Nm) 2908

Peak Power (kW) 321

Low Idle Speed (rpm) 850 

Operating Range (rpm) 850-2250

Other Engine Descriptors CAT 3408E-TA engine, 

Caterpillar HEUI Fuel System, electronic

Table 4.2-5

Arc Welder—1997 Lincoln Electric Shield-Arc 250

Engine Characteristic Value

Rated Speed (rpm) 1,725 

Peak Torque (Nm) 162

Peak Power (kW) 28.3 

Low Idle Speed (rpm) 1375

Operating Range (rpm) 800-1900

Other Engine Descriptors Perkins D3.152 engine

Table 4.2-6

Skid Steer Loader—1997 Daewoo DSL-601

Engine Characteristic Value

Rated Speed (rpm) 2,800 

Peak Torque (Nm) 121 Nm

Peak Power (kW) 30.6 kW

Low Idle Speed (rpm) 800

Peak Torque Speed (rpm) 1,700

Other Engine Descriptors Yanmar 4TNE84 engine, 2.0 L Displacement,

in-line 4 cyl, naturally aspirated
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Two pieces of equipment were selected for generating the excavator duty cycle based on

estimates of equipment population and power distribution among excavators in the nonroad

equipment inventory in the United States at that time.158 With the highest excavator sales

volumes being in the 60-130 kW and 130-225 kW ranges, the Agency created its excavator duty

cycle based on both a Hitachi EX300LC excavator at 155 kW (208 hp) and a Mitsubishi/CAT

320 BL excavator at 95 kW (128 hp). The detailed description of the engines may be seen in

Table 4.2-7 and Table 4.2-8. 

Table 4.2-7

Excavator (higher power output)—1997 Hitachi EX300LC

Engine Characteristic Value

Rated Speed (rpm) 2,200 

Peak Torque (Nm) Nm (636 lbs-ft)

Peak Power (kW) 155 kW

Low Idle Speed (rpm) 680

Peak Torque Speed (rpm) 1,500

Other Engine Descriptors ISUZU A-6SD1TQA(AC/JI) engine, 

9.8 L displacement, mechanical controls

Table 4.2-8

Excavator (lower power output)—1997 Mitsubishi/CAT 320 BL

Engine Characteristic Value

Rated Speed (rpm) 1,800 

Peak Torque (Nm) Nm (473lbs-ft)

Peak Power (kW) 95 kW

Low Idle Speed (rpm) 800

Peak Torque Speed (rpm) 1,200

Other Engine Descriptors Mitsubishi/CAT 3066T engine, 6.4 L

displacement

4.2.2.3 Data Collection Process

The data collection process for both the microtrip-based and the day-in-the-life duty cycles

was based on collecting engine operational data in the field by mechanical and electronic means. 

Engine speed data were measured by instrumenting the engine of each piece of equipment with a

tachometer to measure engine speed in revolutions per minute (rpm). The torque was measured

either mechanically by linear transducer or as transmitted across the engine’s control area
Technologies and Test Procedures for Low-Emission Engines

W3(Oi -Ei)

2

 / Ei where Oi is the Observed frequency in the ith interal and Ei is the Expected frequency in the ith

interval based on the frequency distribution of the entire population for the given quantity.

4-119

network as a fuel-based torque signal. The mechanical torque measurement utilized rack

position to determine the load being demanded of the engine. To calibrate the voltage signal

from the linear actuator the engine rack position versus actual fuel rate and engine-out torque

were determined based on laboratory evaluation of the same model engine. Once a map of

engine speed, load, actual torque, and fuel rate was compiled, the in-field load was determined

based on rack position and engine speed, as measured by the tachometer. 

Data loggers were used to record field data during operation and the data loggers were

equipped with flash memory media. The data loggers recorded engine parameters only during

operation, so data gathering did not occur while the engine was stopped. Data collection rates

varied from cycle to cycle from a rate of 3.33 Hz to 5 Hz. Using cubic spline interpolation, the

data were then reduced to 1 Hz format for the purpose of cycle generation.

4.2.2.4 Cycle Creation Process

The basic methodology of comparing extracted segments to the full body of data were used

for both duty cycle types. The major difference is in how the activity was defined for each. The

microtrip-based activity specified the type of work performed by various implements for a given

piece of nonroad equipment in an effort to effectively incorporate the different types of operation

through which the equipment could be exercised over its lifetime. The day-in-the-life approach

was meant simply to characterize the nature of the full range of activity seen by the equipment

during its typical operation over the period of evaluation. The body of data for neither approach

was meant to be all encompassing to the extent that no other activity would be expected from

that piece of equipment over its lifetime. The microtrip approach represents the broadest sweep

in the compilation of nonroad operation. The resulting duty cycles in each case do represent the

most representative set of data from the full body of data collected.

4.2.2.4.1 Microtrip Cycle Creation

The contractor that conducted the in field testing and data reduction was Southwest Research

Institute (SwRI) with significant input from the Engine Manufacturers Association (EMA) and

direction from the United States Environmental Protection Agency (EPA). The methodology

used for creating the microtrip-based cycles involved extracting the actual data by comparing the

running window of actual data to the full body of data that was collected for each type of

activity. This involved a chi-squareW analysis comparing observed to expected data. The

observed data set was the data being evaluated for inclusion in the cycle for the specific active

window. The expected data set was represented by the full body of data from the given activity. 

The chi-square comparison involved assessing the following for each window of operation:

C Rate of change in speed (dSpeed)

C Rate of change in torque (dTorque)
Regulatory Impact Analysis

XSteady-state is defined as any instantaneous change in normalized speed or normalized torque with a

magnitude less than 2%.

YDelta is used to describe the instantaneous rate of change of the specified quantity.

4-120

C Power

C Rate of change in power (dPower)

C Speed and torque

C Torque and dSpeed

C Speed and dTorque

C Duration and magnitude of change in power

The specific steps involved in cycle generation were the following:

1. Separate the raw vehicle data into data files by vehicle activity.

2. Load first activity file.

3. Calculate power. Add to raw data file.

4. Normalize speed using the FTP process and manufacturer’s specified rated speed. 

Normalize torque, and power using measured peak values and create a scalar-normalized

data file.

5. Calculate the time derivative of normalized speed, torque, and power.

6. Calculate the duration and magnitude of all increases, decreases, and steady-state periods

from the normalized power data.X Count occurrences of duration and magnitude of

changes in power for selected ranges. 

7. Count occurrences of power and rates of change of speed, torque, and power for selected

ranges. Count occurrences of speed and torque, change in speed at selected torque levels,

change in torque at selected speed levels, and duration and magnitude of changes in

power for selected ranges. The relative frequencies of occurrence (RFO) were collected

within the specified ranges of activity (e.g. normalized range of speed of 20 units).

8. Characteristic graphs of each activity was created for each piece of equipment. Several

formats were used to characterize the various analysis of the equipment operation:

- Scatter plots of normalized speed and load data

- RFO data for deltaY speed versus normalized torque

- RFO data for normalized speed versus delta normalized torque

- RFO plots of magnitudes and duration of delta power

9. The analysis of steps 1-8 was conducted by SwRI for each activity for each duty cycle.

10. The scalar normalized speed data (based on manufacturer specified rated speed) and

normalized torque (or load - based on the peak torque available at the given speed) was

used to generate the final set of activity comparisons for extracting the "actual" data for

the microtrip from the full body of activity data collected for the specific application. 

Microtrip Weightings

The microtrips of the agricultural tractor cycle, backhoe loader cycle, and crawler cycle were

weighted based on feedback from the engine manufacturers on the amount of time each
Technologies and Test Procedures for Low-Emission Engines

4-121

Agricultural Tractor

Idle 6%

Oxboard Ripper

18%

Tandem Offset Disc

Field Cultivator

15%

Plow

18%

Bedder

5%

Planter

5%

Turnaround

4%

Figure 4.2-2

Backhoe Loader

Idle

36%

Roading

Trenching 6%

37%

Loading

11%

Grade and Level

10%

Figure 4.2-3

application was expected to operate using a given implement performing a set function over the

lifetime of that piece of equipment. The microtrip weighting for the Agricultural Tractor cycle

may be seen in Figure 4.2-2 to Figure 4.2-4. The cycle creation was based on linking the

microtrips with transition points between each activity segment.
Regulatory Impact Analysis

4-122

Crawler Tractor

Idle

8% Clearing

11%

Road Bed Preparation

47%

Pit Activity

34%

Figure 4.2-4

In generating the duty cycles and conducting the analyses, relative frequency of occurrence

of various parameters as reported by the contractor were compared with the full set of real-world

data. Figure 4.2-5 shows the difference in the full set of real-world data collected versus the

microtrip, for one activity type. As can be seen in this figure, the difference in the total data set

and the identified microtrip was relatively small, based on the relative frequency of occurrence.
Technologies and Test Procedures for Low-Emission Engines

4-123

-20 to 20 20 to 40 40 to 60 60 to 80 80 to 100 100 to

120

0 to 20

20 to 40

40 to 60

60 to 80 

80 to 100

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

Differences in Activity and Microtrip

Normalized Speed Range

Normalized Torque Range

Roading

RFO Differences from Activity to Microtrip

Figure 4.2-.5

Example of Microtrip vs. Data Set for Tractor Activity

Cycle Creation

Each of the microtrip-based duty cycles were created based on the statistical analysis

previously described. The linked component microtrips were then reduced to 1 Hz data from the

original 3.33 Hz signal using a cubic spline interpolation. The duty cycle was then speed and

torque normalized, based on the maximum available power/torque mapping. These duty cycles

were the first set of cycles that were used for creating the composite nonroad transient duty

cycle.

4.2.2.4.2 Day-in-the-Life Duty Cycle Generation

In generating the day-in-the-life data, a similar chi-square analysis was used to compare RFO

data from the running window of data with the full body of data. The distinction lies in that this

was not done for multiple activity types for each piece of equipment. The analysis was

conducted using a nineteen-minute window incremented at one-minute intervals. The approach

used for data reduction, while similar, also varied in that the bin increments used for the day-inthe-life duty cycles was 100 rpm and 200 lb-ft for torque versus the normalized 20 percent

windows from the microtrip approach. The steps taken by SwRI are as follows.
Regulatory Impact Analysis

Z

High transient duty cycles (speed or torque) represent the single most transient speed or torque window of data

(highest number and magnitude of instantaneous changes in speed or torque) from the full body of data. 

4-124

1. Define “bins” sized at 100 rpm for speed by 200 ft-lb for torque.

2. Sort entire data file (e.g. 376,768 observations ~ 26 hours) into bins.

3. Compute a frequency table to indicate the number of observations contained in each bin. 

Similar to the RFO bins from the microtrip analysis.

4. Increment within data file by 1 minute, and sort the next 19 minutes

5. Compute the chi-square statistic for comparison with frequency distribution of the

population data file.

6. The approach to analyzing each nineteen-minute “window” of activity was repeated at

one-minute increments for the entire body of data.

7. The window of activity that best represented the full body of data for that piece of

equipment was selected as the most typical duty cycle.

8. Four iterations on the analysis was conducted to develop a typical 1 duty cycle, a typical 2

duty cycle, a high transient speedZ

 duty cycle, and a high transient torque duty cycle for each

application.

9. For each window of activity, the data used were the actual, contiguous data from the body

of data for that piece of equipment. 

Given the nature of this data-generation process, the detailed analysis needed for weighting

the microtrips and determining the time basis for inclusion into a composite cycle was not

needed. The resulting duty cycles were simply the result of the extraction of data from the

complete raw data set, which were subsequently normalized. 

4.2.2.4.3 Excavator Cycle Generation

Data files for each piece of equipment were appended together in chronological order to form

a data population for that excavator. Each data population contained columns for time of data

acquisition (incremented at 5 Hz), engine speed, and rack position. Data for engine speed and

rack position were used to compute a column for torque in units of pound-feet (lb-ft), based on

the rack-to-torque algorithm using correlation information compiled earlier for the corresponding

excavator engine. Tasks of choosing the representative segments to form a composite excavator

cycle were then initiated based on these two different data populations.

The in-use data population of each excavator was sorted into two-dimensional intervals or

“bins,” and a histogram was compiled based on the frequency of occurrences for speed and

torque pairs within the designated bins. The percent or relative frequency of occurrence (RFO)

is considered a histogram that describes the data population. By choosing a segment that closely

matched the characteristic RFO compilation, it is therefore rationalized that the chosen segment

is indeed representative of the given data population. Using the same bin intervals as were

applied to create a histogram (RFO) for each data population, a similar histogram was created for

each 380-second candidate segment of data. Each candidate segment overlapped the previous

segment by 320 seconds, as the process for excerpting candidate segments incremented through
Technologies and Test Procedures for Low-Emission Engines

4-125

the data population using a 60-second step size. Chi-square analyses tested each candidate

segment to rank each segment by comparing its RFO histogram to the RFO histogram created for

its associated data population. The following is the approach used for computing a chi-square

statistic, relative frequency of occurrence distributions to that of the corresponding population

for engine speed and torque values, for each candidate segment:

1. Define “bins” for speed expressed in rpm, and torque as lb-ft

2. Sort each data population (approximately 38 hours, at 5 Hz) into bins

3. Compute a relative frequency of occurrence table to indicate the percentage of

observations contained in each bin

4. Increment through the data population by 60 seconds, sort the next 380-second segment

into similar bins, and compute a relative frequency of occurrence table

5. Compute a chi-squarea statistic for comparing the frequency distribution of the segment to

that of the population

6. Repeat Steps 4 and 5 for all such 380-second candidate segments, for an entire data

population

7. Sort segments by increasing chi-square rank (low statistic means good correlation)

Note: The chi-square statistic is the summation of:

(Oi

 - Ei)

2

 / Ei

where Oi is the observed frequency in the ith interval of the 380-second sample window, and

Ei is the expected frequency of the ith interval based on the frequency distribution of the

entire population.

The sliding 380-second "window" was used to determine the distribution of speed-torque

combinations experienced by each type of equipment over the entire range of operating data

collected on each unit. The "window" was advanced by one-minute increments through the data

to determine a most typical segment for each excavator and a second most typical segment for

the lower-powered unit. 

Based on initial torque map information obtained with each engine on the steady-state test

bench, a normalizing process was applied to each of the 5 Hz data segments (part of “data

smoothing”). FTP normalizing methods outlined in the 40 CFR part 86, subpart N, were used

for expressing observed engine speed and torque values for the three selected segments of 5 Hz

data in terms of the percentage of an engine’s full load performance and idle speed. The 5 Hz

data for segments chosen to represent the first- and second-most typical segments in the data

population generated with the Caterpillar 320BL excavator were normalized using the rated

speed and torque map information obtained with the Caterpillar 3066T engine mounted on the

steady-state test bench. Similarly, the 5 Hz data for the segment best representing the typical

operation of the higher powered Hitachi excavator were normalized using torque map

information obtained for the Isuzu A-6SD1T engine on the steady-state test bench.
Regulatory Impact Analysis

AASteady State Operation is defined as an instantaneous speed or torque change less than 2% of the maximum

magnitude.

4-126

An averaging method was applied to the three selected segments to convert each segment

from the original 5 Hz to 1 Hz data files. Each 5 Hz data pair was first normalized and then the

percentage values were averaged. In general, the smoothing technique produced a value for

speed and a value for torque for each one-second interval (1 Hz) by averaging the five values in

the interval of interest.

After establishing in-use operating engine speed and torque data populations for excavators

rated in both the low and high power ranges, three representative segments were appended

together to form a 20-minute composite excavator cycle. The first two segments were the most

representative data from the lower and higher powered excavators, respectively. The third

segment represented the second-most typical data from the lower-powered excavator (i.e.,

ranked number two in chi-square analyses for that population). This resulted in a composite

cycle that was apportioned with two-thirds data gathered from the Caterpillar 320BL excavator

rated in the 100 to 175 hp range, and one-third from data gathered from the Hitachi EX300LC

excavator rated in the 176 to 300 hp range. The three segments were then joined into a

composite 20-minute excavator duty cycle by the addition of appropriate transition segments

leading into and linking each segment of transient operation. A three-second transition joined

Segment 1 and Segment 2, and similarly another three-second transition joined Segments 2 and

3. A no-load idle condition was appended for 27 seconds at the beginning and end of the cycle.

4.2.3 Composite Cycle Construction

Having all seven application cycles in hand, including the four cycle variations apiece for the

arc welder, skidsteer loader and rubber-tire loader, we began construction of a transient

composite nonroad duty cycle. The approach for addressing the weighting of contributions from

each equipment type to the composite cycle was left at equally weighting each contribution. 

While consideration was given to population-weighted or inventory-based weighting factors for

the composite cycle, in the interest of ensuring a universally applicable cycle, no unique

weighting factors were assigned. The decision of which data segments to extract from the

component duty cycles was based on uniqueness of operation (avoidance of replicate data in the

composite cycle) and level of transient operation (steady-state operation was not included in the

transient cycle).AA Extracted cycle segments were linked using three second transition periods,

when needed, to ensure smooth transitions within the cycle and to avoid spurious data generation

based on changes in speed and load that were unrealistic between segments. Transition periods

were deemed necessary when the change in the magnitude of the torque or speed value was

greater than twenty using the normalized data. The cycle was constructed using the

denormalized segments for each component cycle based on the original engine map for the

engines used to generate the component cycles. Once the raw data were available, the

normalization based on the max speed map was conducted. This was necessary because each

cycle was originally normalized using different procedures (e.g., FTP speed and torque
Technologies and Test Procedures for Low-Emission Engines

BBGCS Speed or Governed Central Speed is defined as the speed corresponding to the point along the engine’s

MAP (maximum allowable power) curve at which power is 50% of maximum measured rated power once the

maximum measured power has been surpassed.

4-127









Supplemental NRTC (Nonroad Transient Composite) Cycle

Application Nonroad Application Application in Segments from Segment Segment Cumulative Segment in

Number Application Duration Cycle Position Application Cycle Name Duration Cycle Time Cycle Position

(seconds) (#seconds) (#seconds) (seconds) (seconds) (#seconds)

Start/Transition 28 28 0-28

1 Backhoe Loader 206 29-234 52-86 Roading 35 63 29-63

108-141 Trenching 34 97 64-97

174-218 Loading 45 142 98-142

351-442 Grade/Level 92 234 143-234

2 Rubber-Tire Loader 184 235-418 746-822 Typical Operation 77 311 235-311

531-637 Hi-Spd Transient 107 418 312-418

3 Crawler-Dozer 209 419-627 85-206 Road Bed Prep 122 540 419-540

376-462 Clearing 87 627 540-627

4 Agricultural Tractor 150 628-777 265-414 AgTractor 150 777 628-777

5 Excavator 35 778-812 319-338 LowerHp (128Hp) 20 797 778-797

431-445 HigherHp (208Hp) 15 812 798-812

Transition 3 815 813-815

6 Arc Welder 204 816-1019 1007-1103 Typical Operation 97 912 816-912

544-650 Hi-Spd Transient 107 1019 913-1019

7 Skid Steer Loader 185 1020-1204 264-365 Typical Operation 102 1121 1020-1121

150-232 Hi-Trq Transient 83 1204 1122-1204

Idle/Transition/End 34 1238 1215-1238

Figure 4.2-6

normalization or GCSBB speed with FTP torque normalization). The MAP used for normalizing

the raw data remained FTP-based (percent of maximum torque at the given speed) for torque. 

The Maximum Speed Determination was used for the speed normalization. Figure 4.2-6

identifies the location of the cycle segments as extracted from the component application duty

cycles, the segment duration, and segment position in the composite duty cycle.
Regulatory Impact Analysis

4-128

NRC Compared to the 10 Cycle 

Means and the 95% Confidence Limits

0

20

40

60

80

100

Speed accels/min Speed decels/min Torque accels/min Torque decels/min Avg. Speed Avg. Torque

NRC Mean+CL Mean-CL Mean

4.2.4 Cycle Characterization Statistics

The characterization of the operational data were also subsequently revisited for purposes of

comparison in addressing composite cycle construction. The nature of the transient activity is

characterized in a report to EPA by Dyntel.159 The goal of the analysis was to provide an

assessment of the transient nature of nonroad activity between different applications. These

analyses (small bin, large bin, and general cycle) were used to address the comparability of the

resulting composite nonroad diesel transient duty cycle to the component data set that was

collected for each of the component cycles. The size of the bin was simply a reference to the

scale used for the analysis (either coarse or fine). As may be seen in Figure 4.2-7, the composite

nonroad transient duty cycle fit well within the average of all of the original nonroad duty cycles

based on the operational data. The figure is a plot of the nonroad composite cycle characteristics

with the statistics of the remainder of the nonroad diesel cycles plotted as a mean with the

standard deviation between those statistics from the other cycles shown. The ten cycles

represented include: 

•Ag Tractor • Backhoe 

•Crawler •Arc Welder Typical 2

•Skid Steer Typical 1 •Wheel Loader Typical 1

•Wheel Loader High Torque Transient •Excavator

•Arc Welder High Torque Transient •Skid Steer Loader High Torque Transient

Figure 4.2-7

Summary of Nonroad Cycles Comparison to NR Composite
Technologies and Test Procedures for Low-Emission Engines

CC GCS is the speed value on the Maximum Achievable Power (MAP) curve of an engine at which the engine’s

speed is 50% of the measured rated power for that engine, after measured rated power has been passed on the MAP

curve.

4-129

4.2.5 Cycle Normalization/Denormalization Procedure

The actual values for speed and load in rpm and lbs-ft for each of the application cycles

needed to be converted into normalized values before any application cycle could be used on an

engine, other than the engine originally used to create the application cycle itself. This process

of normalization entailed converting the actual in-use operating speed and load values of the

“raw” duty cycle, as recorded from the engine used to create the cycle originally, into a

percentage of that engine’s maximum achievable speed and load values. This yields a schedule

of percentage-based speed and load values that can be converted to absolute values for speed

(rpm) and load (lbs-ft). This conversion depends on applying the normalized percentage values

for speed and load to the maximum achievable power (MAP) for the new test engine. 

Multiplying the percentage values of the normalized cycle by the measured speed and load

maximums of the new engine’s MAP curve, in fact, denormalizes the cycle. This means that the

denormalized speed and load values may be used as commanded values on a test cell

dynamometer to exercise the new engine in exactly the same manner as the original engine was

run for a particular application cycle. The load values in lbs-ft for each of the seven types of

application cycles and all their cycle permutations, i,e., Typical, High Transient Speed , etc.,

were all converted to normalized values (and conversely, into denormalized values, at later

times) using the FTP normalization procedure detailed in 40 CFR Part 86. The speed values in

rpm for each type of application cycle were normalized initially in one of three different ways.

The speed values in each of the original microtrip cycles, the agricultural tractor, backhoe

loader, and crawler-dozer, were all normalized using the FTP procedure. The speed values in

each of the original day-in-the-life cycles, rubber tire loader, skidsteer loader and arc welder

were all normalized using the governed central speed procedure (GCS).CC The speed values in

the excavator cycle were normalized, and later denormalized, using the FTP normalization

procedure detailed in 40 CFR Part 86. However, in time and for the construction of EPA’s

composite nonroad cycle, all the application cycles were normalized using the Agency’s

Maximum Speed determination procedure.

The Maximum Speed Determination procedure uses the measured speed and load values

from an engine’s power curve to determine what is the maximum power that the engine can

attain and at what speed that engine will achieve its maximum power. This value for speed at

maximum power can then be used in lieu of a manufacturer’s rated speed number for a particular

engine to conduct a normalization or denormalization of engine or cycle for purposes of running

a duty cycle on a particular engine. The procedure is based on a spreadsheet calculation and is

discussed in our analysis of comments associated with the final rule for marine diesel engines

(64 FR 73300, December 29, 1999).160, 161 As detailed in Figure 4.2-8, the maximum speed can

be found below the point on the engine power curve that is the farthest distance from the point of
Regulatory Impact Analysis

4-130

0

20

40

60

80

100

120

140

0 250 500 750 1000 1250 1500 1750 2000 2250 2500

rpm

hp

Power Curve

Max Test

Speed

Mfr’s rated

speed

Figure 4.2-8

Maximum Test Speed Determination

origin of the graph of engine’s measured speed and power values. That farthest point on the

curve is described as the point of maximum power achievable by the engine under study.

4.2.6 Cycle Performance Regression Statistics

In assessing the nonroad transient duty cycles, ten nonroad diesel engines were exercised

over the nonregulatory162 nonroad duty cycles to assess emission impacts of each duty cycle, as

well as to determine the ability of typical nonroad diesel engines to pass the existing highway

cycle performance regression statistics. That data may be seen in a report from SwRI with an

accompanying EPA summary of the results in the Memorandum to EPA Air Docket 2001-28

from Cleophas Jackson entitled “Nonroad Duty Cycle Regression Statistics.” Subsequent

analysis on the composite nonroad transient cycle was based on test cell data collected from

testing at the National Vehicle and Fuel Emissions Laboratory and Southwest Research Institute,

as well as through the European Commission’s Joint Research Center (EC-JRC), and various

engine manufacturers from the United States, Europe, and Japan.

4.2.7 Constant-Speed, Variable-Load Equipment Considerations

Some nonroad diesel engines operate in equipment that calls for constant engine speeds. 

Some examples of engines in this category of nonroad diesel equipment include pumps,

electrical power generator sets (gen sets), pavement saws and cement mixers. While the

operating speed in many cases is not truly constant, it is generally true that the unit’s speed will
Technologies and Test Procedures for Low-Emission Engines

4-131

vary little during operation. These types of equipment are more tolerant of changes in operating

load than other more closely governed constant-speed nonroad applications. Some pieces of

constant-speed equipment will be governed to a nominal “zero” variation in rpm during

operation for critical operations such as maintenance of electrical power and refrigeration loads. 

For those engines designed to operate under less restrictive, more “transient” conditions, the

Agency had proposed an alternative constant-speed, variable-load (CSVL) transient duty test

cycle over which an engine manufacturer might operate their engines. The CSVL duty cycle

was meant to capture emissions from these infrequent modes of operation. However, after a

review of comments and a broader look at the wide range of applications embraced by the

constant-speed, variable-load segment of the nonroad diesel equipment population, the Agency

has chosen not to adopt a CSVL transient test cycle at this time. Instead, EPA, with all of its

stakeholders in this regard, will map out a process of engine testing and analysis to better

characterize constant-speed equipment in-use to design the most appropriate test cycle for the

largest number of constant-speed engines. Consideration will also be given to addressing the

operation of gen set applications as a potentially unique subset of this category. EPA

undertakes this process with an eye to initiating a rulemaking which would lead to promulgation

of a transient cycle for constant-speed engines before the Agency's 2007 Nonroad Technical

Review. 

4.2.7.1. Background on Cycle Considered

The CSVL transient test cycle was derived from EPA's Arc Welder Highly-Transient Torque

nonroad application duty cycle. That cycle was developed on a direct-injection, naturallyaspirated, 30kW (40 hp) diesel arc welder engine, a constant-speed application running at

variable load. The Highly-Transient Torque cycle, one of four arc welder cycles, is comprised of

a single twenty-minute segment of all the real-time operating data collected on that engine.

While designed to control nonroad engines in a broad range of constant-speed applications,

commenters noted that EPA’s proposed CSVL test cycle had an average speed which was lower

than the speed which many manufacturers considered optimal for their constant-speed engines

in-use. Further, EPA had received comments that many constant speed engines operated near or

at their rated engine rpm during much of that engine's useful life, as with electrical generating

sets in particular. EPA had proposed that these constant-speed engines, when tested in the

laboratory with installed speed governors, be required to meet cycle statistics for engine load but

not for engine speed. This relief was aimed at addressing the twin concerns that many engines

operated at a significantly high percent of their rated speed much of the time in-use and had

different degrees of engine speed variation during that operation.

Engine manufacturers raised additional design concerns for constant-speed engines required

to meet emission standards over EPA’s proposed cycle. Their concerns generally focused on the

fact that the cycle had relatively light engine loads and was derived from an arc welder powered

by a naturally-aspirated engine. Commenters questioned the representativeness of the CSVL

cycle for generators, which they claimed was a more common application within the

constant-speed engine population than was an arc welder. A second issue involved the average

load that would be experienced by an engine running on the CSVL test cycle. The average load
Regulatory Impact Analysis

DD- When the arc welder application was originally considered for inclusion in the cycle generation effort, EMA

endorsed EPA's choice of the arc welder as a constant speed application.

4-132

factor of the normalized application cycle was approximately 25% of engine capacity. 

Manufacturers of constant-speed engines with significantly higher load factors on their engines

during operation, upwards of 90% of normalized engine load at constant speed, argued that their

engines would not be able to pass cycle-regression statistics for certification without significant

re-tuning of the engines to operate over the CSVL cycle. Several commenters noted that some

nonroad constant-speed engines with high brake-mean effective pressures (BMEP), or high

rated-power constant-speed engines, were narrowly focused on providing higher power

capability at a single speed while meeting emission requirements. These engines used larger,

less-responsive turbochargers to achieve their requisite higher BMEP. Manufacturers pointed

out that the smaller BMEP engine on which the arc welder cycles were developed was more

responsive to torque changes than their high BMEP engines were designed to encounter. As

such, these manufacturers felt that their engines would be penalized by the number and

magnitude of torque changes in the CSVL cycle.

At the same time, however, the Agency shared engine manufacturers' concerns for creating a

duty cycle that achieved emission reductions while appropriately modeling in-use operation of

their engines. EPA would have find it unproductive to require an approach that lead merely to

improvements in the operation and emissions of the engine under laboratory conditions which,

were in turn unrelated to the engine's in-use operation. Based on the comments the Agency has

received regarding the constant-speed, variable-load duty cycle, we intend to continue to work

with all interested parties to develop a new constant-speed, variable-load duty cycle. The

Agency envisions that any new test cycle would result in comparable stringency for ensuring

effective in-use control, as does the current duty cycle developed for fully transient test

characterization - EPA's NRTC test cycle.

4.2.7.2. Follow-on Constant-Speed Engine Testing and Analysis 

In consultation with the Engine Manufacturers Association (EMA) and other stakeholders,

the Agency will embark on a process with the nonroad engine and equipment manufacturers that

will result in collection of additional engine operation data that will appropriately characterize

the operation of nonroad diesel engines used in equipment in constant-speed applications. To

ensure that the data collected is robust and applicable to most, if not all, segments of the nonroad

equipment market, and to facilitate global technical regulations and eventual cycle

harmonization, the Agency, manufacturers and other interested parties, in consultation with

non-domestic governmental entities will work together to develop a plan that incorporates the

following elements:

Define operation of a non-generator, non-transient equipment class: 

– Target Equipment/Application TypesDD
Technologies and Test Procedures for Low-Emission Engines

EEThe Agency's current data base for cold start operation includes construction equipment in the power range of

150 to 350 hp.

4-133

•air/gas compressors, pressure washers, water/irrigation pumps, oil field equipment,

hydro power units, leaf blower/vacuums, shredders, bore/drill rigs, mixing

equipment, pavement saws, arc welding sets, chippers/shredders/grinders, light

plants/sign boards, tampers, rammers, and plate compactors, concrete/industrial saws,

crushers/material handling equipment and refrigeration/AC equipment;

– Engine Speed Range - anticipate EMA feedback

– Power range

• 25 to 175 hp, 175-350 hpEE, and 350 to 750 hp

– Market Sectors

• construction, agriculture, maintenance/handling, pumps/welders

Define sample sizes, duration of "cycle" for application intercomparisons :

– Number of pieces of equipment in each category

• Sufficient to discern significant differences in speed and load characteristics

– Number of hours of operation per application per site

• Forty or more hours of operating data

Define data collection parameters:

– Speed 

– Load

– Exhaust Temperature

– Engine Oil Temperature (1st 20 minutes of engine on after 4 hours of engine off)

– Engine Coolant Temperature (1st 20 minutes of engine on after 4 hours of engine off)

In addition to ensuring that the sampling plan addresses the issues outlined above, EPA will

seek agreement among the stakeholders on the level of involvement of all parties in the data

collection and generation, data reduction and analysis, and final cycle construction and

assessment efforts. Initially, the logistical questions concerning program timing and duration of

all parts of the data collection and eventual cycle development efforts would have to be charted

and agreed upon by program participants. EPA expects that broad groupings of nonroad engines

from various applications would then be compared between and among each other to determine

whether particular applications differed in terms of speed and load operating characteristics (see

Figure 4.2-9 below). One question which is particularly important is whether “constant speed”

applications are similar to one another, but different than either transient or generator-type

applications. As we move forward with the process of data collection and subsequent cycle

generation, other interested parties, including the state of California, will also be invited to

participate in these efforts. Future engine emission control technologies would need to be

anticipated and considered for their impacts on nonroad equipment emissions.
Regulatory Impact Analysis

4-134

Engine Categories

with respect to Certification Cycles

Generator Sets ‘Constant Speed’

- Arc W elders

- Pumps

- Oil Rigs

- Pavem ent Saws

- Irrigation Sets

-Industrial Vacuum s

‘Transient’

- Backhoes

- Dozers

- Others?

Measure: speed, load Measure: speed, load, 

em issions

Measure : on/off

Arrow s represent exam ples of com parisons between applications and engine groups, to determ ine

w hether applications differ in term s of speed/load characteristics. An im portant question is w hether the 

‘constant speed ‘applications are sim ilar to each other, but different from generators and 

’Transient applications.’ 

Figure 4.2-9 

4.2.8 Cycle Harmonization

4.2.8.1 Technical Review

One concern raised by the engine manufacturers was that the mapping method used to

generate the real-world torque data introduced an error by no appropriately accounting for the

impact of transient activity of the actual torque signal from the engine. The basis of the issue

was primarily a torque signal in the field, based on the rack position, that may not have actually

occurred had an in-line torque meter been employed. Two aspects of this warrant review. The

first aspect of actual torque versus inferred torque. The second aspect of this issue is whether or

not rack position or the demanded load is an appropriate metric for developing duty cycles

representing real-world operation. To address the second issue in the context of responsiveness

of a nonroad engine, it should be clear that, although feedback torque from the engine provides a

clear signal of what was accomplished by the engine, it is not a fair metric of the demanded load. 

Given the fact that a typical operator or driver tends to demand a desired torque the engine’s

response to that demand, though not distinct, is a separate issue. It is this reasoning through

which command cycles are generated. The command cycle represents the speed and load

demanded of the engine. The engine’s responsiveness can be addressed through performance

statistics. 
Technologies and Test Procedures for Low-Emission Engines

4-135

No. Engine Mfg Engine Model Machine Mfg Machine Model Application Rated Power (Kw)

Peak 

Torque (Nm)

Rated 

Speed 

(RPM)

Low Idle 

(RPM)

1 Caterpillar 3204-D17 Caterpillar Cat D4H Crawler Tractor 85 peak 442 2200 800

2 Caterpillar 3114-D17 Caterpillar Cat 446B Backhoe Loader

76.8 peak; 70.8 

rated 405 2200 800

3 Caterpillar 3408E - TA Caterpillar 988F-II Wheel Loader (2) 321 2100 850

4 Isuzu A-6SD1 TQA Hitachi EX-300LC Excavator High Power 161 834 2000 850

5 John Deere 6081 John Deere JD 4960 Ag Tractor 186 970 2200 850

6 Mitsubishi 3066T Caterpillar Cat 320 Excavator Excavator Low Power 95 641 1800 860

7 Perkins '97 D3.152 Lincoln

97 'Shield-Arc' 250, 

K1283 Arc Welder 28 1725 800 (1)

8 Yanmar '97 4TNE84 Daewoo DSL-601 Skid Steer Loader 31 121 2800 800

Table 4.2-9

Nonroad Diesel Engines Used for Cycle Generation

No. Engine Mfg Engine Model

Total Inertia 

(Kg-m2) 

Total Inertia 

(N-m-s2) 

Engine Inertia 

(N-m-s2 = kg-m2) 

Flywheel Inertia 

(N-m/s2 = kg-m2) 

1 Caterpillar 3204-D17 1.7899 1.7899 0.2249 1.5650

2 Caterpillar 3114-D17 0.9770 0.9770 0.5550 0.4220

3 Caterpillar 3408E - TA 2.8637 2.8637 1.3147 1.5490

4 Isuzu A-6SD1 TQA 7.5303 7.5303 2.8263 4.7040

5 John Deere 6081 2.4400 2.4400 0.5000 1.9400

6 Mitsubishi 3066T 0.9160 0.9160 0.2160 0.7000

7 Perkins '97 D3.152 0.1083 0.1083 0.1083

8 Yanmar '97 4TNE84 0.2317 2.3629

Table 4.2-10

Engine Inertia Data Used for I" Correction Calculation

Engine manufacturers sought to address the first concern through a playback analysis that

addressed the I" correction as an offset to the commanded load signal. The playback approach

would involve rerunning one of the engines (identical engine model) in the test cell over the

defined duty cycle with the calculated I" offset to measure torque using an in-line torque meter. 

Manufacturers provided the inertia data for their engines either used for cycle development or

anticipated to be included in the testing program. The data provided by members of the Engine

Manufacturers Association (EMA) may be seen in Table 4.2-9 and Table 4.2-10.

The correction that was undertaken by EPA and Southwest Research Institute (SwRI) used

the following methodology. The original 3 Hz data set was used to correct the torque data rather

than interpolated 1 Hz data to ensure the raw data were corrected to avoid error propagation

within the 1 Hz scalar data.

1. Apply the I" correction to calculate the new torque command.

2. Apply original technique to create 1 Hz raw command cycles using the cubic spline

interpolation for the those cycles that were originally collected at 3.33 Hz. 

3. Each resultant correct raw data duty cycle was then normalized using the Maximum Speed

determination method (See Section 4.2.3). 
Regulatory Impact Analysis

4-136

4. Cycle segments for the Composite Nonroad Transient duty cycle were then reassemble

from the component duty cycles.

The result of the correction, as conducted by SwRI, was that there were very small

modifications to the most severe torque excursions. The peaks and valleys were trimmed

slightly. The overall change in the cycle resulted in less than 0.5% correction, typically.

4.2.8.2 Global Harmonization Strategy

4.2.8.2.1 The Need for Harmonization

Given the increasingly global marketplace in which nonroad engines are sold, alignment of

standards and procedures helps facilitate introduction of cleaner technology at lower across in

multiple markets. Given the nature of the nonroad diesel market with a large number of very

diverse product offerings and in some cases, small niche market volumes, the ability to design

once for different markets helps reduce the costs, especially of the lower volume equipment

models. While alignment of limit values may be a key component of harmonized regulations,

alignment of test procedures, measurement protocols, and other aspects of certification and

testing procedures help reduce the testing burden manufacturers will face when selling and

distributing their products in multiple markets. Much of the development of new procedures and

test methods has originated in the United States, Europe, and Japan. While other markets tend to

adopt emission limits and procedures as a part of a more global process on a different time

frame. Given the nature of regulatory and technological development, allowing the leading

markets for which new technology will need to be introduced to have comparable protocols

simply reduces the costs those markets will be forced to absorb. In any effort to utilize

procedures in multiple regulatory arenas, care should be taken to include an assessment of

equivalence and appropriateness. In so doing, both Europe and the United States conducted an

assessment of real-world operation of nonroad diesel equipment. The data-collection effort in

the United States started in 1995. The subsequent data-collection effort in Europe confirmed

that, as expected, nonroad diesel activity in Europe was comparable.

In moving forward with a single test cycle for both Europe and the United States, and

potentially a global nonroad diesel cycle, the basic framework for the cycle was agreed upon. In

addition to the work initiated by the Agency in compiling a nonroad transient duty cycle, it was

important to ensure that concerns about global suitability be addressed. The context used for this

assessment in Europe was the existing European Transient Cycle (ETC). While this duty cycle

was developed for highway diesel applications, it was seen as an adequate basis for which

European industry and government staff could assess EPA’s proposed Nonroad Transient Duty

Cycle. Representatives from Japan’s government and industry have periodically participated in

this process as well; however, no such framework for comparison was requested for the

evaluation process from any representative from Japan. Throughout the development of the duty

cycle, industry representatives from the United States, Europe, and Japan have provided detailed

technical input. In Table 4.2-11 shows early results presented by Deutz exercising a nonroad

diesel engine over the EPA-generated Nonroad Transient Duty Cycle indicating an ability to

pass cycle performance criteria with only a slight problem with the Torque Intercept statistic.
Technologies and Test Procedures for Low-Emission Engines

FFMemorandum to EPA Air Docket A-2001-28 from Cleophas Jackson, Report from the JRC entitled

“Contribution to the NRTC Development Based on Test Data Supplied by Engine Manufacturers,” February 26,

2001.

4-137

Speed Torque Power

Standard error of estimate measured NRTC 56,48 rpm 7,58% 7,15%

(SE) ETC 24,29 rpm 6,59% 5,67%

tolerance max 100 rpm max 13% max 8 %

Slope of the regression line measured NRTC 1,010 0,925 0,968

(m) ETC 0,990 0,963 0,976

tolerance 0,95 to 1,03 0,83 to 1,03 0,89 to 1,03

Regression coefficient measured NRTC 0,996 0,958 0,973

(r2) ETC 0,993 0,980 0,981

tolerance min 0,9700 min 0,88 min 0,91

Y intercept of the measured NRTC 18,01 rpm 30,10 Nm 3,62 kW

regression line (b) ETC 17,67 rpm 5,80 Nm 0,62 kW

tolerance +/- 50 rpm +/- 20 Nm +/- 4 kW

red: out of tolerance

green: near to tolerance limit

Table 4.2-11

Initial Deutz Data Submission for 

EPA Nonroad Diesel Transient Duty Cycle (Nov. 13, 2000)

4.2.8.2.2 Harmonization Methodology

The composite Nonroad Transient (NRTC) duty cycle developed by the Agency was used as

the reference cycle for conducting subsequent development and testing work. It was originally

introduced to the global regulatory community and engine industry in Geneva in June 2000. 

After an on-going dialogue with industry in the United States and Europe, additional

modifications were suggested by the European Commission based on manufacturer concerns

with their ability to meet test cell performance statistics with this duty cycle. In September 2001,

it was decided by a joint European, American, and Japanese government and industry workgroup

that the Joint Research would use the then “candidate” cycle to conduct additional changes

commensurate with the goal of not allowing the instantaneous transient speed and torque

changes to be greater than those experienced within the European Transient Cycle (ETC). Using

a Bessel filtering algorithm, the cycle was then modified by the EC-JRC to meet the ETC target

of 23% of torque events faster than 4 seconds. The two cycles may be seen on a time basis in

Figures 4.2-11 and 4.2-10. The average load and average speed of each cycle are shown in

Table 4.2-12. The speed characteristics of the original cycle were similar to the speed

characteristics of the ETC. This is not an indication that the speed trace was identical, but rather

that the maximum instantaneous speed changes of the NRTC were similar to the maximum

instantaneous speed changes of the ETC.FF 
Regulatory Impact Analysis

4-138

Draft Nonroad Transient Duty Cycle

0

10

20

30

40

50

60

70

80

90

100

110

1

4487

130173216259302345388431474517560603646689732775818861904947990

10331076111911621205

Time (seconds)

Normalized Values

Speed

Load

Figure 4.2-10

EPA Nonroad Transient Test Cycle as of March 2001

Table 4.2-12

Comparison of Cycle Averages

Duty Cycles Average Normalized Speed Average Normalized Torque

EPA NRTC 63% 47%

JRC Modified NRTC 68% 39%
Technologies and Test Procedures for Low-Emission Engines

4-139

Joint EPA-EU Nonroad Transient Cycle, March, 2002

0

10

20

30

40

50

60

70

80

90

100

110

1

4181

121161201241281321361401441481521561601641681721761801841881921961

100110411081112111611201

Time (seconds)

Normalized Values

Speed Load

Figure 4.2-11

JRC Nonroad Transient Test Cycle after Bessel Filtering 

The following figures 4.2-12 through 4.2-16 describe the JRC Modified NRTC with respect

to speed and load and the transient nature of the cycle. This will be contrasted with the same

characteristics of the EPA- generated NRTC. The JRC modified NRTC was also known as the

San Antonio cycle or the JRC.
Regulatory Impact Analysis

4-140

0

10

20

30

40

50

60

70

March EPA Cycle

JRC NRTC

Average Speed Average Load

Figure 4.2-12

Speed Changes EPA March NRC

-80

-60

-40

-20

0

20

40

60

80

100

1

4691

136181226271316361406451496541586631676721766811856901946991

10361081112611711216

Time (seconds)

Normalized Speed Changes

Speed Changes

Figure 4.2-13

Average Speed Changes of the EPA NRTC
Technologies and Test Procedures for Low-Emission Engines

4-141
Regulatory Impact Analysis

4-142

JRC_NRC Speed Changes

-60

-40

-20

0

20

40

60

1

4181

121161201241281321361401441481521561601641681721761801841881921961

100110411081112111611201

Tim e (seconds)

Normalized Speeds

Figure 4.2-13

Average Speed Changes of the EPA NRTC

Figure 4.2-14 

Average Speed Changes of JRC Modified NRTC
Technologies and Test Procedures for Low-Emission Engines

4-143

JRC_NRC Load Changes

-150

-100

-50

0

5 0

100

150

1

4079

118157196235274313352391430469508547586625664703742781820859898937976

101510541093113211711210

Tim e (seconds)

Normalized Load Changes

Figure 4.2-15

Average Load Changes of JRC Modified NRTC
Regulatory Impact Analysis

4-144

March EPA_NRC Load Changes

-150

-100

-50

0

50

100

150

1

4079

118157196235274313352391430469508547586625664703742781820859898937976

101510541093113211711210

Time (seconds)

Normalized Load Changes

Figure 4.2-16

Average Load Changes of the EPA-Generated NRTC

Given the modifications in the duty cycle, it was critical to assess the impact on the emission

signature of the cycle. Table 4.2-13 shows that the emission signature, based on tests at the

National Vehicle and Fuel Emissions Laboratory and at Southwest Research Institute as of May

2001, were relatively unchanged.
Technologies and Test Procedures for Low-Emission Engines

GGMemorandum from Cleophas Jackson to EPA Air Docket A-2001-28, # II-A-170 “JRC December 5, 2001,

Report on Cycle Performance.”

4-145

Caterpillar 3508

Heavy Duty

850 hp

Sep-00

Mar-01

JRC

NOx PM Speed

Mean Standard Dev. Mean Standard Dev. SE M R2 B

Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev.

10.30 0.02 0.20 0.004 79 1.41 1.03 0 0.949 0.001 -35 2.83

10.14 0.03 0.20 0.002 90 2.12 1.01 0.01 0.939 0.002 -9 3.54

11.198 0.03 0.20 0.004 68 0.71 1.03 0.00 0.962 0.001 -33 1.41

Torque Power

SE M R2 B SE M R2 B

Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev.

15 0 0.8 0 0.734 0.004 184 0 14 0 0.88 0 0.801 0.283 29.6 0.283

15 0 0.83 0.007 0.734 0.001 188.5 3.54 14 0 0.9 0 0.804 0.002 29.5 1.273

12 0 0.91 0.007 0.765 0.001 56 1.41 11 0 0.95 0 0.823 0 6.1 0.141

Cummins ISB NOx PM Speed

Medium Duty Mean Standard Dev. Mean Standard Dev. SE M R2 B

Mean Std dev. Mean Std dev. Mean Std dev. Mean Std dev.

Sep-00 3.76 0.01 0.08 0.001 54.7 24.62 0.987 0.011 0.987 0.010 30.0 3.11

Mar-01 3.79 0.03 0.08 0.003 68 18.67 0.98 0.01 0.982 0.008 32 14.48

JRC-Max Spd 4.06 0.03 0.08 0.002 66 6.22 0.98 0.00 0.978 0.005 34 5.23

JRC-ETC Pk Spd 4.09 0.01 0.08 0.009 50 8.15 0.98 0.00 0.991 0.003 37 6.68

Torque Power

SE M R2 B SE M R2 B

M ean Std dev. M ean Std dev. M ean Std dev. M ean Std dev. M ean Std dev. M ean Std dev. M ean Std dev. M ean Std dev.

69.7 2.06 0.955 0.011 0.930 0.005 30.0 3.11 14.8 0.35 0.979 0.009 0.943 0.003 4.5 0.361

67.5 3.12 0.96 0.008 0.933 0.007 26.7 2.64 14.9 0.61 0.981 0.007 0.943 0.005 4.2 0.404

43.5 0.14 0.981 0.002 0.960 0.001 12.0 0.354 9.9 0.21 0.994 0.002 0.961 0.002 1.6 0.141

48.4 2.63 0.985 0.00306 0.946 0.005 11.6 1.386 10.0 0.68 0.999 0.002 0.958 0.005 1.6 0.265

Table 4.2-13

Emissions and Cycle-Regression Performance Summary as Presented to

the Workgroup on June 1, 2001, at the Joint Research Center in Ispera, Italy

As noted earlier, EPA modified the cycle between September 2000 and March 2001 to

address concerns related to the Arc Welder duty cycle segment of the NRTC. The modified EPA

version was provided to JRC in early 2001, for its subsequent analysis; however, not knowing

the impact of the changes, all three cycles were tracked until the September 2000 version was

eventually dropped.

In subsequent data submitted by engine manufacturers through December 5, 2001, the

validity of the cycle from an emission signature and test cell feasibility perspective was

evidenced. Data submitted by Yanmar, Daimler Chrysler, Deere, Caterpillar, and Cummins to

the JRC summary and analysis effort gave clear indication that the duty cycle could be run

across multiple power ranges with good cycle performance results and consistent emission

signature.GG The cycle performance regression statistics would be defined based on nonroad

engines, rather than adopting the highway performance statistics without review. The concern

raised by Daimler Chrysler was that the cycle-regression statistics needed to be sufficiently
Regulatory Impact Analysis

HH Memorandum from Cleophas Jackson to EPA Air Docket A-2001-28, ######Nonroad Transient Duty Cycle

Development Report, Cornetti, G., Hummel, R., and Jackson, C. 

II The deletion point criteria for engine manufacturers to use in deriving these cycle performance statistics may

be found in regulations at 40 CFR Part 1039, subpart F and Part 1065.530. See also cycle performance criteria

discussions in Memorandum from Cleophas Jackson to EPA Air Docket A-2001-28, ###### Nonroad Transient

Duty Cycle Development Report, Cornetti, G., Hummel, R., and Jackson, C. and Memorandum from Matthew Spears

to EPA Air Docket A-2001-28, ##### “Test Point Omission Criteria for Determining Cycle Statistics”.

4-146

stringent to ensure an accurate and repeatable emission signature was achieved.HH With the

conclusion of the international workgroup’s efforts, EPA considered the cycle to be complete. In

an effort to facilitate the use of the cycle as a global nonroad transient duty cycle, it has been

introduced into GRPE as a candidate cycle for the global compendium. The ISO procedure

8178-11 is being drafted to address test cell procedures for exercising an engine over the duty

cycle. New limit values for the cycle performance regression statistics were developed as a part

of this process and may be seen in Table 4.2-14II.

Table 4.2-14

NRTC Cycle-Regression Statistics163

Speed [rpm] Torque [NAm] Power [kW]

Standard Error of

Estimate of Y on X

100 rpm 13% of power map

maximum engine torque

8% of power map

maximum

Slope of the regression

line, m

0.95 to 1.03 0.83-1.03 (hot)

0.77-1.03 (cold)*

0.89-1.03 (hot)

0.87 -1.03 (cold)a

Coefficient of

determination, r2

min 0.970 min 0.8800 (hot)

min 0.8500 (cold)*

min 0.9100 (hot)

min 0.8500 (cold)

Y intercept of the

regression line, b

± 50 rpm ± 20 NAm or ± 2.0% of

max engine torque,

whichever is greater

± 4 kW or ± 2.0% of max

power, whichever is

greater 

a

 Under consideration by ISO workgroup.

4.2.9 Cold-Start Transient Test Procedure

Nonroad diesel engines typically operate in the field by starting and warming to a point of

stabilized hot operation at least once in a workday. Such “cold-start” conditions may also occur

at other times over the course of the workday, such as after a lunch break. We have observed

that certain test engines, which generally had emission-control technologies for meeting Tier 2 or

Tier 3 standards, had elevated emission levels for about 10 minutes after starting from a cold

condition. The extent and duration of increased cold-start emissions will likely be affected by

changing technology for meeting Tier 4 standards, but there is no reason to believe that this

effect will lessen. In fact, cold-start concerns are especially pronounced for engines with

catalytic devices for controlling exhaust emissions, because many require heating to a “light-off”
Technologies and Test Procedures for Low-Emission Engines

JJNote that the cold-start discussion applies only to engines that are subject to testing with transient test

procedures. For example, this excludes constant-speed engines and all engines over 750 hp.

4-147

or peak-efficiency temperature to begin working. EPA’s highway engine and vehicle programs,

which increasingly involve such catalytic devices, address this by specifying a test procedure

that first measures emissions with a cold engine, then repeats the test after the engine is warmed

up, weighting emission results from the two tests for a composite emission measurement.

In the proposal, we described an analytical approach that led to a weighting of 10 percent for

the cold-start test and 90 percent for the hot-start test. Manufacturers pointed out that their

analysis of the same data led to a weighting of about 4 percent for cold-start testing and that a

high cold-start weighting would affect the feasibility of the proposed emission standards. 

Manufacturers also expressed a concern that there would be a big test burden associated with

cold-start testing.

Unlike steady-state tests, which always start with hot-stabilized engine operation, transient

tests come closer to simulating actual in-use operation, in which engines may start operating

after only a short cool-down (hot-start) or after an extended soak (cold-start). The new transient

test and manufacturers’ expected use of catalytic devices to meet Tier 4 emission standards make

it imperative to address cold-start emissions in the measurement procedure.JJ We are therefore

adopting a test procedure that requires measurement of both cold-start and hot-start emissions

over the transient duty cycle, much like for highway diesel engines. We acknowledge that

limited data are available to establish an appropriate cold-start weighting. For this final rule, we

are therefore opting to establish a cold-start weighting of 5 percent. This is based on a typical

scenario of engine operation involving an overnight soak and a total of seven hours of operation

over the course of a workday. Under this scenario, the 20-minute cold-start portion constitutes 5

percent of total engine operation for the day. Section 4.1.2.3.3 above addresses the feasibility of

meeting the emission standards with cold-start testing. Regarding the test burden associated with

cold-start testing, we believe that manufacturers will be able to take steps to minimize the burden

by taking advantage of the provision that would allow for forced cooling to reduce total testing

time.

We believe the 5-percent weighting is based on a reasonable assessment of typical in-use

operation and it addresses the need to design engines to control emissions under cold-start

operation. We believe cold-start testing with these weighting factors will be sufficient to require

manufacturers to take steps to minimize emission increases under cold-start conditions. Once

manufacturers apply technologies and strategies to minimize cold-start emissions, they will be

achieving the greatest degree of emission reductions achievable for those conditions. A higher

weighting factor for cold-start testing will likely not be more effective in achieving in-use

emission control.

However, given our interest in controlling emissions under cold-start conditions and the

relatively small amount of information available in this area, we intend to revisit the cold-start

weighting factor for transient testing in the future as additional data become available. 
Regulatory Impact Analysis

4-148

Additionally, as the composite transient test represents a combination of variable-speed and

constant-speed operations, we would consider operating data from both of these types of engines

in evaluating the cold-start weighting. We will apply the same cold-start weighting, as well,

when we adopt a transient duty cycle specifically for engines certified only for constant-speed

operation. 

The planned data-collection effort will focus on characterizing cold-start operation for

nonroad diesel equipment. The objective will be to reassess, and if necessary, develop a

weighting factor that accounts for the degree of cold-start operation so that in-use engines

effectively control emissions during these conditions. As we move forward with this

investigation, other interested parties, including the State of California, will be invited to

participate. We are interested in pursuing a joint effort, in consultation with other national

government bodies, to ensure a robust and portable data set that will facilitate common global

technical regulations. This effort will require consideration of at least the following factors:

C What types of equipment will we investigate?

C How many units of each equipment type will we instrument?

C How do we select individual models that will together provide an accurate cross-section

of the type of equipment they represent?

C When will the program start and how long will it last?

C How should we define a cold-start event from the range of in-use operation?

We expect to complete our further evaluation of the cold-start weighting in the context of the

2007 Technology Review, if not sooner. In case changes to the regulation are necessary, this

timing will allow enough time for manufacturers to adjust their designs as needed to meet the

Tier 4 standards.

4.2.10 Applicability of Component Cycles to Nonroad Diesel Market

In the 1997-1998 time frame, we started to pursue application-specific operating duty cycles

that could be normalized for laboratory testing of nonroad diesel engines. With a standardized

set of operating duty cycles, we would have a basis upon which to compare the brake-specific

emission rates of nonroad engines, both within and across power categories, or bands. These

cycles became the component cycles of the NRTC cycle. The choice of the seven nonroad

component application duty cycles was based on the frequency of finding engines of that

particular mode of operation in the nonroad population and summing those with

engines/equipment doing related work. Agricultural tractors were seen to have operations

generally similar to combines and off-highway trucks in addition to tractors. Arc welders

represented the broad group of constant-speed applications. The backhoe-loader group included

most of the lawn/garden/commercial turf tractors, commercial lifts and sweepers. The

crawler/dozer application matched with other dozer, grader and scraper applications. Rubbertire loaders were found to be similar to industrial and rough terrain forklifts, aircraft support and

forestry equipment. Skidsteer loaders were seen, at the time, as a unique application/category.

Finally, excavators and cranes were grouped together as similar applications. In time, the seven

base nonroad equipment applications, agricultural tractor, arc welder, backhoe loader,
Technologies and Test Procedures for Low-Emission Engines

4-149

crawler-dozer, excavator, rubber-tire loader and skidsteer loader were characterized for their

daily operations and engine duty cycles were constructed for each type of work.

4.2.10.1 Market Representation of Component Cycles

The determination of which cycles best represent the nonroad equipment population in the

United States was aided by an analysis of the our nonroad equipment population database.164

Our source of data placed the total 1995 nonroad equipment population figure at 7,100,113 units

in the United States. The population broke out into at least 59 different equipment applications,

or specific work categories. Agricultural tractors held the largest percentage by far at

approximately 34% of units. Constant-speed applications like generating sets, A/C and

refrigeration units comprised a further 14%. Of the remaining pieces of the nonroad equipment,

another 11% of the total population were constant-speed engines like welders, air compressors

and irrigation rigs. Commercial lawn and garden equipment made up an additional 7.5% of all

units, with combines, backhoe and skidsteer loaders at 12%, each application adding a further

4% to the total population. In the approximately 20% of units remaining, rubber-tire loaders and

crawler-dozers constituted 6% of all nonroad units, each contributing 3% to the nonroad

population. Excavators and cranes comprised a little more than 2% of the total equipment

population. The seven component application classesalone covered 51% of all nonroad

equipment units. When "related" nonroad applications were grouped with the original seven

applications, over 95% of the nonroad equipment population was represented by the component

applications.

4.2.10.2 Inventory Impact of Equipment Component Cycles

When EPA created an emission distribution from its database according to a list of the seven

nonroad applications used to create the NRTC duty cycle, those seven base applications

accounted for 59 percent of regulated nonroad engine emissions (see Table 4.2-16).

Table 4.2-16

Emissions Attributable to Base Nonroad Applications

Application Emission Distribution by

Application

Ag tractor 34%

Welder 1%

Backhoe/loader 6%

Crawler 7%

Excavator 3%

 R/T Loader 6%

Skid/steer 2%

Total 59%
Regulatory Impact Analysis

4-150

4.2.10.3 Power and Sales Analysis

The nonroad equipment market is broad and varies in both range of power available and

application, or intended use, of each piece of equipment. EPA’s database was the source for the

distribution of nonroad applications between the various engine power bands. Agricultural

tractors, while accounting for fully a third of the nonroad equipment population, are built

generally to smaller engine displacement specifications and so constituted only 20% of total

nonroad power. With similar equipment applications included, the equipment equipped with

engines that have power or displacement similar to that of agricultural tractors approaches 30

percent. Backhoe loaders, crawler dozers and rubber-tire loaders together accounted for 12

percent of the total power in the nonroad population and, with similar applications included,

accounted for approximately 35 percent of total nonroad power. The last three cycle component

applications—excavators, skidsteer loaders and arc welders, with arc welders and like equipment

generally falling under 50 hp—constitute only 8 percent of total nonroad power. However,

because small constant-speed engines exist in numerous applications, they also constitute a large

number of discrete units in the nonroad population. This helps to explain their relatively large

contribution (18%) as a group of similar applications to total nonroad power. Taking the sum of

power represented by all applications similar to the seven component equipment applications

found in the NRTC cycle, we have represented equipment operations and engine displacements

and, by analogy, in-use operations of 91% of nonroad equipment units.

4.2.10.4 Broad Application Control

Aggregating all those equipment classifications whose operating characteristics were similar

to the seven NRTC component cycles for their emission contributions, we found that the

composite nonroad cycle covered emissions from almost 96% of the documented applications in

the nonroad equipment population (see Table 4.2-17).
Technologies and Test Procedures for Low-Emission Engines

4-151

Table 4.2-17

Similarities Among Various Nonroad Equipment Applications

Application

Other Applications with 

Similar Operating Characteristics

Emission

Distribution

Cycle 

characterization

Ag tractor Combine

Off-Hwy Tractor

Off-Hwy Truck 38.4% Heavy-load operation along

governor/lug curve

Welder Air Compressors

Gas Compressors

Generators

Pumps

Bore/Drill Rigs

Cement Mixers

Chippers/Grinders

Concrete/Ind. Saw

Crush/Proc. Equip

Hydr. Power Unit

Irrigation Sets

Leaf Blow/Vacs

Lt Plants/Signal

Board

Oil Fld Equip.

Plate Compactors

Pressure Washers

Refrigeration/AC

Shredder

25.2% Transient loads at tightly

governed rated speeds

Backhoe/loader Aerial Lifts

Comm. Turf

Scrub/Sweeper 

Front Mowers

Lawn/Grdn. Tractor

Rear Eng. Rider

Specialty carts

Terminal Tractor

13.5% Widely varying loads and

speeds, weighted toward

lighter operation; most like

highway operation

Crawler Graders

R/T Dozer

Scrapers

Trenchers

5.7% Widely varying loads and

speeds, weighted toward

heavier operation

Excavator Cranes 2.4% Transient loads at loosely

governed rated speed

R/T Loader Aircraft Support

Forest Equip

Forklifts

Rough Trn Fork. 6.7% Stop and go driving with

widely varying loads.

Skid/steer — 3.6% Widely varying loads at

different nominally

constant-speed points

Total 95.5%

4.2.11 Final Certification Cycle Selection Process

Figure 4.2-18 outlines the process by which a manufacturer of a particular nonroad diesel

engine might approach certification using the nonroad transient and steady-state test

requirements (NTE certification requirements have been deliberately omitted from this

discussion to simplify the presentation). 
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4-152







 



 





 

















































 



Nonroad

Manf Seeks

Engine Duty

Cycle

Certification













TRU Duty Cycle

(option for

transportation

refrigeration units

only)













NRTC Cycle

(NR Transient

Composite) with

Cold Start porttion











Ramped Modal

Cycle option for

5-mode cycle,

“D-2"













Five (5)

Mode Cycle

"D-2"

Weighting













Six (6)

Mode Cycle

"G-2"

Weighting











Eight (8)

Mode

Cycle"C-1"

Weighting

Steady-State

Transient Compliance

Compliance

Option for 19 kW

or less

Constantspeed

operation











Ramped Modal

Cycle option

for 8-mode

cycle,”C-1"











Ramped Modal

Cycle option for

6-mode cycle,

“G-2"















CSVL Cycle

with Cold

Start portion

(ConstantSpeed

Variable-Load)

















CSVL Cycle

with Cold

Start and

set speed

option

Constant

Speed

operation

Dependent on outcome

of CSVL Test Duty

Cycle Program

Figure 4.2-18

NR Diesel Engine Transient and Steady-State Testing Requirements

Steady-state

operation

Option for 19 kW

or less

4.3 Steady-State Testing

Recognizing the variety of both power classes and work applications to be found within the

nonroad vehicle and engine population, EPA will retain current Federal steady-state test

procedures for nonroad engines. The steady-state duty cycle applicable in each of the following
Technologies and Test Procedures for Low-Emission Engines

KKThe three certification steady-state test cycles are similar to test cycles found in International Standard ISO

8178-4:1996 (E) and remain consistent with the existing 40 CFR Part 89 steady state duty cycles.

4-153

categories: 1) nonroad engines 25 hp and greater; 2) nonroad engines less than 25 hp; and 3)

nonroad engines having constant-speed, variable-load applications, (e.g., generator sets) will

remain, respectively, the 8-mode cycle, the 6-mode cycle, and the 5-mode cycle.KK 

Manufacturers are required to meet emission standards under steady-state conditions in addition

to meeting any emission standards under transient test cycle requirements. Steady-state test

cycles are needed so that testing for certification will reflect the broad range of operating

conditions experienced by these engines. A steady-state test cycle represents an important type

of modern engine operation, in power and speed ranges that are typical in-use. The mid-to-high

speeds and loads represented by present steady-state testing requirements are the speeds and

loads at which these engines are designed to operate for extended periods for maximum

efficiency and durability. Manufacturers would perform each steady-state test following all

applicable test procedures detailed in regulations at 40 CFR Part 1039, subpart F, e.g.,

procedures for engine warm-up and exhaust emissions measurement. The testing must be

conducted with all emission-related engine control variables in the maximum NOx-producing

condition which could be encountered for a 30 second or longer averaging period at a given test

point. Details concerning the three steady-state procedures for nonroad engines and equipment

can be found in regulations at 40 CFR 1039.505 and in Appendices I-III to Section 1039 which

follow that section, one for each cycle.

4.3.1 Ramped Modal Cycle

4.3.1.1 Introduction and Background

In response to manufacturers’ concerns for the potential of some PM trap-equipped diesel

engines to exhibit highly variable emissions under current emission test cycles, EPA has

developed ramped modal versions of its steady-state certification duty cycles. These ramped

modal cycle emission tests will reliably and consistently report steady-state emissions from PM

trap and other emission control hardware-equipped nonroad engines.

For all the laboratory- based steady-state testing currently specified in 40 CFR Part 89, EPA

has determined that any certification steady-state test cycle may be run as a ramped modal cycle

(RMC). A RMC consists of the same series of steady-state test modes, but they are connected to

one another by gradual ramps in engine speed and/or torque. However, the mode order is

rearranged so as to alternate between high- and low-torque modes. In a RMC, the steady-state

modes are connected with linear speed and torque transitions. The difference is that these

transitions are sampled as part of the test. In other words, emissions sampling would start at the

beginning of a RMC and would not stop until the last mode of the cycle is completed.

Instead of using weighting factors for each steady-state mode, a RMC specifies different time

durations for each mode. Time durations are proportioned to weight each mode and transition to

reflect the exact original ISO steady-state test weighting factors upon which the certification
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testing is based. The information and test cycle tables needed to run a certification steady-state

test cycle as a RMC are given in 40 CFR Section 1039.505(a)(2). Refer to 40 CFR Part 1039,

subpart F for the procedures required for transforming and running a particular test cycle on a

specific engine.

Because a RMC weights individual modes by the amount of time spent at each mode, we

considered the effect of a RMC's total test time on emissions. Based on the RMC data presented

in this section, we concluded that if insufficient time was spent in an individual mode, the mode

would not adequately represent the steady-state condition that was intended. This effect was

exaggerated when engines with aftertreatment systems were tested. By inspecting data from

individual modes, we determined that emissions differences between a RMC and its respective

certification steady-state test cycle occurred primarily when exhaust temperatures between the

two cycles differed greatly.

As mentioned earlier in this section, the modes in the RMC are intentionally arranged to

alternate between high- and low-torque modes. This results in more moderate and repeatable

aftertreatment temperatures overall. However, in some cases, more time in certain modes would

have helped to achieve exhaust temperatures over a RMC that were more representative of

exhaust temperatures for typical steady-state cycles.

The appropriate total time for the RMC was in part determined from testing of a diesel

engine equipped with both a NOx adsorption catalyst and PM trap exhaust emission controls,

which will be described in this section. Based on the number of modes in a given steady-state

cycle, we determined that twenty minutes is an appropriate total time for a RMC that has five or

fewer steady-state modes. Twenty minutes is also an appropriate minimum time for collecting

an adequate PM sample from an engine certified to a PM standard less than 0.05 g/kW-hr. For

which has six to ten modes, thirty minutes is an appropriate total time. Thirty minutes ensures

that the lightly weighted modes on the RMC have adequate time to approach the same exhaust

temperatures achieved when the test is run as a steady-state test. For a RMC with ten to fourteen

modes, forty minutes is an appropriate total test time. A forty-minute length ensures that a

sufficient amount of the total test time was spent at steady-state rather than in transition from one

mode to the next. For all of the RMCs, these times ensure that less than 10% of the total time is

spent in transition from one steady-state mode to the next.

There are a number of advantages to running a steady-state test as a RMC. The current

procedure for conducting a steady-state test allows emission sampling periods as short as the last

minute of each mode.165 Discrete aftertreatment regeneration events, NOx and SOx regeneration

for NOx adsorption catalysts, forced PM regeneration for PM traps, etc., typically cause

short-duration sharp increases in NOx, HC and PM emissions. Thus, it may be challenging to

gather good, repeatable emissions from the current steady-state procedures since a regeneration

event may or may not be sampled in a given mode. For sampling low concentrations of PM, this

inconsistency is exaggerated because the short sample time per mode may not provide enough

PM sample to weigh in a repeatable way. Furthermore, without specific start and stop times for

sampling each mode, an anticipated regeneration event may be intentionally or unintentionally
Technologies and Test Procedures for Low-Emission Engines

4-155

included or excluded. With a RMC, this variability is removed by requiring emissions sampling

over the entire cycle.

There are other advantages to running a steady-state test as a RMC. The RMC reduces the

number of sampling system starts and stops. This is significant at low emission standards when

considering that a previous mode's emissions may be incorrectly included in the next mode due

to an unavoidable dead volume in a sampling system. The longer sampling period of a RMC

also increases the mass of the PM sampled. This is extremely significant because the PM

standard already approaches the minimum detection limits for many current PM microbalances.

The RMC also enables the use of batch sampling systems, such as bag samplers. This is an

advantage because batch sampling systems are generally capable of quantifying lower levels of

pollutants with less uncertainty than continuous sampling systems at low emission

concentrations. This may be due to:

1. Gas analyzer zero-drift over time can be a much larger percentage of the measured value for

continuous measurements at continuous low average emission concentrations. This is much

less of an issue with batch measurements at low concentrations, since they can conduct a

zero and span operation immediately preceding the concentration measurement.

2. Zero-drift and transient response of the NOx analyzer from engines using high-capacity

NOx-adsorption catalysts can be a significant challenge for continuous measurement systems. 

For some modes of operation, NOx emissions are truly at, or very close to, zero during

adsorption with a rapid spike in NOx emissions during regeneration. Covering the full

dynamic range requires:

a. automatic range switching to allow measurement on a low-concentration analyzer range

when NOx is near zero during adsorption and switching to a higher range to catch the

NOx spike during regeneration, accepting the uncertainty introduced from loss of data

during the short duration needed to accomplish range switching; or

b. operating on a single higher concentration analyzer range and accepting the uncertainty

and increased zero-drift introduced at low concentrations during adsorption; or

c. operating on a single lower concentration analyzer range and accepting loss of data that is

"clipped" when the analyzer signal saturates during regeneration.

Batch-sampled NOx can be measured using a single analyzer range appropriate for the

measured concentration and the same sample can be measured repeatedly over more than one

range using the same analyzer. Thus, repeat measurements may be utilized to ensure an

accurate measurement at the lowest possible range.

3. During a continuous measurement, each instantaneous emission concentration measurement

has a level of uncertainty associated with it that propagates from each collected data point to

the final integrated concentration. By contrast, a batch-sampled emission measurement is
Regulatory Impact Analysis

4-156

typically a stabilized average of repeated measurements of a near-constant concentration

within the bag or other grab-sample container.

During EPA testing of the first pre-production prototype light-duty diesel vehicle (Toyota

Avensis D-Cat) with a NOx adsorption catalyst system, continuous and bag-sampled NOx agreed

to within 4% at very low integrated mass concentrations, but the coefficient of variance for the

continuous NOx measurement was approximately four times the coefficient of variance for the

bag-sampled NOx measurement, which was likely due to a combination of the above effects.

Use of a RMC can also significantly reduce the cost of steady-state testing. Not only is the

per-test cost anticipated to be lower with the RMC, but the lower thermal-load on CVS and

air-handling systems due to less sustained high-load operation during testing may reduce the cost

for construction of test facilities. The RMC can typically be accomplished in much less time,

further reducing total cost. 

4.3.1.2 Comparison of Steady-State vs. RMC Testing

4.3.1.2.1 Manufacturer's testing

An engine manufacturer provided paired and unpaired emissions data to EPA comparing the

13-mode highway SET (supplemental emissions test) to a RMC developed from the highway

SET. The paired data contain 34-39 test replicates representing 29 light-heavy, medium-heavy,

and heavy-heavy-duty highway engine families in the range of 250 - 500 hp certified to the 2004

model year heavy-duty on-highway emission standards. The engines were not equipped with

exhaust aftertreatment, but were equipped with high-pressure, electronically controlled fuel

injection systems and cooled EGR systems. The unpaired data are for 10 engine families built

from one basic engine platform for a heavy-heavy-duty engine of approximately 15 liters

displacement. The paired data are summarized in Figures 4.3-1 and 4.3-2. The results of a F-test

comparison of the unpaired SET data to the RMC data are presented in table 4.3-1. Emissions

results did not differ significantly between the SET and the RMC. Further, when comparing the

uncertainty of the RMC to the SET, it met the F-test criteria at a 90% confidence level using the

test equivalency criteria as per an EPA letter to the Engine Manufacturers Association, dated

December 12, 2002 regarding guidance on test procedures for heavy-duty on-highway and nonroad engines (page 3, item 1).166
Technologies and Test Procedures for Low-Emission Engines

4-157

Figure 4.3-1: A comparison of SET and RMC NOx emissions

based on paired data from 29 engine families certified to a 2.5

g/bhp-hr NOx and 0.1 g/bhp-hr PM standard.

Figure 4.3-2: A comparison of SET and RMC PM and total HC

emissions based on paired data from 29 engine families certified to a

2.5 g/bhp-hr NOx and 0.1 g/bhp-hr PM standard.
Regulatory Impact Analysis

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Table 4.3-1: F-test comparison of the RMC to the SET steady-state

test. NOx and HC emissions were measured using continuous

analyzers. Note that the ability to use batch-sampling for NOx and

HC would further reduce the standard-deviation for the RMC. The

PM measurement for the SET also used a single, flow-weighted PM

filter sample. Using one filter-sample per mode would likely have

further increased the variability in the SET steady-state tests.

NOx PM HC CO CO2

Mean Emissions

(SET)

2.029 0.0754 0.072 0.329 507

FSET 0.056 0.0080 0.014 0.062 13

Mean Emissions

(RMC)

1.931 0.078 0.072 0.372 510

FRMC 0.070 0.0057 0.013 0.091 17

F-test

F90%: 2.44 2.44 2.44 2.44 2.44

FRMC: 1.56 0.516 0.776 2.18 1.69

Pass at 90%

Confidence

Interval?

Pass Pass Pass Pass Pass

4.3.1.2.2 EPA testing over the 8-mode C-1 cycle and its RMC derivative (with and without

exhaust aftertreatment)

EPA has determined that its 8-mode C-1 test cycle (40 CFR Part 89) may be run as a RMC. 

The RMC version of this cycle consists of the same series of eight steady-state test modes but

the modes are connected to one another by linear speed and torque transitions. That is,

emissions sampling would start at the beginning of this RMC and would not stop until its last

“mode” was completed. As well, the mode order from the 8-mode C-1 cycle is rearranged in this

RMC to alternate between high-load and low-load modes. Instead of using weighting factors for

each steady-state mode, the RMC specifies different time durations for each mode. Time

durations are proportioned to weight each mode exactly as the original C-1 weighting factors. 

The information needed to run an 8-mode C-1 test cycle as a RMC is given in 40 CFR,

§1039.505. The procedures required for transforming and running this test cycle with a specific

engine are found on 40 CFR Part 1039 subpart F.

To compare the emission levels between a steady-state 8-mode C-1 test and the

corresponding RMC test, four engines ranging from 42 to 400 brake-horsepower (bhp) were

tested at Southwest Research Institute (SwRI) and at EPA's National Vehicle and Fuel Emissions

Laboratory (NVFEL). Table 4.3-2 below contains a summary of the specifications of these
Technologies and Test Procedures for Low-Emission Engines

4-159

engines. The testing was performed with engines having various exhaust configurations. The

Yanmar engine had no exhaust aftertreatment while the Kubota engine was tested both with and

without a DOC. The DDC engine was tested with a continuously-regenerating trap (CRT)

system that used a platinum-catalyzed DOC located upstream of a non-catalyzed PM trap.

Table 4.3-2: Engine properties

Engine Model

Year

Power 

(bhp)

Fuel

Inj.

Displ.

(L)

Air Induction Configurations

tested

Yanmar 4TNE84 2002 48 DI 1.99 Naturally

Aspirated

No exhaust

aftertreatment

Kubota V1903E 2001 42 IDI 1.9 Naturally

Aspirated

With and without

DOC

DDC Series 60 1998 400 DI 12.7 Turbocharged

With CRT

(passive

regeneration)

Cummins ISB 2000 180 DI 5.9 Turbocharged

With CDPF + NOx

adsorption catalyst

system

The Cummins ISB engine was tested with a system which combined a catalyzed diesel

particulate filter (CDPF) with a NOx adsorption catalyst.167 The engine was also equipped with a

high-pressure common-rail fuel injection system and cooled low-pressure-loop EGR.. The test

configuration of the ISB engine was that of a 180 b-hp rated nonroad engine and EPA developed

the engine’s test calibration values.

Table 4.3-3, below, summarizes the engine operating conditions for the 8-mode C-1 cycle

and for the RMC derived from that cycle. The RMC contains a "split idle mode" (the idle

condition occurs twice versus once in the 8-mode C-1). Note also that it is possible to run the 8-

mode C-1 cycle with different lengths of time-in-mode. A period of five-minutes duration per

steady-state mode is allowable under current regulations in 40 CFR Part 89 and there is no limit

on maximum time-in-mode. Different exhaust sampling periods are also allowed, having a

minimum length of 60 seconds and no maximum length. Thus, for the 8-mode C-1 steady-state

cycle, the minimum time-in-mode under current regulations would be a period of four minutes of

stabilization with one minute of sampling per mode. The maximum time for stabilization and

sampling are left undefined.

All of the engines were tested using a twenty minutes long RMC derived from the 8-mode

C-1 cycle. The EPA-modified Cummins ISB was also tested using a thirty minutes long RMC

cycle. The length of time spent in each mode for the 8-mode C-1 test cycles varied by engine. 

The Yanmar and Kubota engines were tested over the 8-mode C-1 test cycle at mode lengths of
Regulatory Impact Analysis

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ten minutes each. Gaseous emissions and PM emissions were sampled for the last five minutes

of each ten-minute mode. The DDC and the modified Cummins ISB engines were tested over

the 8-mode C-1 cycle at mode lengths totaling ten minutes each. Their gaseous and PM

emissions were sampled for the last three minutes of each ten-minute mode. The modified

Cummins ISB engine was also tested using a five minutes long mode length over the 8-mode C-1

cycle. For those tests having a five minutes long mode length, the first four minutes were used

for stabilization and the last minute was used for emissions sampling to model the minimum time

specifications found in 40 CFR Part 89.

Table 4.3-3:

Engine operating conditions for the steady-state 8-Mode C-1 and RMC tests

8-Mode

C-1

1 2345678

Speed Rated Intermediate Idle

Torque 100 75 50 10 100 75 50 No

load

RMC 1 2 3 4 5 6 7 8 9

Speed Idle Intermediate Rated Idle

Torque No

load

100 50 75 100 10 75 50 No

load

Figures 4.3-3 and 4.3-4 below summarize the emissions results obtained from emission

testing on the DDC Series-60 engine. However, due to the use of a non-standard PM sampling

medium and measurement inconsistencies associated with filter handling during emission

testing, PM data are not available for these tests (PM mass loss was attributed to physical

damage to the sample filters after installation into the sampling cassettes). As shown in these

figures, NOx emissions for both engine-out and CRT-out configurations of this engine over the

RMC and 8-mode C-1 test cycles do not differ at the 95% confidence interval. Differences

between HC and CO emission levels over the two cycles were either negligible or extremely low

during all testing and well under the Tier 4 emission standards. 
Technologies and Test Procedures for Low-Emission Engines

4-161

Figure 4.3-3: Emissions from the DDC Series-60 engine over the steady-state 8-

mode C-1 test and the 20-minute RMC test with no exhaust aftertreatment.

Figure 4.3-4: Emissions from the DDC Series-60 engine over the steady-state 8-

mode C-1 test and the 20-minute RMC test with a CRT.
Regulatory Impact Analysis

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Figures 4.3-5 and 4.3-6 compare exhaust emissions from the Kubota V1903E engine over

both the 8-mode C-1 and RMC cycles without and fitted with a DOC, respectively. PM

emissions over both test cycles from both of the tested engine configurations did not differ at

either the 95% or 90% confidence interval. There was however a general trend toward a reduced

coefficient of variance for RMC versus 8-mode C-1 PM emissions and the number of replicates

was insufficient for a rigorous F-test comparison of variance. Differences in mean NOx

emissions in the no exhaust aftertreatment configuration were small, and did not differ at a 95%

confidence interval, but did differ at a 90% confidence interval. CO emissions were somewhat

lower over the RMC, possibly due to increased CO oxidation caused by the somewhat higher

exhaust temperatures of that cycle compared to the 8-mode C-1 cycle. In both cases, though, CO

emissions were less than 50% of the Tier 4 standard.

Figure 4.3-5: Emissions for the Kubota V1903E engine with no exhaust

aftertreatment over the steady-state 8-mode C-1 test and the 20-minute RMC test.
Technologies and Test Procedures for Low-Emission Engines

4-163

Figure 4.3-6: DOC-out emission levels obtained from the Kubota V1903E engine

over the steady-state 8-mode C-1 test and the 20-minute RMC test.

Figure 4.3-7: Engine-out emission levels obtained from the Yanmar 4TNE84

engine over the steady-state 8-mode C-1 test and the 20-minute RMC test.
Regulatory Impact Analysis

4-164

Emissions from the Yanmar 4TNE84 engine operating without exhaust aftertreatment over

both the 8-mode C-1 and 20 minutes long RMC test cycles are summarized above in Figure

4.3-7. As can be seen in this figure, the average engine-out NOx emission over the RMC is

within the 95% confidence interval of the NOx data gathered over the steady-state 8-mode C-1

test, although the number of test replicates were insufficient to determine a confidence interval

for the RMC for this particular data comparison. With regards to the HC and CO emissions, the

data showed a slight, statistically significant difference for these emissions of 5% or less

between the two cycles. CO emissions exceeded the Tier 1 standards over the 8-mode C-1 cycle

and were unusually high for a diesel engine over both of these cycles. This may indicate that a

mechanical problem exists with this particular test engine.

Figure 4.3-8: Emissions from the EPA-modified Cummins ISB engine over the

steady-state 8-mode C-1 test cycle and the RMC test cycle. Note that the data

represent the 2 different mode lengths specified for the 8-mode C-1 and two

different total test times for the RMC. PM emissions were only available for the

10 minutes per mode 8-mode C-1 and the 20 minutes long RMC results. Results

are shown for mean-emissions calculated for 7 test replicates. Confidence

intervals were calculated using a 2-sided Student t-test.

Figure 4.3-8 above compares the emission levels obtained from testing the Cummins ISB

engine on the 8-mode C-1 cycle at both five minutes per mode and ten minutes per mode, as

described in 40 CFR Part 89, with the RMC version of that cycle at both twenty minutes and

thirty minutes of total cycle time. The five minutes and ten minutes per mode represent mode

lengths that are currently used in the 8-mode C-1 test cycle for emissions testing of nonroad
Technologies and Test Procedures for Low-Emission Engines

4-165

diesel engines. PM emissions were measured only for the ten minutes per mode 8-mode C-1 and

the twenty minutes total time RMC cycles, which among the cycles investigated represented the

largest differences in exhaust temperature and gaseous emissions. PM emissions were extremely

low due to the use of the CDPF and were approximately 50% of the Tier 4 standards. Mean PM

emissions for these two cycles did not differ at either a 95% or a 90% confidence level. Some

statistically significant differences in mean NOx emissions were found between the various

cycles used, including the two different mode length 8-mode C-1 cycles, due to differences in

exhaust temperatures achieved over individual cycles. There were statistically significant

differences in mean NOx emissions between the ten minutes per mode and the five minutes per

mode 8-mode C-1 cycles. Likewise, there were statistically significant differences in mean NOx

emissions between the ten minutes per mode 8-mode C-1 and both the twenty and thirty minutes

total time RMCs. Differences in mean NOx emissions between the thirty minutes total time

RMC and the five minutes per mode 8-mode C-1 were not statistically significant at either a 95%

or a 90% confidence level. All other emission levels were extremely low over both the RMC

and the 8-mode C-1 tests. Mean HC, CO and PM emissions did not differ significantly at either

a 95% or a 90% confidence level for either of these cycles.

4.3.1.2.3 Summary of engine test results

These data confirm that emissions from engines which do not use NOx adsorption catalysts

are relatively insensitive to the choice of the 8-mode C-1 test cycle or its RMC counterpart. 

Neither are these engine emissions sensitive to the impact of time spent at any steady-state

speed-load set-point. However, the effect of test cycle length and time-in-mode on exhaust

temperatures did have an impact on NOx emissions when an engine was equipped with a NOx

adsorption catalyst system, due to the:

1. effect of catalyst temperature on the ability to oxidize NO-to-NO2 for NOx storage

(kinetically-limited at low temperatures and equilibrium-limited at high temperatures);

2. effect of thermal-desorption of NOx at high temperatures; and

3. difficulty in effectively vaporizing fuel reductant at very low exhaust temperatures.

Based on NOx emissions and engine exhaust temperature data from EPA tests of the

modified Cummins ISB engine, a thirty minutes total time 8-mode C-1-based RMC was selected

as comparable to the five minutes per mode 8-mode C-1 test cycle for NOx emission and engine

exhaust temperature results. Furthermore, based on the results of both EPA and engine

manufacturer testing, the Agency has determined that steady-state test procedures should be

modified to include changes necessary to allow repeatable NOx emission results for all steadystate testing conducted on engines having catalytic exhaust emission controls for NOx emissions. 

Steady-state testing for certification will be conducted in the following manner:

1. The manufacturer may choose either the appropriate laboratory-based certification

steady-state test cycle or its RMC derivative as found in regulations at 40 CFR, Section

1039.505. For RMC tests with five or fewer modes, the length of the RMC test cycle will be
Regulatory Impact Analysis

LL Information on the proposed TRU cycle may be found on and downloaded from the CARB website at

http://www.arb.ca.gov/diesel/dieselrrp.htm. In particular, see the Technical Bulletin to the Proposed TRU cycle

determination.

4-166

twenty-minutes long. For RMC tests with six to nine modes, the length of that test cycle will

be thirty-minutes long. For RMC tests with ten or more modes, the length of that test cycle

will be forty-minutes long.

2. When testing an engine having an exhaust aftertreatment system which reduces NOx

emissions, a manufacturer will operate that engine for four to six minutes, then sample

emissions for one to three minutes in each mode. The sampling time for PM emissions may

be extended to improve measurement accuracy, using good engineering judgment. If a

longer sampling time is chosen for PM emissions, the manufacturer must calculate and

validate cycle performance statistics for the gaseous and PM sampling periods separately.

3. When testing other engines, a manufacturer will operate those engines for at least five

minutes, then sample emissions for at least one minute in each mode.

These changes in measurement procedures for nonroad engines have been incorporated into

regulations at 40 CFR Section 1039.505.

4.3.2 Transportation Refrigeration Unit Test Cycle

Transportation refrigeration units (TRU), a specific application of steady-state engine

operation, are refrigeration systems powered by diesel engines designed to refrigerate perishable

products that are transported in various containers, including semi-trailers, truck vans, shipping

containers, and rail cars. TRU engines are relatively small with most units ranging from 7 to 38

kW (10 to 50 horsepower)LL.

Engines that are designated as TRU engines at the time of certification are expected to

operate in the field primarily under steady-state conditions. These engines may from time to

time be subject to minor setpoint performance perturbations; however those changes are not

expected to last for a total duration at any one point of greater than 30 seconds and are not

multiple, highly transient, repetitive changes in speed or load such as seen in the nonroad

transient duty cycle. These parameters appropriately characterize TRU equipment operation

independent of unit application, whether used for fresh product (chilled to 3°C) or for frozen

goods at the standard maximum rating (-20°C). So, to that end, EPA has adopted a four-mode

steady-state test cycle designed specifically for engines used in TRU applications.

The TRU certification test cycle consists of four steady-state modes of operation. Two

modes are to be run at 50% of the manufacturer’s declared peak torque value for that engine. 

The remaining two modes are to be run at 75% of that same declared peak torque value for that

same engine. One of the modes at 50% load is to be run at the engine manufacturer’s speed at

peak, or rated, power, while the other mode at 50% load is to be run at the engine manufacturer’s
Technologies and Test Procedures for Low-Emission Engines

MMDrift is restricted to load deterioration not to exceed 15% over a sixty minute duration.

4-167

“intermediate” test speed. Likewise, one of the modes at 75% load is to be run at the engine

manufacturer’s speed at rated horsepower and the remaining mode at 75% load is to be run at the

manufacturer’s “intermediate” test speed. All four modes would be weighted equally in

determining a particular mode's contribution to the engine's total test cycle emissions. Early data

submissions in response to California-ARB’s call for TRU engine operating data showed that the

majority of TRU engines operated in-use in at least three, if not all four of the test cycle’s

modes168. It was equally clear from comments to the rule that a TRU test cycle was more

representative of refrigeration unit operation than the nonroad cycles currently available to

manufacturers since TRUs generally did not operate at low idle, high idle, peak torque or rated

power conditions. 

EPA will allow manufacturers to test their engines under a broad definition of intermediate

test speed, similar to recommendations found in ISO-8178-4 steady-state test guidelines. The

intermediate speed shall be the declared maximum torque speed if it occurs between 60% and

75% of rated speed / maximum test speed. If the declared maximum torque speed is less than

60% of rated speed, then the intermediate speed shall be 60% of the rated speed. If the declared

maximum torque speed is greater than 75% of the rated speed then the intermediate speed shall

be 75% of rated speed. This will enable an engine manufacturer to more closely match the TRU

cycle at engine certification to the operation of their engines in-use.

The set point value for speed in a TRU engine is expected to remain consistent without

repetitive transient changes on a 1 hertz basis. The magnitude of any changes in actual speed

from the engine are expected to be under 2% which is consistent with the Agency's treatment of

operation as steady state in the creation of the transient duty cycle. Additionally, the set point

value demanded by the application remains within this 2% steady state definition. Should

application demands differ from the steady state condition for speed, the engine shall not be

considered an actual steady state TRU engine. The TRU engine is likewise not allowed to drop,

or driftMM, from a load set point by more than 15% of torque at the speed for a particular

operating mode before changing its load setpoint.

As seen below in Figure 4.3-9169, the operation of the typical piece of TRU equipment tested

is relatively consistent, as evidenced by the power factor curve, a surrogate for engine response

to load demand on the unit. Many factors may affect unit “drift” from a set point, but that set

point of operation does not deteriorate significantly over longer periods of time, in minutes. 

TRU equipment is responsive to feedback from a broad number of engine operating parameters

and user input options. Operating temperature, intake air temperature, i.e., ambient, and exhaust

air temperature are some engine operating parameters to which the engine must be responsive. 

User or owner inputs include tolerances around set point temperatures, minimum time-on, and

minimum time-off for the unit. Likewise the condition and age of the engine and container,

especially the insulation, may influence ability to hold a desired temperature, or load170,

171.
Regulatory Impact Analysis

4-168

Figure 4.3-9

TRU Equipment Operation at Pull-Down

The expectation is that the engine is governed in such a way that this demand is not possible. 

If that engine is deemed a steady-state TRU engine at the time of certification, the application

within which the engine is sold, must meet these standards of operation.

As an additional way of ensuring that TRU certification is limited to those engines for which

it is warranted, we are adding a requirement that any TRU-certified engine must meet

appropriate NTE standards for any in-use operation. Practically, this means that TRU engines

are subject to NTE standards based on the normal operation that these engines would experience

in the field. This is limited neither to later model years nor to any particular range of engine

speeds and loads. If TRU engine operation is limited as much as manufacturers have described,

the resulting “NTE zone” should be practically limited to a narrow range of speeds and loads

very close to those points represented by the specified duty cycle.
Technologies and Test Procedures for Low-Emission Engines

NN Torque is a measure of rotational force. The torque curve for an engine is determined by an engine

“mapping” procedure specified in the Code of Federal Regulations. The intent of the mapping procedure is to

determine the maximum available torque at all engine speeds. The torque curve is merely a graphical representation

of the maximum torque across all engine speeds. 

4-169

4.4 Not-to-Exceed Testing

The Agency’s examination of emissions data from heavy duty highway diesel engines , and the

confidential discussions with several heavy duty diesel engine manufacturers, led EPA to the

conclusion that the 1.25 emission cap associated with the not-to-exceed zone requirement is

technologically feasible. This conclusion has not changed since the initiation of the not-to-exceed

concept. The Agency believes the 1.25 factor proposed for the not-to-exceed standard provides

sufficient room to allow for the uneven nature of the emission maps. For these reasons, EPA

believes the primary technologies discussed earlier in this chapter will provide the necessary

NMHC+NOx and PM control on the existing steady state, as well as on the transient cycle testing

and not-to-exceed zone testing.

 The goal of the Not-To-Exceed (NTE) limits on nonroad diesel engines remains consistent with

the reasoning for highway heavy duty diesel engines . The NTE helps ensure that emission benefits

are achieved in-use and provides a practical approach for a post-promulgation in-use testing

program. The NTE established for the highway heavy duty diesel engines has been demonstrated

to be not only feasible, but practical. The NTE approach provides an area under the maximum

allowable torque curve of an engine for which an engine may not exceed a specified value for the

regulated pollutants. The NTE zones, limits, and ambient conditions are described in detail below.

 The advantages to adopting an NTE strategy originally adopted for highway diesel engines are

numerous. These include:

C Proven design strategy can be utilized by manufacturers

C Development costs can be minimized as new test protocols will not need to be refined

C Assurance of comparable control effectiveness analogous to existing programs

C Demonstrated effectiveness in the heavy duty highway diesel market can be carried forward

to the nonroad diesel market

C Allows for direct comparison of control effectiveness in-use

The Not-To-Exceed (NTE) provision was initially finalized for HDDEs certified to the 2004 FTP

emission standards with implementation beginning in model year 2007. (See 65 FR 59896, October

6, 2000.) The NTE approach establishes an area (the “NTE control area”) under the torque curve

of an engine where emissions must not exceed a specified value for any of the regulated

pollutants.NN The NTE requirements apply under engine operating conditions that could reasonably

be expected to be seen in normal vehicle operation and use which occur during the conditions

specified in the NTE test procedure. (See 40 CFR 86.1370.) This test procedure covers a specific

range of engine operation and ambient operating conditions (i.e., temperature, altitude, and
Regulatory Impact Analysis

4-170

humidity). The NTE control area, emissions standards, ambient conditions and test procedures for

nonroad diesel engines are described in the 40 CFR 1039.515.

The NTE provisions for nonroad diesel engines mirror the highway diesel program and so a

manufacturer will need to undertake the engine mapping procedure as defined in 40 CFR 1065;

however, speed definitions will need to be determined based on 40 CFR 86.1360(c). Valid NTE

compliance evaluation will be based on the following factors:

C Operating speeds greater than the speed determined by: nlo + 0.15 x (nhi-nlo) 

C Engine load points greater than or equal to 30% of the maximum torque value produced by

the engine

C Brake Specific Fuel Consumption (BSFC) requirements as specified in 40 CFR 86.1370-

2007 (b)(3)

C Exclusion areas for which the NTE requirement does not apply may be found in 40 CFR

86.1370-2007 (e.g. PM carve-out zones for engines certifying to a PM standard above 0.07

g / kW-hr) 

C Control area limits as defined in 40 CFR86.1370-2007 (d) for averaging times that may or

may not include discrete regeneration events

C Corrections for ambient conditions as defined in 40 CFR 86.1370-2007 (e) 

C Cold temperature exclusions as adopted in 40 CFR 86.1370-2007 (f)

C Engines equipped with NOx and NMHC aftertreatment systems (both single and multi-bed

systems) with warm-up provisions as defined in 40 CFR 86.1370-2007 (g)

The NTE requirements will not apply during engine start-up conditions 40 CFR 86.1370-2007

(g). In addition, with the application of advanced exhaust emission control devices, an exhaust

emission control device warm-up provision is a necessary criterion for the NTE to address the

impact of thermal inertia on aftertreatment efficiency for the catalytic reduction strategies. Until the

exhaust gas temperature on the outlet side of the exhaust emission control device(s) achieves 250

degrees Celsius, the engine is not subject to the NTE as discussed in 40 CFR 86.1370-2007 (g).

Control of cold-start emissions is expected to happen through the nonroad transient cycle cold-start

provisions. 

For a more detailed technical description of the application of the NTE Zone to diesel engines,

please see the Regulatory Impact Analysis: Heavy -Duty Engine and Vehicle Standards and

Highway Diesel Fuel Sulfur Control Requirements EPA420-R-00-026.
Technologies and Test Procedures for Low-Emission Engines

4-171

1. Control of Air Pollution from New Motor Vehicles: Heavy-duty Engine and Vehicle

Standards and Highway Diesel Sulfur Control Requirements; Final Rule, 66 FR 5002, January

18, 2001.

2. Highway Diesel Progress Review, United States Environmental Protection Agency, June

2002, EPA 420-R-02-016. Copy available in Docket OAR-2003-0012-0919.

3. Highway Diesel Progress Review Report 2, United States Environmental Protection Agency,

March 2004, EPA 420-R-04-004. Copy available in Docket OAR-2003-0012-0918.

4. Final Regulatory Impact Analysis: Control of Emissions of Air Pollution from Highway

Heavy-Duty Engines, Air Docket OAR-2003-0012-0949.

5. Regulatory Impact Analysis: Control of Emissions of Air Pollution from Highway HeavyDuty Engines, Air Docket OAR-2003-0012-950.

6. Final Regulatory Impact Analysis: Control of Emissions from NR Diesel Engines, Air

Docket, OAR-2003-0012-0952.

7. Nonroad Diesel Emissions Standards Staff Technical Paper, Air Docket OAR-2003-0012-

0951.

8. Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling - CompressionIgnition, EPA420-P-02-016, NR-009B, Air Docket A-2001-28. 

9. Onishi, S. et al, “Active Thermo-Atmosphere Combustion (ATAC) - A New Combustion

Process for Internal Combustion Engines,” SAE 790840.

10. Najt, P. and Foster, D. “Compression-Ignited Homogeneous Charge Combustion,” March

1983, SAE 830264.

11. Dickey, D. et al, “NOx Control in Heavy-Duty Diesel Engines - What is the Limit,”

February, 1998, SAE 980174.

12. Kimura, S. et al, “Ultra-Clean Combustion Technology Combining a Low-Temperature and

Premixed Combustion Concept for Meeting Future Emission Standards,” SAE 2001-01-0200.

13. Kimura, S. et al, “An Experimental Analysis of Low-Temperature and Premixed

Combustion for Simultaneous Reduction of NOx and Particulate Emissions in Direct Injection

Diesel Engines,” International Journal of Engine Research, Vol 3 No.4, pages 249-259, June

2002.

14. Gray, A. and Ryan, T., “Homogenous Charge Compression Ignition (HCCI) of Diesel Fuel,”

May, 1997 SAE 971676.

Chapter 4 References
Regulatory Impact Analysis

4-172

15. Stanglmaier, R. et al, “HCCI Operation of a Dual-Fuel Natural Gas Engine for Improved

Fuel Efficiency and Ultra-Low NOx Emissions at Low to Moderate Engine Loads,” May, 2002

SAE 2001-01-1897.

16. Stanglmaier, R. and Roberts, C. “Homogenous Charge Compression Ignition (HCCI):

Benefits, Compromises, and Future Engine Applications,” SAE 1999-01-3682.

17. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-Duty Engines to Achieve Low Emission Levels”, Manufacturers of Emission Controls

Association, June 1999 Air Docket A-2001-28.

18. See Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

19. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-duty Engines to Achieve Low Emission Levels: Interim Report Number 1 - Oxidation

Catalyst Technology, copy available in EPA Air Docket A-2001-28. “Reduction of Diesel

Exhaust Emissions by Using Oxidation Catalysts,” Zelenka et al, SAE Paper 90211, 1990. See

Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA Publication

EPA420-R-01-052, October 2001, copy available in EPA Air Docket A-2001-28.

20. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-Duty Engines to Achieve Low Emission Levels”, Manufacturers of Emission Controls

Association, June 1999 Air Docket A-2001-28.

21. Miller, R. et al, “Design, Development and Performance of a Composite Diesel Particulate

Filter,” March 2002, SAE 2002-01-0323.

22. “Wall Flow Monoliths,” DieselNet Technology Guide, http://www.dieselnet.com/

tech/dpf_wallflow.html

23. “Ceramic Fibers and Cartridges,” DieselNet Technology Guide, http://www.dieselnet.com/

tech/dpf_fiber.html

24. Hori, S. and Narusawa, K. “Fuel Composition Effects on SOF and PAH Exhaust Emissions

from DI Diesel Engines,” SAE 980507.

25. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-Duty Engines to Achieve Low Emission Levels”, Manufacturers of Emission Controls

Association, June 1999 Air Docket A-2001-28.

26. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-Duty Engines to Achieve Low Emission Levels”, Manufacturers of Emission Controls

Association, June 1999 Air Docket A-2001-28.
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27. Hawker, P., et al, Effect of a Continuously Regenerating Diesel Particulate Filter on NonRegulated Emissions and Particle Size Distribution, SAE 980189.

28. Application of Diesel Particulate Filters to Three Nonroad Engines - Interim Report, January

2003. Copy available in EPA Air Docket A-2001-28.

29. “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA Publication EPA420-R01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

30. Engelhard DPX catalyzed diesel particulate filter retrofit verification,

www.epa.gov/otaq/retrofit/techlist-engelhard.htm, a copy of this information is available in Air

Docket A-2001-28.

31. “Particulate Traps for Construction Machines, Properties and Field Experience,” 2000, SAE

2000-01-1923.

32. Letter from Dr. Barry Cooper, Johnson Matthey, to Don Kopinski, U.S. EPA, Air Docket A2001-28.

33. EPA Recognizes Green Diesel Technology Vehicles at Washington Ceremony, Press

Release from International Truck and Engine Company, July 27, 2001, Air Docket A-2001-28.

34. Nino, S. and Lagarrigue, M. “French Perspective on Diesel Engines and Emissions,”

presentation at the 2002 Diesel Engine Emission Reduction workshop in San Diego, California,

Air Docket A-2001-28.

35. Highway Diesel Progress Review, United States Environmental Protection Agency, June

2002, EPA 420-R-02-016, Air Docket A-2001-28.

36. “Nonroad Diesel Emissions Standards Staff Technical Paper”, EPA420-R-01-052, October

2001, Air Docket A-2001-28.

37. Allansson, et al, European Experience of High Mileage Durability of Continuously

Regenerating Diesel Particulate Filter Technology. SAE 2000-01-0480.

38. LeTavec, Chuck, et al, “EC-Diesel Technology Validation Program Interim Report,” SAE

2000-01-1854; Clark, Nigel N., et al, “Class 8 Trucks Operating On Ultra-Low Sulfur Diesel

With Particulate Filter Systems: Regulated Emissions,” SAE 2000-01-2815; Vertin, Keith, et al,

“Class 8 Trucks Operating On Ultra-Low Sulfur Diesel With Particulate Filter Systems: A Fleet

Start-Up Experience,” SAE 2000-01-2821.

39. Vertin, Keith, et al, “Class 8 Trucks Operating On Ultra-Low Sulfur Diesel With Particulate

Filter Systems: A Fleet Start-Up Experience,” SAE 2000-01-2821.

40. Allanson, R. et al, “Optimising the Low Temperature Performance and Regeneration

Efficiency of the Continuously Regenerating Diesel Particulate Filer (CR-DPF) System,” March

2002, SAE 2002-01-0428.
Regulatory Impact Analysis

4-174

41. Jeuland, N., et al, “Performances and Durability of DPF (Diesel Particulate Filter) Tested on

a Fleet of Peugeot 607 Taxis First and Second Test Phases Results,” October 2002, SAE 2002-

01-2790.

42. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” EPA420-R-00-026, December 2000, Docket A-2001-

28, Document No. II-A-01.

43. Koichiro Nakatani, Shinya Hirota, Shinichi Takeshima, Kazuhiro Itoh, Toshiaki Tanaka, and

Kazuhiko Dohmae, “Simultaneous PM and NOx Reduction System for Diesel Engines.”, SAE

2002-01-0957, SAE Congress March 2002.

44. Allanson, R. et al, “Optimising the Low Temperature Performance and Regeneration

Efficiency of the Continuously Regenerating Diesel Particulate Filer (CR-DPF) System,” March

2002, SAE 2002-01-0428.

45. Flynn, P. et al, “Minimum Engine Flame Temperature Impacts on Diesel and Spark-Ignition

Engine NOx Production,” SAE 2000-01-1177, March 2000.

46. Regulatory Impact Analysis: Control of Emissions of Air Pollution from Highway HeavyDuty Engines, Air Docket OAR-2003-0012-950.

47. Final Regulatory Impact Analysis: Control of Emissions from NR Diesel Engines, Air

Docket, OAR-2003-0012-0952.

48. Stanglmaier, Rudolf and Roberts, Charles “Homogenous Charge Compression Ignition

(HCCI): Benefits, Compromises, and Future Engine Applications”. SAE 1999-01-3682.

49. Kimura, Shuji, et al, “Ultra-Clean Combustion Technology Combining a Low-Temperature

and Premixed Combustion Concept for Meeting Future Emission Standards”, SAE 2001-01-

0200.

50. Diesel Emission Control-Sulfur Effects Program, Phase I Interim Data Report No. 1,

August, 1999, www.ott.doe.gov/decse Copy available in Air Docket A-2001-28.

51. Kawanami, M., et al, Advanced Catalyst Studies of Diesel NOx Reduction for Highway

Trucks, SAE 950154.

52. Hakim, N. “NOx Adsorbers for Heavy Duty Truck Engines - Testing and Simulation,”

presentation at Motor Fuels: Effects on Energy Efficiency and Emissions in the Transportation

Sector Joint Meeting of Research Program Sponsored by the U.S. Department of Energy, Clean

Air for Europe and Japan Clean Air, October 9-10, 2002. Copy available in EPA Air Docket A2001-28.

53. Koichiro Nakatani, Shinya Hirota, Shinichi Takeshima, Kazuhiro Itoh, Toshiaki Tanaka, and

Kazuhiko Dohmae, “Simultaneous PM and NOx Reduction System for Diesel Engines.”, SAE
Technologies and Test Procedures for Low-Emission Engines

4-175

2002-01-0957, SAE Congress March 2002.

54. Schenk, C., McDonald, J. and Olson, B. “High Efficiency NOx and PM Exhaust Emission

Control for Heavy-Duty On-Highway Diesel Engines,” SAE 2001-01-1351.

55. Gregory, D. et al, “Evolution of Lean-NOx Traps on PFI and DISI Lean Burn Vehicles”,

SAE 1999-01-3498.

56. McDonald, J., et al, “Demonstration of Tier 2 Emission Levels for Heavy Light-Duty

Trucks,” SAE 2000-01-1957. 

57. Brogan, M, et al, Evaluation of NOx Adsorber Catalysts Systems to Reduce Emissions of

Lean Running Gasoline Engines, SAE 962045.

58. Gregory, D. et al, “Evolution of Lean-NOx Traps on PFI and DISI Lean Burn Vehicles”,

SAE 1999-01-3498.

59. Sasaki, S., Ito, T., and Iguchi, S., “Smoke-less Rich Combustion by Low Temperature

Oxidation in Diesel Engines,” 9th Aachener Kolloquim Fahrzeug - und Motorentechnik 2000.

Copy available in Air Docket A-2001-28.

60. Whiteacre, S. et al., “Systems Approach to Meeting EPA 2010 Heavy-Duty Emission

Standards Using a NOx Adsorber Catalyst and Diesel Particle Filter on a 15l Engine,” SAE

2004-01-0587, March 2004.

61. Highway Diesel Progress Review Report 2, United States Environmental Protection Agency,

March 2004, EPA 420-R-04-004, Air Docket OAR-2003-0012-0918.

62. Brogan, M, et al, Evaluation of NOx Adsorber Catalysts Systems to Reduce Emissions of

Lean Running Gasoline Engines, SAE 962045.

63. Gregory, D. et al, “Evolution of Lean-NOx Traps on PFI and DISI Lean Burn Vehicles”,

SAE 1999-01-3498.

64. Highway Diesel Progress Review, United States Environmental Protection Agency, June

2002, EPA 420-R-02-016, Air Docket A-2001-28.

65. Kato, N. et al, “Thick Film ZrO2 NOx Sensor for the Measurement of Low NOx

Concentration,” February 1998, SAE 980170.

66. Kato, N. et al, “Long Term Stable NOx Sensor with Integrated In-Connector Control

Electronics,” March 1999, SAE 1999-01-0202.

67. Sasaki, S., Ito, T., and Iguchi, S., “Smoke-less Rich Combustion by Low Temperature

Oxidation in Diesel Engines,” 9th Aachener Kolloquim Fahrzeug - und Motorentechnik 2000.

Copy available in Air Docket A-2001-28.
Regulatory Impact Analysis

4-176

68. Diesel Emission Control - Sulfur Effects (DECSE) Program Phase II Summary Report: NOx

Adsorber Catalysts, October 2000. Copy available in Air Docket A-2001-28.

69. Memo from Byron Bunker to Docket A-99-06, “Estimating Fuel Economy Impacts of NOx

Adsorber De-Sulfurization,” December 10, 1999. Copy available in Air Docket A-2001-28.

70. Jobson, E. et al, “Research Results and Progress in LeaNOx II - A Cooperation for Lean

NOx Abatement,” SAE 2000-01-2909.

71. Asanuma, T. et al, “Influence of Sulfur Concentration in Gasoline on NOx Storage -

Reduction Catalyst,” SAE 1999-01-3501.

72. Guyon, M. et al, “NOx-Trap System Development and Characterization for Diesel Engines

Emission Control,” SAE 2000-01-2910.

73. Dou, Danan and Bailey, Owen, “Investigation of NOx Adsorber Catalyst Deactivation,”

SAE 982594.

74. Guyon, M. et al, “Impact of Sulfur on NOx Trap Catalyst Activity - Study of the

Regeneration Conditions”, SAE 982607.

75. Dearth, et al, “Sulfur Interaction with Lean NOx Traps: Laboratory and Engine

Dynamometer Studies”, SAE 982595.

76. Guyon, M. et al, “NOx-Trap System Development and Characterization for Diesel Engines

Emission Control,” SAE 2000-01-2910.

77. Dou, D and Bailey, O.,”Investigation of NOx Adsorber Catalyst Deactivation,” SAE

982594. 

78. Dearth, et al, “Sulfur Interaction with Lean NOx Traps: Laboratory and Engine

Dynamometer Studies”, SAE 982595.

79. Dearth, et al, “Sulfur Interaction with Lean NOx Traps: Laboratory and Engine

Dynamometer Studies”, Figure 5 SAE 982595. 

80. Dearth, et al, “Sulfur Interaction with Lean NOx Traps: Laboratory and Engine

Dynamometer Studies”, SAE 982595.

81. Dou, D and Bailey, O.,”Investigation of NOx Adsorber Catalyst Deactivation,” SAE

982594. 

82. Heck, R. and Farrauto, R. Catalytic Air Pollution Control - Commercial Technology, page

64-65. 1995 Van Nostrand Reinhold Publishing.

83. Heck, R. and Farrauto, R. Catalytic Air Pollution Control - Commercial Technology,

Chapter 6. 1995 Van Nostrand Reinhold Publishing.
Technologies and Test Procedures for Low-Emission Engines

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84. Asanuma, T. et al, “Influence of Sulfur Concentration in Gasoline on NOx Storage -

Reduction Catalyst,” SAE 1999-01-3501.

85. Diesel Emission Control - Sulfur Effects (DECSE) Program Phase II Summary Report: NOx

Adsorber Catalysts, October 2000. Copy available in Air Docket A-2001-28.

86. Tanaka, H., Yamamoto, M., “Improvement in Oxygen Storage Capacity,” SAE 960794.

87. Yamada, T., Kobayashi, T., Kayano, K., Funabiki M., “Development of Zr Containing TWC

Catalysts”, SAE 970466.

88. McDonald, Joseph, and Lee Jones, U.S. EPA, “Demonstration of Tier 2 Emission Levels for

Heavy Light-Duty Trucks,” SAE 2000-01-1957.

89. Dearth, et al, “Sulfur Interaction with Lean NOx Traps: Laboratory and Engine

Dynamometer Studies”, SAE 982595.

90. Letter from Barry Wallerstein, Acting Executive Officer, SCAQMD, to Robert Danziger,

Goal Line Environmental Technologies, dated December 8, 1997, www.glet.com Air Docket A99-06 item II-G-137.

91. Reyes and Cutshaw, SCONOx Catalytic Absorption System, December 8, 1998,

www.glet.com Air Docket A-99-06 item II-G-147.

92. Danziger, R. et al 21,000 Hour Performance Report on SCONOX, 15 September 2000 EPA

Docket A-99-06 item IV-G-69.

93. Table from May 11, 2002 edition of the Frankfurter Allgemeine Zeitung listing Direct

Injection Gasoline Vehicles for sale in Europe; the table has been edited to indicate which

vehicles are lean-burn (i.e., would use a NOx adsorber catalyst) and which are stoichiometricburn (i.e., would use a conventional 3-way catalyst, indicated by 8 = 1). Copy available in Air

Docket A-2001-28.

94. Schenk, Charles “Summary of NVFEL Testing of Advanced NOx and PM Emission Control

Technologies” memo to EPA Docket A-99-06, item IV-A-29.

95. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” EPA420-R-00-026, December 2000, Docket A-2001-

28, Document No. II-A-01.

96. Schenk, C., McDonald, J., and Laroo, C., “High-Efficiency NOx and PM Exhaust Emission

Control for Heavy-Duty On-Highway Diesel Engines - Part Two” SAE 2001-01-3619, Air

Docket A-2001-28.

97. Schenk, C., McDonald, J., and Laroo, C., “High-Efficiency NOx and PM Exhaust Emission

Control for Heavy-Duty On-Highway Diesel Engines - Part Two” SAE 2001-01-3619, Air

Docket A-2001-28.
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98. Schenk, C., McDonald, J., and Laroo, C., “High-Efficiency NOx and PM Exhaust Emission

Control for Heavy-Duty On-Highway Diesel Engines - Part Two” SAE 2001-01-3619, Air

Docket A-2001-28.

99. Schenk, C. and Laroo, C. “ NOx Adsorber Aging on a Heavy-Duty On-Highway Diesel

Engine - Part One,” SAE 2003-01-0042. Copy available in Air Docket A-2001-28.

100. Schenk, C. and Laroo, C. “ NOx Adsorber Aging on a Heavy-Duty On-Highway Diesel

Engine - Part One,” SAE 2003-01-0042. Copy available in Air Docket A-2001-28.

101. Diesel Emission Control Sulfur Effects (DECSE) Program - Phase I Interim Data Report

No. 1, August 1999. Copy available in Air Docket A-2001-28.

102. Diesel Emission Control Sulfur Effects (DECSE) Program - Phase I Interim Data Report

No. 2: NOx Adsorber Catalysts, October 1999. Copy available in Air Docket A-2001-28.

103. Diesel Emission Control Sulfur Effects (DECSE) Program - Phase I Interim Date Report

No. 3: Diesel Fuel Sulfur Effects on Particulate Matter Emissions, November 1999. Copy

available in Air Docket A-2001-28.

104. Diesel Emission Control Sulfur Effects (DECSE) Program - Phase I Interim Data Report

No. 4, Diesel Particulate Filters-Final Report, January 2000. Copy available in Air Docket A2001-28.

105. Diesel Emission Control - Sulfur Effects (DECSE) Program Phase II Summary Report:

NOx Adsorber Catalysts, October 2000. Copy available in Air Docket A-2001-28.

106. Diesel Emission Control - Sulfur Effects (DECSE) Program Phase II Summary Report:

NOx Adsorber Catalysts, October 2000. Copy available in Air Docket A-2001-28.

107. Details with quarterly updates on the APBF-DEC programs can be found on the DOE

website at the following location http://www.ott.doe.gov/apbf.shtml..

108. Hakim, N. “NOx Adsorbers for Heavy Duty Truck Engines - Testing and Simulation,”

presentation at Motor Fuels: Effects on Energy Efficiency and Emissions in the Transportation

Sector Joint Meeting of Research Program Sponsored by the U.S. Department of Energy, Clean

Air for Europe and Japan Clean Air, October 9-10, 2002. Copy available in EPA Air Docket A2001-28.

109. Shoji, A.; Kamoshita, S.; Watanabe, T.; Tanaka, T.; and Yabe, M., “Development of a

Simultaneous Reduction System of NOx and PM for Light-Duty Truck,” JSAE 2003-5567.

110. McDonald, J. “Progress in the Development of Tier 2 Light-Duty Diesel Vehicles,” SAE

2004-01-1791, March 2004.

111. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-Duty Engines to Achieve Low Emission Levels”, Manufacturers of Emissions Controls
Technologies and Test Procedures for Low-Emission Engines

4-179

Association, June 1999 Air Docket A-2001-28.

112. Fable, S. et al, “Subcontractor Report - Selective Catalytic Reduction Infrastructure Study,”

AD Little under contract to National Renewable Energy Laboratory, July 2002, NREL/SR-5040-

32689. Copy available in EPA Air Docket A-2001-28.

113. Engelhard DPX catalyzed diesel particulate filter retrofit verification,

www.epa.gov/otaq/retrofit/techlist-engelhard.htm, a copy of this information is available in Air

Docket A-2001-28.

114. Engelhard DPX catalyzed diesel particulate filter retrofit verification,

www.epa.gov/otaq/retrofit/techlist-engelhard.htm, a copy of this information is available in Air

Docket A-2001-28.

115. Johnson Matthey CRT filter retroift verification,

http://www.epa.gov/otaq/retrofit/techlist-johnmatt.htm#jm4 a copy of this information is

available in Air Docket A-2001-28.

116. “Investigation of the Feasibility of PM Filters for NRMM”, Report by the European

Association of Internal Combustion Engine Manufacturers and Engine Manufacturers

Association, July, 2002. Copy available in EPA Air Docket A-2001-28, item # II-B-12

117. Sasaki, S., Ito, T., and Iguchi, S., “Smoke-less Rich Combustion by Low Temperature

Oxidation in Diesel Engines,” 9th Aachener Kolloquim Fahrzeug - und Motorentechnik 2000.

Copy available in Air Docket A-2001-28.

118. Jeuland, N., et al, “Performances and Durability of DPF (Diesel Particulate Filter) Tested

on a Fleet of Peugeot 607 Taxis First and Second Test Phases Results,” October 2002, SAE

2002-01-2790.

119. “Summary of Conference Call between U.S. EPA and Deutz Corporation on September 19,

2002 regarding Deutz Diesel Particulate Filter System”, EPA Memorandum to Air Docket A2001-28.

120. “Particulate Traps for Construction Machines: Properties and Field Experience” J.

Czerwinski et al, Society of Automotive Engineers Technical Paper 2000-01-1923.

121. “Engine Technology and Application Aspects for Earthmoving Machines and Mobile

Cranes, Dr. E. Brucker, Liebherr Machines Bulle, SA, AVL International Commercial

Powertrain Conference, October 2001. Copy available in EPA Air Docket A-2001-28, Docket

Item # II-A-12.

122. Phone conversation with Manufacturers of Emission Control Association (MECA), 9 April,

2003 confirming the use of emission-control technologies on nonroad equipment used in coal

mines, refineries, and other locations where explosion proofing may be required.
Regulatory Impact Analysis

4-180

123. See for example “Diesel-engine Management” published by Robert Bosch GmbH, 1999,

second edition, pages 6-8 for a more detailed discussion of the differences between and IDI and

DI engines.

124. See Chapter 14, Section 4 of “Turbocharging the Internal Combustion Engine”, N. Watson

and M.S. Janota, published by John Wiley and Sons, 1982.

125. See Section 2.2 through 2.3 in “Nonroad Diesel Emission Standards - Staff Technical

Paper”, EPA Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket

A-2001-28.

126. See Table 3-2 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

127. EPA Memorandum “2002 Model Year Certification Data for Engines <50 Hp”, William

Charmley, copy available in EPA Air Docket A-2001-28"

128. See Section 2.2 through 2.3 in “Nonroad Diesel Emission Standards - Staff Technical

Paper”, EPA Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket

A-2001-28.

129. Ikegami, M., K. Nakatani, S. Tanaka, K. Yamane: “Fuel Injection Rate Shaping and Its

Effect on Exhaust Emissions in a Direct-Injection Diesel Engine Using a Spool Acceleration

Type Injection System”, SAE paper 970347, 1997. Dickey D.W., T.W. Ryan III, A.C.

Matheaus: “NOx Control in Heavy-Duty Engines-What is the Limit?”, SAE paper 980174, 1998. 

Uchida N, K. Shimokawa, Y. Kudo, M. Shimoda: “Combustion Optimization by Means of

Common Rail Injection System for Heavy-Duty Diesel Engines”, SAE paper 982679, 1998.

130. "Effects of Injection Pressure and Nozzle Geometry on DI Diesel Emissions and

Performance," Pierpont, D., and Reitz, R., SAE Paper 950604, 1995.

131. EPA Memorandum “Documentation of the Availability of Diesel Oxidation Catalysts on

Current Production Nonroad Diesel Equipment”, William Charmley. Copy available in EPA Air

Docket A-2001-28.

132. See Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

133. See Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

134. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-duty Engines to Achieve Low Emission Levels: Interim Report Number 1 - Oxidation

Catalyst Technology, copy available in EPA Air Docket A-2001-28. “Reduction of Diesel

Exhaust Emissions by Using Oxidation Catalysts,” Zelenka et al, SAE Paper 90211, 1990. See

Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA Publication
Technologies and Test Procedures for Low-Emission Engines

4-181

EPA420-R-01-052, October 2001, copy available in EPA Air Docket A-2001-28.

135. “The Optimized Deutz Service Diesel Particulate Filter System II”, H. Houben et al, SAE

Technical Paper 942264, 1994 and “Development of a Full-Flow Burner DPF System for Heavy

Duty Diesel Engines, P. Zelenka et al, SAE Technical Paper 2002-01-2787, 2002.

136. See Tables 6, 8, and 14 of “Nonroad Emission Study of Catalyzed Particulate Filter

Equipped Small Diesel Engines” Southwest Research Institute, September 2001. Copy available

in EPA Air Docket A-2001-28.

137. See Section 2.2 through 2.3 in “Nonroad Diesel Emission Standards - Staff Technical

Paper”, EPA Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket

A-2001-28.

138. Highway Diesel Progress Review Report 2, United States Environmental Protection

Agency, March 2004, EPA 420-R-04-004. Copy available in Air Docket OAR-2003-0012-0918.

139. See Section 3 of “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

140. See Table 3-2 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

141. EPA Memorandum “Summary of Model Year 2001 Certification data for Nonroad Tier l

Compression-ignition Engines with rated power between 0 and 50 horsepower”, William

Charmley, copy available in EPA Air Docket A-2001-28, docket item II-B-08.

142. "Effects of Injection Pressure and Nozzle Geometry on DI Diesel Emissions and

Performance," Pierpont, D., and Reitz, R., SAE Paper 950604, 1995.

143. EPA Memorandum “Documentation of the Availability of Diesel Oxidation Catalysts on

Current Production Nonroad Diesel Equipment”, William Charmley. Copy available in EPA Air

Docket A-2001-28.

144. See Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA

Publication EPA420-R-01-052, October 2001. Copy available in EPA Air Docket A-2001-28.

145. “Demonstration of Advanced Emission Control Technologies Enabling Diesel-Powered

Heavy-duty Engines to Achieve Low Emission Levels: Interim Report Number 1 - Oxidation

Catalyst Technology, copy available in EPA Air Docket A-2001-28. “Reduction of Diesel

Exhaust Emissions by Using Oxidation Catalysts,” Zelenka et al, SAE Paper 90211, 1990. See

Table 2-4 in “Nonroad Diesel Emission Standards - Staff Technical Paper”, EPA Publication

EPA420-R-01-052, October 2001, copy available in EPA Air Docket A-2001-28.

146. Letter from Marty Barris, Donaldson Corporation, to Byron Bunker, U.S. EPA, March

2000. A copy is available in Air Docket A-2001-28.
Regulatory Impact Analysis

4-182

147. Hawker, P. et al, “Experience with a New Particulate Trap Technology in Europe,” SAE

970182.

148. Hawker, P. et al, “Experience with a New Particulate Trap Technology in Europe,” SAE

970182.

149. Allansson, et al, “European Experience of High Mileage Durability of Continuously

Regenerating Filter Technology,” SAE 2000-01-0480.

150. Letter from Dr. Barry Cooper, Johnson Matthey, to Don Kopinski, U.S. EPA. A copy is

available in Air Docket A-2001-28.

151. Telephone conversation between Dr. Barry Cooper, Johnson Matthey, and Todd Sherwood,

EPA, Air Docket A-99-06.

152. Letter from Dr. Barry Cooper to Don Kopinski U.S. EPA. A copy is available in Air

Docket A-2001-28.

153. Dou, Danan and Bailey, Owen, “Investigation of NOx Adsorber Catalyst Deactivation,”

SAE 982594.

154.Guyon, M. et al, “Impact of Sulfur on NOx Trap Catalyst Activity - Study of the

Regeneration Conditions”, SAE 982607.

155. Though it was favorable to decompose sulfate at 800/C, performance of the NSR (NOx

Storage Reduction catalyst, i.e., NOx Adsorber) catalyst decreased due to sintering of precious

metal. - Asanuma, T. et al, “Influence of Sulfur Concentration in Gasoline on NOx Storage -

Reduction Catalyst”, SAE 1999-01-3501.

156. Nonroad Test Cycle Development, Starr, M., Southwest Research Institute Contractor

report for the United States Environmental Protection Agency, September 1998

157. Nonroad Data Analysis and Composite Cycle Development, Webb, C., Southwest Research

Institute contractor report to the United States Environmental Protection Agency, September

1997 

158. Memorandum from Kent Helmer to Cleophas Jackson, “National Excavator Fleet

Population Estimate”, Docket A-2001-28, # II-B-32.

159.Bin Analysis of Nonroad Diesel Transient Duty Cycles; Hoffman, G., Dyntel Corporation;

Ann Arbor, MI, March 2003

160.“Maximum Speed Determination Procedure,” EPA memo to Docket A-2001-28, # II-B-45.

161. See Chapter 8 of “Summary and Analysis of Comments: Control of Emissions from Marine

Diesel Engines” (EPA420-R-99-028), December 1999. This report may be found on and

downloaded from the EPA-OTAQ website at http://www.epa.gov/otaq/marine.htm.
Technologies and Test Procedures for Low-Emission Engines

4-183

162. See http://www.epa.gov/oms/regs/nonroad/equip-hd/cycles/nrcycles.htm.

163. ISO Report on NRTC Cycle Development “Final Report on NRTC test Procedure, Summer

2002" Docket A-2001-28.

164. Memorandum from Kent Helmer to Cleophas Jackson, “Applicability of EPA’s NRTC

cycle to the U.S. Nonroad Diesel Population”, Docket A-2001-28, # II-B-34.

165. Title 40, U.S. Code of Federal Regulations, §89.407(c)(10-11), July 2003.

166. Guidance Letter to Engine Manufacturers Association from Greg Green, Division

Director, Certification and Compliance Division, OTAQ to Jed Mandel, Engine Manufacturers

Association, Dated 12 December 2002, “Guidance Regarding Test Procedures for Heavy-Duty

On-Highway and Non-Road Engines.”

167. Schenk, C., Laroo, C., Olson, B., Fisher, L., "Four-Flow Path High-Efficiency NOx and

PM Exhaust Emission Control System for Heavy-Duty On-Highway Diesel Engines" SAE

Technical Paper 2003-01-2305, 2003.

168. Memorandum from Kent Helmer to Cleophas Jackson, “Tabular Summary of California

EPA-ARB TRU engine Operating Data”, Docket A-2001-28, # IV-E-35.

169. Memorandum from Kent Helmer to EPA Air Docket A-2001-28, # “Discussion with

Kubota and Carrier Representatives, March 2, 2004”, e-Docket OAR-2003-0012-0996.

170. Memorandum from Kent Helmer to EPA Air Docket A-2001-28, # “Correspondence from

Carrier Representative, March 4, 2004”, e-Docket OAR-2003-0012-0998.

171. Memorandum from Kent Helmer to EPA Air Docket A-2001-28, # “Corespondence from

Tom Sem of Thermo King, March 6, 2004,” e-Docket OAR-2003-0012-0995.
CHAPTER 5: Fuel Standard Feasibility

5.1 The Blendstocks and Properties of Non-Highway Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1.1 Blendstocks Comprising Non-highway Diesel Fuel and their Sulfur Levels . . . . . . . . . . 5-1

5.1.2 Current Levels of Other Fuel Parameters in Non-highway Distillate . . . . . . . . . . . . . . . . 5-4

5.2 Evaluation of Diesel Fuel Desulfurization Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

5.2.1 Introduction to Diesel Fuel Sulfur Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-7

5.2.2 Conventional Hydrotreating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-8

5.2.2.1 Fundamentals of Distillate Hydrotreating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-9

5.2.2.2 Meeting a 15 ppm Cap with Distillate Hydrotreating . . . . . . . . . . . . . . . . . . . . . . 5-13

5.2.2.3 Low-Sulfur Performance of Distillate Hydrotreating . . . . . . . . . . . . . . . . . . . . . . 5-19

5.2.3 Process Dynamics Isotherming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-21

5.2.4 Phillips S-Zorb Sulfur Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-24

5.2.5 Chemical Oxidation and Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-25

5.3 Feasibility of Producing 500 ppm Sulfur NRLM Diesel Fuel in 2007 . . . . . . . . . . . . . . . . . . . 5-27

5.3.1 Expected use of Desulfurization Technologies for 2007 . . . . . . . . . . . . . . . . . . . . . . . . . 5-27

5.3.2 Lead-time Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-28

5.3.2.1 Tier 2 Gasoline Sulfur Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-29

5.3.2.2 15 ppm Highway Diesel Fuel Sulfur Cap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-30

5.3.2.3 Lead-time Projections for Production of 500 ppm NRLM Diesel Fuel . . . . . . . . . 5-31

5.3.2.4 Comparison with the 500 ppm Highway Diesel Fuel Program . . . . . . . . . . . . . . . 5-35

5.3.2.5 Small Refiners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-35

5.4 Feasibility of Producing 15 ppm Sulfur NRLM in 2010 and 2012 . . . . . . . . . . . . . . . . . . . . . . 5-36

5.4.1 Expected use of Desulfurization Technologies in 2010 and 2012 . . . . . . . . . . . . . . . . . . 5-36

5.4.2 Lead-time Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-39

5.5 Distribution Feasibility Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-40

5.5.1 Ability of Distribution System to Accommodate the Need for Additional Product

Segregations That Could Result from This Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-40

5.5.1.1 The Diesel Fuel Distribution System Prior to Implementation of the NRLM SulfurControl Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-40

5.5.1.2 Potential for Additional Product Segregation Under the NRLM Sulfur Program . 5-41

5.5.1.3 Ability of Fuel Distributors to Handle New Product Segregations that Will Result

from the NRLM Sulfur Control Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-50

5.5.1.4 Determining the Boundaries for the Northeast/Mid-Atlantic Area . . . . . . . . . . . . 5-55

5.5.2 Limiting Sulfur Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-63

5.5.3 Handling Practices for Distillate Fuels that Become Mixed in the Pipeline Distribution

System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-65

5.6 Feasibility of the Use of a Marker in Heating Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-68

5.7 Impacts on the Engineering and Construction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-75

5.7.1 Design and Construction Resources Related to Desulfurization Equipment . . . . . . . . . . 5-76

5.7.2 Number and Timing of Revamped and New Desulfurization Units . . . . . . . . . . . . . . . . 5-77

5.7.3 Timing of Desulfurization Projects Starting up in the Same Year . . . . . . . . . . . . . . . . . . 5-78

5.7.4 Timing of Design and Construction Resources Within a Project . . . . . . . . . . . . . . . . . . 5-78

5.7.5 Projected Levels of Design and Construction Resources . . . . . . . . . . . . . . . . . . . . . . . . 5-80

5.8 Supply of Nonroad, Locomotive, and Marine Diesel Fuel (NRLM) . . . . . . . . . . . . . . . . . . . . 5-84

5.9 Desulfurization Effect on Other Non-Highway Diesel Fuel Properties . . . . . . . . . . . . . . . . . . 5-92

5.9.1 Fuel Lubricity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-92

5.9.2 Volumetric Energy Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-95

5.9.3 Fuel Properties Related to Storage and Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-97

5.9.4 Cetane Index and Aromatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-97

5.9.5 Other Fuel Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-98

Appendix 5A: EPA’s Legal Authority for Adopting Nonroad, Locomotive, and Marine Diesel Fuel

Sulfur Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-101
Fuel Standard Feasibility

A Additives that contain sulfur are sometimes intentionally added to diesel fuel. For a discussion how the

addition of these additives will be affected under this program, see Section IV.D.5. 

B

 Distillate refers to a broad category of fuels falling into a specific boiling range. Distillate fuels have a heavier

molecular weight and therefore boil at higher temperatures than gasoline. Distillate includes diesel fuel, kerosene

and home heating oil. For the purposes of this discussion, we will focus on No. 2 distillate, which comprises the

majority of diesel fuel and heating oil. 

5-1

CHAPTER 5: Fuel Standard Feasibility

In this chapter, we present an analysis of the feasibility of complying with the fuel program

adopted in this final rule, including a discussion of the technology used to desulfurize and

distribute ultra low diesel fuel. In Section 5.1, we discuss the sources of the blendstocks which

comprise diesel fuel and summarize their reported sulfur levels. In Section 5.2, we present and

evaluate a wide variety of distillate desulfurization technologies that refiners might use to meet

the 500 and 15 ppm sulfur caps. In Section 5.3, we formally assess the technical feasibility of

meeting the 500 ppm sulfur cap in 2007, including the sufficiency of the lead time for refiners. 

In Section 5.4, we assess the technical feasibility meeting the 15 ppm sulfur cap, including the

sufficiency of lead time for refiners. In Section 5.5, we assess the feasibility of distributing 500

and 15 ppm sulfur fuel. In Section 5.6, we assess the feasibility of using a marker in heating oil. 

In Section 5.7, we evaluate the impacts of this program and other sulfur control regulations on

the engineering and construction industry. In Section 5.8 we assess the impacts of this program

on the supply of NRLM diesel fuel. In Section 5.9 we discuss how hydro-desulfurization is

expected to affect NRLM diesel fuel properties other than sulfur. Finally, in Chapter 5.10 we

assess how properties other than sulfur will be impacted by desulfurizing NRLM diesel fuel. At

the end of Chapter 5 we include an Appendix summarizing EPA’s authority for adopting NRLM

sulfur standards. 

5.1 The Blendstocks and Properties of Non-Highway Diesel Fuel 

5.1.1 Blendstocks Comprising Non-highway Diesel Fuel and their Sulfur Levels

The primary sources of sulfur in diesel fuel are the sulfur-containing compounds that occur

naturally in crude oil.A Depending on the source, crude oil contains anywhere from fractions of

a percent of sulfur, such as less than 0.05 weight percent (500 ppm) to as much as several weight

percent.1 The average amount of sulfur in crude oil refined in the United States is about one

weight percent.2

 Most of the sulfur in crude oil is in the heaviest boiling fractions. Since most

of the refinery blendstocks that are used to manufacture diesel fuel come from the heavier

boiling components of crude oil, they contain substantial amounts of sulfur.

The distillateB produced by a given refinery is composed of one or more blendstocks from

crude oil fractionation and conversion units at the refinery. Refinery configuration and

equipment, and the types and relative volumes of products manufactured (the product slate) can
Final Regulatory Impact Analysis

5-2

Aromatics

Natural

Gas

Crude 

Oil

Fuel Gas

LPG

Gasoline

Kerosine

Jet Fuel

Off-roadDiesel

Fuel Oil

Resid

Coke

Gas Plant

Polymerization

Alkylation

Coker

Crude Tower

Vacuum Tower

Aromatics

Extraction

Hydrocracker

Hydrotreater Reformer

Distillate

Hydrotreater

Fluidized Cat

Cracker

Hydrogen

Plant

H2

H2

H2

H2

Isomerization

Straight Run

Splitter

Naphtha 

Splitter

H2

H2

On-Highway 

Diesel

Figure 5.1-1

Diagram of a Typical Complex Refinery

significantly affect the sulfur content of diesel fuel. The diagram on the following page

illustrates the configuration and equipment used at a typical complex refinery in the United

States.

Refineries differ from the model in the preceding diagram depending on the characteristics of

the crude oils refined, and their product slate, as illustrated in the following examples:

- Refineries that process lighter crude oils are less likely to have coker and hydrocracker

units.

- Refinery streams that can be used to manufacture diesel fuel can also be used to

manufacture heating oil, kerosene, and jet fuel. Much of the distillate product from the

hydrocracker is often blended into jet fuel rather than diesel fuel; current highway

regulations generally require that a refinery have a hydrotreater, which is usually not

necessary if the refinery produces only high sulfur non-highway diesel fuel. 

On an aggregate basis, most of the distillate manufactured in the United States comes from

the crude fractionation tower (called straight-run or SR). Most of the remainder comes from the

fluid catalytic cracker (FCC) conversion unit (called light cycle oil or LCO). The remaining
Fuel Standard Feasibility

5-3

small fraction of diesel fuel volume comes from a coker conversion unit or other units that crack

heavy compounds such as a visbreaker or steam cracker (called other cracked stocks in this

document), or from the hydrocracker conversion unit (called hydrocrackate).

To comply with the current federal regulatory requirement on the sulfur content of highway

diesel fuel (500 ppm cap), the blendstock streams from these process units are typically further

processed to reduce their sulfur content. Desulfurization of highway diesel blendstocks to meet

the 500 ppm cap is accomplished in fixed-bed hydrotreaters that operate at moderate pressures

(500 to 800 psi and higher).3

 Nearly all the low-sulfur diesel blendstocks come from such

hydrotreaters. However, a small amount of low-sulfur diesel also comes from hydrocrackers

operating at pressures of 500 to 3000 psi, although most operate at 1500 to 3000 psi, which

naturally produces distillate fuel with sulfur levels of 100 ppm or less.

To comply with applicable non-highway sulfur requirements which range from 2000 to 5000

ppm, or the 40 cetane standard for nonroad, locomotive and marine diesel fuel, some of the

distillate blendstocks used to produce non-highway diesel fuel and heating oil are hydrotreated. 

A significant amount of hydrocracked distillate is also blended into non-highway diesel fuel and

heating oil. As discussed in Chapter 7, the use of hydrotreated blendstocks in non-highway

diesel fuel has important implications for the cost of desulfurizing NRLM diesel fuel. 

The distillate blendstocks used to produce non-highway diesel fuel and their sulfur content

vary considerably from refinery to refinery. A survey conducted by the American Petroleum

Institute (API) and National Petroleum Refiners Association (NPRA) in 1996 examined the

typical blendstock properties for the U.S. highway and the non-highway diesel pools.4

 The

results of this survey for the non-highway distillate pool are in Table 5.1-1.
Final Regulatory Impact Analysis

5-4

Table 5.1-1

Average Composition and Sulfur Content of the 

Non-highway Distillate Pool Outside of California in 19965

Type of Distillate

Stream

Diesel Blendstock Percentage Sulfur Content

(ppm)

Unhydrotreated

Straight-Run 45 2274

Light Cycle Oil (LCO) 12 3493

Coker Gas Oil 1 2345

Unhydrotreated Subtotal 58 -

Hydrotreated

Hydrotreated Straight-Run 18 353

Hydrotreated LCO 10 1139

Hydrotreated Coker Gas Oil 4 270

Hydrocrackate 10 115

Hydrotreated Subtotal 42 -

Total 100 -

As shown in Table 5.1-1, approximately 42 percent of all blendstocks used to manufacture

non-highway distillate outside of California are hydrotreated to reduce their sulfur content. This

includes hydrocrackate (10 percent of the non-highway distillate pool), which is desulfurized to a

substantial extent as a necessary element of the hydrocracking process and is not further

processed in a hydrotreater. Table 5.1-1 also shows that approximately 58 percent of nonhighway distillate comes from nonhydrotreated blendstocks. As expected, the sulfur levels of

the hydrotreated blendstocks are lower than the nonhydrotreated distillate blendstocks.

In Chapter 7 of the RIA we use this blendstock information as one of the input parameters for

estimating the relative difficulty and ultimately the cost for desulfurizing diesel fuel. The 1996

data is an important input for our cost analysis, and we update the mix of blendstocks to 2002

based on changes in relative unit capacities. 

5.1.2 Current Levels of Other Fuel Parameters in Non-highway Distillate

It is useful to review other qualities of high-sulfur distillate, as well as sulfur content. First,

some of the desulfurization technologies affect these other fuel properties. Second, as discussed

further below, some sulfur compounds are more difficult to treat than others. In some cases,

refiners might try to shift these more difficult compounds to fuels that face less stringent sulfur

standards. Their ability to do this depends, not only on the economics of doing so, but also on

the effect of such shifts on nonsulfur properties and whether or not these other properties still

meet industry specifications. Thus, it is helpful to evaluate the degree to which current nonhighway distillate fuels meet or exceed applicable industry standards.
Fuel Standard Feasibility

5-5

Data on the current distillation characteristics, API gravity, pour point, natural cetane level,

and aromatics content of diesel fuel blendstocks are in Table 5.1-2.

Table 5.1-2

Average Non-highway Distillate Fuel Property Levels by Geographic Area6 7

(Data from 1997 API/NPRA Survey unless specified) 

Fuel Parameter PADD 1 PADD 2 PADD 3 PADD 4 PADD 5 

(CA Excluded)

U.S. 

(CA Excluded)

CA

API Gravity 32.6 34.1 32.6 35.6 33.8 32.8 30.8

Cetane Numbera N/A N/A N/A N/A N/A 47 N/A

Pour Point (°F)

[additized] -6 -8 0 6 12 -1 4

Pour Point Depressant

Additive (ppmw) 0 71 0 13 0 18 0

Distillation 

(°F)

T10 434 425 418 411 466 419 498

T30 492 476 457 443 517 464

T50 517 508 502 499 542 503 556

T70 545 558 536 522 570 539

T90 613 604 598 591 616 595 620

a

 From 1997 NIPER/TRW survey data, U.S. average includes California. N/A means not available. 

The American Society for Testing Materials (ASTM) has established requirements that apply

to No. 2 non-highway diesel fuel, as well as for No. 2 distillate fuel (e.g., heating oil).8 The

requirements most relevant to desulfurization are summarized in Table 5.1-3. 

Table 5.1-3

ASTM Requirements that Apply to Non-Highway Distillate Fuels

No. 2 Diesel Fuel

(Non-highway)

No. 2 Fuel Oil/Heating

Oil

No. 2 Marine Distillate

(DMA)

T-90 Min °F

T-90 Max °F

540

640

540

640

—

—

Density max (g/cm3

) (API Gravity min) None 0.876 (30.0) 0.890 (27.5)

Pour Point max °F

Cloud Point °F 46 to -0.4

21.2 21.2

Sulfur max (ppm) 5000 5000

Cetane Number min 40 40
Final Regulatory Impact Analysis

5-6

Comparing Tables 5.1-2 and 5.1-3 shows that the average properties of current non-highway

distillate are within the ASTM requirements, and for some properties, well within requirements. 

For example, except for California, the T90 of current non-highway diesel fuel is 25-40°F below

the maximum allowed. The average cetane number of all non-highway distillate is well above

the minimum of 40. Finally the pour point is well below the maximum allowed for fuel

oil/heating oil and marine distillate fuel. One exception is that the API gravity of non-highway

distillate fuel in PADDs 1 and 3, which includes the heating oil used in the Northeast, is just

above the minimum. 

While refiners might try to perform such shifts in blendstocks between fuels, note that we did

not assume refineries would be shifting blendstocks between various distillate fuels to reduce the

compliance costs associated with the NRLM diesel fuel sulfur standards. Instead, we projected

the use of desulfurization techniques that will be sufficient to meet the new sulfur standards

without shifting more difficult-to-treat sulfur compounds to other fuels. This approach appeared

reasonable, given that we were evaluating the potential of over 100 refineries currently

producing non-highway distillate fuel to reduce sulfur in NRLM diesel fuel. The ability to shift

blendstocks between fuels to reduce costs is very refinery-specific and difficult to estimate on

average across a wide range of refineries. Also, two primary types of shifts are possible and

both have limits. One approach is to shift the heaviest portion of selected blendstocks such as

LCO to the bunker or residual fuel pool, avoiding the need to desulfurize this material. 

However, the market for these heavy fuels is limited and on a national basis, this approach is

generally not economically feasible. The other approach is to shift these difficult-to-treat

streams and portions of streams to heating oil, which can meet less stringent sulfur standards. 

This would likely require the addition of additional product tankage and require more refineries

to produce lower-sulfur NRLM diesel fuel. The material being shifted to heating oil could still

require additional desulfurization to ensure that ASTM and state standards were still being met. 

Thus, there would be a cost trade-off, not just a cost reduction. Again, given the national scale

of this analysis, we decided to avoid the projection of such shifts and limit our analysis to the

desulfurization of current non-highway diesel fuel blendstocks. In this regard, our cost analysis

as presented in Chapter 7 can be viewed as somewhat conservative.

5.2 Evaluation of Diesel Fuel Desulfurization Technology

5.2.1 Introduction to Diesel Fuel Sulfur Control 

As mentioned in Section 5.1, the sulfur in diesel fuel comes from the crude oil processed by

the refinery. One way to reduce the amount of sulfur in diesel fuel is therefore to process a crude

oil that is lower in sulfur. Some refiners already do this. Others could switch to low- or at least

lower-sulfur crude oils. However, there is limited capability worldwide to produce low-sulfur

crude oil. While new oil fields producing light, sweet crude oil are still being discovered, most

of the new crude oil production being brought on-line is heavier, more sour (i.e., higher sulfur)

crude oils. The incentive to use low-sulfur crude oils has existed for some time and low-sulfur

crude oils have traditionally commanded a premium price relative to higher-sulfur crude oils. 

While a few refiners with access to lower-sulfur crude oil might reduce their diesel sulfur levels
Fuel Standard Feasibility

5-7

this way, it is not feasible for most, let alone all U.S. refiners to switch to low-sulfur crude oils to

meet a tighter diesel fuel sulfur standard. In addition, while helpful, a simple change to a lowsulfur crude oil may fall short of complying with the 500 ppm sulfur standard, and certainly fall

short of the 15 ppm sulfur standard. Thus, changing to a sweeter crude oil was not considered

viable for complying with the nonroad, locomotive, and marine diesel sulfur standards.

A method to reduce diesel fuel sulfur much more significantly is to chemically remove sulfur

from the hydrocarbon compounds that comprise diesel fuel. This is usually accomplished

through catalytically reacting the diesel fuel with hydrogen at moderate to high temperature and

pressure over a fixed bed of hydrotreating catalyst. Two specific examples of this process are

hydrotreating and hydrocracking. A modified version of hydrotreating that operates solely in the

liquid state is now available by Process Dynamics. Another process licensed by Conoco-Phillips

uses a moving bed catalyst to both remove and adsorb the sulfur using hydrogen at moderate

temperature and pressure. There are other low-temperature and low-pressure processes being

developed that don’t rely on hydrotreating, such as chemical oxidation. Sulfur can be removed

via these processes up front in the refinery, such as from crude oil, before being processed in the

refinery into diesel fuel. Or, sulfur can be removed from individual refinery streams that are to

be blended directly into diesel fuel. Finally, another method to moderately reduce diesel fuel

sulfur is to shift sulfur-containing hydrocarbon compounds to other fuels produced by the

refinery.

After careful review of all these approaches, we expect that the sulfur reduction required by

the 500 ppm sulfur standard will occur through chemical removal via conventional

hydrotreating. For complying with the 15 ppm cap for NRLM diesel fuel, we expect it will be

met primarily through liquid-phase hydrotreating, which is an emerging advanced

desulfurization technology. This section will begin with a relatively detailed discussion of the

capabilities of these various processes. Refiners may use the other methods to obtain costeffective sulfur reductions that will complement the primary sulfur reduction achieved via

hydrotreating. These other methods, such as FCC feed hydrotreating, adsorption and chemical

oxidation are discussed following the primary discussion of distillate hydrotreating and liquidphase hydrotreating. Another means for aiding the desulfurization of diesel fuel, particularly to

comply with the 15 ppm standard, is undercutting, which removes the most difficult-to-treat

sulfur compounds. Since undercutting can help ease the task of complying with the 15 ppm

standard for any of the desulfurization technologies, we provide a discussion of undercutting

below.

5.2.2 Conventional Hydrotreating

Hydrotreating generally combines hydrogen with a hydrocarbon stream at high temperature

and pressure in the presence of a catalyst. Refineries currently employ a wide range of these

processes for various purposes. For example, naphtha (gasoline-like material that does not meet

gasoline specifications, such as octane level) being fed to the refinery reformer is always

hydrotreated to remove nearly all sulfur, nitrogen and metal contaminants that would deactivate

the noble metal catalyst used in the reforming process. Similarly, feed to the FCC unit is often

hydrotreated to remove most of the sulfur, nitrogen and metal contaminants to improve the yield
Final Regulatory Impact Analysis

5-8

and quality of high value products, such as gasoline and distillate, from the FCC unit. Refineries

currently producing highway diesel fuel to the 500 ppm standard hydrotreat their distillate to

remove much of the sulfur present and to improve the cetane. That same unit or another

hydrotreating unit in the refinery also hydrotreats some of the refinery streams used to blend up

non-highway distillate. We expect that nearly all refiners will hydrotreat the naphtha produced

by the FCC unit to remove most of the sulfur present to comply with the Tier 2 gasoline sulfur

standards.9

If the temperature or pressure is increased sufficiently and if a noble metal catalyst is used,

hydrotreating can more dramatically affect the chemical nature of the hydrocarbons, as well as

remove contaminants. For example, through a process called hydrocracking, smaller, lighter

molecules are created by splitting larger, heavier molecules. In the process, nearly all the

contaminants are removed and olefins and aromatics are saturated into paraffins and naphthenes. 

Outside the United States, this process is commonly used to produce distillate from heavier, less

marketable refinery streams. In the United States the hydrocracker is most often used to produce

gasoline from poor quality distillate, such as LCO from the FCC unit.

A few refineries also currently hydrotreat their distillate more severely than is typical, but not

as severely as hydrocracking. Their intent is to remove the sulfur, nitrogen and metallic

contaminants and to also saturate most of the aromatics present. This is done primarily in

Europe to meet very stringent specifications for both sulfur and aromatics applicable to certain

diesel fuels and encouraged by reduced excise taxes. This severe hydrotreating process is also

used in the United States to “upgrade” petroleum streams that are otherwise too heavy or too low

in quality to be blended into the diesel pool, by cracking some of the material to lower molecular

weight compounds and saturating some of the aromatics to meet the distillation and cetane

requirements. A different catalyst that encourages aromatic saturation is used instead of one that

simply encourages contaminant removal.

To meet the 500 ppm and the 15 ppm sulfur standards, we expect refiners to focus as much

as possible on sulfur removal. Other contaminants, such as metals, are already sufficiently

removed by existing refinery processes. While saturation of aromatics generally improves

cetane, the cetane numbers of current nonroad, locomotive, and marine diesel fuels are typically

already sufficient to comply with the applicable ASTM standards. Thus, refiners want to avoid

saturating aromatics to avoid the additional cost of increased hydrogen consumption. 

Consequently, we anticipate refiners will choose desulfurization processes that minimize the

amount of aromatics saturation. Current diesel fuel already meets all applicable specifications;

hydrotreating to remove sulfur should not degrade quality, except possibly lubricity, as discussed

in Section 5.9.1. Thus, with this one exception, there should be no need to improve diesel fuel

quality as a direct result of this new diesel sulfur standard. Refiners choosing to improve fuel
Fuel Standard Feasibility

C Refiners can choose to “upgrade” heavy refinery streams that do not meet the cetane and distillation

requirements for highway diesel fuel. The process for doing so is also called ring opening, since one or more of the

aromatic rings of heavy, aromatic molecules are opened up, improving the value of the stream. Upgrading the heavy

refinery streams to highway diesel fuel improves the stream’s market price by 10 - 30 c/gal. 

5-9

quality would be focusing on improved profitability, rather than meeting the 15 ppm sulfur

standard.C

5.2.2.1 Fundamentals of Distillate Hydrotreating

Almost all distillate hydrotreater designs follow the same broad format. Liquid distillate fuel

is heated to temperatures of 300 to 380oC, pumped to pressures of 500 to 700 psia, mixed with

hydrogen, and passed over a catalyst. Hydrogen reacts with sulfur and nitrogen atoms contained

in the hydrocarbon molecules, forming hydrogen sulfide and ammonia. The resulting vapor is

then separated from the desulfurized distillate. The desulfurized distillate is usually simply

mixed with other distillate streams in the refinery to produce diesel fuel and heating oil.

The vapor coming off the reactor still contains a lot of valuable hydrogen, because the

reaction requires the use of a significant amount of excess hydrogen to operate efficiently and

practically. However, the vapor also contains a significant amount of hydrogen sulfide and

ammonia, which inhibit the desulfurization and denitrogenation reactions and must be removed

from the system. Thus, the hydrogen leaving the reactor is usually mixed with fresh hydrogen

and recycled to the front of the reactor for reaction with fresh distillate feed. This would cause a

build up of hydrogen sulfide and ammonia in the system, since it has no way to leave the system. 

In some cases, the hydrogen sulfide and ammonia are chemically scrubbed from the hydrogen

recycle stream. In other cases, a portion of the recycle stream is simply purged from the system

as a mixture of hydrogen, hydrogen sulfide and ammonia. The latter is less efficient since it

leads to higher levels of hydrogen sulfide and ammonia in the reactor, but it avoids the cost of

building and operating a hydrogen sulfide scrubber.

Current desulfurization processes in the United States generally use only one reactor, due to

the need to desulfurize diesel fuel only to 500 ppm or slightly lower. However, for diesel

upgrading reactions or for deeper desulfurization reactions, a second reactor can be used. 

Instead of liquid distillate fuel going to the diesel fuel/heating oil pool after the first reactor, it

would be stripped of hydrogen sulfide and ammonia and mixed with fresh hydrogen and sent to

the second reactor, which is also called a second stage, after the inter stage stripping that occurs.

Traditional reactors are cocurrent in nature. The hydrogen is mixed together with the

distillate at the entrance to the reactor and flow through the reactor together. Because the

reaction is exothermic, heat must be removed periodically. This is sometimes done through the

introduction of fresh hydrogen and distillate fuel in the middle of the reactor. The advantage of

cocurrent design is practical as it eases the control of gas-liquid mixing and contact with the

catalyst. The disadvantage is that the concentration of hydrogen is the highest at the front of the

reactor where the easiest to remove sulfur compounds are highest in concentration and lowest at

the outlet where the hardest to remove sulfur compounds are highest in concentration. The
Final Regulatory Impact Analysis

5-10

opposite is true for the concentration of hydrogen sulfide. This increases the difficulty of

achieving extremely low sulfur levels due to the low hydrogen concentration and high hydrogen

sulfide concentration at the end of the reactor.

The normal solution to this problem is to design a counter-current reactor, where the fresh

hydrogen is introduced at one end of the reactor and the liquid distillate at the other end. Here,

the hydrogen concentration is highest (and the hydrogen sulfide concentration is lowest) where

the reactor is trying to desulfurize the most difficult (sterically hindered) compounds. The

difficulty of counter-current designs in the case of distillate hydrotreating is vapor-liquid contact

and the prevention of hot spots within the reactor. The SynAlliance (Criterion Catalyst Corp.,

and Shell Oil Co.) has patented a counter-current reactor design called SynTechnology. With

this technology, in a single reactor design, the initial portion of the reactor will follow a cocurrent design, while the last portion of the reactor will be counter-current. In a two reactor

design, the first reactor could be co-current, while the second reactor could be counter-current.

ABB Lummus estimates that the counter-current design can reduce the catalyst volume

needed to achieve 97 percent desulfurization by 16 percent relative to a co-current design.10 The

impact of the counter-current design is even more significant when aromatics reduction (or

cetane improvement) is desired in addition to sulfur control.

Sulfur-containing compounds in distillate can be classified according to the ease with which

they are desulfurized. Sulfur contained in paraffins or aromatics with a single aromatic ring are

relatively easy to desulfurize. These molecules are sufficiently flexible so the sulfur atom is in a

geometric position where it can make physical contact with the surface of the catalyst. The more

difficult compounds are contained in aromatics consisting of two aromatic rings, particularly

dibenzothiophenes. Dibenzothiophene contains two benzene rings that are connected by a

carbon-carbon bond and two carbon-sulfur bonds (both benzene rings are bonded to the same

sulfur atom). This compound is nearly flat in nature and the carbon atoms bound to the sulfur

atom hinder the approach of the sulfur atom to the catalyst surface. Despite this, current

catalysts are very effective in desulfurizing dibenzothiophenes, as long as only hydrogen is

attached to the carbon atoms bound directly to the sulfur atom.

Distillate fuel, however, can contain dibenzothiophenes that have methyl or ethyl groups

bound to the carbon atoms, which are in turn bound to the sulfur atom. These extra methyl or

ethyl groups further hinder the approach of the sulfur atom to the catalyst surface. 

Dibenzothiophenes with such methyl or ethyl groups are commonly referred to as being

sterically hindered. An example of a dibenzothiophene with a single methyl or ethyl group next

to the sulfur atom is 4-methyl dibenzothiophene. An example of a dibenzothiophene with two

methyl or ethyl groups next to the sulfur atom is 4,6-dimethyl dibenzothiophene. In 4,6-

dimethyl dibenzothiophene, and similar compounds, the presence of a methyl group on either

side of the sulfur atom makes it very difficult for the sulfur atom to react with the catalyst

surface to assist the hydrogenation of the sulfur atom.

Most straight-run distillates contain relatively low levels of these sterically hindered

compounds. LCO contains the greatest concentration of sterically hindered compounds, while
Fuel Standard Feasibility

5-11

other cracked distillate streams from the coker and the visbreaker contain levels of sterically

hindered compounds in concentrations between straight-run and LCO. Thus, LCO is generally

more difficult to desulfurize than coker distillate, which is in turn more difficult to treat than

straight-run distillate.11 In addition, cracked stocks, particularly LCO, have a greater tendency to

form coke on the catalyst, which deactivates the catalyst and requires its regeneration or

replacement.

The greater presence of sterically hindered compounds in LCO is related to two fundamental

factors. First, LCO contains much higher concentrations of aromatics than typical straight run

distillate.12 All sterically hindered compounds are aromatics. Second, the chemical equilibria

existing in cracking reactions favors the production of sterically hindered dibenzothiophenes

over unsubstituted dibenzothiophenes. For example, in LCO, methyl substituted aromatics are

twice as prevalent as unsubstituted aromatics. Di-methyl aromatics are twice as prevalent as

methyl aromatics, or four times more prevalent as unsubstituted aromatics. Generally,

desulfurizing 4-methyl dibenzothiophene using conventional desulfurization is six times slower

than desulfurizing similar non-sterically hindered molecules, while desulfurizing 4,6-dimethyl

dibenzothiophene using conventional desulfurization is 30 times slower. Slower reactions mean

that either the volume of the reactor must be that much larger, or that the reaction must be

somehow speeded up. The latter implies either a more active catalyst, higher temperature, or

higher pressure. These alternatives are discussed below.

Because moderate sulfur reduction is often all that is required in current distillate

hydrotreating, catalysts have been developed that focus almost exclusively on sulfur and other

contaminant removal, such as nitrogen and metals. The most commonly used desulfurization

catalyst consists of a mixture of cobalt and molybdenum (Co/Mo). These catalysts interact

primarily with the sulfur atom and encourage the reaction of sulfur with hydrogen.

Other catalysts have been developed that encourage the saturation (hydrogenation) of the

aromatic rings. As mentioned above, this generally improves the quality of the diesel fuel

produced from this distillate. These catalysts also indirectly encourage the removal of sulfur

from sterically hindered compounds by eliminating one or both of the aromatic rings contained

in dibenzothiophene. Without one or both of the rings, the molecule is much more flexible and

the sulfur atom can reach the catalyst surface unhindered. Thus, the desulfurization rate of

sterically hindered compounds is greatly increased through the hydrogenation route. The most

commonly used hydrogenation/desulfurization catalyst consists of a mixture of nickel and

molybdenum (Ni/Mo).

Several important issues related to using the hydrogenation pathway for desulfurization

should be highlighted. As pointed out above, one or both of the aromatics rings are being

saturated, which significantly increases the consumption of hydrogen. It is important that one of

the aromatic rings of a polyaromatic compound is saturated, as this is the facilitating step

resulting in the desulfurization of a sterically hindered compound. If the mono aromatics

compounds are also saturated, there is only a modest improvement in the desulfurization reaction

rate of the sterically hindered compounds, however, at a large hydrogen cost. In addition, certain

diesel fuel qualities, such as cetane, improve significantly as more of the aromatic compounds
Final Regulatory Impact Analysis

5-12

are saturated. However, the vendors of diesel desulfurization technology explained to us that if

cetane improvement is not a goal, then the most cost-effective path to desulfurize the sterically

hindered compounds is to saturate the polyaromatic compounds to monoaromatic compounds,

but not to saturate the monoaromatic compounds. The vendors tell us that because the

concentration of the monoaromatic compounds is at equilibrium conditions within the reactor,

the monoaromatic compounds are being both saturated and unsaturated, which helps to enable

the desulfurization of these compounds. It also means that the concentration of aromatics can be

controlled by the reaction temperature and pressure.

The vendors also point out a variety of reasons why the cycle length of the catalysts that

catalyze hydrogenation reactions, which likely occur in a second stage, is longer than the first

stage desulfurization catalyst. First, the temperature at which the hydrogenation reactions occur

to saturate the polyaromatic compounds to monoaromatic compounds, but not to saturate the

monaromatic compounds, is significantly lower than the temperature of the first stage. The

lower temperature avoids color change problems and reduces the amount of coke formation on

the hydrogenation catalyst. Furthermore, since the first stage has somewhat “cleaned” the diesel

fuel of contaminants such as sulfur, nitrogen and metals, the catalyst in this second

hydrogenation stage is not degraded as quickly. Because the second stage has a cycle length as

long as or longer than the first stage, adding the second stage is not expected to shorten the cycle

length of the current distillate hydrotreater.

If refiners are “upgrading” their diesel fuel by converting heavy, high aromatic, low cetane,

stocks to 15 ppm sulfur standard, they are intentionally reacting a lot of hydrogen with the diesel

fuel. The hydrogen reactions with the diesel fuel saturates many or most of the aromatics,

increases cetane number and greatly eases the reduction of sulfur. The lower concentration of

aromatics and improved cetane of the upgraded feedstock then allows the product to be sold as

highway diesel fuel. The much higher sales price of the highway diesel fuel compared with the

lower value of the feedstock justifies the much larger consumption in hydrogen and the cost of a

larger reactor.

Up to a certain level of sulfur removal, the CoMo catalyst is generally preferred. It is more

active with respect to desulfurizing non-sterically hindered compounds, which comprise the bulk

of the sulfur in distillate, straight-run or cracked. Below that level, the need to desulfurize

sterically hindered compounds leads to greater interest in NiMo catalysts. Acreon Catalysts had

indicated that NiMo are preferred for deep desulfurization due to this catalyst’s ability to saturate

aromatic rings and make the sulfur atom more accessible to the catalyst. On the other hand,

Haldor-Topsoe has performed studies indicating that CoMo catalysts may still have an advantage

over NiMo catalysts, even at sulfur levels below 50 ppm.13

Two-stage processes may also be preferable to achieve ultra-low sulfur levels. Both stages

could emphasize desulfurization or desulfurization could be emphasized in the first stage and

hydrogenation/desulfurization emphasized in the second stage. In addition to this advantage, the

main advantage of two stages lies in the removal of hydrogen sulfide from the gas phase after the

first stage. Hydrogen sulfide inhibits desulfurization reactions, as discussed further in the next

section. It can also recombine with nonsulfur-containing hydrocarbon compounds at the end of
Fuel Standard Feasibility

5-13

the reactor or even in subsequent piping, effectively adding sulfur to the desulfurized distillate. 

Removing hydrogen sulfide after the first stage reduces the hydrogen sulfide concentration at the

end of the second stage by roughly two orders of magnitude, dramatically reducing both

inhibition and recombination.

In one study, Haldor-Topsoe analyzed a specific desulfurized 50/50 blend of straight run

distillate and LCO at 150 ppm sulfur and found that nearly all the sulfur is contained in sterically

hindered compounds.14 This feed contains more LCO than would be processed in the typical

refinery. A refinery processing less LCO would presumably reach the point where the sulfur

compounds were dominated by sterically hindered compounds at a lower sulfur level. They also

compared the performance of CoMo and NiMo catalysts on a straight run distillate feed at the

same space velocity. The NiMo catalyst performed more poorly than the CoMo catalyst above

200 ppm sulfur, and better below that level. This implies that much of the sulfur left at 200 ppm

(and even above this level) was sterically hindered. These two studies indicate that the amount

of sterically hindered compounds can exceed the 15 ppm sulfur cap by a substantial margin.

In addition to NiMo catalysts, precious metal catalysts are also very effective at desulfurizing 

sterically hindered compounds. An example of a precious metal catalyst is the ASAT catalyst

developed by United Catalysts and Sud-Chemie AG, which uses both platinum and palladium.15

They are most commonly used to more severely dearomatize distillate and increase cetane by

opening up the aromatic rings, a process called ring opening.

5.2.2.2 Meeting a 15 ppm Cap with Distillate Hydrotreating

Using distillate hydrotreating to meet a 15 ppm sulfur cap on diesel fuel has been

commercially demonstrated. Thus, meeting the 15 ppm cap is quite feasible using current

refining technology. Assessing the most reliable and economic means of doing so is more

complicated. Refiners already hydrotreat their highway diesel fuel to meet a 500 ppm sulfur cap. 

These hydrotreaters use a variety of catalysts and have a range of excess capacity. Thus, refiners

are not all starting from the same place. Many refiners will also be producing heating oil, which

must meet only a 5000 ppm cap (lower in some states). The high-sulfur heating oil may, for

example, provide a place to blend the sterically hindered sulfur-containing compounds. Finally,

the amount of cracked stocks that a refiner processes into diesel fuel varies widely. Those with a

greater fraction of LCO will face a more difficult task of meeting a 15 ppm cap than those

processing primarily straight-run distillate.

To understand the types of possible modifications to current distillate hydrotreating to

improve its performance, it is useful to better understand the quantitative relationships between

the various physical and chemical parameters involved in hydrotreating. Haldor-Topsoe has

developed the following algebraic expression to describe the rate of desulfurization via both

direct desulfurization and hydrogenation/desulfurization.
Final Regulatory Impact Analysis

5-14

Rate of = k × Cs

n

 × PH2

a

 + k × Cs

m × PH2b

Desulfurization (1 + KH2S × PH2S) (1 + KF × CF)

Per Catalyst

Surface Area

Where:

k, KH2S and KF are various rate constants, which vary only with temperature.

Cs is the concentration of sulfur in the distillate.

PH2 and PH2S are the partial pressures of hydrogen and hydrogen sulfide in the vapor phase.

KF × CF is the total inhibition due to hydrogen sulfide, ammonia, and aromatics n, m, a, and b

are various constant exponents.

The first term represents the rate of direct desulfurization, such as that catalyzed by CoMo. 

This reaction rate increased by increasing the partial pressure of hydrogen. However, it is

inhibited by increasing concentrations of hydrogen sulfide, which competes with the distillate for

sites on the catalyst surface.

The second term represents the rate of desulfurization via hydrogenation of the aromatic ring

next to the sulfur atom. This rate of desulfurization also increases with higher hydrogen partial

pressure. However, this reaction is inhibited by hydrogen sulfide, ammonia, and aromatics. This

inhibition by aromatics leads to the presence of a thermodynamic equilibrium condition that can

prevent the complete saturation of aromatics. Also, this inhibition makes it more difficult to

desulfurize cracked stocks, which contain high concentrations of both sterically hindered sulfur

compounds and aromatics. While the literature generally expresses a preference for NiMo

catalysts for desulfurizing cracked stocks, Haldor-Topsoe has found situations where this

aromatics inhibition leads them to favor CoMo catalysts even for desulfurizing feeds with a high

concentration of sterically hindered compounds.

These relationships identify the types of changes that could improve the performance of

current distillate hydrotreaters. First, a more active catalyst can be used. This increases the “k”

terms in the above equations. Second, temperature can be increased, which also increases the

“k” terms in the above equations. Third, improvements can often be made in vapor-liquid

contact, which effectively increases the surface area of the catalyst. Fourth, hydrogen purity can

be increased. This increases the hydrogen concentration, which the PH2 term in the two

numerator terms of the equation. Fifth, the concentration of hydrogen sulfide in the recycle

stream can be removed by scrubbing. This decreases the PH2S and CF terms in the two

denominator terms of the equation. Finally, more volume of catalyst can be used, which

increases the surface area proportionally.

Regarding catalysts, at least two firms have announced the development of improved

catalysts since the time that most distillate hydrotreaters were built in the United States to meet

the 1993 500 ppm sulfur cap: Akzo Nobel / Nippon Ketjen Catalysts (Akzo Nobel) and HaldorTopsoe. Akzo Nobel currently markets four CoMo desulfurization catalysts: KF 752, KF 756

and KF 757, which have been available for several years, and KF 848, which was announced in

2000.16 KF 752 can be considered to be typical of an Akzo Nobel catalyst of the 1992-93 time
Fuel Standard Feasibility

5-15

frame, while KF 756 and 757 catalysts represent improvements. Akzo Nobel estimates that

under typical conditions (e.g., 500 ppm sulfur), KF 756 is 25 percent more active than KF 752,

while KF 757 is more than 50 percent more active than KF 752 and 30 percent more active than

KF 756.17 However, under more severe conditions (e.g., <50 ppm sulfur), KF 757 is 35-75

percent more active than KF 756. KF 848 is 15 - 50 percent more active than KF 757. 

Commercial experience exists for both advanced catalysts. KF 756 is widely used in Europe (20

percent of all distillate hydrotreaters operating on January 1, 1998), while KF 757 has been used

in at least three hydrotreaters commercially. KF 757 and KF 842 utilizes what Akzo Nobel calls

STARS technology, Super Type II Active Reaction Sites. Type II refers to a specific kind of

catalyst site that is particularly good at removing sulfur from sterically hindered compounds.

In terms of sulfur removal, Akzo Nobel projects that a desulfurization unit producing 500

ppm sulfur with KF 752 will produce 405, 270 and 160 ppm sulfur with KF 756, KF757, and KF

842, respectively.

In 2001 and 2003, Akzo Nobel announced two new catalysts. In 2001, Akzo announced the

introduction of a highly active catalyst named Nebula, which offers a different way to use

coatings for catalysts. A typical catalyst is composed of two parts: an active coating containing

metals and a generally inactive substrate. For Nebula, Akzo Nobel concentrated the metal

coatings and omitted the substrate. Because of the very high metals content, Nebula costs

several times more than conventional catalysts. The higher activity of the Nebula catalyst leads

to an increased tendency for coking, which must be countered by using a high hydrogen partial

pressure, resulting in a higher hydrogen consumption. (The hydrogen consumption is higher

because a higher percentage of the aromatics are saturated to nonaromatic compounds.) 

According to Akzo Nobel, a refiner may be able to meet the 15 ppm sulfur standard by simply

replacing a part of or all of its existing catalyst with Nebula and providing significantly more

hydrogen (which may possibly require the addition of a hydrogen plant). Nebula may

significantly reduce the capital investment for meeting the 15 ppm sulfur standard. In 2003,

Akzo announced that Nebula was modified somewhat to contain 15 - 20 percent less metals, but

with the same activity as the original Nebula. The updated Nebula catalyst, now called Nebula

20, can better handle heavier feeds.18

 In 2003, Akzo Nobel announced a new catalyst named KF-760. The KF-760 catalyst is a

CoMo catalyst designed for better denitrogenation of diesel fuel, in addition to the

desulfurization being sought after. Where the nitrogen content is inhibiting the desulfurization

of the diesel fuel, this catalyst can have 15 - 20 percent higher activity compared to their

previous best, KF-757, with only a modest increase in hydrogen consumption.19

Haldor-Topsoe has also developed more active catalysts. Its TK-554 catalyst is analogous to

Akzo Nobel’s KF 756 catalyst, while its newer, more active catalyst is termed TK-574. For

example, in pilot plant studies, under conditions where TK-554 produces 400 ppm sulfur in

straight run distillate, TK 574 will produce 280 ppm. Under more severe conditions, TK-554

will produce 60 ppm, while TK 574 will produce 30 ppm. Similar benefits are found with a

mixture of straight-run and cracked stocks. Just this year, Haldor Topsoe announced a new line
Final Regulatory Impact Analysis

5-16

of catalysts named Brim.20 The announcement did not include information about the

improvements of this line of catalysts over its previous catalysts.

UOP projects a similar reduction in sulfur due to an improved catalyst. They estimate that a

hydrotreater producing 500 ppm sulfur distillate today (20 percent LCO, 10 percent light-coker

gas oil) could produce 280 ppm sulfur distillate with a 50 percent more active catalyst.21

Over the last six years, Criterion Catalyst Company announced two new catalyst

technologies. One was called Century, and the other was called Centinel.22 These two lines of

catalysts were reported to be 45 to 70 percent and 80 percent more active, respectively, at

desulfurizing petroleum fuel than conventional catalysts used in the mid-90s. These

improvements have come about primarily through better dispersion of the active metal on the

catalyst substrate. Criterion announced a new line of catalyts in early 2004 named Ascent.23

These catalysts are expected to be at least 20 percent more active than the Centinel line of

catalysts.24 

Axens catalysts, which is associated with IFP, offers three catalysts designed for deep

desulfurization of distillate fuel. One is a CoMo catalyst named HR 406 and it is reported to be

40 percent more active than HR 306, its predecessor. Another catalyst offered by Axens is

named HR 468 and it offers a mixture of CoMo with NiMo metals. The third catalyst offered by

Axens is a NiMo catalyst named HR 448. The NiMo catalyst is recommended for deep

desulfurization at higher pressures, while HR 468 is more recommended for use at lower

pressures.25

This shows that changing to a more active catalyst, by itself, can reduce sulfur significantly. 

Based on the history of the industry, improvements in catalyst performance can be anticipated

over time to result in roughly a 25 percent increase in catalyst activity every four years. Vendors

have informed us that the cost of these advanced catalysts is very modest relative to less active

catalysts. BP-Amoco projects that a 70 percent improvement in catalyst activity could reduce

sulfur from a current hydrotreater meeting a 500 ppm sulfur specification to 30 ppm.26

Acreon/IFP/Procatalyse is not optimistic, however, that a catalyst change alone will enable

refiners to meet this sulfur level.27 Improved catalysts will, however, reduce the reactor size

needed for achieving the target sulfur level compared to a less active catalyst.

The second way to improve the hydrotreating of diesel fuel for deeper desulfurization is to

reduce the concentration of hydrogen sulfide, which reduces the inhibition of the desulfurization

and hydrogenation reactions. Hydrogen sulfide can be removed by chemical scrubbing. HaldorTopsoe indicates that decreasing the concentration of hydrogen sulfide at the inlet to a co-current

reactor by three to six volume percent can decrease the average temperature needed to achieve a

specific sulfur reduction by 15-20o

C, or reduce final sulfur levels by more than two-thirds. UOP

projects that scrubbing hydrogen sulfide from recycled hydrogen can reduce sulfur levels from

roughly 285 to 180 ppm in an existing hydrotreater.

The third type of improvement to current distillate hydrotreating is to improve vapor-liquid

contact. Akzo Nobel estimates that an improved vapor-liquid distributor can reduce the
Fuel Standard Feasibility

5-17

temperature necessary to meet a 50 ppm sulfur level by 10 oC, which would in turn increase

catalyst life and allow an increase in cycle length from 10 to 18 months. Based on the above

data from Haldor-Topsoe, if temperature were maintained, the final sulfur level could be reduced

by 50 percent. Similarly, in testing of an improved vapor-liquid distributor in commercial use,

Haldor-Topsoe found that the new distributor allowed a 30 percent higher-sulfur feed to be

processed at 25o

C lower temperatures, while reducing the sulfur content of the product from 500

to 350 ppm. Maintaining temperature should have allowed an additional reduction in sulfur of

more than two-thirds. Thus, ensuring adequate vapor-liquid contact can have a major impact on

final sulfur levels.

The fourth type of improvement possible is to increase hydrogen partial pressure and/or

purity. As discussed above, this increases the rate of both desulfurization and hydrogenation

reactions. Haldor-Topsoe indicates that increasing hydrogen purity is preferable to a simple

increase in the pressure of the hydrogen feed gas, since the latter will also increase the partial

pressure of hydrogen sulfide later in the process, which inhibits both beneficial reactions. 

Haldor-Topsoe projects that an increase in hydrogen purity of 30 percent lowers the temperature

needed to achieve the same sulfur removal rate by 8 to 9o

C. Alternatively, temperature could be

maintained while increasing the amount of sulfur removed by roughly 40 percent. Hydrogen

purity can be increased through the use of a membrane separation system or a PSA unit. UOP

projects that purifying hydrogen can reduce distillate sulfur from 180 to 140 ppm from an

existing hydrotreater.

The fifth type of improvement is to increase reactor temperature. Haldor-Topsoe has shown

that an increase of 14o

C while processing a mix of straight run distillate and LCO with its

advanced TK-574 CoMo catalyst will reduce sulfur from 120 ppm to 40 ppm.28 UOP projects

that a 20 oF increase in reactor temperature would decrease sulfur from 140 to 120 ppm. The

downside of increased temperature is reduced catalyst life (i.e., the need to change catalyst more

frequently). This increases the cost of catalyst, as well as affects highway diesel fuel production

while the unit is down for the catalyst change. Still, current catalyst life currently ranges from 6

to 60 months, so some refiners could increase temperature and still remain well within the range

of current industry performance. The relationship between temperature and life of a catalyst is a

primary criterion affecting its marketability. Thus, catalyst suppliers generally do not publish

these figures.

Sixth, additional sulfur can be removed by increasing the amount of recycle gas sent to the

inlet of the reactor. However, the effect is relatively small. Haldor-Topsoe indicates that a 50

percent increase in the ratio of total gas/liquid ratio decreases the necessary reactor temperature

only by 6 to 8oC. Or, temperature can be maintained and the final sulfur level reduced by 35 to

45 percent.

Overall, Akzo-Nobel projects that current hydrotreaters can be modified short of a revamp

with a second reactor to achieve 50 ppm sulfur. While this improvement is somewhat greater

than the 50 percent improvement measured by Akzo Nobel at current desulfurization severity, it

indicates that it may be possible to improve current hydrotreaters to produce distillate sulfur

levels in the 50-100 ppm range. Thus, it appears that additional measures would be needed to
Final Regulatory Impact Analysis

5-18

meet a 15 ppm cap. This leads to the seventh means to realize deeper desulfurization, which is

to increase catalyst volume through the addition of a second reactor. UOP projects that doubling

the catalysts volume by adding another reactor would reduce sulfur from 120 to 30 ppm. For

each refinery, refiners would need to examine how much additional sulfur control they would be

able to achieve through measures one through six, and then size this second reactor to achieve

the 15 ppm sulfur cap.

These individual improvements described cannot be simply combined, either additively or

multiplicatively. As mentioned earlier, each existing distillate hydrotreater is unique in its

combination of design, catalyst, feedstock, and operating conditions. While the improvements

described above can be made in many cases, it is not likely that all the improvements mentioned

are applicable to any one unit; the degree of improvement could either be greater than or less

than the benefits indicated.

Some refiners may therefore have to implement one additional technical change listed by

UOP to be able to meet the 15 ppm standard. This last technical change is to add a second stage

to current single-stage 500 ppm hydrotreaters. This second stage would consist of a second

reactor, and a high pressure, hydrogen sulfide scrubber between the first and second reactor. The

compressor would also be upgraded to allow the new second reactor to be operated at a higher

pressure. Assuming use of the most active catalysts available in both reactors, UOP projects that

converting from a one-stage to a two-stage hydrotreater could produce 5 ppm sulfur relative to a

current level of 500 ppm today.

In addition to these major technological options, refiners may have to debottleneck or add

other more minor units to support the new desulfurization unit. These units could include

hydrogen plants, sulfur recovery plants, amine plants and sour water scrubbing facilities. All

these units are already operating in refineries but may have to be expanded or enlarged.

 To assess the degree that these measures would be needed, it is useful to examine the

commercial and pilot plant performance of distillate hydrotreating to achieve very low sulfur

levels.

5.2.2.3 Low-Sulfur Performance of Distillate Hydrotreating

Data from both pilot plant studies and commercial performance are available indicating the

capability of various hydrotreating technologies to reduce distillate sulfur levels to very low

levels. While many reports of existing commercial operations focus on reducing sulfur to meet a

500 ppm sulfur standard, or somewhat below that sulfur level, studies of achieving lower sulfur

levels (e.g., 10 to 50 ppm) are associated with also reducing aromatic content significantly. This

combination is related to the fact that Swedish Class II diesel fuel must meet a tight aromatics

specification in 2005 along with a 10 ppm sulfur standard. Other European diesel fuel must also

meet a 10 ppm sulfur standard.

Another study projected the technology and resulting cost to reduce diesel fuel sulfur to

comply with EPA’s highway 15 ppm sulfur cap standard and sulfur standards on nonhighway
Fuel Standard Feasibility

D Dense loading is a process of packing a certain volume of catalyst into a smaller space than conventional

catalyst loading.

5-19

distillate . The Engine Manufacturers Association retained Mathpro for this study. The

projections of this study are discussed in Chapter 7. The discussion in this chapter will focus on

the available pilot plant and commercial data demonstrating the achievement of low sulfur

levels. It is worth noting that until the 15 ppm standard was established for highway diesel fuel

in the United States and the announcements by the German government to seek sulfur levels as

low as 10 ppm, there had been little effort by industry to develop technology capable of such a

level across the diesel pool. Recent advances by catalyst manufacturers demonstrating the

feasibility of producing diesel fuel meeting these levels through pilot plant testing and some

commercial demonstrations should be considered a first-generation of technology, with new and

continual advances expected over time.

As of mid 2003, Criterion Centinel and SynCatTM catalysts were installed in 37 deep

desulfurization units in operation in the World, including 13 Syn Technology Units. While the

purpose for each unit is to desulfurize distillate to 50 ppm or below, eight of them served as a

first stage of a two stage dearomatization type unit where ULSD was capable of being produced. 

(Lummus’ licensed SynTechnology). 

The other 24 hydroprocessing units operating with Criterion’s Centinel’s catalysts are

desulfurizing distillate down to under 50 ppm sulfur, with 6 of these consistently under 15 ppm. 

IFP, using Axens catalysts, offers its Prime D technology for deep desulfurization,

aromatics saturation and cetane improvement.29 Using a NiMo catalyst, IFP’s Prime D process

can produce distillate sulfur levels of 10 ppm from straight run distillate and of less than 20 ppm

from distillate containing 20 to 100 percent cracked material using a single-stage reactor. With a

two-stage process, less than one ppm sulfur can be achieved.

United Catalysts and Sud-Chemie AG have published data on the performance of their

ASAT catalyst, which uses platinum and palladium.30 The focus of their study was to reduce

aromatics to less than 10 volume percent starting with a feed distillate containing up to 500 ppm

sulfur and at least 100 ppm nitrogen. Starting with a feed distillate containing 400 ppm sulfur

and 127 ppm nitrogen and 42.5 volume percent aromatics, the ASAT catalyst was able to reduce

sulfur to eight to nine ppm, nearly eliminate nitrogen, and reduce aromatics to two to five

volume percent. Hydrogen consumption was 800 to 971 standard cubic feet per barrel (SCFB).

Akzo Nobel has summarized the commercial experience of about a year’s worth of

operations of their STARS catalyst for desulfurizing diesel fuel at the BP-Amoco refinery in

Grangemouth, UK.31 The original unit was designed to produce 35,000 barrels per day of diesel

fuel at 500 ppm treating mostly straight-run material, but some LCO was treated as well. Akzo

Nobel’s newest and best catalyst (KF 757 at that time) was dense-loaded into the reactor to

produce 45,000 barrels per day diesel fuel at 10-20 ppm (to meet the 50 ppm standard).D From

the data, it was clear to see that as the space velocity changed, the sulfur level changed inversely
Final Regulatory Impact Analysis

5-20

proportional to the change in space velocity. Usually when the space velocity dipped below 1.0,

the sulfur level dropped below 10 ppm. At that refinery, however, it was not necessary to

maintain the sulfur level below 10 ppm.

Akzo Nobel also has its STARS catalysts operating in four other units in Europe and the

Middle East, three of which are producing diesel fuel with less than 10 ppm sulfur, and another

unit producing diesel fuel with less than 20 ppm sulfur. Three of these units process a blend of

light and heavy straight run feeds, while the other is processing a stream which is predominantly

comprised of cracked stocks. Additionally, Akzo Nobel is demonstrating its Nebula catalysts 

commercially in three different applications in Europe producing diesel fuel ranging from 5 ppm

to 50 ppm. One of those is for treating cracked stocks in addition to straight run, and the refinery

is meeting a 10 ppm standard at 650 psi partial pressure. 

Haldor Topsoe has their catalysts in 27 units worldwide, either as standalone

desulfurization units or the first stage of a desulfurization and dearomatization unit, producing

diesel fuel to under 50 ppm sulfur. While most of these are in Europe, some are also in the U.S. 

Of these, 17 are producing diesel fuel to under 10 ppm sulfur; some of these have cracked stocks

while others do not. 

Based on all this laboratory and real world experience, it is clearly feasible to produce

diesel fuel with a sulfur level of 15 ppm or less even if the feedstocks contain a great deal of

cracked stocks. The challenge refiners will face is how to minimize the cost of doing so. To

minimize costs, refiners will have to figure out how to apply the desulfurization/hydrogenation

methods on their own diesel fuels. The specifics, and thus the economics, of accomplishing this

depends on the amount of cracked stocks that the refiner blends into diesel fuel. A few refiners

have the possibility of shifting some of the sterically hindered compounds to fuels complying

with less stringent sulfur standards, such as heating oil. However, our analysis of the feasibility

of desulfurization technology did not consider the occurrence of feedstock shifting as necessary

for refiners to meet the diesel sulfur standards.

5.2.3 Process Dynamics Isotherming

In the late 1990s, a professor at the University of Arkansas applied some ingenuity in

reaction chemistry to diesel desulfurization. After conceiving of this process, he started a

company named Process Dynamics. The reaction technology reacts diesel fuel with hydrogen,

which is totally dissolved in the diesel fuel, in a plug flow reactor. Since the hydrogen gas is

dissolved into the diesel fuel, the reactor needs to be designed only to handle a liquid, instead of

the two phase reactors designed for conventional hydrotreating. Because only about 75 standard

cubic feet of hydrogen can be dissolved into each barrel of diesel fuel and the hydrogen

consumption for a particular desulfurization step can be much higher than that, this technology

cannot be a once-through process. Process Dynamics solved that limitation by recycling the feed

after a very short residence time in the reactor to recharge the liquid with more hydrogen and to

mix this recycle with some untreated diesel fuel before sending it to the reactor. Thus, the

recycled partially desulfurized diesel fuel acts like a diluent to the fresh feed controlling the

hydrogen consumption, and the diesel fuel is recharged with hydrogen and sent to the reactor to
Fuel Standard Feasibility

5-21

be desulfurized several times as it is being treated.32 33

The Process Dynamics Isotherming process has some apparent advantages over

conventional desulfurization. First, since the hydrogen is already in the liquid phase, the

hydrotreating reaction can occur much more quickly, because, as described by Process

Dynamics, the kinetics of conventional hydrotreating are mass transfer-limited, which is the rate

at which gaseous hydrogen can transfer into the liquid phase. Process Dynamics makes this

point by the following reaction equations for hydrotreating diesel fuel:34 

rg = kg (PH2 - P×H2) (rate of hydrogen mass transfer into the liquid phase)

Where: 

rg = transfer rate of hydrogen gas into diesel fuel.

kg = hydrogen gas mass transfer rate.

PH2 = Partial pressure of hydrogen in the gas phase.

P×H2 = Partial pressure of hydrogen at the catalyst.

and

rs = ks T[S][P×H2] (rate of desulfurization at the catalyst site)

Where:

rs = rate of reaction of sulfur.

ks = reaction rate constant for sulfur removal.

P×H2 = partial pressure of hydrogen at the catalyst.

T = temperature in degrees absolute.

[S] = concentration of sulfur.

If the desulfurization rate of reaction (rs) is much slower than the rate at which hydrogen

can dissolve into diesel fuel (rg), then there would probably not be any benefit for the Process

Dynamics Isotherming process. However, according to Process Dynamics, the rate of reaction

for desulfurization is faster than the rate of mass transfer, thus, the rate of reaction for diesel

hydrotreating is limited by the mass transfer of hydrogen into diesel fuel. Thus, the Process

Dynamics process increases the rate of reaction by dissolving the hydrogen needed for the

reaction into the liquid phase before sending this liquid to the reactor. The faster rate of reaction

is indicated by the fact that the Process Dynamics desulfurization process, desulfurize an

unhydrotreated distillate comprised of a typical mix of distillate blendstocks down to about 500

ppm at a space velocity of 8 hour-1. Conversely, conventional hydrotreating requires a space

velocity of about 2 hour-1 to accomplish the same task. However, as you go lower and lower in

sulfur levels, the rate of reaction slows due to the increased concentration of sterically hindered

compounds. When the rate of reaction for desulfurization gets slower than the mass transfer rate,

the Process Dynamics process loses its advantage over conventional hydrotreating. Therefore,

the Process Dynamics process can be used in conjunction with conventional hydrotreating to

desulfurize diesel fuel to the 15 ppm standard. The Process Dynamics unit would be inserted

before the conventional hydrotreater to treat untreated distillate fuel down to 500 ppm and the

conventional hydroteater would then handle the desulfurization duty from 500 ppm to 15 ppm.
Final Regulatory Impact Analysis

5-22

There are a two important benefits to the Process Dynamics process because it has a

higher space velocity. One benefit is that the Process Dynamics process requires a smaller

amount of catalyst. By definition, if the same volume of feed can be treated faster than another

process, the amount of catalyst needed is proportionally lower by the inverse proportion of the

space velocity. The second advantage of having a faster space velocity is that the reactors are

sized much smaller to hold the lower volume of catalyst. Both of these benefits result in lower

costs for the Process Dynamics Isotherming deslfurization process. The lower catalyst volume

required by Process Dynamics Isotherming costs proportionally less because the Process

Dynamics desulfurization process uses the same catalysts as conventional hydrotreating. 

Similarly, the smaller reactor volume reduces the capital costs, although in this case the cost

reduction is not necessarily proportionally less as smaller reactors have a poorer economy of

scale compared with larger reactors.

The Process Dynamics engineers point out that the Isotherming process also has other

benefits over conventional hydrotreating. When some of the aromatics in diesel fuel are

saturated during the desulfurization process, heat is generated. In the case of conventional

hydrotreating, much of this heat is intentionally quenched away in an attempt to avoid excessive

temperature excursions. Excessive temperature excursions and local low hydrogen

concentration can lead to coking, which is a constant problem with conventional hydrotreating. 

However, the higher space velocity of the Process Dynamics process coupled with the fact that

the feed is diluted by the recycle stream allows for better control of the process temperature. 

Furthermore, the ready availability of hydrogen in the liquid phase along with the better

temperature control prevents most of the coking from occurring. Thus, the internally generated

heat can be conserved, instead of being quenched away, and used to heat the process. The

conserved heat means that little to no external heating is required, which provides a savings in

natural gas consumption relative to conventional hydrotreating. However, a small heater is still

needed to heat the feed during start-up.

Another advantage of the Process Dynamics desulfurization process is that it does not

need a hydrogen gas recycle compressor. Because the hydrogen pumped into solution and going

to the reactor is either used up or remains in solution, there is no residual hydrogen gas to

recycle. Compressors operating at the pressures that diesel fuel desulfurization occurs are

expensive, long leadtime delivery items. Thus, by omitting the recycle gas compressor and using

smaller reactors, the Process Dynamics desulfurization process not only saves substantial capital

costs compared with conventional hydrotreating, but it also means a somewhat shorter

construction time. The smaller reactors and heater coupled with the fact that a recycle gas

compressor is not needed means that the Process Dynamics process requires a smaller footprint

compared with conventional hydrotreating, facilitating the installation of the Process Dynamics

unit in today’s refineries which are often space-limited.

While aspects of the Process Dynamics Isotherming desulfurization process for diesel

fuel desulfurization are novel compared with conventional diesel desulfurization, many aspects

of the process are the same. Much of the list of required equipment is the same for the Process

Dynamics process as for conventional hydrotreating. Table 5.2-1 shows both the similarities and

differences between the two.
Fuel Standard Feasibility

5-23

Table 5.2-1

Major Equipment Needed for Process Dynamics Isotherming and Conventional Hydrotreating

Process Dynamics Isotherming Conventional Hydrotreating

Heat Exchangers Yes Yes

Heater Yes (small and for startup only) Yes

Hydrogen gas compressor Yes Yes (for hydrogen makeup)

Mixers for dissolving hydrogen into

the diesel fuel

Yes No

Reactor (s) Yes (2 - 4 small plug flow) Yes (1 - 2 large trickle bed)

Reactor distributor No Yes

High-pressure flash drum and

hydrogen separator

Yes Yes

Low-pressure separator Yes Yes

Recycle hydrogen compressor No Yes

Recycle hydrogen gas scrubber No Yes

Process Dynamics has accumulated some data on the Isotherming desulfurization process

from testing they have done with their pilot plant. Process Dynamics started up a pilot plant in

late 2001. Recently, Process Dynamics installed a commercial demonstration unit of their

technology at a Giant refinery as a revamp to an existing highway hydrotreater to demonstrate

compliance with the highway diesel fuel 15 ppm sulfur standard, which begins in mid 2006. The

unit was started up in September of 2002 and the Process Dynamics engineers have been

working with the refinery engineers to optimize the unit for the refinery. Since early 2003, the

Process Dynamics demonstration unit has consistently been producing diesel fuel under 15 ppm.

After successful demonstration of its technology at the Giant refinery, Process Dynamics

is working on signing license agreements for the Process Dynamics desulfurization process. In

early 2004, Process Dynamics was working on signing four additional license agreements here in

the U.S.35 

5.2.4 Phillips S-Zorb Sulfur Adsorption 

A prospective diesel desulfurization process was announced by Phillips Petroleum in late

2001.36 This process is an extension of their S-Zorb process for gasoline and thus is called SZorb for diesel fuel. The process is very different from conventional diesel fuel hydrotreating in

which reacts the sulfur with hydrogen over a catalyst to form H2S. The S-Zorb process adsorbs

the sulfur molecule, still attached to the hydrocarbon, onto a sorbent at a pressure of 275 to 500

pounds per square inch gauge (psig) and at a temperature of 700 to 800/ F and in the presence of

hydrogen in the S-Zorb reactor. The catalyst activity of the sorbent next cleaves the sulfur atom
Final Regulatory Impact Analysis

E

 Starting this year, many refiners will be starting up their gasoline desulfurization units for complying with the

30 ppm Tier 2 gasoline sulfur standard, which phases in from 2004 to 2006. 

5-24

from the sulfur-containing hydrocarbon. To prevent the accumulation of sulfur on the catalyst,

the sulfur containing sorbent is continually removed from the reactor. The removed sorbent is

moved over to a receiving vessel by an inert lift gas, at which point the lift gas and the entrained

diesel fuel is removed from the sorbent. The sorbent next drops down into a lockhopper that

facilitates the movement of the sorbent to the regenerator. In the regeneration vessel, the sulfur

is burned off of the sorbent with oxygen and the generated SO2 is sent to the sulfur plant. The

regenerated sorbent then drops down into a reducer vessel where the sorbent is returned back to

its active state. The sorbent is then recycled back to the reactor for removing more sulfur. 

Because the catalyst is continuously being regenerated, Phillips estimates that the unit will be

able to operate four to five years between shutdowns. Because untreated distillate can contain

several percent sulfur, Phillips believes that its S-Zorb process for diesel could be overwhelmed

by the amount of sulfur adsorbing onto the catalyst. Thus, the S-Zorb process may not be able to

economically treat all untreated distillate streams that are high in sulfur, and is best suited to treat

distillate containing 500 ppm sulfur or less. However, some refiners running sweet crudes and

producing low-sulfur non-highway diesel volumes (from straight-run diesel and hydrocrackate

diesel) may have lower uncontrolled nonhighway sulfur levels. These refiners may be able to

use the S-Zorb process to lower their nonhighway diesel sulfur.

Phillips’ S-Zorb diesel desulfurization process has been demonstrated in a pilot plant that

started up in early 2002. This pilot plant has provided Phillips data on how the unit will process

varying formulations of diesel fuel or diesel fuel blendstocks. The pilot plant testing data

released by Phillips has shown that diesel fuels blended with LCO can be desulfurized below 5

ppm. Phillips has also shown that straight-run diesel fuel can be desulfurized below measurable

levels and a 100 percent LCO stream can be desulfurized down to 10 ppm.

While the S-Zorb diesel desulfurization process has not been demonstrated commercially,

Phillips has demonstrated the S-Zorb technology for desulfurizing gasoline. An S-Zorb gasoline

desulfurization unit started up at Phillips’ Borger refinery in April of 2001. According to

Phillips, their gasoline desulfurization unit has operated as designed for the past three years. The

successful demonstration of their gasoline desulfurization unit at Borger has interested many

refiners in using S-Zorb gasoline desulfurization process for complying with the Tier 2 gasoline

sulfur program.E

 Phillips shared with us in late 2003 that they have licensed their S-Zorb for

gasoline processing for installation in 23 refineries in North America. That the Borger S-Zorb

gasoline desulfurization unit has operated as designed and that there are 23 new S-Zorb gasoline

units planned to start up demonstrates that there is agreement within the refining industry that the

S-Zorb process works.

Most refiners, however, are very conservative and will not be willing to rely only on pilot

plant testing or demonstration of a technology for another fuel as the basis for purchasing a

desulfurization unit that costs tens of millions of dollars. They will want to see a particular

technology operating as a commercial unit for desulfurizing diesel fuel for at least two years
Fuel Standard Feasibility

5-25

before trusting that the technology is reliable. However, Phillips is not planning to install a

commercial demonstration unit of its S-Zorb diesel fuel desulfurization process, nor is Phillips

planning on installing an S-Zorb for diesel unit for complying with the 15 ppm sulfur highway

diesel fuel standard, which begins to take effect in mid-2006, in any of its refineries.37

Consequently, even though S Zorb for diesel may be capable of desulfurizing diesel fuel to less

than 15 ppm sulfur, it does not appear that it will factor into the mix of technologies used to meet

the NRLM 15 ppm diesel fuel standards.

5.2.5 Chemical Oxidation and Extraction

Another desulfurization technology being developed by Unipure and UOP is based on

chemical oxidation. For these companies, the chemical oxidation desulfurization of diesel fuel is

accomplished by first forming a water emulsion with the diesel fuel. In the emulsion, the sulfur

atom is oxidized to a sulfone using a strong oxidizing agent, such as catalyzed peroxyacetic acid. 

With an oxygen atom attached to the sulfur atom, the sulfur-containing hydrocarbon molecules

become polar and hydrophilic and then move into the aqueous phase. These sulfone compounds

can either be desulfurized or perhaps be converted to a surfactant that could be sold to the soap

industry at an economically desirable price. The earnings made from the sales of the surfactant

could offset much of the cost of oxidative desulfurization.

Unipure has set up a 50 barrel per day pilot plant which started operating in the spring of 

2003. UOP is still developing its oxidation technology in the lab. Neither of these oxidation

processes are available for licensing at this time.

Late in the 1990s, Petrostar had started the development of an oxidation process for

desulfurizing diesel fuel. This oxidation technology was similar to that of Unipure’s. However,

sometime in the last year Petrostar abandoned its work on that technology. Early in 2003,

Lyondell-Citgo announced that they had recently developed a chemical oxidation desulfurization

technology. This process is similar in some ways to Unipure's and Petrostar's oxidation

processes, but also different in some pronounced ways. The differences are that instead of the

using expensive peroxyacetic acid to create sulfones, this process uses t-butyl hydroperoxide

oxidant to convert sulfur species in diesel to sulfones (this eliminates the need to recycle a cooxidant acid). T- butyl hydroperoxide is not as corrosive as peroxyacetic acid, thus Lyondell’s

process is projected to be constructed from less expensive metallurgy. Lyondell has pilot plant

success desulfurizing 500 ppm diesel fuel to less than 10 ppm, but abandoned further

development of this technology in late 2003.

The best opportunity for oxidation and extraction technologies to penetrate the

desulfurization market my lie with smaller refineries and terminals. Terminals may find that it is

cheaper to implement some sort of desulfurization technology to handle the overproduction of

off spec downgrade and interface than it would be to ship it off to the nearest entity equipped to

distill and hydrotreat this material. Many small refineries and terminals don’t have access to a

cheap source of hydrogen and may not have sulfur plants, so having a technology which can treat

their distillate material without the need to install grassroots hydrogen units and sulfur plants

could make the costs associated with desulfurization reasonable to them. 
Final Regulatory Impact Analysis

5-26

5.2.6 FCC Feed Hydrotreating

As described earlier in this section, sulfur can be removed from distillate material early

or late in the refining process. Early in the process, the most practical place to remove sulfur is

before the FCC unit. The FCC unit primarily produces gasoline, but it also produces a

significant quantity of LCO which makes up 23% of diesel fuel supply in the U.S.

Many refineries already have an FCC feed hydrotreating unit. The LCO from these

refineries should contain a much lower concentration of sulfur and fewer sterically hindered

compounds than refineries not hydrotreating their FCC feed. Adding an FCC feed hydrotreating

is much more costly than distillate hydrotreating. Just on the basis of sulfur removal, FCC feed

hydrotreating is more costly than distillate hydrotreating, even considering the need to reduce

gasoline sulfur concentrations, as well. This is partly due to the fact that FCC feed hydrotreating

by itself is generally not capable of reducing the level of diesel fuel sulfur to those being

considered in this rule, so post-treating is still necessary. However, FCC feed hydrotreating

provides other environmental and economic benefits. FCC feed hydrotreating decreases the

sulfur content of gasoline significantly, as well as reducing sulfur oxide emissions from the FCC

unit. It also increases the yield of relatively high value gasoline and LPG from the FCC unit and

reduces the formation of coke on the FCC catalyst. For individual refiners, these additional

benefits may offset enough of the cost of FCC hydrotreating to make it more economical than

distillate hydrotreating. However, these benefits are difficult to estimate in a nationwide study

such as this. Also, feed hydrotreating is not expected to, by itself, enable a refinery to meet

either the 500 or the 15 ppm standards. Thus, this study will rely on distillate hydrotreating as

the primary means with which refiners will meet the 15 ppm sulfur cap. For those refiners that

choose FCC feed hydrotreating, their costs will presumably be lower than distillate hydrotreating

and the costs estimated in Chapter 7 can then be considered somewhat conservative in this

respect.

5.3 Feasibility of Producing 500 ppm Sulfur NRLM Diesel Fuel in 2007

5.3.1 Expected use of Desulfurization Technologies for 2007

To enable our determination of whether it is feasible for the refining industry to meet the

2007 sulfur cap and to estimate the cost of complying with the sulfur standard (see Chapter 7),

we needed to project the mix of available technologies that will be used for compliance. We

considered several different factors for projecting the mix of technologies. First and foremost,

we considered the time refiners will have to choose a new technology, which is important

because of the relatively short lead time before implementation of the 500 ppm standard. 

Second, we considered whether the technology will be available for 2007 and, if the technology

is available, how proven it is. Third, we considered whether the technology is cost-competitive

by comparing it with other technologies. If a refiner finds that a technology is available at a

lower cost, it is more likely to use that technology. We also considered whether the technology

is available from a vendor that has proven itself to the industry by providing other successful

refining technologies and particularly if the vendor has proven itself in the United States. 
Fuel Standard Feasibility

F

 Refiners want low-maintenance refining units because they have cut back their engineering staff to reduce

their refining costs for improving their margins, and thus will seek units consistent with that strategy.

5-27

Finally, we considered the capability of the vendor to meet the demand of the industry. We

considered all these issues for each technology but, as described below, some of these issues are

more prominent than others.

To comply with the 500 ppm sulfur standard in 2007, refiners will have to decide what

technology they will want to use several years before the standard needs to be met. Several

years are needed to perform a preliminary design, complete a detailed design, purchase the

hardware needed, obtain the air quality permits needed, and then install and start up the

hardware. The timing of this final rule provides refiners three full years to comply with the 500

ppm sulfur standard. Because refiners need about three years to complete the mentioned steps to

have a working new unit, there is little time to shop around for a new desulfurization technology

that is just beginning to prove itself. A thorough review of a newer technology can take months,

so if refiners do not have this extra time, they will tend toward technologies that are more

familiar. See Section 5.3.2 for a more detailed discussion about the lead-time issues for the 2007

standard.

Of the various technologies we list above for desulfurizing diesel fuel, conventional

hydrotreating is by far the most familiar to refiners. Refiners are using conventional

hydrotreating to meet the current highway diesel fuel 500 ppm sulfur standard. In the United

States, there are about 90 distillate hydrotreaters with virtually all of them being conventional

hydrotreaters operating since 1993 or before. The one exception is a Process Dynamics

Isotherming commercial demonstration unit that started up recently at a Giant refinery in New

Mexico. Phillips S-Zorb for diesel and the two oxidation and extraction technologies have yet to

accumulate commercial experience. However, refiners usually want to see that a refinery unit

has operated successfully for at least two years to ensure that it will operate with high reliability

and low maintenance requirements.F

 The Process Dynamics desulfurization unit that is installed

now and has started to accrue valuable commercial experience will have accumulated somewhat

less than two years of commercial experience by then.

After considering the above issues, it seems that the short lead time is the central issue of

whether refiners will choose between conventional hydrotreating and other advanced

desulfurization technologies for 2007. Refiners do not have the many months needed to

carefully consider the advanced technologies still in development and still at the beginning of the

demonstration stage, so we believe this issue is the most critical one affecting refiners’ choice of

desulfurization technologies for 2007. For these reasons, we believe refiners will default to what

they know will work, which is conventional desulfurization. Since multiple vendors can provide

the preliminary engineering design and any followup support for conventional hydrotreating,

these vendors will be able to serve the refiners needing to install desulfurization units for 2007.
Final Regulatory Impact Analysis

G Without the small-refiner provisions, an additional 20 refineries would have to produce 500 ppm NRLM fuel

by June 1, 2007.

H Final Regulatory Impact Analysis, Control of Air Pollution from New Motor Vehicles: Tier 2 Motor Vehicle

Emissions Standards and Gasoline Sulfur Control Requirements, U.S. EPA, December 1999. 

I

 “Highway Diesel Progress Review,” U.S. EPA, June 2002, EPA420-R-02-016.

5-28

5.3.2 Lead-time Evaluation

Refiners need sufficient lead time to design, construct, and start up desulfurization

technology to meet the 500 ppm standard if this standard is to be implemented in an orderly way. 

If one or more refiners were unable to comply in time, it would have major repercussions for the

refiner and potentially for the regional fuel supply. If refiners planning on producing 500 ppm

NRLM fuel could not do so in time and could not buy credits, they would have to sell their highsulfur distillate fuel as heating oil, export it, or temporarily cease production. As discussed in

Section 5.8, heating oil will no longer be widely distributed in many markets. Thus, selling large

quantities of heating oil may require distressed pricing and the absorption of trucking costs. 

Exportation would be very costly for refiners not located on an ocean coastline. Temporary

closure would result in serious financial loss. In addition, users of NRLM diesel fuel would

likely face high fuel prices. Fuel prices respond quickly to supply shortages. Significant price

increases would be expected if refiners were not able to fulfill demand for NRLM diesel fuel

starting June 1, 2007. Thus, providing adequate lead time for refiners to design, construct, and

prove out the necessary new hydrotreaters is critical to avoiding serious economic harm to both

the refiners and the users of NRLM diesel fuel.

Because of this, we project that refiners will use conventional hydrotreating to meet the

500 ppm standard beginning on June 1, 2007. Of the 35 refineries projected to produce 500 ppm

NRLM diesel fuel beginning in 2007, 8 are projected to do so by using recently idled highway

diesel fuel hydrotreaters. These refineries are expected to idle their highway hydrotreaters in

response to exiting the highway market or by installing a new grassroots diesel fuel hydrotreater. 

The remaining 27 refineries would need to design and construct a new hydrotreater to produce

500 ppm NRLM fuel.G This is roughly 20 percent of all U.S. refineries currently producing

transportation fuels. Thus, the time available between the date of the final rule and June 1, 2007

must be sufficient across a wide spectrum of refiners and situations.

We have conducted two lead-time assessments for the refining industry in the past four

years. One assessment supported the Tier 2 gasoline sulfur program.H The other assessment was

part of our review of progress being made towards compliance with the 15 ppm sulfur standard

for the highway diesel fuel program.I

 The results of both of these assessments are reviewed

below and then applied to the new NRLM sulfur control program.
Fuel Standard Feasibility

5-29

5.3.2.1 Tier 2 Gasoline Sulfur Program

Chapter IV of the Final Regulatory Impact Analysis for the Tier 2 gasoline sulfur

program presented the following table containing the results of its lead-time assessment.

Table 5.3-1

Lead-time Projections Under the Tier 2 Gasoline Sulfur Program (years)

Project Stage

Naphtha/Gasoline Hydrotreating More Major Refinery Modification (e.g., FCC

Feed Hydrotreating)

Time for

Individual Step

Cumulative

Timea

Time for Individual Step Cumulative Timea

Scoping Studies 0.5-1.0b 0.5 0.5-1.0b 0.5

Process Design 0.5 1.0 0.5-0.75 1.0-1.25

Permitting 0.25-1.0 1.25-2.0 0.25-1.0 1.25-2.0

Detailed Engineering 0.5-0.75 1.5-2.25 0.5-1.0 1.5-2.25

Field Construction 0.75-1.0 2.0-3.0 1.0-1.5 2.5-3.5

Start-up/Shakedown 0.25 2.25-3.25 0.25 2.75-3.75

a

 Several of the steps shown can overlap.

b

 Projected to begin before Tier 2 gasoline final rule.

This table contains lead-time projections for two distinctly different approaches to

gasoline sulfur control. The first, naphtha hydtrotreating, is more closely related to conventional

distillate hydrotreating. In fact, several naphtha hydrotreating processes utilize fixed-bed

hydrotreating, which is directly comparable to distillate hydrotreating. The second, FCC feed

hydrotreating, is more complex, extensive, and costly. As discussed earlier in this chapter, some

refiners might use FCC feed hydrotreating to facilitate the production of 500 ppm diesel fuel. 

However, this decision was likely tied to their compliance plans for the Tier 2 gasoline sulfur

program, since FCC feed hydrotreating significantly reduces the sulfur content of gasoline, as

well as moderately reducing the sulfur content of LCO. Since refiners will not be able to meet

the sulfur standard using FCC feed hydrotreating, it is highly unlikely that a refiner would just

begin considering FCC feed hydrotreating as the result of this NRLM rule. We will therefore

focus only on the portion of the table that addresses the lead time for naphtha hydrotreating.

It should also be noted that the cumulative times listed in the table above are not simply

the sum of the times for each step. Some steps overlap, in particular process design and

permitting, permitting and detailed engineering, and detailed engineering and construction. The

relationship between the time necessary for each step in the design and construction of naphtha

and distillate hydrotreaters are examined in detail below. However, it is useful first to review the

projected lead time related to the 15 ppm highway diesel fuel cap.
Final Regulatory Impact Analysis

5-30

5.3.2.2 15 ppm Highway Diesel Fuel Sulfur Cap

The rulemaking implementing the 15 ppm sulfur cap for highway diesel fuel did not

evaluate the lead time required for each individual step of the process. That rule provided 5.5

years of lead time between promulgation and initial implementation. This amount of lead time

significantly exceeded that considered necessary to design and construct desulfurization

equipment. This amount of lead time was provided, since the timing of the 15 ppm sulfur cap

was set primarily by the availability of highly efficient aftertreatment technology for diesel

engines and not on refiners’ ability to meet the 15 ppm standard.

We reviewed the progress that refiners were making towards complying with the 15 ppm

highway diesel fuel cap in 2002. Part of this review included an assessment of the tasks refiners

had already completed and the length of time needed for those still remaining. The tasks

considered were generally the same as those listed in Table 5.3-1 above, with one exception. 

That was the inclusion of the need to develop a corporate strategy towards compliance in the

initial step. This strategy involved a decision regarding the degree to which refiners would

continue marketing highway diesel fuel and if so, whether they would comply with the 15 ppm

standard initially in 2006 or later in 2010. However, diesel fuel can be sold to the highway or

non-highway markets, involving compliance with very different sulfur standards. The flexibility

afforded by the rule’s temporary compliance option also gave refiners a choice of when they

chose to comply with the 15 ppm cap. This issue didn’t arise in the Tier 2 gasoline rule, since

nearly all gasoline sold in the United States meets highway quality standards and refiners have

no other market for their gasoline feedstocks.

The results of the lead-time review are presented in Table 5.3-2.

Table 5.3-2

Lead-time Assessment: Progress Review of 15 ppm Highway Diesel Fuel Cap

Project Stage Time Allotted Latest Start Date

Strategic Planning 0.25-2 years ----------

Planning and Front-End Engineeringa 0.5 Mid-2003

Detailed Engineering and Permits 1.0 Late 2003 - Early 2004

Procurement and Construction 1.25-2.5 October 2004

Commissioning and Start-Up 0.25-0.5 March 2006

a

 Labeled Process Design in Table 5.3-1.

By grouping several of the process steps shown in Table 5.3-1 this later assessment

reduces the overlap between the various steps considerably. The primary overlap still remaining

is between detailed engineering and permits and procurement and construction. While

construction cannot begin until permits have been obtained, procurement can proceed. This is

often essential to any time constrained refining project, due to the long lead times needed to
Fuel Standard Feasibility

5-31

fabricate specialized equipment.

Because the progress review was conducted more than a year after the rule was adopted,

we did not add up the times associated with each step to develop a range of cumulative time

requirements. Instead, we focused on the dates by which refiners should have begun each step to

determine if they had indeed begun those steps that should have been started by the date of the

assessment.

5.3.2.3 Lead-time Projections for Production of 500 ppm NRLM Diesel Fuel

We utilized the information for gasoline and highway diesel analyses to project the lead

time necessary for a wide spectrum of refiners to start producing 500 ppm NRLM diesel fuel. 

Beginning with strategic planning, refiners currently producing high-sulfur diesel fuel/heating oil

will have to decide whether they are going to continue producing high-sulfur heating oil or

produce 500 ppm NRLM diesel fuel. This would not likely be a difficult choice for many

refiners, as the heating oil market will be too small in their area to support their entire production

of high-sulfur fuel. For those with a real choice, this step will likely involve discussions between

the refining and marketing divisions of the firm, as well as with any common carrier pipelines

used by the refiner. While many refiners prefer to be able to observe their competition’s choices

and the relative production volumes and prices of 500 ppm NRLM diesel fuel and high-sulfur

heating oil before making a decision, this is not possible. Given this, it seems reasonable to

allow a relatively short period of time, such as three to six months, to arrive at a corporate

decision to participate either in the NRLM or heating oil markets.

Scoping and screening studies refer to the process whereby refiners investigate various

approaches to sulfur control. These studies involve discussions with firms supplying

desulfurization and other refining technology, as well as studies by the refiner to assess the

economic impacts of various approaches to meeting the sulfur standard. In the case of distillate

desulfurization, refiners will likely send samples of their various distillate streams to the firms

marketing desulfurization technology to determine how well each catalyst and associated

hydrotreating technology removes the sulfur from that particular type of distillate (e.g., sulfur

removal efficiency, yield loss, hydrogen consumption, etc.).

Under the Tier 2 rule, we projected that six to twelve months were required to evaluate

the various available technologies for naphtha desulfurization. This extensive period of time was

considered appropriate due to the wide range of technologies available. More importantly,

however, was the fact that many of the new gasoline desulfurization technologies had not been

demonstrated in actual refinery applications by the time of the final rule. Refiners naturally

desire as much demonstrated experience with any new technology as possible before investing

significant amounts of capital in these technologies. We believed that at a minimum, refiners

should have six months after the final rule to assess their situation with respect to the final sulfur

control program and select their vendor and technology. Because the Tier 2 gasoline sulfur

standards phased in over two years, some refiners had more time than others before their new

desulfurization equipment had to be operational. Thus, we expected refiners to take as much

time as they could afford to select the particular desulfurization technology that was optimum for
Final Regulatory Impact Analysis

J

 Many of these issues are uncertainties for refiners installing a new diesel fuel hydrotreater, but would be fixed

for those adapting an existing desulfurization unit or reactor.

5-32

their situation. Thus, there was really no upper limit to the amount of time for this step.

The scoping and screening task refiners face with respect to the 500 ppm NRLM sulfur

cap is both different from and similar to the situation refiners faced with the Tier 2 gasoline

program. The NRLM program differs because refiners had to choose between a wide variety of

gasoline desulfurization technologies to comply with the Tier 2 sulfur standards. In contrast, we

project above that conventional hydrotreating will likely be the dominant choice for

desulfurizing diesel fuel to 500 ppm in 2007. Furthermore, this is already a well known

technology. The similarity exists, because refiners will have to consider how to comply with the

15 ppm nonroad diesel fuel cap in 2010 and 15 ppm L&M diesel fuel cap for 2012 when they

design their conventional hydrotreater for 2007. While conventional hydrotreating is well

understood, there are numerous ways to “conventionally hydrotreat” distillate. Variations exist

in operating pressure, hydrogen purity, physical catalyst loading, etc.J

 To avoid scrapping their

conventional hydrotreaters after just three to five years, we project that the refiners building new

conventional hydrotreating units for 2007 will plan these units to be easily revamped to produce

15 ppm nonroad diesel fuel in 2010 and L&M diesel fuel in 2012. The specific conventional

hydrotreating design selected for 2007 will therefore have to mesh with their plans for 2010 and

2012. At a minimum, this will involve selection of the operating pressure of the conventional

hydrotreater, provision of physical space for additional equipment, and the capacity of hydrogen

supply and treatment lines. Selecting the operating pressure is likely the most time-critical,

because of the long lead times involved in procuring pressure vessels. Also, vendors need some

time to assess the deep desulfurization performance of their desulfurization technologies via pilot

plants testing on specific refiners’ diesel fuel samples.

Fortunately, this process has been underway for some time involving refiners’ highway

diesel fuels. By mid-2004, this process should be nearly complete. In fact, 27 out of the 35

refineries projected to produce 500 ppm NRLM diesel fuel for 2007 have experience producing

highway diesel fuel today under the 500 ppm cap. Vendors’ should have ample capacity to test

refiners’ NRLM diesel fuel samples, as well as have developed efficient approaches to translate

test results into specific process designs. Thus, six months should be more than sufficient for

refiners to make the necessary, critical choices about their conventional hydrotreater design. In

fact, the selection of operating pressure could be made during the process-design step,

effectively reducing the amount of time to scoping and screening to three months.

The strategic decision to produce 500 ppm NRLM diesel fuel involves not only

marketing, but an economic assessment of the cost of producing this fuel, both absolutely and

relative to the competition. The scoping and screening studies are also not expensive to conduct. 

Refiners do not risk much to conduct them while they are still developing their corporate

strategy. Also, the scoping and screening studies can go on concurrent with the development of

a corporate strategy towards the rule. This means that the time for strategic planning (three to

six months) and the time for scoping and screening (three to six months) can go on concurrently.
Fuel Standard Feasibility

5-33

The time required for process design of a conventional distillate hydrotreater should be

no greater than that for a naphtha hydrotreater or the revamp of a diesel fuel hydrotreater (i.e.,

six months in both Tables 5.3-1 and 5.3-2). In fact, the design of the naphtha hydrotreater may

be more complex due to the desire to avoid too great a loss in octane from olefin saturation. 

Avoiding octane loss may lead the refiner to treat different parts of the naphtha stream

differently. Octane is not an issue with distillate hydrotreating. In general, the design of a

grassroots distillate hydrotreater is more complex than that of a revamp. However, the eventual

revamp in 2010 or 2012 which must follow this 500 ppm step will be is to produce 15 ppm diesel

fuel, a much more challenging task than producing 500 ppm diesel fuel. Thus, some extra

planning may be necessary for designing this 500 ppm hydrotreater. Regardless, six months

should be sufficient for the process design of a 500 ppm NRLM unit. The cumulative time for

the strategy, scoping, and process-design steps should range from nine to twelve months, as the

choice of distillate hydrotreating is clear.

Regarding permitting, we have taken steps to help state and local permitting agencies to

efficiently process refiners’ requests for permits related to environmental-related projects such as

these. Our experience with permits related to naphtha desulfurization indicates that three to nine

months is a more realistic range, as opposed to the three to twelve months projected in the Tier 2

Final Regulatory Impact Analysis. There, we identified twelve months as being a worst-case

scenario. Experience has confirmed this and we are not aware of any specific situations where

obtaining a permit has taken this long and held up the project completion.

The detailed design and construction of a distillate hydrotreater could require some

additional time relative to that for a naphtha hydrotreater due to the higher operating pressures

required for distillate hydrotreating. Because fewer firms fabricate higher pressure reactors and

compressors, the lead time for construction and delivery are usually longer. At the same time,

less time should be required than required for a FCC feed hydrotreater. FCC feed hydrotreating

usually occurs at even higher hydrogen pressures and involves much more cracking of large

molecules into smaller ones. Additional equipment is necessary to handle the significant amount

of gaseous product generated, etc. Interpolating between the times allocated for the detailed

design and construction of a naphtha hydrotreater and a FCC feed hydrotreater results in six to

nine months to design and twelve to fifteen months to construct a distillate hydrotreater. 

Cumulatively, the two steps would take a little more than 1 year and up to 2 years, or 1 to 1.25

years from the time permits were obtained.

This range is about three months shorter than that projected in Table 5.3-2 for the 15 ppm

highway diesel fuel rule. The difference on the high end is due to the fact that 2.5 years for

construction does not appear to be necessary. For this to be typical, all refiners planning to

produce 15 ppm highway diesel fuel would have already been constructing their new or

revamped hydrotreaters by the time of the 2003 precompliance reports. Clearly this was not the

case in the precompliance report results, yet refiners considered themselves on track to meet the

standard. Thus, the time periods resulting from an interpolation of the naphtha and FCC feed

hydrotreating estimates of Table 5.3-1 appear reasonable for producing 500 ppm NRLM fuel.

Finally, both the Tier 2 gasoline rule and 15 ppm highway diesel fuel review allocated
Final Regulatory Impact Analysis

5-34

three months for start up for naphtha, FCC feed and highway diesel fuel hydrotreaters. 

Allocating the same time period for starting a distillate hydrotreater should therefore be

appropriate.

Table 5.3-3 presents the results of the above assessment.

Table 5.3-3

Lead-time Projections for 500 ppm NRLM Diesel Fuel

Project Stage Time for Individual Step Cumulative Time

Strategic Planning 0.25-0.5 0.25-0.5

Scoping and Screening Studies 0.25-0.5 0.25-0.5

Process Design 0.5 0.75-1.0

Permitting 0.25-0.75 1.0-1.75

Detailed Engineering 0.5-0.75 1.5-2.25

Field Construction 1.0-1.25 2.0-3.0

Start-up/Shakedown 0.25 2.25-3.25

The timing of this final rule should allow some refiners to produce 500 ppm NRLM fuel

as early as July 2006. This coincides with implementation of the 15 ppm highway diesel fuel

cap and the ability to generate early 500 ppm NRLM credits. This analysis indicates that the last

refiners should be able to produce 500 ppm NRLM fuel by July 2007. This is within a month of

implementation of the 500 ppm NRLM cap. If any refiners are in the situation of needing this

last month to produce 500 ppm NRLM fuel, they should be able to purchase early credits from

other refiners and continue producing NRLM fuel until they are able to meet the 500 ppm cap.

5.3.2.4 Comparison with the 500 ppm Highway Diesel Fuel Program

The tasks refiners face in meeting the 500 ppm NRLM cap is very similar to the task

refiners faced with meeting the 500 ppm highway diesel fuel cap by October 1, 1993. The

primary difference is that refiners have ten years of experience producing 500 ppm diesel fuel

commercially. This should only shorten the time required to prepare for complying with the

standard relative to 1993. The 500 ppm highway diesel rulemaking was adopted in August 1990

and took effect October 1, 1993.38 Thus, that rulemaking provided 38 months of lead time,

nearly identical to that provided in this final rule for NRLM. Some price spikes occurred with

the 500 ppm highway diesel fuel standard. However, these were almost exclusively in

California, where a 10 volume percent aromatics standard was implemented at the same time. 

Also, the October implementation coincided with the annual increase in refiners’ distillate

production related to winter heating oil use. At that time, the United States was one of the first

nation’s to require 500 ppm diesel fuel, so little commercial experience was available upon

which to base designs. Refiners and technology vendors currently have over ten years of
Fuel Standard Feasibility

5-35

commercial experience in producing 500 ppm diesel fuel. We have also shifted the

implementation date away from the peak heating oil production season. Finally, the volume of

highway diesel fuel affected was more than three times as much as that affected by this final

rule, causing greater stress on the engineering and construction industries than we expect to

result from this final rule.

Many refiners likely to produce 500 ppm NRLM diesel fuel in 2007 also have to invest to

meet the Tier 2 gasoline sulfur standards and the 15 ppm highway diesel fuel cap. However, the

Tier 2 program finishes phasing in in 2006 for most refiners. The 15 ppm highway diesel fuel

likewise has a 2006 implementation date. This puts them at least one year ahead of the 500 ppm

NRLM standard. This minimum offset of one year should ease the burden on any specific aspect

of the process (e.g., raising capital funds, design personnel, construction personnel, etc.). The

1993 500 ppm highway diesel fuel cap also occurred in the midst of other fuel-quality

regulations. The phase 2 gasoline Reid vapor pressure standards and the oxygenated gasoline

programs took affect in 1992, while the reformulated gasoline program began in 1995. Thus, the

experience with the 500 ppm highway diesel fuel program appears to be a strong confirmation

that the final rule provides sufficient lead time.

5.3.2.5 Small Refiners

Small refiners may need more time to comply with a sulfur control program. Small

refiners generally have a more difficult time obtaining funding for capital projects, and must plan

further in advance of when the funds are needed. We contracted a study of the refining industry

that assessed the time required for small refiners to obtain loans for capital investments. The

simple survey revealed that small refiners need two to three months longer than large refiners to

obtain funding. If small refiners are forced to or prefer to seek funding through public means,

such as through bond sales, then the time to obtain funding could be longer yet, by up to one

third longer.39 In addition, because of the more limited engineering expertise of many small

refiners, the design and construction process for these refineries is relatively more difficult and

time consuming. We also believe the contractors that design and install refinery processing units

will likely focus first on completing the more expensive upgrade projects for large refiners. This

would also contribute to the additional time for design and construction of desulfurization

hardware for small refiners. The three additional years being provided small refiners should be

sufficient to compensate for these factors. This additional lead time should provide not only

enough time for these small refiners to construct equipment, but also allow more time for them to

select the most advantageous desulfurization technology. This additional time for technology

selection will help to compensate for the relatively poor economy of scale inherent with adding

equipment to a small refinery.

5.4 Feasibility of Producing 15 ppm Sulfur NRLM in 2010 and 2012
Final Regulatory Impact Analysis

5-36

5.4.1 Expected use of Desulfurization Technologies in 2010 and 2012

Like the 500 ppm sulfur standard for 2007, we considered several criteria to project

which desulfurization technologies will be used to meet the 15 ppm standard for nonroad in 2010

and the 15 ppm L&M standard in 2012. The criteria we considered included: (1) the time

refiners will have to choose a new technology, (2) whether the technology will be available for

2010 ane 2012 and, if the technology is available, how proven it is, (3) whether the technology is

cost-competitive by comparing it with other technologies, (4) whether the technology is

available from a vendor that has proven itself to the industry by providing other successful

refining technologies, particularly if the vendor has proven itself in the United States, and (5)

whether the vendor has the capability to meet the industry demands.

Refiners will have six and eight years to meet the 2010 and 2012 standards, respectively. 

Refiners will have from 2 to 4 more years to evaluate the slate of technologies in addition to the

usual amount of time they must have to construct and start up the necessary capital investments. 

Refiners are therefore not constrained when making their decisions and this particular issue did

not figure into our judgment regarding projected technologies.

Next, we considered whether a technology will be available in 2010 and 2012. 

Conventional hydrotreating is available, as it has been used in a variety of applications to meet

very stringent sulfur standards. In addition, many refiners are expected to use conventional

hydrotreating to comply with the highway diesel 15 ppm cap, which applies in 2006. This would

give refiners some experience with this technology before they decide which technology to use.

Process Dynamics already has a diesel fuel hydrotreating commercial demonstration unit

operating which is a revamp of a 500 ppm highway diesel fuel desulfurization unit (installed

before the existing highway hydrotreater). This unit demonstrates that the technology does

indeed work for treating untreated diesel fuel to 500 ppm, and thus would provide a proven

upgrade path through the revamp of the conventional 500 ppm units installed in 2007 to comply

with the 15 ppm cap standard in 2010 or 2012. A couple more refiners may choose to revamp

their refineries with the Process Dynamics technology for complying with the 15 ppm highway

diesel fuel sulfur standard taking effect in 2006, thus providing several more examples of the

Process Dynamics desulfurization technology being used to revamp 500 ppm treaters to meet the

15 ppm sulfur cap. Thus, refiners seeking to comply with the 15 ppm sulfur NRLM standard

should be able to see at least one, and probably more examples of the Process Dynamics

Isotherming process operating to desulfurize diesel fuel down to 15 ppm.

The oxidation and extraction technologies by Unipure and perhaps UOP do not have

units operating now, but Unipure is projecting to have a commercial demonstration unit

operating by 2006. However, an oxidation and extraction unit that begins operation in 2006 will

not provide two years of operations for interested refiners before they need to choose their

technology for 2010. As a result, it is unlikely to see any significant use by 2010, and use may

be limited to small refineries and terminals which would take advantage of their lower costs for

smaller installations. Furthermore, without a commercial demonstration unit operating along

with the technology’s perceived success, it is difficult to project the penetration into the
Fuel Standard Feasibility

5-37

desulfurization market even for 2012. 

Another issue refiners will consider is the cost of installing and operating these various

technologies. Of the oxidation and extraction technologies, Unipure did provide us with

desulfurization cost information based on testing at their laboratory, and that information shows

that it might be cost competitive with conventional hydrotreating. Phillips also has provided us

with diesel fuel desulfurization cost information from their pilot plant, which is backed up by the

success they have had with their commercial gasoline desulfurization unit (see Section 7.2). 

That technology seems to be less expensive than conventional hydrotreating for some refineries;

it appears to be suited primarily for desulfurizing low-sulfur diesel fuel down to very low sulfur

levels rather than for desulfurizing higher-sulfur feedstocks. Finally, Process Dynamics

provided us diesel fuel desulfurization cost information based on their pilot plant and their

engineering cost estimates for the commercial demonstration unit at the Giant refinery. The

Process Dynamics process seems to be less expensive than conventional hydrotreating (see

Section 7.2) and has been demonstrated to meet a 15 ppm sulfur standard by revamping a

conventional hydrotreater. 

We next evaluated whether each diesel fuel desulfurization technology vendor is

equipped to provide preliminary engineering and support the installations of its technology to a

significant part of the refining industry. Conventional hydrotreating is provided by numerous

vendors (Akzo Nobel, Criterion, Haldor Topsoe, IFP, and UOP) the majority of which

manufacture their own line of diesel desulfurization catalysts. Also, these vendors supported the

installation of many diesel fuel hydrotreaters to meet the 500 ppm highway diesel fuel sulfur

standard, which went into effect in 1993, and will be working with refiners to meet the very

stringent 15 ppm highway diesel fuel sulfur standard, which begins to take effect in 2006. Thus,

conventional desulfurization technology is poised to make a significant contribution.

Process Dynamics has only a very small engineering staff, however, they are associated

with Linde Process Plants and Roddy Engineering. Linde currently licenses several different

technologies, including sulfur and olefins recovery, natural gas processing, hydrogen production,

reforming, air separation. Linde has a large engineering and design department that has been

active for over 30 years. Roddy Engineering has a small engineering staff for additional

engineering support. Thus, Linde and Roddy Engineering are capable of providing substantial

engineering support to Process Dynamics for its IsoTherming desulfurization technology for a

significant penetration into the U.S. refining industry.

Phillips licenses several different technologies to refiners now, including its S-Zorb

gasoline desulfurization technology and an alkylation technology, and has licensed refining

technologies for over 60 years. Phillips has a robust research and development staff and also an

engineering staff to support the licensing of its S-Zorb technology.

The oxidation and extraction technologies are being developed by two separate entities,

one being Unipure and the other UOP. Unipure is associated with Texaco and Mustang

engineering. Thus, Unipure potentially has both research and development and engineering

support for its technology. UOP has substantial capacity for conducting engineering support for
Final Regulatory Impact Analysis

5-38

refiners.

After evaluating the various criteria for each technology and comparing across

technologies, we developed a projection for the mix of technologies that will be used in 2010

and 2012 for meeting the 15 ppm standards. Since refiners will have plenty of time to sort

through the various technologies, we believe lead time will have no bearing on refiners ability to

choose an advanced desulfurization technology. Whether a technology will have accumulated at

least two years of commercial experience is an important issue for the S Zorb and oxidation and

extraction technologies as the developers are not expected to have a commercial demonstration

unit operating for at least two years. Thus, while the Phillips S Zorb, Unipure and UOP

desulfurization technologies might be selected by refiners for 2010, we are not including their

technologies in our projected mix of technologies. 

This leaves conventional hydrotreating and Process Dynamics Isotherming. 

Conventional hydrotreating will clearly have the most refining experience due to refiners’

previous experience and also due to production of 15 ppm highway fuel for 2006. However,

Process Dynamics already has one unit operating and perhaps more diesel fuel desulfurization

commercial demonstration units will be operating for over two years. The Process Dynamics

hydrotreating process is expected to be lower in cost than conventional hydrotreating providing a

strong incentive to refiners seeking to reduce their capital and operating costs. Also Linde has

research and development and engineering capacity to support Process Dynamics with their

IsoTherming desulfurization processes, though not the same level of support as the multiple

conventional hydrotreating firms. After comparing these various criteria, we believe the lower

cost of Process Dynamics Isotherming will be the most important driver for these technologies. 

However, we also believe that some refiners will not be willing to try out a newer desulfurization

technology, especially since they may already have an established relationship with another

vendor. Thus, we believe the Process Dynamics process will be used to a greater extent than

conventional hydrotreating, but still be somewhat market limited. We project that Process

Dynamics Isotherming will capture 60 percent of the nonroad desulfurization market by 2010,

with conventional hydrotreating capturing the remaining 40 percent of the nonroad

desulfurization market. 

Refiners will have two more years to assess which technology they will use for

complying with the 15 ppm sulfur locomotive and marine standard in 2012. Despite the

additional two years, though, we assume the same penetration of advanced technologies because

of limiting factors for these technologies. Process Dynamics, even when associated with Linde

and Roddy engineering, is expected to be limited by the engineering staff available to them and

the conservative view by some refiners to new technologies. Furthermore, until a commercial

demonstration unit is operating for Unipure, UOP or Phillips, it did not seem appropriate to

assess potential market penetration for these advanced technologies. Thus, for 2012 we continue

to assume Processed Dynamic’s IsoTherming will meet 60 percent of the desulfurization demand

while extensions of conventional hydrotreating will meet the remaining 40 percent. 
Fuel Standard Feasibility

5-39

5.4.2 Lead-time Evaluation

More lead time is needed to meet a 15 ppm sulfur standard than a 500 ppm standard. The

additional time primarily involves the scoping and screening step, as the technology to achieve a

15 ppm sulfur cap is just being demonstrated on a commercial scale and some advanced

technologies promising lower costs are under development. This additional time might be on the

order of a few months, while the 2010 implementation date for 15 ppm nonroad and the 2012

implementation date for 15 ppm L&M fuel provides an additional three and five years of lead

time, respectively. The amount of lead time available for the 15 ppm NRLM caps should

therefore be more than sufficient for refiners to prepare for producing this fuel.

Of more interest is the interaction between the timing of the 15 ppm cap on highway

diesel fuel and that for NRLM diesel fuel. The time periods listed in Table 5.3-3 indicate that

refiners must start their process designs 2.0 to 2.75 years before first producing 15 ppm diesel

fuel and complete these process designs 1.5 to 2.25 years before the implementation date. This

means that process design should begin by September 1, 2007 to June 1, 2008, and be completed

by March 1 to December 1, 2008. This would provide refiners planning to produce 15 ppm

nonroad diesel fuel with 15 to 24 months of desulfurization experience from highway diesel fuel

desulfurization units started up in mid-2006 before initiating their process design. Similarly,

refiners producing 15 ppm L&M diesel fuel in 2012 are expected to have 39 to 48 months before

initiating their process design. Given that catalyst cycles last two to three years, refiners could

observe the performance of catalysts used to produce 15 ppm highway diesel fuel for one-third

of a cycle to a full cycle before having to begin their process design for desulfurizing nonroad

diesel fuel. Refiners producing L&M diesel fuel in 2012 will be able to observe the performance

of highway diesel fuel desulfurization catalysts for one to two cycles. While most of the units

producing highway diesel fuel in 2006 are expected to use conventional hydrotreating, as

discussed above, we also expect the Process Dynamics Isotherming process to have acquired

significant commercial experience and perhaps be demonstrated by more refineries choosing to

commercially produce 15 ppm for the highway program. Thus, refiners planning for 2010 would

be able to observe this newer process for more than three years before selecting their technology

and vendor. This should be sufficient to overcome uncertainty on the part of most refiners about

its performance. Overall, the available lead time allows all refiners to take advantage of the

operating performance of the highway units and minimize their costs.

5.5 Distribution Feasibility Issues

There are three considerations with respect to the feasibility of distributing NRLM diesel

fuels meeting the sulfur standard’s in this final rule. The first pertains to the extent that the

distribution system can reasonably accommodate the additional product segregation which might

result from this final rule, given the existing limitations in the system and the potential cost of

overcome such limitations. The second pertains to whether sulfur contamination can be

adequately managed throughout the distribution system so fuel delivered to the end-user does not

exceed the sulfur requirements in this rule. The third pertains to the ability to handle products

that become mixed in the pipeline distribution system so that they can be made saleable into the
Final Regulatory Impact Analysis

5-40

distillate market. These considerations are evaluated in the following Sections 5.5.1, 5.5.2., and

5.5.3. As discussed in these sections, we have designed the NRLM fuel program to avoid

significant distribution feasibility issues, and therefore have concluded that compliance with the

NRLM diesel sulfur control program will represent a manageable challenge to fuel distributors

that is not unduly burdensome. As a result, these issues are more correctly related to the cost of

compliance rather than feasibility.

5.5.1 Ability of Distribution System to Accommodate the Need for Additional Product

Segregations That Could Result from This Rule

5.5.1.1 The Diesel Fuel Distribution System Prior to Implementation of the NRLM

Sulfur-Control Program

Before 1993, most No. 2 distillate fuel was produced to nearly the same specifications,

shipped fungibly, and used interchangeably for highway diesel engines, nonroad diesel engines,

locomotive and marine diesel engines and heating oil (e.g., furnaces and boilers) applications. 

Beginning in 1993, highway diesel fuel was required to meet a 500 ppm sulfur cap and be

segregated from other distillate fuels as it left the refinery by the use of a visible level of dye

solvent red 164 in all non-highway distillate. At about the same time, the Internal Revenue

Service (IRS) similarly required non-highway diesel fuel to be dyed red (to a much higher

concentration) prior to retail sale to distinguish it from highway diesel fuel for excise tax

purposes (dyed non-highway fuel is exempt from this tax). This splitting up of the distillate pool

necessitated costly changes in the distribution system to ship and store the now distinct products

separately.

In some parts of the country where the costs to segregate non-highway diesel fuel from

highway diesel fuel could not be justified, both fuels have been produced to the highway

specifications. Diesel fuel produced to highway specifications but used for non-highway

purposes is referred to as “spill-over.” It leaves the refinery gate and is fungibly distributed as if

it were highway diesel fuel, and is typically dyed at a point later in the distribution system. Once

it is dyed it is no longer available for use in highway vehicles, and is not part of the supply of

highway fuel.

When the 15 ppm highway diesel fuel standard takes effect in 2006, an additional

segregation of the distillate pool is anticipated. Since up to 20 percent of the highway diesel fuel

pool is allowed to remain at 500 ppm until 2010, in some portions of the country as many as

three grades of distillate may be distributed; 15 ppm highway, 500 ppm highway, and high-sulfur

for all non-highway uses. The final highway diesel rule estimated that 500 ppm diesel fuel will

be present in 40 percent of the fungible fuel distribution system including the Northeast, parts of

the Midwest and in the area adjacent to the concentration of refineries in PADD 3. However,

given the results of its refiner’s pre-compliance reports which suggests that more than 95 percent

of highway diesel may be manufactured to a 15 ppm sulfur standard, 500 ppm fuel will likely be

restricted to a much smaller portion of the distribution system in 2006.
Fuel Standard Feasibility

K The Northeast/Mid-Atlantic Area provisions are discussed in detail in Section IV.D. of the preamble to the

final rule. Our determination of the boundaries of the Northeast/Mid-Atlantic Area is discussed in Section 5.5.1.4. 

5-41

5.5.1.2 Potential for Additional Product Segregation Under the NRLM Sulfur

Program

The NRLM sulfur-control program is discussed in detail in Section IV of the preamble to

the final rule. Following is a summary of these requirements and a discussion of the potential for

additional product segregation which might result.

This final rule requires that NRLM fuel comply with a 500 ppm sulfur standard

beginning in 2007. These provisions mirror controls on highway diesel fuel to 500 ppm in 1993. 

Refiners and importers can comply with the requirement either by producing NRLM fuel at or

below 500 ppm or, if located outside of the Northeast/Mid-Atlantic Area and Alaska, by

obtaining sufficient credits under the averaging banking and trading (ABT) provisions to cover

their continued production of high-sulfur (HS) NRLM through 2010.K Small refiners outside of

the Northeast/Mid-Atlantic Area may also continue to produce high HSNRLM until the

HSNRLM small-refiner and credit-use provisions expire in June 1, 2010.

The 15 ppm sulfur standard for nonroad diesel fuel takes effect June 1, 2010 and for

L&M diesel fuel takes effect June 1, 2012. The options available to comply with this 15 ppm

requirement parallel those available to comply with the earlier 500 ppm NRLM requirement. 

Refiners and importers can produce nonroad and L&M fuel at or below 15 ppm or, if located

outside of the Northeast/Mid-Atlantic Area and Alaska can obtain sufficient credits under the

averaging banking and trading (ABT) provisions to cover their continued production of 500 ppm

through June 1, 2014. Small refiners outside of the Northeast/Mid-Atlantic Area may also

continue to produce 500 ppm NRLM until the 500 ppm NRLM small-refiner and credit-use

provisions expire in June 1, 2014. After June 1 2014, all NRLM diesel fuel must meet a 15 ppm

sulfur standard except for 500 ppm fuel produced in the distribution system due to pipeline

interface mixing and product contamination. Outside of the Northeast/Mid-Atlantic Area and

Alaska, the prescribed marker must be added to heating oil at the terminal beginning June 1,

2007 and to 500 ppm sulfur L&M diesel fuel produced at a refinery or imported from June 1

2010 through May 31, 2012.

The application of different sulfur standards to portions of the non-highway distillate

pool based on end-use raises concerns regarding the potential need for additional product

segregation. Currently, distillate fuel for all non-highway uses is typically drawn from a single

pool that meets the most stringent specifications for any non-highway use. For example, it is our

understanding that nearly all heating oil meets the cetane specification for nonroad diesel engine

use despite the lack of applicability of a cetane specification for distillate fuel used as heating oil. 

This is because fuel manufactures and marketers have found that the potential savings from

manufacturing a low cetane heating oil are typically outweighed by the additional costs of

segregating an additional heating-oil-only product throughout the distribution system.
Final Regulatory Impact Analysis

5-42

We anticipate that the significant cost of desulfurizing NRLM diesel fuel to meet the new

sulfur standards provides a strong incentive for the fuel distribution system to evaluate whether

the additional costs of distributing non-highway distillate fuels of different sulfur specifications

is economically justified. This situation is analogous to that faced by industry after the 500 ppm

sulfur standard for highway diesel fuel took effect in 1993.

The IRS requirement that diesel fuel used in NRLM engines be dyed before it leaves the

terminal to indicate its nontaxed status also raises concerns about the potential need for

additional product segregation under the NRLM sulfur program. Fuel that meets highway diesel

specifications but is destined for the NRLM market can leave the terminal undyed provided that

the tax is payed. Non-highway users of such fuel can then apply to the federal and applicable

state revenue offices for a refund of the highway taxes payed on the fuel. In areas of the country

where only 500 ppm diesel fuel is currently available by pipeline, most bulk plant operators

nevertheless maintain dual tankage for dyed and undyed 500 ppm diesel fuel to meet the

demands of their customers for highway-tax-free non-highway diesel fuel. Such bulk plant

operators currently receive dyed diesel fuel by truck from local refineries. Thus, the IRS NRLM

diesel dye requirement may result in a strong incentive for parties in the fuel distribution system

downstream of the terminal to maintain segregated pools of undyed highway and dyed NRLM

diesel fuel that differ in no other respect than the presence of dye (after implementation of both

the 15 ppm highway diesel requirements in 2007 and the new requirements for NRLM fuel). We

expect that after the NRLM standards take effect, most bulk plant operators will request that the

terminal (or refinery rack) dye the fuel destined for sale into the NRLM market, so they can

continue their current practice of offering untaxed diesel fuel to their NRLM customers. 

We designed the NRLM sulfur program to minimize the need for additional product

segregation and resulting cost to fuel distributors associated with the need for additional storage

tanks, tank trucks, marker injection equipment, and other hardware and procedural factors. The

designate and track provisions in this final rule allows the fungible distribution of diesel fuels

that have the same sulfur content through much of the distribution system despite the fact that

they are destined for different end-uses. Fuel subject to the 500 ppm and 15 ppm NRLM sulfur

standards may be shipped fungibly with highway diesel fuel subject to the same sulfur standard

until the fuel leaves that terminal when red dye must be added to NRLM fuel to comply with IRS

fuel tax requirements. Similarly, high-sulfur and 500 ppm NRLM small-refiner and credit-use

fuel can be shipped fungibly with heating oil meeting the same sulfur specification until the

point when heating oil must be injected with the marker prescribed in this final rule. In addition,

high-sulfur NRLM small-refiner and credit-use fuel (present until 2010) may be commingled

with 500 ppm NRLM diesel fuel.

The number of possible product segregations that might exist under this rule varies

temporally, geographically, and based on the location in the fuel distribution system. The

variation over time is a function of the timing of the implementation dates of the two-step sulfur

control program, and the implementation and sunset dates of the small-refiner and credit use

provisions. In general, the number of possible segregations is the highest from 2007 - 2010, and

then begins to decline thereafter as the diesel fuel standards for all highway, nonroad, and L&M

diesel fuel begin to coalesce. The geographic variation is a function of limitations on where
Fuel Standard Feasibility

L

 The fuel marker requirements are necessary to support the small-refiner and credit-use provisions. See Section

IV.D of the preamble to the final rule for a discussion of the interactions between the small-refiner and credit-use

provisions and the heating oil marker requirement. 

5-43

small-refiner and/or credit-use fuel can be used, and where the fuel marker requirements apply.L

In the Northeast/Mid-Atlantic Area, the marker is not required since small-refiner and credit-use

NRLM fuel can not be sold there. In areas outside of the Northeast/Mid-Atlantic Area except

Alaska, the marker is required in heating oil beginning 2007 and in LM diesel fuel produced at a

refinery or imported from 2010-2012. In these areas small-refiner and credit-use NRLM fuel

may be sold. No marker is required in heating oil used in Alaska. However alternate

requirements apply in Alaska which allow small-refiner NRLM to be sold in Alaska. The

variation in the number of product segregations by location in the fuel distribution system is

primarily a result of: (1) the IRS requirement that off-highway distillate be dye red to indicate its

non-taxed status before leaving the terminal, (2) the requirement that heating oil outside of the

Northeast/Mid-Atlantic Area and Alaska contain the marker specified under this final rule prior

to leaving the terminal, and (3) the provision under this rule that the downstream standard for

L&M outside of the Northeast/Mid-Atlantic Area and Alaska is 500 ppm to account for fuel

generated due to mixing in the pipeline distribution system which can be sold into the

locomotive and marine market after the sale of fuel above 15 ppm is otherwise prohibited.

Many of the possible product segregations are discretionary, the decision to carry an

additional grade of diesel fuel being based on an economic evaluation of the associated carrying

costs versus the potential market demand in their area and the additional cost associated with

supplying a single fuel for multiple end-uses which meets the most stringent specifications for

any of these end-uses. We expect that a substantial part of the fuel distribution system in the

U.S. upstream of the terminal will carry only highway diesel fuel (for sale into both the highway

and NRLM markets). As noted earlier, this is currently the case due to logistical constraints in

the distribution system. We anticipate that these new NRLM sulfur standards will result in an

expansion of the area in which only highway diesel fuel is supplied for sale into both the

highway and NRLM markets. In such cases, the fuel is only differentiated for sale into either the

highway or NRLM markets when it leaves the terminal by the addition of red dye to NRLM fuel

to satisfy IRS requirements. Other segregations are unavoidable such as the segregation between

15 ppm highway and 15 ppm NRLM downstream of the terminal due to the presence of the IRS

specified red dye in NRLM fuel after it leaves the terminal, and the segregation of heating oil

from NRLM downstream of the terminal due to the required presence of the marker in heating

oil under this final rule (outside the Northeast/Mid-Atlantic Area and Alaska).

The following tables list the possible product segregations during various stages by

location in the distribution system. Table 5.5.1.2-1 lists the possible segregations outside of the

Northeast/Mid-Atlantic Area and Alaska. Table 5.5.1.2-2 lists the possible segregations in the

Northeast/Mid-Atlantic Area. Table 5.5.1.2-3 lists the possible segregations in Alaska. These

tables represent the maximum potential number of product segregations that could result from

this final rule. In most cases there will be fewer actual product segregations particularly in areas

of the country that will receive pipeline shipments of only a single grade of No. 2 diesel fuel for
Final Regulatory Impact Analysis

5-44

use in multiple distillate fuel markets. Furthermore, it is important to note that these possible

segregations are not equal in volume. As time goes by, most of the distribution system is

expected to coalesce around a few segregations such that it will look much as it does today. 

Table 5.5.4. lists the possible number of product segregations in such areas. Section 5.5.1.3. in

this RIA discusses the need for fuel distributors to invest in new storage tanks, tank trucks,

injection equipment, and other hardware or to change their operating practices in response to the

new product segregations caused by this rule. 
Fuel Standard Feasibility

5-45

Table 5.5.1.2.-1

Summary of Possible Product Segregations 

Outside of the Northeast/Mid-Atlantic Area and Alaska

Time Frame Refinery Gate

June 1 - May 31

Distribution to Terminal1

June 1 - Aug 15

Post Terminal

June 1 - Sept 30

Current

2004

500 ppm Hwy

HS NRLM/HO (dyed)

500 ppm Hwy

HS NRLM/HO (dyed)

500 ppm Hwy

500 ppm NRLM (dyed)

HS NRLM/HO (dyed)

2006-20072 15 ppm Hwy

500 ppm Hwy/NRLM7

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy/NRLM7

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy

500ppm & HS NRLM/HO (dyed)

2007-20093 15 ppm Hwy

500 ppm Hwy/NRLM

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy/NRLM

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy

500 ppm NRLM (dyed)

HS NRLM/500ppm NRLM (dyed)

HO (dyed & marked)

2009-20104 15 ppm Hwy/NRLM8

500 ppm Hwy/NRLM

HS NRLM/HO (dyed)

15 ppm Hwy/NRLM8

500 ppm Hwy/NRLM

HS NRLM/HO (dyed)

15 ppm Hwy

15 ppm NRLM8 (dyed)

500 ppm Hwy

500 ppm NRLM (dyed)

HS NRLM/500 ppm NRLM (dyed)

HO (dyed & marked)

2010-2012 15 ppm Hwy/NR

500 ppm NR/LM

HS HO

15 ppm Hwy/NR

500 ppm NR/LM

HS HO

15 ppm Hwy

15 ppm NR (dyed)

500 ppm NR (dyed)

500 ppm L&M (dyed and marked)

HS or 500 ppm HO (dyed and marked)

2012-20145 15 ppm Hwy/NRLM

500 ppm NRLM/HO9

HS HO

15 ppm Hwy/NRLM

500 ppm NRLM/HO9

HS HO

15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm NRLM (dyed)

500 ppm HO9 (dyed & marked)

HS HO (dyed & marked)

2014 &

later6

15 ppm Hwy/NRLM

500 ppm HO9

HS HO

15 ppm Hwy/NRLM

500 ppm LM/HO9

HS HO

15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm L&M (dyed)

500 ppm HO9 (dyed & marked)

HS HO (dyed & marked)

1

 The term “terminal” is used as shorthand to refer to the point where taxes are paid on highway fuel, dye added to 

 NRLM, or marker added to heating oil.

2

 The 15 ppm highway diesel program and the 500 ppm NRLM early credit provisions are effective 2006. 3

 500 ppm NRLM program effective 2007.

4

 15 ppm NRLM early credit generating provisions effective 2009.

5

 15 ppm NRLM program effective 2010. HS NRLM small-refiner and credit-use provisions expire. No 500 ppm 

 NRLM may be sold except small-refiner, credit, and pipeline interface generated 500 ppm NRLM.

6

 500 ppm NRLM small refiner, and credit use provisions expire 2014

7

 500 ppm early credit generating NRLM.

8

 15 ppm early credit generating NRLM.

9

 500 ppm heating oil is not required, but is a fuel grade that some refiners may choose to produce and distributors 
Final Regulatory Impact Analysis

5-46

 transport. Earlier, when 500 ppm NRLM was available, such fuel could have been used for heating purposes.
Fuel Standard Feasibility

5-47

Table 5.5.1.2.-2:

Summary of Possible Product Segregations In the Northeast/Mid-Atlantic Area

Time

Frame

Refinery Gate

June 1 - May 31

Distribution to Terminal1

June 1 - Aug 15

Post Terminal

June 1 - Sept 30

Current

2004

500 ppm Hwy

HS NRLM/HO (dyed)

500 ppm Hwy

HS NRLM/HO (dyed)

500 ppm Hwy

HS NRLM/HO (dyed)

2006 -

20072

15 ppm Hwy

500 ppm Hwy/NRLM6

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy/NRLM6

HS NRLM/HO (dyed)

15 ppm Hwy

500 ppm Hwy

500 ppm6 & HS NRLM/HO (dyed)

2007 -

20093

15 ppm Hwy

500 ppm Hwy/NRLM

HO (dyed)

15 ppm Hwy

500 ppm Hwy/NRLM

HO (dyed)

15 ppm Hwy

500 ppm Hwy

500 ppm NRLM (dyed)

500 ppm NRLM/HO (dyed)

2009 -

20104

15 ppm Hwy/NRLM

500 ppm Hwy/NRLM7

HO (dyed)

15 ppm Hwy/NRLM7

500 ppm Hwy/NRLM

HO (dyed)

15 ppm Hwy

15 ppm NRLM7 (dyed)

500 ppm Hwy

500 ppm NRLM (dyed)

HO (dyed)

2012-

2012

15 ppm Hwy/NR

500 ppm LM

HO

15 ppm Hwy/NR

500 ppm LM

HO

15 ppm Hwy

15 ppm NR (dyed)

500 ppm L&M (dyed)

HO (dyed)

2012 &

later5

15 ppm Hwy/NRLM

500ppm HO9

HS HO

15 ppm Hwy/NRLM

500 ppm HO9

HS HO

15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm HO9 (dyed)

HS HO (dyed)

1

 Terminal used as shorthand refers to the point where taxes are paid on highway fuel, dye added to NRLM, or marker 

 added to heating oil.

2

 The 15 ppm highway diesel and the 500 ppm NRLM early credit provisions are effective. 3

 500 ppm NRLM program effective 2007 and no HS NRLM may be sold except small-refiner and credit HS NRLM. HS 

 NRLM small-refiner and credit-use fuel may not be sold in the Northeast/Mid-Atlantic Area.

4

 15 ppm NRLM early credit provisions effective 2009.

5

 15 ppm NRLM program effective 2010. No 500 ppm NRLM small refiner, credit use, or pipeline interface generated

 fuels may be sold in the Northeast/Mid-Atlantic Area. 

6

 500 ppm NRLM credit fuel.

7

 15 ppm NRLM credit fuel.

8

 500 ppm heating oil is not required, but is a fuel grade that some refiners may choose to produce and distributors 

 transport. Earlier, when 500 ppm NRLM was available, such fuel could have been used for heating purposes.
Final Regulatory Impact Analysis

5-48

Table 5.5.1.2.-3:

Summary of Possible Product Segregations in Alaska

Time Frame Refinery Gate Distribution System to

Terminal1

Post Terminal

Current

2004

500 ppm Hwy

HS NRLM/HO

500 ppm Hwy

HS NRLM/HO 

500 ppm Hwy

HS NRLM/HO 

2006-20072 15 ppm Hwy

500 ppm Hwy/NRLM7

HS NRLM/HO 

15 ppm Hwy

500 ppm Hwy/NRLM7

HS NRLM/HO 

15 ppm Hwy

500 ppm Hwy

500 ppm7 & HS NRLM/HO (dyed) 

2007-20093 15 ppm Hwy

500 ppm Hwy/NRLM 

HS NRLM10

HO 

15 ppm Hwy

500 ppm Hwy/NRLM

HS NRLM10

HO 

15 ppm Hwy

500 ppm Hwy/NRLM

HS NRLM10

HO 

2009-20104 15 ppm Hwy/NRLM8

500 ppm Hwy/NRLM

HS NRLM10

HO 

15 ppm Hwy/NRLM8

500 ppm Hwy/NRLM

HS NRLM10

HS HO 

15 ppm Hwy/NRLM8

500 ppm Hwy/NRLM 

HS NRLM10

HS HO

2010-2012 15 ppm Hwy/NR

500 ppm LM

500 ppm NR12

HO

15 ppm Hwy/NR

500 ppm LM

500 ppm NR12

HO

15 ppm Hwy/NR

500 ppm LM

500 ppm NR12

HO

 2012-20145 15 ppm Hwy/NRLM

500 ppm NRLM11

HO 

15 ppm Hwy/NRLM

500 ppm NRLM11

HO 

15 ppm Hwy/NRLM 

500 ppm NRLM11

HO

2014 & later6 15 ppm Hwy/NRLM

500 ppm HO9

HO 

15 ppm Hwy/NRLM

500 ppm HO9

HO

15 ppm Hwy/NRLM 

500 ppm HO9

HO

1

 Terminal used as shorthand refers to the point where taxes are paid on highway fuel, dye added to NRLM, or marker 

 added to heating oil.

2

 The 15 ppm highway diesel and the 500 ppm NRLM early credit provisions are effective. 3

 500 ppm NRLM program effective 2007. HS NRLM small-refiner provisions require segregation and tracking of HS 

 NRLM. 

4

 15 ppm NRLM early credit provisions effective 2009.

5

 15 ppm NRLM program effective 2010. HS NRLM small-refiner provisions expire in 2010. 500 ppm small-refiner 

 NRLM provisions require segregation and tracking of 500 ppm NRLM. 6

 500 ppm NRLM small-refiner provisions expire 2014. 

7

 500 ppm NRLM credit fuel.

8

 15 ppm NRLM credit fuel.

9

 500 ppm heating oil is not required, but is a fuel grade that some refiners may choose to produce and distributors 

 transport. Earlier, when 500 ppm NRLM was available, such fuel could have been used for heating purposes. 10 Segregated HS NRLM small-refiner fuel only.

11 Segregated 500 ppm NRLM small-refiner fuel only.

12 Segregated 500 ppm NR small-refiner fuel only.
Fuel Standard Feasibility

5-49

Table 5.5.1.2.-4:

Summary of Possible Product Segregations In Areas of the Country Supplied with only a Single

Grade of No.2 Diesel Fuel by Pipeline (outside of the Northeast/Mid-Atlantic Area and AK)

Time Frame Refinery Gate1

June 1 - May 31

Distribution to Terminal2

June 1 - Aug 15

Post Terminal

June 1 - Sept 30

Current

2004

500 ppm Hwy 500 ppm Hwy 500 ppm Hwy

500 ppm NRLM (dyed)

NRLM/HO (dyed)

2006-20073 15 ppm Hwy 15 ppm Hwy 15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm NRLM8

 (dyed)

HS NRLM/HO8

 (dyed)

2007-20094 15 ppm Hwy 15 ppm Hwy 15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm Hwy8

500 ppm NRLM8 (dyed)

HS NRLM10/500ppm NRLM8 (dyed)

HO (dyed & marked)8

2009-20105 15 ppm Hwy/NRLM13 15 ppm Hwy/NRLM13 15 ppm Hwy

15 ppm NRLM10 (dyed)

500 ppm Hwy8

500 ppm NRLM8 (dyed)

HS NRLM8/500 ppm NRLM8 (dyed)

HO (dyed & marked)8

2010-20146 15 ppm Hwy/NRLM 15 ppm Hwy/NRLM 15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm NRLM8 (dyed)

500 ppm HO8 (dyed & marked)

HS HO (dyed & marked)8

2014 &

later7

15 ppm Hwy/NRLM 15 ppm Hwy/NRLM 15 ppm Hwy

15 ppm NRLM (dyed)

500 ppm L&M (dyed)9

500 ppm HO8 (dyed & marked)

HS HO (dyed & marked)8

1

 Refinery rack sales are covered under the “Post Terminal” segment.

2

 The term “terminal” is used as shorthand to refer to the point where taxes are paid on highway fuel, dye added to 

 NRLM, or marker added to heating oil.

3

 15 ppm highway diesel program and 500 ppm NRLM early credit generating provisions are effective 2006. 4

 500 ppm NRLM program effective 2007.

5

 15 ppm NRLM early credit generating provisions effective 2009.

6

 15 ppm NRLM program effective 2010. HS NRLM small-refiner and credit-use provisions expire. 7

 500 ppm NRLM small-refiner and credit-use provisions expire 2014.

8

 Refinery rack sales or sales at terminals of segregated interface.

9

 Sales at terminals of segregated interface and from transmix processors of fuel produced from transmix. 

10 15 ppm early credit generating NRLM.
Final Regulatory Impact Analysis

5-50

5.5.1.3 Ability of Fuel Distributors to Handle New Product Segregations that Will

Result from the NRLM Sulfur Control Program

As noted in Section 5.5.1.1, distribution feasibility concerns related to new product

segregations primarily pertain to the ability of fuel distributors to bear the economic burden of

installing new storage tanks and other equipment. Thus, the issue is one of cost not feasibility. 

Representatives of terminal and bulk plant operators stated that the physical boundaries of some

of their locations and/or the local safety and environmental ordinances under which some of their

facilities operate would prevent them from installing any new storage tanks. Even where the

expansion of tankage facilities is limited by space or other considerations, the issue is still one of

the cost of providing a fuel grade meeting a more stringent standard than necessary and not one

of the feasibility of supplying fuel to a given market. These considerations and others led us to

structure the NRLM program to minimize the number of additional new product segregations

that would be needed. As discussed in Section 5.5.1.3, this rule allows fuels of like sulfur

content to be shipped fungibly until they leave the terminal.

We also structured the fuel marker requirements to minimize the potential impact on

terminal operators. One issue that concerned terminal operators is that they wished to be able to

blend 500 ppm NRLM diesel fuel from high-sulfur heating oil and 15 ppm diesel fuel in order to

avoid the need to install a storage tank for 500 ppm at some of their facilities (while still being

able to serve the 500 ppm NRLM market). The final rule allows the marker to be added as the

fuel leaves the terminal, thereby providing that terminals can blend 500 ppm diesel fuel from 15

ppm highway diesel fuel and high-sulfur heating oil subject to the anti-downgrading provisions

for 15 ppm highway diesel fuel. The primary concern expressed by terminal operators regarding

the potential impact of the fuel marker pertained to the cost of installing new injection equipment

to add the marker to heating oil. The Northeast/Mid-Atlantic Area provisions exclude the area in

which the majority of heating oil will continue to be sold after implementation of this rule,

thereby minimizing this concern. Our determination of the optimal boundaries for the

Northeast/Mid-Atlantic Area is discussed in Section 5.5.1.4.

The following sections evaluate the potential need for additional product segregation in

each segment of the distribution system from the refinery through to the end-user due to

implementation of the NRLM diesel sulfur standards. Based on the following discussion, we

believe the potential impacts of this final rule on the distribution system due to the need for

additional product segregation will be minimal and can be readily accommodated by industry in

the lead time available. See Section 7.3 of this RIA for a discussion of the increased distribution

costs that will result from this final rule.

Refineries:

Due to economies of scale involved in desulfurization, we expect that many individual

refineries will choose to manufacture a single grade of diesel fuel, or perhaps two grades in some

cases. We do not anticipate that individual refineries will produce substantial quantities of all

the different diesel fuel sulfur grades (15 ppm fuel, 500 ppm, and heating oil). Therefore, we do

not anticipate the need for additional product segregation at refineries. Because this final rule
Fuel Standard Feasibility

M There will be no physical differences between highway and NRLM fuel produced by refiners to the same

sulfur specification. The distinction between the two fuels is made only for accounting purposes to ensure

compliance with limitations on the volume of 500 ppm highway diesel fuel that can be produced by refiners (under

the highway diesel final rule) is complied with.

N Under this final rule, heating oil (beginning 2007) and 500 ppm sulfur L&M diesel fuel (2010-2012) must be

marked before it leaves the terminal in areas outside of Alaska and the Northeast/Mid-Atlantic Area.

O See Section 7.4. of this RIA for a discussion of the estimated costs of marker injection equipment.

5-51

allows highway and nonroad diesel fuels to be shipped fungibly until NRLM fuel is dyed

pursuant to IRS requirements at the terminal, we do not expect that the NRLM sulfur standards

will require refiners to install new product storage tanks.M

We do not expect that the fuel marker requirements will cause the need for additional

product segregation at the refinery.N However, refiners that market heating oil beginning in

2007 and 500 ppm L&M diesel fuel from 2010 through 2012 from their racks outside of the

Northeast/Mid-Atlantic Area and Alaska will have to inject the marker into the fuel sold off their

refinery racks as it is loaded into tank trucks. In the NPRM, we projected that the same

equipment currently used for injection of red dye could be used to inject the fuel marker. We

now recognize that due to concerns about contaminating red dyed fuel which is required to

contain no marker, this will only be possible at refineries at which the only untaxed fuels that

they carry are the fuels subject to the marker requirement. At other refineries, a completely new

injection system will be needed so that the existing system can continue to be used to inject red

dye into fuels in which this is required by IRS, but which this final rule prohibits from containing

the fuelmarker. Nevertheless, we do not expect that the installation of such equipment represents

a significant concern given that the cost of such equipment is modest, the number of refineries

that will need to install such equipment is limited, and the space requirements and construction

resource requirements are minimal.O

Pipelines:

Similar to refiners, we anticipate that most pipelines will carry only one or two of the

sulfur level grades (e.g. 15 ppm, 15 ppm and 500 ppm, or 15 ppm and HS), although in a few

instances they may carry all three. We expect that the pipelines that we projected will carry 500

ppm fuel under the 2007 highway diesel rule’s temporary compliance option (TCO) will be the

same pipelines that elect to carry 500 ppm diesel fuel after the NRLM diesel fuel program starts. 

We do not expect that any common carrier pipelines will carry 500 ppm diesel fuel after the

implementation of the 15 ppm sulfur standard for nonroad diesel fuel in 2010. All product

pipelines are expected to carry 15 ppm highway diesel fuel beginning in 2006. As noted earlier,

the final rule provides for the fungible shipment by pipeline of highway and NRLM fuels that

meet the same sulfur specification. We therefore do not expect the NRLM sulfur standards to

necessitate additional product segregation in the pipeline distribution system.

There is no physical separation between product batches shipped by pipeline. When the
Final Regulatory Impact Analysis

5-52

mixture that results at the interface between two products that touch each other in the pipeline

can be cut into the one of these products, it is referred to as interface. When the mixture must be

removed for reprocessing, it is referred to as transmix. Given that the pipeline operators will be

able to combine batches of highway and NRLM diesel fuel meeting the same sulfur

specification, we do not expect that the NRLM program will increase the volume of product

downgrade or transmix volumes. To the contrary, there may be some opportunity for improved

efficiency because of the increase in batch sizes shipped by pipeline. This potential benefit

could be significant, given that the volume of NRLM shipped by pipeline represents a sizeable

fraction of the total diesel fuel volume.

The marker requirements for heating oil (beginning 2007) and for 500 ppm sulfur LM

diesel fuel produced by refiners or imported (2010-2012) applies prior to leaving the terminal. 

Furthermore, these marker requirements do not apply in the Norhteast/Mid-Atlantic Area where

most heating oil is used. Therefore, we do not expect that the marker requirement will result in

an increased need for product segregation in the pipeline or an increase in product downgrade or

transmix volumes.

We believe the demand for heating oil will be sufficiently large only in the

Northeast/Mid-Atlantic to justify the continued distribution of high-sulfur diesel fuel once

nonroad, locomotive, and marine diesel fuel is removed from the potential high-sulfur diesel

pool (by implementation of the NRLM sulfur standards). Heating oil will therefore unlikely be

present in pipeline systems that supply areas outside of the Northeast, and Mid-Atlantic states.

The pipelines that we project will handle heating oil after the requirements of this final rule take

effect are those that we earlier projected to carry 500 ppm highway diesel fuel in addition to 15

ppm from 2006-10. 

Under the final rule, all nonroad and L&M diesel fuel produced must meet a 15 ppm

sulfur standard in 2010 and 2012 respectively. However, limited quantities of small-refiner, and

credit fuel that could remain at 500 ppm until 2014. Due to the reduction in the total potential

500 ppm diesel pool in 2010 and again in 2012, it is likely that some pipelines will no longer

find it economical to carry 500 ppm as well as 15 ppm diesel fuel. We are projecting that most

pipelines will elect not to carry 500 ppm diesel fuel and will carry only 15 ppm diesel fuel after

2010. This could result in some overall simplification of the diesel distribution system. We

expect that nonroad and L&M fuel, which is produced by refiners to a 500 ppm standard after

2010, will be distributed by the refiner to the end-user via segregated pathways. Outside of

Alaska and the Northeast/Mid-Atlantic Area, limited volumes of 500 ppm fuel can continue to be

produced as locomotive and marine diesel fuel from interface, and transmix indefinitely. This

fuel can also be sold as heating oil within the Northeast/Mid-Atlantic Area and Alaska. We

anticipate that such fuel will be distributed directly from the transmix facility or terminal that

produces such fuel to the end-user. Therefore, the presence of such 500 ppm fuels in the

distribution system will not result in the need for additional product segregation in pipelines.

A limited number of refiners outside of the Northeast/Mid-Atlantic Area may continue to

produce high-sulfur NRLM until 2010, 500 ppm nonroad from 2010 to 2014, and 500 ppm L&M

from 2012 to 2014 under the small-refiner and credit-use provisions. We expect most of this fuel
Fuel Standard Feasibility

5-53

will be distributed via segregated means from the refinery rack to the end-user. However, if such

HS or 500 ppm nonroad or L&M is shipped by pipeline, it can be combined with heating oil

meeting the same sulfur specification up to the point where it is distributed from the terminal. 

Therefore, we do not expect the small-refiner or credit provisions to create the need for

additional tankage at any location in the fuel distribution system.

Terminals:

The product segregation needs at terminals are directly affected by the range of products

that they receive by pipeline. Thus, the discussion regarding the potential impacts of this final

rule on terminal operators closely parallels the preceding discussion on the potential impacts on

pipeline operators. The allowance that highway and NRLM diesel fuel meeting the same sulfur

specification may be shipped fungibly until NRLM diesel fuel must be dyed to indicate its nontax status upon leaving the terminal obviates the need for additional product segregation at the

terminal for NRLM fuel meeting the sulfur standards in this rule with the exception of a limited

number of small additional storage tanks needed to handle “downstream flexibility” fuel created

due to interface mixing in pipelines (discussed below). We expect that terminal operators will

generally store NRLM and highway diesel fuel meeting the same sulfur specification in the same

tank and that NRLM fuel will be injected with red dye, and LM diesel fuel produced or imported

injected with the fuel marker (from 2010-2012) and red dye as it is delivered from the tank into

tank trucks. 

Similarly, since the marker is required to be present in heating oil (and L&M diesel fuel

from 2010-2012) after it leaves the terminal, we expect that terminal operators will store heating

oil and HS NRLM (allowed from 2007-2010) in the same storage tank, and 500 ppm L&M

diesel fuel (2010-2012) and 500 ppm nonroad diesel fuel (allowed until 2014) in the same

storage tank. Marker will be added to the heating oil and 500 ppm sulfur diesel fuel (2010-2012)

when it is dispensed from the storage tank into tank trucks. A limited number of terminal

operators will need to install new equipment to inject the fuel marker. As discussed in Section

5.5.1.4, we crafted the Northeast/Mid-Atlantic Area provisions to minimize the number of

terminals that will need to install such equipment. We do not expect that the installation of such

equipment represents a significant concern given that the cost of such equipment is modest, the

number of terminal that will need to install such equipment is limited, and the space

requirements and construction resource requirements are minimal.

Some terminals outside of these Northeast/Mid-Atlantic Area may market limited

quantities of 500 ppm diesel fuel that was generated during the distribution of 15 ppm diesel fuel

(“downstream flexibility fuel”). We expect that such fuel will be marketed directly from the

terminal to the end user. Limited additional tankage will be needed at terminals to handle this

500 ppm product as discussed in Section 7.4.3. 

Bulk Plants:

Bulk plants are secondary distributors of refined petroleum products. They typically

receive fuel from refinery racks or terminals by tank truck and distribute off-highway diesel fuel
Final Regulatory Impact Analysis

P

 In the Northeast/Mid-Atlantic Area heating oil would be dyed. Outside of the Northeast/Mid-Atlantic Area

and Alaska, heating oil would be dyed and marked. In Alaska, heating oil will neither be dyed or marked. 

5-54

in bulk by truck to end users, serving the role of the retailer. Bulk plants are one point in the

distribution system where we anticipate some additional tankage will likely be needed as a result

of this final rule. However, we project that only a small subset of the bulk plants will be faced

with the choice of adding additional tankage. In most areas of the country, a distinct grade of

heating oil will no longer be carried, and bulk plant operators can simply switch the tank that

they previously devoted to high-sulfur service to 500 ppm NRLM service in 2007 and supply

their HO needs out of this same tank.

In areas where heating oil is anticipated to remain as a separate grade, we anticipate that

bulk plants will face the choice of adding a new tank and perhaps demanifolding their delivery

truck(s) to distribute dyed 500 ppm NRLM diesel fuel in addition to high-sulfur heating oil.P

 In

this context demanifolding refers to the process of separating a single storage tank on a delivery

tank truck (or trucks) to make two compartments. Some bulk plants that face the choice of

installing the facilities to allow additional product segregation may find the cost of a new storage

tank and demanifolding their delivery truck(s) is too high, or may not have the space or

capability to add new tank. However, such bulk plants have other options. If they own another

bulk plant facility in the area, they may choose to optimize use of available tankage by carrying

one of the grades at each facility. Even if they do not own another facility, they may be able to

establish a similar arrangement with a terminal or other bulk plant in the area. They could

choose to supply heating oil only during the winter months, and supply NRLM during the

summer months to both markets. Finally, they could simply choose not to distribute one of the

fuel grades. For example, either sell NRLM for both uses or sell only heating oil and allow other

fuel distributors in the area to satisfy the NRLM market. We anticipate that approximately 1,600

bulk plants will face the decision of adding new tankage or finding some other means of

continuing to serve both heating oil and nonroad markets. This is the number of bulk plants that

we project will be located in the areas of the country where heating oil will continue to be

carried by the fungible distribution system after the NRLM standards take effect and where 500

ppm fuel will also be carried. Of these, we expect no more than 1,000 will choose to install a

new tank. Given the ample lead time to prepare for implementation of the NRLM sulfur

standards, the installation of additional tanks at bulk plants is an economic issue rather than a

feasibility issue. Even where the expansion of tankage facilities is limited by space or other

considerations, the issue is still one of the cost of providing a fuel grade meeting a more stringent

standard than necessary and not one of the feasibility of supplying fuel to a given market. 

We do not anticipate that bulk plants will invest to carry a separate 500 ppm grade of

NRfuel in addition to 15 ppm nonroad fuel after 2010. The majority of the nonroad volume will

meet the15 ppm sulfur standard. We expect that few, if any, bulk plants will carry 500 diesel

L&M diesel fuel since this market is not a substantial one for bulk plants. Unless a bulk plant

had existing tankage available or supplied a majority of its fuel to NRLM uses, 500 ppm nonroad

and L&M will therefore likely be limited to refinery and terminal distribution. This is how the

bulk of the distribution of locomotive and marine diesel fuel occurs today.
Fuel Standard Feasibility

Q Comments from John Huber of the National Oil Heat Research Alliance (NORA), Docket ID No. OAR-2003-

0012-0840.

5-55

5.5.1.4 Determining the Boundaries for the Northeast/Mid-Atlantic Area

Our goal in adopting the Northeast/Mid-Atlantic Area approach is to minimize the

number of terminals that will need to install new injection equipment and the amount of fuel that

will need to be marked, while preserving to the maximum extent possible the flexibilities for

refiners and importers. The key to balancing these somewhat competing concerns of refiners and

terminal operators is the selection of where to draw the boundary of the Northeast/Mid-Atlantic

Area.

The Northeast/Mid-Atlantic Area approach was first suggested in comments from the

National Oil Heat Research Alliance (NORA).Q NORA suggested that limiting the small-refiner

and credit-use provisions to Petroleum Administration for Defense Districts (PADDs) 2,3,4 & 5

would make the marker requirement for heating oil unnecessary in PADD 1. Excluding PADD 1

from the heating oil marker requirement could then eliminate nearly all costs associated with the

marker requirement, and might not impose any limits on refiners who may wish to take

advantage of the small-refiner and credit flexibilities. The definition of the 5 PADDs is

illustrated in Figure 5.5.1.4.-1.

Figure 5.5.1.4.-1: Definition of PADDs

NORA presented a PADD by PADD analysis of data from the Energy Information

Administration (EIA) regarding the volume of diesel fuel used for heating purposes compared to

the volume of fuel used in other non-highway distillate end-uses which it used to support its

suggested exclusion of PADD 1 from the marker requirement for heating oil. Selected results of

this analysis are presented in Table 5.5.1.4-1.
Final Regulatory Impact Analysis

R "Paying for" refers to the volume of heating oil bearing the costs related to the marker requirements where

these requirements are needed to make the small refiner and credit provisions enforceable.

5-56

Table 5.5.1.4-1

Ratio of Heating Oil to Other Non-Highway 

Area Ratio of Non-Highway Diesel Fuel Used for Heating Purposes 

to Non-Highway Diesel Used for Other Purposes

PADD I (Total) 3.57

PADD IA1 16.73

PADD IB 6.73

PADD IC 0.31

PADD II 0.34

PADD III 0.09

PADD IV 0.22

PADD V 0.31

1

 The sub-regions that make up PADD I are illustrated in Figure 5.5.1.4-3.

NORA stated that the number of heating oil gallons paying for the application of the

small-refiner and credit provisions in PADD I would be much greater than the potential number

of gallons that might use the provisions.R NORA stated that this indicated that the application

of the small refiner and credit provisions in PADD I was not a good value. NORA stated that an

evaluation of the cost of the marker requirement versus the potential benefits of the small-refiner

and credit provisions indicates that the application of these provisions should be limited to

PADDs in which the ratio of non-highway diesel fuel used as heating oil to non-highway diesel

fuel used for other purposes, essentially NRLM, was less than 1.

To assess where to draw the boundaries of the Northeast/Mid-Atlantic Area we evaluated

the area supplied by the pipeline distribution systems that are expected to continue to ship

heating oil after implementation of this rule, evaluated the magnitude of heating oil demand by

state, evaluated where the terminals are located that are likely to carry heating oil, evaluated the

distribution area of small refiner(s) for high-sulfur NRLM diesel fuel and refiner expectations

regarding the market for high-sulfur NRLM, and solicited input from the potentially affected

parties.

The marker requirement for 500 ppm sulfur L&M diesel fuel that will be effective

outside of the Northeast/Mid-Atlantic Area and Alaska from June 1, 2010, through May 31,

2012, was not a significant factor in our evaluation how to define the boundary of the

Northeast/Mid-Atlantic Area. We expect that locomotive and marine diesel fuel subject to the

marker requirements will primarily be distributed via segregated pathways from a limited
Fuel Standard Feasibility

5-57

number of refineries. Therefore, a significant number of terminals will not need to handle L&M

diesel fuel that is subject to the marker requirement. Thus, the potential cost of installing

injection equipment to add the marker to 500 ppm sulfur L&M diesel fuel which is subject to the

marker requirement will be limited to only a few refineries and terminals (i.e. approximately 15,

see section 7.4.4. of this RIA). 

Area Supplied by Pipelines that are Expected to Continue to Ship Heating Oil, and

Location of Terminals that Will Carry Heating Oil:

After implementation of the NRLM program, we expect that the demand for heating oil

outside of the Northeast and Mid-Atlantic States will be insufficient to justify its continued

shipment as a segregated product by pipeline. Heating oil that is shipped by pipeline into the

Northeast and Mid-Atlantic states primarily originates in the cluster of refineries located in

PADD III (e.g. in Texas and Louisiana) and is shipped on the Colonial and Plantation pipelines

North. The Buckeye/Laurel pipeline receives fuel from these pipelines for shipment North and

West into New York state and Pennsylvania. Some heating oil shipped by pipeline in this area

will also likely originate from refineries within PADD I and from imports into New York harbor. 

No heating oil flows by pipeline from PADD I into PADD II. The Buckeye/Laurel has a

pipeline through Southern Pennsylvania that ends in Pittsburgh and a pipeline in New York that

runs West to Buffalo South of the Lake Erie shore. The Sun pipeline also runs West from

Philadelphia to Pittsburgh. A simplified illustration of these pipeline systems is presented in

Figure 5.5.1.4-2. We anticipate that the branch lines off of the main pipelines South of North

Carolina may no longer find it economical to distribute a separate grade of heating oil. 
Final Regulatory Impact Analysis

S

 Energy Information Administration Fuel Oil and Kerosene Sales 2002.

5-58

Colonial Pipeline 

Plantation Pipeline

Buckeye-Laurel 

& Sun Pipelines

Legend

Figure 5.5.1.4-2: Simplified Illustration of the Pipeline Distribution

System that Supplies the Northeast and Mid-Atlantic States*

*All branch lines are not shown in this figure, and in some cases a more complex local system is condensed into a single

line. The location of the lines are approximate. Product flows from the South to the end of the lines.

Magnitude of Heating Oil Demand:

Figure 5.5.1.4-3 shows the residential heating oil use in PADD I by state and by the subdistricts in PADD I.S
Fuel Standard Feasibility

5-59

PADD I Refining District

New England

(PADD IA)

Central Atlantic

(PADD 1B)

Sales of No. 2 Distillate Fuel Oil

for Residential Use

 (Thousand Gallons)

PADD IA

ME. 271,855

N.H. 167,740

VT. 85,505

MASS. 892,675

R.I. 135,745

CONN. 529,648

PADD IB

N.Y. 1,330,288

PA. 351,645

N.J. 366,112

DEL. 40,038

MD 178,006

D.C. 14,234

PADD IC

W.VA. 19,948

VA. 196,518

NC. 113,584

SC. 15,585

GA 2,225

FLA 3,785

PADD I Summary

PADD 1 Total 5,192,749

PADD 1A 2,083,168 (40%)

PADD 1B 2,757,936 (53%)

PADD 1C 351,645 (7%)

Residential Use of No. 2 Distillate in PADD I

Lower Atlantic

(PADD IC)

Central Atlantic

(PADD IB)

ME.

N.H.

 MASS.

 R.I.

 CONN.

N.J.

DEL.

MD.

W.VA.

PA.

N.Y.

VT.

VA.

N.C.

S.C.

GA.

FLA.

Figure 5.5.1.4-3: Residential Use of Heating Oil in PADD I

The data summary presented by NORA indicated that PADD IC was more similar to the

other PADDs than to PADDs IA and IB with respect to the volume of heating oil used in relation

to the use of NRLM fuel. However, a review of the levels of heating oil by state (in Figure

5.5.1.4-1) reveals that the level of heating oil use in Virginia and North Carolina is more similar

in magnitude to that in the PADD IA and PADD IB states than to the other states in PADD IC. 

This suggests that assigning Virginia, North Carolina, and the areas in PADD IA and IB to the

Northeast/Mid-Atlantic Area but not the remaining states in PADD IC might best balance the

criteria of excluding areas with high heating oil demand from the marker requirement while

preserving the widest possible area in which refiners could use the small-refiner and credit

provisions.

However, a review of the pipeline map in Figure 5.5.1.4-2 and the topography of West

Virginia suggests that the Eastern panhandle of West Virginia should also be in the

Northeast/Mid-Atlantic Area. The topography of West Virginia has dictated that in some ways

the state’s Eastern panhandle is more closely linked with the surrounding states than to the rest
Final Regulatory Impact Analysis

T

 West Virginia University: The Sources of the Political Agenda: Geography, History and Economy, and

Political Culture (of West Virginia), http://www.polsci.wvu.edu/faculty/dilger/PS321/CHAP-1.htm#N_3_

U Phone conversation with the Western Virginia Petroleum Marketers Association.

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of West Virginia.T This also suggests that Eastern panhandle may receive its fuel from the

pipelines that serve the northeast and Mid-Atlantic states. Discussion with the West Virginia

Petroleum Marketers Association confirmed that the counties in the Eastern panhandle of West

Virginia do receive their fuel from sources that draw from the Colonial and Plantation pipelines,

while the remainder of the state receives its fuel from other sources.U Therefore, we believe that

it is appropriate to assign the counties in the Eastern panhandle of West Virginia to the

Northeast/Mid-Atlantic Area but not the rest of the state.

We believe that states outside of PADD I should not be assigned to the Northeast/MidAtlantic Area for several reasons. The first reason is that heating oil users are predominately

located in PADD I. Therefore, assigning areas outside of PADD 1 to the Northeast/Mid-Atlantic

Area would provide relatively little relief with respect the burden of the marker requirement for

heating oil, while substantially eroding the potential benefits of the small refiner and credit

provisions under today’s rule. Table 5.5.1.4-2 illustrates that the great majority of heating oil

use is localized in PADD IA and IB.

Table 5.5.1.4-2

Residential Heating Oil Use in the U.S.

Area Residential Heating Oil Use1

(thousand gallons)

Percent of U.S. Total

U.S. Total 5,830,179 -

 PADD I 5,192,749 89.1%

 PADD IA 2,083,168 35.7%

 PADD IB 2,757,936 47.3%

 PADD IC 351,645 6.0%

 PADD II 473,972 8.1%

 PADD III 3,138 0.1%

 PADD IV 19,796 0.3%

 PADD V 140,524 2.4%

1

 Energy Information Administration (EIA), Fuel Oil and Kerosene Sales 2002, Table 19, Adjusted Sales for Residential

Use: Distillate Fuel Oil and Kerosene.

The estimates in Table 5.5.1.4-2 are based on the reported use and do not speak to the

sulfur content of the fuel. A sizeable fraction of the fuel reported as used as heating oil may be

spillover from the highway diesel pool. This is most likely in areas where heating oil is currently
Fuel Standard Feasibility

V We project that the majority of this segregated interface will meet a 500 ppm specification. Under the

provisions of the final rule, such 500 ppm diesel fuel could be sold directly into the NRLM market from 2007 - 2014

and into the locomotive and marine diesel markets after 2014. 

5-61

not distributed by pipeline. As noted earlier, we anticipate that after implementation of the

NRLM program, heating oil will only be distributed by pipeline to supply the Northeast and

Mid-Atlantic states. Therefore, it is likely that this rule will result in a greater proportion of the

fuel used for heating purposes outside of PADD I to come from the highway diesel and NRLM

pools. Though used for heating purposes, such spillover would be designated as highway and

NRLM, would meet the applicable sulfur standards, and thus would not be subject to the marker

requirement. The marker requirement is associated with the sulfur content of the fuel rather than

its designation.

The second reason is that we expect that the heating oil which is sold outside of the

Northeast and Mid-Atlantic states will primarily be distributed directly from refiner racks. We

expect that the vast majority of terminals that will continue to carry heating oil will be supplied

by the pipeline systems illustrated in Figure 5.5.1.4-2 and by marine shipments into Northern

PADD I and thus will be located adjacent to these sources. Only a few entities, primarily

refiners, would need to install new injection equipment for the heating oil marker if the marker

requirement were to apply only to areas outside of the Northeast and Mid-Atlantic states.

Limited volumes of heating oil produced from segregated pipeline interface may be sold

at some terminals outside of the Northeast and Mid-Atlantic states.V However, we anticipate that

for many of the terminal operators that occasionally receive such fuel, the number of such fuel

batches will not be great enough to justify the installation of marker injection equipment. 

Instead of adding the marker, such terminals would have the option of designating it as NRLM

through May 31, 2010, 500 ppm nonroad through May 31, 2012, 500 ppm NRLM from June 1,

2012 through May 31, 2014, or 500 ppm L&M beyond 2014. Any fuel designated as such could

still be sold as heating oil.

The final reason is that we believe that assigning areas outside of Northeast and MidAtlantic states to the Northeast/Mid-Atlantic Area would significantly diminish the intended

relief of the refinery flexibility provisions. Thus, we believe that implementation of the heating

oil marker requirement outside of the Northeast and Mid-Atlantic states would allow

implementation of refiner flexibilities that would be of substantial value to refiners in reducing

their compliance burden, especially small refiners who might otherwise find the burden of

compliance prohibitive, while resulting in an acceptably small burden to industry.

Based on our assessment discussed above, the following areas seemed the best candidates

for assignment to the Northeast/Mid-Atlantic Area: PADD 1A, PADD 1B, Virginia, North

Carolina, and the Eastern Panhandle of West Virginia. The following section discusses how we

further refined the definition of the Northeast/Mid-Atlantic Area based on our evaluation of the

distribution area of small refiners and additional input from the potentially affected industries.
Final Regulatory Impact Analysis

5-62

Input from refiners and other parties on the appropriate boundary of the Northeast/MidAtlantic Area.

A critical factor in defining the boundary of the Northeast/Mid-Atlantic Area is

evaluating its impact on small refiners’ access to the small-refiner provisions. Our evaluation of

the location of small refiners who will likely use these provisions indicates that one such small

refiner’s distribution area, in Northwestern Pennsylvania, is located within the aforementioned

areas. With the exception of this refinery, our evaluation indicated that assigning these areas to

the Northeast/Mid-Atlantic Area would not interfere with the use of the small-refiner provisions

or significantly reduce the value of the NRLM credit provisions. We sought input from the

range of potentially affected parties on this assessment and on how we might accommodate the

needs of the small refiner to have access to the small-refiner provisions while maintaining our

goal of minimizing the potential number of entities that would need to install injection

equipment and the volume of heating oil that would need to be marked. The parties that we

solicited input from include: the American Petroleum Institute, the National Petroleum Refiners

Association, the Ad Hoc Coalition of Small Refiners, the Independent Fuel Terminal Operators

Association (IFTOA), the Association of Oil Pipelines, the National Oil-heat Research Alliance,

Colonial Pipeline, Buckeye Pipeline, the American Refining Group, and Marathon-Ashland

Petroleum.

Based on these discussions, we determined that they the small-refiner flexibilities would

remain intact if the following counties were not assigned to the Northeast/Mid-Atlantic Area:

Chautauqua, Cattaraugus, and Allegany counties in New York, and Erie, Crawford, Warren

McKean, Potter, Mercer, Venango, Forest, Clarion, Elf, Jefferson, and Cameron counties in

Pennsylvania. These counties are located between the two arms of the Buckeye/Laurel pipeline

that project West into New York and Pennsylvania (see Figure 5.5.1.4.-2). There are many

terminals along the paths of these pipelines but none to our knowledge in the aforementioned

counties. Our review also indicates that it would be most consistent with current distribution

patterns to not assign the Pennsylvania border counties of Lawrence and Greene to the

Northeast/Mid-Atlantic Area. Thus, it appears that not assigning these counties to the

Northeast/Mid-Atlantic Area would not substantially increase the burden to terminal operators

and most closely conforms to the current patterns of product distribution. Input from the all the

parties we contacted was favorable to not assigning these counties to the Northeast/Mid-Atlantic

Area.

Conclusion:

Based on the above, we determined that the Northeast/Mid-Atlantic Area defined below

would minimize the number of terminals that would need to install new injection equipment and

the amount of fuel that would need to be marked, while preserving the benefits of the smallrefiner and credit high-sulfur NRLM provisions. All the industry representatives we contacted

stated that the definition of the Northeast/Mid-Atlantic Area in the final rule represents the best

balance of the various selection criteria and meets our stated goals in adopting the exclusion-area

approach. The areas excluded from the marker requirement and where the sale of fuel

manufactured under the credit and hardship provision is prohibited are: North Carolina, Virginia,
Fuel Standard Feasibility

W The Northeast/Mid-Atlantic Area is shaded.

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Maryland, Delaware, New Jersey, Connecticut, Rhode Island, Massachusetts, Vermont, New

Hampshire, Maine, Washington D.C., New York (except for the counties of Chautauqua,

Cattaraugus, and Allegany), Pennsylvania (except for the counties of Erie, Warren, Mc Kean,

Potter, Cameron, Elk, Jefferson, Clarion, Forest, Venango, Mercer, Crawford, Lawrence, Beaver,

Washington, and Greene), and the eight Eastern-most counties in West Virginia (namely:

Jefferson, Berkely, Morgan, Hampshire, Mineral, Hardy, Grant, and Pendleton). The

Northeast/Mid-Atlantic Northeast/Mid-Atlantic Area is illustrated in Figure 5.5.1.4-1.W

Figure 5.5.1.4.-1: Northeast/Mid-Atlantic Area 

5.5.2 Limiting Sulfur Contamination

The physical hardware and distribution practices for NRLM fuel does not differ

significantly from those for current highway diesel fuel. Therefore, we do not anticipate any

new issues with respect to limiting sulfur contamination during the distribution of 500 ppm

NRLM fuel that would not have already been accounted for in distributing highway diesel fuel. 

Highway diesel fuel has been required to meet a 500 ppm sulfur standard since 1993. Thus, we

expect that limiting contamination during the distribution of 500 ppm non-highway diesel engine

fuel can be readily accomplished by industry.

In the highway diesel rule, we acknowledged that meeting a 15 ppm sulfur specification

would pose a substantial new challenge to the distribution system. Refiners, pipelines and

terminals would have to pay careful attention to and eliminate any potential sources of
Final Regulatory Impact Analysis

5-64

contamination in the system (e.g., tank bottoms, dead legs in pipelines, leaking valves, interface

cuts, etc.) In addition, bulk plant operators and delivery truck operators would have to carefully

observe recommended industry practices to limit contamination, including things as simple as

cleaning out transfer hoses, proper sequencing of fuel deliveries, and parking on a level surface. 

The necessary changes to distribution hardware and practices and the associated costs are

detailed in the RIA to the highway diesel final rule.40

We are continuing to work with industry to ensure a smooth transition to the 15 ppm

sulfur standard for highway diesel fuel. In November of 2002, a joint industry-EPA Clean

Diesel Fuel Implementation Workshop was held in Houston, Texas. This workshop was cosponsored by a broad cross-section of trade organizations representing the diesel fuel producers

and distributors who will be responsible for compliance with the 15 ppm highway diesel

standard: the National Petroleum Refiners Association (NPRA), the Association of Oil Pipelines

(AOL), the Independent Fuel Terminal Operators Association (IFTOA), the National

Association of Conveniences Stores (NACS), the Society of Independent Gasoline Marketers of

America, and the Petroleum Marketers Association of America (PMAA). The workshop

featured over 20 presentations by industry the topic of distributing 15 ppm diesel fuel, as well as

a questions and answers discussion.41 Some of these presentations contained the results of the

first test programs conducted by the pipeline industry to develop procedures and identify the

changes needed to limit sulfur contamination. These initial test programs did not resolve all of

industry’s concerns related to the ability to limit sulfur contamination during the distribution of

15 ppm diesel fuel. However, the results were promising and indicated that with further testing

and development the distribution industry can successfully manage sulfur contamination during

the distribution of 15 ppm diesel fuel. We understand that the fuel distribution industry is in the

process of conducting such additional work and that there are plans to develop standard industry

practices for each segment of the distribution industry to limit sulfur contamination. We will

keep abreast of developments in this area.

Due to the need to prepare for compliance with the highway diesel program, we

anticipate that issues related to limiting sulfur contamination during the distribution of 15 ppm

NRLM diesel fuel will be resolved well in advance of the proposed 2010 implementation date

for 15 ppm sulfur standard for nonroad fuel. We are not aware of any additional issues that

might be raised unique to nonroad fuel. If anything we anticipate limiting contamination will

become easier. We expect that 15 ppm nonroad diesel fuel will be distributed in fungible

batches with 15 ppm highway diesel fuel up to the point when it leaves the terminal and nonroad

diesel fuel must be dyed per IRS requirements. The resulting larger batch sizes as a percentage

of the total 15 ppm diesel throughput may make it somewhat easier to limit sulfur contamination

and could reduce losses to product downgrade during transportation by pipeline. We also expect

that the projected absence of high-sulfur diesel fuel and heating oil in many pipeline systems will

lessen the opportunity for sulfur contamination. As a result, if anything the opportunity for

contamination should decline with the expansion of the 15 ppm pool to include nonroad and

L&M in addition to highway diesel fuel.
Fuel Standard Feasibility

5-65

5.5.3 Handling Practices for Distillate Fuels that Become Mixed in the Pipeline Distribution

System

The NRLM sulfur program in this rule raises two issues regarding the potential impact on

the current handling practices for diesel fuel that become mixed with other distillate fuels or with

gasoline during transport by pipeline (pipeline interface). The first pertains to whether there will

be suitable market for the diesel fuel that is recovered from these mixed products. The second

pertains to whether the requirements in this rule would interfere with the operations of transmix

processors. As discussed in the following sections, we included provisions in the NRLM

program to address these potential concerns.

Ensuring a Suitable Market for Diesel Fuel Recovered from Pipeline Interface

Fuel batches shipped by pipeline abut each other with no physical separation between the

batches. Consequently, mixing between the fuel batches that abut each other in the distribution

is unavoidable. When the volume in the mixing zone (interface) meets the specifications of one

of the two fuels being shipped next to each other, the interface is simply added to the batch of

that fuel. For example, the interface between regular and premium gasoline is added to the

regular grade batch. Or, the interface between jet fuel and heating oil is added to the heating oil

batch. One interface which is never added to either adjacent batch is a mixture of gasoline and

any distillate fuel, such as jet or diesel fuel. If this interface was added to the distillate batch, the

gasoline content in the interface would result in a violation of the distillate’s flash point

specification. If this interface was added to the gasoline batch, it would cause the gasoline to

violate its end point specification. Therefore, this interface must be shipped to a transmix

processor to separate the mixture into naphtha (a sub-octane gasoline) and distillate. The 2007

highway diesel fuel program will not change this practice. Most of the naphtha produced by

transmix processors from gasoline/distillate mixtures is usually blended with premium gasoline

to produce regular grade gasoline. The heaviest portion of this naphtha is typically cut into the

distillate fuel produced so as to lessen the impact on octane (and the resulting need to blend in

premium gasoline to make regular gasoline). The distillate produced is an acceptable high-sulfur

diesel fuel or heating oil, though if the feed material was primarily low-sulfur distillate and

gasoline it will likely also meet the current 500 ppm highway fuel cap.

The interface between jet fuel and highway diesel can not be cut into jet fuel due to end

point and other concerns. However, it can usually be cut into 500 ppm diesel fuel as long as the

sulfur level of the jet fuel is not too high. With the lowering of the highway standard to 15 ppm,

however, this will no longer be possible. We expect that pipelines minimize this interface by

abutting jet fuel and high-sulfur distillate in the pipeline whenever possible. However, it will be

unavoidable under many circumstances. A substantial part of the pipeline distribution system

currently does not handle high-sulfur distillate. We expect that the highway program and this

final rule will cause additional pipeline systems to discontinue carrying high-sulfur distillate. 

Pipelines that do not carry high-sulfur distillates will generate this interface whenever they ship

jet fuel. Under the highway program and this final rule, we project that pipeline operators will

segregate this interface by cutting it into a separate storage tank. Because this interface can be

sold as 500 ppm NRLM fuel or heating oil without reprocessing, and because these markets exist
Final Regulatory Impact Analysis

X The costs are not significantly different from 2010-2012 than they are from 2012-2014.

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nationwide, there is little impact beyond the need for refiners to produce more 15 ppm highway

diesel fuel to offset the downgraded volume, which was considered as part of the refining costs

in the highway diesel rule.

With control of nonroad diesel fuel to 15 ppm sulfur in 2010, and L&M in 2012, the

opportunities to downgrade interface to another product become increasing limited. Where

limited this will increase costs due to the need to transport the interface to where it can be

marketed or to a facility for reprocessing. In areas with large heating oil markets, such as the

Northeast and the Gulf Coast, the control of NRLM sulfur content will still have little impact on

the sale of this interface. However, in areas lacking a large heating oil market, the sale of this

distillate interface will be more restricted. Because this interface will be composed of 15 ppm

diesel fuel and jet fuel, we estimate that the distillate interface created should nearly always meet

a 500 ppm cap. Thus, this interface can be added to 500 ppm NRLM batches (as well as heating

oil, where it is present at the terminal) through 2014. After 2014, this 500 ppm interface fuel can

only be sold as L&M fuel or heating oil. 

In Chapter 7 of the Final RIA, we estimate the costs related to handling this interface fuel

during the three time periods (2007-2010, 2010-2014X, and 2014 and beyond). We project that

there will be no additional costs prior to 2010, as 500 ppm fuel will be the primary NRLM fuel

and be widely distributed. Beyond 2010, we estimate that some terminals will have to add a

small storage tank (or dedicate an existing tank) for this fuel, as 500 ppm highway diesel fuel

and the majority of 500 ppm nonroad disappears from the distribution system. In many places,

this interface will be the primary, if not sole source of 500 ppm fuel, so existing tankage for this

interface will be limited. We have also added shipping costs to transport this fuel to NRLM and

heating oil users. The volume of this interface is significant, sometimes a sizeable percentage of

the combined NRLM fuel and heating oil markets. In the post-2014 period, the volume of this

interface fuel is larger than the combined L&M fuel and heating oil markets in certain PADDs. 

Also, the volume of interface received at each terminal will vary substantially, depending on

where that terminal is on the pipeline. The advantage of this is that where the interface

accumulates it may be of sufficient volume to justify marketing as a separate grade of fuel. 

Conversely, the potential users of this 500 ppm interface fuel may not be located near the

terminals with the fuel necessitating additional transportation costs.

Prior to 2014, 500 ppm fuel can be used as NRLM fuel and heating oil. Additional

storage tanks will be needed in some cases, as this will be the only source of 500 ppm fuel in the

marketplace. There will also be additional costs associated with transporting this 500 ppm to an

appropriate end-user. Starting in 2014, this interface fuel can no longer be sold to the nonroad

fuel market. Since the interface volume does not change, this increases the proportion which

gets sold to the L&M and heating oil markets. Thus, overall, transportation distances and costs

will likely increase. We also estimate that some fuel will have to be shipped back to refineries

and reprocessed to meet a 15 ppm cap and shipped out a second time.
Fuel Standard Feasibility

5-67

By allowing the 500 ppm fuel to continue to be sold into the NRLM market until 2014

and into the L&M market thereafter, the final rule removes issues regarding the feasibility of

handling this material. Without these provisions, a substantial portion of this fuel would need to

be returned to the refinery for reprocessing raising significant cost issues, since the material

would need to be transported by truck in many cases and it might be difficult to locate refiners

willing to reprocess all of the volume. As discussed above there will be some additional

transportation costs to deliver such 500 ppm to a suitable market and a limited volume will need

to be reprocessed starting in 2014. However, as discussed in Chapter 7 of this RIA, we expect

the associated costs will be modest and can be accommodated by fuel distributors. 

The Potential Impact on Transmix Processors

There are two issues regarding the potential impact of this rule on transmix processors. 

The first pertains to whether a transmix processor should be subject to the requirements

applicable to all refiners. The second pertains to whether the heating oil marker requirements

will restrict their ability sell the distillate fuels they produce into non-heating oil markets 

As discussed above, some pipeline interfaces do not meet the specifications for sale into

any end-use market. In such cases the interface is referred to as transmix and delivered to a

transmix processor for separation into marketable products. Transmix processors operate

distillation towers that separate the gasoline/distillate mixture into their component parts:

gasoline and distillate fuel (as discussed above). Transmix processors possess no facilities with

which to remove sulfur from fuel and it currently would be burdensome for them to install such

equipment. For example, they do not have access to any hydrogen for desulfurization like at a

typical refinery. Based on these realities, we believe that it would be inappropriate to treat

transmix processors as refiners with respect to compliance with the sulfur standards under this

rule. Consequently, the final rule provides that transmix processors may produce fuels for sale

into the NRLM markets that meet the applicable small-refiner provisions as long as they remain

in effect. After the NRLM small-refiner provisions expire in 2014, transmix processors may

continue to sell 500 ppm fuel into the L&M market as discussed above. This allows 500 ppm

fuel produced by transmix processors to stay in the diesel fuel market and avoids the costs that

would accrue other wise. The final rule also amends the highway program to allow similar

flexibility for transmix processors. Consequently, there are no feasibility issues associated with

transmix processors.

Transmix processors stated that the presence of a marker in heating oil would limit the

available markets for their reprocessed distillates. The feed material for transmix processors

primarily consists of the interface mixing zone between batches of fuels that abut each other

during shipment by pipeline where this mixing zone can not be cut into either of the adjacent

products. If marked heating oil was shipped by pipeline, the source material for transmix

processors fed by pipelines that carry heating oil would contain SY-124. Transmix processors

stated that it would be prohibitively expensive to segregate pipeline-generated transmix

containing the marker from that which does not contain the marker prior to processing, and that

they could not economically remove the marker during reprocessing. Thus, in cases where the

marker would be present in a transmix processor’s feed material, they would be limited to
Final Regulatory Impact Analysis

YHeating oil sold inside the Northeast/Mid-Atlantic Area finalized under today’s rule does not need to contain a

marker (see Section IV.D. of today’s preamble). 

5-68

marketing their reprocessed distillate fuels into the heating oil market. Since the final rule

requires that the marker be added at the terminal gate (rather than at the refinery gate), the feed

material that transmix processors receive from pipelines will not contain the marker. Hence,

they will not typically need to process transmix containing the heating oil marker, and today’s

marker requirement is not expected to significantly alter their operations. There is little

opportunity for marker contamination of non-heating oil fuel to occur at the terminal and further

downstream. In the rare instances where this might occur, the fuel contaminated would likely

also be a distillate fuel, and thus could be sold into the heating oil market without need for

reprocessing.

5.6 Feasibility of the Use of a Marker in Heating Oil

As discussed in Section IV.D. of the preamble, to ensure that heating oil is not shifted

into the NRLM market, we need a way to distinguish heating oil from high-sulfur NRLM

produced under the small-refiner and credit provisions. Currently, there is no differentiation

today between fuel used for NRLM uses and heating oil. Both are typically produced to the

same sulfur specification, and both are required to have the same red dye added prior to

distribution from downstream of the terminal. Based on recommendations from refiners, in the

NPRM, we concluded that the best approach to differentiate heating oil from high-sulfur NRLM

would be to require that a marker be added to heating oil at the refinery gate. Since the proposal

we received additional information which allows us to rely upon recordkeeping and reporting

provisions to differentiate heating oil from high-sulfur NRLM up the point where it leaves the

terminal (see Section IV.D. of the preamble to the final rule). The final rule therefore requires

that a marker be added to heating oil before it leaves the terminal, rather than proposed approach

of requiring it to be added at the refinery gate.Y

Terminal operators suggested that we might also be able to rely on recordkeeping and

reporting downstream of the terminal to differentiate heating oil from high-sulfur NRLM,

thereby eliminating any need for a marker in heating oil. However, we believe such

recordkeeping and reporting mechanisms would be insufficient to keep heating oil out of the

NRLM market downstream of the terminal under typical circumstances. We can rely on such

measures before the fuel leaves the terminal, because it is feasible to require all the facilities in

the distribution system to send us reports describing their fuel transfers. As discussed in Section

IV.D of the preamble to the final rule, we can compare these electronic reports to identify parties

responsible for shifting heating oil into the NRLM market. Downstream of the terminal the

parties involved in the fuel distribution system become far too numerous for such a system to be

implemented and enforced (including jobbers, bulk plant operators, heating oil dealers, retailers,

and including farmers. Reporting errors for even a small fraction would require too many

resources to track down and correct and would eliminate the effectiveness of the system.

Our proposal envisioned that a fuel marker would be required in heating oil from June 1,
Fuel Standard Feasibility

Z

 Opinion on Selection of a Community-wide Mineral Oils Marking System, (“Euromarker”), European Union

Scientific Committee for Toxicity, Ecotoxicity and the Environment plenary meeting, September 28, 1999.

5-69

2007 through May 31, 2010, and that the same marker would be required in locomotive and

marine fuel from June 1, 2010 through May 1, 2014. As a consequence of finalizing a 15 ppm

sulfur standard for locomotive and marine fuel in 2012 we are now requiring the use of a marker

in locomotive and marine fuel from 2010-2012. However, we are also requiring the continued

use of the marker in heating oil indefinitely (see Section IV of the preamble to the final rule).

We proposed and are finalizing that solvent yellow 124 (SY-124) must be added to

heating oil beginning June 1, 2007, and to 500 ppm sulfur L&M diesel fuel produced or

imported from June 1, 2010 through May 31, 2012 at a concentration of 6 milligrams per liter

(mg/l). The chemical composition of SY-124 is as follows: N-ethyl-–[2-[1-(2-

methylpropoxy)ethoxyl]-4-phenylazo]-benzeneamine.Z

 This concentration is sufficient to ensure

detection of SY-124 in the distribution system, even if diluted by a factor of 50. Any fuel found

with a marker concentration of 0.10 milligrams per liter or more will be presumed to be heating

oil from June 1, 2007 through May 31, 2010, and after May 31, 2012. From June 1, 2010

through May 31, 2012, any fuel found to contain a marker concentration of 0.10 milligrams per

liter or less will be considered heating oil if its sulfur content is above 500 ppm, or L&M diesel

fuel if its sulfur content is below 500 ppm. Below a concentration of 0.10 mg/L, the prohibition

on the use of fuel containing the marker does not apply.

There are a number of other types of dyes and markers. Visible dyes are most common,

are inexpensive, and are easily detected. Using a second dye in addition to the red dye required

by IRS in all non-highway fuel for segregation of heating oil based on visual identification raises

certain challenges. The marker that we require under today’s rule must be different from the red

dye currently required by IRS and EPA and not interfere with the identification of red dye in

distillate fuels. Invisible markers are beginning to see more use in branded fuels and are

somewhat more expensive than visible markers. Such markers are detected either by the

addition of a chemical reagent or by their fluorescence when subjected to near-infra-red or

ultraviolet light. Some chemical-based detection methods are suitable for use in the field. 

Others must be conducted in the laboratory due to the complexity of the detection process or

concerns regarding the toxicity of the reagents used to reveal the presence of the marker. Nearinfra-red and ultra-violet fluorescent markers can be easily detected in the field using a small

device and after brief training of the operator. There are also more exotic markers available such

as those based on immunoassay, and isotopic or molecular enhancement. Such markers typically

need to be detected by laboratory analysis.

We selected SY-124, however, for a number of reasons:

1) There is considerable data and experience with it which indicates there are no

significant issues with its use.

2) It is compatible with the existing red dye

3) Test methods exist to quantify its concentration, even if diluted by a factor of 50

to 1
Final Regulatory Impact Analysis

AA The European Union marker legislation, 2001/574/EC, document C(2001) 1728, was published in the

European Council Official Journal, L203 28.072001.

BBThe color of distillate fuel can range from near water white to a dark blackish brown but is most frequently

straw colored.

5-70

4) It is reasonably inexpensive

5) It can be produced and provided by a number of sources

Effective in August 2002, the European Union (EU) enacted the requirement that SY-124

be added at 6 mg/l to diesel fuel that is taxed at a lower rate in all EU member states.AA Solvent

yellow 124 is referred to as the “Euromarker” in the EU. The EU has found this treatment rate to

be sufficient for their enforcement purposes while not interfering with the identification of the

various different colored dyes required by different EU member states (including the same red

dye that is required in the U.S.). Despite its name, solvent yellow 124 does not impart a strong

color to diesel fuel when used at a concentration of 6 mg/l. Most often it is reportedly nearly

invisible in distillate fuel given that the slight yellow color imparted is similar to the natural

color of many distillate fuels.BB In the presence of red dye, SY-124 can impart a slight orange

tinge to the fuel. However, it does not interfere with the visual identification of the presence of

red dye or the quantification of the concentration of red dye in distillate fuel. Thus, the use of

SY-124 at 6 mg/l in diesel fuel should not interfere with the use of the red dye by IRS to identify

non-taxed fuels.

Solvent yellow 124 is chemically similar to other additives used in gasoline and diesel

fuel, and EPA has registered it as a fuel additive under 40 CFR part 79. Therefore, we expect

that its products of combustion would not have an adverse impact on emission control devices,

such as a catalytic converter. Extensive evaluation and testing of solvent yellow 124 was

conducted by the European Commission. This included combustion testing which showed no

detectable difference between the emissions from marked and unmarked fuel. Norway

specifically evaluated the use of distillate fuel containing solvent yellow 124 for heating

purposes and determined that the presence of the Euromarker did not cause an increase in

harmful emissions from heating equipment. Based on the European experience with solvent

yellow 124, we do not expect that there would be concerns regarding the compatibility of solvent

yellow 124 in the U.S. fuel distribution system or for use in motor vehicle engines and other

equipment such as in residential furnaces. 

Our evaluation of the process conducted by the EU in selecting the SY-124 for use in the

EU convinced us that SY-124 was also the most appropriate marker to propose for use in heating

oil under the final rule. We received a number of comments expressing concern about the use of

SY-124. Based on our evaluation of these comments (summarized below and in the Summary

and Analysis of Comments), we continue to believe that SY-124 is the most appropriate marker

to specify for use under today’s rule. The final rule therefore requires that, beginning June 1,

2007, SY-124 be added to heating oil, and from June 1, 2020 through May 31, 2012, SY-124 be

added to LM diesel fuel produced at a refinery or imported at a concentration of 6 mg/l before

the fuel leaves the terminal, except in the Northeast/Mid-Atlantic Area and Alaska.
Fuel Standard Feasibility

CCSee the Summary and Analysis of Comments for a more detailed discussion of our response to concerns about

the possible contamination of jet fuel with the heating oil marker.

5-71

The concerns regarding the use of SY-124 primarily pertained to: the potential impact on

jet engines if jet fuel were contaminated with SY-124; the potential health effects of SY-124

when used in fuel for heating purposes, particularly for unvented heaters; the potential cost

impact on fuel distributors and transmix processors; and the potential conflict with IRS red dye

requirements.

The American Society of Testing and Materials (ASTM), the Coordinating Research

Council (CRC), and the Federal Aviation Administration (FAA) requested that we delay

finalizing the selection of a specific marker for use in this final rule. They requested that

selection of a specific marker should be deferred until testing could be conducted regarding the

potential impact of SY-124 on jet engines. The Air Transport Association stated that we should

conduct an extensive study regarding the potential for contamination, determine the levels at

which the marker will not pose a risk to jet engines, and seek approval of SY-124 as a jet fuel

additive. Other parties, including the Department of Defense (DoD), also stated that we should

refrain from specifying marker under this rule until industry and other potentially affected parties

can recommend an appropriate marker. Representatives of the heating oil industry expressed a

concern that we had not conducted an independent review regarding the safety/suitability of SY124 for use in heating oil.

We met and corresponded with numerous and diverse parties to evaluate the concerns

expressed regarding the use of SY-124, and to determine whether it might be more appropriate to

specify a different marker for use under today’s rule. These parties include IRS, FAA, ASTM,

CRC, various marker/dye manufacturers, European distributors of fuels containing the

Euromarker, marker suppliers, and members of all segments in the U.S. fuel distribution system. 

We believe that concerns related to potential jet fuel contamination have been sufficiently

addressed for us to finalize the selection of SY-124 as the required marker in this rule.CC As

discussed in Section IV.D of the preamble to the final rule, changes in the structure of the fuel

program since the proposal have allowed us to move the point where the marker must be added

to from the refinery gate to the terminal. The vast majority of concerns regarding the potential

for contamination of jet fuel with SY-124 pertained to the shipment of marked heating oil by

pipeline. All parties were in agreement that nearly all the potential for marker contamination of

jet fuel would disappear if the point of marker addition was moved to the terminal. We spoke

with terminal operators, both large and small, who confirmed that they maintain strictly

segregated distribution facilities for red dyed fuel and jet fuel because of jet fuel contamination

concerns. The same type of segregation practices can be readily adapted regarding the handling

of marked heating oil and jet fuel, and would be equally effective in limiting contamination of jet

fuel with SY-124. Downstream of the terminal, the only other chance for marker contamination

of jet fuel pertains to bulk plant operators and jobbers that handle marked fuel and jet fuel. For

the most part, these parties also currently maintain strict segregation of the facilities used to

transport jet fuel and heating oil (or L&M fuel that will be marked under toady’s rule). The one
Final Regulatory Impact Analysis

5-72

exception is that small bulk plant operators that supply small airports sometimes use the same

tank truck to alternately transport jet fuel and heating oil. In such cases, they flush the tank

compartment prior to transporting jet fuel to remove any residual heating oil left behind after the

tank is drained. We do not expect that bulk plant operators will handle marked L&M diesel fuel.

The final rule requires that fuel which is required to contain the marker must also contain

red dye. Therefore, the "white bucket" test that distributors currently use to detect red dye

contamination of jet fuel can also be relied upon to detect marker contamination of jet fuel. 

Based on the above discussion, we concluded that the marker requirements under today’s rule

would not significantly increase the likelihood of jet fuel contamination, and that when such

contamination might occur, it could be readily identified without the need for additional testing. 

Our finalization of the Northeast/Mid-Atlantic Area in (see Section IV.D. of the preamble to the

final rule) also minimizes potential concerns regarding the potential that jet fuel may become

contaminated with the marker since no marker is required in heating oil (or 500 ppm L&M diesel

fuel produced by refiners or imported from 2010-2012) in this area and there is expected to be

little heating oil used outside of the Northeast/Mid-Atlantic Area. 

This final rule requires addition of the marker at the terminal rather than the refinery gate

as proposed. Based on this change, ASTM withdrew its request to delay finalization of the

marker requirements in this rule. However, ASTM stated that some concern remains regarding

jet fuel contamination downstream of the terminal (due to the limited use of the same tank

wagons to alternately transport jet fuel and heating oil discussed above). Nevertheless, ASTM

related that these concerns need not delay finalization of the marker requirements in this rule. 

ASTM intends to support a CRC program to evaluate the compatibility of markers with jet fuel. 

FAA is also undertaking an effort to identify fuel markers that would be compatible for use in jet

fuel. We commit to a review of the use of SY-124 in the future based on the findings of the

CRC and the FAA, experience with the use of SY-124 in Europe, and future input from ASTM

or other concerned parties. If alternative markers are identified that do not raise concerns

regarding the potential contamination of jet fuel, we will initiate a rulemaking to evaluate the use

of one of these markers in place of SY-124.

After 2010, today’s rule removes the current EPA refinery gate requirement that any

diesel fuel that not meet the specifications for highway diesel fuel must contain visible evidence

of red dye (40 CFR § 80.520(b)(2)). This requirement means that diesel fuel which does not

meet highway diesel specifications must currently be dyed before it is shipped by pipeline from

the refinery. As a result of the implementation of today’s rule, we do not expect that any red

dyed fuel will be shipped by pipeline due to the need to comply with EPA requirements after

2010. Based on this change, we expect that today’s rule will actually result in an overall

reduction in the potential for jet fuel to become contaminated with azo dyes such as red dye and

SY-124. 

Since the NPRM, no new information has been provided which indicates that the

combustion of SY-124 in heating equipment would result in more harmful emissions than when

combusted in engines, or would result in more harmful emissions than combustion of unmarked

heating oil. The European experience with the use of solvent yellow 124 and the evaluation
Fuel Standard Feasibility

DDTerminals that manufacture 500 ppm diesel fuel by blending 15 ppm and high-sulfur fuel are treated as a

refiner under the final rule. They must also comply with all applicable designate and track requirements, antidowngrading provisions, and other applicable requirements (see Section IV.D of the preamble to the final rule). 

5-73

process it underwent prior to selection by the EU, provides strong support regarding the

compatibility of SY 124 in the U.S. fuel distribution system, and for use in motor vehicle engines

and other equipment such as in residential furnaces. We believe that hypothesized concerns

regarding health impacts from the use of SY-124 do not present sufficient cause to delay

finalization of the marker requirements under today’s rule.

The European Union intends to review the use of Solvent yellow 124 after December

2005, but may undertake the review earlier if any health and safety or environmental concerns

about its use are raised. We intend to keep abreast of such activities and may initiate our own

review of the use of solvent yellow 124 depending on the European Union’s findings, or other

relevant information. There will be nearly four years of accumulated field experience with the

use of SY-124 in Europe at the time of the review by the EU and nearly 5 years by

implementation of the marker requirement under this rule. This will provide ample time to

identify any new issues with SY-124 and to choose a different marker if warranted.

Commenters stated that potential health concerns regarding the use of SY-124 might be

exacerbated with respect to its use in unvented space heaters. Commenters further stated that

there are prohibitions against the dying of kerosene (No. 1 diesel) used in such heaters. No

information was provided to support these concerns, however, and we have no information to

suggest any health concerns exist regarding the use of SY-124 in unvented heaters. 

Nevertheless, even if there were such concerns, this rule will not require SY-124 to be used in

the fuel used in unvented heaters. Furthermore, this rule does not require that SY-124 be added

to kerosene. This resolves most of what concern might remain regarding this issue, since

kerosene is the predominate fuel used in unvented heaters. However, the DoD stated that diesel

fuel is sometimes used in its tent heaters and expressed concern regarding the presence of SY124 in fuel used for this purpose. We understand that to simplify the DoD fuel distribution

system, it is DoD policy to use a single fuel called JP-8 for multiple purposes where practicable,

including space heating. Neither JP-8 not diesel fuel used for such a purpose would not be

subject to the heating oil marker requirement in this rule.

We believe that the concerns expressed regarding the potential impact on distributors and

transmix processors from the presence of SY-124 in heating oil have been addressed by moving

the point of marker addition to the terminal. Terminal operators stated that they desire the

flexibility to blend 500 ppm diesel fuel from 15 ppm diesel fuel and heating oil. This practice

would have been prevented by the proposed addition of the marker at the refinery gate. Under

the final rule, terminal operators will have access to unmarked high-sulfur fuel with which to

manufacture 500 ppm diesel fuel by blending with 15 ppm diesel fuel.DD 

Transmix processors stated that the presence of a marker in heating oil would limit the

available markets for their reprocessed distillates. The feed material for transmix processors
Final Regulatory Impact Analysis

EEPhone conversation between Carl Dalton, IRS and Jeff Herzog, EPA February 19, 2004.

5-74

primarily consists of the interface mixing zone between batches of fuels that abut each other

during shipment by pipeline where this mixing zone can not be cut into either of the adjacent

products. If marked fuel was shipped by pipeline, the source material for transmix processors

fed by pipelines that carry heating oil (or marked L&M diesel fuel) would contain SY-124. 

Transmix processors stated that it would be prohibitively expensive to segregate pipelinegenerated transmix containing the marker from that which does not contain the marker prior to

processing, and that they could not economically remove the marker during reprocessing. Thus,

in cases where the marker would be present in a transmix processor’s feed material, they would

be limited to marketing their reprocessed distillate fuels into the heating oil market (or the L&M

market from 2010-2012 if the fuel met a 500 ppm sulfur specification). Since the final rule

requires that the marker be added at the terminal gate (rather than at the refinery gate), the feed

material that transmix processors receive from pipelines will not contain the marker. Hence,

they will not typically need process transmix containing the marker, and the marker requirement

is not expected to significantly alter their operations. There is little opportunity for marker

contamination of fuels that are required to be marker free to occur at the terminal and further

downstream. In the rare instances where this might occur, the fuel contaminated would likely

also be a distillate fuel, and thus could be sold into the heating oil market (or the L&M market

from 2010-2012 if the fuel met a 500 ppm sulfur specification) without need for reprocessing.

We do not expect that the marker requirement will result in the need for additional fuel

storage tanks or tank trucks in the distribution system. As discussed in Section VI.A of the

preamble to the final rule, we project that implementation of the NRLM sulfur standards will

result in the need for additional storage tanks and tank truck demanifolding at a limited number

of bulk plant facilities. The marker requirement does not add another criteria apart from the

sulfur content of the fuel which would force additional product segregation. 

As discussed above, industry has expressed concern about the use of the same tank trucks

to alternately transport marked fuel and jet fuel. We do not expect that the addition of marker to

heating oil (and 500 ppm sulfur diesel fuel produced by refiners or imported from 2010-2012)

will exacerbate these concerns. However, depending on the outcome of the aforementioned

CRC program, the fuel marker requirements under today’s rule may hasten the current trend to

avoid the use of tank trucks to alternately transport jet fuel and heating oil (or L&M diesel fuel

to the extent that this occurs today). To the extent that this does occur, we do not expect that it

would result in substantial additional costs since few tank truck operators currently use the same

tank truck compartments to alternately transport heating oil and jet fuel and we are aware of no

instances where tank truck operators currently use the same tank truck compartments to

alternately transport L&M diesel fuel and jet fuel.

Through our discussions with the IRS, we have confirmed that the presence of SY-124

will not interfere with enforcement of their red dye requirement.EE Although, SY-124 may

impart a slight orange tint to red-dyed diesel fuel, this will not complicate the identification of

the presence of the IRS red dye. In fact, IRS has determined that the presence of SY-124 may
Fuel Standard Feasibility

FFibid

5-75

even enhance enforcement of their fuel tax program.FF However, as identified in the comments,

implementation of the marker requirement for heating oil arguably may be in conflict with IRS

regulations at 26 CFR 48.4082-1(b), which states that no dye other than the IRS-specified red

dye must be present in untaxed diesel fuel. IRS is evaluating what actions might be necessary to

clarify that the addition of SY-124 to heating oil would not be in violation of IRS regulations. 

IRS related that they are investigating a family of markers for potential use in addition to red dye

under their diesel tax program which might be compatible with jet fuel. IRS stated that the use

of one of the markers in this family under this rule might result in a reduced burden on industry. 

Given the changes reflected in the final rule, the marker provisions will not impose a significant

burden. However, if the IRS program were to develop alternate markers that would be

compatible with jet fuel, we will initiate a rulemaking to evaluate the use of one of these markers

in place of SY-124 for heating oil.

Commenters also expressed concerns regarding the proprietary rights related to the

manufacture and use of SY-124, and stated that we should adopt a nonproprietary marker if

possible. The proprietary rights related to SY-124 expire several months after implementation of

the marker requirements in this rule. Therefore, we do not expect that the current proprietary

rights regarding SY-124 are a significant concern. Commenters also stated that our estimated

cost of SY-124 in the NPRM (0.2 cents per gallon of treated fuel) was high compared to other

markers that cost hundredths of a cent a gallon. Since the proposal we have obtained more

accurate information which indicates that the current cost of bulk quantities of SY-124 is

approximately 0.03 cents per gallon of treated fuel (see Section 7.4. of this RIA). Based on

conversations with various marker manufacturers, this cost is comparable to or less than other

fuel markers.

5.7 Impacts on the Engineering and Construction Industry

An important aspect of the feasibility of any fuel quality program is the ability of the

refining industry to design and construct any new equipment required to meet the new fuel

quality standard. In this section we assess the impact of the final NRLM fuel program on

engineering design and construction personnel needs. Specifically, we focus on three types of

workers: front-end designers, detailed designers and construction workers needed to design and

build new desulfurization equipment. In doing this, we consider the impacts of the Tier 2

gasoline sulfur and the 2007 highway diesel sulfur programs on these same types of personnel. 

We compare the overall need for these workers to estimates of total employment in these areas. 

In general, it would also be useful to expand this assessment to specific types of construction

workers which might be in especially high demand, such as pipe-fitters and welders. However,

estimates of the number of people currently employed in these job categories are not available. 

Thus, it is not possible to determine how implementing the nonroad diesel fuel sulfur cap and

other programs might stress the number of personnel needed in specific job categories.

To accomplish this task, we first estimated the level of design and construction resources
Final Regulatory Impact Analysis

5-76

related to revamped and new desulfurization equipment. We next projected the number of

revamped and new desulfurization units which would be needed under the final NRLM fuel

program. Then, we developed a schedule for how desulfurization projects due to be completed

at the same time might be spread out during the year. We next developed a time schedule for

when the various resources would be needed throughout each project. Finally, we project the

level of design and construction resources needed in each month and year from 2004 and 2014

and compare this to the number of people employed in each job category.

5.7.1 Design and Construction Resources Related to Desulfurization Equipment

The number of job-hours necessary to design and build individual pieces of equipment

and the number of pieces of equipment per project were taken from an NPRA technical paper by

Moncrief and Ragsdale.42 Their study was performed to support a recent National Petroleum

Council study of gasoline and diesel fuel desulfurization, as well as other potential fuel quality

changes.43 These estimated job hours are summarized in Table 5.7-1.

Table 5.7-1

Design and Construction Factors for Desulfurization Equipment

Gasolinea Highway and

Nonroad

Diesel

Treaters

Highway and

Nonroad

Diesel

Treaters

New

Hydrotreater

New

Hydrotreater

Revamp

Existing

Hydrotreater

Number of Pieces of Equipment per Refinery 60 60 30

Job hours per piece of equipmenta

 Front End Design 300 300 150

 Detailed Design 1200 1200 600

 Direct and indirect construction 9150 9150 4575

a

 Revamped equipment estimated to require half as many hours per piece of equipment. All gasoline treaters for Tier 2

compliance are assumed to be new. 

As discussed in Section 5.3.2, we projected that the lead time for NRLM hydrotreater

modifications can be shortened relative to that required by other fuel programs due to refiners

combining their efforts to comply with this NRLM fuel rule with those for the 2007 highway

diesel fuel program. These tasks include scoping and corporate screening studies, technology

evaluation and permit approvals. We did not, however, reduce the level of E&C personnel

required for the NRLM fuel program to reflect these synergies. Thus, the above resource

requirements are conservative in this regard. The primary reason for the lack of impact is that

the 2007 implementation date for the 500 ppm NRLM standard is later than the primary 2004-

2006 phase-in period for the Tier 2 gasoline and the 2006 implementation date for the 15 ppm
Fuel Standard Feasibility

5-77

highway diesel fuel standard.

5.7.2 Number and Timing of Revamped and New Desulfurization Units

In the Final Regulatory Impact Analysis for the 2007 highway diesel program, we

estimated the number of new and revamped desulfurization units projected for both the Tier 2

and highway diesel fuel programs.44 We subsequently received pre-compliance reports for each

refinery in the country regarding their plans for complying with the highway diesel program. In

most cases the information was preliminary, but never the less sufficient to provide a better

estimate of the number and timing of new diesel desulfurization units becoming operational, as

shown in Table 5.7-2. We simplified our highway program analysis by assuming that refineries

who comply early and produce 15 ppm fuel before 2006 will invest to produce highway fuel in

year 2006.

Table 5.7-2

Number of Gasoline and Highway Diesel Desulfurization Units Becoming Operationala45

Fuel Type and Stage Before

2004

2004 2005 2006 2007 2008 2009 2010

New gasoline desulfurization units 10 37 6 26 5 3 4 6

Highway Diesel Desulfurization Units

(80% revamps, 20% new)

96 5

a

 Units become operational on January 1st for gasoline desulfurization and June 1st for highway diesel desulfurization

units.

The next step was to estimate the types of equipment modifications necessary to meet the

final rule NRLM fuel requirements. This was a complex task, due to the overlap of the highway

and NRLM fuel programs and the fact that refiners’ relative production of highway and highsulfur distillate fuel varies dramatically. In our assessment of the cost of this rule (see Chapter

7), we separated refineries which produce high-sulfur distillate into three categories and assessed

their need for new or revamped desulfurization equipment separately. These three categories (as

also discussed in Section 7.2.1) are: highway refiners (95% or more of their no. 2 distillate

production meets highway diesel fuel specifications), high-sulfur refiners (5% or less of their no.

2 distillate production meets highway diesel fuel specifications), and mix refiners (producers of

high-sulfur distillate fuel not falling into one of the other categories). In Section 7.2.2.2, we

describe in detail how we projected the number of refiners which would build new hydrotreaters

or revamp existing hydrotreaters by calendar year in response to the final NRLM sulfur program. 

In applying the results of the cost analysis, we assumed that new hydrotreaters designed

to produce 500 ppm NRLM fuel would utilize the level of personnel for a new unit listed in the

table above. In those cases where a refiner produced 15 ppm NRLM fuel in one step, they would

utilize this same level of personnel. However, when a hydrotreater capable of producing 500

ppm was modified to produce 15 ppm NRLM fuel, either using conventional or Process
Dynamics technology, we assumed that the personnel levels for a revamp applied.

Table 5.7-3 presents the results of this analysis for the 63 refineries which we project will

produce 500 ppm and 15 ppm NRLM diesel fuel under the final program.

Table 5.7-3

Number and Timing of NRLM Desulfurization Units 

2007 2008 2009 2010 2011 2012 2013 2014

Revamped Hydrotreater 0 17 9 14

New Hydrotreater 28 24 6 2

5.7.3 Timing of Desulfurization Projects Starting up in the Same Year

A worst-case assumption would be that all the units scheduled to start up on January 1 for

gasoline and June 1 for diesel would begin and complete their design and construction at the

exact same time. However, this is not reasonable for a couple of reasons. Our early credit

programs for gasoline, highway and nonroad diesel production will entice some refiners to make

treater modifications ahead of our program startup dates thus shifting E&C workload ahead for

these refiners. Also, an industry-wide analysis such as this one assumes that all projects take the

same amount of effort and time. This means that each refinery is using every specific type of

resource at exactly the same time as other refineries with the same start-up date. However, in

reality, refineries’ projects will differ in complexity and scope. Even if they all desired to

complete their project on the same date, their projects would begin over a range of months. 

Thus, two projects scheduled to start up at exactly the same time are not likely to proceed

through each step of the design and construction process at the same time. Second, the design

and construction industries will likely provide refiners with economic incentives to avoid

temporary peaks in the demand for personnel. 

For these reasons, we spread out the design and construction of units expected to start up

in the same calendar year. We assumed that 25 percent of the units would initiate design and

thus, start up each quarter leading up to the date upon which they had to be operating. 

5.7.4 Timing of Design and Construction Resources Within a Project

The next step in this analysis was to estimate how the engineering and construction

resources are spread out during a project. We developed a distribution of each type of resource

across the duration of a project for the Tier 2 gasoline and 2007 highway diesel sulfur programs. 

The fractions of total hours expended each month were derived as follows.

Per Moncrief and Ragsdale, front end design typically takes six months to complete.46 If

25 percent of the refineries scheduled to start up in a given year start their projects every quarter,

each subsequent group of the refineries starts when the previous group is halfway through their

front end design. Overall, front end design for the four groups covers a period of 15 months, or

6 months for the first group plus 3 months for each of the three subsequent groups. In spreading

this work out over the 15 months, we assumed that the total engineering effort would be roughly

equal over the middle 9 months. The effort during the first and last 3 month period would be
Fuel Standard Feasibility

5-79

roughly two-thirds of that during the peak middle months. The same process was applied to the

other two job categories. The reader is referred to the Final RIA for the 2007 highway diesel

rule for a more detailed description of the methodology used.

The distribution of resources is summarized in Table 5.7-5. 

Table 5.7-5

Distribution of Personnel Requirements Throughout the Project

Front-End Design Detailed Engineering Construction

Duration per project 6 months 11 months 14 months

Duration for projects starting up in a

given calendar year

15 months 20 months 23 months

Month Fraction of total hours expended per month from start of that portion of the

project

1 0.050 0.020 0.030

2 0.050 0.030 0.030

3 0.050 0.040 0.030

4 0.078 0.040 0.040

5 0.078 0.040 0.040

6 0.078 0.050 0.040

7 0.078 0.050 0.040

8 0.078 0.060 0.050

9 0.078 0.065 0.050

10 0.078 0.075 0.055

11 0.078 0.075 0.055

12 0.078 0.075 0.060

13 0.050 0.060 0.060

14 0.050 0.060 0.055

15 0.050 0.050 0.055

16 0.050 0.050

17 0.040 0.050

18 0.040 0.040

19 0.030 0.040

20 0.020 0.040

21 0.030

22 0.030

23 0.030

The initiation of each of these three tasks relative to the start-up of the new equipment

and relative to each other was discussed above in Section 5.3.2.3, where we discuss the leadtime

necessary to meet the 2007, 2010 and 2012 NLRM sulfur caps. The following table summarizes
Final Regulatory Impact Analysis

5-80

the relative position of the first month shown in Table 5.7-5 above relative to the June 1 start

date for the two standards.

Table 5.7-6 

Initiation of Activity (Number of Months Prior to Standard Implementation (June 1))

2007 2010 2012

Front End Design 30 42 66

Detailed Engineering 24 36 60

Construction 24 36 60

As can be seen from Table 5.7-6, we assumed that the design and construction of new

hydrotreaters for the 2007 500 ppm NRLM standard would occur in a somewhat compressed

time frame due to the relatively short lead time available between the promulgation of the

NRLM rule and June 1, 2007. 

5.7.5 Projected Levels of Design and Construction Resources

We calculated the number of workers in each of the three categories required in each

month by applying the distributions of the various resources per project (Table 5.7-5) to the

number of new and revamped hydrotreaters projected to start up in each calendar year (Tables

5.7-2 and -3) and the number of person-hours required per project (Table 5.7-1). We converted

hours of work into person-years by assuming that personnel were able to actively work 1877

hours per year, or at 90 percent of capacity assuming a 40 hour work week. We then determined

the maximum number of personnel needed in any specific month over the years 2004-2010 for

each job category both before and after the NRLM diesel fuel program. The results are shown in

Table 5.7-6. In addition to total personnel required, the percentage of the U.S. workforce

currently employed in these areas is also shown. These percentages were based on estimates of

the most recently available employment levels on the Gulf Coast for the three job categories:

1920 front end design personnel, 9585 detailed engineering personnel and roughly 160,000

construction workers (taken from Moncrief and Ragsdale). We assumed that half of all refining

projects occurred on the Gulf Coast. 
Fuel Standard Feasibility

5-81

Table 5.7-7

Maximum Monthly Demand for Personnel

Program Parameter Front-End

Design

Detailed

Engineering

Construction

Tier 2 Gasoline Sulfur Program

Plus Highway Diesel Fuel

Program

Number of

Workers

383 

(Jan 04)

2,720 

(Apr 04)

17,646 

(Nov 04)

Current

Workforce 1

20% 28% 11%

With Final NRLM Program Number of

Workers

383 

(Jan 04)

2,720 

(April 04)

17,646 

(Nov 04)

Current

Workforce 1

20% 28% 11%

1

 Based on recent employment in the U.S. Gulf Coast, assuming that half of all projects occur in the Gulf Coast. The year

and month of maximum personnel demand is shown in parenthesis.

As can be seen from Table 5.7-7, the final NRLM diesel fuel program has no impact on

the maximum monthly personnel requirements for the front end, detailed design and construction

personnel.

Table 5.7-8 presents a summary of the average annual personnel demand for the demand

for front end engineering in each year. 
Final Regulatory Impact Analysis

5-82

Table 5.7-8

Annual Front End Engineering Personnel Demand

Calendar Year Gasoline + Highway Diesel

Baseline

Plus

Final NRLM Program

2002 159 159

2003 651 651

2004 97 97

2005 32 261

2006 47 87

2007 55 320

2008 2 49

2009 0 86

2010 0 23

2011 0 73

2012 0 13

2013 0 0

2014 0 0

The impact of the NRLM program on annual front end engineering demand in Table 5.7-

8 reveals that the front end engineers will be needed for the three fuel programs considered here

for over a decade. Prior to this NRLM rule, the peak impact occurs in 2003 and decreases

thereafter. After this NRLM rule, the peak still occurs in 2003, but lesser peaks occur in 2005

2007 related to the design of new hydrotreaters in 2007 and 2010. Because the level of front

end engineering after 2003 is much less than that in 2003, we do not expect that refiners will

experience any difficulties in obtaining the necessary front end engineering required to meet the

NRLM sulfur caps. 

Table 5.7-9 presents a summary of the average annual personnel demand for the detailed

end engineering in each year.
Fuel Standard Feasibility

5-83

Table 5.7-9

Annual Detailed Engineering Personnel Demand

Calendar Year Gasoline + Highway Diesel

Baseline

Plus

Final NRLM Program

2002 682 682

2003 1,315 1,315

2004 2,031 2,031

2005 400 690

2006 345 1,076

2007 370 760

2008 193 1,041

2009 5 176

2010 0 273

2011 0 113

2012 0 235

2013 0 17

2014 0 0

The impact of the NRLM program on annual detailed engineering demand in Table 5.7-9

reveals that the detailed engineers will be needed for the three fuel programs considered here for

over a decade. Prior to this NRLM rule, the peak impact occurs in 2004 and decreases

thereafter. After this NRLM rule, the peak still occurs in 2004, but lesser peaks occur in 2006

and 2008 related to the design of new hydrotreaters for 2007 and 2010. Because the level of

front end engineering after 2004 is much less than that in 2004, we do not expect that refiners

will experience any difficulties in obtaining the necessary front end engineering required to meet

the 2007 or 2010 NRLM sulfur caps. 

Table 5.7-10 presents a summary of the average annual personnel demand for

construction workers in each year. 
Final Regulatory Impact Analysis

5-84

Table 5.7-10

Construction Worker Personnel Demand

Calendar Year Gasoline + Highway Diesel

Baseline

Plus

Final NRLM Program

2002 7,574 7,574

2003 5,040 5,040

2004 14,778 14,778

2005 9,422 11,469

2006 249 5,326

2007 390 3,830

2008 1,474 7,370

2009 593 2,596

2010 0 1,904

2011 0 1,057

2012 0 1,632

2013 0 342

2014 0 0

The impact of the NRLM program on annual construction worker demand in Table 5.7-

10 reveals that construction workers will be needed for the three fuel programs considered here

for over a decade. Prior to this NRLM rule, the peak impact occurs in 2004 and decreases

thereafter. After this NRLM rule, the peak still occurs in 2004, from which demand for

construction workers decreases less gradually to 2007. There is another relative peak in 2008, 

related to the design of new hydrotreaters 2010. Because the level of front end engineering after

2004 is much less than that in 2004, we do not expect that refiners will experience any

difficulties in obtaining the necessary front end engineering required to meet the NRLM sulfur

caps. 

Thus, we believe that the E&C industry is capable of supplying the refining industry with

the equipment necessary to comply with our final nonroad diesel fuel program. We believe that

this is facilitated by the synergies obtained with highway diesel rule implementation and the later

phase in dates for nonroad compliance.

5.8 Supply of Nonroad, Locomotive, and Marine Diesel Fuel (NRLM)

We have developed the fuel program in this final rule to minimize the impact on the

distillate fuel supply. For example, the final rule transitions the fuel sulfur level down to 15 ppm

in two steps, providing an estimated six years of leadtime for the final step for nonroad diesel
Fuel Standard Feasibility

GGMeeting a 500 ppm standard can be met without desulfurizing much or any of the sterically hindered

compounds.

5-85

fuel and eight years for L&M diesel fuel (up to ten years for small refiners). Banking and

trading provisions provide flexibility to refiners and hardship provisions are available for

qualifying refiners. To evaluate the effect of the new fuel standards on supply, we evaluated

four possible cases: (1) whether the new standards could cause refiners to remove certain

blendstocks from the fuel pool, (2) whether the new standards could require chemical processing

that loses fuel in the process, (3) whether the cost of meeting the new standards could lead some

refiners to leave a particular market, and (4) whether the cost of meeting the new standards could

lead some refiners to stop operations altogether (i.e., shut down). In all cases, as discussed

below, we have concluded that the answer is no. Therefore, consistent with our findings made

during the HD2007 rule, we do not expect this rule to cause any supply shortages of nonroad,

locomotive, or marine diesel fuel. 

Blendstock Shift: As mentioned above, we first evaluated whether certain blendstocks or

portions of blendstocks may need to be removed from the NRLM diesel fuel pool. Technology

exists to desulfurize any commercial diesel fuel to less than 10 ppm sulfur. Technologies, such

as hydro-dearomatization, have been used on a commercial scale. More direct, desulfurization

technologies are just now being demonstrated fairly widely as refiners in both the United States

and Europe are producing No. 2 diesel fuel at 15 ppm sulfur or less. Pilot plant studies have

demonstrated that diesel fuels consisting of a wide range of feedstocks and containing high

levels of sulfur can be desulfurized to less than 15 ppm. Such studies and experience have

reliably demonstrated that at pressures within the range of many current conventional

hydrotreaters, the single most important variable that limits desulfurization to very low sulfur

levels is the length of time the fuel is in contact with hydrogen and the catalyst. This "residence

time" is primarily a function of reactor volume. Therefore, we believe there is no technical

reason to remove certain feedstocks from the diesel fuel pool. It may cost more for refiners to

process certain blendstocks, such as light cycle oil, than others. Consequently, there may be

economic incentives for refiners to move these blendstocks out of the diesel fuel market to

reduce compliance costs. However, that is an economic issue, not a technical issue and is

addressed next. Thus, this rulemaking should not result in any long-term reduction in the

volume of products derived from crude oil available for blending into diesel fuel or heating oil.

As mentioned above, certain feedstocks are more expensive to desulfurize than others. 

The primary challenge of desulfurizing distillate to sulfur levels meeting the 15 ppm cap is the

presence of sterically hindered compounds, particularly those with two methyl or ethyl groups

blocking the sulfur atom.GG These compounds are aromatic in nature, and are found in greatest

concentration in light cycle oil (LCO), which itself is highly aromatic. These compounds can be

desulfurized readily if saturated. However, due to the much higher hydrogen cost of doing so,

could be better economically if this can be avoided. Because these compounds are large in size

and high in molecular weight due to their chemical structure, they distill near the high end of the

diesel range of distillation temperatures. Thus, it is technically possible to segregate these

compounds from the rest of the LCO via distillation to avoid the need to desulfurize them. One
Final Regulatory Impact Analysis

5-86

option would be to construct a separate distillation column to keep this stream separate from

other refinery streams, however, this would lead to significant capital costs and operating costs

in the form of heat input. Another likely more cost-effective option would be to use the existing

FCC fractionator to shift these heavy molecules out of the LCO pool. They would be shifted to

slurry oil, which eventually becomes part of residual fuel. Once there, it would be very difficult

to recover them for blending into heating oil. 

Residual fuel is priced well below diesel fuel. The residual fuel oil market is also not

growing in the U.S. and growing only slowly worldwide. We investigated several sources of

price information, including EIA, LCM online and BP publications. According to EIA, spot

heating oil prices averaged roughly 75 cents per gallon from 2000-2003. According to the above

sources, residual fuel averaged 25-35% less, or 48-55 cents per gallon. Thus, shifting LCO or

heavy LCO to residual fuel would involve a significant long-term reduction in revenue (and

profits), ranging from 20-27 cents per gallon. Thus, we believe refiners will generally not

attempt to reduce the cost of desulfurizing diesel fuel in this way.

To evaluate this possibility, using the distillate desulfurization model described in

Section 7.2 above, we estimated the incremental cost of processing LCO (the worse of the two

blendstocks) into 15 ppm diesel fuel for each domestic refinery. On average, desulfurizing LCO

to 15 ppm sulfur cost 11.4 cents per gallon. However, in some cases, this cost reached 15 cents

per gallon. The model is not able to estimate the cost of processing heavy LCO. In fact, the

quality of LCO and especially heavy LCO is very crude oil dependent. However, the cost for

heavy LCO could be twice these amounts, since the concentration of both total sulfur and the

most difficult to remove sulfur are concentrated in the heaviest molecules. Thus, the upper end

of the range of incremental desulfurization costs for heavy LCO could potentially exceed the loss

in revenue from shifting this material to the residual fuel market. The U.S. residual fuel market

is small relative to the distillate fuel market, flat, and already being fulfilled. Thus, any

significant shift would likely depress residual fuel prices and increase the reduction in profits,

further discouraging the shift. Worldwide, the residual fuel market is growing slowly. Thus, it

is unlikely that large volumes of LCO could leave the NRLM fuel market. However, we cannot

rule out the possibility that some LCO, particularly that produced by capital-strapped refiners,

could be shifted to residual fuel. 

To estimate the upper limit of this shift, we estimated the volume of heavy LCO

produced by refineries whose LCO processing costs exceeded 12 cents per gallon and which

were not owned by large, integrated oil companies or small refiners. We excluded refineries

located in PADDs 2 and 4, since these refineries face sizeable transportation costs to get this

material to a residual fuel market, such as marine. This costly, heavy LCO represents 0.4% of

total NRLM fuel demand, a very small volume. In this case, we would expect that this loss

could easily be made up by increased imports of 15 ppm diesel fuel or domestic refiners facing

lower 15 ppm NRLM fuel costs. 

It is possible that refiners could exchange material between the NRLM and heating oil

markets to reduce the cost of meeting a 15 ppm cap, while still maintaining their NRLM fuel

production volume. In our cost projections, we projected that individual refineries will produce
Fuel Standard Feasibility

HH While the addition of the Process Dynamics process would facilitate the desulfurization to 15 ppm, the

Process Dynamics unit is expected to be installed as a revamp before the existing conventional hydrotreater handling

the 3000 to 500 ppm step while the conventional hydrotreater would be moved to address the 500 ppm to 15 ppm

step.

5-87

either 15 ppm, 500 ppm or high-sulfur distillate with their existing slate of blendstocks to avoid

additional tankage and maximize economies of scale for the desulfurization equipment. Thus,

we did not assume that refiners would reduce costs by exchanging feedstocks around, such as

sending LCO to heating oil and straight-run from heating oil to NRLM diesel fuel. Despite this,

the costs appear to be reasonable. Thus, some refiners with adequate tankage and access to the

heating oil market may be able to reduce costs with such an exchange of feedstocks. However,

we did not factor these savings into our cost projections. Even if there were such exchanges,

they would not reduce the supply of NRLM diesel fuel.

Processing Losses: We evaluated whether the new fuel standards might require chemical

processing that results in fuel losses. Conventional desulfurization processes do not reduce the

energy content of feedstocks, although the feedstock composition may be slightly altered. A

conventional hydrotreater used to produce 15 ppm sulfur diesel converts about 98 percent of its

feedstock to finished diesel fuel. About 1.5 percent of the remaining two-percent leaves the unit

as naphtha or light-crackate (i.e., gasoline feedstock), while the last 0.5 percent is split about

evenly between liquified petroleum gas (LPG) and refinery fuel gas. Both naphtha and LPG are

valuable liquids used to produce other finished products including gasoline. Refiners can easily

adjust the relative amounts of gasoline and diesel fuel produced by a unit, especially at the

process level under discussion. This additional naphtha can displace other gasoline or kerosene

blendstocks, which can then be shifted to the diesel fuel pool. LPG, on the other hand, is used

primarily for space-heating, but depending on where it’s produced and how it’s cut, can be used

as a feedstock in the petrochemical industry. Because LPG can be used for space heating, it will

likely displace some volume of heating oil, which in turn could be shifted to the diesel pool. 

Currently, heating oil or high-sulfur fuel, has the same basic composition as highway diesel,

other than its sulfur content, and can be used to fuel nonroad, locomotive, and commercial

marine equipment. Thus, the desulfurization process usually has little or no direct impact on a

refinery’s net fuel production. The volume-shift from diesel fuel to fuel gas is very small (0.25

percent) and the gas can be used to reduce consumption of natural gas within the refinery. This

discussion applies to the full effect of the new fuel standards (i.e., the reduction in sulfur content

from 3000 ppm to 500 ppm and from 500 ppm to 15 ppm). For the first step of fuel standards

the impacts are only about 40 percent of those described above.

The conversion rate of a given feedstock to light products is reportedly much lower for

the emerging or advanced technologies than for conventional hydrotreaters. For the purposes of

this rulemaking, the newer or advanced technologies are projected to be used only as a second

step to reduce the fuel to 15 ppm sulfur after it has been reduced from 3000 ppm to 500 ppm

using conventional hydrotreating technology.HH We project that the Process Dynamics process

might reduce the conversion to light products for the second step by 55 percent.

Exit the NRLM Diesel Fuel Market: We evaluated whether the compliance costs
Final Regulatory Impact Analysis

5-88

associated with this rulemaking might cause some refiners to consider reducing their production

of NRLM or to leave those markets altogether. As mentioned above, diesel fuel and heating oil

are chemically and physically similar, except for sulfur level. Thus, beginning in mid-2007, a

refiner may shift his high-sulfur distillate from NRLM fuel to the heating oil market and avoid

the need to invest in new desulfurization equipment. Likewise, beginning in mid-2010 or mid2012, a refiner may shift part or all of its supply to heating oil. The result would be a potential

oversupply of heating oil beginning in 2007. We expect such an oversupply of these fuels to

result in a substantial drop in their market price and would consequently increase the cost for a

given refiner to exit the NRLM diesel fuel markets. Furthermore, refiners may be forced to find

new export markets for their excess high-sulfur fuel. Overseas market prices are often no higher

and are occasionally lower than those in the United States. We believe these low market

differentials combined with the additional transportation costs will encourage most refiners to

comply with the NRLM program to remain in the domestic low-sulfur fuel markets.

We addressed this same issue during the development of the highway diesel rule (66 FR

5002). We contracted with Southwest Research Institute (SwRI) and with Muse, Stancil &

Company, an engineering firm involved primarily in economic studies and evaluations

concerning the refining industry to help us assess the potential for refiners to sell their highway

diesel fuel (< 500 ppm) or the blendstocks used to produce it into alternative markets. At that

time, Muse, Stancil & Company found that most refiners had few domestic alternatives for

accommodating highway diesel fuel or its blendstocks. PADD I imports significant quantities of

high-sulfur fuel for use as nonroad diesel fuel and heating oil. Muse, Stancil & Company

concluded that PADD I refineries could produce less highway fuel and more high-sulfur fuel and

still avoid over supplying the market by reducing imports. However, refineries in other PADDs

that import little, if any, high-sulfur fuel would be forced to find other, less valuable markets,

including new markets for export, if they exited the highway diesel fuel market. We concluded

that, at current production levels, refiners faced greater economic losses trying to avoid meeting

the 15 ppm cap than by trying to comply with it, even if the market did not allow them to recover

their capital investment. We believe a similar conclusion can be drawn from an analysis of this

final rule for the following six reasons:

1. Approximately one-half of what is currently the U.S. high-sulfur diesel fuel

market will have become part of the 500 ppm and 15 ppm markets by the time the

HD2007 program and the sulfur caps on NRLM fuel have been implemented.

Within that same time frame we expect few, if any, of the common carrier

pipelines, except perhaps those serving the Northeast, to carry high-sulfur heating

oil. Therefore, the sale of high-sulfur distillate may be limited to markets that a

refiner can serve by truck.

2. The technology to desulfurize fuel, including refractory feedstocks, to less than

500 ppm sulfur has been used commercially for over a decade. The technology to

reduce fuel to less than 15 ppm sulfur will have been commercially demonstrated

in mid-2006, a full four years before the 15 ppm sulfur standard for nonroad

diesel fuel takes effect.
Fuel Standard Feasibility

II Europe currently imports diesel fuel and is expected to continue to do so. However, European sulfur caps will

be equivalent to those in the United States. Therefore, exporting distillate fuel to Europe is not an option for U.S.

refiners to avoid complying with stringent sulfur caps here. Likewise, imports from European refiners are not likely. 

JJThe terms “margin” or the plural “margins” are often used in the petroleum industry in reference to several

different variables including “spread” or “spreads,” “net margin” or “cash margin,” “gross margin,” and “profit

margin.” The numbers these terms represent are all basically a measure of a revenue minus the cost to produce that

revenue, expressed on a per barrel-basis of either crude oil or finished product(s). 

5-89

3. The volume of fuel affected by the 15 ppm nonroad diesel fuel standard in 2010

and L&M standard in 2012 will be a small fraction of that affected by the

HD2007 program. This dramatically reduces the required capital investment.

4. Canada, Europe and Japan are implementing rules to reduce sulfur levels in

highway and nonroad diesel fuel to the 10-15 ppm range, which will effectively

eliminate these regions as alternative export markets for high-sulfur fuel.

5. Refineries outside of the United States and Europe are operating at a lower

percentage of their capacity than U.S. refineries.II Capacity utilization rates at

U.S. refineries are well over 90 percent. Historically, if refinery utilization rates

approached their maxima, it was usually a strong indication that demand for

finished products was high. In this environment, product prices usually rose and

held until the demand pressure was reduced or eliminated. Foreign refinery

utilization rates as well as wholesale prices tend to be well below domestic rates,

again, a reflection of lower demand relative to the potential output of finished

products. The preceding condition can have at least two effects on the marketing

decisions domestic refiners may face. First, if foreign margins are low and U.S.

market prices high, a foreign refiner can, and most likely will, sell his products

into the U.S. market, thereby reducing the upward pressure on prices and likely

reducing domestic refinery margins. And, second, it is highly unlikely that a

domestic refiner will decide to further reduce his margins by adding the cost to

ship his product into a foreign market with a less stringent sulfur standard where

wholesale prices are already lower than in the United States. Consequently, we

believe U.S. refiners will not have a reasonable opportunity to export their highsulfur fuel.

6. One measure of the overall fiscal well-being of a refining operation is its margin.

Refinery profit marginsJJ during the 1990s were not very encouraging until about

1997. In fact, in 1994, the net margin was less than $0.50 per refined barrel. By

1997 it had nearly tripled and by 2000 had increased to nearly five times the 1994

average. Margins leveled out again during 2001 and decreased somewhat during

2002, but recovered during the last few months of 2002 and in early 2003. 

Current industry projections into the future indicate the expectation for continued

high profit margins.
Final Regulatory Impact Analysis

KK There will also be 500 ppm locomotive and marine diesel fuel produced from transmix in the distribution

system which can be used to satisfy the locomotive and marine demand, although this 500 ppm fuel will be produced

downstream at terminals. 

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Once refiners have made their investments to meet the NRLM diesel fuel standards, or

have decided to produce high-sulfur heating oil, we expect the various distillate markets to

operate very similar to current markets. When fully implemented in 2014, there will be three

distillate fuels in the market, 15 ppm highway and NRLM diesel fuelKK and high-sulfur heating

oil. The resulting options are similar to the current situation in which there are two fuels—500

ppm and high-sulfur distillate. In this case, refiners with the capability of producing 15 ppm

diesel fuel have the most flexibility, since they can sell their fuel to any of the three markets. 

Those refiners capable of producing only high-sulfur distillate will be able to participate in only

the heating oil market. Generally, we do not expect one market to provide vastly different profit

margins than the others, as high profit margins in one market will attract refiners from another

via investment in desulfurization equipment. 

Refinery Closure: There are several reasons why we believe refineries will not

completely close down as a result of this final rule. One reason is that the regulations include a

provision to adjust the sulfur caps for small refiners, as well as any refiner facing unusual

financial hardship. Another reason is that nonroad, locomotive, and marine diesel fuel is usually

the third or fourth most important product produced by the refinery from a financial perspective. 

A total shutdown would mean losing all the revenue and profit from these other products. 

Gasoline is usually the most important product, followed by highway diesel fuel and jet fuel. A

few refineries do not produce either gasoline or highway diesel fuel, so jet fuel and high-sulfur

diesel fuel and heating oil are their most important products. The few refiners in this category

likely face the biggest financial challenge in meeting the requirements in this final rule. 

However, those refiners will also presumably be in the best position to apply for the special

hardship provisions, presuming they do not have readily available source of investment capital.

The additional time afforded by these provisions should allow the refiner to generate sufficient

cash flow to invest in the required desulfurization equipment. Investment here could also

provide them the opportunity to expand into more profitable (e.g., highway diesel) markets. 

A quantitative evaluation of whether the cost of the fuel program in this final rule could

cause some refineries to cease operations completely would be very difficult, if not impossible to

perform. A major factor in any decision to shut down is the refiner’s current financial situation. 

It is very difficult to assess an individual refinery’s current financial situation. This includes a

refiner’s debt, as well as its profitability in producing fuels other than those affected by a

particular regulation. It can also include the profitability of other operations and businesses

owned by the refiner. 

Such an intensive analysis can be done to some degree in the context of an application for

special hardship provisions, as discussed above. However, in this case, we may request detailed

financial documents that are not normally available. Prior to such application, as is the case

now, this financial information is usually confidential. Even when it is published, the data
Fuel Standard Feasibility

LL The U.S. Congress is considering legislation that would require the increased use of renewables, like ethanol,

in gasoline and diesel fuel. While the amount of renewables could be considerable, it is well below the annual

growth in transportation fuel use. 

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usually apply to more than just the operation of a single refinery. 

Another factor is the need for capital investments other than for this rule. We can

roughly project the capital needed to meet other new fuel-quality specifications, such as the Tier

2 or highway diesel sulfur standards. However, we cannot predict investments to meet local

environmental and safety regulations, nor other investments needed to compete economically

with other refiners. 

Finally, any decision to close in the future must be based on some assumption of future

fuel prices. Fuel prices are very difficult to project in absolute terms. The response of prices to

changes in fuel-quality specifications, such as sulfur content, as is discussed in the next section,

are also very difficult to predict. Thus, even if we had complete knowledge of a refiner’s

financial status and its need for future investments, the decision to stay in business or close

would still depend on future earnings, which are highly dependent on prices. 

Some studies in this area point to fuel pricing over the past 20 years or so and conclude

that prices will increase only to reflect increased operating costs and will not reflect the cost of

capital. In fact, the rate of return on refining assets has been poor until the late 1990s and until

recently, there has been a steady decline in the number of refineries operating in the United

States. However, this may have been due to circumstances specific to that time period. The

primary reason is that refinery capacity utilization was less than 80 percent in 1985. 

Current refinery capacity utilization in the United States is generally considered to be at

its maximum sustainable rate. There are no regulatory mandates on the horizon that will

increase production capacity significantly, even if ethanol use in gasoline increases

substantially.LL Consistent with this, refining margins have been much better over the past few

years than during the previous 15 years and the refining industry itself is projecting good returns

for the foreseeable future. 

Conclusion: Therefore, consistent with our findings made during the HD2007 rule and

the nonroad NPRM, we do not expect this final rule to cause any supply shortages of nonroad,

locomotive, or marine diesel fuel.

5.9 Desulfurization Effect on Other Non-Highway Diesel Fuel Properties

5.9.1 Fuel Lubricity

Engine manufacturers depend on diesel fuel lubricity properties to lubricate and protect

moving parts within fuel pumps and injection systems for reliable performance. Unit injector

systems and in-line pumps, commonly used in diesel engines, are actuated by cams lubricated
Final Regulatory Impact Analysis

5-92

with crankcase oil, and have minimal sensitivity to fuel lubricity. However, rotary and

distributor type pumps, commonly used in light and medium-duty diesel engines, are completely

fuel lubricated, resulting in high sensitivity to fuel lubricity. The types of fuel pumps and

injection systems used in nonroad diesel engines are the same as those used in highway diesel

vehicles. Consequently, nonroad and highway diesel engines share the same need for adequate

fuel lubricity to maintain fuel pump and injection system durability.

The state of California currently requires the use of the same diesel fuel in nonroad

equipment as in highway equipment. Outside of California, highway diesel fuel is often used in

nonroad equipment when logistical constraints or market influences in the fuel distribution

system limit the availability of high-sulfur fuel. Thus, nonroad equipment has been using federal

500 ppm sulfur diesel fuel and California diesel fuel, some of which may have been treated with

lubricity additives for nearly a decade. During this time, there has been no indication that the

level of diesel lubricity needed for fuel used in nonroad engines differs substantially from the

level needed for fuel used in highway diesel engines.

Diesel fuel lubricity concerns were first highlighted during implementation of the federal

500 ppm sulfur highway diesel program and the state of California’s diesel program circa 1993.47

The diesel fuel requirements in the state of California differ from the federal requirements by

substantially restricting the aromatics content of diesel fuel in addition to the sulfur content. 

Considerable research remains to better understand which fuel components are most responsible

for fuel lubricity. Nevertheless, there is evidence that the typical process used to reduce diesel

fuel sulfur content or aromatics content of diesel fuel (i.e., hydrotreating) can reduce fuel

lubricity. Consequently, implementing the sulfur standards in this final rule will likely require

some action to maintain the lubricity of non-highway diesel fuel.

The potential impacts on fuel lubricity from NRLM sulfur standards are associated solely

with the additional refinery processing that is necessary to meet these standards. Although we

are extending the cetane index/aromatics content specification to NRLM diesel fuel, we do not

expect this to have a significant impact on fuel lubricity. We require that highway diesel fuel

meet a minimum cetane index level of 40 or, as an alternative, contain no more than 35 volume

percent aromatics. ASTM already applies a cetane number specification of 40 to NRLM diesel

fuel, which is generally more stringent than the similar 40 cetane index specification. Because

of this, the vast majority of current NRLM diesel fuel already meets the EPA cetane

index/aromatics specification for highway diesel fuel. Thus, the new requirement will have an

impact only on a limited number of refiners and there will be little overall impact on other diesel

fuel qualities (including fuel lubricity) associated with producing fuel to meet the

cetane/aromatic requirement.

Blending small amounts of lubricity-enhancing additives increases the lubricity of poorlubricity fuels to acceptable levels. These additives currently are available in the market, are

effective, and are in widespread use around the world. Several commenters on our final rule

setting a 15 ppm sulfur standard for highway diesel fuel indicated that biodiesel can be used to

increase the lubricity of conventional diesel fuel to acceptable levels. Some testing suggested

that only two volume percent is necessary. However, more testing may be required to determine
Fuel Standard Feasibility

5-93

the necessary level of biodiesel for fuels not yet being produced, such as the 15 ppm fuel

required under this final rule.

In the United States, there is no government or industry standard for diesel fuel lubricity. 

Therefore, specifications for lubricity are determined by the market. Since the beginning of the

500 ppm sulfur highway diesel program in 1993, fuel system producers, engine and engine

manufacturers, and the military have been working with the American Society for Testing and

Materials (ASTM) to develop protocols and standards for diesel fuel lubricity in its D-975

specifications for diesel fuel. ASTM is working towards a single lubricity specification that

would apply to all diesel fuel used in any type of engine. The ASTM development process has

reached an agreement on the High Frequency Reciprocating Rig (HFRR) lubricity test method

and an initial lubricity level of 520 micron Wear Scar Diameter (WSD) for its lubricity

specification. The specification has been balloted four times in recent years and the current hold

up on the passing of the specification is the lack of an implementation date. ASTM is hoping to

overcome implementation date issues by allowing an implementation date of 1/1/2005 in the

next ballot or by not putting the specification to a vote until late in 2004. In light of this, the

California Air Resources Board (CARB) has decided to regulate lubricity starting in August

2004. Initial lubricity levels will require diesel fuel to have a WSD of < 520 microns for the

HFRR. CARB also has provisions in its regulation to lower the required lubricity level to < 460

micron WSD, HFRR pending the outcome of the work being performed by the CRC Diesel

Performance Group. CARB may withdraw this specification if ASTM reaches a consensus and

passes it’s lubricity standard before the CARB implementation date. We will follow suit with a

separate lubricity rulemaking similar to CARB’s if ASTM does not reach a consensus on its

lubricity standard in reasonable time.

Although ASTM has not yet adopted specific protocols and standards, refiners that

supply the U.S. market have been treating diesel fuel with lubricity additives on a batch to batch

basis, when poor lubricity fuel is expected. Other evidence of how refiners are ensuring

adequate fuel lubricity can be found in Sweden, Canada, and the U.S. military. The U.S. military

has found that traditional corrosion inhibitor additives have been highly effective in reducing

fuel system component wear. Since 1991, the use of lubricity additives in Sweden's 10 ppm

sulfur Class I fuel and 50 ppm sulfur Class II fuel has resulted in acceptable equipment

durability.48 Since 1997, Canada has required that its 500 ppm sulfur diesel fuel not meeting a

minimum lubricity be treated with lubricity additives.

The potential need for lubricity additives in diesel fuel meeting a 15 ppm sulfur

specification was evaluated during the development of EPA’s highway diesel rule. The final

highway diesel rule did not establish a lubricity standard for highway diesel fuel. We believe the

issues related to the need for diesel lubricity in fuel used in non-highway diesel engines are not

substantially different from those related to the need for diesel lubricity for highway engines. 

Consequently, we are relying on the same industry-based voluntary approach to ensuring

adequate lubricity in non-highway diesel fuels that we relied upon for highway diesel fuel. 

Consistent with the highway diesel final rule, we believe the best approach is to allow the

industry and the market to address the lubricity issue in the most economical manner. We expect

that a voluntary approach will provide adequate customer protection from engine failures due to
Final Regulatory Impact Analysis

5-94

low lubricity, while providing the maximum flexibility for the industry. We expect that the

American Society for Testing and Materials (ASTM) will finalize a fuel lubricity standard for

use by industry that could be applied to low-sulfur NRLM diesel fuel. 

The degree to which removing the sulfur content from diesel fuel may impact fuel

lubricity depends on the characteristics of the blendstocks used as well as the severity of the

treatment process. Based on our comparison of the blendstocks and processes used to

manufacture non-highway diesel fuels, we project that the potential decrease in the lubricity of

non-highway diesel fuel that might result from the new sulfur standards will be substantially the

same as that experienced in desulfurizing highway diesel fuel to meet the same sulfur standard.

A refiner of diesel fuel for use in California and for much of the rest of the United States

as well evaluated the impacts on fuel lubricity of the current federal and California diesel fuel

requirements.49 This refiner concluded that, reducing the aromatics content of diesel fuel

requires more severe hydrotreating than reducing the sulfur content to meet a 500 ppm standard. 

Consequently, concerns regarding diesel fuel lubricity have primarily been associated with

California diesel fuel and some California refiners treat their diesel fuel with a lubricity additive

as needed. The subject refiner stated that outside of California, hydrotreating to meet the current

500 ppm sulfur specification seldom results in a sufficient reduction in fuel lubricity to require

the use of a lubricity additive. We expect that the same hydrotreating process currently used to

produce highway diesel fuel will be used to reduce the sulfur content of non-highway diesel fuel

to meet the 500 ppm sulfur standard during the first step under this final rule. We therefore

estimate that there will be only a marginal increase in the use of lubricity additives in NRLM

diesel fuel meeting the 500 ppm sulfur standard for 2007.

The highway diesel program projected that hydrotreating will be the process most

frequently used to meet the 15 ppm sulfur standard for highway diesel fuel in 2006. However,

we project that the 2010 and 2012 implementation dates for the 15 ppm standard for NRLM

diesel fuel will allow the use of advanced technologies to remove sulfur from 60 percent of the

affected diesel pool. The use of such developing desulfurization processes is discussed in

Section 5.5. These new processes have less of a tendency to affect other fuel properties than

does hydrotreating. Therefore, the use of such new desulfurization technologies might tend to

have less of an impact on fuel lubricity. However, we have no specific information with which

to quantify the impacts of the developing technologies on fuel lubricity. To provide a

conservatively high estimate of the potential impact of meeting the 15 ppm standard for nonroad

diesel fuel, we assumed that the potential impact on fuel lubricity of the new desulfurization

processes will be the same as that experienced when hydrotreating diesel fuel to meet a 15 ppm

sulfur standard. We therefore assumed, as we did for 15 ppm highway diesel fuel, that all 15

ppm NRLM diesel fuel must be treated with lubricity additives. The cost associated with the

increased use of lubricity additives in 500 ppm NRLM diesel fuel and in 15 ppm NRLM diesel

fuel is discussed in Chapter 7.

Railroads and locomotive manufacturers have expressed concern that low-sulfur fuel

might damage existing locomotives. Locomotives already use a significant amount of low-sulfur

fuel, especially in California, and there has not been any evidence of sulfur-related problems. 
Fuel Standard Feasibility

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Low-sulfur locomotive diesel fuel meeting the soon to be specified lubricity requirements will

provide adequate protection to these engine and fuel systems.

5.9.2 Volumetric Energy Content

Some of the projected desulfurization processes for meeting the non-highway diesel

sulfur standards tend to reduce the volumetric energy content (VEC) of the fuel during

processing. Desulfuization also tends to result in a swell in the total volume of fuel. These two

effects tend to cancel each other out so there is no overall loss in the energy content in a given

batch of fuel that is subjected to desulfurization. Thus, we do not expect the potential reduction

in VEC that might result from the new sulfur standards to affect the refiners’ ability to supply

sufficient quantities of non-highway diesel fuel. The potential impacts on diesel supply are

discussed in Section 5.8.

Since a greater volume of fuel must be consumed in the engine to produce the same

amount of power, however, a larger volume of fuel is needed to meet the same level of demand. 

The potential increase in the distribution costs associated with a reduction in NRLM diesel VEC

is discussed in Section 7.3.

The impact of desulfurization on diesel fuel VEC varies depending on the type of

blendstocks and desulfurization process used. A comparison of the blendstocks used to produce

high-sulfur diesel fuel with those used to produce highway diesel fuel shows that both pools

contain similar fractions of each type of blendstock.50 Based on this comparison, we believe a

comparable level of severity in the desulfurization process is required to produce NRLM diesel

fuel meeting a given sulfur specification as will be required to produce highway diesel fuel

meeting the same sulfur specification. Refiners with experience in the use of

hydrodesulfurization to manufacture both 500 ppm and 15 ppm highway diesel fuel provided us

with information that we used to estimate the accompanying reduction in VEC. Using this

information, we estimate that hydrodesulfurization of NRLM diesel fuel to meet a 500 ppm

sulfur standard will result in a reduction in volumetric energy content of 0.7 percent.

The 15 ppm sulfur standard for nonroad diesel fuel does not start until 2010 and for L&M

diesel fuel until 2012. The additional lead time allows refiners to take advantage of several lessexpensive desulfurization technologies currently under development to produce diesel fuel

complying with the 15 ppm sulfur standard in addition to conventional hydrotreating. Of the

advanced desulfurization technologies which refiners may consider, we believe that only Process

Dynamics Isotherming will be used extensively (see Section 5.3). We project that Process

Dynamics Isotherming will be used by 60% of the NRLM market, while conventional

hydrotreating will be used by the remaining 40%. The Process Dynamics engineers estimate that

the Isotherming desulfurization process will have less of an impact on diesel fuel volumetric

energy content than does hydrodesulfurization. Using the mix of desulfurization technologies

we expect to be available, we estimate that desulfurizing NRLM diesel fuel from 500 ppm to 15

ppm will reduce the volumetric energy content by an additional 0.5 percent (0.7% conventional

hydrotreating and 0.4% for IsoTherming). Thus, reducing the sulfur content of nonroad diesel

fuel from the current maximum 5,000 ppm sulfur cap to the 15 ppm sulfur standard is estimated
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to result in a 1.2 percent reduction in VEC. Table 5.9-1 summarizes the projections for

estimating the impact of the new sulfur standards on VEC, including: (1) the percentage of the

applicable NRLM diesel fuel pool that we expect will be desulfurized using each of the available

desulfurization processes and (2) the projected impact of each desulfurization process on VEC.

Table 5.9-1

Projections Used in Estimating the in Reduction in 

Volumetric Energy Content Associated with Meeting the New Sulfur Standards

Desulfurization Processa Percent of Diesel Pool Desulfurized

Using a Given Process to Meet the

Applicable Sulfur Standard

Reduction in Volumetric Energy Content

Associated with a Given Desulfurization

Process

NRLMb

500 ppm

in 2007

NR 

15 ppm

in 2010

L&M 

15 ppm

in 2012

Reduction in Sulfur Content

HSc

 to 500 ppm 500 ppm to 15 ppm

Conventional

Desulfurization

100 % 40% 40% 0.7% 0.7 %

Process Dynamics 

Isotherming

NA 60% 60% NA 0.4 %

Over-all Impact on VEC of

All Desulfurization

Processes Used

- - 0.7% 0.5%

a

 See Section 5.3 regarding the use of conventional hydrodesulfurization , and the Process Dynamics Isotherming process

to meet the new sulfur standards. b

 NR = nonroad diesel fuel, L = locomotive diesel fuel, and M = marine diesel fuel. c

 HS refers to high-sulfur diesel fuel at the current uncontrolled average sulfur level of approximately 3000 ppm.

It is important to remember that the anticipated reduction in VEC discussed above

applies only to those gallons of NRLM diesel fuel that currently have a high sulfur content. Due

to logistical constraints in the fuel distribution system, much of the fuel used in NRLM engines

meets highway diesel fuel standards (see Section 7.1). The costs related to the reduction in

NRLM diesel fuel VEC accompanying the new sulfur standards are discussed in Section 7.3.

5.9.3 Fuel Properties Related to Storage and Handling 

In addition to fuel lubricity additives, a range of other additives are also sometimes

required in diesel fuel to compensate for deficiencies in fuel quality. These additives include

cold flow improvers, static dissipation additives, anti-corrosion additives, and anti-oxidants. The

highway diesel fuel program projected that, except for an increase in the fuel lubricity additives,

reducing the sulfur content of highway diesel fuel to meet a 15 ppm standard will not result in an

increase in the use of diesel performance additives. Since that time, we have identified no new

information to alter that projection. Consequently, our estimate of the increase in additive use

resulting from this final rule parallels that under the highway program. We estimate that the use

of lubricity additives will increase and that the use of other additives will be unaffected.
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5.9.4 Cetane Index and Aromatics

We require that nonroad, locomotive, and marine diesel fuel comply with the current

highway diesel fuel requirements for cetane index or aromatics. Thus, these non-highway diesel

fuels must meet either a 40 minimum cetane index, or a 35 percent maximum aromatics limit. In

this section, we present information on what these properties are currently for non-highway

diesel fuel, then we estimate how much they are likely to change when these streams are

desulfurized.

We have reports of non-highway diesel fuel cetane index values from refinery samples

from 1997 to 2001. The 1997 and 1998 reports were published by the National Institute for

Petroleum and Energy Research (NIPER), Bartlesville, OK, and then this organization changed

their name to TRW Petroleum Technologies, which published the reports for 1999 through 2001. 

The reports divided the country into the Eastern, Southern, Central, Rocky Mountain, and

Western Regions. The samples, which averaged about 17 per year, were pooled from the various

regions. The range of cetane index values for the 85 total samples is 39.4 - 57.0. Out of the 85

samples, 5 samples were under the cetane index value of 40 and potentially would not comply

with the cetane index minimum of 40. However, those that were below the 40 cetane index

minimum, were barely below it (i.e., 39.4 versus 40). Since the aromatics levels were not

provided for these 5 samples, we could not verify if these samples would also not comply with

the aromatics part of the specification.

As refiners desulfurize their NRLM diesel fuel to comply with the 500 ppm standard in

2007 and then again to comply with the 15 ppm standard in 2010 and 2012, we expect them to

see increased cetane levels in their NRLM diesel fuel. Vendors of the desulfurization

technologies either provided information on the impact that their technologies have on the cetane

index of diesel fuel, or we were able to estimate the impact using changes to API gravity and the

T-50 distillation point. While the changes in cetane index were provided for the desulfurization

of highway diesel fuel, they apply to NRLM diesel fuel as well, as it is similar in quality and

composition to highway diesel fuel. The estimated impact of the desulfurization technologies on

cetane index summarized in the following table. As described in Chapter 7, much of the highsulfur diesel pool is already hydrotreated (on the order of 50 percent in some PADDs) and will

therefore not be impacted by the first step of fuel control to 500 ppm, so the cetane index is

expressed as a range for the high-sulfur to 500 ppm step. The lower value of the range reflects

the fact that refiners will have to hydrotreat only half their existing high-sulfur pool to produce

500 ppm sulfur fuel, while the upper value reflects the fact that refiners will have to treat their

entire pool. For conventional hydrotreating, a range in the amount of increase in cetane index

values is also reflected in the 500 ppm to 15 ppm sulfur reduction step, which reflects the

different estimates for the two vendors that provided us the desulfurization information. 
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Table 5.9-2

Impact of Desulfurization Technologies on Diesel Fuel Cetane Index

Conventional Hydrotreating Process Dynamics Isotherming

High-Sulfur to 500 ppm +2 to +4 +2 to +4

500 ppm to 15 ppm +1 to +2 +2

Total High-Sulfur to 15 ppm +3 to +6 +4 to +6

As summarized in the above table, conventional hydrotreating improves the cetane index

of diesel fuel by 2 to 4 numbers for the 500 ppm sulfur standard, and 1 to 2 numbers for the 15

ppm sulfur standard incremental to the 500 ppm standard. If the lowest cetane index values of

non-highway diesel fuel are indeed between 39 and 40 as the NIPER/TRW data suggest, then the

desulfurization of that pool to comply with the 500 ppm sulfur standard, which we expect to be

accomplished using conventional desulfurization technology, is expected to increase the cetane

index to a value above the 40 minimum, thus we do not expect refiners to be constrained by a

cetane index requirement.

Aromatics should also decrease, although this decrease is expected to occur mostly

through the saturation of polynuclear aromatics to monoaromatics.

5.9.5 Other Fuel Properties

Desulfurization is expected to impact other qualities of non-highway diesel fuel. The

concentration of nitrogen in current high-sulfur diesel fuel is on the order of several hundred

parts per million. The desulfurization technologies projected to be used for compliance with the

500 ppm sulfur standard are expected to lower nitrogen levels down to under 100 ppm, although

they may still be above 50 ppm. These same desulfurization technologies are expected to lower

nitrogen levels down to under 10 ppm when achieving compliance with the 15 ppm sulfur

standard.

Conventional desulfurization and Process Dynamics Isotherming are expected to affect

the distillation temperature of NRLM diesel fuel. For desulfurizing high-sulfur diesel fuel down

to 15 ppm, one vendor of conventional hydrotreating technology estimates that each distillation

point (T-10 - T-90) will experience a 5/F decrease. Consistent with that, API gravity is expected

to increase by 4 numbers, with density decreasing commensurately. Process Dynamics

Isotherming is expected to impact the distillation temperature less than conventional

hydrotreating due to the lower API gravity increase caused by Process Dynamics compared with

conventional hydrotreating.
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Appendix 5A: EPA’s Legal Authority for Adopting Nonroad,

Locomotive, and Marine Diesel Fuel Sulfur Controls

We are adopting diesel fuel sulfur controls under our authority in section 211(c)(1) of the

Clean Air Act. This section gives us the authority to “control or prohibit the manufacture,

introduction into commerce, offering for sale, or sale” of any fuel or fuel additive for use in an

off-highway engine or vehicle (1) whose emission products, in the judgment of the

Administrator, cause or contribute to air pollution which may reasonably be anticipated to

endanger the public health or welfare or (2) whose emission products will impair to a significant

degree the performance of any emission control device or system which is in general use, or

which the Administrator finds has been developed to a point where in a reasonable time it would

be in general use were the fuel control or prohibition adopted. 

We currently do not have regulatory requirements for sulfur in nonroad, locomotive, or

marine diesel fuel. Beginning in 1993, highway diesel fuel was required to meet a sulfur cap of

500 ppm and be segregated from other distillate fuels as it left the refinery by the use of a visible

level of dye solvent red 164 in all non-highway distillate. Any fuel not dyed is treated as

highway fuel. Beginning in 2006, highway diesel fuel will be required to start meeting a sulfur

cap of 15 ppm. 

We are adopting controls on sulfur levels in off-highway diesel fuel based on both of the

Clean Air Act criteria described above. Under the first criterion, we believe that emission

products of sulfur in nonroad, locomotive, and marine diesel fuel used in these engines

contribute to PM and SOx pollution. As discussed in Chapter 2, emissions of these pollutants

cause or contribute to ambient levels of air pollution that endanger public health and welfare. 

Control of sulfur to 15 ppm for NRLM fuel will lead to significant, cost-effective reductions in

emissions of these pollutants, with the benefits to public health and welfare significantly

outweighing the costs. In the proposal and Draft RIA EPA discussed controlling sulfur through

a first step to 500 ppm for NRLM fuel, based on the public health and welfare benefits from such

a fuel control, with a second step to 15 ppm for nonroad fuel, based on technology enablement

for associated nonroad engine standards. EPA also discussed various alternatives, such as a

second step to 15 ppm for locomotive and marine fuel as well as a single step to 15 ppm for

NRLM fuel, both based on the public health and welfare benefits from such a fuel sulfur control.

Adopting a 15 ppm standard for locomotive and marine fuel makes it clear that for

purposes of section 211(c)(1)(A) the most appropriate way to view the final fuel control program

adopted in this rule is as a complete program, covering all of NRLM fuel. This is because the

reduction to 15 ppm for nonroad fuel is in essence no different from the reduction to 15 ppm for

locomotive and marine fuel. Basically, the same desulfurization technology is used, the same

per-gallon desulfurization costs are incurred, and the same per gallon emissions reductions and

benefits are achieved from the fuel control. The only significant difference is the magnitude of

total actual reductions and costs, based on the volume of diesel fuel controlled. Therefore for

purposes of section 211(c)(1)(A), EPA has analyzed and justified the reduction of NRLM fuel
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sulfur from current sulfur levels to 15 ppm as a complete program, without drawing any

distinction between nonroad and locomotive and marine fuel.

Under the second criterion, we believe that sulfur in nonroad diesel fuel will significantly

impair the emission-control systems expected to be in general use in nonroad engines designed

to meet the emission standards adopted in this rule. Chapter 4.1.7 describes the substantial

adverse effect of high fuel-sulfur levels on the emission-control devices or systems for diesel

engines meeting the proposed emission standards. Controlling sulfur levels in nonroad diesel

fuel to 15 ppm will enable emission-control technology that will achieve additional significant,

cost-effective reduction in emissions of NOx, NMHC and PM pollutants, beyond that achieved

by the fuel control itself. The following sections summarize our analysis of the various issues

related to adopting fuel-sulfur controls for nonroad, locomotive, and marine diesel fuel.

5A.1 Health and Welfare Concerns of Air Pollution Caused by Sulfur in

Diesel Fuel

At the current unregulated levels of sulfur in this diesel fuel, the emission products from

the combustion of diesel sulfur in these engines can reasonably be anticipated to endanger public

health and welfare. Sulfur in nonroad, locomotive and marine diesel fuel leads directly to

emissions of SO2 and sulfate PM from the exhaust of diesel vehicles, both of which cause

adverse health and welfare impacts, as described in Chapter 2. SO2 emissions from nonroad,

locomotive and marine engines are directly proportional to the amount of sulfur in the fuel. SO2

is oxidized in the atmosphere to SO3 which then combines with water to form sulfuric acid

(H2SO4) and further combines with ammonium in the atmosphere to form ammonium sulfate

aerosols. These aerosols are what is often referred to as sulfate PM. This sulfate PM comprises

a significant portion of the “secondary” PM that does not come directly from the tailpipe, but is

nevertheless formed in the atmosphere from exhaust pollutants. Exposure to secondary PM may

be different from that of PM emitted directly from the exhaust, but the health concerns of

secondary PM are just as severe as for directly emitted particulate matter, with the possible

exception of the carcinogenicity concerns with diesel exhaust.

Approximately 1-2% of the sulfur in nonroad, locomotive and marine diesel fuel is not

converted into SO2, but is instead further oxidized into SO3 which then forms sulfuric acid

aerosols (sulfate PM) as it leaves the tailpipe. While only a small fraction of the overall sulfur is

converted into sulfate emissions in the exhaust, it nevertheless accounts for approximately 10%

of the total PM emissions from diesel engines today. This sulfate PM is also directly

proportional to the sulfur concentration in the fuel. The health and welfare implications of

emissions of PM and SO2 and the need for reductions in these emissions are discussed in

Chapter 2.

The reduction in the sulfur level of nonroad, locomotive, and marine diesel fuel to 15

ppm would achieve in excess of 99 percent reduction in the emissions of SO2 and sulfate PM

emissions from nonroad, locomotive, and marine diesel engines compared with today’s levels. 

The first step to 500 ppm would achieve about a 90% reduction and the second step to 15 ppm
Fuel Standard Feasibility

MM The cost per gallon to go from current levels to 15 ppm is the same cost per gallon to go from current sulfur

levels to 500 ppm plus the cost per gallon to go from 500 to 15 ppm. The cost per gallon for each of the separate

steps is by definition less than the cost for the combined steps of the total fuel program.

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would achieve in excess of a 99 percent reduction in these pollutants. 

EPA has evaluated the technical feasability of achieving these sulfur levels, including the

cost of the reductions and the impact on fuel supply. EPA has concluded that these reductions

are feasible in the lead time provided, and should not have an adverse impact on the adequacy of

NRLM fuel supply to meet demand; see RIA Chapter 5.

EPA also evaluated the emissions reductions achieved by controlling NRLM sulfur levels

and compared them to the benefits and the costs to achieve these reductions. EPA evaluated the

monetary value of many of the public health and welfare benefits that will be achieved by these

reductions in emissions; see RIA Chapter 9. The monetized value of the health and welfare

benefits of the emissions reductions obtained by lowering sulfur in NRLM diesel fuel from

current levels to 15 ppm are expected to significantly exceed the costs of this reduction in sulfur

levels. This is the case for the complete fuel program (going from current levels of sulfur in

NRLM to 15 ppm for NRLM), as well as for each of the two steps used to achieve the complete

fuel program (going from current levels to 500 ppm, and then going from 500 ppm to 15 ppm). 

The costs per gallon are also reasonable for going from current sulfur levels to 15 ppm.MM EPA

also evaluated the cost per ton of emissions reduced for lowering sulfur in NRLM from current

levels down to 15 ppm, the complete program. The results are comparable to the cost per ton of

the entire engine and fuel program adopted in this final rule, as well as for other control

programs designed to reduce emissions of the same pollutants; see RIA Chapter 8. The most

appropriate way to evaluate the cost per ton is to consider the complete fuel program adopted in

the final rule, since that is the action we are taking. However, we have also evaluated the cost

per ton considering the two steps separately. The cost per ton of emissions reduced in the first

step to 500 ppm is comparable to other control programs. The cost per ton for the second step,

when considered in isolation, is somewhat high compared to the cost per ton of other control

programs, however the monetized benefits from the reduction in emissions achieved by the

second step are greater than the costs to achieve these reductions. In sum, EPA concludes that

the entire body of evidence strongly supports the view that controlling sulfur in NRLM fuel to 15

ppm, through a two step process, is quite reasonable in light of the emissions reductions and

benefits achieved, taking costs into consideration. 

The rationales for the two-step approach to fuel sulfur control and the levels associated

with each step are discussed in Chapters 5 and 12. Aside from its dramatic and immediate in-use

emission benefits, the proposed sulfur level of 500 ppm for the first step was chosen primarily

due to its consistency with the current highway diesel fuel standard. The magnitude of the

distribution system costs would virtually prohibit the widespread distribution of any other grades

of diesel fuel, as discussed in Section IV.B of the preamble to the proposed rule. The 15 ppm

level was chosen as the final level for the same reasons, as well as for the reasons discussed

below concerning the need for 15 ppm sulfur fuel to enable the use of advanced emissions
Final Regulatory Impact Analysis

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control technology. Consequently, the choice of sulfur level was limited to one of the existing

three grades; 15 ppm, 500 ppm, or uncontrolled. A reduction in the sulfur directly to 15 ppm

was inconsistent with the proposed 2-step approach to diesel fuel sulfur control. Therefore,

given the need to achieve reductions, the 500 ppm level was selected for this temporary first step

of control.

Section 211(c)(2)(A) requires that, prior to adopting a fuel control based on a finding that

the fuel’s emission products contribute to air pollution that can reasonably be anticipated to

endanger public health or welfare, EPA consider “all relevant medical and scientific evidence

available, including consideration of other technologically or economically feasible means of

achieving emission standards under [section 202 of the Act].” EPA’s analysis of the medical and

scientific evidence relating to the emissions impact from nonroad, locomotive and marine

engines, which are impacted by sulfur in diesel fuel, is described in more detail in Chapter 2 of

the RIA.

EPA has also satisfied the statutory requirement to consider “other technologically or

economically feasible means of achieving emission standards under section [202 of the Act].” 

This provision has been interpreted as requiring consideration of establishing emission standards

under section 202 prior to establishing controls or prohibitions on fuels or fuel additives under

section 211(c)(1)(A). See Ethyl Corp. v. EPA, 541 F.2d. 1, 31-32 (D.C. Cir. 1976). In Ethyl, the

court stated that section 211(c)(2)(A) calls for good faith consideration of the evidence and

options, not for mandatory deference to regulation under section 202 compared to fuel controls. 

Id. at 32, n.66.

EPA recently set emissions standards for heavy-duty highway diesel engines under

section 202 (66 FR 5002, January 18, 2001). That program will reduce particulate matter and

oxides of nitrogen emissions from heavy duty engines by 90 percent. In order to meet these

more stringent standards for diesel engines, the program requires a 97 percent reduction in the

sulfur content of diesel fuel. EPA does not believe it is appropriate to seek further reductions at

this time from these engines. Also, section 211(c)(2)(A) refers to standard setting under section

202 for highway engines or vehicles, and does not refer to standard setting under section 213. In

any case, EPA is adopting stringent new standards for nonroad diesel engines under section 213.

The two-step reduction of sulfur to 15 ppm for nonroad, locomotive and marine diesel

fuel represents an appropriate exercise of the Agency’s discretion under section 211(c)(1)(A). 

The control of NRLM fuel down to 15 ppm provides significant reductions in emissions of PM

and SO2, producing reductions in excess of 99% of these emissions. The fuel program is cost

effective and produces benefits to public health and welfare whose value significantly outweighs

the costs. These reductions can be achieved in a manner that is technologically feasible, will not

disrupt fuel supply, and is harmonized with the similar fuel controls for highway diesel fuel. 

Using two steps to reduce the level of NRLM sulfur to 15 ppm allows for a short lead time for

implementation, enabling the environmental benefits to begin as soon as possible.
Fuel Standard Feasibility

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5A.2 Impact of Diesel Sulfur Emission Products on Emission-Control

Systems

EPA is restricting the sulfur content of nonroad diesel fuel nationwide to no more than

15 ppm beginning in 2010, to enable compliance with new emission standards based on the use

of advanced emission control technology that will be available to nonroad diesel engines. It is

apparent that sulfur in nonroad diesel fuel significantly impairs the emission-control technology

of nonroad engines designed to meet the final emission standards. As discussed in Chapter 4.1,

existing aftertreatment technologies will be capable of achieving dramatic reductions in NOx and

PM emissions from nonroad engines when the standards based on use of advanced aftertreatment

devices take effect in the 2011 and later model years. The aftertreatment technology for PM is

already in an advanced state of development and being tested in fleet demonstrations in the U.S.

and Europe. The NOx aftertreatment technology is in a less-advanced, but still highly

promising, state of development, and, as discussed in Chapter 4.1, EPA believes the lead time

between now and 2011 will provide sufficient opportunity to adapt this technology for use on

nonroad engines. EPA believes these aftertreatment technologies will be in general use

beginning in 2011, with the diesel sulfur controls adopted in this rule.

At today’s typical sulfur concentrations, these aftertreatment technologies cannot be

introduced widely into the marketplace. Not only does their efficiency at reducing emissions fall

off dramatically at elevated fuel sulfur concentrations, but engine operation impacts and

permanent damage to the aftertreatment systems are also possible. To ensure regeneration of

the diesel particulate filter at exhaust temperatures typical of nonroad diesel engines as described

in Chapter 4.1.1.3, we are expecting that precious group metals (primarily platinum) will be

used in their washcoat formulations. There are two primary mechanisms by which sulfur in

nonroad diesel fuel can limit the effectiveness or robustness of diesel particulate filters which

rely on a precious metal oxidizing catalyst. The first is inhibition of the oxidation of NO to NO2

and the second is the preferential oxidation of SO2 to SO3, forming a precursor to sulfate

particulate matter. With respect to NOx aftertreatment, all the NOx aftertreatment technologies

discussed in Chapter 4.1.2 that EPA believes will generally be available to meet the standards

are expected to utilize platinum to oxidize NO to NO2 to either improve the NOx reduction

efficiency of the catalysts at low temperatures or, as in the case of the NOx adsorber, as an

essential part of the process of NOx storage and regeneration. This reliance of NO2 as an

integral part of the reduction process means that the NOx aftertreatment technologies, like the

PM aftertreatment technologies, would be significantly impaired by the sulfur in nonroad diesel

fuel. This is because sulfur, in the form of SOx, competes with NOx to be stored by the

aftertreatment device. The resulting sulfate is harder to break down than the stored NOx, and is

not normally released during the regeneration phase (i.e. SOx is stored preferentially to NOx by

the device). The sulfur therefore continues to build up, preventing storage of NOx, and

rendering the device ineffective. Further, although this problem can be addressed by adding a

“desulfation” phase to aftertreatment operation, the number of these desulfation events needs to

be minimized in order to prevent damage to the aftertreatment device. 

 Current sulfur levels also impair performance and durability of diesel oxidation catalysts
Final Regulatory Impact Analysis

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(DOCs), which some of the 0-75 hp nonroad engines may utilize to achieve the 2008 emission

standards for PM. See chapter II. A of the preamble and Chapter 4.1.1.2 of this RIA. Although

EPA would not justify its decision to reduce sulfur levels in nonroad diesel fuel to 500 ppm for

this reason alone, it is worth pointing out the benefits to these PM emission control technologies

which result from the reduction. 

5A.3 Sulfur Levels that Nonroad Engines Can Tolerate

As discussed in Chapter 4, there are three key factors which, taken together, lead us to

conclude that a nonroad diesel sulfur cap of 15 ppm is necessary so the NOx and PM

aftertreatment technology on nonroad engines will function properly and be able to meet the 

emission standards. These factors are the impact of higher sulfur levels on the efficiency and

reliability of the control systems, and on the engine’s fuel economy.

The efficiency of emission control technologies at reducing harmful pollutants is directly

impacted by sulfur in nonroad diesel fuel. Initial and long term conversion efficiencies for NOx,

HC, CO and diesel PM emissions are significantly reduced by catalyst poisoning and catalyst

inhibition due to sulfur. NOx conversion efficiencies with the NOx adsorber technology in

particular are dramatically reduced in a very short time due to sulfur poisoning of the NOx

storage bed. In addition, total PM control efficiency is negatively impacted by the formation of

sulfate PM. The formation of sulfate PM is likely to be in excess of the total PM standard ,

unless nonroad diesel fuel sulfur levels are below 15 ppm. When sulfur is kept at these low

levels, both PM and NOx aftertreatment devices are expected to operate at high levels of

conversion efficiency, allowing compliance with the PM and NOx emission standards.

The reliability of the emission control technologies to continue to function as required

under all operating conditions for the life of the engine is also directly impacted by sulfur in

nonroad diesel fuel. As discussed in Chapter 4, sulfur in nonroad diesel fuel can prevent proper

operation and regeneration of both NOx and PM advanced aftertreatment control technologies

leading to permanent loss in emission control effectiveness and even catastrophic failure of the

systems. For example, if regeneration of a PM filter does not occur, catastrophic failure of the

filter can occur in less than a single tank full of high-sulfur nonroad diesel fuel. For NOx

adsorbers, keeping sulfur levels no higher than 15 ppm is needed to minimize the number of

desulfation events to provide a high efficiency operation over the useful life of the engine. It is

only through the availability of nonroad diesel fuel with sulfur levels less than 15 ppm that these

technologies can reliably be used to achieve the 90+ % emission reductions of PM and NOx on

which the 2011 and later model year standards are based. We believe that diesel fuel sulfur

levels of 15 ppm are needed and would allow these technologies to operate properly throughout

the life of the vehicle, including proper periodic or continuous regeneration.

 The sulfur content of nonroad diesel fuel will also impact the fuel economy of nonroad

engines equipped with NOx and PM aftertreatment technologies. As discussed in detail in

Chapter 4.1.7, NOx adsorbers are expected to consume nonroad diesel fuel in order to cleanse

themselves of stored sulfates and maintain efficiency. The larger the amount of sulfur in
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nonroad diesel fuel, the greater this adverse impact on fuel economy. As sulfur levels increase

above 15 ppm, the fuel economy impact quickly changes from merely noticeable to

unacceptable. Likewise PM trap regeneration is inhibited by sulfur in nonroad diesel fuel. This

leads to increased PM loading in the diesel particulate filter, increased exhaust backpressure, and

poorer fuel economy. Thus for both NOx and PM technologies, the lower the fuel sulfur level,

the better the fuel economy of the vehicle.

As a result of these factors, we find that 15 ppm represents an upper threshold of

acceptable nonroad diesel fuel sulfur levels for use with nonroad engines using generally

available advanced aftertreatment for PM and for NOx.

5A.4 Sulfur Sensitivity of Other Emission Control Devices or Systems

Section 211(c)(2)(B) requires that, prior to adopting a fuel control based on a significant

impairment to vehicle emission-control systems, EPA consider available scientific and economic

data, including a cost benefit analysis comparing emission-control devices or systems which are

or will be in general use that require the proposed fuel control with such devices or systems

which are or will be in general use that do not require the proposed fuel control. As described

below, we conclude that the aftertreatment technology expected to be used to meet the nonroad

standards would be significantly impaired by operation on high-sulfur (greater than 15 ppm)

nonroad diesel fuel. Our analysis of the available scientific and economic data can be found

elsewhere in this document, including an analysis of the environmental benefits of the emission

standards (Chapter 3), an analysis of the costs and the technological feasibility of controlling

sulfur to the levels established in the final rule (Chapter 7), and a cost-effectiveness analysis of

the sulfur control and nonroad emission standards (Chapter 8). Under section 211(c)(2)(B), as

just noted, EPA is also required to compare the costs and benefits of achieving emission 

standards through emission-control systems that would not be sulfur-sensitive, if any such

systems are or will be in general use. 

We have determined that there are not (and will not be in the foreseeable future) emission

control devices available for general use in nonroad engines that can meet the nonroad emission

standards and would not be significantly impaired by nonroad diesel fuel with high sulfur levels. 

NOx and PM emissions cannot be reduced anywhere near the magnitude contemplated by the

final emission standards without the application of aftertreatment technology. As discussed in

Chapter 4, there are a number of aftertreatment technologies that are currently being developed

for both NOx and PM control with varying levels of effectiveness, sulfur sensitivity, and

potential application to nonroad engines. 

As discussed in Chapter 4.1, all the aftertreatment technologies that could be used to

meet the PM or NOx standards are significantly impaired by the sulfur in diesel fuel. For PM

control, all PM aftertreatment t technology that is capable of meeting the PM aftertreatmentbased Tier 4 standards would need the level of sulfur control adopted in this rule. In addition,

the NOx aftertreatment technologies evaluated by EPA all rely on the use of catalytic processes

to increase the effectiveness of the device in reducing NOx emissions. For example both NOx
Final Regulatory Impact Analysis

5-106

adsorbers and compact SCR would rely on noble metals to oxidize NO to NO2, to increase NOx

conversion efficiency at the lower exhaust temperatures found in diesel motor vehicle operation. 

This catalytic process, however, produces sulfate PM from the sulfur in the diesel fuel, and these

NOx aftertreatment devices therefore need the level of sulfur control adopted in this rule in order

for the vehicle to comply with the PM standard. 

In addition, compact SCR is not a technology that would be generally available by the

model year 2011 time frame. SCR systems require refilling with urea on a regular basis in order

to operate. Significant and widespread changes to the fuel distribution system infrastructure thus

would have to be made, and there is no practical expectation that this would occur, with or

without the low-sulfur standard adopted in this final rule. While it is feasible and practical to

expect that compact SCR may have a role in specific controlled circumstances, such as certain

centrally fueled fleets, or for generator sets using greater than 750 hp engines, it is not realistic at

this time to expect that the fuel distribution system infrastructure changes needed for widespread

and general use of compact SCR on nonroad engines will be in place by the model year 2011

time frame. Finally, for NOx control, both NOx adsorbers and compact SCR are significantly

impaired by sulfur in diesel fuel, and (as explained above) both technologies would need very

large reductions in sulfur from current levels to meet the NOx standard adopted in this final rule.

EPA believes that the requirement of a cost benefit analysis under section 211(c)(2)(B) is not

aimed at evaluating emission-control technologies that would each require significant additional

or different EPA fuel control regulations before the technology could be considered generally

available. 

Moreover, it is undisputed that any generally available technology capable of achieving

the PM aftertreatment-based standards requires 15 ppm sulfur fuel. Thus,15 ppm sulfur fuel will

be needed in any event.

In sum, EPA believes that both PM and NOx aftertreatment technologies require 15 ppm

sulfur fuel. 

 As described in Chapter 4, EPA anticipates that all the nonroad engine technologies

expected to be used to meet the final nonroad standards will require the use of nonroad diesel

fuel with sulfur levels capped at 15 ppm. If we do not control diesel sulfur to the finalized

levels, we would not be able to set nonroad standards as stringent as those we are finalizing in

this final rule. Consequently, EPA concludes that the benefits that would be achieved through

implementation of the engine and sulfur control programs cannot be achieved through the use of

emission control technology that does not need the sulfur control adopted in this rule, and would

be generally available to meet the emission standards adopted in this rule.

This also means that if EPA were to adopt emission standards without controlling diesel

sulfur content, the standards would be significantly less stringent than those finalized in this rule,

based on what would be technologically feasible with current or 500 ppm sulfur levels.
Fuel Standard Feasibility

5-107

5A.5 Effect of Nonroad Diesel Sulfur Control on the Use of Other Fuels or

Fuel Additives

Section 211(c)(2)(C) requires that prior to prohibiting a fuel or fuel additive, EPA

establish that such prohibition will not cause the use of another fuel or fuel additive “which will

produce emissions which endanger the public health or welfare to the same or greater degree”

than the prohibited fuel or additive. This finding is required by the Act only prior to prohibiting

a fuel or additive, not prior to controlling a fuel or additive. Since EPA is not prohibiting use of 

sulfur in nonroad, locomotive or marine fuel, but rather is controlling the level of sulfur in these

diesel fuels, this finding is not required for this rulemaking. However, EPA does not believe that

the sulfur control will result in the use of any other fuel or additive that will produce emissions

that will endanger public health or welfare to the same or greater degree as the emissions

produced by nonroad diesel with uncontrolled sulfur levels.

Unlike the case of unleaded gasoline in the past, where lead performed a primary

function by providing the necessary octane for the vehicles to function properly, sulfur does not

serve any useful function in nonroad, locomotive or marine diesel fuel. It is not added to diesel

fuel, but comes naturally in the crude oil into which diesel fuel is processed. Were it not for the

expense of sulfur removal, it would have been removed from diesel fuel years ago to improve the

maintenance and durability characteristics of diesel engines. EPA is unaware of any function of

sulfur in nonroad, locomotive or marine diesel fuel that might have to be replaced once sulfur is

removed, with the possible exception of lubricity characteristics of the fuel. As discussed in

Chapters 4 and 5, there is some evidence suggesting that as sulfur is removed from diesel fuel

the natural lubricity characteristics of diesel fuel may be reduced. Depending on the crude oil

and the manner in which desulfurization occurs some low-sulfur diesel fuels can exhibit poor

lubricity characteristics. To offset this concern lubricity additives are sometimes added to the

diesel fuel. These additives, however, are already in common use today and EPA is unaware of

any health hazards associated with the use of these additives in diesel fuel, which would merely

be used in larger fractions of the diesel fuel pool. We do not anticipate that their use would

produce emissions which would reduce the large public health and welfare benefits that this rule

would achieve.

EPA is unaware of any other additives that might be necessary to add to nonroad,

locomotive or marine diesel fuel to offset the existence of sulfur in the fuel. EPA is also

unaware of any additives that might need to be added to nonroad, locomotive or marine diesel

fuel to offset any other changes to the fuel which might occur during the process of removing

sulfur.
Final Regulatory Impact Analysis

5-108

1. Baseline Submissions for the Reformulated Gasoline Program.

2. Swain, Edward J., Gravity, Sulfur Content of U.S. Crude Slate Holding Steady, Oil and Gas

Journal, January 13, 1997.

3. Montcrieff, Ian T., Montgomery, David W., Ross, Martin T., An Assessment of the Potential

Impacts of Proposed Environmental Regulations on U.S. Refinery Supply of Diesel Fuel,

Charles River Associates, August 2000.

4. Final Report, 1996 American Petroleum Institute / National Petroleum Refiners Association,

Survey of Refining Operations and Product Quality, July 1997.

5. Final Report, 1996 American Petroleum Institute / National Petroleum Refiners Association,

Survey of Refining Operations and Product Quality, July 1997.

6. Final Report, 1996 American Petroleum Institute / National Petroleum Refiners Association,

Survey of Refining Operations and Product Quality, July 1997.

7. Dickinson, Cherl L., Strum, Gene P., Diesel Fuel Oils, 1997, TRW Petroleum Technologies,

November 2001.

8. American Society for Testing and Materials (ASTM), “Standard Specification for Diesel Fuel

Oils”, ASTM D 975 and “Standard Specification for Fuel Oils”, ASTM D 396. Some pipeline

companies that transport diesel fuel have limits for density and pour point, which are properties

that ASTM D 975 does not provide specifications on. 

9. Regulatory Impact Analysis - Control of Air Pollution from New Motor Vehicles, Tier 2

Motor Vehicle Emission Standards and Gasoline Sulfur Control Requirements, Environmental

Protection Agency, December 1999.

10. Hamilton, Gary L., ABB Lummus, Letter to Lester Wyborny, U.S. EPA, August 2, 1999.

11. Mayo, S.W., “Mid-Distillate Hydrotreating: The Perils and Pitfalls of Processing LCO.”

12. Peries, J-P., Jeanlouis, P-E, Schmidt, M, and Vance, P.W., “Combining NiMo and CoMo

Catalysts for Diesel Hydrotreaters,” NPRA 1999 Annual Meeting, Paper 99-51, March 21-23,

1999.

13. Tippett, T., Knudsen, and Cooper, B., “Ultra Low Sulfur Diesel: Catalyst and Process

Options,” NPRA 1999 Annual Meeting, Paper 99-06, March 21-23, 1999.

14.Tippett, T., Knudsen, and Cooper, B., “Ultra Low Sulfur Diesel: Catalyst and Process

Options,” NPRA 1999 Annual Meeting, Paper 99-06, March 21-23, 1999.

References to Chapter 5
Fuel Standard Feasibility

5-109

15.Tungate, F.L., Hopkins, D., Huang, D.C., Fletcher, J.C.Q., and E. Kohler, “Advanced

distillate Hydroprocessing, ASAT, A Trifunctional HDAr/HDS/HDN Catalyst,” NPRA 1999

Annual Meeting, Paper AM-99-38., March 21-23, 1999.

16.Gerritsen, L.A., Production of Green Diesel in the BP Amoco Refineries, Presentation by

Akzo Nobel at the WEFA conference in Berlin, Germany, June 2000.

17.Gerritsen, L.A., Sonnemans, J.W M, Lee, S.L., and Kimbara, M., “Options to Met Future

European Diesel Demand and Specifications.”

18.Conversation with Steve Mayo, Technical Service Development Manager, Akzo Nobel,

January 2003.

19.www.akzonobel-catalysts.com.

20. Brim Technology Bulletin, Haldor Topsoe Incorporated, March 2004.

21.Eng, Odette T., Kennedy, James E., “FCC Light Cycle Oil: Liability or Opportunity?,”

Technical Paper #AM-00-28, presented at the National Petrochemical and Refiners Association

Annual Meeting, March 26-28, 2000.

22.Centinel Hydroprocessing Catalysts: A New Generation of Catalysts for High-Quality Fuels,

Criterion Catalysts and Technologies Company, October 2000.

23. Ascent and Centinel Catalysts, Criterion Catalysts and Technologies Bulletin, March 2004.

24.Conversation with Lee Grannis, Criterion Catalysts, February 2004.

25.Axens catalyst bulletins 021HR-406A and 021HR-468A.

26.Wilson, R., “Cost Curves for Conventional HDS to Very Low Levels,” February 2, 1999.

27. Peries, J-P., Jeanlouis, P-E, Schmidt, M, and Vance, P.W., “Combining NiMo and CoMo

Catalysts for Diesel Hydrotreaters,” NPRA 1999 Annual Meeting, March 21-23, 1999.

28.Tippett, T., Knudsen, and Cooper, B., “Ultra Low Sulfur Diesel: Catalyst and Process

Options,” NPRA 1999 Annual Meeting, Paper 99-06, March 21-23, 1999.

29. “Processes for Sulfur Management,” IFP.

30.Tungate, F.L., Hopkins, D., Huang, D.C., Fletcher, J.C.Q., and E. Kohler, “Advanced

distillate Hydroprocessing, ASAT, A Trifunctional HDAr/HDS/HDN Catalyst,” NPRA 1999

Annual Meeting, Paper AM-99-38., March 21-23, 1999.

31.Gerritsen, L.A., Production of Green Diesel in the BP Amoco Refineries, Presentation by

Akzo Nobel at the WEFA conference in Berlin, Germany, June 2000.
Final Regulatory Impact Analysis

5-110

32.Patent number 6,123,835, filed June 1998, granted September 2000.

33.Patent number 6,428,686, filed June 2000, granted August 2002.

34.Ackerson, Michael; Skeds, Jon, Presentation to the Clean Diesel Independent Review Panel,

Process Dynamics and Linde Process Plants, July 30, 2002. 

35.Conversation with Jon Skeds, Director of Refining, Linde BOC Process Plants LLC, January

2004. 

36.Kidd, Dennis, S-Zorb - Advances in Applications of Phillips S-Zorb Technology, Presented at

the NPRA Q & A meeting, October 2000.

37.Conversation with Gary Schoonveld, Fuel Regulation/Asset Development, Conoco-Phillips,

November 2003. 

38. 55 FR 34138, August 21, 1990.

39.Refining Industry Profile Study; EPA contract 68-C5-0010, Work Assignment #2-15, ICF

Resources, September 30, 1998.

40.Regulatory Impact Analysis for the Highway Diesel Final Rule, EPA Air Docket A-99-06

41.Presentations from the November 2002 Clean Diesel Fuel Implementation Workshop in

Houston, Texas are available at http://www.epa.gov/otaq/diesel.htm#public Also available at this

website are rulemaking documents and fact sheets related to the highway diesel fuel final rule.

42. Moncrief, Philip and Ralph Ragsdale, “Can the U.S. E&C Industry Meet the EPA’s Low

Sulfur Timetable,” NPRA 2000 Annual Meeting, March 26-28. 2000, Paper No. AM-00-57.

43. National Petroleum Council, “ U.S. Petroleum Assuring Adequacy and Affordability of

Cleaner Fuels”, June 2000 pages 118-133.

44. Regulatory Impact Analysis - Control of Air Pollution from New Motor Vehicles: The Tier

2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements, U.S. EPA,

December 1999, EPA 420-R-99-023.

45. Regulatory Impact Analysis - Control of Air Pollution from New Motor Vehicles: The Tier

2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements, U.S. EPA,

December 1999, EPA 420-R-99-023.

46. Moncrief, Philip and Ralph Ragsdale, “Can the U.S. E&C Industry Meet the EPA’s Low

Sulfur Timetable,” NPRA 2000 Annual Meeting, March 26-28. 2000, Paper No. AM-00-57.

47.Chapter IV of the Regulatory Impact Analysis for the Final Highway Diesel Rule contained a

substantial background discussion regarding past experience in maintaining adequate fuel
Fuel Standard Feasibility

5-111

lubricity in low-sulfur fuels, EPA Air docket A-99-06.

48. Letter from L. Erlandsson, MTC AB, to Michael P. Walsh, dated October 16, 2000. Docket

A-99-06, item IV-G-42.

49. Chevron Products Diesel Fuel Technical Review provides a discussion of the impacts on fuel

lubricity of current diesel fuel compositional requirements in California versus the rest of the

nation. http://www.chevron.com/prodserv/fuels/bulletin/diesel/l2%5F7%5F2%5Frf.htm

50. Final Report, 1996 American Petroleum Institute / National Petroleum Refiners Association,

Survey of Refining Operations and Product Quality, July 1997.
CHAPTER 6: Estimated Engine and Equipment Costs

6.1 Methodology for Estimating Engine and Equipment Costs . . . . . . . . . . . . . . . . . . . . . 6-2

6.2 Engine-Related Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.1 Engine Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.1.1 Engine and Emission-Control Device R&D . . . . . . . . . . . . . . . . . . . . . . . . 6-5

6.2.1.2 Engine-Related Tooling Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-17

6.2.1.3 Engine Certification Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-21

6.2.2 Engine Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-25

6.2.2.1 NOx Adsorber System Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-28

6.2.2.2 Catalyzed Diesel Particulate Filter Costs . . . . . . . . . . . . . . . . . . . . . . . . . 6-34

6.2.2.3 CDPF Regeneration System Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-38

6.2.2.4 Diesel Oxidation Catalyst (DOC) Costs . . . . . . . . . . . . . . . . . . . . . . . . . . 6-40

6.2.2.5 Closed-Crankcase Ventilation (CCV) System Costs . . . . . . . . . . . . . . . . . 6-42

6.2.2.6 Variable Costs of Conventional Technologies for Engines under 75 hp and

over 750 hp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-43

6.2.2.7 Summary of Engine Variable Cost Equations . . . . . . . . . . . . . . . . . . . . . . 6-48

6.2.3 Engine Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-49

6.2.3.1 Operating Costs Associated with Oil-Change Maintenance for New and

Existing Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-50

6.2.3.2 Operating Costs Associated with CDPF Maintenance for New CDPFEquipped Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-54

6.2.3.3 Operating Costs Associated with Fuel Economy Impacts on New Engines

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-55

6.2.3.4 Operating Costs Associated CCV Maintenance on New Engines . . . . . . . 6-60

6.3 Equipment-Related Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-60

6.3.1 Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-61

6.3.1.1 Equipment Redesign Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-61

6.3.1.2 Costs Associated with Changes to Product Support Literature . . . . . . . . . 6-67

6.3.1.3 Total Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-67

6.3.2 Equipment Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-69

6.3.3 Potential Impact of the Transition Provisions for Equipment Manufacturers . . 6-72

6.4 Summary of Engine and Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-74

6.4.1 Engine Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-74

6.4.1.1 Engine Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-74

6.4.1.2 Engine Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-75

6.4.1.3 Engine Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-75

6.4.2 Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-77

6.4.2.1 Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-77

6.4.2.2 Equipment Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-77

6.4.3 Engine and Equipment Costs on a Per Unit Basis . . . . . . . . . . . . . . . . . . . . . . . 6-78

6.5 Weighted Average Costs for Example Types of Equipment . . . . . . . . . . . . . . . . . . . . 6-82

6.5.1 Summary of Costs for Some Example Types of Equipment . . . . . . . . . . . . . . . 6-82

6.5.2 Method of Generating Costs for a Specific Piece of Equipment . . . . . . . . . . . . 6-86

6.5.3 Costs for Specific Examples from the Proposal . . . . . . . . . . . . . . . . . . . . . . . . . 6-89

6.6 Residual Value of Platinum Group Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-90
Estimated Engine and Equipment Costs

6-1

CHAPTER 6: Estimated Engine and Equipment Costs

This chapter presents the engine and equipment costs we have estimated for meeting the new

engine emissions standards. Section 6.1 includes a brief outline of the methodology used to

estimate the engine and equipment costs. Sections 6.2 and 6.3 present the projected costs of the

individual technologies we expect manufacturers to use to comply with the new emissions

standards, along with a discussion of fixed costs such as research and development (R&D),

tooling, certification, and equipment redesign. Section 6.4 summarizes these costs and Section

6.5 details cost estimates for several example pieces of equipment. A complete presentation of

the aggregate cost of compliance for engines and equipment is in Chapter 8.

Note that the costs presented here are for those nonroad engines and equipment that are

mobile nonroad equipment and are, therefore, subject to nonroad engine standards. These costs

would not apply for that equipment that is stationary—some portion of some equipment

segments such as generator sets, pumps, compressors—and not subject to nonroad engine

standards. The reader should know that some nonroad diesel equipment is not covered by

nonroad engine standards. Those nonroad engines that receive permits from local authorities as

stationary source emitters (i.e., some gensets, pumps, compressors, etc.) are not covered by

nonroad engine standards. In most cases, for what are very similar products, some fraction will

be permitted as stationary sources while others remain mobile sources. 

To maintain consistency in the way our emission reductions, costs, and cost-effectiveness

estimates are calculated, our cost methodology for engines and equipment relies on the same

projections of new nonroad engine growth as those used in our emissions inventory projections. 

Our NONROAD emission inventory model includes estimates of future engine populations that

are consistent with the future engine sales used in our cost estimates. The NONROAD model

inputs include an estimate of what percentage of gensets sold in the U.S. are “mobile” and, thus,

subject to the nonroad standards, and what percentage are “stationary” and not subject to the

nonroad standards. These percentages vary by power category and are documented in “Nonroad

Engine Population Estimates,” EPA Report 420-P-02-004, December 2002. For gensets >750

horsepower, NONROAD assumes 100 percent are stationary and, therefore, not subject to the

new nonroad standards. For gensets <750 horsepower, we have assumed other percentages of

mobile versus stationary. During our discussions with engine manufacturers after the proposal,

it became apparent not only that our estimate for >750 horsepower gensets may not be correct

and many are indeed mobile, but also that some of our estimates for <750 horsepower gensets

may also not be correct and many more than we estimate may indeed be mobile. If true, this

increased percentage of mobile gensets will be subject to the new nonroad standards. 

Unfortunately, we have not received sufficient data to make a conclusive change to the

NONROAD model and, therefore, for the above described purpose of maintaining consistency,

we have not included the costs or the emissions reductions in our official estimates for this final

rule. In Chapter 8, Appendix A, we present a sensitivity analysis that includes both an estimate
Final Regulatory Impact Analysis

6-2

of the costs and emissions reductions that would result from including a higher percentage of

gensets as mobile machines and subject to the new standards.

Note also that the costs presented here do not include potential savings associated with our

engine ABT program or our Transition Program for Equipment Manufacturers. In addition, we

have assumed that engine companies who are eligible for the small business engine manufacturer

specific provisions do not take advantage of the unique flexibilities the rule provides for them,

which includes the opportunity to delay compliance with the Tier 4 emission standards for a full

three model years. While we fully expect companies to use them to reduce compliance costs, we

do not factor them into the cost analysis because they are voluntary programs. This analysis of

compliance costs relates to regulatory requirements that are part of the nonroad Tier 4 final rule. 

Unless noted otherwise, all costs are in 2002 dollars.

6.1 Methodology for Estimating Engine and Equipment Costs

This analysis makes several simplifying assumptions regarding how manufacturers will

comply with the new emission standards. First, in each power category, we assume a single

technology recipe, as discussed in Chapter 4. However, we expect that each manufacturer will

evaluate all possible technology avenues to determine how to best balance costs while ensuring

compliance. As noted, for developing cost estimates, we have assumed that the industry does

not use either the transition program for equipment manufacturers or averaging, banking, and

trading, both of which offer the opportunity for significant cost reductions. Given these

simplifying assumptions, we believe the projections presented here probably overestimate the

costs of the different approaches toward compliance that manufacturers may ultimately take.

For smaller nonroad engines—those under 75 hp—many of the anticipated emission-control

technologies will be applied for the first time. Therefore, we have sought input from a large

section of the regulated community regarding the future costs of applying these technologies to

diesel engines. Under contract with EPA, ICF Consulting provided questions to several engine

and parts manufacturers regarding costs associated with emission-control technologies for diesel

engines. The responses to these questions were used as a first step toward estimating the costs

for many of the technologies we believe manufacturers will use. These costs form the basis for

our estimated costs for “traditional” engine technologies such as EGR and fuel-injection

systems.1 Note that, while these technologies are expected to be added to <75hp engines for the

first time, they are being added, or will be, to >75hp engines to meet the Tier2/3 standards. We

have used the same methodology to develop the costs for these technologies for <75hp engines

as was used to develop the costs for >75hp engines.2

Costs for exhaust emission-control devices (for example, catalyzed diesel particulate filters

(CDPF), NOx adsorbers, and diesel oxidation catalysts (DOC)) were estimated using the

methodology used in our HD2007 rulemaking. In that rulemaking effort, ICF Consulting, under

contract to EPA, provided surveys to nine engine manufacturers seeking information relevant to

estimating the costs for and types of emission-control technologies that might be enabled with

low-sulfur diesel fuel. The survey responses were used as the first step in estimating the costs
Estimated Engine and Equipment Costs

A There is one exception to this – for engine R&D conducted to support the new standards for <75 horsepower

engines in the 2008 model year, we have used a four year period (i.e., 2004 through 2007) over which to spread the

R&D expenditures.

B Throughout this analysis we use the term “redesign” to refer to all work needed to complete the equipment

modifications we believe will be necessary to accommodate the engine changes that will result from the new engine

standards.

6-3

for advanced emission-control technologies anticipated for meeting the HD2007 standards.3 We

then built upon these costs based on input from members of the Manufacturers of Emission

Controls Association. Because the anticipated emission-control technologies are the same as

expected for highway engines, and because the suppliers of the technologies are the same for

nonroad engines as for highway engines, we have used that analysis as the basis for estimating

the costs of these technologies in this rulemaking. 

Costs of control include variable costs (for incremental hardware costs, assembly costs, and

associated markups) and fixed costs (for tooling, R&D, and certification). For technologies sold

by a supplier to the engine manufacturers, costs are either estimated based on a direct cost to

manufacture the system components plus a 29 percent markup to account for the supplier's

overhead and profit or, when available, based on estimates from suppliers on expected total costs

to the manufacturers (inclusive of markups).4 Estimated variable costs for new technologies

include a markup to account for increased warranty costs. Variable costs are additionally

marked up to account for both manufacturer and dealer overhead and carrying costs. The

manufacturer’s carrying cost was estimated to be four percent of the direct costs to account for

the capital cost of the extra inventory and the incremental costs of insurance, handling, and

storage. The dealer’s carrying cost was estimated to be three percent of their direct costs to

account for the cost of capital tied up in inventory. We adopted this same approach to markups

in the HD2007 rule, based on industry input.5

We have also identified various factors that cause cost impacts to decrease over time, making

it appropriate to distinguish between near-term and long-term costs. Research in the costs of

manufacturing has consistently shown that, as manufacturers gain experience in production, they

are able to apply innovations to simplify machining and assembly operations, use lower cost

materials, and reduce the number or complexity of component parts.6 This analysis incorporates

the effects of this learning curve as described in Section 6.2.2.

Fixed costs for engine R&D are estimated to be incurred over the five-year period preceding

introduction of the engine.A Fixed costs for tooling and certification are estimated to be incurred

one year ahead of initial production. Fixed costs for equipment redesignB are estimated to be

incurred over a two-year period preceding introduction of the piece of equipment, while

equipment tooling costs are estimated to be incurred one year ahead of initial production. All

fixed cost expenditures are amortized using a seven percent capital cost to reflect the time value

of money. Engine fixed costs are then “recovered” over a five-year amortization period

including the same seven percent cost of capital. This is true except where a phase-in of a new

standard occurs in which case the fixed costs are recovered during the phase-in years and then
Final Regulatory Impact Analysis

C We have estimated a “recovered” cost for all engine and equipment fixed costs to provide for a per-unit analysis of

the cost of the final rule. In general, in environmental economics, it is more conventional to simply count the total costs

of the program (i.e., opportunity costs) in the year they occur. However, this approach does not directly estimate a perunit production cost since fixed costs occur before the standards take effect and, therefore, prior to the production of new

compliant engines. In our methodology, fixed costs grow at a seven percent rate until they can be “recovered” on

complying units. Note that the approach used here results in a higher estimate of the total costs of the program since the

recovered costs include a seven percent capital cost to reflect the time value of money. Our intent is to reflect the cost of

capital investments made in emissions control rather than investments made in other activities.

6-4

during the five years following 100 percent compliance.C Equipment fixed costs are recovered

over a 10-year amortization period including the same seven percent captial cost; the longer

amortization period for equipment fixed costs reflects the longer product cycle for equipment. 

We have also included lifetime operating costs where applicable. These include costs associated

with the higher cost fuel, expected fuel economy impacts, increased maintenance demands

resulting from the addition of new emission-control hardware, and expected savings associated

with lower oil-change maintenance costs as a result of the low-sulfur fuel.

A simplified overview of the methodology used to estimate engine and equipment costs is as

follows:

• For fixed costs (i.e., R&D, redesign, tooling, certification), we estimate the total dollars that

industry will spend. We then calculate the total dollars that they will recover in each year of

the program following implementation. These annual recovered costs represent our estimate

of fixed costs associated with this final rule. In Section 6.5 and in some engine-related fixed

cost tables in Section 6.2.1, we also present an estimate of per-unit fixed costs. These perunit fixed costs are impacted by the way we have broken up the power categories in this cost

analysis and by other factors (for example, the engine prices we have estimated) as discussed

in more detail below. Because we do not know how manufacturers recover their costs on a

per-unit basis, we present these per-unit fixed costs for informational purposes only. We do

not use these per-unit fixed cost estimates in our cost-per-ton calculations; instead, we use

the annual cost of recovery totals in the aggregate cost-per-ton calculations presented in

Chapter 8.

• For engine variable costs (i.e., emission-control hardware), we first estimate the cost per

piece of technology/hardware. As described in detail in Section 6.2.2, emission-control

hardware costs tend to be directly related to engine characteristics—for example, emissioncontrol devices are sized according to engine displacement so costs vary by displacement;

fuel-injection systems vary in cost according to how many fuel injectors are required so costs

vary by number of cylinders. This way we are able to determine a variable cost equation as a

function of engine displacement or as a function of the number of cylinders. We then

consider each unique engine’s baseline technology package using a database from Power

Systems Research of all nonroad equipment sold in the United States.7

 That database lists

engine characteristics for every one of over 4,500 unique equipment models sold in the

United States and provides the sales of each piece of equipment. Using the baseline engine

characteristics of each engine, the projected technology package for that engine, and the
Estimated Engine and Equipment Costs

6-5

variable cost equations described in Section 6.2, we calculate a variable cost for the engine in

each of the over 4,500 unique equipment models sold in the United States. This variable cost

per engine is then multiplied by that engine’s projected sales in each year for the years after

the new standards take effect. We then total the annual costs for all engines to get the

fleetwide variable costs per year. These fleetwide variable costs per year are then used in the

cost-per- ton calculations presented in Chapter 8.

• Note that the cost-per-ton calculation (see Chapter 8 of this RIA for our cost-per-ton

analysis) is never impacted by how many power categories we use in our cost analysis. We

sometimes break up the fleet into more power categories than would seem reasonable given

the structure of the emission standards. We do this for several reasons: (1) phase-ins of

standards and/or different levels of baseline versus new standards sometimes force such

breakouts; and, (2) greater stratification (i.e., breaking up the 75 to 175 hp range and the 175

to 750 hp range) provides a better picture for use in our estimate of potential recovery of

fixed costs. Importantly, the number of power categories used does not impact the total costs

estimated as a result of the new emission standards, and these are the total costs used to

calculate a cost-per-ton number. 

Engine costs are presented first – fixed costs, variable costs, then operating costs. Equipment

costs follow – fixed costs then variable costs. A summation of engine and equipment costs

follows these discussions. Variable cost estimates presented here represent an expected

incremental cost of the engine or piece of equipment in the model year of introduction. Variable

costs in subsequent years decrease as a result of several factors, as described below. All costs

are presented in 2002 dollars.

6.2 Engine-Related Costs

6.2.1 Engine Fixed Costs

6.2.1.1 Engine and Emission-Control Device R&D

The technologies described in Chapter 4 represent those technologies we believe will be used

to comply with the Tier 4 emission standards. These technologies are also part of an ongoing

research and development effort geared toward compliance with the HD2007 standards and, to

some extent, the current and future light-duty diesel vehicle standards in the US and in Europe. 

Those engine manufacturers making R&D expenditures toward compliance with highway

emission standards will have to undertake some R&D effort to transfer emission-control

technologies to engines they wish to sell into the nonroad market. These R&D efforts will allow

engine manufacturers to develop and optimize these new technologies for maximum emissioncontrol effectiveness, while continuing to design engines with good performance, durability, and

fuel efficiency characteristics. However, many nonroad engine manufacturers are not part of the

ongoing R&D effort toward compliance with highway emission standards because they do not

sell engines into the highway market. These manufacturers are expected to learn from the R&D

work that has already occurred and will continue through the coming years through their contact
Final Regulatory Impact Analysis

D In order to avoid inconsistencies in the way our emission reductions, and cost-effectiveness estimates are

calculated, our cost methodology for engines and equipment relies on the same projections of new nonroad engine

growth as those used in our emissions inventory projections. Our NONROAD emission inventory model includes

estimates of future engine populations that are consistent with the future engine sales used in our cost estimates. The

NONROAD model inputs include an estimate of what percentage of gensets sold in the U.S. are “mobile” and, thus,

subject to the nonroad standards, and what percentage are “stationary” and not subject to the nonroad standards. 

These percentages vary by power category and are documented in “Nonroad Engine Population Estimates,” EPA

6-6

with highway manufacturers, emission-control device manufacturers, and the independent engine

research laboratories conducting relevant R&D. Despite these opportunities for learning, we

expect the R&D expenditures for these nonroad-only manufacturers to be higher than for those

manufacturers already conducting R&D in response to the HD2007 rule and the light-duty diesel

requirements in the US and Europe.

We are projecting that several technologies will be used to comply with the Tier 4 emission

standards. We are projecting that NOx adsorbers and CDPFs will be the most likely

technologies used to meet the new emission standards for engines over 75 hp and, for engines

between 25 and 75 hp, that CDPFs will be used in 2013 to meet the new PM standard. The fact

that these technologies are being developed for implementation in the highway market before the

emission standards in this final rule take effect, and the fact that engine manufacturers have

several years to comply with the Tier 4 standards, ensures that the technologies used to comply

with the nonroad standards will undergo significant development before reaching production. 

This ongoing development will likely lead to reduced costs in three ways. First, we expect

research will lead to enhanced effectiveness for individual technologies, allowing manufacturers

to use simpler packages of emission-control technologies than we would predict currently, given

the current state of development. Second, we anticipate that the continuing effort to improve the

emission-control technologies will include innovations that allow lower-cost production. And

finally, we believe manufacturers will focus research efforts on any drawbacks, such as fuel

economy impacts or maintenance costs, in an effort to minimize or overcome any potential

negative effects.

We anticipate that manufacturers will introduce a combination of primary technology

upgrades to meet the new emission standards. Achieving very low NOx emissions requires basic

research on NOx emission-control technologies and improvements in engine management. 

Manufacturers are expected to address the challenge by optimizing the engine and exhaust

emission-control system to realize the best overall performance. This will entail optimizing the

engine and emission control system for both emissions and fuel economy performance in light of

the presence of the new exhaust emission control devices and their ability to control pollutants

previously controlled only via in-cylinder means or with exhaust gas recirculation. The NOx

adsorber technology in particular is expected to benefit from re-optimization of the engine

management system to better match the NOx adsorber’s performance characteristics. The

majority of the dollars we have estimated for research is expected to be spent on developing this

synergy between the engine and NOx exhaust emission-control systems. Therefore, for engines

where we project use of both a CDPF and a NOx adsorber (i.e., 75 to 750 hp), we have attributed

two-thirds of the R&D expenditures to NOx control, and one-third to PM control.D
Estimated Engine and Equipment Costs

Report 420-P-02-004, December 2002. For gensets >750 horsepower, NONROAD assumes 100 percent are

stationary and, therefore, not subject to the new nonroad standards. For gensets <750 horsepower, we have assumed

other percentages of mobile versus stationary. During our discussions with engine manufacturers after the proposal,

it became apparent not only that our estimate for >750 horsepower gensets may not be correct and many are indeed

mobile, but also that some of our estimates for <750 horsepower gensets may also not be correct and many more

than we estimate may indeed be mobile. If true, this increased percentage of mobile gensets will be subject to the

new nonroad standards. Unfortunately, we have not received sufficient data to make a conclusive change to the

NONROAD model to include the potentially increased percentages of mobile gensets and, therefore, for the above

described purpose of maintaining consistency, we have not included their costs or their emissions reductions in our

official estimates for this final rule (costs and emissions reductions for the current percentages in the NONROAD

model are included in our estimates for the final rule). Instead, we present a sensitivity analysis in Chapter 8 of the

RIA that includes both an estimate of the costs and emissions reductions that would result from including a higher

percentage of gensets as mobile equipment and subject to the new standards.

E Note that, while >750 hp mobile machine engines are not expected to add a NOx adsorber to comply with the new

engine standards, we have considered that the corporate R&D conducted for engines expected to add both a NOx

adsorber and a CDPF will apply for engines >750 hp given the general similarity between large engines above and below

6-7

For this analysis, we have estimated two elements to engine R&D: (1) corporate R&D, or

that R&D conducted by manufacturers using test engines to learn how NOx and PM control

technologies work and how they work together in a system; and, (2) engine line specific R&D,

or that R&D done to tailor the corporate R&D knowledge to each particular engine line. To

distinguish between these two R&D elements, here we refer to the former as corporate R&D and

the latter as engine line R&D. 

With respect to the former of these R&D elements—corporate R&D—we begin with our

HD2007 rule. In that rule, we estimated that each engine manufacturer would expend $35

million for R&D toward successfully implementing catalyzed diesel particulate filters (CDPF)

and NOx adsorbers. For this analysis, we express all monetary values in 2002 dollars which

means our HD2007 starting point equates to $36.1 million. For their nonroad R&D efforts on

>75 hp engines – those engines where we project that compliance will require a CDPF and a

NOx adsorber or CDPFs-only (engines >750 hp) – engine manufacturers that also sell into the

highway market will incur some level of R&D effort but not at the level incurred for the highway

rule. In many cases, the engines used by highway manufacturers in nonroad products are based

on the same engine platform as those engines used in highway products. However, power and

torque characteristics are often different, so manufacturers will need to expend some effort to

accommodate those differences. For these manufacturers, we have estimated that they will incur

an average R&D expense of $3.6 million not including the engine line R&D. This $3.6 million

R&D expense allows for the transfer of learning from highway R&D to their nonroad engines. 

For reasons noted above, two-thirds of this R&D is attributed to NOx control and one-third to

PM control for 75 to 750 hp engines; for the portion of this R&D that is allocated to engines

>750 hp, all of this R&D is attributed to PM control.

For those manufacturers that sell larger engines only into the nonroad market, and where we

project those engines to add a CDPF and a NOx adsorber (75 to 750 hp) or a CDPF-only (>750

hp), we believe they will incur a corporate R&D expense approaching that incurred by highway

manufacturers for the highway rule although not quite at the same levelE

. Nonroad
Final Regulatory Impact Analysis

750 hp. We have included additional engine line R&D for all engines, including those >750hp, that is unique from this

corporate R&D estimate.

6-8

manufacturers will be able to learn from the R&D efforts already underway for both the highway

rule and for the Tier 2 light-duty highway rule (65 FR 6698), and the light-duty and heavy-duty

diesel requirements in Europe. This learning may come from seminars, conferences, technical

publications regarding diesel engine technology (e.g., Society of Automotive Engineers technical

papers), and contact with highway manufacturers, emission-control device manufacturers, and

the independent engine research laboratories conducting relevant R&D. Therefore, we have 

estimated an average expenditure of 70 percent of that spent by highway manufacturers in their

highway efforts. This lower number—$25.3 million versus $36.1 million in the highway

rule—reflects the transfer of knowledge to nonroad manufacturers from the many other

stakeholders in the diesel industry. As noted above, two-thirds of this R&D is attributed to NOx

control and one-third to PM control. This value does not include the engine line R&D.

Note that the $3.6 million and $25.3 million estimates represent our estimate of the average

corporate R&D expected by manufacturers. Each manufacturer may have more or less than

these average figures.

For manufacturers selling smaller engines that we project will add only a CDPF (i.e., 25 to

75 hp engines in 2013), we have estimated that their average R&D will be roughly one-third that

incurred by manufacturers conducting CDPF/NOx adsorber R&D. We believe this is a

reasonable estimate because CDPF technology is further along in its development than is NOx

adsorber technology and, therefore, a 50/50 split is not appropriate. Using this estimate, the

average corporate R&D incurred by manufacturers that already have been selling engines into

both the highway and the nonroad markets will be $1.2 million not including engine line R&D,

and the average corporate R&D for manufacturers selling engines only into the nonroad market

will be roughly $8.3 million not including engine line R&D. All this R&D is attributed to PM

control.

For manufacturers selling engines that will add only a DOC or will make only some engineout modification (i.e., to meet the PM standard for engines under 75 hp in 2008), we have

estimated that their average corporate R&D will be roughly one-half the amount estimated for

their CDPF-only R&D. Application of a DOC should require very little R&D effort because

these devices have been used for years and because they require no special fueling strategies or

operating conditions to operate properly. Nonetheless, to avoid underestimating costs, we have

estimated that the R&D incurred by manufacturers selling any engines into both the highway and

nonroad markets will be roughly $600,000 not including engine line R&D, and the corporate

R&D for manufacturers selling engines only into the nonroad market will be roughly $4.2

million not including engine line R&D. Because these R&D expenditures are strictly for

meeting a PM standard, they are fully attributed to PM control.

All these corporate R&D estimates are outlined in Table 6.2-1.
Estimated Engine and Equipment Costs

F We have used the 2002 model year certification data for consistency with the analysis done for the proposal which

was done at a time when the 2002 model year was the most recent year for which complete certification data was

available. Throughout this analysis, we assume the manufacturers that certified engines for 2002 are the manufacturers

that will be certifying engines to the new Tier 4 standards. 

6-9

Table 6.2-1

Estimated Corporate R&D Expenditures by Type of Manufacturer

Totals per Manufacturer over Five Years

($Million)

R&D for

DOC/engine-out

Engines

 R&D for CDPF&NOx

Adsorber Engines

R&D for CDPF-only

Engines 

Horsepower range 0<hp<75 hp$75 25#hp<75

For new standards starting in year: 2008 2011 (175-750hp)

 2012 (75-175hp)

2015 (>750hp)

2013

Manufacturer sells into both highway and

nonroad markets

$0.6 $3.6

Manufacturer sells only into the nonroad

market

$4.2 $25.3

Manufacturer has already done

CDPF&NOx Adsorber R&D

$1.2

Manufacturer has not done CDPF&NOx

Adsorber R&D

$8.3

% Allocated to PM 100% 33% 100%

% Allocated to NOx 67%

Some manufacturers may actually incur more than one of the corporate R&D amounts shown

in Table 6.2-1. For example, we would estimate that a manufacturer with engines in both the 25-

75 hp range and the 175-750 hp range that sells only into the nonroad market would incur $30.7

million ($4.2 + $25.3 + $1.2). Likewise, we would estimate that a manufacturer with engines

only in the 25-75 hp range that sells only into the nonroad market would incur $8.3 million. This

way, we have estimated a unique corporate R&D expenditure for each manufacturer. To do this,

we used certification data for the 2002 model year along with our best understanding of which

manufacturers sell into both the highway and nonroad markets and which sell only into the

nonroad market.F
Final Regulatory Impact Analysis

G Projected sales information is confidential business information. We cannot present this information here nor can

we present details of calculations that use projected sales data since back calculating could shed light on the projected

sales data. 

H Detroit Diesel and VM Motori were treated as part of DaimlerChrysler; IVECO, New Holland, and CNH were

treated as one; Kirloskar and Kukje were treated as partners of Cummins; Mitsubishi Motors Corporation and Mitsubishi

Heavy Industries are treated as one company; Perkins R&D is attributed to Caterpillar; and, Volvo Construction

Equipment and Volvo Penta AB are treated as one company.

I Estimated engine prices are shown in Table 6.2-3. We multiplied these prices by the manufacturer’s projected

sales volume to determine if projected revenues from engine sales will exceed our estimated R&D costs. If not, we have

assumed that the manufacturer would not invest in the R&D and would instead license the R&D from another

manufacturer. While this would result in costs to the licensing manufacturer, it would also result in profits to the licensor;

it would therefore not result in increased costs associated with the new emission standards.

6-10

When certifying engines, manufacturers project the sales of each engine they certify.G Using

the projected sales information, we were able to determine how many engine sales each

manufacturer expects to have in each of the power categories of interest. As a result, not every

manufacturer is expected to incur all the R&D costs shown in Table 6.2-1. For example, some

manufacturers do not certify engines under 75 hp. Such a manufacturer will not incur R&D

costs for CDPF-only engines or for those engines expected to add a DOC or make only engineout changes. Also, some engine manufacturers produce and sell engines to specifications

developed by other manufacturers. Such joint venture manufacturers or wholly owned

manufacturers do not conduct engine-related R&D but simply manufacture an engine designed

and developed by another manufacturer. For such manufacturers, we have assumed no engine

R&D expenditures, given that we believe they will conduct no R&D themselves and will instead

rely on their joint venture partner. This is true unless the parent company has no engine sales in

the power categories covered by the partner company. Under such a situation, we have

accounted for the necessary R&D by attributing it to the parent company. For example, Perkins

is an engine manufacturer wholly owned by Caterpillar so we have attributed no R&D costs to

Perkins. However, Perkins sells engines in power categories that Caterpillar does not. As a

result, we have attributed R&D costs to Caterpillar for conducting R&D that will benefit Perkins

engines. We have identified nine manufacturers to whom we have attributed no R&D because of

a joint partner agreement.H For some of these (such as Perkins), we have attributed R&D costs

to their parent for the engines they will sell, and some are effectively the same company as their

parent (for example, Detroit Diesel and their parent DaimlerChrysler, New Holland and their

parent CNH). In the end, it is not important to our analysis to what manufacturer the R&D is

allocated because we have attempted to estimate the total R&D that will be spent by the entire

industry.

We have also estimated that some manufacturers will choose not to invest in R&D for the

U.S. nonroad market due to low volume sales that cannot justify the expense. We have

identified three such manufacturers to whom we have attributed no R&D due to the cost of that

R&D relative to our best estimate of the revenues they receive from engine sales to which the

new NRT4 standards would apply.I

 This is not to say that we believe these manufacturers will

cease to do business or even choose to leave the market; it only means that, given their low U.S.
Estimated Engine and Equipment Costs

J These eight are: Alaska Diesel Electric; American Jawa; Eastern Tools and Equipment; Escorts, Ltd.; Harvest

Drivemaster USA; International Tractors; Northern Tool and Equipment; Same Deutz-Fahr Group.

6-11

sales volumes, we believe it is unlikely that they will conduct the necessary R&D themselves. 

Instead, they will probably license the technology from another manufacturer, which will serve

to increase their own costs but reduce the net costs incurred by the licensing manufacturer, all

while having no impact on the total costs of the rule. Determining which manufacturers will or

will not invest in R&D is based on projected sales data, so we cannot share the manufacturers’

names. It is important to note that the total projected sales for all three engine manufacturers

was 77 engines in the 2002 model year.

Lastly, some certifying manufacturers do not appear to actually make engines. Instead, they

purchase engines from another engine manufacturer and then certify them as their own. We

have identified eight such certifying manufacturers and have attributed no R&D to these eight.J

Excluding the manufacturers we have identified as being in a joint partner arrangement or as

unlikely to invest in R&D, there remain 20 manufacturers expected to invest in CDPF&NOx

Adsorber R&D, 27 manufacturers expected to invest in CDPF-only R&D, and 28 manufacturers

expected to invest in DOC/engine-out R&D. The total estimated corporate R&D expenditures

are shown in Table 6.2-2.

Table 6.2-2

Estimated Industry-wide Corporate R&D Expenditures for the NRT4 Standardsa

DOC/engine-out

R&Db

CDPF+NOx

Adsorber R&Db, c

CDPF-only R&Db Corporate R&D

Totalb

Expenditures during Years 2004-2007 2006-2014 2008-2012 2004-2014

Horsepower 0<hp<75 $75 hp 25#hp<75 all hp

Total Industry-wide

Corporate R&D

Expenditures

$37.2 $121.8 $46.7 $205.7

Corporate R&D for PM $37.2 $40.2 $46.7 $124.1

Corporate R&D for NOx — $81.6 — $81.6

a

 Dollar values are in millions of 2002 dollars.

b

 Corporate R&D attributable to US sales resulting from this final rule (see discussion in text). Engine line R&D is

presented in Table 6.2-3. Total R&D – corporate R&D plus engine line R&D – is presented in Table 6.2-4. c

 This includes corporate R&D for >750 hp engines.

To this corporate R&D estimate, we have added an engine line R&D element. This engine

line R&D will cover costs for a manufacturer to tailor the knowledge gained through corporate

R&D to each particular engine line in their mix. Based on confidential comments submitted

during the public comment period and our analysis of them, we have estimated these costs to be
Final Regulatory Impact Analysis

6-12

$1 million for each engine line in the 25-75 hp range (to meet the 2013 standards), $3 million for

each engine line from 75-750 hp, and $6 million for those engine lines over 750 hp. We have

assumed no engine line R&D for <75 hp engines to meet the 2008 standards because we do not

believe that the relatively simple addition of a DOC or the modifications impacting engine-out

emissions will require such a R&D effort. We have determined the number of engine lines by

considering that, typically, the same basic diesel engine design can be increased or decreased in

size by simply adding or subtracting cylinders. As a result, a four-, six-, or eight-cylinder engine

may be produced from the same basic engine design. While these engines have different total

displacement, they each have the same displacement per cylinder. Using the PSR database, we

grouped each engine manufacturer’s engines into distinct engine lines using increments of 0.5

liters per cylinder. This way, engines having similar displacements per cylinder are grouped

together and are considered to be one engine line. Table 6.2-3 presents the number of engine

lines for which we have estimated this engine line R&D expenditure along with the total

industry-wide engine line R&D we have estimated.

Table 6.2-3

Estimated Industry-wide Engine Line R&D Expenditures for the NRT4 Standardsa

Expenditures during Years 2008-2012 2006-2010 2007-2011 2010-2014 2006-2014

Horsepower 25<hp<75 175-750 hp 75#hp<175 >750 hp All

Engine Lines 21 52b 28 3 104

Engine Line R&D per Line $1.0 $3.0 $3.0 $6.0 – 

Engine Line R&D Totalc $8.8 $65.7 $35.4 $7.6 $117.5

Engine Line R&D for PMc $8.8 $21.7 $11.7 $7.6 $49.8

Engine Line R&D for NOxc – $44.0 $23.7 – $67.7

a

 Dollar values are in millions of 2002 dollars. 

b

 This excludes 16 engine lines – those engine lines considered in the HD2007 rule. We have not included these

highway engine lines since manufacturers will be conducting engine line R&D to meet the HD2007 standards. c

 Dollar amounts shown here are those amounts attributable to US sales, as discussed in the main text.

We have estimated that all engine R&D expenditures—corporate R&D plus engine line

R&D—occur over a five year span preceding the first year any emission-control device is

introduced into the market. The one exception to this being corporate R&D done for the 2008

standards which would be incurred over a four year span beginning today. Those expenditures

are then recovered by the engine manufacturer during any phase-in years and then over a fiveyear span following full introduction of the technology. Since PM standards take effect without

a multi-year phase-in, most PM costs are recovered for five years following the first year of

implementation. Most NOx costs are recovered over the two- or three-year phase-in and then

five years following complete implementation, or a total of seven or eight years. We include a

cost of seven percent when amortizing engine R&D expenditures.

Our R&D estimates represent the cost to develop advanced aftertreatment-based emission-
Estimated Engine and Equipment Costs

K We considered using revenue and income data for nonroad engine/equipment companies that might show what

percent of those business metrics were US based versus non-US based. However, we were not able to find information

on all of the more than 50 nonroad diesel engine companies and the more than 600 nonroad diesel equipment companies. 

In fact, we were able to locate information on only 10 nonroad engine/equipment companies because many companies

are not publicly traded in the US or do not present revenue and income data on a geographic basis. The results of our

research are contained in a memorandum to the docket (see Charmley, April 7, 2004, EDOCKET OAR-2003-0012-

0927). The limited data set generated by that research shows geographic distribution of revenue and income that is not

inconsistent with our 42 percent distribution.

L According to the Worldbank, in 2000, the European countries of Austria, Belgium, Denmark, Finland, France,

Germany, Greece, Ireland, Italy, Luxembourg, The Netherlands, Portugal, Spain, Sweden, and the United Kingdom had a

combined GDP of $7.8 trillion; Australia’s GDP was $0.4 trillion; Canada’s GDP was $0.7 trillion; Japan’s GDP was

$4.7 trillion; and the U.S. GDP was $9.9 trillion; for a total GDP of $23.5 trillion (www.worldbank.org).

M This is already factored into the costs shown in Tables 6.2-2 through 6.2-4, but is not factored into the costs shown

in Table 6.2-1.

6-13

control systems enabled by 15 ppm sulfur fuel. We are projecting that manufacturers will need

to do this R&D to sell engines in Europe, Japan, Australia, and Canada because we expect that 

similar emission standards will be required in a similar time frame for each of these regions or

countries.8

 Therefore, we have attempted to attribute the costs of R&D to the total engine sales

for these regions. Since we do not have sales data for every manufacturer showing what percent

of their engines are sold in the United States relative to these other regions, we have used Gross

Domestic Product (GDP) as a surrogate for sales.K,9 As a result, we have attributed only a

portion of the R&D expenditures to engine sales within the United States. The United States’

GDP is 42 percent of the total GDP from all the countries that are expected to adopt Tier 4 or

similar emission standards for nonroad diesel engines.L Therefore, we have attributed 42 percent

of the total R&D costs to U.S. sales.M Note that all engine R&D costs for <25 hp engines have

been attributed to U.S. sales since other countries are not expected to have similar standards on

these engines (though, as noted in the preamble for this final rule, the European Commission

may revisit this issue in their 2007 Nonroad standards review).

The total estimated R&D attributable to US sales associated with the NRT4 engine

standards—corporate R&D presented in Table 6.2-2 and engine line R&D presented in Table

6.2-3—is shown in Table 6.2-4.
Final Regulatory Impact Analysis

6-14

Table 6.2-4

Estimated Total R&D Expenditures for the NRT4 Standardsa

DOC/engine-out

R&Db

CDPF+NOx

Adsorber R&Db, c

CDPF-only R&Db Total R&Db

Expenditures during Years 2004-2007 2006-2014 2008-2012 2004-2014

Horsepower 0<hp<75 $75 hp 25#hp<75 all hp

Total Industry-wide R&D

Expendituresc

$37.2 $230.5 $55.5 $323.2

Total R&D for PMc $37.2 $81.2 $55.5 $173.9

Total R&D for NOxc — $149.3 — $149.3

a

 Dollar values are in millions of 2002 dollars.

b

 Total R&D – corporate R&D plus engine line R&D.

c

 Dollar amounts shown here are those amounts attributable to US sales, as discussed in the main text.

We have weighted R&D recovery according to estimated revenues for engines sold in each

power category. For example, CDPF&NOx Adsorber R&D benefits all engines over 75 hp. 

However, we have assumed that engines in the 175-750 hp range must introduce the new

technologies in 2011, while engines from 75 to 175 hp will introduce it a year later. As a result,

R&D costs are assumed to be recovered on engines in the 175-750 hp range between 2011 and

2015/2018 and on 75 to 175 hp engines between 2012 and 2016/2018. R&D costs for >750 hp

engines are assumed to be recovered between 2015-2019. Delaying implementation dates for

these engines, or a subset of these engines, would not impact our estimated R&D expenditures or

their recovery but would, instead, only affect the timing of their recovery. To weight the costs

between engines in these categories, we have used revenue-weighting rather than a more

simplistic sales-weighting under the belief that manufacturers will attempt to recover more costs

where more revenues occur. Revenue-weighting is simply an estimated price multiplied by a

unit sales figure. The revenue weightings we have used are shown in Table 6.2-5.

Using this methodology, we have estimated the total R&D expenditures associated with the

new emission standards to vary from $9 to $57 million per year, with an average of $27 million

per year and a total of $323 million. Total R&D recovery on U.S. sales is estimated at $452

million. All estimated R&D costs are shown in Table 6.2-6. Note that the engine sales numbers

shown in Table 6.2-6 are discussed in greater detail in Chapter 8, where we present aggregate

costs to society.
Estimated Engine and Equipment Costs

6-15

Table 6.2-5

Revenue Weightings Used to Allocate R&D Cost Recovery

Horsepower 2000

Sales

Estimated

Engine

Price

Revenue-Weighted Recovery of R&D in the Indicated Years

PM 2008-2012 2011-2015 2012-2016 2013-2017 2015-2019

NOx N/A 2011-2018 2012-2018 N/A N/A

0<hp<25 119,159 $1,500 22%

25#hp<50 132,981 $2,900 46% 59%

50#hp<75 93,914 $2,900 32% 41%

75#hp<100 68,665 $5,200 12%

100#hp<175 112,340 $5,200 19%

175#hp<300 61,851 $10,300 30% 21%

300#hp<600 34,095 $31,000 49% 34%

600#hp#750 2,752 $80,500 10% 7%

hp>750 2,785 $80,500 11% 7% 100%

Total 628,542 100% 100% 100% 100% 100%
Estimated R&D Costs Incurred (Non-Annualized) and Recovered (Annualized) -- expressed in $2002

Millions of dollars, except engine sales and per engine costs

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2

Estimated US Sales 131,507 135,623 139,739 143,855 147,971 152,087 156,203 160,319 164,435 168,551 172,667 176,783 180,899 185,015 189,131 193,247 197,3

PM Costs Incurred $0.0 $2.0 $2.0 $2.0 $2.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $2.2 $2.2 $2.2 $2.2 $2.2 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

Per Engine Cost $0 $0 $0 $0 $0 $15 $14 $14 $13 $13 $0 $0 $0 $0 $0 $0 Estimated US Sales 143,496 147,001 150,506 154,011 157,516 161,021 164,526 168,031 171,536 175,041 178,546 182,051 185,556 189,061 192,566 196,071 199,5

PM Costs Incurred $0.0 $4.3 $4.3 $4.3 $4.3 $6.5 $6.5 $6.5 $6.5 $6.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $4.6 $4.6 $4.6 $4.6 $4.6 $9.1 $9.1 $9.1 $9.1 $9.1 $0.0 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

Per Engine Cost $0 $0 $0 $0 $0 $29 $28 $27 $27 $26 $51 $50 $49 $48 $47 $0 

Estimated US Sales 100,051 102,097 104,142 106,188 108,234 110,279 112,325 114,371 116,416 118,462 120,507 122,553 124,599 126,644 128,690 130,736 132,7

PM Costs Incurred $0.0 $3.0 $3.0 $3.0 $3.0 $4.6 $4.6 $4.6 $4.6 $4.6 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $3.3 $3.3 $3.3 $3.3 $3.3 $6.5 $6.5 $6.5 $6.5 $6.5 $0.0 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

Per Engine Cost $0 $0 $0 $0 $0 $29 $29 $28 $28 $27 $54 $53 $52 $51 $50 $0 

Estimated US Sales 73,162 74,662 76,161 77,660 79,159 80,659 82,158 83,657 85,157 86,656 88,155 89,654 91,154 92,653 94,152 95,652 97,1

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $1.5 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $1.6 $1.6 $3.1 $3.1 $3.1 $1.6 $1.6 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.2 $2.2 $2.2 $2.2 $2.2 $0.0 $0.0 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.2 $2.2 $4.4 $4.4 $4.4 $2.2 $2.2 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $0 $50 $49 $73 $72 $70 $23 $23 

Estimated US Sales 119,303 121,625 123,946 126,267 128,588 130,909 133,230 135,551 137,872 140,193 142,514 144,836 147,157 149,478 151,799 154,120 156,4

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.5 $2.5 $2.5 $2.5 $2.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.5 $2.5 $5.1 $5.1 $5.1 $2.5 $2.5 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $3.5 $3.5 $3.5 $3.5 $3.5 $0.0 $0.0 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $3.6 $3.6 $7.1 $7.1 $7.1 $3.6 $3.6 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $0 $51 $50 $74 $72 $71 $24 $23 

Estimated US Sales 66,093 67,507 68,921 70,335 71,749 73,163 74,577 75,991 77,405 78,819 80,233 81,647 83,061 84,475 85,889 87,303 88,7

PM Costs Incurred $0.0 $0.0 $0.0 $3.3 $3.3 $3.3 $3.3 $3.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $3.6 $3.6 $3.6 $7.2 $7.2 $3.6 $3.6 $3.6 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $4.7 $4.7 $4.7 $4.7 $4.7 $0.0 $0.0 $0.0 $NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $5.1 $5.1 $5.1 $10.1 $10.1 $5.1 $5.1 $5.1 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $126 $124 $121 $181 $178 $60 $59 $58 Estimated US Sales 35,403 35,839 36,275 36,711 37,147 37,583 38,019 38,455 38,891 39,327 39,763 40,199 40,635 41,071 41,507 41,943 42,3

PM Costs Incurred $0.0 $0.0 $0.0 $5.5 $5.5 $5.5 $5.5 $5.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $6.0 $6.0 $6.0 $11.9 $11.9 $6.0 $6.0 $6.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $7.7 $7.7 $7.7 $7.7 $7.7 $0.0 $0.0 $0.0 $NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $8.4 $8.4 $8.4 $16.7 $16.7 $8.4 $8.4 $8.4 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $414 $410 $405 $609 $602 $204 $202 $200 Estimated US Sales 2,902 2,952 3,002 3,052 3,102 3,152 3,202 3,252 3,302 3,352 3,402 3,452 3,502 3,552 3,602 3,652 3,7

PM Costs Incurred $0.0 $0.0 $0.0 $1.2 $1.2 $1.2 $1.2 $1.2 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $1.3 $1.3 $1.3 $2.5 $2.5 $1.3 $1.3 $1.3 $0.0 $0.0 $0.0 $0.0 $0.0 $PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $1.6 $1.6 $1.6 $1.6 $1.6 $0.0 $0.0 $0.0 $NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $1.8 $1.8 $1.8 $3.5 $3.5 $1.8 $1.8 $1.8 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $1,023 $1,007 $993 $1,487 $1,465 $494 $487 $481 Estimated US Sales 2,938 2,989 3,040 3,091 3,142 3,193 3,244 3,295 3,346 3,397 3,448 3,499 3,550 3,601 3,652 3,703 3,7

PM Costs Incurred $0.0 $0.0 $0.0 $0.7 $0.7 $0.7 $0.7 $2.2 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.9 $0.9 $0.9 $0.9 $3.1 $2.1 $2.1 $2.1 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $

Per Engine Cost $0 $0 $0 $0 $0 $0 $0 $0 $278 $274 $270 $266 $861 $591 $582 $574 $

PM Costs Incurred $0.0 $9.3 $9.3 $20.0 $24.0 $25.8 $25.8 $27.3 $16.7 $12.6 $1.5 $1.5 $0.0 $0.0 $0.0 $0.0 $

NOx Costs Incurred $0.0 $0.0 $0.0 $10.8 $14.9 $14.9 $29.9 $29.9 $19.0 $14.9 $14.9 $0.0 $0.0 $0.0 $0.0 $0.0 $Total Costs Incurred $0.0 $9.3 $9.3 $30.8 $38.9 $40.8 $55.7 $57.2 $35.7 $27.6 $16.5 $1.5 $0.0 $0.0 $0.0 $0.0 $

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $10.1 $10.1 $10.1 $25.0 $30.7 $36.2 $36.2 $38.3 $23.4 $17.7 $2.1 $

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $15.2 $20.9 $20.9 $41.9 $41.9 $26.7 $20.9 $20.9 $

Total Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $10.1 $10.1 $10.1 $40.2 $51.6 $57.2 $78.1 $80.2 $50.1 $38.7 $23.1 $

All hp 600<=hp<=750 >750hp 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600

Table 6.2-6
Estimated Engine and Equipment Costs

6-17

6.2.1.2 Engine-Related Tooling Costs

Once engines are ready for production, new tooling will be required to accommodate the

assembly of the new engines. In the HD2007 rule, we estimated approximately $1.6 million per

engine line for tooling costs associated with CDPF/NOx adsorber systems. For the Tier 4

standards, we have estimated that nonroad-only manufacturers will incur the same amount –

$1.65 million expressed in 2002 dollars – for each engine line that requires a CDPF/NOx

adsorber system. These costs are assigned equally to NOx control and PM control. We have

estimated the same tooling costs as in the HD2007 rule because we expect Tier 4 engines to use

the same technologies (i.e., a CDPF and a NOx adsorber). For those systems requiring only a

CDPF, we have estimated one-half that amount, or $825,000 per engine line. For those systems

requiring only a DOC or some engine-out modifications, we have estimated one-half the CDPFonly amount, or $412,500 per engine line. Tooling costs for CDPF-only and for DOC engines

are attributed solely to PM control.

For those manufacturers selling into both the highway and nonroad markets, we have started

with the same $1.65 million baseline discussed above. For those engines requiring a CPDF/NOx

adsorber system (i.e., those over 75 hp) we have adjusted that $1.65 million baseline by 50

percent. We believe this 50 percent adjustment is reasonable since many nonroad engines over

75 hp are produced on the same engine line with their highway counterparts. For such lines,

tooling costs will be negligible. For engine lines without a highway counterpart, the $1.65

million tooling cost applies. For highway manufacturers selling into both the highway and the

nonroad markets, we have estimated a 50/50 split of nonroad engine product lines (i.e., 50

percent with highway counterparts and 50 percent without) and therefore applied a 50 percent

factor to the $1.65 million baseline. These tooling costs are split evenly between NOx control

and PM control. For those engine lines requiring only a CDPF (i.e., those between 25 and 75

hp), we have estimated the same tooling cost as used for nonroad-only manufacturers, or

$825,000. Similarly, the tooling costs for DOC and/or engine-out engine lines has been

estimated to be $412,500. We have used the same tooling costs as the nonroad-only

manufacturers for engines under 75 hp because these engines tend not to have a highway

counterpart. Tooling costs for CDPF-only and for DOC engines are attributed solely to PM

control.

We project that engines between 25 and 50 hp will apply EGR systems to meet the new NOx

standards for 2013. For these engines, we have included an additional tooling cost of $41,300

per engine line, consistent with the EGR-related tooling cost estimated for 50 to 100 hp engines

in our Tier 2/Tier 3 rulemaking which specified the same NOx standards. This tooling cost is

applied equally to all engine lines in that power range, regardless of the markets into which the

manufacturer sells. We have applied this tooling cost equally because engines in this power

range do not tend to have highway counterparts. We expect EGR systems to be added to engines

between 25 and 50 hp to meet the new NOx standard, so tooling costs for EGR systems are

attributed solely to NOx control.
Final Regulatory Impact Analysis

6-18

We have also estimated some tooling costs for >750 horsepower engines to meet the 2011

standards. We have estimated this amount at ten times the amount for 25 to 50 horsepower

engines, or $413,000 per engine line. This cost was not in the proposal since NOx adsorbers

were being projected for all >750 horsepower engines. We have applied this tooling to all

engine lines >750 horsepower, regardless of what markets into which a manufacturer sells, since

such engines clearly have no highway counterpart. We have attributed this cost to NOx control.

Tooling costs per engine line and type of manufacturer are summarized in Table 6.2-7.

Table 6.2-7

Estimated Tooling Expenditures per Engine Line by Type of Manufacturera

DOC/engineout EnginesCDPF-only

Engines

CDPF and

NOx

Adsorber

Engines

EGR Enginesb EGR Engines

Horsepower range 0<hp<75 25#hp<75 75#hp<750 >750hp 25#hp<50

For new standards starting in 2008 2013 2011/2012 2011 2013

Manufacturer sells into both

highway and nonroad markets

$412,500 $825,000 $825,000 $413,000 $41,300

Manufacturer sells only into

the nonroad market

$412,500 $825,000 $1,650,000 $413,000 $41,300

% Allocated to PM 100% 100% 50% 0% 0%

% Allocated to NOx 0% 0% 50% 100% 100%

a

 Dollar values are in millions of 2002 dollars.

b

 To remain conservative in our cost estimate, we have assumed that all engines >750hp add cooled EGR in 2011. We

would expect manufacturers to use a less costly means of control if it allows them to meet the new standard (see

section 4.1.2 of this RIA for more information regarding our estimates of EGR use).

As noted, we have applied tooling costs by engine line assuming that engines in the same

line are produced on the same production line. Typically, the same basic diesel engine design

can be increased or decreased in size by simply adding or subtracting cylinders. As a result, a

four-, six-, or eight-cylinder engine may be produced from the same basic engine design. While

these engines have different total displacement, they each have the same displacement per

cylinder. Using the PSR database, we grouped each engine manufacturer’s engines into distinct

engine lines using increments of 0.5 liters per cylinder. This way, engines having similar

displacements per cylinder are grouped together and are considered to be built on the same

production line. Note that a tooling expenditure for a single engine line may cover engines over

several power categories. To allocate the tooling expenditure for a given production line to a

specific power range, we have used sales-weighting within that engine line.

We have applied the above tooling costs to all manufacturers that appear to actually make

engines. We have not eliminated joint venture manufacturers because these manufacturers still
Estimated Engine and Equipment Costs

6-19

need to invest in tooling to make the engines, even if they do not conduct any R&D. Doing this,

we determined there to be 62 manufacturers expected to invest in tooling for a total of 133

engine lines. Of these, 19 manufacturers sell into both the highway and nonroad markets and

sell a total of 56 engine lines, while 43 manufacturers sell only into the nonroad market and sell

a total of 77 engine lines. For the same reasons as explained for R&D costs, we have attributed a

portion of the tooling costs to U.S. sales and a portion to sales in other countries expected to

have similar levels of emission control; tooling costs for <25 hp engines are attributed only to

US sales since other countries are not expected to have similar standards on <25 hp engines. All

tooling costs are assumed to be incurred one year before the standard they support and are then

recovered over a five-year period following introduction of the new standard. We include a cost

of seven percent when amortizing engine tooling costs.

Using this methodology, we estimate the total tooling expenditures attributable to this final

rule at $74 million. Total tooling recovery on U.S. sales is estimated at $91 million. All

estimated tooling costs are shown in Table 6.2-8.
Final Regulatory Impact Analysis

6-20

Table 6.2-8

Estimated Tooling Costs Incurred (Non-Annualized) and Recovered (Annualized) -- expressed in $2002

Millions of dollars, except engine sales and per engine costs

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total

Estimated US Sales 147,971 152,087 156,203 160,319 164,435 168,551 172,667 176,783 180,899 185,015 189,131 193,247 197,363 

PM Costs Incurred $5.2 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $5.2

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

PM Costs Recovered $0.0 $1.3 $1.3 $1.3 $1.3 $1.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $6.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Per Engine Cost $0 $8 $8 $8 $8 $8 $0 $0 $0 $0 $0 $0 $0

Estimated US Sales 157,516 161,021 164,526 168,031 171,536 175,041 178,546 182,051 185,556 189,061 192,566 196,071 199,576 

PM Costs Incurred $5.9 $0.0 $0.0 $0.0 $0.0 $4.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $10.1

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.5

PM Costs Recovered $0.0 $1.4 $1.4 $1.4 $1.4 $1.4 $1.0 $1.0 $1.0 $1.0 $1.0 $0.0 $0.0 $12.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0 $0.0 $0.6

Per Engine Cost $0 $9 $9 $9 $8 $8 $7 $6 $6 $6 $6 $0 $0

Estimated US Sales 108,234 110,279 112,325 114,371 116,416 118,462 120,507 122,553 124,599 126,644 128,690 130,736 132,781 

PM Costs Incurred $4.1 $0.0 $0.0 $0.0 $0.0 $3.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $7.2

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

PM Costs Recovered $0.0 $1.0 $1.0 $1.0 $1.0 $1.0 $0.7 $0.7 $0.7 $0.7 $0.7 $0.0 $0.0 $8.7

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Per Engine Cost $0 $9 $9 $9 $9 $9 $6 $6 $6 $6 $6 $0 $0

Estimated US Sales 79,159 80,659 82,158 83,657 85,157 86,656 88,155 89,654 91,154 92,653 94,152 95,652 97,151 

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.8 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.8

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.8 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.8

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.7 $0.7 $0.7 $0.7 $0.7 $0.0 $0.0 $0.0 $3.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.7 $0.7 $0.7 $0.7 $0.7 $0.0 $0.0 $0.0 $3.4

Per Engine Cost $0 $0 $0 $0 $0 $16 $15 $15 $15 $15 $0 $0 $0

Estimated US Sales 128,588 130,909 133,230 135,551 137,872 140,193 142,514 144,836 147,157 149,478 151,799 154,120 156,441 

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $4.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $4.5

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $4.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $4.5

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $1.1 $1.1 $1.1 $1.1 $1.1 $0.0 $0.0 $0.0 $5.5

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $1.1 $1.1 $1.1 $1.1 $1.1 $0.0 $0.0 $0.0 $5.5

Per Engine Cost $0 $0 $0 $0 $0 $16 $16 $15 $15 $15 $0 $0 $0

Estimated US Sales 71,749 73,163 74,577 75,991 77,405 78,819 80,233 81,647 83,061 84,475 85,889 87,303 88,717 

PM Costs Incurred $0.0 $0.0 $0.0 $11.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $11.0

NOx Costs Incurred $0.0 $0.0 $0.0 $11.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $11.0

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $2.7 $2.7 $2.7 $2.7 $2.7 $0.0 $0.0 $0.0 $0.0 $13.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $2.7 $2.7 $2.7 $2.7 $2.7 $0.0 $0.0 $0.0 $0.0 $13.4

Per Engine Cost $0 $0 $0 $0 $69 $68 $67 $66 $65 $0 $0 $0 $0

Estimated US Sales 37,147 37,583 38,019 38,455 38,891 39,327 39,763 40,199 40,635 41,071 41,507 41,943 42,379 

PM Costs Incurred $0.0 $0.0 $0.0 $6.1 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $6.1

NOx Costs Incurred $0.0 $0.0 $0.0 $6.1 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $6.1

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $1.5 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $0.0 $0.0 $7.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $1.5 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $0.0 $0.0 $7.4

Per Engine Cost $0 $0 $0 $0 $76 $75 $74 $74 $73 $0 $0 $0 $0

Estimated US Sales 3,102 3,152 3,202 3,252 3,302 3,352 3,402 3,452 3,502 3,552 3,602 3,652 3,702 

PM Costs Incurred $0.0 $0.0 $0.0 $0.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.5

NOx Costs Incurred $0.0 $0.0 $0.0 $0.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.5

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0 $0.0 $0.0 $0.0 $0.6

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0 $0.0 $0.0 $0.0 $0.6

Per Engine Cost $0 $0 $0 $0 $72 $71 $70 $69 $68 $0 $0 $0 $0

Estimated US Sales 3,142 3,193 3,244 3,295 3,346 3,397 3,448 3,499 3,550 3,601 3,652 3,703 3,754 

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $1.0 $0.0 $0.0 $0.0 $0.0 $0.0 $1.0

NOx Costs Incurred $0.0 $0.0 $0.0 $0.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.5

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.3 $0.3 $0.3 $0.3 $0.3 $1.3

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0 $0.0 $0.0 $0.0 $0.6

Per Engine Cost $0 $0 $0 $0 $38 $37 $37 $36 $107 $71 $70 $69 $68

PM Costs Incurred $15.2 $0.0 $0.0 $17.6 $7.3 $7.3 $0.0 $1.0 $0.0 $0.0 $0.0 $0.0 $0.0 $48.4

NOx Costs Incurred $0.0 $0.0 $0.0 $18.1 $7.3 $0.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $25.9

Total Costs Incurred $15.2 $0.0 $0.0 $35.6 $14.6 $7.8 $0.0 $1.0 $0.0 $0.0 $0.0 $0.0 $0.0 $74.3

PM Costs Recovered $0.0 $3.7 $3.7 $3.7 $8.0 $9.8 $7.8 $7.8 $8.1 $3.8 $2.0 $0.3 $0.3 $59.1

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $4.4 $6.2 $6.3 $6.3 $6.3 $1.9 $0.1 $0.0 $0.0 $31.6

Total Costs Recovered $0.0 $3.7 $3.7 $3.7 $12.4 $16.0 $14.2 $14.2 $14.4 $5.7 $2.2 $0.3 $0.3 $90.6

0<hp<25 50<=hp<75 100<=hp<175 25<=hp<50 75<=hp<100 All hp 175<=hp<300 300<=hp<600 600<=hp<=750 >750hp
Estimated Engine and Equipment Costs

N Note that the transport refrigeration unit (TRU) test cycle is an optional duty cycle for steady-state

certification testing specifically tailored to the operation of TRU engines. Likewise, the ramped modal cycles are

available test cycles that can be used to replace existing steady-state test requirements for nonroad constant-speed

engines, generally. Manufacturers of these engines who opt to use one of these test cycles would incur no new costs

above those estimated here and may incur less cost. 

6-21

6.2.1.3 Engine Certification Costs

Manufacturers will incur more than the normal level of certification costs during the first few

years of implementation because engines will need to be certified to the new emission standards

using new test procedures. Consistent with our recent standard setting regulations, we have

estimated engine certification costs at $60,000 per new engine certification to cover testing and

administrative costs.10 The $60,000 certification cost per engine family was used for engines in

the 25 to 75 hp range certifying to the 2008 standards. For 25 to 75 hp engines certifying to the

2013 standards, and for 75-750 hp engines certifying to the appropriate standards, we have added

costs to cover the new test procedures for nonroad diesel engines (i.e., the transient test and the

NTE);N these costs were estimated at $31,500 per engine family. For engines >750 hp, the

certification costs used were $87,000 per family since these engines will not be certifying over

the new transient test procedure. For engines <25 hp, we have assumed (for cost purposes) that

all engines will certify to the transient test and the NTE in 2008. We believe manufacturers may

choose to do this rather than certifying all engines again in 2013 when the transient test and NTE

requirements actually begin for those engines (and the rules explicitly provide the option of

certifying these engines starting in 2008 using these tests). This assumption results in higher

certification costs in 2008 than if these engines certified only to the steady-state standard. 

However, we believe manufacturers may choose to do this because it would avoid the need to

recertify all <25 hp engines again in 2013. Certification costs (for engines in all hp ranges)

apply equally to all engine families for all manufacturers regardless of the markets into which

the manufacturer sells.

To determine the number of engine families to be certified, we used our certification

database for the 2002 model year. That database provides the number of engine families and the

associated power rating of each. We grouped those power ratings into the nine ranges shown in

Table 6.2-9. We have chosen these nine power categories because: (1) phasing in standards and

having different levels of baseline and complying emission levels force such breakouts; and, (2)

greater stratification (i.e., breaking up the 75 to 175 hp range and the 175 to 750 hp range)

provides a better picture of cost recovery because it more accurately matches the number of

engine families (certification costs) with the level of engine sales (cost recovery). Some engine

families will undergo more than one certification process due to the structure of new emission

standards in the final rule. Table 6.2-9 shows the number of engine families in each power range

and the year for they are subject to new emission standards, along with the total certification

expenditures for those standards.

The cost expenditures shown in Table 6.2-9 are estimated to occur one year before the year

shown in the table. The years shown in the table coincide with the years for which the new

standards begin, thereby requiring engine certification. Half the 175 to 750 hp engine families
Final Regulatory Impact Analysis

6-22

certified for 2011 must again be certified in 2014 when the NOx phase-in becomes 100 percent. 

For 25 to 50 hp engines in 2013, half the certification costs are attributed to PM and half are

attributed to NOx, due to the new PM and NOx standards for those engines in that year; all the

certification costs for 50 to 75 hp engine families are attributed to PM because only a new PM

standard applies in that year for those engines.

Note that these certification costs may overestimate actual costs because they assume all

engines are certified as a result of the new emission standards in this final rule. However, some

engines would have been scheduled for new certification independent of this final rule due to

design changes or power increases among other possible reasons. For such engines, the

incremental certification cost would be those costs associated with the new test procedures and

would not include certification costs associated with the existing test procedure. However, to

remain conservative, here we have applied the full certification costs to all engine families. 

Given the magnitude of certification costs relative to other costs in this final rule, this has little

impact on the costs per ton of emissions reduced or the cost/benefit results.

Table 6.2-9

Number of Engine Families, Estimated 

Certification Costs, and Allocation of Certification Costsa

Power range

Model Year for New Emission Standards

2008 2011 2012 2013 2014 2015

0<hp<25 102

25#hp<50 132 132

50#hp<75 88 88

75#hp<100 55 28

100#hp<175 73 37

175#hp<300 102 51

300#hp<600 64 32

600#hp#750 9 5

hp>750a 40 40

Total families 322 215 128 132 88 88 64 40

Total Cert Costs $22.5 $19.5 $11.7 $12.1 $8.1 $8.0 $5.9 $3.5

% Allocated to PM 100% 50% 50% 50% 100% 0% 0% 50%

% Allocated to NOx 0% 50% 50% 50% 0% 100% 100% 50%

a

 Dollar values are in millions of 2002 dollars.
Estimated Engine and Equipment Costs

6-23

To estimate recovery of certification expenditures, we have attributed the expenditures to

engines sold in the specific power range and spread the recovery of costs over U.S. sales within

that category. Expenditures are incurred one year before the emission standard for which the

certification is conducted, and are then recovered over a five-year period following the

certification. We include a cost of seven percent when amortizing engine certification costs. We

have spread these certification costs only over the engines sold in the United States because U.S.

EPA certification is not presumed to fulfill the certification requirements of other countries. 

Total certification expenditures are estimated at $91 million. Recovery of certification costs is

estimated at $111 million. All estimated certification expenditures and the recovery of those

expenditures are shown in Table 6.2-10.
Final Regulatory Impact Analysis

6-24

Table 6.2-10

Estimated Certification Costs Incurred (Non-Annualized) and Recovered (Annualized) -- expressed in $2002

Millions of dollars, except engine sales and per engine costs

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total

Estimated US Sales 147,971 152,087 156,203 160,319 164,435 168,551 172,667 176,783 180,899 185,015 189,131 193,247 197,363 

PM Costs Incurred $9.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $9.3

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

PM Costs Recovered $0.0 $2.3 $2.3 $2.3 $2.3 $2.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $11.4

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Per Engine Cost $0 $15 $15 $14 $14 $14 $0 $0 $0 $0 $0 $0 $0

Estimated US Sales 157,516 161,021 164,526 168,031 171,536 175,041 178,546 182,051 185,556 189,061 192,566 196,071 199,576 

PM Costs Incurred $7.9 $0.0 $0.0 $0.0 $0.0 $6.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $14.0

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $6.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $6.0

PM Costs Recovered $0.0 $1.9 $1.9 $1.9 $1.9 $1.9 $1.5 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $17.0

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $1.5 $1.5 $1.5 $1.5 $1.5 $0.0 $0.0 $7.4

Per Engine Cost $0 $12 $12 $11 $11 $11 $16 $16 $16 $16 $15 $0 $0

Estimated US Sales 108,234 110,279 112,325 114,371 116,416 118,462 120,507 122,553 124,599 126,644 128,690 130,736 132,781 

PM Costs Incurred $5.3 $0.0 $0.0 $0.0 $0.0 $8.1 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $13.3

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

PM Costs Recovered $0.0 $1.3 $1.3 $1.3 $1.3 $1.3 $2.0 $2.0 $2.0 $2.0 $2.0 $0.0 $0.0 $16.3

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Per Engine Cost $0 $12 $11 $11 $11 $11 $16 $16 $16 $16 $15 $0 $0

Estimated US Sales 79,159 80,659 82,158 83,657 85,157 86,656 88,155 89,654 91,154 92,653 94,152 95,652 97,151 

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.5 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.5

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $2.5 $0.0 $2.2 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $4.7

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.6 $0.6 $0.6 $0.6 $0.6 $0.0 $0.0 $0.0 $3.1

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.6 $0.6 $1.2 $1.2 $1.2 $0.5 $0.5 $0.0 $5.8

Per Engine Cost $0 $0 $0 $0 $0 $14 $14 $20 $19 $19 $6 $6 $0

Estimated US Sales 128,588 130,909 133,230 135,551 137,872 140,193 142,514 144,836 147,157 149,478 151,799 154,120 156,441 

PM Costs Incurred $0.0 $0.0 $0.0 $0.0 $3.3 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $3.3

NOx Costs Incurred $0.0 $0.0 $0.0 $0.0 $3.3 $0.0 $3.6 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $7.0

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.8 $0.8 $0.8 $0.8 $0.8 $0.0 $0.0 $0.0 $4.1

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.0 $0.8 $0.8 $1.7 $1.7 $1.7 $0.9 $0.9 $0.0 $8.5

Per Engine Cost $0 $0 $0 $0 $0 $12 $11 $17 $17 $17 $6 $6 $0

Estimated US Sales 71,749 73,163 74,577 75,991 77,405 78,819 80,233 81,647 83,061 84,475 85,889 87,303 88,717 

PM Costs Incurred $0.0 $0.0 $0.0 $4.7 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $4.7

NOx Costs Incurred $0.0 $0.0 $0.0 $4.7 $0.0 $0.0 $5.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $9.7

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $1.1 $1.1 $1.1 $1.1 $1.1 $0.0 $0.0 $0.0 $0.0 $5.7

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $1.1 $1.1 $1.1 $2.4 $2.4 $1.2 $1.2 $1.2 $0.0 $11.8

Per Engine Cost $0 $0 $0 $0 $29 $29 $28 $43 $42 $14 $14 $14 $0

Estimated US Sales 37,147 37,583 38,019 38,455 38,891 39,327 39,763 40,199 40,635 41,071 41,507 41,943 42,379 

PM Costs Incurred $0.0 $0.0 $0.0 $2.9 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $2.9

NOx Costs Incurred $0.0 $0.0 $0.0 $2.9 $0.0 $0.0 $2.8 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $5.7

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.7 $0.7 $0.7 $0.7 $0.7 $0.0 $0.0 $0.0 $0.0 $3.6

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.7 $0.7 $0.7 $1.4 $1.4 $0.7 $0.7 $0.7 $0.0 $6.9

Per Engine Cost $0 $0 $0 $0 $37 $36 $36 $52 $52 $16 $16 $16 $0

Estimated US Sales 3,102 3,152 3,202 3,252 3,302 3,352 3,402 3,452 3,502 3,552 3,602 3,652 3,702 

PM Costs Incurred $0.0 $0.0 $0.0 $0.4 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.4

NOx Costs Incurred $0.0 $0.0 $0.0 $0.4 $0.0 $0.0 $0.2 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.6

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0 $0.0 $0.0 $0.0 $0.5

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.1 $0.1 $0.1 $0.2 $0.2 $0.1 $0.1 $0.1 $0.0 $0.8

Per Engine Cost $0 $0 $0 $0 $61 $60 $59 $74 $73 $15 $15 $15 $0

Estimated US Sales 3,142 3,193 3,244 3,295 3,346 3,397 3,448 3,499 3,550 3,601 3,652 3,703 3,754 

PM Costs Incurred $0.0 $0.0 $0.0 $1.7 $0.0 $0.0 $0.0 $1.7 $0.0 $0.0 $0.0 $0.0 $0.0 $3.5

NOx Costs Incurred $0.0 $0.0 $0.0 $1.7 $0.0 $0.0 $0.0 $1.7 $0.0 $0.0 $0.0 $0.0 $0.0 $3.5

PM Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.4 $0.4 $0.4 $0.4 $0.8 $0.4 $0.4 $0.4 $0.4 $4.2

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $0.4 $0.4 $0.4 $0.4 $0.8 $0.4 $0.4 $0.4 $0.4 $4.2

Per Engine Cost $0 $0 $0 $0 $254 $250 $246 $243 $478 $236 $232 $229 $226

PM Costs Incurred $22.5 $0.0 $0.0 $9.7 $5.9 $14.1 $0.0 $1.7 $0.0 $0.0 $0.0 $0.0 $0.0 $54.0

NOx Costs Incurred $0.0 $0.0 $0.0 $9.7 $5.9 $6.0 $13.9 $1.7 $0.0 $0.0 $0.0 $0.0 $0.0 $37.2

Total Costs Incurred $22.5 $0.0 $0.0 $19.5 $11.7 $20.1 $13.9 $3.5 $0.0 $0.0 $0.0 $0.0 $0.0 $91.2

PM Costs Recovered $0.0 $5.5 $5.5 $5.5 $7.9 $9.3 $7.2 $7.2 $7.7 $5.3 $3.9 $0.4 $0.4 $65.8

NOx Costs Recovered $0.0 $0.0 $0.0 $0.0 $2.4 $3.8 $5.3 $8.7 $9.1 $6.7 $5.3 $3.8 $0.4 $45.4

Total Costs Recovered $0.0 $5.5 $5.5 $5.5 $10.2 $13.1 $12.5 $15.9 $16.7 $12.0 $9.1 $4.2 $0.8 $111.2

All hp 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=750 >750hp 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100
Estimated Engine and Equipment Costs

6-25

6.2.2 Engine Variable Costs

Engine variable costs are those costs for new hardware required to meet the new emission

standards. In this section, we present our estimates of engine variable costs. Because of the

wide variation of engine sizes in the nonroad market, we have chosen an approach that results

not in a specific cost per engine for engines within a given power range, but rather a set of

equations that can be used to determine the variable costs for any engine provided its

displacement and number of cylinders are known. As a result, we do not present here a cost of,

say, $50 per engine for engines in the 25 to 50 power range, but instead present cost equations

that can be used to determine the variable costs for an engine having, for example, a 0.5 liter

engine with two cylinders. We believe this is a more comprehensive approach because it allows

the reader to calculate costs more precisely for whatever engine(s) they are interested in. 

Further, variable costs can vary quite significantly within a given power range unless the range is

kept very small. To state an average variable cost for a range such as 175 to 300 hp is far less

precise than what we present here. Using the equations presented in this section, we have then

estimated the engine variable costs for certain specific pieces of equipment and for the sales

weighted average piece of equipment. These estimates can be found in Section 6.5.

The discussion here considers both near-term and long-term cost estimates. We believe there

are factors that cause variable hardware costs to decrease over time, making it appropriate to

distinguish between near-term and long-term costs. Research in the costs of manufacturing has

consistently shown that as manufacturers gain experience in production, they are able to apply

innovations to simplify machining and assembly operations, use lower cost materials, and reduce

the number or complexity of component parts, all of which allows them to lower the per-unit

cost of production. These effects are often described as the manufacturing learning curve.11

The learning curve is a well documented phenomenon dating back to the 1930s. The general

concept is that unit costs decrease as cumulative production increases. Learning curves are often

characterized in terms of a progress ratio, where each doubling of cumulative production leads to

a reduction in unit cost to a percentage “p” of its former value (referred to as a “p cycle”). 

Organizational learning, which brings about a reduction in total cost, is caused by improvements

in several areas. Areas involving direct labor and material are usually the source of the greatest

savings. Examples include, but are not limited to, a reduction in the number or complexity of

component parts, improved component production, improved assembly speed and processes,

reduced error rates, and improved manufacturing process. These all result in higher overall

production, less scrappage of materials and products, and better overall quality. As each

successive p cycle takes longer to complete, production proficiency generally reaches a

relatively stable plateau, beyond which increased production does not necessarily lead to

markedly decreased costs.

Companies and industry sectors learn differently. In a 1984 publication, Dutton and Thomas

reviewed the progress ratios for 108 manufactured items from 22 separate field studies

representing a variety of products and services.12 The distribution of these progress ratios is

shown in Figure 6.2-1. Except for one company that saw increasing costs as production

continued, every study showed cost savings of at least five percent for every doubling of
Final Regulatory Impact Analysis

6-26

55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 101 103 105 107

Progress Ratio

0

5

10

15

Frequency

From 22 field studies (n = 108).

Distribution of Progress Ratios

Figure 6.2-1

Distribution of Progress Ratios

production volume. The average progress ratio for the whole data set falls between 81 and 82

percent. Other studies (Alchian 1963, Argote and Epple 1990, Benkard 1999) appear to support

the commonly used p value of 80 percent, i.e., each doubling of cumulative production reduces

the former cost level by 20 percent.

The learning curve is not the same in all industries. For example, the effect of the learning

curve seems to be less in the chemical industry and the nuclear power industry where a doubling

of cumulative output is associated with 11 percent decrease in cost (Lieberman 1984,

Zimmerman 1982). The effect of learning is more difficult to decipher in the computer chip

industry (Gruber 1992). 

We believe the learning curve is appropriate to consider in assessing the cost impact of diesel

engine emission controls. The learning curve applies to new technology, new manufacturing

operations, new parts, and new assembly operations. Nonroad diesel engines currently do not

use any form of NOx aftertreatment and have used diesel particulate filters only in limited

application. These are therefore new technologies for nonroad diesel engines and will involve

some new manufacturing operations, new parts, and new assembly operations beyond those

anticipated in response to the HD2007 rule. Since this will be a new product, we believe this is

an appropriate situation for the learning curve concept to apply. Opportunities to reduce unit

labor and material costs and increase productivity (as discussed above) will be great. We believe

a similar opportunity exists for the new control systems that will integrate the function of the
Estimated Engine and Equipment Costs

6-27

engine and emission-control technologies. While all nonroad diesel engines beginning with Tier

3 compliance are expected to have the basic components of this system—advanced engine

control modules (computers), advanced engine air management systems (cooled EGR, and

variable geometry turbocharging), and advanced electronic fuel systems including common rail

systems— they will be applied in some new ways in response to the Tier 4 standards. 

Additionally some new components will be applied for the first time. These new parts and new

assemblies will involve new manufacturing operations. As manufacturers gain experience with

these new systems, comparable learning is expected to occur with respect to unit labor and

material costs. These changes require manufacturers to start new production procedures, which

will improve with experience.

We have applied a p value of 80 percent beginning with the first year of introduction of any

new technology. That is, variable costs were reduced by 20 percent for each doubling of

cumulative production following the year in which the technology was first introduced in a given

power range of engines. This way, learning is applied at the start of 2013 for engines over 175

hp and in 2014 for engines between 75 to 175 hp because of the one-year difference in their first

year of compliance (i.e., the first year in which new technologies are introduced). Because the

timing of the emission standards in this final rule follows that of the HD2007 rule, we have used

the first stage of learning done via that rule as the starting point of learning for nonroad engines. 

In other words, the first learning phase for highway engines serves as the baseline level of

learning for nonroad engines. We have then applied one additional learning step from there. In

the HD2007 rule, we applied a second learning step following the second doubling of production

that occurs at the end of the 2010 model year. We could have chosen that point as our baseline

case for nonroad and then applied a single learning curve effect from there. Instead, we have

chosen to use as our nonroad baseline the first learning step from the highway rule so that, with

our single nonroad learning step, we have costs consistent with those costs estimated for

highway diesel engines. In the long term, after applying the nonroad learning curve, our cost

estimates for CDPFs and NOx adsorbers are the same for similar nonroad and highway diesel

engines. This approach is consistent with the approach taken in our Tier 2 light-duty highway

rule and the HD2007 rule for heavy-duty gasoline engines. There, compliance was being met

through improvements to existing technologies rather than the development of new technologies. 

We argued in those rules that, with existing technologies, there is less opportunity for lowering

production costs. For that reason, we applied only one learning curve effect. The situation is

similar for nonroad engines. Because these will be existing technologies by the time they are

introduced into the market, there would arguably be less opportunity for learning than there will

be for the highway engines where the technologies are first introduced.

Another factor that plays into our near-term and long-term cost estimates is that for warranty

claim rates. In our HD2007 rule, we estimated a warranty claim rate of one percent. Subsequent

to that rule, we learned from industry that repair rates can be as much as two to three times

higher during the initial years of production for a new technology relative to later years.13 For

this analysis, we have applied what we have learned in our warranty estimates by using a three

percent warranty claim rate during the first two years and then one percent warranty claim rate

thereafter. This difference in warranty claim rates, in addition to the learning effects discussed

above, is reflected in the different long-term costs relative to near-term costs.
Final Regulatory Impact Analysis

6-28

6.2.2.1 NOx Adsorber System Costs

The NOx adsorber system anticipated for Tier 4 is the same technology as for highway

applications. For the NOx adsorber to function properly, a systems approach that includes a

reductant metering system and control of engine air-fuel ratio is also necessary. Many of the

new air handling and electronic system technologies developed in order to meet the Tier 2/Tier 3

nonroad diesel engine standards can be applied to accomplish the NOx adsorber control

functions as well. Some additional hardware for exhaust NOx or O2 sensing and for fuel

metering probably will be required. The cost estimates include a DOC for clean-up of

hydrocarbon emissions that occur during NOx adsorber regeneration events.

We have used the same methodology to estimate costs associated with NOx adsorber systems

as was used in our HD2007 rulemaking. The basic components of the NOx adsorber catalyst are

well known and include the following material elements:

• an oxidation catalyst, typically platinum-based;

• an alkaline earth metal to store NOx, typically barium-based;

• a NOx reduction catalyst, typically rhodium-based;

• a substrate upon which the catalyst washcoating is applied; and,

• a can to hold and support the substrate.

Examples of these material costs are summarized in Table 6.2-11 and represent costs to the

engine manufacturers inclusive of supplier markups. The manufacturer costs shown in Table

6.2-11 (as well as Tables 6.2-13 and 6.2-18 for CDPF systems and DOCs, respectively) include

additional markups to account for both manufacturer and dealer overhead and carrying costs. 

The application of overhead and carrying costs are consistent with the approach taken in the

HD2007 rulemaking. In that rule, we used an approach to estimating the markup for catalyzed

emission-control technologies based on input from catalyst manufacturers. Specifically, we were

told that device manufacturers could not mark up the cost of the individual components within

their products because those components consist of basic commodities (for example, precious

metals used in the catalyst could not be arbitrarily marked up because of their commodity status). 

Instead, manufacturing entities could mark up costs only where they add a unique value to the

product. In the case of catalyst systems, we were told that the underlying cost of precious

metals, catalyst substrates, PM filter substrates, and canning materials were well known to both

buyer and seller and no markup or profit recovery for those component costs could be derived by

the catalyst manufacturer. In essence, these are components to which the supplier provides little

value-added engineering. The one component that was unique to each catalyst manufacturer

(i.e., the component where they add a unique value) was the catalyst washcoat support materials. 

This mixture (which is effectively specialized clays) serves to hold the catalytic metals in place

and to control the surface area of the catalytic metals available for emission control. Although

the commodity price for the materials used in the washcoat is almost negligible (i.e., perhaps one

or two dollars), we have estimated a substantial cost for washcoating based on the engineering

value added by the catalyst manufacturer in this step. This is reflected in the costs presented for

NOx adsorber systems, CDPF systems, and DOCs. This portion of the cost estimate – the

washcoating – is where the catalyst manufacturer recovers the fixed cost for research and
Estimated Engine and Equipment Costs

6-29

development as well as realizes a profit. To these manufacturer costs, we have added a four

percent carrying costs to account for the capital cost of the extra inventory, and the incremental

costs of insurance, handling, and storage. A dealer carrying cost in included to cover the cost of

capital tied up in extra inventory. Considering input received from industry, we have adopted

this approach of estimating individually the manufacturer and dealer markups in an effort to

better reflect the value each entity adds at various stages of the supply chain.14 Also included is

our estimate of warranty costs for the NOx adsorber system.
Final Regulatory Impact Analysis

6-30

Table 6.2-11. NOx Adsorber System Costs

Horsepower 9 hp 33 hp 76 hp 150 hp 250 hp 503 hp 660 hp 1000 hp

Engine Displacement (Liter) 0.39 1.50 3.92 4.70 7.64 18.00 20.30 34.50

Material and Component Costs

 Catalyst Volume (Liter) 0.59 2.25 5.88 7.05 11.46 27.00 30.45 51.75

 Substrate $3 $12 $32 $38 $62 $147 $166 $282

 Washcoating and Canning $13 $52 $135 $162 $263 $620 $700 $1,189

 Platinum $16 $62 $163 $195 $318 $748 $844 $1,434

 Rhodium $3 $11 $28 $34 $55 $129 $145 $246

 Alkaline Earth Oxide, Barium $1 $1 $1 $1 $1 $1 $1 $1

 Catalyst Can Housing $9 $9 $9 $9 $13 $18 $18 $18

Direct Labor Costs

 Estimated Labor hours 2 2222222

 Labor Rate ($/hr) $30 $30 $30 $30 $30 $30 $30 $30

 Labor Cost $45 $45 $45 $45 $45 $60 $60 $60

Labor Overhead @ 40% $18 $18 $18 $18 $18 $24 $24 $24

Total Direct Costs to Mfr. $109 $210 $431 $502 $775 $1,747 $1,957 $3,254

Warranty Cost -- Near Term (3% claim rate) $9 $17 $34 $39 $59 $131 $146 $244

Mfr. Carrying Cost -- Near Term $4 $8 $17 $20 $31 $70 $78 $130

Total Cost to Dealer -- Near Term $122 $235 $482 $561 $865 $1,948 $2,182 $3,628

Dealer Carrying Cost -- Near Term $4 $7 $14 $17 $26 $58 $65 $109

DOC for cleanup -- Near Term $105 $132 $192 $211 $286 $459 $497 $734

Baseline Cost to Buyer -- Near Term $231 $375 $688 $789 $1,177 $2,465 $2,745 $4,471

Cost to Buyer w/ Highway learning -- Near Term $206 $326 $589 $674 $999 $2,064 $2,295 $3,724

Warranty Cost -- Long Term (1% claim rate) $3 $6 $11 $13 $20 $44 $49 $81

Mfr. Carrying Cost -- Long Term $4 $8 $17 $20 $31 $70 $78 $130

Total Cost to Dealer -- Long Term $116 $224 $459 $535 $826 $1,861 $2,084 $3,466

Dealer Carrying Cost -- Long Term $3 $7 $14 $16 $25 $56 $63 $104

DOC for cleanup -- Long Term $99 $125 $182 $201 $272 $437 $474 $700

Baseline Cost to Buyer -- Long Term $219 $356 $656 $752 $1,123 $2,354 $2,621 $4,270

Cost to Buyer w/ Highway learning -- Long Term $195 $310 $561 $642 $952 $1,970 $2,191 $3,556

Cost to Buyer w/ Nonroad learning -- Long Term $176 $273 $485 $554 $816 $1,664 $1,848 $2,985

NOx Adsorber Costs ($2002)
Estimated Engine and Equipment Costs

6-31

We have estimated the cost of this system based on information from several reports.15, 16, 17

The individual estimates and assumptions used to estimate the cost for the system are

documented in the following paragraphs.

NOx Adsorber Catalyst Volume

The Engine Manufacturers Association was asked as part of a contractor work assignment to

gather input from their members on likely technology solutions including the NOx adsorber

catalyst.18 The respondents indicated that the catalyst volume for a NOx adsorber catalyst may

range from 1.5 times the engine displacement to as much as 2.5 times the engine displacement

based on current washcoat technology. Based on current lean burn gasoline catalyst designs and

engineering judgment, we have estimated that the NOx adsorber catalyst will be sized on

average 1.5 times the engine displacement. This is consistent with the size of the NOx adsorber

catalyst on the Toyota Avensis diesel passenger car (60 prototypes of a planned 2003 production

car are being tested in Europe), which is sized at 1.4 times engine displacement.19

NOx Adsorber Substrate

The ceramic flow-through substrates used for the NOx adsorber catalyst were estimated to

cost $5.27 ($1999) per liter during our HD2007 rule. This cost estimate was based on a

relationship developed for current heavy-duty gasoline catalyst substrates.20 We have converted

that value to $5.44 ($2002) using the PPI for Motor Vehicle Parts and Accessories, Catalytic

Convertors.21

NOx Adsorber Washcoating and Canning

We have estimated a “value-added” engineering and material product, called washcoating

and canning, based on feedback from members of the Manufacturers of Emission Control

Association (MECA).22 By using a value-added component that accounts for fixed costs

(including R&D), overhead, marketing and profits from likely suppliers of the technology, we

can estimate this fraction of the cost for the technology apart from other components that are

more widely available as commodities (e.g, precious metals and catalyst substrates). Based on

conversations with MECA, we understand this element of the product to represent the catalyst

manufacturer’s value added and, therefore, their opportunity for markup. As a result, the

washcoating and canning costs shown in Table 6.2-11 represent costs with manufacturer

markups included. 

NOx Adsorber Precious Metals

The total precious metal content for the NOx adsorber is estimated to be 50 g/ft3 with

platinum representing 90 percent of that total and rhodium representing 10 percent. The costs

for rhodium and platinum used in this analysis are the 2002 average prices of $839 per troy

ounce for rhodium and $542 per troy ounce for platinum, as reported by Johnson Matthey.23

NOx Adsorber Alkaline Earth Metal – Barium
Final Regulatory Impact Analysis

6-32

The cost for barium carbonate (the primary NOx storage material) is assumed to be less than

$1 per catalyst as estimated in “Economic Analysis of Diesel Aftertreatment System Changes

Made Possible By Reduction of Diesel Fuel Sulfur Content.”

NOx Adsorber Can Housing

The material cost for the can housing is estimated based on the catalyst volume plus 20

percent for transition cones, plus 20 percent for scrappage (material purchased but unused in the

final product) and a price of $1.01 per pound for 18 gauge stainless steel as estimated in a

contractor report to EPA and converted into $2002.24

NOx Adsorber Direct Labor

The direct labor costs for the catalyst are estimated based on an estimate of the number of

hours required for assembly and established labor rates. Additional overhead for labor was

estimated as 40 percent of the labor rate.25

NOx Adsorber Warranty

We have estimated both near-term and long-term warranty costs. Near-term warranty costs

are based on a three percent claim rate and an estimate of parts and labor costs per incident,

while long-term warranty costs are based on a one percent claim rate and an estimate of parts

and labor costs per incident. The labor rate is assumed to be $50 per hour with four hours

required per claim, and parts costs are estimated to be 2.5 times the original manufacturing cost

for the component. The calculation of near-term warranty costs for the 9 hp engine shown in

Table 6.2-11 is as follows:

[($3 + $13 + $16 + $3 + $1 + $9)(2.5) + ($50)(4hours)](3%) = $9

NOx Adsorber Manufacturer and Dealer Carrying Costs

The manufacturer’s carrying cost was estimated at 4 percent of the direct costs. This reflects

primarily the costs of capital tied up in extra inventory, and secondarily the incremental costs of

insurance, handling and storage. The dealer’s carrying cost was estimated at 3 percent of the

incremental cost, again reflecting primarily the cost of capital tied up in extra inventory.26

NOx Adsorber DOC for System Clean-up

Included in the costs for the NOx adsorber system are costs for a diesel oxidation catalyst

(DOC) for clean-up of possible excess hydrocarbon emissions that might occur as a result of

system regeneration (removal of stored NOx and reduction to N2 and O2). The methodology

used to estimate DOC system costs is consistent with the methodology outlined here for NOx

adsorber systems and is presented below in Section 6.2.2.3. Important to note here is that the

DOC costs shown in Table 6.2-11 are lower in the long term because of the lower warranty
Estimated Engine and Equipment Costs

6-33

claim rate—three percent in the near term and one percent in the long term; learning effects, as

discussed below, are not applied to DOC costs.

NOx Adsorber Cost Estimation Function

Using the example NOx adsorber costs shown in Table 6.2-11, we calculated a linear

regression to determine the NOx adsorber system cost as a function of engine displacement. 

This way, the function can be applied to the wide array of engines in the nonroad fleet to

determine the total or per engine costs for NOx adsorber hardware. The functions calculated for

NOx adsorber system costs used throughout this analysis are shown in Table 6.2-12. Note that

Table 6.2-11 shows NOx adsorber system costs for engines under 75 hp. We do not anticipate

any engines under 75 hp will apply NOx adsorber systems to comply with the new emission

standards. Nonetheless, the costs shown were used to generate the equations shown in Table

6.2-12. Because of the linear relationship between engine displacement and NOx adsorber

system size (and, therefore, cost), including the costs for these smaller engines does not

inappropriately shift the cost equation downward.

Table 6.2-12

NOx Adsorber System Costs as a Function of 

Engine Displacement (x represents engine displacement in liters)

$2002

Near-Term Cost Function $103(x) + $183 R2=0.9998

Long-Term Cost Function $83(x) + $160 R2=0.9997

Table 6.2-12 shows both a near-term and a long-term cost function for NOx adsorber system

costs. The near-term function incorporates the near-term warranty costs determined using a

three percent claim rate, while the long-term function incorporates the long-term warranty costs

determined using a one percent claim rate. Additionally, the long-term function incorporates

learning curve effects for certain elements of the NOx adsorber system (i.e., learning effects

were not applied to the DOC portion of the NOx adsorber system, for reasons discussed below). 

In the HD2007 rule, we applied two learning effects of 20 percent. Here, we have assumed one

learning effect of 20 percent as a baseline level of learning; this represents learning done as a

result of the HD2007 rule. After a single doubling of production (i.e., two years), we have then

applied a single nonroad learning effect of 20 percent. Note that the equations shown in Table

6.2-12 include costs for a clean-up DOC; results generated using the DOC cost estimation

equations presented in Table 6.2-16 should not be added to results generated using the equations

in Table 6.2-12 to determine NOx adsorber system costs.

 

6.2.2.2 Catalyzed Diesel Particulate Filter Costs

As with the NOx adsorber system, the anticipated CDPF system for Tier 4 is the same as that

used for highway applications, except that we are projecting that some form of active

regeneration system will be employed as a backup to the passive regeneration capability of the
Final Regulatory Impact Analysis

6-34

CDPF. For the CDPF to function properly, a systems approach that includes a reductant

metering system and control of engine air-fuel ratio is also necessary. Many of the new air

handling and electronic fuel system technologies developed in order to meet the Tier 2/Tier 3

nonroad engine standards can be applied to accomplish the CDPF control functions as well. 

Nonroad applications are expected to present challenges beyond those of highway applications

with respect to implementing CDPFs. For this reason, we anticipate that some additional

hardware beyond the diesel particulate filter itself may be required to ensure that CDPF

regeneration occurs. For some engines this may be new fuel control strategies that force

regeneration under some circumstances, while in other engines it might involve an exhaust

system fuel injector to inject fuel upstream of the CDPF to provide necessary heat for

regeneration under some operating conditions. The cost estimates for such a regeneration system

are presented in Section 6.2.2.3.

We have used the same methodology to estimate costs associated with CDPF systems used in

our HD2007 rulemaking (although here, for nonroad engines, we have included costs for a

regeneration system that was not part of the cost estimate in the HD2007 rule). The basic

components of the CDPF are well known and include the following material elements:

• an oxidation catalyst, typically platinum-based;

• a substrate upon which the catalyst washcoating is applied and upon which PM is trapped;

• a can to hold and support the substrate; and,

• a regeneration system to ensure regeneration under all operating conditions (see Section

6.2.2.3).

Examples of these material costs are summarized in Table 6.2-13 and represent costs to the

engine manufacturers inclusive of supplier markups. The total direct cost to the manufacturer

includes an estimate of warranty costs for the CDPF system. Hardware costs are additionally

marked up to account for both manufacturer and dealer overhead and carrying costs. The

manufacturer’s carrying cost was estimated to be four percent of the direct costs accounting for

the capital cost of the extra inventory, and the incremental costs of insurance, handling, and

storage. The dealer’s carrying cost was marked up three percent reflecting the cost of capital

tied up in inventory. Considering input received from industry, we have adopted this approach

of estimating individually the manufacturer and dealer markups in an effort to better reflect the

value added at each stage of the supply chain.27
Estimated Engine and Equipment Costs

6-35

Table 6.2-13. Catalyzed Diesel Particulate Filter (CDPF) System Costs

Horsepower 9 hp 33 hp 76 hp 150 hp 250 hp 503 hp 660 hp 1000 hp

Average Engine Displacement (Liter) 0.39 1.50 3.92 4.70 7.64 18.00 20.30 34.50

Material and Component Costs

 Filter Volume (Liter) 0.59 2.25 5.88 7.05 11.46 27.00 30.45 51.75

 Filter Trap $36 $139 $364 $437 $710 $1,673 $1,886 $3,206

 Washcoating and Canning $13 $52 $135 $162 $263 $620 $700 $1,189

 Platinum $11 $42 $109 $130 $212 $499 $563 $956

 Filter Can Housing $7 $7 $7 $7 $10 $14 $14 $14

 Differential Pressure Sensor $46 $46 $46 $46 $46 $46 $93 $93

Direct Labor Costs $0 $0 $0 $0 $0 $0 $0 $0

 Estimated Labor hours 2 2222244

 Labor Rate ($/hr) $30 $30 $30 $30 $30 $30 $30 $30

 Labor Cost $60 $60 $60 $60 $60 $60 $120 $120

Labor Overhead @ 40% $24 $24 $24 $24 $24 $24 $48 $48

Total Direct Costs to Mfr. $198 $370 $746 $867 $1,326 $2,937 $3,424 $5,626

Warranty Cost -- Near Term (3% claim rate) $12 $24 $53 $62 $96 $217 $247 $412

Mfr. Carrying Cost -- Near Term $8 $15 $30 $35 $53 $117 $137 $225

Total Cost to Dealer -- Near Term $218 $409 $828 $963 $1,475 $3,271 $3,808 $6,264

Dealer Carrying Cost -- Near Term $7 $12 $25 $29 $44 $98 $114 $188

Savings by removing muffler -$46 -$46 -$46 -$46 -$46 -$46 -$46 -$46

Baseline Cost to Buyer -- Near Term $178 $375 $806 $945 $1,473 $3,323 $3,876 $6,405

Cost to Buyer w/ Highway learning -- Near Term $142 $300 $645 $756 $1,178 $2,658 $3,101 $5,124

Warranty Cost -- Long Term (1% claim rate) $4 $8 $18 $21 $32 $72 $82 $137

Mfr. Carrying Cost -- Long Term $8 $15 $30 $35 $53 $117 $137 $225

Total Cost to Dealer -- Long Term $210 $393 $793 $922 $1,411 $3,126 $3,643 $5,989

Dealer Carrying Cost -- Long Term $6 $12 $24 $28 $42 $94 $109 $180

Savings by removing muffler -$46 -$46 -$46 -$46 -$46 -$46 -$46 -$46

Baseline Cost to Buyer -- Long Term $170 $359 $770 $903 $1,407 $3,174 $3,706 $6,122

Cost to Buyer w/ Highway learning -- Long Term $136 $287 $616 $722 $1,125 $2,539 $2,965 $4,898

Cost to Buyer w/ Nonroad learning -- Long Term $109 $229 $493 $578 $900 $2,031 $2,372 $3,918

Catalyzed Diesel Particulate Filter (CDPF) Costs ($2002)

CDPF Volume

During development of our HD2007 rule, the Engine Manufacturers Association was asked

as part of a contractor work assignment to gather input from their members on catalyzed diesel

particulate filters for heavy-duty highway applications.28 The respondents indicated that the

particulate filter volume may range from 1.5 times the engine displacement to as much as 2.5

times the engine displacement based on their experiences at that time with cordierite filter

technologies. The size of the diesel particulate filter is selected largely based on the maximum

allowable flow restriction for the engine. Generically, the filter size is inversely proportional to

its resistance to flow (a larger filter is less restrictive than a similar smaller filter). In the

HD2007 rule and here, we have estimated that the diesel particulate filter will be sized to be 1.5

times the engine displacement based on the responses received from EMA and on-going research
Final Regulatory Impact Analysis

O Note that we are being especially conservative with respect to >750 horsepower mobile machines where we

believe that manufacturers may in fact use a wire mesh substrate rather than the SiC substrate we have costed and,

indeed, we have based the level of the 2015 PM standard on this use of wire mesh substrates. We have chosen to remain

conservative in our cost estimates by assuming use of a SiC substrate for all engines.

6-36

aimed at improving filter porosity control to give a better trade-off between flow restrictions and

filtering efficiency.

CDPF Substrate

CDPFs can be made from a wide range of filter materials including wire mesh, sintered

metals, fibrous media, or ceramic extrusions. The most common material used for CDPFs for

heavy-duty diesel engines is cordierite. Here we have based our cost estimates on the use of

silicon carbide (SiC) even though it is more expensive than other filter materials. In the HD2007

rule, we estimated that CDPFs will consist of a cordierite filter costing $30 per liter. To remain

conservative in our cost estimates for nonroad applications, we have assumed the use of silicon

carbide filters costing double that amount, or $60 per liter.O This cost is directly proportional to

filter volume, which is proportional to engine displacement. This $60 value is then converted to

$2002 using the PPI for Motor Vehicle Parts and Accessories, Catalytic Convertors.29 The end

result being a cost of $62 per liter.

CDPF Washcoating and Canning

These costs were done in a consistent manner as done for NOx adsorber catalyst systems, as

discussed above.

CDPF Precious Metals

The total precious metal content for catalyzed diesel particulate filters is estimated to be 30

g/ft3 with platinum as the only precious metal used in the filter. As done for NOx adsorbers, we

have used a price of $542 per troy ounce for platinum.

CDPF Can Housing

The material cost for the can housing is estimated based on the CDPF volume plus 20

percent for transition cones, plus 20 percent for scrappage (material purchased but unused in the

final product) and a price of $1.01 per pound for 18 gauge stainless steel as estimated in a

contractor report to EPA and converted into $2002.30

CDPF Differential Pressure Sensor

We have assumed that the catalyzed diesel particulate filter system will require the use of a

differential pressure sensor to provide a diagnostic monitoring function of the filter. A

contractor report to EPA estimated the cost for such a sensor at $45.31 A PPI adjusted cost of

$46 per sensor has been used in this analysis.
Estimated Engine and Equipment Costs

6-37

CDPF Direct Labor

Consistent with the approach for NOx adsorber systems, the direct labor costs for the CDPF

are estimated based on an estimate of the number of hours required for assembly and established

labor rates. Additional overhead for labor was estimated as 40 percent of the labor rate.32

CDPF Warranty

We have estimated both near-term and long-term warranty costs. Near-term warranty costs

are based on a three percent claim rate and an estimate of parts and labor costs per incident,

while long-term warranty costs are based on a one percent claim rate and an estimate of parts

and labor costs per incident. The labor rate is assumed to be $50 per hour with two hours

required per claim, and parts cost are estimated to be 2.5 times the original manufacturing cost

for the component.

CDPF Manufacturer and Dealer Carrying Costs

Consistent with the approach for NOx adsorber systems, the manufacturer’s carrying cost

was estimated at 4 percent of the direct costs. This reflects primarily the costs of capital tied up

in extra inventory, and secondarily the incremental costs of insurance, handling and storage. The

dealer’s carrying cost was estimated at 3 percent of the incremental cost, again reflecting

primarily the cost of capital tied up in extra inventory.33

Savings Associated with Muffler Removal

CDPF retrofits are currently often incorporated in, or are simply replacements for, the

muffler for diesel-powered vehicles and equipment. One report noted that, “Often, the trap could

be mounted in place of the muffler and had the same dimensions. Thus, rapid replacement was

possible. The muffling effect was often even better.”34 We have assumed that applying a CDPF

allows for the removal of the muffler due to the noise attenuation characteristics of the CDPF. 

We have accounted for this savings and have estimated a muffler cost of $46. The $46 estimate

is an average for all engines; the actual savings will be higher for some and lower for others.

CDPF System Cost Estimation Function

Using the example CDPF costs shown in Table 6.2-13, we calculated a linear regression to

determine the CDPF system cost as a function of engine displacement. This way, the function

can be applied to the wide array of engines in the nonroad fleet to determine the total or per

engine costs for CDPF system hardware. The functions calculated for CDPF system costs used

throughout this analysis are shown in Table 6.2-14.
Final Regulatory Impact Analysis

6-38

Table 6.2-14

CDPF System Costs as a Function of 

Engine Displacement (x represents engine displacement in liters)

$2002

Near-term Cost Function $146(x) + $75 R2=0.9997

Long-term Cost Function $112(x) + $57 R2=0.9997

The near-term and long-term costs shown in Table 6.2-14 change due to the different

warranty claim rates and the application of a 20 percent learning curve effect.

6.2.2.3 CDPF Regeneration System Costs

The CDPF regeneration system is likely to include an O2 sensor, a means for exhaust air to

fuel ratio control (one or more exhaust fuel injectors or in-cylinder means), a temperature sensor

and possibly a means to control mass flow through a portion of the catalyst system (for example,

for a “dual-bed” system). Incremental costs for a CDPF regeneration system, along with several

other costs discussed below, were developed by ICF Consulting under contract to EPA.35 The

cost estimates developed by ICF for a CDPF regeneration system are summarized in Table 6.2-

15.

Table 6.2-15.

CDPF Regeneration System – Costs to the Manufacturer

Horsepower 20 35 80 150 250 400 650 1000

Displacement (L) 1 2 3 6 8 10 16 24

CDPF Regeneration System Costs $265 $279 $293 $384 $408 $431 $530 $676

ICF Estimated Regeneration System Costs to Manufacturers ($2002)

Using these costs, we then estimated costs to the buyer using the same learning curve effects

and warranty claim rate factors discussed above. These results are presented in Table 6.2-16. 
Estimated Engine and Equipment Costs

6-39

Table 6.2-16.

CDPF Regeneration System – Costs to the User

Horsepower 20 35 80 150 250 400 650 1000

Displacement (L) 1 2 3 6 8 10 16 24

CDPF Regeneration System Costs $265 $279 $293 $384 $408 $431 $530 $676

Warranty Cost -- Near Term (3% claim rate) $23 $24 $25 $32 $34 $35 $43 $54

Mfr. Carrying Cost (4%) -- Near Term $11 $11 $12 $15 $16 $17 $21 $27

Total Cost to Dealer -- Near Term $298 $314 $330 $432 $458 $484 $593 $756

Dealer Carrying Cost (3%) -- Near Term $9 $9 $10 $13 $14 $15 $18 $23

Total Cost to Buyer -- Near Term $307 $323 $340 $445 $471 $498 $611 $779

Warranty Cost -- Long Term (1% claim rate) $8 $8 $8 $11 $11 $12 $14 $18

Mfr. Carrying Cost (4%)-- Long Term $11 $11 $12 $15 $16 $17 $21 $27

Total Cost to Dealer -- Long Term $283 $298 $313 $410 $435 $460 $565 $721

Dealer Carrying Cost (3%) -- Long Term $8 $9 $9 $12 $13 $14 $17 $22

Subtotal $291 $307 $323 $423 $448 $474 $582 $742

Total Cost to Buyer -- Long-Term w/ learning $233 $246 $258 $338 $359 $379 $466 $594

EPA Estimate of CDPF Regeneration System Costs ($2002)

As noted above, the CDPF regeneration system is expected to consist of an O2 sensor, a

temperature sensor, and probably a pressure sensor. The costs shown in Table 6.2-16 assume

none of these sensors or other pieces of hardware exist and, more importantly, they assume the

fuel control systems present in the engine are not capable of the sort of precise fuel control that

could perform many of the necessary functions of the regeneration system without any additional

hardware. For this reason, we consider the costs shown in Table 6.2-16 to be representative of

the costs for an engine with an indirect-injection (IDI) fuel system. For a direct-injection (DI)

fuel system, we expect that many of the functional capabilities for which costs were generated

will be handled by the existing fuel system. For example, we are assuming that all DI engines

will either convert to a fuel system capable of late injection or will already have a fuel system

capable of late injection. Late injection is one of the primary means of using fuel strategies to

force a CDPF regeneration event. Our cost estimates associated with conversion to such fuel

systems are discussed below. Because the regeneration system costs for DI engines are lower

than for an IDI engine, we have estimated that the regeneration system costs for a DI engine are

half of those presented in Table 6.2-16.

Also, note that the air handling, electronic, and fuel system hardware used for backup active

CDPF regeneration is expected to be used in common with the NOx adsorber regeneration

system. We have accounted for these costs here (as a CDPF regeneration system) because

CDPFs are required on a broader range of engines and, for many engines, earlier than are NOx

adsorbers. 
Final Regulatory Impact Analysis

6-40

CDPF Regeneration System Cost Estimation Function

Using the example regeneration system costs shown in Table 6.2-16, we calculated a linear

regression to determine the CDPF regeneration system cost as a function of engine displacement. 

This way, the function can be applied to the wide array of engines in the nonroad fleet to

determine the total costs for CDPF regeneration system hardware. The functions calculated for

CDPF regeneration system costs used throughout this analysis are shown in Table 6.2-17.

Table 6.2-17

CDPF Regeneration System Costs as a Function of 

Engine Displacement (x represents engine displacement in liters)

$2002

IDI Engine Near-term Cost Function $20(x) + $293 R2=0.9916

Long-term Cost Function $16(x) + $223 R2=0.9916

DI Engine Near-term Cost Function $10(x) + $147 R2=0.9916

Long-term Cost Function $8(x) + $111 R2=0.9916

Note that these costs—either the IDI or the DI costs, depending on the type of engine—are

incurred for any engine adding a CDPF. The near-term and long-term costs shown in Table 6.2-

17 change due to the different warranty claim rates and the application of a 20 percent learning

curve effect.

 

6.2.2.4 Diesel Oxidation Catalyst (DOC) Costs

The NOx adsorber regeneration and desulfation functions may produce undesirable byproducts in the form of momentary increases in HC emissions or in odorous hydrogen sulfide

(H2S) emissions. We have assumed that manufacturers may choose to apply a diesel oxidation

catalyst (DOC) downstream of the NOx adsorber technology to control these potential products. 

The DOC serves a “clean-up” function to oxidize any HC and H2S emissions to more desirable

products. As discussed below, for our cost analysis we have also projected that engines under 75

hp will add a DOC to comply with the 2008 PM standards, not to serve a “clean-up” function but

rather to serve as the primary means of emission control.

Our estimates of DOC costs are shown in Table 6.2-18. The individual component costs for

the DOC were estimated in the same manner as for the NOx adsorber systems and CDPF

systems, as discussed above. However, no learning effects were applied to DOCs because we

believe DOCs have been manufactured for a long enough time period such that learning has

already taken place.
Estimated Engine and Equipment Costs

6-41

Table 6.2-18.

Diesel Oxidation Catalyst (DOC) Costs

Horsepower 9 hp 33 hp 76 hp 150 hp 250 hp 503 hp 660 hp 1000 hp

Average Engine Displacement (Liter) 0.39 1.50 3.92 4.70 7.64 18.00 20.30 34.50

Material and Component Costs

 Catalyst Volume (liter) 0.39 1.50 3.92 4.70 7.64 18.00 20.30 34.50

 Substrate $2 $8 $21 $26 $42 $98 $110 $188

 Washcoating and Canning $61 $76 $107 $117 $155 $208 $220 $294

 Platinum (5 g/ft3) $1 $5 $12 $14 $24 $55 $63 $106

 Catalyst Can Housing $4 $4 $4 $4 $7 $15 $17 $30

Direct Labor Costs

 Estimated Labor hours 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

 Labor Rate ($/hr) $30 $30 $30 $30 $30 $30 $30 $30

 Labor Cost $15 $15 $15 $15 $15 $15 $15 $15

Labor Overhead @ 40% $6 $6 $6 $6 $6 $6 $6 $6

Total Direct Costs to Mfr. $90 $114 $166 $182 $248 $398 $432 $638

Warranty Cost -- Near Term (3% claim rate) $8 $10 $14 $15 $20 $31 $34 $49

Mfr. Carrying Cost -- Near Term $4 $5 $7 $7 $10 $16 $17 $26

Total Cost to Dealer -- Near Term $102 $128 $186 $205 $277 $445 $483 $713

Dealer Carrying Cost -- Near Term $3 $4 $6 $6 $8 $13 $14 $21

Total Cost to Buyer -- Near Term $105 $132 $192 $211 $286 $459 $497 $734

Warranty Cost -- Long Term (1% claim rate) $3 $3 $5 $5 $7 $10 $11 $16

Mfr. Carrying Cost -- Long Term $4 $5 $7 $7 $10 $16 $17 $26

Total Cost to Dealer -- Long Term $96 $122 $177 $195 $264 $425 $460 $680

Dealer Carrying Cost -- Long Term $3 $4 $5 $6 $8 $13 $14 $20

Total Cost to Buyer -- Long Term $99 $125 $182 $201 $272 $437 $474 $700

Diesel Oxidation Catalyst Costs ($2002)

DOC Cost Estimation Function

Similar to what was done for NOx adsorber systems and CDPFs, we used the example costs

shown in Table 6.2-18 to determine a cost function with engine displacement as the dependent

variable. This way, the function can be applied to the wide array of engines in the nonroad fleet

to determine the total or per unit costs for DOC hardware, whether that hardware be a stand

alone emission-control technology or as part of a NOx adsorber system. The cost functions for

DOCs used throughout this analysis are shown in Table 6.2-19. Note that the NOx adsorber cost

estimation equations shown in Table 6.2-12 include costs for a clean-up DOC; results generated

using the DOC cost estimation equations presented in Table 6.2-19 should not be added to

results generated using the equations in Table 6.2-12 to determine NOx adsorber system costs.
Final Regulatory Impact Analysis

6-42

Table 6.2-19

DOC Costs as a Function of 

Engine Displacement (x represents engine displacement in liters)

$2002

Near-term Cost Function $18(x) + $116 R2=0.9944

Long-term Cost Function $18(x) + $110 R2=0.9944

6.2.2.5 Closed-Crankcase Ventilation (CCV) System Costs

Consistent with our HD2007 rule, we are removing the provision that allows turbocharged

nonroad diesel engines to vent crankcase gases directly to the environment. Such engines are

said to have an open crankcase system. We project that this requirement to close the crankcase

on turbocharged engines will force manufacturers to rely on engineered closed crankcase

ventilation systems that filter oil from the blow-by gases before routing them into either the

engine intake or the exhaust system upstream of the CDPF. We expect these systems to be the

same as those expected for highway engines and have estimated their costs in the same manner

as done in our HD2007 rule. The estimated initial costs of these systems are as shown in Table

6.2-20. These costs are incurred only by turbocharged engines.

Table 6.2-20.

Closed Crankcase Ventilation (CCV) System Costs 

Horsepower 9 hp 33 hp 76 hp 150 hp 250 hp 503 hp 660 hp 1000 hp

Average Engine Displacement (Liter) 0.39 0.93 3.92 4.7 7.64 18 20.3 34.5

Cost to Manufacturer $28 $29 $34 $35 $41 $59 $64 $89

Warranty Cost -- Near Term (3% claim rate) $5 $5 $6 $6 $6 $7 $8 $10

Mfr. Carrying Cost -- Near Term $1 $1 $1 $1 $2 $2 $3 $4

Total Cost to Dealer -- Near Term $34 $35 $41 $42 $48 $69 $74 $103

Dealer Carrying Cost -- Near Term $1 $1 $1 $1 $1 $2 $2 $3

Total Cost to Buyer -- Near Term $35 $36 $42 $44 $50 $71 $76 $106

Warranty Cost -- Long Term (1% claim rate) $2 $2 $2 $2 $2 $2 $3 $3

Mfr. Carrying Cost -- Long Term $1 $1 $1 $1 $2 $2 $3 $4

Total Cost to Dealer -- Long Term $30 $31 $37 $39 $44 $64 $69 $96

Dealer Carrying Cost -- Long Term $1 $1 $1 $1 $1 $2 $2 $3

Cost to Buyer w/ Nonroad Learning -- Long Term $25 $26 $31 $32 $37 $53 $57 $79

Closed Crankcase Ventilation (CCV) System Costs ($2002)

CCV Cost Estimation Function

As discussed above, an equation was developed as a function of engine displacement to

calculate total or per unit CCV costs. These functions are shown in Table 6.2-21. Note that

these costs will be incurred only by turbocharged engines.
Estimated Engine and Equipment Costs

6-43

Table 6.2-21

CCV Costs as a Function of 

Engine Displacement (x represents engine displacement in liters)

$2002

Near-term Cost Function $2(x) + $34 R2=1

Long-term Cost Function $2(x) + $24 R2=1

6.2.2.6 Variable Costs of Conventional Technologies for Engines under 75 hp and over

750 hp

For the smaller engines, we have projected a different technology mix for complying with the

applicable emission standards. As explained in Chapter 4 of the RIA, we are projecting that

engines will comply either by adding a DOC or by making some engine modifications resulting

in engine-out emission reductions to comply with the 2008 PM standards. For our cost analysis,

we have assumed that all engines will add a DOC. Manufacturers will presumably choose the

least costly approach that provides the necessary emission control. If engine-out modifications

are less costly than a DOC, the analysis overestimates the costs associated with meeting these

standards. If the DOC proves to be less costly, then our estimate is representative of what most

manufacturers presumably will do. Therefore, we have assumed that, beginning in 2008, all

engines under 75 hp will add a DOC. Note that, as discussed in Chapter 4, some engines under

75 hp already meet the new PM standards (i.e., such engines will not have to make any changes

nor incur any incremental hardware costs for 2008), which also contributes to the likely

overestimate of costs. Our cost estimates for DOCs are presented above in Section 6.2.2.4.

As discussed in Chapter 4, we have also projected that some engines in the 25 to 75 hp range

will have to make changes to their engines to incorporate more conventional engine technology,

such as electronic common rail fuel injection, to meet the demands of the newly added CDPF. 

These costs were assumed for direct-injection (DI) engines. For indirect-injection (IDI) engines

in this power range, we believe manufacturers will comply not through a fuel system upgrade to

electronic common rail, but through the addition of a CDPF regeneration system to ensure

regeneration of the CDPF. The costs for CDPF regeneration systems are discussed above in

Section 6.2.2.3.

In the 25 to 50 hp range, we believe all engines will add cooled EGR to meet NOx standards. 

For our cost analysis, this is also true for engines over 750 hp. Note that engines over 750 hp are

also assumed to add the previously discussed emission-control technologies, i.e., a CDPF system

and some sort of CDPF regeneration system.

We project that manufacturers will add CCV systems to all these engines that are

turbocharged, both large and small. The costs for CCV systems are presented in Section 6.2.2.5.
Final Regulatory Impact Analysis

6-44

6.2.2.6.1 Electronic Common Rail Fuel-Injection System Costs for DI Engines

Cost estimates for fuel-injection systems were developed by ICF Consulting under contract

to EPA.36 Table 6.2-22 presents the costs to manufacturers as estimated by ICF for fuel-injection

systems.

Table 6.2-22

Fuel-Injection System – Costs to Manufacturers

Horsepower 20 hp 35 hp 80 hp 20 hp 35 hp 80 hp

Displacement (L) 1 2 3 1 2 3

# of Cylinders/Injectors 234234

Type of Fuel System Mech Mech ER ECR ECR ECR

High Pressure Fuel Pump $340 $340 $350 $340 $340 $350

Fuel Injectors (each) $16 $16 $25 $80 $80 $80

Cost for Injectors (total) $32 $48 $100 $160 $240 $320

Fuel Rail $100 $100 $100

Computer $300 $280 $280 $280

Sensors, Wiring, Bearings, etc. $68 $82 $189 $231 $625 $639

Total Fuel System Cost $440 $470 $939 $1,111 $1,205 $1,309

Incremental Cost $671 $735 $370

Mech=Mechanical Fuel Injection; ER=Electronic Rotary Injection; ECR=Electronic Common Rail Injection

Fuel System Costs ($2002)

Baseline System New System

Note that engines in the 50 to 75 hp range (represented in Table 6.2-22 by the 80 hp engine)

are assumed to have electronic rotary fuel-injection systems as a baseline configuration while

smaller engines are assumed to have mechanical fuel injection (see section II.A of the preamble

and section 4.1 of the RIA for more discussion on why this is a valid assumption). On an

incremental basis, the costs for common rail fuel injection are much lower when working from

an electronic rotary baseline because the electronic fuel pump and the computer are already part

of the system. This explains the large difference in fuel system costs for the 80 hp engine

relative to the 20 and 35 hp engines.

The costs shown in Table 6.2-22 show consistency for all elements across the power range. 

This is because most of the cost elements – fuel pump, costs per injector, and a computer – have

little to no relation to engine size or engine displacement. The primary cost element that 

changes for each of the example engines shown is that for the total cost of injectors. For this

reason, the costs can be more easily understood by separating the per injector cost out from the

rest of the system. This was done for the costs shown in Table 6.2-23, which also builds on the

manufacturer costs shown in Table 6.2-22 to generate costs to the user in the same manner as

done for other hardware system costs, as discussed above. We have broken out the fuel system

costs this way to make possible a cost equation that applies to all engines. Unlike the other cost

equations we have generated, the cost equation for fuel systems uses the number of injectors
Estimated Engine and Equipment Costs

6-45

(i.e., the number of cylinders) as the dependent variable rather than using engine displacement. 

This equation is presented below in Section 6.2.2.6.3.

Table 6.2-23

Incremental Fuel System Costs – Costs to the User

Horsepower

Number of Cylinders (# of injectors)

Remaining System per Injector

Cost to Manufacturer $56

Warranty Cost -- Near Term (3% claim rate) $7

Mfr. Carrying Cost (4%) -- Near Term $2

Total Cost to Dealer -- Near Term $65

Dealer Carrying Cost (3%) -- Near Term $2

Total Cost to Buyer -- Near Term $67

Warranty Cost -- Long Term (1% claim rate) $2

Mfr. Carrying Cost (4%)-- Long Term $2

Total Cost to Dealer -- Long Term $60

Dealer Carrying Cost (3%) -- Long Term $2

Subtotal $62

Total Cost to Buyer -- Long-Term w/ learning $50

Remaining System includes the fuel pump, fuel rail, computer, wiring, and necessary sensors.

$168

$134

80

4

$5

$6

$163

$18 $5

$605

$484

Remaining System

$152

$14

$6

$173

$5

$178

$15

$22

$551

$44

$22

$617

$551

$44

$22

$617

$3

$70

$2

$72

$75

$2

$78

$3

$605

$484

20

2

EPA Estimated Incremental Fuel System Costs for DI Engines ($2002)

per Injector

$72

$58

$18 $2

$58

$588

$3

$19

$636

$15

$70

$22

$588

$19

$636

$75

$2

$78

$3

$65

$8

$3

Remaining System

35

3

$65

$8

$3

per Injector

Note that these costs are projected to be incurred only on 25 to 75 hp DI engines. Note also

that, in determining aggregate variable costs for fuel-injection systems, we have attributed half

of the costs to the Tier 4 standards. We have done this for two reasons: penetration of electronic

fuel systems into the market and user benefits associated with the new fuel systems. First, we

are projecting that, by 2008, some engines in the 25 to 75 hp range will already be equipped with

electronic fuel systems independent of this rule. This is due to the natural progression of

electronic fuel systems currently available in larger power engines into some of the smaller

power engines. In fact, recent certification data prove that this is already happening, as

discussed in section 4.1.4 of this RIA. During our discussions with some engine companies, they

have indicated that they intend to use electronic fuel system technologies to comply with the

existing Tier 3 standards in the 50 to 100 hp range. These manufacturers have informed us that

these electronic fuel systems will also be sold on engines in the 25 to 50 hp range for those

engine product lines built on the same platform as engines over 50 hp. In addition, there are enduser benefits associated with electronic fuel systems, such as better torque response, lower noise,

easier servicing via on-board diagnostics, and better engine startability. Because we are not able

to predict the precise level of penetration of electronic fuel systems, nor are we able to quantify

the monetary value of the end-user benefits, we have accounted for these two effects by

attributing half of the costs of the electronic fuel systems to the Tier 4 standards.

6.2.2.6.2 Cooled EGR System Costs

Cost estimates for cooled EGR systems were developed by ICF Consulting under contract to

EPA.37 The incremental manufacturer costs for cooled EGR systems are shown in Table 6.2-24.
Final Regulatory Impact Analysis

6-46

Table 6.2-24

Cooled EGR System – Costs to Manufacturers

Horsepower 20 35 1000

Displacement (L) 1 2 24

EGR Cooler $36 $63 $289

EGR Bypass $15 $16 $30

Electronic EGR Valve $14 $15 $88

EGR Total Cost to Manufacturer $66 $95 $413

ICF Estimated Cooled EGR System Costs to Manufacturers ($2002)

Building on these manufacturer costs, we estimated the costs to the user assuming the

warranty claim rates and learning effects already discussed. These results are shown in Table

6.2-25. Included in these costs are costs associated with additional cooling that may be needed

to reject the heat generated by the cooled EGR system or other in-cylinder technologies. These

costs were not included in the proposal. Such additional cooling might take the form of a larger

radiator and/or a larger or more powerful cooling fan. Based on cost estimates from our

Nonconformance Penalty rule (67 FR 51464). In the support document for the NCP rule,38 we

estimated the costs associated with such additional cooling at $130 for a light heavy-duty vehicle

(~200hp) and $300 for a heavy heavy-duty vehicle (~500hp), inclusive of vehicle manufacturer

mark ups. Here, we have used these values to generate a curve with horsepower as the

dependent variable. That curve is $0.60 + $16.7(x), with an R2

=1 and where “x” represents

horsepower. Using this curve and the horsepowers shown in Table 6.2-25 we were able to

estimate the costs for additional cooling. The results shown in Table 6.2-25 include a three

percent dealer carrying cost.
Estimated Engine and Equipment Costs

6-47

Table 6.2-25

Cooled EGR System – Costs to the User

EPA Estimated Cooled EGR Costs ($2002)

Horsepower 20 35 1000

Displacement (L) 1 2 24

EGR System Cost to Manufacturer $66 $95 $413

Warranty Cost -- Near Term (3% claim rate) $8 $10 $34

Mfr. Carrying Cost (4%) -- Near Term $3 $4 $17

Total Cost to Dealer -- Near Term $77 $109 $463

Dealer Carrying Cost (3%) -- Near Term $2 $3 $14

EGR System Cost to Buyer -- Near Term $79 $112 $477

Warranty Cost -- Long Term (1% claim rate) $3 $3 $11

Mfr. Carrying Cost (4%)-- Long Term $3 $4 $17

Total Cost to Dealer -- Long Term $71 $102 $441

Dealer Carrying Cost (3%) -- Long Term $2 $3 $13

Subtotal $73 $105 $454

EGR System Cost to Buyer -- Long Term w/ learning $59 $84 $363

Heat rejection cost to Buyer (incl 3% dealer carrying cost) – Near Term $29 $38 $610

Heat rejection cost to Buyer (incl 3% dealer carrying cost) – Long Term $23 $31 $488

Total EGR-related Costs to Buyer -- Near-term $108 $151 $1,087

Total EGR-related Costs to Buyer -- Long-term $82 $115 $851

Despite the presence of cost data for a 20hp engine in Table 6.2-25, we are projecting that

only engines in the 25 to 50 hp range (in 2013) and engines over 750 hp will need to add cooled

EGR (in 2011), or use some other equally effective approach having presumably similar costs, to

comply with the new engine standards. All the costs associated with these systems have been

attributed to compliance with the new emission standards (i.e., we have not attributed any costs

to user benefits).

6.2.2.6.3 Conventional Technology Cost Estimation Functions

In the same manner as already described for exhaust emission-control devices, we were able

to calculate cost equations for cooled EGR systems (inclusive of additional cooling). For fuel

systems, rather than a linear regression, we simply expressed the fuel system costs as a function

of the number of fuel injectors, and then added on the costs associated with the rest of the

system. The rest of the system includes the fuel pump, the computer, wiring and sensors, which

should not change relative to engine size or displacement. This way, the functions could be

applied to the wide array of engines in the nonroad fleet to determine the total costs or per unit

costs for this hardware. The cost estimation functions for these technologies are shown in Table

6.2-26.
Final Regulatory Impact Analysis

6-48

Table 6.2-26

Costs for Conventional Technologies as a 

Function of the Indicated Parameter (x represents the dependent variable)

$2002

Technology Applicable Hp Range Dependent

Variable

Equation R2

Fuel System Costs – DI Only

 Near Term

 Long Term

 Near Term

 Long Term

25#hp<50

25#hp<50

50#hp<75

50#hp<75

# of cylinders $78(x) + $636

$58(x) + $484

$67(x) + $178

$50(x) + $134

—a

—a

Cooled EGR System (inclusive of

additional cooling)

 Near Term

 Long Term

25#hp<50; >750hp

25#hp<50; >750hp

displacement $43(x) + $65

$33(x) + $48

1

1

a

Not applicable because a linear regression was not used.

6.2.2.7 Summary of Engine Variable Cost Equations

Engine variable costs are discussed in detail in Sections 6.2.2.1 through 6.2.2.6. For engine

variable costs, we have generated cost estimation equations as a function of engine displacement

or number of cylinders. These equations are summarized in Table 6.2-27. Note that not all

equations were used for all engines; equations were used in the manner shown in Table 6.2-27. 

We have calculated the aggregate engine variable costs and present them later in this chapter and

in Chapter 8.
Estimated Engine and Equipment Costs

6-49

Table 6.2-27

Summary of Cost Equations for 

Engine Variable Costs (x represents the dependent variable)

Engine Technology Time Framea Cost Equation Dependent

Variable (x)

How Used

NOx Adsorber System Near term

Long term

$103(x) + $183

$83(x) + $160

Displacementb >75 hp engines according to

phase-in of NRT4 NOx std.

CDPF System Near term

Long term

$146(x) + $75

$112(x) + $57

Displacement >25 hp engines according to

NRT4 PM std.

CDPF Regen System –

IDI engines

Near term

Long term

$20(x) + $293

$16(x) + $223

Displacement IDI engines adding a CDPF

CDPF Regen System –

DI engines

Near term

Long term

$10(x) + $147

$8(x) + $111

Displacement DI engines adding a CDPF

DOC Near term

Long term

$18(x) + $116

$18(x) + $110

Displacement <25 hp engines beginning in

2008;

25-75 hp engines 2008 thru 2012

CCV System Near term

Long term

$2(x) + $34

$2(x) + $24

Displacement All turbocharged engines when

they first meet a Tier 4 PM std.

Cooled EGR System

w/ additional cooling

Near term

Long term

$43(x) + $65

$33(x) + $48

Displacement 25-50 hp engines beginning in

2013;

>750hp engines beginning in

2011

Common Rail Fuel

Injection

(mechanical fuel

system baseline)

Near term

Long term

$78(x) + $636

$58(x) + $484

# of cylinders/

injectors

25-50 hp DI engines when they

add a CDPF

Common Rail Fuel

Injection

(electronic rotary fuel

system baseline)

Near term

Long term

$67(x) + $178

$50(x) + $134

# of cylinders/

injectors

50-75 hp DI engines when they

add a CDPF

a

 Near term = years 1 and 2; Long term = years 3+. Explanation of near term and long term is in Section 6.1.

b

 Displacement refers to engine displacement in liters.

6.2.3 Engine Operating Costs

We are projecting that a variety of new technologies will be introduced to enable nonroad

engines to meet the Tier 4 emission standards. Primary among these are advanced emissioncontrol technologies and low-sulfur diesel fuel. The technology enabling benefits of low-sulfur

diesel fuel are described in Chapter 4. The incremental cost for low-sulfur fuel is described in

Chapter 7 and is not presented here. The new emission-control technologies are themselves

expected to introduce additional operating costs in the form of increased fuel consumption and

increased maintenance demands. Operating costs are estimated over the life of the engine and
Final Regulatory Impact Analysis

6-50

are expressed in terms of cents/gallon of fuel consumed. In Section 6.5 we present these lifetime

operating costs as a net present value (NPV) in 2002 dollars for several example pieces of

equipment.

A note of clarification needs to be added here. In Chapter 8 we present aggregate operating

costs. Every effort is made to be clear what costs are related to (1) the incremental increase in

the cost of fuel (due to the lower sulfur level), and (2) what costs are related to the expected

change in maintenance demands and the expected change in fuel consumption. The operating

costs discussed in this section are only the latter—maintenance related costs and/or savings and

fuel consumption costs. Increased costs associated with the lowering of sulfur in nonroad diesel

fuel are discussed in detail in Chapter 7. The cent-per-gallon costs presented in Chapter 7, along

with the cent-per-gallon costs and savings presented here, are then combined with projected fuel

volumes to generate the aggregate costs of the fuel program in this final rule.

 Total operating costs include the following elements: the change in maintenance costs

associated with applying new emission controls to the engines; the change in maintenance costs

associated with low-sulfur fuel such as extended oil-change intervals (extended oil change

intervals results in maintenance savings); the change in fuel costs associated with the

incrementally higher costs for low-sulfur fuel (see Chapter 7), and the change in fuel costs due to

any fuel consumption impacts associated with applying new emission controls to the engines. 

This latter cost is attributed to the CDPF and its need for periodic regeneration, which we

estimate may result in a small increase in fuel consumption, as discussed in more detail below. 

Maintenance costs associated with the new emission controls on the engines are expected to

increase, since these devices represent new hardware and therefore new maintenance demands. 

Offsetting this cost increase will be a cost savings due to an expected increase in oil-change

intervals, because low-sulfur fuel is far less corrosive than current nonroad diesel fuel. Less

corrosion corresponds with a slower acidification rate (i.e., less degradation) of the engine

lubricating oil and therefore more operating hours between oil changes.

6.2.3.1 Operating Costs Associated with Oil-Change Maintenance for New and Existing

Engines

We estimate that reducing fuel sulfur to 500 ppm will reduce engine wear and oil degradation

to the existing fleet of nonroad diesel engines, as well as locomotive and marine diesel engines. 

Reducing fuel sulfur to 15 ppm will further reduce engine wear and oil degradation. These

improvements provide a savings to users of this equipment. The cost savings will also be

realized by the owners of future nonroad engines that are subject to the emission standards in this

final rule. As discussed below, these maintenance savings have been estimated to be greater

than 3 cents/gallon when comparing current uncontrolled fuel to 15 ppm sulfur fuel.

We have identified a variety of benefits from the low-sulfur diesel fuel. These benefits are

summarized in Table 6.2-28.
Estimated Engine and Equipment Costs

6-51

Table 6.2-28.

Engine Components Potentially Affected by Lower Sulfur Levels in Diesel Fuel

Affected Components Effect of Lower Sulfur Potential Impact on Engine System

Piston Rings Reduced corrosion wear Extended engine life and less frequent

rebuilds

Cylinder Liners Reduced corrosion wear Extended engine life and less frequent

rebuilds

Oil Quality Reduced deposits, reduced

acid build-up, and less need

for alkaline additives

Reduce wear on piston ring and

cylinder liner and less frequent oil

changes

Exhaust System

(tailpipe)

Reduced corrosion wear Less frequent part replacement

Exhaust Gas

Recirculation System

Reduced corrosion wear Less frequent part replacement

The monetary value of these benefits over the life of the equipment will depend upon the

length of time that the equipment operates on low-sulfur diesel fuel and the degree to which

engine and equipment manufacturers specify new maintenance practices and the degree to which

equipment operators change engine maintenance patterns to take advantage of these benefits. 

For equipment near the end of its life in the 2008 time frame, the benefits will be quite small. 

However, for equipment produced in the years immediately preceding the introduction of 500

ppm sulfur fuel, the savings will be substantial. Additional savings will be realized in 2010 with

the introduction of 15 ppm sulfur fuel.

We estimate the single largest savings will be the impact of lower sulfur fuel on oil-change

intervals. We have estimated the extension of oil-change intervals realized by 500 ppm sulfur

fuel in 2007 and the additional extension resulting from 15 ppm sulfur fuel in 2010. These

estimates are based on our analysis of publically available information from nonroad engine

manufacturers. Due to the wide range of diesel fuel sulfur levels that nonroad engines may

currently see around the world, engine manufacturers specify different oil-change intervals as a

function of diesel sulfur levels. We have used these data as the basis for our analysis. Taken

together, when compared with the relatively high sulfur levels in current nonroad diesel fuel, we

estimate the use of 500 ppm sulfur fuel will enable an oil-change interval extension of 31

percent, while 15 ppm sulfur fuel will enable an oil-change interval extension of 35 percent

relative to current products.39

We present here a fuel cost savings attributed to the oil-change interval extension in terms of

a cent-per-gallon operating cost. Table 6.2-29 shows the calculation of cent-per-gallon savings

for various power segments of the nonroad fleet, and the locomotive and marine segments, for

both the 500 ppm fuel and the 15 ppm fuel. The brake specific fuel consumption (BSFC),

average hp, average activity, and average load factor data shown in the table are from our

nonroad model.40 The existing and new NRLM fleets will realize the savings associated with the
Final Regulatory Impact Analysis

6-52

500 ppm fuel for the years 2007 through 2010, and the the savings associated with the 15 ppm

fuel program for the years 2010 and beyond. We estimate that an oil-change interval extension of

31 percent enabled by 500 ppm sulfur fuel results in a weighted savings in fuel operating costs of

2.9 cents/gallon for the nonroad fleet. We project an additional weighted cost savings of 0.3

cents/gallon for the oil-change interval extension enabled by 15 ppm sulfur. Note that the

weighted savings are determined using the fuel use weightings shown in Table 6.2-29. For

locomotive and marine engines, these savings are 1 cent/gallon and 0.1 cent/gallon for the 500

ppm step and the 15 ppm step, respectively. 

Thus, for the nonroad fleet as a whole, beginning in 2010, nonroad equipment users can

realize an operating cost savings of 3.2 cents/gallon relative to current engines. For a typical 100

hp nonroad engine, this represents a net present value lifetime savings of more than $500. For

locomotive and marine engines the savings are estimated at 1.1 cents/gallon, which represents a

net present value lifetime savings of more than $2000. 
Table 6.2-29. Oil-Change Maintenance Savings for Existing and New Nonroad, Locomotive, and Marine Eng

Oil Change Savings due to Low S Units 

Rated Power hp 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<175 175<=hp<300 300<=hp<600 600<=hp<750 BSFC lbm/hp-hr 0.408 0.408 0.408 0.390 0.367 0.367 0.367 Fuel Density lbm/gallon 7.1 7.1 7.1 7.1 7.1 7.1 7.1 Population Weighted Avg. Horsepower hp 16 37 60 109 234 413 694 Population Weighted Avg. Activity hrs/year 523 582 764 675 537 619 947 Population Weighted avg. Load Factor % full load 0.41 0.44 0.40 0.47 0.57 0.57 0.56 Sump Oil Capacity L 1.58 3.62 5.83 10.55 22.68 40.07 67.33 Base Oil Change Interval -- 3000 ppm S hrs 250 250 250 250 250 250 250 Control Oil Change Interval -- 500 ppm S hrs 327.5 327.5 327.5 327.5 327.5 327.5 327.5 Labor Cost Per Oil Change $ $50.00 $50.00 $50.00 $50.00 $50.00 $50.00 $50.00 Cost of Oil Per Oil Change $ $3.16 $7.25 $11.65 $21.11 $45.35 $80.13 $134.66 Cost of Oil Filter Per Oil Change $ $18.00 $18.00 $18.00 $18.00 $35.00 $35.00 $35.00 Total Cost Per Oil Change $ $71.16 $75.25 $79.65 $89.11 $130.35 $165.13 $219.66 Fuel Consumption in 3000 ppm Oil Interval gallons 96 237 349 699 1732 3043 5044 Fuel Consumption in 500 ppm Oil Interval gallons 125 310 457 916 2269 3986 6608 Oil Change Cost/Gallon fuel in 3000 ppm Interval $/gallon $0.74 $0.32 $0.23 $0.13 $0.08 $0.05 $0.04 Oil Change Cost/Gallon fuel 500 ppm Interval $/gallon $0.57 $0.24 $0.17 $0.10 $0.06 $0.04 $0.03 Cost Differential -- 3000 to 500 ppm S $/gallon $0.176 $0.075 $0.054 $0.030 $0.018 $0.013 $0.010 Control Oil Change Interval -- 15 ppm S hrs 337.5 337.5 337.5 337.5 337.5 337.5 337.5 Labor Cost Per Oil Change $ $50.00 $50.00 $50.00 $50.00 $50.00 $50.00 $50.00 Cost of Oil Per Oil Change $ $3.16 $7.25 $11.65 $21.11 $45.35 $80.13 $134.66 Cost of Oil Filter Per Oil Change $ $18.00 $18.00 $18.00 $18.00 $35.00 $35.00 $35.00 Total Cost Per Oil Change $ $71.16 $75.25 $79.65 $89.11 $130.35 $165.13 $219.66 Fuel Consumption in 500 ppm Oil Interval gallons 125 310 457 916 2269 3986 6608 Fuel Consumption in 15 ppm Oil Interval gallons 129 320 471 944 2338 4108 6809 Oil Change Cost/Gallon fuel in 500 ppm Interval $/gallon $0.57 $0.24 $0.17 $0.10 $0.06 $0.04 $0.03 Oil Change Cost/Gallon fuel in 15 ppm Interval $/gallon $0.55 $0.24 $0.17 $0.09 $0.06 $0.04 $0.03 Cost Differential -- 500 to 15 ppm S $/gallon $0.017 $0.007 $0.005 $0.003 $0.002 $0.001 $0.001 Cost Differential -- 3000 to 15 ppm S $/gallon $0.193 $0.082 $0.059 $0.033 $0.020 $0.014 $0.011 Fuel Use Weightings % total 1.8% 5.2% 9.2% 31.6% 23.1% 18.8% 4.1% 

Nonroad Engines

(1) Oil-change intervals are from William Charmley memo to docket.41(2) Labor costs are from ICF Consulting under contract to EPA.42(3) Oil use estimates are based on sump volumes scaled to engine displacement and, as such, they show differences for each power category. The labor and filter costs are average values over a broad powoverstate the cost for some engines while understating the costs for others.
Final Regulatory Impact Analysis

6-54

The savings shown in Table 6.2-29 will occur without additional new cost to the equipment

owner beyond the incremental cost of the low-sulfur diesel fuel although these savings are

dependent on changes to existing maintenance schedules. Such changes seem likely given the

magnitude of the potential savings. We have not estimated the value of the savings from the

other benefits listed in Table 6.2-28. Therefore, we believe the 3.2 cents/gallon savings

underestimates actual cost savings as it accounts only for the impact of low-sulfur fuel on oilchange intervals.

Operating costs (savings) associated with oil-change maintenance are split evenly between

NOx and PM control.

6.2.3.2 Operating Costs Associated with CDPF Maintenance for New CDPF-Equipped

Engines

The maintenance demands associated with the addition of new CDPF hardware are discussed

in Section 4.1.1.3.4. To avoid underestimating costs, we have used a maintenance interval of

3,000 hours for engines under 175 hp and 4,500 hours for engines over 175 hp, both of which are

the minimum allowable maintenance intervals specified in our regulations (i.e., manufacturers

are precluded by regulation from requiring more frequent maintenance, and we believe they may

require less frequent maintenance than these minimum allowable maintenance intervals). We

have estimated costs associated with the maintenance at $65 for engines up to 600 hp and $260

per event for engines over 600 hp. The calculations for CDPF maintenance are shown in Table

6.2-30. Weighting the savings in each power range by the fuel-use weightings shown in the

table, we can calculate the fleet weighted maintenance costs as 0.6 cents/gallon, which will be

incurred only by new engines equipped with a CDPF. Operating costs associated with CDPF

maintenance are attributed entirely to PM control.

Table 6.2-30

CDPF Maintenance Costs for New CDPF-Equipped Engines ($2002)

PM Filter Maintenance Costs Units

Rated Power hp 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<175 175<=hp<300 300<=hp<600 600<=hp<750 >750hp

BSFC lbm/hp-hr 0.408 0.408 0.408 0.390 0.367 0.367 0.367 0.367

Fuel Density lbm/gallon 7.1 7.1 7.1 7.1 7.1 7.1 7.1 7.1

Population Weighted Avg. Horsepower hp 16 37 60 109 234 413 694 1282

Population Weighted Avg. Activity hrs/year 523 582 764 675 537 619 947 1130

Population Weighted avg. Load Factor % full load 0.409 0.441 0.404 0.468 0.573 0.570 0.562 0.571

Filter Maintenance Interval hours 3,000 3,000 3,000 4,500 4,500 4,500 4,500

Filter Maintenance Cost Materials $/event $0 $0 $0 $0 $0 $0 $0

Filter Maintenance Labor $/event $65 $65 $65 $65 $65 $130 $260

Total Filter Maintenance Cost per event $/event $65 $65 $65 $65 $65 $130 $260

Fuel Use Between Maintenance Interval gallons/period 2,844 4,185 8,391 31,174 54,767 90,791 170,326

Maintenance Cost $/gallon $0.023 $0.016 $0.008 $0.002 $0.001 $0.001 $0.002

Fuel Use Weightings % total 1.8% 5.2% 9.2% 31.6% 23.1% 18.8% 4.1% 6.2%

Nonroad Engines

Labor costs are from ICF Consulting under contract to EPA.43
Estimated Engine and Equipment Costs

P

 Typically, the filtering media is a porous ceramic monolith or a metallic fiber mesh. We refer to it as a “filter

trap” in Table 6.2-13. 

6-55

6.2.3.3 Operating Costs Associated with Fuel Economy Impacts on New Engines

6.2.3.3.1 What Are the Estimated Fuel Economy Impacts?

The high efficiency emission-control technologies expected to be applied to meet the PM

standards for engines greater than 25 hp and the NOx standards for engines greater than 75 hp

involve wholly new system components integrated into engine designs and calibrations and, as

such, may be expected to change the fuel consumption characteristics of the overall engine

design. After reviewing the likely technology options available to the engine manufacturers, we

believe the integration of the engine and exhaust emission-control systems into a single

synergistic emission-control system will lead to nonroad engines that can meet demanding

emission-control targets with only a small impact on fuel consumption. Technology

improvements have historically eliminated these marginal impacts in the past and it is our

expectation that this kind of continuing improvement will eliminate the modest impact estimated

here. However, because we cannot project the time frame for this improvement to be realized,

we have included this impact in our cost estimates for the full period of the program to avoid

underestimating costs.

6.2.3.3.1.1 CDPF Systems and Fuel Economy

Diesel particulate filters are anticipated to provide a step-wise decrease in diesel particulate

(PM) emissions by trapping and oxidizing the diesel PM. The trapping of the very fine diesel

PM is accomplished by forcing the exhaust through a porous filtering media with extremely

small openings and long path lengths.P This approach results in filtering efficiencies for diesel

PM greater than 90 percent but requires additional pumping work to force the exhaust through

these small openings. The impact of this additional pumping work on fuel consumption is

dependent on engine operating conditions. At low exhaust flow conditions (i.e., low engine

load, low turbocharger boost levels), the impact is so small that it typically cannot be measured,

while at very high load conditions, with high exhaust flow conditions, the fuel economy impact

can be as large as one to two percent.44,45 We have estimated that the average impact of this

increased pumping work will be equivalent to an increase fuel consumption of approximately

one percent.46

Under conditions typical of much of nonroad engine operation, the soot stored in the PM

filter will be regenerated passively using the heat of the exhaust gas promoted by catalyst

materials. We have performed an analysis of the expected exhaust temperatures for several

typical in-use operating cycles, as described in Section 4.1.3. That analysis shows that for a

many nonroad engines passive regeneration can be expected. Under some conditions, including

very low ambient temperatures, or extended low load operation, the exhaust temperature of the

engine may not be hot enough to ensure complete passive regeneration. We believe some

manufacturers will address this situation by employing active backup regeneration systems that
Final Regulatory Impact Analysis

6-56

provide supplemental heat to initiate regeneration, as discussed in Section 4.1. Also, as

explained in Section 6.2.2.3, we are conservatively costing active regeneration systems for all

engines using a CDPF system. We have done this because we think it is unlikely that nonroad

engine manufacturers will be able to accurately predict which engines will be operated in a

manner conducive to passive regeneration and which engines will require periodic active

regeneration. There will be no fuel economy impact for nonroad engines that have an active

regeneration technology but experience passive regeneration in use. Examples of current active

PM filter systems that do not benefit from low-sulfur diesel fuel, nor catalytic coatings to

promote regeneration, require additional fuel supplementation of approximately two percent for

active filter regeneration.47 Given the new requirements for clean diesel fuel in this final rule,

the ability to use catalytic coatings to promote soot oxidation, and the fact that many kinds of

nonroad equipment are expected to operate in a way that passive regeneration will occur, we

believe the average fuel economy impact of the backup regeneration systems will be no more

than one percent. 

We have projected that engines between 25 hp to 75 hp will comply with the PM standard of

0.02 g/bhp-hr using a CDPF system including a backup active regeneration system. The NOx

control systems expected in this power category are not advanced catalyst-based systems and, as

such, have limited ability to recover fuel economy through timing advance or other in-cylinder

NOx control strategies, as discussed below. We therefore project that a two percent fuel

economy impact (i.e., one percent due to backpressure and one percent due to use of backup

regeneration systems) will occur for engines between 25 hp and 75 hp. We believe

manufacturers will overcome this impact in the long term through continuing technology

refinement, as has historically happened. However, to avoid underestimating costs, we have

included this two percent impact for the duration of the program.

For engines under 25 hp we have projected no need to use CDPF technologies to comply

with the PM standards in the final rule. We therefore estimate no fuel consumption impact from

the CDPF for this category.

We believe engines all engines between 75 hp and 750 hp and mobile gensets above 750hp

will use integrated NOx and PM control technologies to comply with the new emission

standards. The advanced catalyst-based emission-control technology that we project industry

will use to meet the new NOx standard offers the opportunity to improve fuel economy, as

described in the following section. Based on those projected improvements, we have estimated a

net impact on fuel consumption of one percent for engines between 75 and 750 hp as well as

gensets >750 hp with CDPF technology and NOx technology. Future technology improvements

are likely to recover this fuel consumption impact; however, to avoid underestimating costs, we

have assumed that a one-percent fuel consumption impact persists for the duration of the

emission-control program.

At this time we are not setting a NOx standard for nonroad mobile machine engines >750 hp

based on the use of advanced NOx catalyst based technologies (see Preamble Section II.A). 

These engines, like the smaller engines between 25 and 75 hp, are projected to use diesel

particulate filter technologies to meet the Tier 4 PM standards. Therefore like the 25 to 75 hp
Estimated Engine and Equipment Costs

6-57

engines, we are estimating that nonroad mobile machines above 750 hp will have a two percent

fuel economy impact (i.e., one percent due to backpressure and one percent due to use of backup

regeneration systems). We believe manufacturers will overcome this impact in the long term

through continuing technology refinement, as has historically happened. However, to avoid

underestimating costs, we have included this two percent impact for the duration of the program.

6.2.3.3.1.2 NOx Control and Fuel Economy

NOx adsorbers are expected to be the primary technology to reduce NOx emissions for

engines between 75 and 750 hp as well as for mobile gensets above 750 hp. NOx adsorbers

work by storing NOx emissions under fuel-lean operating conditions (normal diesel engine

operating conditions) and then by releasing and reducing the stored NOx emissions over a brief

period of fuel-rich engine operation. This brief periodic NOx release and reduction step is

directly analogous to the catalytic reduction of NOx over a gasoline three-way catalyst. For this

catalyst function to occur, the engine exhaust constituents and conditions must be similar to

normal gasoline exhaust constituents. That is, the exhaust must be fuel rich (devoid of excess

oxygen) and hot (over 250oC). Although it is anticipated that nonroad diesel engines, like

highway diesel engines, can be made to operate in this way, it is anticipated that fuel economy

during operation under these conditions will be worse than normal. This increase in fuel

consumption can be minimized by carefully controlling engine air-fuel ratios using the control

systems we anticipate will be used to meet the Tier 3 emission standards. The lower the engine

air-fuel ratio, the lower the amount of fuel that must be added to reach rich conditions. In the

ideal case where the engine air-fuel ratio is at the stoichiometric level and additional fuel is

required only as a NOx reductant, the fuel economy penalty is nearly zero. We are projecting

that practical limitations on controlling engine air-fuel ratio will mean that the NOx adsorber

release and reduction cycles will lead to a one percent decrease in the engine fuel economy.48

We estimate that this fuel economy impact can be regained through optimization of the enginePM trap-NOx adsorber system, as discussed below.

In addition to the NOx release and regeneration event, another step in NOx adsorber

operation may affect fuel economy. As discussed earlier, sulfur affects NOx adsorbers even at

the low fuel-sulfur levels we are adopting. As discussed in Chapter 4, this effect can (and must)

be reversed through a periodic “desulfation” event. The desulfation of the NOx adsorber is

accomplished in a similar manner to the NOx release and regeneration cycle described above. 

However, it is anticipated that the desulfation event will require extended operation of the diesel

engine at rich conditions.49 This rich operation will, like the NOx regeneration event, require an

increase in the fuel consumption rate and will cause an associated decrease in fuel economy. 

This loss in fuel consumption is directly proportional to the amount of sulfur in diesel fuel. The

frequency of desulfation is therefore a function of the fuel sulfur level and the fuel consumption

rate. Since the desulfation frequency and the associated fuel consumption impacts are

proportional only to fuel rate and to fuel sulfur levels, the projected fuel consumption impacts at

15 ppm sulfur are the same for both highway and nonroad diesel engines. With a 15 ppm fuel

sulfur cap, we are projecting that fuel consumption for desulfation will increase by no more than

one percent, which we believe can be regained through optimization of the engine-CDPF-NOx

adsorber system, as discussed below. 
Final Regulatory Impact Analysis

Q We have estimated the fuel consumption rate for NOx regeneration and desulfation of the NOx adsorber as

approximately 2 percent of total engine fuel consumption. This differs from an EPA contractor report by EF&EE

estimating the total consumption to be approximately 2.5 percent of total fuel consumption. Additionally the contractor’s

estimate of NOx adsorber efficiency ranges from 80 to 90 percent, while we believe over 90 percent control is possible,

as discussed in Chapter 4.

6-58

While NOx adsorbers impact fuel economy by requiring nonpower-producing fuel

consumption to function properly, they are not unique among NOx control technologies in this

way. In fact, NOx adsorbers are likely to have a very favorable tradeoff between NOx emissions

and fuel economy compared with our projected technologies for meeting Tier 3 NOx

standards—cooled EGR and injection timing retard. EGR requires the delivery of exhaust gas

from the exhaust manifold to the intake manifold of the engine and causes a decrease in fuel

economy for two reasons. The first of these reasons is that a certain amount of work is required

to pump the EGR from the exhaust manifold to the intake manifold; this necessitates the use of

intake throttling or some other means to accomplish this pumping. The second of these reasons

is that heat in the exhaust, which is normally partially recovered as work across the turbine of the

turbocharger, is instead lost to the engine coolant through the cooled EGR heat exchanger. In

the end, cooled EGR is approximately 50 percent effective at reducing NOx below the current

Tier 2 NOx levels. Injection timing retard is another strategy that can be employed to control

NOx emissions. By retarding the introduction of fuel into the engine, and thus delaying the start

of combustion, both the peak temperature and pressure of the combustion event are decreased;

this lowers NOx formation rates and, ultimately, NOx emissions. Unfortunately, this also

significantly decreases the thermal efficiency of the engine (lowers fuel economy) while also

increasing PM emissions. As an example, retarding injection timing eight degrees can decrease

NOx emissions by 45 percent, but this occurs at a fuel economy penalty of more than seven

percent.50

Nonroad diesel engines generally rely primarily on charge-air-cooling and injection timing

control (retarding injection timing) to meet Tier 2 NOx+NMHC emission standards. For Tier 3

compliance, we expect that engine manufacturers will use a combination of cooled EGR and

injection timing control to meet the NOx standard. Because of the more favorable fuel economy

trade-off for NOx control with EGR compared with timing control, we forecast that less reliance

on timing control will be needed for Tier 3 than for Tier 2. Fuel economy will therefore not

change even at this lower NOx level. Similarly for the 25-50 hp engines subject to a Tier 4 NOx

standard of 3.3 g/hp-hr, we believe the NOx standard will not cause a change in fuel

consumption. NOx adsorbers have a significantly more favorable trade-off between NOx

emissions and fuel economy compared with cooled EGR or timing retard.51 We expect NOx

adsorbers to be able to accomplish a greater than 90 percent reduction in NOx emissions, while

themselves consuming significantly less fuel than that lost through alternative NOx control

strategies such as retarded injection timing.Q We therefore expect manufacturers to take full

advantage of the NOx control capabilities of the NOx adsorber and project that they will

decrease reliance on the more expensive (from a fuel economy standpoint) technologies,

especially injection timing retard. We therefore predict that the fuel economy impact currently

associated with NOx control from timing retard will be decreased by at least three percent. In

other words, through the application of advanced NOx emission-control technologies, which are
Estimated Engine and Equipment Costs

6-59

enabled by the use of low-sulfur diesel fuel, we expect the NOx trade-off with fuel economy to

continue to improve significantly when compared with current technologies. This will result in

much lower NOx emissions and potentially overall improvements in fuel economy. 

Improvements could easily offset the fuel consumption of the NOx adsorber itself and, in

addition, at least half of the fuel economy impact projected to result from the application of the

CDPF technology. Consequently, we are projecting a one percent fuel economy impact to result

from this rule for engines between 75 and 750 hp as well as mobile gensets above 750 hp. 

6.2.3.3.1.3 Fuel Economy Impacts for Engines without Advanced Emission-Control

Technologies (engines under 25 hp)

The new NOx emission standard for engines under 25 hp is unchanged from the current Tier

2 level. The PM standard, however, decreases by almost 50 percent. We believe manufacturers

will achieve this significant PM reduction through improvements in combustion system design,

improvements in fuel system design and utilization, and through the use of diesel oxidation

catalysts (DOCs). DOCs are expected to have no measurable effect on fuel consumption. 

However, changes to the engine designed to reduce PM emissions can lead to a reduction in fuel

consumption, at least for direct-injected diesel engines. The potential range for improved fuel

economy for engines of this size is unknown but experience with changes to engine design that

improve combustion and reduce PM suggest that the improvement may be significant. However,

because of the difficulty in projecting the future ratio of direct-injected and indirect-injected

diesel engines for this portion of the nonroad market and the first order affect that this ratio has

on average fleet consumption we have not attempted to account for this potential fuel economy

improvement in our cost analysis. We therefore estimate no change in fuel consumption in our

cost analyses for engines under 25 hp.

6.2.3.3.2 Costs Associated with these Fuel Economy Impacts

To calculate the costs associated with these fuel economy impacts, we have used a diesel fuel

price, minus taxes, of 60 cents/gallon. To that, we have added the incremental cost per gallon

for 15 ppm fuel. These incremental fuel costs are discussed in Chapter 7 as 7.0 cents/gallon. 

Using this 67 cent value, we apply the estimated fuel economy impact of an engine – 1% where

both a CDPF and a NOx adsorber are added, and 2% where a CDPF is added and no NOx

adsorber is present. This results in an increased operating cost for 75-750 hp engines of 0.67

cents/gallon (1% × 67 cents/gallon) for CDPF/NOx adsorber equipped engines and 1.34

cents/gallon for CDPF-only engines (2% × 67 cents/gallon). For 25-75 hp engines, and for >750

hp engines, where we estimate a two percent fuel economy impact, the estimated incremental

cost is 1.34 cents/gallon. Importantly, these fuel economy impacts are incurred only on new

engines; existing engines that do not meet the NRT4 standards will not see any fuel economy

impact.

Operating costs associated with fuel economy impacts are attributed only to PM control.
Final Regulatory Impact Analysis

6-60

6.2.3.4 Operating Costs Associated CCV Maintenance on New Engines

For CCV systems, we have used a maintenance interval of 675 hours for all engines and a

cost per maintenance event of $8 to $48 for small to large engines. The 675 maintenance

interval is chosen as twice the oil-change maintenance interval. CCV maintenance is assumed to

be done during every other oil-change event; this results in $0 labor cost for CCV maintenance. 

The calculation of operating costs associated with CCV maintenance is shown in Table 6.2-31. 

The new CCV requirements apply only to turbocharged engines (naturally aspirated engines

already have a closed crankcase requirement) so there are two cent/gallon values shown in Table

6.2-31 within each power range. The first value is the cent/gallon cost for a turbocharged engine

while the weighted cent/gallon cost within the power range (i.e., weighted by the percentage of

turbocharged engines). Using the fuel use weightings, we can calculate the fleetwide cent/gallon

cost using these latter costs within each power range. The result is a 0.2 cent/gallon cost.

Operating costs associated with CCV maintenance are attributed evenly to NOx and PM

control.

Table 6.2-31

Closed Crankcase Ventilation System 

Maintenance Costs for New Turbocharged Engines ($2002)

CCV Maintenance Costs Units

Rated Power hp 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<175 175<=hp<300 300<=hp<600 600<=hp<750 >750hp

BSFC lbm/hp-hr 0.408 0.408 0.408 0.390 0.367 0.367 0.367 0.367

Fuel Density lbm/gallon 7.1 7.1 7.1 7.1 7.1 7.1 7.1 7.1

Population Weighted Avg. Horsepower hp 16 37 60 109 234 413 694 1282

Population Weighted Avg. Activity hrs/year 523 582 764 675 537 619 947 1130

Population Weighted avg. Load Factor % full load 0.409 0.441 0.404 0.468 0.573 0.570 0.562 0.571

CCV Filter Replacement Interval hours 675 675 675 675 675 675 675 675

CCV Filter Replacement Cost $/event $8 $8 $8 $8 $10 $12 $24 $48

Filter Maintenance Labor $/event $0 $0 $0 $0 $0 $0 $0 $0

Total Filter Maintenance Cost per event $/event $8.00 $8.00 $8.00 $8.00 $9.60 $12.00 $24.00 $48.00

Fuel Use Between Maintenance Interval gallons/period 259 640 942 1,888 4,676 8,215 13,619 25,549

Turbcharged Fleet Fraction [%] 0% 2% 9% 62% 99% 100% 100% 100%

Maintenance Cost for engines adding CCV $/gallon $0.031 $0.013 $0.008 $0.004 $0.002 $0.001 $0.002 $0.002

Maintenance Cost - weighted for all engines $/gallon $0.000 $0.000 $0.001 $0.003 $0.002 $0.001 $0.002 $0.002

Fuel Use Weightings % total 1.8% 5.2% 9.2% 31.6% 23.1% 18.8% 4.1% 6.2%

Nonroad Engines

6.3 Equipment-Related Costs

Costs of control to equipment manufacturers include fixed costs (those costs for equipment

redesign and for tooling), and variable costs (for new hardware and increased equipment

assembly time). According to the PSR Sales Database for the year 2000,52 there are

approximately 600 nonroad equipment manufacturers using diesel engines in several thousand

different equipment models. We realize that the time needed for equipment manufacturers to

make the necessary changes on such a large number of equipment models will vary significantly

from manufacturer to manufacturer and from application to application. One of the goals of the

transition program for equipment manufacturers is to reduce the potential for anomalously high

costs for individual equipment models by providing significant additional time (up to seven
Estimated Engine and Equipment Costs

6-61

years) for developing less costly designs or to align the changes with an already scheduled

redesign. To remain conservative in our cost estimates, we have not factored into the analysis

the significant potential cost savings associated with these provisions; Section 6.3.3 explores the

potential cost savings of the transition program for equipment manufacturers.

6.3.1 Equipment Fixed Costs

6.3.1.1 Equipment Redesign Costs

The projected modifications to equipment resulting from the new emission standards relate to

the need to package emission-control hardware that engine manufacturers will incorporate into

their engines. As noted in Section 6.2, the additional emission-control hardware is proportional

in size to engine displacement by a 4:1 ratio (1.5 × engine displacement for both the CDPF and

the NOx adsorber, and 1.0 × displacement for the DOC that is part of the NOx adsorber system). 

We expect that equipment manufacturers will have to redesign their equipment to accommodate

this new volume of hardware. Some redesigns will be major in scale, while others will be minor. 

For example, redesign may simply involve bolting the new devices onto the existing design, but

in most cases we expect devices to be designed into the piece of equipment in a way that their

presence would not be obvious to the casual observer and, in fact, for some equipment they may

simply replace the existing muffler with no redesign needed. Additionally, a redesign to

accommodate a DOC (1.0 × engine displacement) should be less intensive than a redesign to

accommodate a CDPF/NOx adsorber system. Finally, for engines in the 75-750 hp range where

the final rule phases in new NOx standards, we assume that the redesign effort for those final

pieces of complying equipment (i.e., when the phase-in goes from 50 percent to 100 percent)

will be less costly than the first redesign effort.

6.3.1.1.1 Schedule of Equipment Redesigns

The final rule includes a varying compliance dates for different engines, as shown in Table

6.3-1. For this analysis, because we are assuming no use of the transition program for equipment

manufacturers, we assume that the timing of equipment redesigns will correlate with the timing

of new emission standards (assuming no use banking under the engine ABT program). This

results in a redesign schedule as shown in Table 6.3-1. We have noted the percentage of

equipment models we estimate will be redesigned in years for which new emission standards are

implemented. The table also notes the estimated percentage that will be major or minor redesign

efforts. We also note what percentage of the redesign costs are allocated to PM and to NOx.
Final Regulatory Impact Analysis

6-62

Table 6.3-1

Equipment Redesign Assumptions for Equipment Manufacturers

Power Engine

Standard

Dates

Pollutant

Allocation

Percent of Equipment

Models Undergoing

Minor Redesign

Percent of Equipment

Models Undergoing

Major Redesign

0<hp<25 2008 100% PM 100%

25#hp<50

2008 100% PM 100%

2013 50% PM

50% NOx 100%

50#hp<75

2008 100% PM 100%

2013 100% PM 100%

75#hp<175

2012 50% PM

50% NOx 100%

2014 100% NOx 50%

175#hp#750

2011 50% PM

50% NOx 100%

2014 100% NOx 50%

>750 hp

2011 100% NOx 100%

2015 100% PM 100%

Note that we have assumed all equipment redesigns for the 75 to 750 hp range are major in

the first year of new emission standards and minor in the last year. The costs associated with

such minor redesign efforts are assumed to be half those associated with major redesign efforts. 

We believe this is appropriate because equipment manufacturers will expend less effort to

redesign those pieces equipment needing to add only the NOx adsorber (in those years where the

NOx phase-in schedule changes from 50 percent to 100 percent) for three reasons: (1) these

models will already have been redesigned for the CDPF system and will already incorporate the

necessary electronic systems into their design; (2) equipment manufacturers will presumably

have gained experience during the major redesign phase that should make the minor redesign

phase more efficient; and (3) manufacturers that are aware of the future requirement will be able

to make provisions in the first redesign that account for future needs. Therefore, the second

redesign effort should be less intensive.

Our equipment redesign cost estimates were developed based on our meetings and

conversations with engine and equipment manufacturers, specific redesign cost estimates

provided by equipment manufacturers for the redesign of equipment to accommodate engines

meeting the Tier 2 standards, and our engineering judgment as needed. The following section

details our assessment of costs to equipment manufacturers.
Estimated Engine and Equipment Costs

6-63

6.3.1.1.2 Costs of Equipment Redesigns

While developing our equipment redesign cost estimates for the Tier 4 standards, we met

with a wide range of equipment manufacturers. This included equipment manufacturers with

annual revenues less than $50 million and engineering staffs of less than 10 employees,

equipment manufacturers with annual revenues on the order of $200 million and engineering 

staffs on the order of 50 employees, and equipment manufacturers with annual revenue well in

excess of $1 billion with annual research and development budgets of more than $100 million

and engineering staffs of more than 500 employees.

During these meetings and discussions, it became apparent to us that, in spite of the

significant engine technology differences between Tier 2/Tier 3 and Tier 4, the impact on

equipment design and the need for redesign are similar. That is, for Tier 2, many engines have

added electronic fuel systems, turbocharging, and charge-air-cooling. In addition, many Tier 2

engines rely on retarded fuel injection to lower NOx emissions, which therefore increases heat

rejection and requires the equipment manufacturers to install larger radiators and fans. The

process of equipment redesign for Tier 2 involved engineering work to accommodate these new

components (for example, charge-air-coolers, turbochargers, larger radiators and fans) and

electronic fuel systems. In many respects, this is similar to what will be required for Tier 4,

where engines still without electronic fuel systems will require them, and equipment

manufacturers will need to integrate aftertreatment systems (as compared with charge-aircoolers, turbochargers, larger radiators and fans). However, we believe that equipment redesigns

attributable to Tier 4 are more likely to occur early in the design cycle than many design changes

attributable to the Tier 2/3 rules. 

Some companies we met with before the proposal gave us specific redesign cost information

for the existing nonroad standards and, in some cases, projections for equipment redesigns

necessary to integrate aftertreatment (these data are confidential business information). We also

received redesign cost estimates from several equipment manufacturers during the Tier2/3

rulemaking regarding their projected costs for the Tier 2 standards (these data are confidential

business information). The information provided to us through these various channels showed

that there is a very wide range of cost estimates and actual cost data for redesigning nonroad

equipment for the Tier 2 standards. In general, we learned that very large companies tend to

allocate significantly more resources to equipment redesign than the medium or small

companies. 

We have used all this information and data, and our engineering judgment, to develop the

redesign cost estimates presented in Table 6.3-2. This table presents fixed cost per motive and

nonmotive equipment model (motive equipment is that with some form of propulsion system

while nonmotive equipment, such as air compressors, generator sets, hydraulic power units,

irrigation sets, pumps, compressors, and welders, has none) for each power group. In general,

nonmotive equipment has fewer design demands than does motive equipment – no operator lineof-sight demands, fewer serviceability constraints, and almost no impact (collision) concerns. 

As a result, we have estimated a lower redesign cost for nonmotive equipment relative to motive

equipment.
Final Regulatory Impact Analysis

6-64

Table 6.3-2

Estimated Equipment Redesign Costs Per Model

($2002)

Power Motive Nonmotive

0<hp<25 $53,100 $53,100

25#hp<75

 2008

 2013

$53,100

$199,125

$53,100

$79,650

75#hp<100 $371,700 $106,200

100#hp<175 $531,000 $106,200

175#hp<300 $531,000 $106,200

300#hp<600 $796,500 $106,200

600#hp#750 $796,500 N/A

>750hp

 2011

 2015

$106,200

$796,500

N/A

N/A

Using the PSR database we were able to determine the number of equipment models and the

type of equipment model (motive versus nonmotive). We distinguished motive from nonmotive

using our Nonroad Model definition of stationary applications. Nonmotive applications include

air compressors, generator sets, pumps, hydraulic power units, irrigation sets, and welders. All

other applications are considered motive. Table 6.3-3 shows the number of equipment models

we have estimated to be redesigned. Note that the models shown in Table 6.3-3 are not

necessarily all models but are instead the unique models that had 2000 model year sales. The

determination of unique models was based on manufacturer name (i.e., a Caterpillar skid/steer

loader is unique from a Bobcat skid/steer loader) and the market segment to which the model

belonged (i.e., an agricultural tractor is unique from a construction backhoe) and the engine

displacement. Therefore, while a manufacturer may consider two pieces of construction

equipment with the same base engine, one with and one without a turbocharger, to be two

distinct models, we consider that one model for the sake of equipment redesign.
Estimated Engine and Equipment Costs

6-65

Table 6.3-3

Number of Motive vs. Nonmotive Equipment Models

 to be Redesigned

Power Range Motive Nonmotive Total

0<hp<25 245 268 513

25#hp<50 407 177 584

50#hp<75 277 146 423

75#hp<100 354 153 507

100#hp<175 662 244 906

175#hp<300 648 241 889

300#hp<600 386 188 574

600#hp#750 80 0 80

<750hp 86 0 86

Total 3,145 1,417 4,563

Equipment redesign costs are estimated to occur during the two year period prior to the start

of the new emission standards for which the redesign is done. As done for engine fixed costs,

we have attributed only a portion of the equipment redesign costs to sales within the United

States. This is appropriate because we believe these efforts will be needed to sell equipment not

only in the United States, but also in Australia, Canada, Japan, and the countries of the European

Union. As discussed in Section 6.2.1.1, we have therefore attributed 42 percent of the equipment

fixed costs to U.S. sales. This is true with the exception of the <25hp range where we do not

expect other countries to have standards as low as the NRT4 standards and, as a result, all

redesign costs in this power range are attributed to today’s rule. Table 6.3-4 shows the total

redesign cost expenditures attributable to US sales for each power range.
Table 6.3-4

Equipment Redesign Expenditures 

Attributable to US Sales ($2002)

Year Incurred 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<

2006 $ 6,810,075 $ 7,752,600 $ 5,615,325 

2007 $ 6,810,075 $ 7,752,600 $ 5,615,325 2008 2009 $ 184,841,100 $ 163,707,300 $ 31,862010 $ 73,915,200 $ 188,717,400 $ 184,841,100 $ 163,707,300 $ 31,862011 $ 47,570,963 $ 33,393,263 $ 73,915,200 $ 188,717,400 2012 $ 47,570,963 $ 33,393,263 $ 18,478,800 $ 47,179,350 $ 46,210,275 $ 40,926,825 $ 7,962013 $ 18,478,800 $ 47,179,350 $ 46,210,275 $ 40,926,825 $ 7,962014 

Total to US Sales $ 13,620,150 $ 46,471,793 $ 32,767,214 $ 77,610,960 $ 198,153,270 $ 194,083,155 $ 171,892,665 $ 33,45

Table 6.3-5

Expenditures for Changes to Product Support Literature

Attributable to US Sales ($2002)

Year Incurred 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=

2006 $ 1,006,245 $ 2,631,105 $ 1,858,500 2007 $ 1,006,245 $ 2,631,105 $ 1,858,500 2008 2009 $ 4,080,735 $ 2,548,800 $ 4242010 $ 2,285,955 $ 4,163,040 $ 4,080,735 $ 2,548,800 $ 4242011 $ 2,631,105 $ 1,858,500 $ 2,285,955 $ 4,163,040 2012 $ 2,631,105 $ 1,858,500 $ 1,142,978 $ 2,081,520 $ 2,040,368 $ 1,274,400 $ 2122013 $ 1,142,978 $ 2,081,520 $ 2,040,368 $ 1,274,400 $ 2122014 

Total to US Sales $ 2,012,490 $ 4,420,256 $ 3,122,280 $ 2,880,303 $ 5,245,430 $ 5,141,726 $ 3,211,488 $ 535
Estimated Engine and Equipment Costs

6-67

6.3.1.2 Costs Associated with Changes to Product Support Literature

Equipment manufacturers are also expected to modify product support literature (dealer

training manuals, operator manuals, service manuals, etc.) due to the product changes resulting

from the new emission standards. For each product line of motive applications, we estimated

that the level of effort needed by equipment manufacturers to modify the support literature will

be about 100 hours—75 hours of junior engineering time, 20 hours of senior engineering time,

and 5 hours of clerical time—which amounts to about $10,620 in $2002. We projected that the

level of effort needed by equipment manufacturers to modify support literature for each

nonmotive application product line will be about 50 hours (distributed similarly), which is

equivalent to about $5,310. With the exception of the <25hp costs, we have attributed only a

portion of the product support literature costs to US sales as described above for equipment

redesign costs. Table 6.3-5 presents the total costs per power category for changes to support

literature.

6.3.1.3 Total Equipment Fixed Costs

The annual equipment fixed costs for each power category are shown in Table 6.3-6. As

described above and with the exception of <25 hp expenditures, we have attributed only a

portion of the equipment fixed costs to sales within the United States. This is appropriate

because we believe these efforts will be needed to sell equipment not only in the United States,

but also in Australia, Canada, Japan, and the countries of the European Union. As discussed in

Section 6.2.1.1, we have therefore attributed 42 percent of the equipment fixed costs to U.S.

sales.

The analysis projects that the expenditures will be incurred over a two-year period before the

first year of the emission standards. The costs were then amortized over ten years at a seven

percent rate beginning with the first year of the engine standard. The ten-year period for

amortization, as opposed to the five-year period used for engine costs, reflects the longer product

development cycles for equipment relative to engines.
Table 6.3-6

Recovered (Annualized) Equipment Fixed Costs per Power Category ($2002)

Year Recovered 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=7

2008 $ 2,303,637 $ 1,285,326 $ 925,132 $ - $ - $ - $ - $ 2009 $ 2,303,637 $ 1,285,326 $ 925,132 $ - $ - $ - $ - $ 2010 $ 2,303,637 $ 1,285,326 $ 925,132 $ - $ - $ - $ - $ 2011 $ 2,303,637 $ 1,285,326 $ 925,132 $ - $ - $ 23,385,312 $ 20,579,679 $ 3,996,2012 $ 2,303,637 $ 1,285,326 $ 925,132 $ 9,432,408 $ 23,875,320 $ 23,385,312 $ 20,579,679 $ 3,996,

2013 $ 2,303,637 $ 7,499,489 $ 5,288,701 $ 9,432,408 $ 23,875,320 $ 23,385,312 $ 20,579,679 $ 3,996,

2014 $ 2,303,637 $ 7,499,489 $ 5,288,701 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2015 $ 2,303,637 $ 7,499,489 $ 5,288,701 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2016 $ 2,303,637 $ 7,499,489 $ 5,288,701 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2017 $ 2,303,637 $ 7,499,489 $ 5,288,701 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2018 $ - $ 6,214,163 $ 4,363,569 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2019 $ - $ 6,214,163 $ 4,363,569 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2020 $ - $ 6,214,163 $ 4,363,569 $ 11,861,250 $ 29,972,978 $ 29,357,921 $ 25,803,473 $ 5,008,2021 $ - $ 6,214,163 $ 4,363,569 $ 11,861,250 $ 29,972,978 $ 5,972,609 $ 5,223,794 $ 1,012,22022 $ - $ 6,214,163 $ 4,363,569 $ 2,428,843 $ 6,097,658 $ 5,972,609 $ 5,223,794 $ 1,012,22023 $ - $ - $ - $ 2,428,843 $ 6,097,658 $ 5,972,609 $ 5,223,794 $ 1,012,2024 $ - $ - $ - $ - $ - $ - $ - $ Total $ 23,036,370 $ 74,994,887 $ 52,887,014 $ 118,612,501 $ 299,729,780 $ 293,579,210 $ 258,034,732 $ 50,085,
Estimated Engine and Equipment Costs

6-69

6.3.2 Equipment Variable Costs

In addition to the incrementally higher cost of new engines estimated in Sections 6.2.1 and

6.2.2, equipment manufacturers will need to purchase hardware to mount the new exhaust

emission-control devices within each newly redesigned piece of equipment. Note that the

redesign costs we have already discussed are for changes in equipment design to accommodate

aftertreatment devices. We assume that there are minimal changes to the variable costs for the

redesigned elements of the equipment (i.e., the redesigned elements cost roughly the same as

before) because they serve the same function and have the same amount of materials. Here, we

estimate the costs associated with the new hardware that will be necessary – new brackets, bolts,

and sheet metal – for mounting and housing (shrouding) the new aftertreatment devices.

New brackets and bolts will be required to secure the aftertreatment devices within the piece

of equipment. Additionally, increased labor ($29/hour) and overhead costs (40%) will be

incurred to install these devices. Table 6.3-7 shows the costs we have used per piece of

equipment ($/machine as shown in the table). Total costs per power range were calculated using

these costs and equipment sales in the year 2000.
Final Regulatory Impact Analysis

6-70

Table 6.3-7

Costs for Brackets and Bolts and Associated Labor for Equipment ($2002)

Brackets/bolts/etc.

devices added

new sets of 

brackets/bolts 

per device $/set $/machine

0<hp<25 1 0 $2 $0

25<=hp<75

2008 1 0 $0 $0

2013 1 2 $2 $4

75<=hp<175 2 2 $5 $21

175<=hp<300 2 2 $5 $21

300<=hp<=750 2 2 $11 $42

>750hp 2 2 $11 $42

Labor

device added hrs to install subtotal ($) overhead Total

0<hp<25 DOC 0 $0 $0 $0

25<=hp<75

2008 DOC 0 $0 $0 $0

2013 DPF 0.25 $7 $3 $10

75<=hp<175 DPF&NOxAds 0.5 $14 $6 $20

175<=hp<300 DPF&NOxAds 0.75 $22 $9 $30

300<=hp<=750 DPF&NOxAds 1.5 $43 $17 $61

>750hp DPF 1 $29 $12 $40

Note to Table 6.3-7: We have assumed the addition of two devices for engines >750hp when only a CDPF is being

added. It may have been more appropriate to assume one device but that the number of brackets and bolts needed would

be twice that for other engines (i.e., four sets rather than two) given the size of the device. Applying two smaller CDPFs

needing two sets of brackets and bolts leads to the same resultant cost for brackets and bolts. 

Sheet metal costs vary by size of the aftertreatment devices being added which, in turn, vary

by engine displacement as described in section 6.2. The amount of sheet metal for the shroud 

was determined using the engine displacement per equipment model information in the 2002

PSR Sales Database. The volume of the CDPF and NOx adsorber aftertreatment was calculated

for each unique equipment model (as described in section 6.3.1.1.2) in the PSR database with an

engine between 75 and 750 hp (1.5 times engine displacement for the CDPF and 1.5 times

engine displacement for the NOx adsorber). The DOC was assumed to fit in place of the

muffler. The volume of the aftertreatment was then converted to the volume of a cube and two

inches were added to each dimension for space between the aftertreatment and the shroud. Sheet

metal was assumed to cover four sides of the aftertreatment with no cover for the bottom or

equipment facing side of the shroud. Sheet metal was assumed to cost $1.14 per square foot for

hot rolled steel. The sheet metal cost for each model was multiplied by the total sales for that

model using the 2000 sales information in the 2002 PSR Sales Database.
Estimated Engine and Equipment Costs

R Note that for costing purposes we have assumed that a DOC is used on all engines under 75 hp to comply with the

2008 standards, although test data show that some engines already meet the new emission standards without a DOC. 

6-71

Summing these variable costs for each equipment model—sheet metal costs plus costs for

bolts, brackets, and labor—within each power range and then dividing by sales within the power

range gives a rough estimate of the costs we have estimated for a piece of equipment. It is

important to realize that this is weighted value within each power range determined by

calculating a unique cost for each piece of equipment, multiplying that cost by its sales, and then

totaling those costs within each power range. Table 6.3-8 shows the sales weighted equipment

variable costs within each power range. A twenty-nine percent manufacturer markup is also

included in the final cost estimates shown in Table 6.3-8.

Table 6.3-8

Sales Weighted Variable Costs per Piece of Equipment by Power Rangea

Totals include a 29% Manufacturer Markup ($2002)

Power Range Year Total

0<hp<25 2008 $0

25#hp<50 2013 $20

50#hp<75 2013 $21

75#hp<100 2012 $60

100#hp<175 2012 $61

175#hp<300 2011 $77

300#hp<600 2011 $146

600#hp#750 2011 $154

>750 hp 2011 $123

a

 These costs do not include the engine variable costs described in section

6.2.

As shown in Table 6.3-8, we have estimated equipment variable costs to be zero for

equipment with engines under 25 hp, under the expectation that an added DOC will replace the

existing muffler and make use of the same bracket/bolt/labor used for the muffler. This is also

expected for engines in the 25 to 75 hp range from 2008 through 2012 when, for our cost

anlaysis, only a DOC is being used by the engine manufacturer for compliance; additional bolts

and labor costs are included for the addition of a CDPF beginning in 2013.R While we have

assumed the CDPF will simply replace the muffler, there will be additional bracket/bolt/labor

demands due to the greater weight of the CDPF relative to the replaced muffler.
Final Regulatory Impact Analysis

6-72

6.3.3 Potential Impact of the Transition Provisions for Equipment Manufacturers

As discussed in Section III.B of the preamble, we are extending, and in some respects are

expanding, the transition program for equipment manufacturers (TPEM) that was developed in

the 1998 final rule. The TPEM is an important component of this final rule because of the

flexibility it provides for equipment manufacturers. However, as explained earlier, because the

program is optional, we have not included the potential impacts of TPEM on the estimated costs

of the Tier 4 program. Nevertheless, this section discusses how the TPEM program may

substantially reduce equipment manufacturer costs.

The TPEM can reduce equipment manufacturer costs in two ways. First, it allows equipment

manufacturers to continue to sell limited numbers of equipment with non-Tier 4 engines even

after the Tier 4 standards go into effect. Any engine price increase associated with the Tier 4

standards will therefore not be incurred by the equipment manufacturer or by the end user during

the time frame the manufacturers use the TPEM. Second, the TPEM allows manufacturers to

schedule equipment design cycles to coincide with any redesign necessary because of EPA’s

emission standards. We believe this is the most significant cost savings impact of the TPEM. 

This is due to the fact that many equipment manufacturers have a several small-volume model

lines. Using the TPEM program, companies can delay the redesign costs associated with Tier 4

engines for up to seven years on a limited number of products.

We performed a detailed analysis on an equipment manufacturer-by-equipment manufacturer

basis of the more than 6,000 equipment models and 600 equipment manufacturers in an industrywide database (the Power Systems Research database).53 This analysis looked at each equipment

manufacturer’s product offerings by power category and the estimated 2000 U.S. sales of each

equipment model. We used this database to analyze how equipment manufacturers can use

TPEM to maximize the number of equipment models with delayed redesign until the eighth year

of the program (as discussed in Section III.B of the preamble, TPEM provisions allow equipment

manufacturers to sell products with uncertified engines until seven years after the applicable Tier

4 standard is implemented.). We specifically analyzed the percent-of-production allowance and

the small-volume allowance programs being adopted for the Tier 4 rule (as discussed in the

preamble). The results are shown in Table 6.3-9. (It should be noted that the newly adopted

technical hardship flexibility provision, which potentially allows an additional 70 percent of

equipment manufacturer’s sales in a power category to use non-Tier 4 engines for a limited time

provided an appropriate case-by-case demonstration of extreme technical hardship is made to

EPA, likewise could have associated cost savings.)
Estimated Engine and Equipment Costs

6-73

Table 6.3-9

Potential Impact of TPEM Program on Equipment Models and Sales (all equipment companies)

Equipment Models/

Equipment Sales

Engine Power Category

<25 hp 25< hp <70a 70a

< hp <175 175< hp <750 >750 hp

All Power

Categories

Percent of all equipment models

that could use TPEM for fullseven years 56% 61% 66% 71% 80% 66%

Percent of equipment sales

that could use TPEM for fullseven years 7% 10% 13% 12% 21% 10%

a

 Note that the power ranges are 25-75 hp and 75-175 hp. This analysis was done using 70 hp as a cut-point. We believe

the results of this analysis would not have been significantly different if the power outpoint had been 75 hp.

This analysis indicates that if fully utilized by equipment manufacturers, 66 percent of

nonroad diesel equipment models can use the TPEM program to delay an equipment redesign

necessary for the Tier 4 standards for seven years. Without the TPEM program, equipment

manufactures would need to redesign all their equipment models using a nonroad diesel engine

in the first year of the engine standard implementation. As an example of the flexibility offered

by the TPEM program, Table 6.3-9 indicates that for engines between 25 and 75 hp, 61 percent

of all equipment models in this power range can take advantage of the TPEM (i.e., the percent of

production allowance and the small volume allowance options) to delay an equipment redesign

for seven years. It is important to note that while the TPEM can substantially reduce equipment

redesign costs, it is expected to have a much smaller impact on the emission reductions of the

program. While the TPEM can allow equipment companies to continue selling products with the

previous tier standards on many equipment models, the total sales that can be impacted by the

TPEM (i.e., the percent of production allowance and the small volume allowance options), which

is also shown in Table 6.3-9, is estimated to be no higher than ten percent for no more than seven

years.

The analysis presented in Table 6.3-9 is based on the equipment produced by a wide range of

equipment manufacturers, both very large, multi-billion dollar corporations as well as small

companies who produce a limited number of products. We have performed a similar analysis

using only those equipment companies whose data is contained in the PSR database which we

were able to identify as small businesses. In some respects the TPEM program, while available

to all equipment manufacturers, was designed specifically to benefit small businesses. Within

the PSR database, we were able to identify 337 small businesses who together produce more

than 2,500 different equipment models. This data was analyzed as described above for Table

6.3-9. The results are shown in Table 6.3-10.
Final Regulatory Impact Analysis

6-74

Table 6.3-10

Potential Impact of TPEM Program on Equipment Models and Sales of Small Business

Equipment Manufacturers

Equipment Models/

Equipment Sales

Engine Power Category

<25 hp 25< hp <70a 70a

< hp <175 175< hp <750 >750 hp

All Power

Categories

Percent of all equipment models

that could use TPEM for fullseven years 69% 74% 78% 86% 93% 79%

Percent of equipment sales

that could use TPEM for fullseven years 17% 24% 29% 51% 76% 26%

a

 Note that the power ranges are 25-75 hp and 75-175 hp. This analysis was done using 70 hp as a cut-point. We believe

the results of this analysis would not have been significantly different if the power outpoint had been 75 hp.

The results in Table 6.3-10 show that in all power categories, the TPEM program provides

more flexibility for small business equipment companies than for the equipment industry as a

whole. In every power category, the number of equipment models which small companies can

delay redesigning for the full seven years is greater than for the industry as a whole, and for the

power categories which will likely require engine aftertreatment (i.e., >25hp), approximately 75

percent or more of the equipment models could delay redesign for a full seven years. The actual

equipment sales for all of the small business equipment companies which could use the TPEM

program under this analysis is 26 percent of the total sales, but in reality this is less than 3

percent of the total nonroad diesel market, as small business companies have a relatively small

portion of the total nonroad diesel equipment sales.

6.4 Summary of Engine and Equipment Costs

Details of our engine and equipment cost estimates were presented in Sections 6.2 and 6.3. 

Here we summarize the cost estimates. Section 6.4.1.1 summarizes the total engine fixed costs. 

Section 6.4.1.2 summarizes the engine variable cost equations for estimating engine variable

costs. Section 6.4.1.3 summarizes the engine operating costs. Section 6.4.2.1 summarizes the

total equipment fixed costs and 6.4.2.2 summarizes the estimated equipment variable costs. 

Section 6.4.3 presents these costs on a per unit basis. Note that all present value costs presented

here are 30-year numbers (the net present values in 2004 of the stream of costs/reductions

occurring from 2007 through 2036, expressed in $2002). 

6.4.1 Engine Costs

6.4.1.1 Engine Fixed Costs

Engine fixed costs include costs for engine R&D, tooling, and certification. These costs are

discussed in detail in Section 6.2.1. The total estimated engine fixed costs are summarized in

Table 6.4-1. The table also includes 30-year net present values using both a three percent and a

seven percent social discount rate.
Estimated Engine and Equipment Costs

6-75

Table 6.4-1

Summary of Engine Fixed Costs ($2002)

Incurred Costs

($Million)

Recovered Cost

($Million)

30 Year NPV of

Recovered Cost

 at 3%

 ($Million)

30 Year NPV of

Recovered Cost

at 7%

 ($Million

Engine R&D $323 $452 $336 $233

Engine Tooling $74 $91 $70 $50

Engine Certification $91 $111 $84 $60

Total $489 $653 $490 $343

6.4.1.2 Engine Variable Costs

Engine variable costs are discussed in detail in Section 6.2.2. For engine variable costs, we

have generated cost estimation equations as a function of engine displacement or number of

cylinders (see Table 6.2-27). Using these equations, we have calculated the costs for each

nonroad diesel engine sold in the year 2000, multiplied that cost by its projected sales during the

30 year period following implementation of the NRT4 program, and then added the future annual

costs for each engine to arrive at annual costs during each of those 30 years. We present those

annual engine variable costs in Chapter 8. Table 6.4-2 shows the 30-year net present value of

those annual costs assuming a three percent social discount rate and a seven percent social

discount rate.

Table 6.4-2

30-Year Net Present Value of Engine Variable Costs

($2002)

30 Year NPVat 3%

($Million)

30 Year NPVat 7%

($Million)

Engine Variable Costs $13,562 $6,871

6.4.1.3 Engine Operating Costs

Engine operating costs are discussed in detail in Section 6.2.3. Table 6.4-3 summarizes

engine operating costs, excluding costs associated with the desulfurization of diesel fuel; these

costs are presented in Chapter 7.
Final Regulatory Impact Analysis

6-76

Table 6.4-3

Engine Operating Costs Associated with the NRLM Fuel Program

 (cents/gallon of 15ppm fuel consumed)

Power category Oil-Change

Savings

CDPF

Maintenance

CCV

Maintenance

CDPF

Regenerationa

Net Operating

Costsb

0<hp<25 (19.3) 0.0 0.0 0.0 (19.3)

25#hp<50 (8.2) 2.3 0.0 1.3 (4.6)

50#hp<75 (5.9) 1.6 0.1 1.3 (2.9)

75#hp<175 (3.3) 0.8 0.3 0.7 (1.5)

175#hp<300 (2.0) 0.2 0.2 0.7 (0.9)

300#hp<600 (1.4) 0.1 0.1 0.7 (0.5)

600#hp<750 (1.1) 0.1 0.2 0.7 (0.1)

>750 hp (1.1) 0.2 0.2 1.3 0.6

Locomotive/Marine (1.1) -- -- -- (1.1)

a

 A one or two percent fuel consumption increase, a 60 cent/gallon baseline fuel price, and a 7.0 cent/gallon

incremental fuel cost.

b

 The incremental costs for low-sulfur fuel are presented in Chapter 7.

Engines that make up the existing fleet will realize the oil-change savings shown in Table

6.4-3 while incurring none of the other operating costs, because these engines will not have

CDPF or CCV systems. New engines would incur all the costs and savings shown in Table

6.4-3.

Table 6.4-3 shows operating costs on a cent-per-gallon basis. Lifetime engine operating

costs vary by the amount of fuel consumed. We have calculated lifetime operating costs for

some example types of equipment and present those in Section 6.5. Aggregate operating costs

(the annual total costs) are presented in Chapter 8 and the 30-year net present value of the

NRLM fleet operating costs are shown in Table 6.4-4.
Estimated Engine and Equipment Costs

6-77

Table 6.4-4

30-Year Net Present Value of NRLM Fleetwide Engine Operating Costs

Excluding Fuel Costs

($2002)

30 Year NPV at

3%

($Million)

30 Year NPV at

7%

($Million)

Engine Operating Costs (a

negative value indicates a

savings)

-$4,517 -$2,745

6.4.2 Equipment Costs

6.4.2.1 Equipment Fixed Costs

Equipment fixed costs are discussed in detail in Section 6.3.1. Table 6.4-5 shows the

estimated equipment fixed costs associated with the Tier 4 emission standards. These figures

include estimated costs for equipment redesign and generation of new product support literature.

Table 6.4-5

Summary of Equipment Fixed Costs ($2002)

Incurred Costs

($Millions)

Recovered Costs

($Millions)

30 Year NPV of

Recovered Cost at

3%

 ($Million)

30 Year NPV of

Recovered Cost at

7%

 ($Million)

Redesign $801 $1,180 $819 $518

Product Literature $27 $40 $28 $18

Total $828 $1,220 $847 $537

6.4.2.2 Equipment Variable Costs

Equipment variable costs are discussed in detail in Section 6.3.2. Using the costs presented

there we have calculated the variable costs for the equipment sold in the year 2000 and then

projected those costs over the 30 year period following implementation of the NRT4 program. 

We present those annual equipment variable costs in Chapter 8. Table 6.4-6 shows the 30-year

net present value of those annual costs assuming a three percent and a seven percent social

discount rate.
Final Regulatory Impact Analysis

6-78

Table 6.4-6

30-Year Net Present Value of Equipment Variable Costs

($2002)

30 Year NPV at 3%

($Million)

30 Year NPV at 7%

($Million)

Equipment Variable Costs $434 $217

6.4.3 Engine and Equipment Costs on a Per Unit Basis

For the Nonroad Diesel Economic Impact Analysis Model (NDEIM, see Chapter 10), we

need engine and equipment costs per unit sold. These per unit costs serve as inputs to the model

to determine how the cost increases might impact the quantity of units sold. The costs presented

here in Chapter 6 are aggregated in Chapter 8 into annual fleetwide costs during a 30 year period

following implementation of the NRT4 program. The annual fleetwide engine fixed costs by

power category are shown in Table 8.2-1. The costs presented there represent the annual

recovered costs associated with engine R&D, tooling, and certification (note that these costs are

also presented in Tables 6.2-6, 6.2-8, 6.2-10, and 6.3-6. As explained earlier in this chapter, the

recovered engine R&D costs are revenue weighted, meaning that we have attributed the total

industry costs for engine R&D according to our best estimate of revenues from engine sales. 

Doing this does not impact the resultant total cost of the new Tier 4 standards and only impacts

how the costs are allocated to each power range. Such an allocation is of importance only when

trying to determine the per unit cost as we are here. Manufacturers may choose to recover their

investments in ways different than we have estimated, although recovering investments based on

revenues seems like the most likely probability.

Table 6.4-7 shows the per unit costs using this methodology. The values shown in the table

are simply the result of dividing the annual costs by power range shown in Table 8.2-1 by the

engine sales by power range shown in Table 8.1-1. The costs per unit change from year to year

because engine standards are implemented differently in each power category. As more engines

across more power categories phase-in to a new set of engine standards, the engine R&D costs

are recovered according to a different revenue weighting. Note also that tooling costs within

each power range can vary year to year on a per unit basis. This occurs because there are many

engine platforms that span different power ranges. Therefore, tooling expenditures done for an

engine platform that spans the 100-175 hp and the 175-300 hp ranges would be recovered only

on the 175-300 hp engines in 2011 and then on both 100-175 hp and 175-300 hp engines

beginning in 2012. Engine fixed costs per unit become zero after several years because the fixed

costs invested have been completely recovered. 

We can get the engine variable costs per unit in much the same way by dividing the

aggregate engine variable costs by power range shown in Table 8.2-3 by the engine sales by

power range shown in Table 8.1-1. The results are shown in Table 6.4-8. Note that the engine

variable costs per unit continue indefinitely and do not go to zero as do the engine fixed costs

shown in Table 6.4-7. Note also that, by 2020, the engine variable costs are not longer changing
Estimated Engine and Equipment Costs

6-79

due to phase-ins, learning curves, or other factors.

Equipment fixed and variable costs per unit can be generated in the same way. Tables 8.3-1

and 8.3-3 present the annual fleetwide equipment fixed and equipment variable costs by power

category. Dividing these costs by sales (Table 8.1-1) results in the per unit costs shown in

Tables 6.4-9 and 6.4-10 for equipment fixed and equipment variable costs per unit, respectively.
Table 6.4-7

Estimated Engine Fixed Costs per Unit ($2002)

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 

0<hp<25 $ 38 $ 37 $ 36 $ 35 $ 34 $ - $ - $ - $ - $ - $ - $ - $ - 

25<=hp<50 $ 49 $ 48 $ 47 $ 46 $ 45 $ 74 $ 73 $ 71 $ 70 $ 69 $ - $ - $ - 50<=hp<75 $ 50 $ 49 $ 49 $ 48 $ 47 $ 76 $ 75 $ 73 $ 72 $ 71 $ - $ - $ - 75<=hp<100 $ - $ - $ - $ - $ 80 $ 78 $ 108 $ 106 $ 104 $ 29 $ 28 $ - $ - 100<=hp<175 $ - $ - $ - $ - $ 78 $ 77 $ 106 $ 105 $ 103 $ 29 $ 29 $ - $ - 175<=hp<300 $ - $ - $ - $ 225 $ 220 $ 217 $ 290 $ 285 $ 74 $ 73 $ 72 $ - $ - 300<=hp<600 $ - $ - $ - $ 527 $ 521 $ 515 $ 735 $ 727 $ 220 $ 218 $ 216 $ - $ - 600<=hp<=750 $ - $ - $ - $ 1,156 $ 1,138 $ 1,122 $ 1,630 $ 1,606 $ 509 $ 502 $ 495 $ - $ - >750hp $ - $ - $ - $ 570 $ 561 $ 553 $ 545 $ 1,447 $ 897 $ 884 $ 872 $ 860 $ - 

Table 6.4-8

Estimated Engine Variable Costs per Unit ($2002)

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 

0<hp<25 $ 129 $ 129 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 

25<=hp<50 $ 147 $ 147 $ 139 $ 139 $ 139 $ 887 $ 887 $ 675 $ 675 $ 675 $ 675 $ 675 $ 675 50<=hp<75 $ 167 $ 167 $ 158 $ 158 $ 158 $ 837 $ 837 $ 636 $ 636 $ 636 $ 636 $ 636 $ 636 75<=hp<100 $ - $ - $ - $ - $ 1,133 $ 1,133 $ 1,122 $ 1,122 $ 1,122 $ 1,122 $ 1,122 $ 1,122 $ 1,122 100<=hp<175 $ - $ - $ - $ - $ 1,375 $ 1,375 $ 1,351 $ 1,351 $ 1,351 $ 1,351 $ 1,351 $ 1,351 $ 1,351 175<=hp<300 $ - $ - $ - $ 1,981 $ 1,981 $ 1,536 $ 1,937 $ 1,937 $ 1,937 $ 1,937 $ 1,937 $ 1,937 $ 1,937 300<=hp<600 $ - $ - $ - $ 2,609 $ 2,609 $ 2,021 $ 2,545 $ 2,545 $ 2,545 $ 2,545 $ 2,545 $ 2,545 $ 2,545 600<=hp<=750 $ - $ - $ - $ 4,944 $ 4,944 $ 3,825 $ 4,807 $ 4,807 $ 4,807 $ 4,807 $ 4,807 $ 4,807 $ 4,807 >750hp $ - $ - $ - $ 1,973 $ 1,973 $ 1,543 $ 1,543 $ 8,335 $ 8,335 $ 6,734 $ 6,734 $ 6,734 $ 6,734 
Table 6.4-9

Estimated Equipment Fixed Costs per Unit ($2002)

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 20

0<hp<25 $ 15 $ 15 $ 14 $ 14 $ 14 $ 13 $ 13 $ 13 $ 12 $ 12 $ - $ - $ - $ 

25<=hp<50 $ 8 $ 8 $ 8 $ 7 $ 7 $ 42 $ 41 $ 40 $ 40 $ 39 $ 32 $ 31 $ 31 $ 50<=hp<75 $ 8 $ 8 $ 8 $ 8 $ 8 $ 44 $ 43 $ 42 $ 42 $ 41 $ 33 $ 33 $ 32 $ 75<=hp<100 $ - $ - $ - $ - $ 109 $ 107 $ 132 $ 130 $ 128 $ 126 $ 124 $ 122 $ 120 $ 100<=hp<175 $ - $ - $ - $ - $ 170 $ 168 $ 207 $ 204 $ 201 $ 197 $ 194 $ 192 $ 189 $ 175<=hp<300 $ - $ - $ - $ 302 $ 297 $ 291 $ 360 $ 353 $ 348 $ 342 $ 336 $ 331 $ 326 $ 300<=hp<600 $ - $ - $ - $ 529 $ 523 $ 518 $ 642 $ 635 $ 628 $ 622 $ 615 $ 609 $ 603 $ 600<=hp<=750 $ - $ - $ - $ 1,210 $ 1,192 $ 1,175 $ 1,451 $ 1,430 $ 1,410 $ 1,390 $ 1,371 $ 1,353 $ 1,335 $ >750hp $ - $ - $ - $ 177 $ 175 $ 172 $ 170 $ 1,377 $ 1,358 $ 1,339 $ 1,320 $ 1,302 $ 1,285 $ 1

Table 6.4-10

Estimated Equipment Variable Costs per Unit ($2002)

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 20

0<hp<25 $ - $ - $ - $ - $ - $ - $ - $ - $ - $ - $ - $ - $ - $ 

25<=hp<50 $ - $ - $ - $ - $ - $ 20 $ 20 $ 16 $ 16 $ 16 $ 16 $ 16 $ 16 $ 50<=hp<75 $ - $ - $ - $ - $ - $ 21 $ 21 $ 17 $ 17 $ 17 $ 17 $ 17 $ 17 $ 75<=hp<100 $ - $ - $ - $ - $ 45 $ 45 $ 48 $ 48 $ 48 $ 48 $ 48 $ 48 $ 48 $ 100<=hp<175 $ - $ - $ - $ - $ 46 $ 46 $ 49 $ 49 $ 49 $ 49 $ 49 $ 49 $ 49 $ 175<=hp<300 $ - $ - $ - $ 58 $ 58 $ 46 $ 62 $ 62 $ 62 $ 62 $ 62 $ 62 $ 62 $ 300<=hp<600 $ - $ - $ - $ 110 $ 110 $ 88 $ 117 $ 117 $ 117 $ 117 $ 117 $ 117 $ 117 $ 600<=hp<=750 $ - $ - $ - $ 116 $ 116 $ 92 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ 123 $ >750hp $ - $ - $ - $ - $ - $ - $ - $ 123 $ 123 $ 98 $ 98 $ 98 $ 98 $ 
Final Regulatory Impact Analysis

6-82

6.5 Weighted Average Costs for Example Types of Equipment

6.5.1 Summary of Costs for Some Example Types of Equipment

To better illustrate the engine and equipment cost impacts for this final rule, we have chosen

several types of equipment and present the estimated costs for them using weighted average

inputs—horsepower, displacement, number of cylinders, etc. Using these sales weighted inputs,

we can calculate the costs for these types of equipment in several power ranges and better

illustrate the cost impacts of the new emission standards. For the weighted average inputs, we

have used the PSR database and determined the sales weighted averages of various parameters of

interest. These results are shown in Table 6.5-1. We can use the sales weighted average inputs

shown in Table 6.5-1 along with the engine variable cost equations presented in Table 6.4-2 to

generate the sales weighted average engine variable costs within each power range (doing so will

match the costs presented in Table 6.4-8). For engine fixed costs per unit and equipment fixed

and variable costs per unit, we can use the costs per unit presented in Tables 6.4-7, 6.4-9, and

6.4-10, respectively.

These results are presented in Table 6.5-2. Costs presented are near-term and long-term

costs for the final standards to which engines in each power category must comply. Long-term

costs include only variable costs and therefore represent costs after all fixed costs have been

recovered. Note that not all engines in each power category would incur all the costs shown in

the table. For example, only turbocharged engines will add a CCV system as a result of the

NRT4 final rule—it is important to remember that the costs presented in Table 6.5-2 are sales

weighted averages within each power range. Included in Table 6.5-2 are estimated operating

costs for each power range, again using the sales weighted average inputs shown in Table 6.5-1

along with information presented in Tables 6.2-29 through 6.2-31 and the fuel economy impacts

discussed in section 6.2.3.3. 

We can compare these sales weighted average costs by power range to the typical price of

various types of equipment—construction, agricultural, pumps & compressors, gensets &

welders, refrigeration & A/C, general industrial, and lawn & garden. We have estimated the

prices of these equipment using a linear relationship between the price for these types of

equipment and their power.54 Table 6.5-3 shows the resultant equipment prices. Table 6.5-4

shows the near-term and long-term costs (Table 6.5-2) as a percentage of equipment prices

(Table 6.5-3).
Table 6.5-1

Sales Weighted Average Inputs for Engine & Equipment Costs ($2002)

 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 

Sales Weighted Displacement (L) 0.753 1.650 2.592 3.872 4.916 7.773 10.755 Sales Weighted # Cylinders 2.2 3.1 3.8 4.0 4.7 6.0 6.1 Sales Weighted Hp 16.9 36.6 57.1 83.3 126.6 224.8 363.7 % Naturally Aspirated 100% 98% 91% 75% 13% 1% 0% % Turbo 0% 2% 9% 25% 87% 99% 100% % DI 33% 41% 85% 98% 100% 100% 100% % IDI 67% 59% 15% 2% 0% 0% 0% 

%DI and %IDI refer to the percentage of engines that have a direct injection fuel system and the percentage that have an indirect injection fuel system.
Table 6.5-2

Sales Weighted Average Near-Term and Long-Term Costs by Power Categorya

($2002, for the final emission standards to which the equipment must comply)

0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 30

Near-term costs calculated in the year: 2008 2013 2013 2012 2012 2011 

Engine variable costsFuel System $0 $182 $184 $0 $0 $0 EGR $0 $136 $0 $0 $0 $0 CCV* $0 $1 $3 $10 $39 $49 CDPF $0 $316 $454 $642 $795 $1,213 CDPF regen system $0 $259 $198 $190 $197 $226 NOx adsorber $0 $0 $0 $583 $691 $986 DOC $129 $0 $0 $0 $0 $0 

Engine Fixed Costs

R&D $15 $51 $54 $50 $51 $126 Tooling $8 $7 $6 $16 $16 $69 Cert $15 $16 $16 $14 $12 $29 

Equipment Variable Costs $0 $20 $21 $45 $46 $58 Equipment Fixed Costs $15 $42 $44 $109 $170 $302 Near-term Total Engine & Equipment Costs $180 $1,030 $980 $1,660 $2,020 $3,060 Long-term Total Engine & Equipment Costs in the year 2030 $120 $700 $650 $1,170 $1,400 $2,000 Operating Costs (discounted lifetime $)

Fuel Costs $110 $260 $650 $910 $1,390 $2,290 Oil Change Costs (Savings) -$310 -$310 -$550 -$430 -$660 -$640 System regenerations $0 $50 $120 $90 $130 $220 CCV maintenance $0 $0 $10 $30 $50 $70 CDPF maintenance $0 $90 $140 $100 $150 $70 

Total Incremental Operating Costs (Savings) -$200 $90 $370 $710 $1,070 $2,000 Baseline Operating Costs (fuel and oil only) $2,170 $3,410 $7,630 $9,490 $13,400 $21,360 

a. Near-term costs include both variable costs and fixed costs; long-term costs include only variable costs and represent those costs that remain following recovery 

b. For 25 to 75 hp engines, CCV costs in 2013 will be long term because CCV systems are first required in 2008.
6-85

Table 6.5-3

Sales Weighted Average Prices for Various Types of Equipment ($2002)

 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 

Construction Equipment $ 18,000 $ 29,700 $ 31,600 $ 57,900 $ 122,700 $ 247,300 $ 431,400 Agricultural Equipment $ 6,900 $ 14,400 $ 22,600 $ 33,400 $ 69,100 $ 125,900 $ 175,900 Pumps & Compressors $ 6,000 $ 12,200 $ 10,600 $ 12,500 $ 23,800 $ 37,500 $ 81,000 GenSets & Welders $ 6,800 $ 8,700 $ 8,300 $ 18,000 $ 21,400 $ 33,500 $ 39,500 Refrigeration & A/C $ 12,500 --- --- NA NA NA NA General Industrial $ 17,300 $ 42,300 $ 56,400 $ 74,300 $ 116,900 $ 141,700 $ 176,700 Lawn & Garden $ 9,300 $ 21,500 $ 33,100 $ 38,500 $ 29,900 $ 52,700 $ 85,100 

Table 6.5-4

Estimated Costs as a Percentage of New Equipment Price

0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 

Near-term Cost to Price Ratio

Construction Equipment 1% 3% 3% 3% 2% 1% 1% Agricultural Equipment 3% 7% 4% 5% 3% 2% 3%Pumps & Compressors 3% 8% 9% 13% 8% 8% 5%GenSets & Welders 3% 12% 12% 9% 9% 9% 11%Refrigeration & A/C 1%General Industrial 1% 2% 2% 2% 2% 2% 3% Lawn & Garden 2% 5% 3% 4% 7% 6% 5%

Long-term Cost to Price Ratio

Construction Equipment 1% 2% 2% 2% 1% 1% 1% Agricultural Equipment 2% 5% 3% 4% 2% 2% 2%Pumps & Compressors 2% 6% 6% 9% 6% 5% 3%GenSets & Welders 2% 8% 8% 7% 7% 6% 7%Refrigeration & A/C 1%General Industrial 1% 2% 1% 2% 1% 1% 2% Lawn & Garden 1% 3% 2% 3% 5% 4% 3%

* Note that the above percentages include equipment cost estimates that are averaged across all equipment types (i.e, motive and non-motive equipment

equipment are lower than for motive equipment (see Table 6.3-2). Therefore, the near-term percentages for non-motive equipment types (e.g., gensets, p

as the near-term percentages for motive equipment types are skewed slightly low. As a result, the long-term percentages, that represent the percentages equipment redesign have been recovered and are no longer part of the estimated cost, are probably better representations of the possible effect of the ru
Final Regulatory Impact Analysis

6-86

6.5.2 Method of Generating Costs for a Specific Piece of Equipment

To facilitate the effort to duplicate this example analysis for specific pieces of equipment,

this section will briefly describe the necessary steps to create the cost analysis based on the

information in this document.

The first step required to develop an estimate of our projected cost for control under the Tier

4 program is to define certain characteristics of the engine in the piece of equipment for which a

cost estimate is desired. Specifically, the following items must be defined:

• displacement of the engine (i.e., the cylinder swept volume) in liters;

• type of aspiration (i.e., turbocharged or naturally aspirated);

• number of cylinders;

• type of combustion system used by the engine (i.e., indirect-injection, IDI, or directinjection, DI);

• model year of production; and,

• the power category of the engine.

With this information and the data tables elsewhere in this document, it is possible to

estimate the costs of meeting the new standards for any particular piece of equipment.

As an example, we will estimate the cost of compliance for a 76 hp backhoe in the year 2012. 

The first step is to define our engine characteristics, as shown in Table 6.5-6.

Table 6.5-6

Engine and Equipment Characteristics of an Example Cost Estimate

76 hp Backhoe Example

Model Year 2012 reader defined

Displacement (liters) 3.9 application specific

Cylinder (number) 4 application specific

Aspiration Turbocharged application specific

Combustion System Direct Injection application specific

Power Category 75 to 175 hp regulations define the standards and

the timing of the standards

For engines produced in the early years of the program, an accounting of the fixed costs

needs to be made. Fixed costs include the engine fixed cost for research and development,

tooling, and certification as well as equipment fixed includes including redesign and manual

costs. These fixed costs are reported in this chapter on a per engine/piece of equipment basis in

each year of the program for which a fixed cost is applied. The necessary numbers to calculate

the fixed costs can simply be read from these tables.
Estimated Engine and Equipment Costs

6-87

Table 6.5-3

Fixed Costs for an Example Cost Estimate

2012 76hp Backhoe Example

Engine R&D $50 Table 6.2-6 Engine R&D Costs (per engine)

Engine Tooling $16 Table 6.2-8 Engine Tooling Costs (per engine)

Engine Certification $14 Table 6.2-10 Engine Certification Costs (per engine)

Total Engine Fixed $80 Summation (see also Table 6.4-7)

Total Equipment Fixed $109 Table 6.4-9 Equipment Fixed Cost per Unit

Total Fixed Costs $189 Summation

The engine variable costs are related to specific engine technology characteristics in a series

of linear equations described in table 6.2-27. The table includes all the different variable cost

components for different size ranges of engines meeting applicable emission standards. It

includes a description of the particular engine categories for which the costs are incurred. The

simplest approach to estimating the variable costs is to repeat the table and then to simply zero

out any components that do not apply for a particular example (see Table 6.5-4 below).
6-88

Table 6.5-4

Summary of Cost Equations for Engine Variable Costs 

for a 76hp Backhoe Example (x represents the dependent variable)

Engine Technology Time Framea Cost Equation Dependent

Variable (x)

How Used

NOx Adsorber System Near term

Long term

$103(x) + $183

$83(x) + $160 Displacementb >75 hp engines according to

phase-in of NRT4 NOx std.

2012 76hp Backhoe 2012 is 

Near Term

$103 (3.9)+$183 =

$585 3.9 liters

In 2012 a 76 hp engine in the

NOx phase-in set will require a

NOx adsorber

CDPF System Near term

Long term

$146(x) + $75

$112(x) + $57 Displacement >25 hp engines according toNRT4 PM std.

2012 76hp Backhoe 2012 is

Near Term

$146(3.9)+$75=

$644 3.9 liters In 2012 all 76hp engines are

projected to require CDPFs

CDPF Regen System –

IDI engines

Near term

Long term

$20(x) + $293

$16(x) + $223 Displacement IDI engines adding a CDPF

2012 76hp Backhoe 2012 is

Near Term not applicable 3.9 liters

The example engine has a directinjection combustion system, not

indirect-injection

CDPF Regen System –

DI engines

Near term

Long term

$10(x) + $147

$8(x) + $111 Displacement DI engines adding a CDPF

2012 76hp Backhoe 2012 is

Near Term

$10(3.9)+$147=

$186 3.9 liters The example engine is a DIengine and has a CDPF

DOC Near term

Long term

$18(x) + $116

$18(x) + $110 Displacement

<25 hp engines beginning in

2008;

25-75 hp engines 2008 thru 2012

2012 76hp Backhoe 2012 is

Near Term not applicable 3.9 liters Example engine rated power is

greater than 75 hp

CCV System Near term

Long term

$2(x) + $34

$2(x) + $24 Displacement All turbocharged engines whenthey first meet a Tier 4 PM std.

2012 76hp Backhoe 2012 is

Near Term

$2(3.9)+$34=

$42 3.9 liters The example engine is

turbocharged

Cooled EGR System Near term

Long term

$43(x) + $65

$33(x) + $48 Displacement

25-50 hp engines beginning in

2013; >750hp engines beginning

in 2011

2012 76hp Backhoe 2012 is

Near Term not applicable 3.9 liters Example rated power is greater

than 50 hp

Common Rail Fuel

Injection

(mechanical fuel

system baseline)

Near term

Long term

$78(x) + $636

$58(x) + $484

# of cylinders/

injectors

25-50 hp DI engines when they

add a CDPF

2012 76hp Backhoe 2012 is

Near Term not applicable 3.9 liters Example rated power is greater

than 50 hp

Common Rail Fuel

Injection

(electronic rotary fuel

system baseline)

Near term

Long term

$67(x) + $178

$50(x) + $134

# of cylinders/

injectors

50-75 hp DI engines when they

add a CDPF

2012 76hp Backhoe 2012 is

Near Term not applicable 3.9 liters Example rated power is greaterthan 75 hp

a

 Near term = years 1 and 2; Long term = years 3+. Explanation of near term and long term is in Section 6.1.

b

 Displacement refers to engine displacement in liters.
Estimated Engine and Equipment Costs

S Another important point here is that we have used the same load factor, activity, and fuel consumption inputs, etc.,

that were used in the draft RIA to ensure a fair comparison of operating cost differences between the draft analysis and

the final analysis. Note also that the inputs used for the values shown in Table 6.5-5 are for the specific pieces of

equipment and are not the sales weighted inputs used to generate the operating costs shown in Table 6.5-2, this explains

the different results.

6-89

Summing the applicable variable costs estimated in table 6.5-4 gives a total engine variable

cost for the 76hp Backhoe example of $1457 (Note that this value of $1457 differs from the

value shown in Table 6.4-8 due to that value being based on only 50 percent of engines in this

power range adding a NOx adsorber in 2012). The equipment variable costs are presented in

table 6.4-10 and are referenced by engine power category. For the 76hp example here, the

estimated equipment variable costs are $45.

Having estimated the engine and equipment fixed and variable costs it is possible to estimate

the total new product costs (excluding operating costs changes) by simply totaling the fixed and

variable costs estimated here. The resulting total is $1691 ($189 + $1457 + $45, note that

rounding may result in slightly different results). Typically we have presented these total cost

estimates to the nearest ten dollars.

6.5.3 Costs for Specific Examples from the Proposal

In the proposal, we developed costs and prices for several specific example pieces of

equipment. Here we recreate that analysis using the costs presented above for the final rule. 

Table 6.5-5 shows these results. For this table, we have used the same engine and equipment

related inputs (power, displacement, etc.) as was used in Table 6.5-1 of the draft RIA to facilitate

the comparison.S
Final Regulatory Impact Analysis

6-90

Table 6.5-5

Near Term and Long Term Costs for Several Example Pieces of Equipmenta

($2002, for the final emission standards to which the equipment must comply)

GenSet Skid/Steer

Loader

Backhoe Dozer Ag

Tractor

Dozer OffHighway

Truck

Horsepower 9 hp 33 hp 76 hp 175 hp 250 hp 503 hp 1000 hp

Displacement (L) 0.4 1.5 3.9 10.5 7.6 18 28

# of cylinders/injectors 1 3 4 6 6 8 12

Aspiration natural natural turbo turbo turbo turbo turbo

Fuel System DI DI DI DI DI DI DI

Incremental Engine &

Equipment Cost

 Long Term

 Near Term

$120

$180

$790

$1,160

$1,200

$1,700

$2,560

$3,770

$1,970

$3,020

$4,140

$6,320

$4,670

$8,610

Estimated Equipment

Priceb

$4,000 $20,000 $49,000 $238,000 $135,000 $618,000 $840,000

Incremental Operating

Costsc

-$80 $70 $610 $2,480 $2,110 $7,630 $20,670

Baseline Operating Costs

(Fuel & Oil only)c

$940 $2,680 $7,960 $27,080d $23,750 $77,850 $179,530

a. Near-term costs include both variable costs and fixed costs; long-term costs include only variable costs and

represent those costs that remain following recovery of all fixed costs.

b. Updated prices for the final analysis taken from, “Price Database for New Non-road Equipment,” memorandum

from Zuimdie Guerra to docket A-2001-28.55

c. Present value of lifetime costs.

d. This value corrects an error that existed in the draft RIA where we incorrectly reported the baseline operating cost

as $77,850 (the value for the 503 hp dozer).

6.6 Residual Value of Platinum Group Metals

One element not considered in our cost analysis is the residual value of the platinum group

metals (PGMs) in the aftertreatment devices that may be added to comply with the new engine

standards. These devices cannot be lawfully removed at the end of an engine’s life and reused

on a new engine or piece of equipment due to deterioration and/or agglomeration of the PGMs. 

However, virtually all of the PGMs contained in the devices will remain there and can be

removed and recycled back into the open market for use in new aftertreatment devices. This

represents a residual value to these metals much like the residual value to many other parts of a

truck headed for scrappage. Typically, today, the item of greatest residual value would be the

engine which can be removed from an old vehicle/truck prior to scrappage, rebuilt, and then sold

back into the market. This same thing can be expected to happen with the PGMs installed in the
6-91

aftertreatment devices.

From experts in the field,56, 57 we learned that there are as many as 50 major used/spent auto

catalyst collection sites in the United States. Further, roughly 80 percent of spent auto catalysts

are recycled in the US (only 30 percent are recycled currently in Europe, a percentage that will

presumably increase as more PGM containing devices are used in Europe). We also learned that

only one to two percent of platinum is lost during the recovery process and the same is true for

paladium. For rhodium, as much as 10 percent is lost during the recovery process.

We can estimate the residual value of PGMs being used to comply with the Tier 4 standards

by using the PGM loadings and the aftertreatment device volumes we have estimated will be

used (see section 6.2.2). Doing this results in a 30-year net present value, assuming a three

percent discount rate, of $3 billion (using the NRT4 PGM prices). This is roughly 20 percent of

the $13.6 billion engine variable costs we have estimated. But, according to experts in the field,

we cannot expect all of this value to be returned to the market. To be conservative, we have

assumed that 80 percent of aftertreatment devices would be recycled and that 98 percent of the

platinum in those devices would be recovered and returned to the market while only 90 percent

of the rhodium would be recovered and returned to the market. Further, we have assumed that

ten percent of the residual value would be kept by the recycler to cover costs associated with

recycling the material (i.e., energy use, labor, and profit).58 We must also consider the time gap

between installation on a new truck and recovery. For these calculations, we used the average

lifetimes by power category from our NONROAD model and assumed that, at the end of those

lifetimes, 80 percent of devices would be recovered. In this way, we calculate a net present

value of PGMs recovered in the year they first enter the new truck market. We have done this

for each of the 30 years following implementation of the Tier 4 standards giving us a series of

present values of recovered PGMs for each of 30 years. Note that, when accounting for the

latency period between the new equipment purchase and the ultimate recycling, we have used a

seven percent discount rate rather than three percent. Had we used a three percent rate, the

savings would have been higher. Table 6.6-1 shows these results along with the total annual

engine variable costs for comparison (see Table 8.2-3). 

The table shows that the residual value of PGMs could amount to a 30-year net present value

savings of roughly $1.2 billion, assuming a three percent social discount rate. Note that, while

we have estimated the residual value at $1.2 billion versus PGM use of $3 billion, this does not

mean that only 40 percent of PGMs are actually returned to the market. Instead, it means that

the present value of PGMs recovered are 40 percent of the value of those initially used. By our

estimation, nearly 80 percent of platinum will be recovered (98% of 80%) and just over 70

percent of rhodium will be recovered (90% of 80%). Note also that, to remain conservative in

our cost estimates, we have not used these estimates in any of our cost per ton or our benefit-cost

analyses. We have presented them here only for the information of the reader. 
Final Regulatory Impact Analysis

6-92

Table 6.6-1

Potential Impact of PGM Recovery on Costs

($Millions of 2002 dollars)

Year Engine Variable

Costs

(including PGMs)

PGM Costs PV of PGMs

Recovered

2008 $ 62 $ 2 $ (1)

2009 $ 63 $ 2 $ (1)

2010 $ 61 $ 2 $ (1)

2011 $ 340 $ 59 $ (22)

2012 $ 637 $ 113 $ (46)

2013 $ 798 $ 130 $ (54)

2014 $ 864 $ 186 $ (76)

2015 $ 839 $ 193 $ (79)

2016 $ 852 $ 196 $ (80)

2017 $ 860 $ 199 $ (82)

2018 $ 873 $ 202 $ (83)

2019 $ 887 $ 205 $ (84)

2020 $ 900 $ 208 $ (85)

2021 $ 913 $ 211 $ (87)

2022 $ 927 $ 214 $ (88)

2023 $ 940 $ 217 $ (89)

2024 $ 954 $ 220 $ (90)

2025 $ 967 $ 223 $ (92)

2026 $ 980 $ 226 $ (93)

2027 $ 994 $ 229 $ (94)

2028 $ 1,007 $ 232 $ (95)

2029 $ 1,021 $ 234 $ (97)

2030 $ 1,034 $ 237 $ (98)

2031 $ 1,048 $ 240 $ (99)

2032 $ 1,061 $ 243 $ (100)

2033 $ 1,074 $ 246 $ (102)

2034 $ 1,088 $ 249 $ (103)

2035 $ 1,101 $ 252 $ (104)

2036 $ 1,115 $ 255 $ (105)

30 Yr NPV at 3% $ 13,562 $ 2,996 $ (1,231)

30 Yr NPV at 7% $ 6,871 $ 1,488 $ (611)
Estimated Engine and Equipment Costs

6-93

1. “Electronic Systems and EGR Costs for Nonroad Engines,” Final Report, ICF Consulting,

December, 2002, Public Docket No. A-2001-28, Docket Item II-A-10.

2. “Estimated Economic Impact of New Emission Standards for Heavy-Duty On-Highway

Engines,” Acurex Environmental Corporation Final Report (FR 97-103), March 31, 1997, Public

Docket No. A-1996-40, Docket Item II-A-12.

3. “Economic Analysis of Vehicle and Engine Changes Made Possible by the Reduction of

Diesel Fuel Sulfur Content, Task 2 - Benefits for Durability and Reduced Maintenance” ICF

Consulting, December 9, 1999, Public Docket No. A-2001-28, Docket Item II-A-75.

4. “Update of EPA's Motor Vehicle Emission Control Equipment Retail Price Equivalent (RPE)

Calculation Formula," Jack Faucett Associates, Report No. JACKFAU-85-322-3, September

1985, Public Docket No. A-2001-28, Docket Item II-A-74.

5. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

6. “Learning Curves in Manufacturing," Linda Argote and Dennis Epple, Science, February 23,

1990, Vol. 247, pp. 920-924.

7. Power Systems Research, OELink Sales Version, 2002.

8. For the European Union: Directive of the European Parliament and of the Council amending

Directive 97/68/EC; For Canada: memo to public docket from Todd Sherwood, Public Docket

No. A-2001-28, Docket Item II-B-36.

9. “Financial Data regarding Geographic Allocation of Nonroad Diesel Equipment and Engine

Company Revenue and Sales,” memorandum from William Charmley to Air Docket OAR-2003-

0012, April 7, 2004, EDOCKET OAR-2003-0012-0927.

10. Nonroad Diesel Final Rule, 63 FR 56968, October 23, 1998.

11. “Learning Curves in Manufacturing,” Linda Argote and Dennis Epple, Science, February 23,

1990, Vol. 247, pp. 920-924.

12. “Treating Progress Functions As Managerial Opportunity”, J.M Dutton and A. Thomas,

Academy of Management Review, Rev. 9, 235, 1984, Public Docket A-2001-28, Docket Item IIA-73.

13. Nonconformance Penalty Final Rule, 67 FR 51464, August 8, 2002.

Chapter 6 References
Final Regulatory Impact Analysis

6-94

14. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

15. “Estimated Economic Impact of New Emission Standards for Heavy-Duty On-Highway

Engines,” March 1997, EPA420-R-97-009, Public Docket A-2001-28, Docket Item II-A-136.

16. “Cost Estimates for Heavy-Duty Gasoline Vehicles,” Arcadis Geraghty & Miller, September

1998, EPA Air Docket A-2001-28, Docket Item II-A-77.

17. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

18. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

19. McDonald and Bunker, “Testing of the Toyota Avensis DPNR at U.S. EPA-NVFEL,” SAE

2002-01-2877, October 2002.

20. “Cost Estimates for Heavy-Duty Gasoline Vehicles,” Arcadis Geraghty & Miller, September

1998, EPA Air Docket A-2001-28, Docket Item II-A-77.

21. U.S. Department of Labor, Bureau of Labor Statistics, Producer Price Index Home Page at

www.bls.gov/ppi , Industry: Motor Vehicle Parts and Accessories, Product: Catalytic

Convertors, Series Id: PCU3714#503. 

22. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

23. Johnson Matthey Platinum Today, www.platinum.matthey.com/prices .

24. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

25. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

26. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.
Estimated Engine and Equipment Costs

6-95

27. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

28. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

29. U.S. Department of Labor, Bureau of Labor Statistics, Producer Price Index Home Page at

www.bls.gov/ppi , Industry: Motor Vehicle Parts and Accessories, Product: Catalytic

Convertors, Series Id: PCU3714#503. 

30. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

31. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

32. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

33. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

34. Czerwinski, Jaussi, Wyser, and Mayer, “Particulate Traps for Construction Machines

Properties and Field Experience,” SAE 2000-01-1923, June 2000.

35. “Electronic Systems and EGR Costs for Nonroad Engines,” Final Report, ICF Consulting,

December, 2002, Public Docket No. A-2001-28, Docket Item II-A-10.

36. “Electronic Systems and EGR Costs for Nonroad Engines,” Final Report, ICF Consulting,

December, 2002, Public Docket No. A-2001-28, Docket Item II-A-10.

37. “Electronic Systems and EGR Costs for Nonroad Engines,” Final Report, ICF Consulting,

December, 2002, Public Docket No. A-2001-28, Docket Item II-A-10.

38. “Final Technical Support Document: Nonconformance Penalties for 2004 Highway Heavy

Duty Diesel Engines,” EPA420-R-02-021, August 2002.

39. “Estimate of the Impact of Low Sulfur Fuel on Oil Change Intervals for Nonroad Diesel

Equipment”, memo from William Charmley to Public Docket No. A-2001-28, Docket Item II-A194.
Final Regulatory Impact Analysis

6-96

40. “Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling: Compression

Ignition,” NR-009b, November 2002, Air Docket A-2001-28, Docket Item II-A-29; and, the

OTAQ web site for the Nonroad Model and supporting documentation at

www.epa.gov/otaq/nonrdmdl.htm

41. “Estimate of the Impact of Low Sulfur Fuel on Oil Change Intervals for Nonroad Diesel

Equipment”, memorandum from William Charmley to Public Docket No. A-2001-28, Docket

Item II-A-194.

42. “Economic Analysis of Vehicle and Engine Changes Made Possible by the Reduction of

Diesel Fuel Sulfur Content; Task 2 Final Report: Benefits for Durability and Reduced

Maintenance,” ICF Consulting, December 9, 1999, Air Docket A-2001-28, Docket Item II-A-75.

43. “Economic Analysis of Vehicle and Engine Changes Made Possible by the Reduction of

Diesel Fuel Sulfur Content; Task 2 Final Report: Benefits for Durability and Reduced

Maintenance,” ICF Consulting, December 9, 1999, Air Docket A-2001-28, Docket Item II-A-75.

44. Schenk, C., McDonald, J., and Laroo, C. “High-Efficiency NOx and PM Exhaust Emission

Control for Heavy-Duty On-Highway Diesel Engines - Part Two,” SAE 2001-01-3619.

45. LeTavec, C., et al, “Year-Long Evaluation of Trucks and Buses Equipped with Passive

Diesel Particulate Filters,” March 20002, SAE 2002-01-0433.

46. “Economic Analysis of Diesel Aftertreatment System Changes Made Possible by Reduction

of Diesel Fuel Sulfur Content,” Engine, Fuel, and Emissions Engineering, Incorporated,

December 15, 1999, Public Docket No. A-2001-28, Docket Item II-A-76.

47. Johnson, T., “Diesel Emission Control: 2001 in Review,” March 2002, SAE 2002-01-0285.

48. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” December 2000, EPA420-R-00-026, Docket Item IIA-01.

49. Dou, D. and Bailey, O., “Investigation of NOx Adsorber Catalyst Deactivation”

SAE982594.

50. Herzog, P. et al, NOx Reduction Strategies for DI Diesel Engines, SAE 920470, Society of

Automotive Engineers 1992 (from Figure 1).

51. Zelenka, P., et al., “Cooled EGR - A Key Technology for Future Efficient HD Diesels”,

SAE 980190. 

52. Power Systems Research, OELink Sales Version, 2002.

53. Power Systems Research, OELink Sales Version, 2002.
Estimated Engine and Equipment Costs

6-97

54. “Price Database for New Nonroad Equipment,” memorandum from Zuimdie Guerra to EPA

Air Docket OAR-2003-0012, EDOCKET OAR-2003-0012-0960.

55. “Price Database for New Nonroad Equipment,” memorandum from Zuimdie Guerra to EPA

Air Docket OAR-2003-0012, EDOCKET OAR-2003-0012-0960.

56. “Meeting with Johnson Matthey regarding PGM Recycling,” memorandum from Todd

Sherwood to Air Docket A-2001-28, Docket Item IV-E-43, EDOCKET OAR-2003-0012-0877,

March 16, 2004.

57. “Telephone Conversation with Jim Roberts of Multimetco, Inc., regarding PGM Recycling,”

memorandum from Todd Sherwood to Air Docket A-2001-28, Docket Item IV-E-39, EDOCKET

OAR-2003-0012-0869, March 16, 2004.

58. “Telephone Conversation with Jim Roberts of Multimetco, Inc., regarding PGM Recycling,”

memorandum from Todd Sherwood to Air Docket A-2001-28, Docket Item IV-E-39, EDOCKET

OAR-2003-0012-0869, March 16, 2004.
CHAPTER 7: Estimated Costs of Low-Sulfur Fuels

7.1 Production and Consumption of NRLM Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

7.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

7.1.2 Distillate Fuel Production and Demand in 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

7.1.2.1 2001 Distillate Demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

7.1.2.2 2001 Distillate Fuel Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-10

7.1.3 Distillate Fuel Production and Demand in 2014 . . . . . . . . . . . . . . . . . . . . . . . . . 7-18

7.1.3.1 Distillate Fuel Demand in 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-19

7.1.3.2 Future Distillate Fuel Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

7.1.4 Sensitivity Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-45

7.1.4.1 NRLM Regulated to 500 ppm Indefinitely . . . . . . . . . . . . . . . . . . . . . . . . 7-46

7.1.4.2 Proposed Rule - 500 ppm NRLM Cap in 2007; 15 ppm Nonroad Fuel Cap in

2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-47

7.1.4.3 Final NRLM Fuel Program With Nonroad Fuel Demand Derived from EIA

FOKS and AEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-49

7.1.5 Methodology for Annual Distillate Fuel Demand: 1996 to 2040 . . . . . . . . . . . . 7-62

7.1.6 Annual Distillate Fuel Demand and Sulfur Content . . . . . . . . . . . . . . . . . . . . . . 7-67

7.1.6.1 Sulfur Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-67

7.1.4.2 Distillate Fuel Demand and Sulfur Content by Year . . . . . . . . . . . . . . . . . 7-77

7.2 Refining Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-86

7.2.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-86

7.2.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-86

7.2.1.2 Basic Cost Inputs for Specific Desulfurization Technologies . . . . . . . . . . 7-87

7.2.1.3 Refinery-Specific Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-109

7.2.1.4 Summary of Cost Estimation Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-148

7.2.1.5 Projected Use of Advanced Desulfurization Technologies . . . . . . . . . . . 7-157

7.2.2 Refining Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-157

7.2.2.1 15 ppm Highway Diesel Fuel Program . . . . . . . . . . . . . . . . . . . . . . . . . . 7-158

7.2.2.2 Costs for Final Two Step Nonroad Program . . . . . . . . . . . . . . . . . . . . . . 7-159

7.2.2.3 Refining Costs for Sensitivity Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-168

7.2.2.4 Capital Investments by the Refining Industry . . . . . . . . . . . . . . . . . . . . . 7-174

7.2.2.5 Other Cost Estimates for Desulfurizing Highway Diesel Fuel . . . . . . . . 7-177

7.3 Cost of Lubricity Additives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-188

7.4 Cost of Distributing Non-Highway Diesel Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-189

7.4.1 New Production Segregation at Bulk Plants . . . . . . . . . . . . . . . . . . . . . . . . . . 7-190

7.4.2 Reduction in Fuel Volumetric Energy Content . . . . . . . . . . . . . . . . . . . . . . . . 7-192

7.4.3 Handling of Distillate Fuel Produced from Pipeline Interface . . . . . . . . . . . . . 7-194

7.4.4 Fuel Marker Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-200

7.4.5 Distribution and Marker Costs Under Alternative Sulfur Control Options . . . 7-205

7.5 Total Cost of Supplying NRLM Fuel Under the Two-Step Program . . . . . . . . . . . . 7-206

7.6 Potential Fuel Price Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-208
Estimated Costs of Low-Sulfur Fuels

7-1

CHAPTER 7: Estimated Costs of Low-Sulfur Fuels

This chapter presents the methodology and costs, and discusses the possible price impacts,

for supplying nonroad, locomotive and marine (NRLM) diesel fuel under the final two step

program. It also presents similar information for various sensitivity cases analyzed. Section 7.1

contains our analysis of the volume of NRLM diesel fuel and other distillate fuels which are

affected by this program. This section also presents our estimates of the sulfur levels of NRLM

diesel fuel and other fuels impacted, which is used in our emissions analysis. Section 7.2

discusses our methodology for estimating the refining costs. We present our refining cost

estimates for the final rule program as well as several sensitivity cases. We also compare our

cost estimates to other parties. Section 7.3 contains our estimate of the cost of adding lubricity

additive to NRLM diesel fuel. Section 7.4 presents our analysis of the cost of distributing diesel

fuel under this program. Section 7.5 contains a summary of the refining and distribution cost for

the final rule NRLM program. Section 7.6 discusses the potential price impacts of the final

NRLM program. 

Table 7-1 summarizes the number of refineries we estimate will be affected by the final

NRLM fuel program, as well as the total volume of NRLM fuel affected.

Table 7-1

Number of Refineries and Refining Costs for the Final NRLM Program

Year of

Program

500 ppm Fuel 15 ppm Fuel 

All Refineries Small

Refineries

All

Refineries

Small

Refineries

Number of Refineries Producing

500 or 15 ppm NRLM Diesel

Fuel

2007-2010 36a 000

2010-2012 26 13 32 2

2012-2014 15 13 47 2

2014-2020 0 0 63 15

Production Volume 

(Million gallons per year in 2014)

2007-2010 13,327 0 0 0

2010-2012 3,792 393 8,598 335

2012-2014 728 393 12,247 335

2014-2020 0 0 13,030 728

Table 2 summarizes the per gallon refining, distribution and lubricity additive costs during

the various phases of the final NRLM fuel program.
Final Regulatory Support Document

7-2

Table 7-2

Summary of Fuel Costs for NRLM Fuel Control Options (cents per gallon, $2002)

Option Specification Year Refining

Costs

(c/gal)

Distribution &

Additive Costs

(c/gal)

Total

Costs

(c/gal)

Final Rule 500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm NRLM 2010-12 2.7 0.6 3.3

500 ppm NRLM 2012-14 2.9 0.6 3.5

15 ppm Nonroad 2010-12 5.0 0.8 5.8

15 ppm NRLM 2012-14 5.6 0.8 6.4

15 ppm NRLM 2014+ 5.8 1.2 7.0

Table 7-3 and 7-4 summarize the potential price impacts of the final NRLM fuel program

during the initial 500 ppm phase (2007-2010) and the final 15 ppm phase (2014 and beyond). 

Due to the uncertainty in projecting price impacts from cost estimates, we develop three

potential price impacts to indicate the range of possible outcomes.

Table 7-3

Range of Possible Total Diesel Fuel Price Increases (cents per gallon)a

Lower Limit Mid-Range Estimate Upper Limit

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2007-2010)

PADDs 1 and 3 2.9 1.8 4.5

PADD 2 3.0 2.5 3.8

PADD 4 3.7 3.5 6.1

PADD 5 1.2 1.5 1.5

15 ppm Sulfur Cap: NRLM Fuel (fully implemented program: 2014 +)

PADDs 1 and 3 7.7 6.3 9.8

PADD 2 7.6 7.9 11.2

PADD 4 8.2 13.0 13.9

PADD 5 5.1 6.8 7.2

a

 At a wholesale price of approximately $1.00 per gallon, these values also represent the percentage increase in

diesel fuel price.

7.1 Production and Consumption of NRLM Diesel Fuel 

7.1.1 Overview

This subsection describes how we estimated the distillate fuel production and demand for

land-based nonroad engines, locomotives, and marine vessels that will be affected by the

requirements of this final rule. This analysis also estimates the volumes of the highway diesel
Estimated Costs of Low-Sulfur Fuels

A The term heating oil as used here represents fuel used for stationary source purposes including home heating

industrial boilers, and electrical generation. 

B

 There is also a No. 6 fuel, but this is usually considered a heavy fuel or heavy oil and not included in

“distillate.”

7-3

fuel and heating oilA pools which also affect or are affected by the final NRLM fuel program. 

Fuel production and demand are estimated for various geographic regions of interest. We begin

by estimating production and consumption of various distillate fuels in 2001. We then project

these volumes to 2014, which is the year in which we project per gallon costs. We selected

2014, as IRS guidelines allow refinery equipment to be depreciated over 15 years and 2014

represents the mid-point in the depreciation life of new hydrotreaters built for the 2007 500 ppm

NRLM fuel cap. NRLM fuel demand is projected to increase steadily in the future. As the

number of domestic refineries is not projected to increase, the economy of scale will gradually

improve over time. Selecting 2014 as the year in which to project per gallon fuel costs provides

a reasonable estimate of the average economies of scale which will exist with the hydrotreaters

constructed in response to the rule. 

These NRLM production and consumption estimates are developed for the final NRLM fuel

program, as well as for a number of alternative scenarios. We then develop a set of production

and consumption estimates for NRLM fuel for each year from 1996 to 2040, which are used to

estimate annual emission reductions (see Chapter 3) and fuel-related costs (Sections 7.2 through

7.5 below). Finally, we estimate how the final rule and the various alternative scenarios affect

the sulfur content of the various types of distillate fuel, which is again used to estimate annual

emission reductions associated with each of these scenarios. 

It is important early on in this discussion to define distillate fuel and how it is used. 

Distillate fuel is often split into three groups according to the range of temperatures at which the

hydrocarbons comprising the fuel boil (boiling range). No. 1 distillate fuel is the lightest fuel, or

has the lowest boiling range. Common No. 1 distillate fuels are jet fuel, No. 1 diesel fuel, and

kerosene (also known as No. 1 fuel oil). No. 2 distillate fuel is somewhat heavier and has a

higher boiling range, though there is significant overlap between No. 1 and No. 2 distillate fuels. 

No. 2 distillate fuels are usually excellent diesel fuels. Finally, No. 4 distillate fuel is the

heaviest of the three, having the highest boiling range.B

 No. 4 distillate fuel is generally a poor

diesel fuel and can only be used in slower speed diesel engines. This rule does not address the

sulfur content of No. 4 distillate fuel. Thus, we will not address No. 4 distillate fuels in this

analysis. All of these distillate fuels boil at higher temperatures than gasoline, though there is

some overlap between the heaviest compounds in gasoline and the lightest compounds in No. 1

distillates.

The vast majority of the fuel used in NRLM engines falls into the No. 2 distillate fuel

category. As will be seen below, a very small volume of No. 1 distillate fuel is used to fuel
Final Regulatory Support Document

C No. 1 distillate fuels is mostly consumed in jet engines and tends to cost more than No. 2 distillate fuels. 

Since diesel engines can burn either fuel, No. 2 distillates are their preferred choice.

D Some states, particularly those in the Northeast, limit the sulfur content of No. 2 fuel oil to 2000 - 3000 ppm.

7-4

NRLM engines.C Also No. 1 distillate fuel is often blended into No. 2 distillate fuels in the

winter in cold climates to avoid fuel gelling. Thus, we will address the impact of this rule on No.

1 distillate fuel in this analysis, though the primary focus will be on No. 2 distillate fuels.

The American Society of Testing and Materials (ASTM) defines three No. 2 distillate fuels:

1) low sulfur No. 2-D, 2) high sulfur No. 2-D, and 3) No. 2 fuel oil. Low sulfur No. 2-D fuel

must contain 500 ppm sulfur or less, have a minimum cetane number of 40, and have a minimum

cetane index limit of 40 (or a maximum aromatic content of 35 volume percent). These

specifications match those set by EPA for highway diesel fuel, so essentially these ASTM limits

are legal specifications. Per ASTM, both high sulfur No. 2-D and No. 2 fuel oil (heating oil)

must contain no more than 5000 ppm sulfur,D and currently averages about 3000 ppm. The

ASTM specifications for high sulfur No. 2-D fuel also include a minimum cetane number

specification of 40. The ASTM specifications for high sulfur No. 2-D and No. 2 fuel oil only

have the force of law in those states which have incorporated the ASTM standards in their state

laws or regulations. There are no federal standards currently for these two high sulfur fuel. 

We will break down No. 2-D distillate fuel into three fuels, according to the way we regulate

its quality: highway diesel fuel, NRLM diesel fuel, and heating oil. Operators of highway diesel

engines must use low sulfur highway diesel fuel engines, though the low sulfur fuel can be and is

used in other applications. As will be discussed further below, highway diesel fuel must

currently meet a 500 ppm sulfur cap. Starting in 2006, 80% of highway diesel fuel volume will

have to meet a 15 ppm cap, with 100% having to do so in 2010. NRLM diesel fuel is that fuel

used in nonroad, locomotive and marine diesel engines and is the fuel primarily affected by this

rule. Heating oil is all other No. 2 distillate fuel. It includes No. 2 fuel oil used in boilers,

furnaces and turbines. It also includes No. 2 diesel fuel used in stationary diesel engines (e.g.,

for electricity generation). Heating oil is not covered by the NRLM fuel standards, but is

affected because of limitations in the fuel distribution system.

We base our estimates of historical distillate fuel demand used in this analysis on EPA’s

Nonroad Model (NONROAD) and the Energy Information Administration’s (EIA) Fuel Oil and

Kerosene Sales (FOKS) report for 2001. NONROAD estimates diesel fuel consumption by the

land-based nonroad engines based on the sales, scrappage and use of nonroad engines. FOKS

contains detailed, comprehensive distillate fuel sales to highway vehicles and ten non-highway

sectors. We use FOKS to estimate the consumption of highway, marine, and locomotive diesel

fuel and heating oil, given the nonroad diesel fuel consumption from NONROAD. 

We base future demand for nonroad diesel fuel again on estimates from NONROAD. Future

demand for highway diesel fuel and the other non-highway sectors (locomotive, marine and

heating oil) is based on estimates from EIA’s Annual Energy Outlook (AEO) for 2002.
Estimated Costs of Low-Sulfur Fuels

E

 The increment of the final rule program to this regulatory scenario is the basis for our 500 ppm to 15 ppm

locomotive and marine incremental analysis. 

7-5

The methodology used for the final rule differs somewhat from that used in the NPRM. For

the NPRM, we used different methodologies to estimate distillate fuel demand for the purpose of

estimating emissions and for estimating fuel-related costs. For emissions, we used a

methodology very similar to that being used for this final rule. However, for fuel cost

estimation, we did not use NONROAD to estimate nonroad fuel consumption. We derived all of

our fuel consumption estimates from FOKS and AEO, although we projected future nonroad fuel

consumption with NONROAD. To avoid this inconsistency, we decided to utilize the same

methodology for both emission and cost estimation purposes. As discussed in Section 2.3.2.2 of

the Summary and Analysis document for this rule, we decided to use NONROAD to estimate

nonroad fuel consumption for both emission and cost estimation purposes. In addition, the

analysis for this final rule utilizes more recent information from FOKS 2001 and AEO 2002, as

opposed to FOKS 2000 and AEO 2001, which were used in the analysis for the NPRM. 

We estimate historic production of distillate fuel in these pools by starting with downstream

demand. We used Information from EIA’s Petroleum Supply Annual on the sales of highway

diesel fuel and high sulfur distillate from refinery racks and terminals. The volume of highway

diesel fuel supplied at terminals is compared to that consumed in highway vehicles to estimate

the percentage of highway fuel which is used in other applications. We call highway fuel used in

other applications “spillover.” We then adjust the terminal level supply of highway diesel fuel to

represent shifts in the volume of various fuels during distribution, particularly through pipelines. 

These shifts are referred to as “downgrades.” The result is an estimate of production needed by

refineries and importers to supply demand in the various sectors. 

The sulfur level of the various distillate fuels produced at refineries is primarily controlled by

applicable EPA standards. These of course vary depending on the regulatory scenario being

evaluated. We also consider the impact of the small refiner provisions, which usually allow the

sale of higher sulfur fuel into a particular market than would otherwise be the case. The

spillover of highway fuel into non-highway sectors also affects the sulfur content of these fuels,

as do the downgrades that occur during distribution. Our estimate of in-use sulfur levels of the

various distillate fuels begins with in-use survey data and then adjusts these levels for changes in

the sulfur content of fuel being produced, spillover and downgrades during distribution.

The two primary regulatory scenarios evaluated are: 1) a reference case, which assumes no

NRLM sulfur standards and 2) the final NRLM fuel program. In addition, we evaluate several

sensitivity cases:

- NRLM control only to 500 ppm in 2007 (no second step to 15 ppm),

- nonroad fuel control to 15 ppm in 2010, but keeping locomotive and marine (L&M) fuel at

500 ppm indefinitely (the proposal or NPRM case),E

 and
Final Regulatory Support Document

F

 The Department of Energy split up the nation into five districts, called Petroleum Allocation for Defense

Districts, or PADDs, during the 1970's. The regions primarily reflect where refineries get their crude oil.

7-6

- the final NPRM fuel program with the volume of nonroad diesel fuel derived from FOKS

and AEO 2003 instead of NONROAD. 

7.1.2 Distillate Fuel Production and Demand in 2001

This section describes our estimates of total production and demand by region for the various

distillate fuels. The primary regions of interest are the different refining districts called PADDs.F

There are five PADDs: 1) the East Coast, 2) the Midwest, 3) the Gulf Coast, 4) the Mountain

states and 5) the West Coast, Alaska and Hawaii. Because the Alaskan and Hawaiian fuel

markets are mostly distinct from the rest of PADD 5 and because California applies distinct

specifications to diesel fuel sold in that state, we split PADD 5 into four pieces: the states of

California, Hawaii and Alaska and the remainder of PADD 5. We will refer to this remainder of

PADD 5 as PADD 5-O (with “O” denoting “other” than the specific states listed). 

We begin with estimating the demand for each type distillate fuel, highway, NRLM and

heating oil. We then estimate how much highway fuel was supplied at the terminal level to

estimate spillover of highway fuel into the other sectors. Finally, we estimate downgrade of

higher quality fuels to lower quality fuels during distribution to back-calculate the volume of

each fuel produced by refineries. 

7.1.2.1 2001 Distillate Demand

We obtain our estimate of total distillate demand from EIA’s FOKS report for 2001.1 This

report presents results of a national statistical survey of approximately 4,700 fuel suppliers,

including refiners and large companies that sell distillate fuels for end use (rather than resale). 

The sample design involves classification of fuel suppliers based on sales volume with

subsamples in individual classes optimized to improve sample precision. Distillate fuels

surveyed that are relevant to this analysis include diesel and heating oils in grades No. 1, No. 2

and No. 4. The survey requests respondents to report estimates of fuel sold for eleven “end

uses” that correspond to broad economic sectors. These eleven sectors are highway, industrial,

off-highway (construction and other), farm, military, railroad, marine vessel, commercial,

residential, oil company and electric utility. Suppliers presumably determine the applicable

sector by the type of entity which purchases the fuel (e.g., farmers buy fuel for farming). FOKS

is therefore not a direct measure of how fuel is used, but a measure of who buys fuel. However,

for most of these sectors it should provide a reasonable estimate. The reader is referred to

Section 2.3.2.2 of the Summary and Analysis document for this rule for a more detailed

description of FOKS and the fuel user surveys which provide an independent assessment of its

accuracy. 

FOKS presents two sets of fuel demand estimates. The first, labeled unadjusted, includes

adjustments to reflect estimates of highway fuel use from the Federal Highway Administration. 
Estimated Costs of Low-Sulfur Fuels

G Since the volume of No. 4 distillate fuel is small compared to total distillate use, we did not attempt exclude

No. 4 distillate use from the 2001 FOKS estimate of total distillate demand. Because of the methodology used, any

incremental volume of No. 4 distillate fuel shows up as heating oil demand in Table 7.1.2-1.

7-7

The second, labeled adjusted, includes further adjustments to reflect distillate fuel use to

generate electricity and to match total distillate demand to total distillate fuel supply, as

estimated in EIA’s Petroleum Supply Annual (PSA). EIA’s PSA reports an aggregation of the

volumes of fuels sold by primary suppliers, which includes refinery racks and terminals. As the

PSA figures represent recorded sales from all primary suppliers, and not a survey of

representative suppliers, it is a more accurate estimate of total distillate fuel supply than the total

demand estimated in FOKS. Because of this, we use the adjusted FOKS demand estimates here. 

Thus, while we refer to total distillate fuel demand as being taken from FOKS, it is just as

accurate to say that it comes from PSA.

Of the eleven economic sectors evaluated by FOKS, we are interested primarily in three:

highway, railroad and marine vessels. Little fuel used in these sectors involves nonroad

equipment or heating oil. The remaining eight sectors all include significant portions of nonroad

fuel use and heating oil use. Because of this, we use the EPA NONROAD model to estimate

nonroad fuel use and assume that the remainder is heating oil. 

Table 7.1.2-1 shows total distillate fuel demand from the 2001 FOKS report, as well as total

demand for highway, railroad and marine fuel from this same report.G Nonroad diesel fuel

demand was taken from the draft NONROAD2004 model (see Chapter 3 for a detailed

description of this model). Heating oil demand was set so that the total fuel demand from the

five sectors equaled total fuel demand. 

Table 7.1.2-1

Total Distillate Demand in 2001 by Region (million gallons)

End Use

Region

1 2 3 4 5-O* AK HI CA

Highway 10,284 10,947 5,743 1,570 1,901 111 33 2,627

Railroad 506 1,051 883 223 100 4 0 183

Marine 461 318 1,153 0 23 67 20 52

Other

 

Nonroad

2,935 4,174 1,409 597 631 25 32 783

Heating

Oil

7,363 602 1,744 78 45 205 129 (41)

Total Demand 21,549 17,092 10,932 2,468 2,700 412 214 3,604

* Represents the states of AZ, NV, OR, and WA.

For this analysis, we made several small modifications to the fuel demand estimates shown in

2001 FOKS. We made one adjustment to the estimate of highway fuel demand. FHWA
Final Regulatory Support Document

7-8

estimates highway fuel demand based on fuel excise tax receipts. Individuals and businesses that

purchase highway fuel for off-highway use can request a refund of this excise tax on their income

tax forms. FHWA adjusts their estimates for these refund requests. However, it is possible that

not everyone who uses taxed, highway diesel fuel for non-highway use files for a refund. For

example, many businesses own fleets of both highway and nonroad equipment. Some owners or

operators, particularly rentals, might find it expedient or necessary to purchase at least some of

their nonroad diesel fuel at retail outlets such as gas stations, where high sulfur diesel fuel is

usually not available. It is plausible that some fraction of the fuel attributed by FHWA to

highway use is actually used for non-highway purposes. This fuel would likely be used by

construction and commercial nonroad equipment users, as they are the most likely to refuel their

nonroad engines at retail fuel outlets. 

To gain a better understanding of this issue, EPA provided a grant to the Northeast States for

Coordinated Air Use Management (NESCAUM) to conduct a survey of diesel fuel use in

construction equipment in New England.2

 The survey was designed to develop methods to

estimate emission inventories for construction equipment. The study area included two counties,

one in Massachusetts and one in Pennsylvania. Equipment owners in selected sectors were

targeted, including construction, equipment rental, wholesale trade, and government (local

highway departments). Surveyors administered a questionnaire requesting information about fuel

purchases and associated tax-credits. Owners reported quantities and proportions of high-sulfur

(dyed and untaxed) and low-sulfur (undyed and taxed) diesel fuel purchased over the previous

year. Owners who reported purchases of undyed diesel fuel for use in construction equipment

were also requested to indicate whether they applied for tax credits for which they were eligible

under state or federal law. The survey showed that approximately 20 percent of all diesel fuel

purchased for use in “construction” was undyed diesel fuel for which the purchaser had not

applied for a tax refund. 

To ensure that this type of adjustment was not already included in the FOKS estimates, we

confirmed with FHWA that they only subtract tax refunds from the total tax receipts from

highway diesel fuel sales.3, 4 In other words, they assume that all purchasers of taxed diesel fuel

for non-highway use request a refund. Similarly, we confirmed with EIA that they do not make a

similar type of adjustment.5

To estimate the volume of nonroad diesel fuel classified as highway fuel demand in FOKS,

we applied the results of the NESCAUM survey to the FOKS estimates of construction fuel

demand plus a portion of commercial fuel demand. As discussed in Section 7.1.3. below, fuel

demand in the commercial sector is broken out by the type of distillate purchased. One of these

fuel types is high sulfur diesel fuel, which we believe is primarily used in nonroad equipment. 

We believe that the results of the NESCAUM are equally applicable to these types of nonroad

equipment, as they tend to be used away from the business’ primary location (e.g., lawn and

garden equipment). However, because the survey only covered two counties, the results are not

necessarily representative of the entire U.S. Extrapolating the results to the entire U.S. is

therefore uncertain. Given that we lack any other estimate, we decided to use the results of the

NESCAUM survey with an ad hoc adjustment, where the percentage of unrefunded highway fuel

used is assumed to be 10%, as opposed to the surveyed 20%. 
Estimated Costs of Low-Sulfur Fuels

7-9

Table 7.1.2-2 shows the volume of construction and commercial, high sulfur diesel fuel, and

the portion believed to be made up from unrefunded highway fuel by region. We reduced the

total construction volume by 5% to not base our estimates of unrefunded fuel on that portion

which is estimated to be used as heating oil (see below). On a nationwide average, this

unrefunded highway fuel represents 0.7% of total highway fuel demand. As will be shown

below, we reduce the volume of highway fuel demand in each region by the volume shown in

Table 7.1.2-2. 

Table 7.1.2-2

Unrefunded Use of Taxed Highway Fuel in Nonroad Equipment in 2001 (million gallons)

Region

1 2 3 4 5-O HI AK CA

Total Construction* 550 602 448 124 87 4 7 264

Nonroad Portion (0.95) 523 572 425 118 83 3 7 251

Unrefunded Fuel (10%) 52 57 43 12 8 0.3 0.7 25

Commercial: #2 High Sulfur

Diesel Fuel *

203 155 71 8 19 2 21 3

Unrefunded Fuel (10%) 20 16 7 1 2 0.2 2 0.3

Total Unrefunded Fuel 73 73 50 13 10 1 3 25

* FOKS 2001

While we believe that this highway fuel is used in nonroad engines, we did not increase the

nonroad fuel demand shown in Table 7.1.1-1 above. This adjustment is not necessary since the

NONROAD model projects fuel use for the entire in-use nonroad equipment fleet and does not

consider where the fuel is purchased. As will be seen below, the result is that this reduction in

highway fuel demand causes an analogous increase in the demand for heating oil under our

methodology. 

We also made minor adjustments to the FOKS estimates for diesel fuel demand for

locomotive engines and marine vessels. Based on guidance from EIA staff, 5% of the fuel

purchased by railroads is heating oil, under our definitions described above.6

 Thus, we reduced

the railroad fuel demand from FOKS by 5%. We further reduced the railroad fuel demand by an

additional 1%, which represents fuel believed to be used in nonroad diesel engines in railyards

and which is already included in the nonroad fuel demand estimates from NONROAD.7 The

FOKS estimates of fuel demand for marine vessels were multiplied by 90%, to remove the use of

heating oil and No. 4 distillate fuel included in the FOKS estimates. Again, this was based on

guidance from EIA staff.8

Table 7.1.2-3 shows the FOKS and NONROAD estimates of distillate fuel demand, the

adjustments made and the final estimates. Only the revised estimate of heating oil demand is
Final Regulatory Support Document

7-10

shown, as this is simply back-calculated from the total demand for the other fuels and total

distillate demand. 

Table 7.1.2-3

Adjusted Distillate Demand by Region in 2001 (million gallons)

End Use

Region

1 2 3 4 5-O AK HI CA

FOKS Highway 10,284 10,947 5,743 1,570 1,901 111 33 2,627

Unrefunded fuel (0.7%) 73 73 50 13 10 3 1 25

Revised Highway 10,211 10,873 5,694 1,557 1,890 108 32 2602

FOKS Railroad 506 1,051 883 223 100 4 0 183

Revised Railroad 476 989 831 209 94 4 0 172

FOKS Marine 461 318 1,153 0 23 67 20 52

Revised Marine 415 286 1,037 0 20 60 18 46

Nonroad 2,935 4,174 1,409 597 631 25 32 783

Heating Oil 7,511 769 1,961 105 64 214 132 0

Total 21,549 17,092 10,932 2,468 2,700 412 214 3,604

7.1.2.2 2001 Distillate Fuel Production 

Refiners do not produce exactly the same volume of fuel which is consumed. This is

especially true for the specific categories of distillate fuel. The largest difference occurs with

highway diesel fuel. All fuel used in highway diesel engines must meet EPA’s 500 ppm sulfur

cap. Other distillate fuel does not. However, fuel meeting the highway diesel fuel specification

can be used in the other four categories. As is shown below, this occurs to a significant extent. 

We refer to this as spillover. Thus, the production of highway diesel fuel tends to be much larger

than is actually consumed in highway diesel engines. More importantly for this rule, the highway

fuel used in NRLM engines already meets the sulfur caps of the final NRLM fuel program. Thus,

this spillover fuel faces no new production or distribution costs due to this rule. 

Also, a certain amount of mixing occurs when fuel is shipped in pipelines, particularly at the

interface between fuel batches. The properties of this interface material are a blend of the

properties of the two distinct fuel batches. Generally, this interface material does not meet the

specification of one of the two fuels and is cut into the batch of the lower quality fuel. We refer

to the volume of the higher quality fuel that is lost to the lower quality fuel as downgrade. 

However, sometimes this interface does not meet the specifications of either fuel and has to be

segregated from both batches and reprocessed. This downgraded material is referred to as

transmix. 
Estimated Costs of Low-Sulfur Fuels

7-11

Downgrade can both increase and decrease the supply of distillate fuel relative to that which

was produced by refineries. We consider these changes in the supply various distillate fuels

below when estimating the cost of providing NRLM fuel meeting the final NRLM sulfur

standards. 

Spillover

Spillover is the volume of highway diesel fuel supplied which exceeds highway diesel fuel

demand and is thus used by off-highway users. We estimate spillover volume by subtracting

diesel fuel consumption by highway vehicles from the total supply of low-sulfur, highway fuel. 

We already estimated highway fuel consumption by highway engines (see Table 7.1.2-3 above). 

We obtain highway fuel supply to each region from EIA’s Petroleum Marketing Annual 2001.9

 It

should be noted that PMA estimates distillate fuel supply from primary suppliers, which are

primarily refinery racks and terminals. Thus, any downgrades occurring in pipelines have already

occurred. However, fuel sales by transmix processors are included in PMA. Thus, any distillate

fuel recovered from transmix processing is also included in PMA. Table 7.1.2-4 shows the

spillover volumes in each region based on the above information. 

Table 7.1.2-4

Highway Fuel Spillover in 2001 (million gallons)

1 2 3 4 5-O AK HI CA U.S.

Total Supply 10,596 12,549 6,532 2,067 2,206 111 45 3,568 37,674

Highway Engine Demand 10,211 10,873 5,694 1,557 1,890 108 32 2,602 32,967

Spillover 385 1,676 838 510 316 3 13 966 4,707

Information on the use of this spillover of highway fuel in the individual nonroad, locomotive,

marine, and heating oil markets does not exist. Therefore, we assume that this spillover

represents the same percentage of total demand for each fuel category within a region. Table

7.1.2-5 shows spillover, total non-highway distillate demand, and the percentage of spillover to

non-highway distillate demand by region.

Table 7.1.2-5

Spillover As Percentage of the Non-Highway Distillate Demand, 2001 (million gallons)

1 2 3 4 5-O AK HI CA

Spillover 385 1,676 838 510 316 3 13 9

Non-Highway

Distillate Demand

11,337 6,218 5,238 911 809 303 182 1,001

 Spillover (% of NonHighway Demand)3.4 26.9 16.0 55.9 38.9 1.0 7.1 100

As can be seen, the degree of spillover varies widely across the U.S. Spillover is very low in

Alaska and Hawaii, because of the absence of fuel product pipelines. Spillover is also very low in
Final Regulatory Support Document

7-12

PADD 1, because of its large demand for high sulfur heating oil. This large demand causes high

sulfur distillate to be available nearly everywhere, particularly in the northern portion of PADD 1. 

Thus, there is little reason for highway fuel to be used in non-highway applications. Spillover is

relatively high in PADD 4 due to the fact that several pipelines in the region do not carry high

sulfur distillate. Finally, spillover is very high in California, as that State requires the use of 500

ppm fuel in nonroad engines. 

The final issue is the distribution of this spillover into the four high sulfur distillate markets:

nonroad, locomotive, marine, and heating oil. Differences do exist in the way that these fuels are

typically shipped, particularly for locomotive and marine fuel. This could affect the relative

volume of spillover added to that market. However, data are not available which indicate any

difference in the distribution of spillover. Thus, except for the unrefunded use of highway fuel in

the construction and commercial sectors, we assume that the spillover is distributed into the four

high sulfur distillate markets in proportion to their total demand. Consistent with the way the

NESCAUM survey was conducted, we assume that the portion of spillover coming from

unrefunded use of highway fuel is all nonroad fuel demand.

Downgrade

When fuel is shipped through pipelines, the batch of one fuel flows immediately next to a

batch of another fuel. As the fuel flows through the pipeline, the two fuels start to mix at the

interface of the two batches. This interface takes on a character of its own and its properties are a

blend of the properties of the two fuels. The mixture is commonly called interface material or

simply interface. Depending on the properties of the two fuels and the stringency of the

specifications what each fuel must meet, this interface material can simply be cut in half and

blended into the two batches of fuel. In this case, there is no loss of volume in either batch. 

However, usually one of the two fuels is of higher quality than the other and the interface is

blended into the lower quality batch. In this case, the lower quality fuel gains volume, while the

higher quality fuel loses volume. This loss of volume is called downgrade. 

The loss of higher quality fuel volume through downgrade means that more of this fuel must

be produced than implied by demand. Likewise, the gain of lower quality fuel volume through

downgrade means that less of this fuel must be produced than implied by demand. The latter is

particularly important after the control of NRLM fuel sulfur content, as heating oil demand (a

sink for high sulfur downgrade) in some of the regions is quite limited. Also, the sulfur content of

downgrade will differ from that of fuels produced at refineries. Thus, the relative volume of

downgrade being sold in each fuel market will affect the average in-use sulfur content of that fuel

and the emission reductions resulting from this NRLM rule.

Figure 7.1-1 shows the order in which petroleum fuels are typically shipped through pipelines

today.10 Jet fuel is often “wrapped” with high sulfur distillate and highway diesel fuel. The sides

of the batches of high sulfur distillate and highway diesel fuel not adjacent to jet fuel are often

adjacent to gasoline of some type. The order of fuels can vary from pipeline to pipeline. 

However, the specific order will generally not affect the volumes and quality of downgrade

estimated here. According to our methodology, the size of the various interfaces are generally
Estimated Costs of Low-Sulfur Fuels

H The sulfur content of jet fuel often exceeds 500 ppm. However, adding a small volume jet fuel to highway

diesel fuel usually will not cause the sulfur content of the highway diesel fuel to exceed 500 ppm.

7-13

independent of the adjacent fuels and any distillate fuel lost to transmix is recovered by transmix

processors. The only difference might be the percentage of downgraded distillate which is able to

be sold to the 500 ppm highway fuel market versus the high sulfur distillate market. While this

breakdown affects current fuel supply, it is not an issue once diesel fuel must meet a 15 ppm cap.

HS

NRLM Diesel

and Heating Oil

Jet Fuel

Figure 7.1-1 Pipeline Sequence and Fate of 

the Interface Between Fuel Pipeline Batches in 2001

Transmix

+ 1.75% Jet 

cut into HS

Distillate Transmix Products

Distillate volume = 2.2% Hwy + 1/3 of gasoline in transmix

1/3 of gasoline in gasoline/HS transmix

Distillate quality: All > 500 ppm

500 ppm

Highway 

Gasoline

Diesel

Gasoline

+ 1.75% Jet 

Transmix cut into Hwy

1.75% Jet

2.2% Hwy

Gasoline in equal 

amounts

At the interface between these different fuels there is a mixing zone which results in the two

fuels contaminating each other. There are two different ways this mixed fuel between the two

fuels is dealt with by the pipeline companies. One way that pipeline companies deal with the

interface between the two fuels is to simply downgrade the mixture into the batch of fuel with the

lowest quality. Pipeline companies have informed us that the entire interface zone between jet

fuel and highway diesel fuel and also the interface zone between jet fuel and high sulfur distillate

is simply “cut” into the batches of highway diesel fuel and high sulfur distillate, respectively, by

timing their valve actions. This can occur because jet fuel would generally comply with the

specifications of the other two pools.H 

The second way to handle this interface occurs when the specifications governing the quality

of each fuel prevents the interface from being blended into either fuel. This always occurs

between a batch of gasoline and a batch of any distillate fuel. Even a small amount of gasoline

would cause diesel fuel to exceed its flashpoint limit. Similarly, a small amount of diesel fuel

would cause gasoline to exceed its endpoint limits. In this case, the interface is commonly

referred to as transmix. Transmix must be separated from either batch, is usually stored in a

transmix tank with other types of transmix, and then shipped to a transmix processor. The
Final Regulatory Support Document

7-14

physical characteristics of pipeline mixing indicate that the interface would generally contain

roughly even quantities of gasoline and distillate. We assume that this is the case here. 

The transmix processor distills the transmix to produce a reprocessed gasoline and distillate

fuel. However, there is some overlap between the lower temperature boiling components of

distillate, particularly jet fuel and the higher temperature boiling components of gasoline. The

lower temperature boiling components of distillate have a particularly low octane number. If any

significant quantity of distillate is mixed with the gasoline product, the cost of raising the octane

number to back to 87 or higher is economically prohibitive. Therefore, transmix processors

operate their distillation columns so that roughly one-third of the original gasoline contained in

the transmix leaves with distillate product. 

We are not concerned with the gasoline produced by transmix processors here. However, the

gasoline portion of the original transmix which enters the distillate pool in this fashion affects

both the volume and sulfur content of the distillate fuel pool and is, thus, relevant to this

discussion.

The distillate portion of current transmix can consist of highway diesel fuel, jet fuel and high

sulfur distillate, plus the heaviest components of gasoline. Because most pipelines carry high

sulfur distillate fuel currently and jet fuel often exceeds 500 ppm sulfur, and because most

facilities have only one tank for storing transmix from all interfaces, we assume that the distillate

produced from transmix is usually sold as high sulfur distillate. Thus, per Figure 7.1-1, the

highway diesel fuel portion of transmix is shifted to high sulfur distillate supply. 

The next step in our assessment of downgrade is to estimate its volume. The jet fuel

downgrade is easiest to estimate because, assuming the shipping order shown in Figure 7.1-1, it is

simply cut into each adjacent pool. We polled several pipeline companies to obtain an estimate

on the quantity of jet fuel downgraded today. Their estimates of the volume of jet fuel

downgraded during distribution ranged from 1% to 7%.11 We assumed that the national average

downgrade percentage was near the mid-point of this range, or 3.5%. Per Figure 7.1-1, half of

this volume is shifted to the highway fuel market and half is shifted to the high sulfur distillate

market. Table 7.1.2-6 shows this shift.
Estimated Costs of Low-Sulfur Fuels

7-15

Table 7.1.2-6

Types of Downgrade and Their Volumes in 2001

Interface Original

Fuel

Destination Volume

Jet Fuel

Interface

Jet Fuel Highway Diesel Fuel 1.75% of jet fuel demand

High Sulfur Distillate 1.75% of jet fuel demand

Gasoline -

High Sulfur

Distillate

Interface

High Sulfur

Distillate

High Sulfur Distillate Neutral

Gasoline High Sulfur Distillate Equivalent to 0.58% of jet fuel demand

Gasoline -

Highway

Diesel Fuel

Interface

Highway

Diesel 

High Sulfur Distillate 2.2% of highway diesel fuel supply

Gasoline High Sulfur Distillate Equivalent to 0.73% of highway diesel fuel supply

The other downgrades occur through the creation of transmix and its processing. Starting

with high sulfur distillate fuel, some of the volume of this fuel is lost to transmix. However,

transmix processors return all of the distillate portion of the original transmix to their distillate

product. As stated above, we assume that all the distillate produced by transmix processors

contains more than 500 ppm sulfur and is sold to the high sulfur distillate market. Thus, the

volume of high sulfur distillate which is lost to transmix is eventually returned to the high sulfur

distillate market by transmix processors. The result is no net loss or gain in the high sulfur

distillate market through its mixture with gasoline. This is shown in Table 7.1.2-6.

While the high sulfur distillate portion of this transmix returns to the fuel pool from which it

came, the gasoline which abuts high sulfur distillate in the pipeline does not all return to gasoline

supply. The heaviest portion of this gasoline moves from the gasoline market to the high sulfur

distillate market. We were not able to obtain a direct estimate of the volume of gasoline lost in

this manner or the volume of high sulfur distillate shifted to transmix. Thus, we estimate this

volume by comparing it to the volume of jet fuel moved to the high sulfur distillate pool. As

mentioned above, the mixing properties of all these fuels are fairly similar. They also have

flowed through the pipeline over the same distance (i.e., all these fuels are major products which

tend to flow the entire length of the pipeline). Thus, it is reasonable to assume that the interface

on either side of the batch of high sulfur distillate has the same volume. If 1.75% of jet fuel is

lost to high sulfur distillate on one side of the batch, then the same volume of high sulfur distillate

will be lost to transmix on the other side of the batch. Likewise, the same volume of gasoline will

be lost to this transmix through the interface with high sulfur distillate. The percentages of

gasoline and high sulfur distillate lost will not be the same as the size of the jet fuel, gasoline and

high sulfur distillate batches will likely differ, since their total demands vary widely. However,

the absolute volumes of jet fuel, gasoline and high sulfur distillate contributing to the interfaces

should be very similar. 
Final Regulatory Support Document

I

 When highway diesel fuel must meet a 15 ppm cap standard starting in 2006, we project that the amount of

downgrade will increase to protect the cleaner highway diesel fuel. We discuss this in the next section.

7-16

As mentioned above, two-thirds of the gasoline portion of transmix leaves the transmix

processor as naphtha and returns to the gasoline pool. However, the other one-third leaves as

distillate. As mentioned above, we assume that it does so as high sulfur distillate today. Thus, a

volume of gasoline equivalent to one-third of 1.75% of jet fuel demand (or 0.58% of jet fuel

demand) is shifted from gasoline to the high sulfur distillate fuel market. This is shown in Table

7.1.2-6. 

This leaves the downgrade of highway diesel fuel. In the Final RIA for the 2007 highway

diesel rule, we estimated that a clean cut on one side of highway diesel fuel batches would

downgrade 2.2% of the supply of highway diesel fuel.I

 We have applied this estimate in this

analysis, as well. In Figure 7.1-1, this 2.2% loss occurs via the creation of transmix with

gasoline. We assume that the volume of gasoline contributing to this transmix is the same, 2.2%

of highway diesel fuel supply. All of the highway diesel fuel leaves the transmix processor as

high sulfur distillate. One-third of the gasoline (equivalent to 0.73% of highway diesel fuel

supply) does so, as well. These downgrades are shown in Table 7.1.2-6.

The volumes of the various types of downgrade shown in Table 7.1.2-6 fall into two groups. 

The first are a function of jet fuel demand, while the second are a function of highway diesel fuel

supply. To simplify our calculations, we aggregated the volumes of these two types of

downgrades to create just two categories of downgrades, jet-based downgrade and highway fuelbased downgrade. Jet-based downgrade consists of the jet fuel lost to both the highway and high

sulfur distillate fuel supplies. It also includes the gasoline lost to the high sulfur distillate pool via

interface with high sulfur distillate fuel in the pipeline. In total, the jet-based downgrade

represents 4.08% of jet fuel demand. Of this 4.08%, 1.75% shifts to highway diesel fuel supply,

while 2.33% shifts to high sulfur distillate supply. Highway fuel-based downgrade consists of the

highway diesel fuel and gasoline which is shifted to high sulfur distillate supply via the interface

between highway diesel fuel and gasoline in the pipeline. This downgrade consists of 2.93% of

highway diesel fuel supply. 

The relative volumes of jet fuel demand and highway diesel fuel supply vary across the

various regions of the country being evaluated here. Thus, the relative volumes of the two types

of downgrade will vary, as well. Table 7.1.2-7 shows the demand for jet fuel and highway diesel

fuel, the volume of each type of downgrade and the portions of these downgrades shifted to

highway and high sulfur distillate fuel. Since the States of Alaska and Hawaii have no product

pipelines, we assumed no downgrade occurs there.
Estimated Costs of Low-Sulfur Fuels

7-17

Table 7.1.2-7

Downgrade Generation and Disposition in 2001 (Million gallons)

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK HI CA

Jet-Based Downgrade

Jet Fuel Demand (PMA) 4,585 3,776 6,095 562 1,580 1,014 325 3,772

Downgrade Loss 187 154 249 23 64 0 0 154

 To Highway Fuel 80 66 107 10 28 0 0 66

 To High Sulfur Fuel 107 88 142 13 37 0 0 88

Highway Fuel Based Downgrade

Highway Fuel Supply 10,596 12,549 6,532 2,067 2,206 111 45 3,568

Downgrade Loss 310 368 191 61 65 0 0 105

 Net Highway Fuel Loss* 233 276 144 45 49 0 0 78

 High Sulfur Fuel Gain 310 368 191 61 65 0 0 105

* The difference is due to downgrade from gasoline.

The final issue is how the new supply of high sulfur distillate is apportioned among the four

uses of high sulfur distillate fuel: nonroad, locomotive, marine, and heating oil. Data are not

available which indicate any difference in the final disposition of high sulfur distillate fuel

produced from transmix compared to that produced by refineries. Thus, we assume that the

spillover is equally distributed into the four non-highway distillate markets in proportion to their

demand. 

Production

Distillate fuel production must be sufficient to supply demand, considering changes in supply

during distribution. Since the net loss in highway fuel produced is 2.2%, highway fuel production

must be 2.2% higher than that indicated in EIA’s PMA for 2001. Likewise, the production of

high sulfur distillate fuel is lower than the estimate of supply from PMA, due to the addition of

some gasoline, jet fuel and highway diesel fuel. The balance of production, gains and losses

during distribution and final supply are shown in Table 7.1.2-8.
Final Regulatory Support Document

J

 In Chapter 8, we project the cost of replacing the hydrotreaters built in 2007. In doing so, we did not increase

the estimated refinery-specific production volumes to represent growth in NRLM fuel demand beyond 2022 (2007

plus the 15 year life of the equipment). This overestimates the cost of replacement equipment to a small extent. 

7-18

Table 7.1.2-8

 Distillate Production and Demand in 2001 (million gallons)

Fuel Use

Category

Fuel Type PADD AK HI US -

CA

CA US

1 2 3 4 5-O

Highway

Production 500 ppm 10,840 12,847 6,622 2,115 2,227 111 45 34,806 3,468 38,275

Spillover to Non-hwy -383 -1,656 -831 -504 -312 -3 -13 -3,701 -830 -4,532

Hwy Downgrade -327 -387 -202 -64 -68 0 0 -1,048 -95 -1,143

Jet Downgrade 81 69 105 10 43 0 0 309 59 368

Demand 10,211 10,873 5,694 1,557 1,890 108 32 30,366 2,602 32,968

Nonroad

Production HS 2,672 2,725 1,064 215 289 22 29 7,016 0 7,015

Hwy Spillover 151 1,130 255 332 245 3 3 2,118 675 2,787

Jet Downgrade 28 61 38 9 45 0 0 181 61 242

Hwy Downgrade 83 258 53 41 53 0 0 489 72 561

Demand 2,935 4,174 1,409 597 631 25 32 9,803 783 10,586

Locomotive

Production HS 445 658 651 77 44 4 0 1,878 0 1,879

Hwy Spillover 13 255 125 114 36 0 0 543 142 685

Jet Downgrade 5 15 22 3 7 0 0 51 14 65

Hwy Downgrade 14 62 32 15 8 0 0 131 17 148

Demand 476 989 831 209 94 4 0 2,604 172 2,776

Marine

Production HS 388 190 813 0 9 60 17 1,478 0 1,477

Hwy Spillover 11 74 156 0 8 0 1 250 38 288

Jet Downgrade 43 4 28 0 1 0 0 37 4 41

Hwy Downgrade 12 18 40 0 2 0 0 72 4 77

Demand 415 286 1,037 0 20 60 18 1,838 46 1,884

Heating

Oil 

Production HS 7,014 511 1,537 39 30 214 123 9,469 0 9,469

Hwy Spillover 207 198 295 57 24 0 9 791 0 791

Jet Downgrade 72 11 52 2 5 0 0 142 0 142

Hwy Downgrade 218 48 76 7 5 0 0 356 0 356

Demand 7,511 769 1,961 105 64 214 132 10,757 0 10,757

7.1.3 Distillate Fuel Production and Demand in 2014

As described in Section 7.2.1, we estimate the cost per gallon of desulfurizating NRLM fuel

using refinery specific production volumes indicative of 2014. This is the mid-point of the useful

life of hydrotreating equipment built in 2007, per IRS depreciation guidelines. Thus, using

production volumes from 2014 provides a reasonable estimate of the economies of scale of

hydrotreating expected to exist over the life of new equipment built in response to this rule.J

 As

was the case for 2001, we begin with estimating future demand, and then estimate the fuel

production necessary to satisfy this demand considering spillover and downgrades. 
Estimated Costs of Low-Sulfur Fuels

7-19

7.1.3.1 Distillate Fuel Demand in 2014

We derive our estimates of growth in highway, locomotive and marine fuel demand from

2001 to 2014 from EIA’s AEO for 2003.12 Table 7.1.3-1 shows the projected growth in demand

for these three fuels, as well as projected growth for jet fuel demand. The fuel demand in each of

these three categories in 2001 (shown in Table 7.1.2-8) were multiplied by the respective growth

factors to estimate fuel demand in 2014. This implicitly assumes that the same growth rate

applies in each region. 

Table 7.1.3-1

Projected Growth in Highway, Locomotive and Marine Fuel Demand: EIA 2003 AEO

Highway Locomotive Marine Jet Fuel

Demand in 2001 (trillion BTU) 5440 630 340 3960

Demand in 2014 (trillion BTU) 7840 710 390 2970

Growth Factor to 2014 1.44 1.13 1.14 1.34

Nonroad fuel demand in 2014 was estimated using the draft NONROAD2004 model, as was

done for 2001. Nonroad fuel demand in 2014 is estimated to be 14,379 million gallons per year,

which represents a 36% increase over 2001. 

We projected the growth in heating oil demand from information contained in the 2003 AEO

2003, along with our own estimates of the heating oil portion of each of the economic sectors

tracked in AEO. In its 2003 AEO, EIA projects the demand of petroleum fuels from 2001-2025

based on historical demand and econometric and engineering forecasts. AEO does not provide

forecasts for heating oil demand as we define it here. Thus, we estimate the heating oil portion

of the fuel demand in each economic sectors tracked in AEO. We then weighted the growth in

the fuel demand in each of the economic sectors by its contribution to total heating oil demand in

2001. Table 7.1.3.2 shows distillate fuel demand in each of the economic sectors tracked by

AEO. (Highway fuel use is not shown, since there is no heating oil use in this category.) The

estimates of demand were taken from the 2001 FOKS report. FOKS breaks down fuel use by fuel

type for several of the sectors. We believe that the use of distillate fuel varies depending on the

type of fuel being consumed (e.g., low sulfur diesel fuel, high sulfur diesel fuel, high sulfur fuel

oil) The FOKS breakdown allows us to apply distinct heating oil percentages to each sector and

fuel type combination. The information presented in Table 7.1.3-2 describes the process we used

to estimate the source of heating oil demand in 2001.
Final Regulatory Support Document

7-20

Table 7.1.3-2

Source of Heating Oil Demand: 2001

End Use Fuel Grade

Distillate Fuel Heating Oil

FOKS Volume 

 (1000 gal)

 Percent

Heating Oil

Volume 

(1000 gal)

Percent Heating

Oil Pool

Farm diesel 3,351 0 0 0

distillate 77 100 77 0.7

Construction distillate 2,086 5 104 0.9

Other/(Logging) distillate 428 5 21 0.2

Industrial No. 2 fuel oil 354 100 354 3.2

No. 4 distillate 44 100 44 0.4

No. 1 distillate 44 60 26 0.2

No. 2 low-S diesel 849 0 0 0

No. 2 high-S diesel 1,033 0 0 0

Commercial No. 2 fuel oil 1,546 100 1,546 14.1

No. 4 distillate 200 100 200 1.8

No. 1 distillate 63 80 50 0.5

No. 2 low-S diesel 1,212 0 0 0

No. 2 high-S diesel 483 0 0 0

Oil Company distillate 820 50 410 3.7

Military diesel 310 0 0 0

distillate 36 100 36 0.4

Electric Utility distillate 1,510 0 1,510 13.8

Railroad distillate 2,952 5 148 1.3

Vessel Bunkering distillate 2,093 10 209 1.9

On-Highway diesel 33,130 0 0 0

Residential No. 2 fuel oil 6,151 100 6,151 55.9

No. 1 distillate 112 100 112 1.0

Total 58,971 10,998 100

The key figures in Table 7.1.3-2 are the percentages of each economic sector and fuel type

combination which we believe falls into our definition of heating oil. These percentages were

derived using the same methodology which we use in Section 7.1.4 below to derive an estimate of

nonroad fuel demand from FOKS fuel demand estimates. The difference here is that we are not
Estimated Costs of Low-Sulfur Fuels

7-21

focused on nonroad fuel demand, but on heating oil demand. In most of the economic sectors

shown in Table 7.1.3-2, if the fuel is not nonroad fuel, it is heating oil. The exceptions to this are:

1) locomotive and marine vessel fuel, where the fuel that is not heating oil is locomotive or

marine fuel, respectively, and low sulfur diesel commercial fuel, which is highway fuel which is

not subject to highway fuel excise taxes (e.g., school buses). 

As shown in Table 7.1.3-2, we multiply the total fuel demand for that specific economic

sector and fuel type by its heating oil percentage to estimate the volume of heating oil demanded

in that sector-fuel type combination. We then divide that heating oil demand by total heating oil

demand to derive the percentage of total heating oil demand represented by that sector-fuel type

combination. The information presented in Table 7.1.3-3 describes the next step in this process. 

Table 7.1.3-3 shows the total distillate fuel demand in 2001 and 2014 from 2003 AEO and the

ratio of these fuel demand volumes. 

Table 7.1.3-3

Projected Growth in Heating Oil Demand: 2001 to 2014

Category 2001 Distillate

Demand *

2014 Distillate 

Demand *

Ratio of 2014 to 2001

Distillate Demand

Percent of Total

Heating Oil Demand

Farm 469 533 1.14 0.7

Construction 238 274 1.15 0.9

Logging/Other 55.6 59.9 1.08 0.2

Industrial 1,130 1,270 1.12 3.8

Commercial 460 490 1.07 16.4

Oil Company 6.2 0 0 3.7

Military 101 124 1.22 0.4

Electric Utility 170 90 0.70 13.8

Railroad 628 707 1.13 1.3

Vessel Bunkering 345 394 1.14 1.9

Residential 910 880 0.97 56.9

Weighted Ave. - - 0.93

* Trillion BTU from the 2003 AEO.

We weighted the growth in each sector’s distillate fuel demand by that sectors’ contribution to

2001 heating oil demand. For farm, industrial, commercial, residential and military, the

contributions of the various fuel types shown in Table 7.1.3-2 were combined for use in Table

7.1.3-3. The result is that heating oil demand is projected to shrink by 7% between 2001 and

2014. Thus, we multiplied the heating oil demand in each region shown in Table 7.1.2-8 by 0.93

to estimate heating oil demand in 2014. Table 7.1.3-4 shows the resulting distillate demands
Final Regulatory Support Document

7-22

projected for 2014 for the five fuel categories. Table 7.1.3-4 also shows jet fuel demand in 2014,

which represents a 34% increase over those shown in Table 7.1.2-7.

Table 7.1.3-4

Distillate Demand in 2014 (million gallons)

End Use

Region

1 2 3 4 5-O AK HI CA U.S.

Highway 14,722 15,676 8,210 2,245 2,725 157 46 3,752 47,533

Nonroad 3,987 5,670 1,914 810 857 34 43 1,064 14,379

Railroad 536 1,114 935 236 106 5 0 194 3,126

Marine 475 327 1,187 0 23 69 21 53 2,155

Heating Oil 6,970 714 1,820 98 59 199 122 0 9,982

Total No. 2

Distillate Demand 

26,690 23,501 14,066 3,389 3,770 464 232 5,063 77,175

Jet Fuel 6,143 5,060 9,313 753 2,117 1,359 436 5,054 30,235

7.1.3.2 Future Distillate Fuel Production

The primary purpose of projecting production of the various types of distillate fuel in 2014 is

to factor in appropriate economies of scale for the investment in new desulfurization equipment to

comply with the NRLM sulfur standards. We use 2014 production volumes to estimate these

costs for all of the steps of the final NRLM fuel program, because 2014 represents the mid-point

of the life of refinery equipment for the purposes of calculating annual depreciation under IRS

guidelines. The five steps for which production volumes were estimated are:

1) Reference Case (i.e., no NRLM Program),

2) Final NRLM fuel Program: 2007-2010,

3) Final NRLM fuel Program: 2010-2012, 

4) Final NRLM fuel Program: 2012-2014, and

5) Final NRLM fuel Program: 2014 and beyond

7.1.3.2.1 Reference Case; no NRLM Fuel Program 

There are two distinct periods which define the reference case which assumes that the NRLM

fuel program was not promulgated. One is during the period between 2007 and 2010 when the

highway diesel fuel program’s temporary compliance option is in effect. During this time,

consistent with the refiners’ pre-compliance reports under the highway fuel program, we assume

5% of highway diesel fuel will be produced at 500 ppm.13 The remainder will be 15 ppm fuel. 

The second period is after 2010 when the highway diesel fuel program’s temporary compliance
Estimated Costs of Low-Sulfur Fuels

K Our conclusion that California will not be affected by the NRLM program is based on our nationwide analysis

on how fuels are produced and distributed throughout the U.S. focusing on areas outside of California. It is possible

that California fuel production and distribution is different enough that some fuel would in fact be affected by this

rulemaking. 

7-23

option expires and all highway diesel fuel must meet a 15 ppm cap. During both of these periods,

NRLM fuel would continue to be high sulfur diesel fuel. 

California has implemented its own sulfur standards for highway and nonroad diesel fuel pool

starting in 2006. Thus, nonroad diesel fuel in California was assumed to already meet the 15 ppm

standard in the reference case. While California will not be regulating the locomotive and marine

diesel fuel quality as part of its regulation, our analysis shows that the locomotive and marine

diesel fuel demand will be met using spillover and the low sulfur diesel fuel downgrade once the

nonroad pool is regulated to 15 ppm. Therefore, EPA’s NRLM program is not expected to have

any impact on the production or distribution of locomotive and marine diesel fuel in that State.K 

We project the production volume of highway diesel fuel in 2014 using a slightly different

methodology than we used for 2001 production. For 2001, we started with supply and demand

and calculated spillover. Downgraded volume was then added to estimate total production. For

2014, we start with highway fuel demand, add the spillover of highway fuel into non-highway

fuel markets based on 2001 estimates, and add the volume of highway fuel which is downgraded

to lower quality fuel. 

The demand for highway diesel fuel was estimated in the previous section. Regarding

spillover, we assume that the same constraints in the distribution system which cause most

spillover to occur today will continue in the future. This means that the volume of highway fuel

spilling over into each of the four non-highway fuel markets will grow as each of these markets

grows. Thus, we have increased the spillover volumes shown in Table 7.1.2-5 for the nonroad,

locomotive, marine and heating oil markets by the 2001 to 2014 growth factors for these fuels

shown in Tables 7.1.3-1 and 7.1.3-3 (and a factor of 1.36 for nonroad fuel). The net effect of this

assumption is that the percentage of demand represented by spillover in each of the four nonhighway fuel markets is the same in 2014 as in 2001. Table 7.1.3-5 shows the demand for

highway fuel, spillover into each of the four non-highway fuel markets, and the resultant supply

of highway fuel needed to provide for this demand and spillover.
Final Regulatory Support Document

L

 Due to a miscalculation, the highway diesel fuel downgrade is estimated to be 4.5% instead of 4.4% for all

analyses after 2010. The overestimated highway downgrade volume overestimates the costs of the program. 

7-24

Table 7.1.3-5

Spillover of Highway Fuel in 2014 (million gallons)

End Use

Region

1 2 3 4 5-O AK HI CA

Highway Demand 14,722 15,676 8,210 2,245 2,725 157 46 3,752

Spillover

 Nonroad 206 1,535 345 451 333 4 4 1,054

 Railroad 15 287 141 129 40 0 0 0

 Marine 13 84 179 0 9 0 1 0

 Heating Oil 192 184 274 53 22 0 8 0

Total Spillover 425 2,090 939 633 404 4 13 1,298

Highway Supply 15,247 17,911 9,127 2,900 3,111 161 60 4,978

As mentioned above, the State of California has promulgated regulations requiring that

nonroad fuel meet a 15 ppm cap, as well as highway fuel, in 2006. We have categorized this 15

ppm nonroad fuel as highway fuel to better distinguish between 15 ppm fuel which would be

produced prior to this NRLM rule and that which will be produced because of this rule. Because

15 ppm nonroad fuel in California will be produced with or without this rule, we have classified it

as highway fuel in our presentation. Thus, any production of 15 ppm nonroad fuel shown below

will be due to this rule and not due to California regulations.

The next step is to estimate the volume of downgrade into and out of the various fuel supply

pools, as was done for 2001. In the Final RIA for the 2007 highway diesel rule, we projected that

the downgrade of 15 ppm highway diesel fuel would increase to 4.4% from the current estimated

level of 2.2%. Thus, we assume that 4.4%L of the supply of highway fuel shown in Table 7.1.3-5

will be downgraded to a lower quality distillate. 

The implementation of the 15 ppm highway fuel cap in 2006 could affect sequencing in some

pipelines. Most pipelines will simply replace their 500 ppm highway fuel with 15 ppm highway

fuel. However, some pipelines will continue to carry a 500 ppm highway fuel through mid-2010. 

In the Final RIA of the highway rule, we projected that roughly 40% of fuel markets would

include a 500 ppm fuel to distribute the roughly 20% of highway fuel which would be at 500

ppm. However, the highway pre-compliance reports indicate a much lower percentage of

highway fuel which likely be produced at 500 ppm. Because of this and for simplicity, we

assume that most pipelines would not carry 500 ppm highway fuel absent the NRLM rule. 

However, we believe that the sequencing of fuels in pipelines will still likely change from that
Estimated Costs of Low-Sulfur Fuels

7-25

shown in Figure 7.1.1. In particular, we believe that pipelines would not wrap 15 ppm highway

fuel with jet fuel and heating oil, but would wrap it with heating oil and gasoline, as shown in

Figure 7.1-2. With the sequence shown in Figure 7.1-1, the interface between jet fuel and 15 ppm

highway fuel could not be cut into either fuel, but would have to be segregated and added to the

heating oil storage tank. With the sequence in Figure 7.1-2, all of the distillate-distillate

interfaces can be cut into heating oil and the only interfaces requiring segregation and processing

are those containing gasoline and distillate, as is currently the case. 

Jet NRLM +

Heating Oil

15 ppm 

Highway Fuel Tier 2

Gasoline

Figure 7.1-2 Pipeline Sequence and Fate of Interface Between Fuel Batches 

in Areas that Carry Heating Oil; Prior to NRLM Rule: 2006+

Heating Oil 

Batch Swell Transmix + 1.75%

Jet

+ 2.2%

Hwy 1.75% Jet

2.2% Hwy

Gasoline in equal amounts

Transmix Products

Distillate volume = 1.75% Jet + 2.2% Hwy + 1/3 of gasoline in transmix

Distillate quality: <500 ppm

Jet

The change in sequencing affects the types of downgrade which will occur. Table 7.1.3-6

shows these downgrades and their volumes. Overall 3.5% of jet fuel volume is still downgraded

to the distillate market. In addition, gasoline volume equivalent to 0.58% of jet fuel demand and

0.73% of highway fuel supply will also be downgraded to the distillate market. The volume of

high sulfur distillate supplied should again not be affected. Only the volume of highway fuel

downgraded will increase, from 2.2% to 4.4% of total supply. We assume that the jet fuel and

highway diesel fuel interfaces with high sulfur distillate will be cut directly into the batch of high

sulfur distillate. Therefore, half of the jet fuel downgrade and half of the highway diesel fuel

downgrade will be cut directly into batches of high sulfur distillate. The remaining downgrades

are mixed with gasoline and sent to transmix processors, where distillate fuel is recovered and

sold. Due to the Tier 2 sulfur standards applicable to gasoline in 2004 and beyond and the 15

ppm highway diesel fuel cap, the sulfur content of distillate produced by transmix processors will

decrease dramatically. As described in Section 7.7 below, we estimate that the sulfur content of

distillate produced by transmix processors will be well below 500 ppm. The 500 ppm highway

diesel fuel market should command a price premium over high sulfur distillate fuel during this

timeframe. Therefore, we assume that this distillate will be sold to the 500 ppm highway diesel

fuel market. 
Final Regulatory Support Document

7-26

Table 7.1.3-6

Types of Downgrade and Their Volumes for the Reference Case: 2006-2010 

Interface Original

Fuel

Destination Volume

Jet Fuel- High Sulfur

Distillate Interface

High Sulfur

Distillate

High Sulfur Distillate Zero

Jet Fuel High Sulfur Distillate 1.75% of jet fuel demand

Gasoline - Jet Fuel

Interface

Jet Fuel 500 ppm Highway Fuel 1.75% of jet fuel demand

Gasoline 500 ppm Highway Fuel Equivalent to 0.58% of jet fuel demand

Highway Diesel FuelHigh Sulfur Distillate

Interface

High Sulfur

Distillate

High Sulfur Distillate Zero

Highway

Diesel Fuel

High Sulfur Distillate 2.2% of highway diesel fuel supply

Gasoline - Highway Diesel

Fuel Interface

Highway

Diesel 

500 ppm Highway Fuel 2.2% of highway diesel fuel supply

Gasoline 500 ppm Highway Fuel Equivalent to 0.73% of highway diesel

fuel supply

We obtained future demand for jet fuel from 2003 AEO. There, EIA projects a 34% increase

in jet fuel demand compared to demand in 2001. We applied this nationwide increase to the 2001

jet fuel demand by region shown in Table 7.1.2-7. The resultant 2014 jet fuel demand by region

is summarized in Table 7.1.3-7. 

Table 7.1.3-7

Downgrade Generation and Disposition for the Reference Case: 2006-2010 (Million gallons)

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK HI CA

 Jet-Based Downgrade

 Jet Fuel Demand (PMA) 6,144 5,060 8,167 753 2,117 1,359 435 5,054

 To High Sulfur Fuel 108 89 143 13 37 24 8 88

 To 500 ppm Fuel 143 118 190 18 49 32 10 118

 Total Downgrade 251 206 333 31 86 55 18 206

 Highway Fuel Based Downgrade

 Highway Fuel Supply 15,825 18,487 9,527 2,981 3,254 161 60 5,223

 To High Sulfur Fuel 348 407 210 66 72 4 1 115

 To 500 ppm Fuel 464 542 279 87 95 5 2 153

 Total Downgrade 812 948 489 153 167 8 3 268

The downgraded jet fuel and highway diesel fuel are cut directly into batches of high sulfur

distillate being carried in the pipeline. Therefore, it is reasonable to assume that this downgrade
Estimated Costs of Low-Sulfur Fuels

M Due to a miscalculation , the jet fuel downgrade is about 10 percent lower than if calculated as described. 

This error results in slightly overestimating the cost and the benefits of the program. This miscalculation occurred in

all the volume analyses prior to 2010. 

7-27

would be distributed just as the rest of the high sulfur distillate supply. Thus, we allocate this

downgrade to the four high sulfur distillate markets in proportion to the demand for each of these

fuels in each region. The final projections of production, spillover, downgrade and demand for

2006-2010 for the Reference Case which assumes no implementation of this NRLM rule are

shown in Table 7.1.3-8.

Table 7.1.3-8

Distillate Supply and Demand for the Reference Case: 2006-2010 (million gallons in 2014)M

Fuel Use

Category

Fuel Type PADD

AK HI US -

CA

CA US

1 2 3 4 5-O

Highway

Production 15 ppm 14,363 16,648 8,616 2,658 2,928 152 56 45,436 4,978 50,377

Production 500 ppm 866 1,213 532 219 200 8 4 3,029 0 3,066

Spillover to Non-hwy -425 -2090 -939 -633 -404 -4 -13 -4508 -1053 -5561

Hwy Downgrade -680 -724 -379 -104 -126 0 0 -2012 -173 -2185

Jet Downgrade to 500 ppm 126 90 137 11 52 0 0 416 0 416

15 ppm Hwy Downgrade to

500 ppm

453 452 235 62 73 0 0 1,276 0 1,276

Demand 15 ppm 13,306 14,169 7,420 2,029 2,463 149 44 39,580 3,752 43,332

Demand 500 ppm 1,416 1,508 790 216 262 8 2 4,201 0 4,201

Nonroad

Production HS 3,626 3,726 1,445 290 408 30 39 9,565 10 9,575

Hwy Spillover 206 1,535 345 450 333 4 3 2,877 1,054 3,930

Jet Downgrade to 500* 2 9 6 2 6 0 0 25 0 25

Hwy Downgrade to 500* 6 44 10 12 9 0 0 82 0 82

Jet Downgrade to HS 32 59 40 8 42 0 0 181 0 181

Hwy Downgrade to HS 115 297 68 47 59 0 0 586 0 586

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production HS 500 755 739 90 53 5 0 2,143 0 2,143

Hwy Spillover 14 287 141 128 40 0 0 611 0 611

Jet Downgrade to HS 5 12 20 2 5 0 0 45 144 189

Hwy Downgrade to HS 16 60 35 14 7 0 0 133 217 350

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production HS 443 222 938 0 12 69 20 1,704 0 1,704

Hwy Spillover 13 84 179 0 9 0 1 287 0 287

Jet Downgrade to HS 4 3 26 0 1 0 0 35 46 81

Hwy Downgrade to HS 15 18 44 0 2 0 0 78 59 137

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil

Production HS 6,514 484 1,440 37 30 199 114 8,819 0 8,819

Hwy Spillover 191 184 274 53 22 0 8 734 0 734

Jet Downgrade to HS 57 8 39 1 3 0 0 108 0 108

Hwy Downgrade HS 206 38 67 6 4 0 0 321 0 321

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

* Highway and jet downgrade to 500 ppm spillover pool. This is not shown for other PADDs.
Final Regulatory Support Document

7-28

In 2010, the temporary compliance option of the highway program ends. Therefore, there

would not be any 500 ppm highway fuel, only 15 ppm highway fuel and high sulfur distillate. 

The pipeline sequence shown in Figure 7.1-2 applies. All of the downgrade volumes shown in

Table 7.1.3-6 would still apply. No downgraded distillate fuel would meet a 15 ppm cap. 

Therefore, all the downgraded distillate would be shifted to the high sulfur distillate market. As

for 2006-2010, we assume that this downgrade is distributed to the four high sulfur distillate

markets in proportion to the demand for each fuel in each region. The projections of production,

spillover, downgrade and demand for 2010 and beyond for the Reference Case which assumes no

implementation of this NRLM rule are shown in Table 7.1.3-9.

Table 7.1.3-9

Distillate Supply and Demand for the Reference Case: 2010+ (million gallons in 2014)

Fuel Use

Category

Fuel Type PADD

AK HI US -

CA

CA US

1 2 3 4 5-O

Highway

Production 15 15,825 18,487 9,527 2,981 3,254 161 60 50,294 5,223 55,517

Spillover to Non- -425 -2,090 -939 -633 -404 -4 -13 -4,508 -1,053 -5,561

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production HS 3,401 3,235 1,275 221 242 30 39 8,443 10 8,453

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 1,054 3,930

Jet Downgrade 108 199 133 28 142 0 0 610 0 610

Hwy Downgrade 272 702 160 111 140 0 0 1,385 0 1,385

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production HS 469 647 646 66 30 5 0 1,863 0 1,863

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 15 40 69 8 18 0 0 150 144 294

Hwy Downgrade 38 140 81 33 18 0 0 310 217 527

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production HS 416 190 820 0 7 69 20 1,521 0 1,521

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 13 12 86 0 4 0 0 114 46 161

Hwy Downgrade 33 41 103 0 4 0 0 181 59 241

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil 

Production HS 6,097 414 1,257 27 17 199 114 8,125 0 8,125

Hwy Spillover 192 184 274 53 22 0 8 734 0 734

Jet Downgrade 194 25 131 3 10 0 0 364 0 364

Hwy Downgrade 488 90 158 14 10 0 0 759 0 759

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

7.1.3.2.2 Final NRLM Fuel Program: 2007-2010
Estimated Costs of Low-Sulfur Fuels

7-29

Demand for the various categories of distillate fuel are assumed to not change under the final

NRLM fuel program. Therefore, the fuel demand estimates shown in Table 7.1.3-5 apply to this

scenario, as well as prior to the NRLM rule. We also assume that spillover will not be affected by

the NRLM rule, because spillover occurs where only one fuel is available and this fuel will still

be 15 ppm highway fuel. Thus, the production of highway fuel and the spillover of this fuel to

the NRLM and heating oil markets will be the same as shown in Tables 7.1.3-5 and 7.1.3-8.

With the initiation of the NRLM fuel program in 2007, 500 ppm NRLM fuel will be widely

distributed and available. Thus, pipeline sequencing will be affected. While most 500 ppm fuel

is likely to be NRLM fuel, the widespread distribution of 500 ppm NRLM fuel will also facilitate

the distribute of 500 ppm highway fuel. In areas with relatively small heating oil markets, such as

PADDs 2 and 4 and California, we assume that the heating oil volume will be too small to justify

pipelines handling a separate high sulfur distillate fuel for this market. Thus, 500 ppm NRLM

fuel will replace high sulfur distillate in the common carrier distribution systems in these regions. 

Generally, this means that most heating oil in these regions will meet a 500 ppm cap.

Outside of PADDs 2 and 4, we believe that the heating oil market is either sufficiently large

or the distribution system is sufficiently flexible to allow the distribution of high sulfur distillate

fuel to this market. The pipelines in PADD 1 are expected to carry heating oil for the large

market there, and PADD 3 pipelines are expected to carry heating oil, in part, to supply the

PADD 1 market. The heating oil market in the Pacific Northwest is not large. However, this area

has a fairly simple distribution system and much of this heating oil consumption is believed to be

on the coast. Thus, we believe that it would be feasible for a refiner to produce and distribute

high sulfur distillate fuel to this market, though this distribution will not likely be by pipeline. 

The same is true for Hawaii. Table 7.1.3-10a summarizes these assumptions for the various

regions.

Table 7.1.3-10a

Production and Distribution of High Sulfur Distillate: Final NRLM Rule: 2007-2010

PADDs 1&3 PADDs 2 & 4 PADD 5-O AK and HI CA

High Sulfur Distillate in Pipelines Yes No No No pipelines No

High Sulfur Distillate Produced for

Heating Oil Market

Yes No Yes Yes No

Figures 7.1-3 depicts pipeline sequencing with 500 ppm NRLM fuel and heating oil both

being carried. As shown in Table 7.1.3-10, this applies to pipelines in PADDs 1 and 3.
Final Regulatory Support Document

7-30

Jet High Sulfur

Distillate

15 ppm 

Highway

Tier 2 

Gasoline

Figure 7.1-3 Pipeline Sequence and Fate of the Interface Between Fuel

Batches in Areas that Carry Heating Oil; After NRLM Rule: 2007 - 2010

Transmix

+ 1.75%

Jet

+ 2.2%

15 Hwy

1.75% Jet

2.2% Hwy

Transmix Products Gasoline in equal amounts

Distillate volume = 1.75% Jet + 2.2% Hwy + 1/3 of gasoline in transmix

Distillate quality: < 500 ppm

Jet

500 ppm 

Hwy & 

NRLM

+ 2.2%

500 Hwy

In this case, 15 ppm highway diesel fuel is downgraded directly to batches of 500 ppm fuel in the

pipeline. A similar volume of 500 ppm fuel will be downgraded to high sulfur heating oil. Thus,

there will be essentially no net loss of 500 ppm fuel from its batch during distribution. The loss of

15 ppm highway fuel is essentially shifted to high sulfur distillate. The interfaces containing

gasoline and distillate are not affected, relative to that occurring prior to the NRLM rule. Thus,

the net downgrade of 15 ppm highway diesel fuel, jet fuel and heavy gasoline is the same as that

prior to the NRLM rule during this timeframe. The distillate fuel produced from transmix should

still contain less than 500 ppm sulfur and can be sold to either the highway or NRLM fuel market. 

We generally presumed that this fuel would be sold to the highway fuel market, given the higher

prices likely to exist there. However, under the designate and track provisions of the final NRLM

rule, the total volume of highway fuel cannot increase during shipment. Thus, the net loss of 15

ppm highway fuel to the high sulfur distillate market must be greater than the increase in 500 ppm

highway fuel from transmix distillate. Therefore, we limited the volume of transmix distillate

shifted to the 500 ppm highway fuel market to the volume of 15 ppm highway fuel lost. Any

remaining 500 ppm fuel produced from transmix was sent to the 500 ppm NRLM market. A

detailed description of these downgrades and their volumes is shown in Table 7.1.3-10.
Estimated Costs of Low-Sulfur Fuels

7-31

Table 7.1.3-10

Types of Downgrade and Their Volumes Under the NRLM Rule: 2007-2010

Pipelines Carrying Both 500 ppm NRLM Fuel and High Sulfur Distillate (PADDs 1 and 3)

Interface Original Fuel Destination Volume

Jet Fuel- High Sulfur

Distillate Interface

High Sulfur

Distillate

High Sulfur Distillate Zero

Jet Fuel High Sulfur Distillate 1.75% of jet fuel demand

Gasoline - Jet Fuel

Interface

Jet Fuel 500 ppm Highway Fuel 1.75% of jet fuel demand

Gasoline 500 ppm Highway Fuel Equivalent to 0.58% of jet fuel

demand

Highway Diesel Fuel500 ppm NRLM Fuel

Interface

Highway Diesel

Fuel

500 ppm NRLM Fuel 2.2% of highway diesel fuel supply

500 ppm NRLM Fuel

- High Sulfur

Distillate Interface

500 ppm NRLM

Fuel 

High Sulfur Distillate 2.2% of highway diesel fuel supply

Gasoline - Highway

Diesel Fuel Interface

Highway Diesel 500 ppm Highway Fuel 2.2% of highway diesel fuel supply

Gasoline 500 ppm Highway Fuel Equivalent to 0.73% of highway diesel

fuel supply

Figure 7.1-4 depicts pipeline sequencing in systems that no longer carry high sulfur heating

oil. This applies to pipelines in PADDs 2, 4 and 5.

Jet 500 ppm Hwy 

& NRLM

15 ppm 

Highway

Tier 2

Gasoline

Figure 7.1-4 Pipeline Sequence and Fate of the Interface Between Batches 

in Areas that do not Carry Heating Oil; After NRLM Rule: 2007 - 2010 

Transmix + 1.75%

Jet

+ 2.2%

Hwy

1.75% Jet

2.2% Hwy

Transmix Products Gasoline in equal amounts

Distillate volume = 1.75% Jet + 2.2% Hwy + 1/3 of gasoline in transmix

Distillate quality: < 500 ppm

Jet
Final Regulatory Support Document

7-32

The absence of high sulfur distillate in the pipeline affects the types of downgrade occurring. 

Both downgraded 15 ppm highway diesel fuel and jet fuel are cut directly into batches of 500

ppm fuel in the pipeline. The interfaces containing gasoline and distillate are not affected by the

NRLM rule during this timeframe. As discussed in Section 7.1.6, the sulfur level of the distillate

produced by transmix operators is estimated to be less than 500 ppm. 

We made different assumptions regarding the disposition of this downgrade in the four

applicable regions due to varying circumstances existing in each one. Because of the small size

of the heating oil market in PADDs 2 and 4 (see Table 7.1.3-8), we assume that refiners will not

produce high sulfur distillate fuel for the heating oil market. Thus, in these areas, we assume that

this downgraded distillate will preferentially fulfill remaining heating oil demand. This might

entail some additional distribution costs to reach all heating oil users, but no sulfur content testing

would be required. If the volume of downgrade exceeded heating oil demand in these areas, we

assumed that the downgrade would then be used in the 500 ppm highway fuel market, up to the

volume of 15 ppm highway fuel lost during distribution(due to designate and track limitations). 

Any remaining downgrade distillate was assumed to be used as 500 ppm NRLM fuel, in

proportion to each region’s demand for nonroad, locomotive and marine fuel. 

In California, we also assumed that refiners would not produce high sulfur distillate fuel for

the heating oil market. However, California’s regulations require that all highway and nonroad

fuel meet a 15 ppm cap in this timeframe. Also, we project essentially no demand for heating oil

in California. Thus, all downgrade distillate was assumed to be used in the L&M markets, in

proportion to the demand for each fuel.

Finally, in PADD 5-O, we assumed that refiners could produce high sulfur distillate for the

heating oil market, but that this would not be shipped inland in pipelines. Therefore, we assumed

that the downgrade distillate would not be used to fulfill heating oil demand, but would be used as

500 ppm highway fuel up to the point allowed by the designate and track procedures. The

remainder would then be used as 500 ppm NRLM fuel, in proportion to the region’s demand for

nonroad, locomotive and marine fuel. Table 7.1.3-11 summarizes these priorities of downgrade

use in PADDs 2, 4, and 5 from 2007 - 2010 uncer the fuel rule provisions.

Table 7.1.3-11

Use of Distillate Downgrade by Region: Final NRLM Rule: 2007 to 2010

PADD 2 PADD 4 PADD 5-O CA

1st Priority HO HO 500 ppm Highway * L&M

2nd Priority 500 ppm Highway * 500 ppm Highway * 500 ppm NRLM -

3rd Priority 500 ppm NRLM 500 ppm NRLM - -

* Volume limited by loss of 15 ppm highway fuel
Estimated Costs of Low-Sulfur Fuels

N The final NRLM rule includes an Northeast/Mid-Atlantic Area within which no high sulfur NRLM fuel can

be sold. This area covers the most of the Northeast and Middle Atlantic states. Thus, it might be difficult for the

levels of small refiner fuel assumed here to be sold in PADD 1 under these provisions. If this were the case, this

small refiner fuel would likely stay in PADD 3. The net result would be that the sulfur content of NRLM fuel in

PADD 1 would decrease and that in PADD 3 would increase. The net nationwide impact would be negligible.

7-33

Table 7.1.3-12 shows the sources of downgrades and their volumes.

Table 7.1.3-12

Types of Downgrade and Their Volumes Under the NRLM Rule: 2007-2010 

Pipelines Not Carrying High Sulfur Distillate (PADDs 2, 4, 5-O, California)

Original Fuel Quality of Downgrade * Volume

Jet Fuel- 500 ppm

Diesel Fuel

Jet Fuel 500 ppm Diesel Fuel 1.75% of jet fuel demand

Gasoline - Jet Fuel

Interface

Jet Fuel 500 ppm Diesel Fuel 1.75% of jet fuel demand

Gasoline 500 ppm Diesel Fuel Equivalent to 0.58% of jet fuel

demand

15 ppm Highway

Diesel Fuel- 500 ppm

Diesel Fuel Interface

Highway

Diesel Fuel

500 ppm Diesel Fuel 2.2% of highway diesel fuel supply

Gasoline - Highway

Diesel Fuel Interface

Highway

Diesel 

500 ppm Diesel Fuel 2.2% of highway diesel fuel supply

Gasoline 500 ppm Diesel Fuel Equivalent to 0.73% of highway diesel

fuel supply

* Destination of the new 500 ppm diesel fuel varies by region.

One last effect of the NRLM rule during the 2007-2010 timeframe is the provision for small

refiners to be able to sell high sulfur distillate fuel to the NRLM market. If a small refiner

chooses to produce 500 ppm NRLM fuel, then they can sell credits to other refiners, which allows

them to produce and market high sulfur NRLM fuel. In either case, the volume of fuel potentially

affected by this provision is the production of high sulfur distillate fuel by small refiners. The

production of both highway fuel and high sulfur distillate by small refiners is addressed in Section

7.2.1. Since so much of the fuel produced in PADD 3 is distributed to PADD 1, we spread the

volume of PADD 3 small refiner fuel over the two PADDs in proportion to the demand for

NRLM fuel in the two PADDs.N Within each PADD we assume that the high sulfur, small refiner

NRLM fuel is blended into the nonroad, locomotive and marine markets in proportion to the

demand in each market. The volume of small refiner fuel is summarized in Table 7.1.3-13.
Final Regulatory Support Document

7-34

Table 7.1.3-13

Small Refiner NRLM Fuel: 2007-2010 (million gallons)

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK HI CA

420 140 291 0 60 104 0 0

The final projections of production, spillover, downgrade and demand under the final NRLM

fuel program from 2007-2010 are shown in Table 7.1.3-14.
Estimated Costs of Low-Sulfur Fuels

O Due to a miscalculation , the jet fuel downgrade is about 10 percent lower than if calculated as described. This

error results in slightly overestimating the costs and the benefits of the program. This miscalculation occurred in all

the volume analyses prior to 2010.

7-35

Table 7.1.3-14

Distillate Supply and Demand: Final Rule: 2007-2010 (million gallons in 2014)O

Fuel Use

Category

Fuel Type PADD

AK HI

US -

CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 14,363 16,648 8,616 2,658 2,928 152 56 45,436 4,760 50,196

Production 500 ppm 866 1,213 532 219 200 8 4 3,029 0 3,029

Spillover to Non-Hwy -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Dwngr 15 ppm -678 -714 -375 -101 -124 0 0 -1,991 -173 -2,164

Jet Downgrade 130 107 139 15 52 0 0 437 0 437

Hwy Downgrade 466 542 239 85 73 0 0 1,378 0 1,378

Demand 15 ppm 13,284 13,986 7,357 1,973 2,427 148 44 39,219 3,752 42,971

Demand 500 ppm 1,438 1,690 853 271 299 8 3 4,562 0 4,562

Nonroad

Production 500 ppm 3,448 4,025 1,402 329 330 0 39 9,573 10 9,584

Small Refiner Fuel 333 111 135 0 52 30 0 661 0 661

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 835 3,712

Jet Downgrade 0 0 11 5 59 0 0 75 0 75

Hwy Downgrade 0 0 19 26 83 0 0 129 0 129

Reproc. Downgrade 0 0 0 0 0 0 0 0 219 219

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Loco

motive

Production 500 ppm 476 805 710 98 41 0 0 2,130 0 2,130

Small Refiner Fuel 46 22 69 0 7 5 0 148 0 148

Hwy Spillover 15 287 141 129 40 0 0 611 0 612

Jet Downgrade 0 0 6 1 7 0 0 15 141 159

Hwy Downgrade 0 0 10 8 10 0 0 28 213 245

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500 ppm 421 236 901 0 9 0 20 1,588 0 1,588

Small Refiner Fuel 41 7 87 0 1 69 0 205 0 205

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 0 0 7 0 2 0 0 9 46 55

Hwy Downgrade 0 0 13 0 2 0 0 15 59 74

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil

Production HS 6,329 0 1,210 0 37 199 115 7,888 0 7,888

Hwy Spillover 192 184 274 53 22 0 8 734 0 734

Jet Downgrade 98 88 124 7 0 0 0 316 0 316

Hwy Downgrade 351 442 212 38 0 0 0 1,043 0 1,043

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981
Final Regulatory Support Document

7-36

7.1.3.2.3 Final Rule Program - 2010 to 2012

Beginning in mid-2010, two regulatory requirements change: 1) the temporary compliance

option under the highway fuel program ends and all highway fuel must meet a 15 ppm cap and 2)

nonroad fuel must meet a 15 ppm cap (L&M fuel continues to meet a 500 ppm cap). However,

downgraded 500 ppm fuel produced during shipment of 15 ppm highway diesel fuel and jet fuel

(or produced by small refiners or with small refiner credits) can continue to be sold to the NRLM

fuel markets outside of the Northeast/Mid-Atlantic Area. Within the Northeast/Mid-Atlantic

Area, downgraded 500 ppm fuel produced during shipment of 15 ppm fuel and jet fuel can only

be sold to the L&M fuel market. 

As was the case from 2007-2010, the demand for each distillate fuel and the spillover of

highway fuel into these markets are assumed to remain unchanged from those occurring prior to

the NRLM rule (see Table 7.1.3-5). With the application of the 15 ppm cap on nonroad fuel in

2010, 500 ppm fuel is not likely to be widely distributed through pipelines. Thus, pipeline

sequencing will again be affected. All pipelines will continue to carry 15 ppm fuel, now for both

the highway and NRLM markets. Pipelines serving PADD 1 will continue to carry high sulfur

distillate for the heating oil market. However, due to the small size of the heating oil markets

elsewhere (or the lack of pipelines, as in Alaska and Hawaii), we do not expect that pipelines

other than those serving PADD 1 will carry high sulfur distillate. While some pipelines are likely

to carry some 500 ppm L&M or small refiner fuel, this is likely to be in proprietary shipments and

not as a fungible product. Thus, in assessing pipeline sequencing, we assume that no 500 ppm

fuel will be regularly present. 

Figure 7.1-5 shows the pipeline sequence for the pipelines in PADDs 1 and 3 which are

expected to carry high sulfur heating oil in the 2010-2012 timeframe (applies to the period 2012 -

2014 period as well). 
Estimated Costs of Low-Sulfur Fuels

7-37

Jet Heating Oil

15 ppm 

Highway and 

NRLM Fuel

Tier 2

Gasoline

Figure 7.1-5 Pipeline Sequence and Fate of Interface Between Fuel Batches 

in Areas that Carry Heating Oil; After NRLM Rule: 2010-2012

Heating Oil 

Batch Swell Transmix + 1.75%

Jet

+ 2.2%

Hwy 1.75% Jet

2.2% Hwy

Gasoline in equal amounts

Transmix Products

Distillate volume = 1.75% Jet + 2.2% Hwy + 1/3 of gasoline in transmix

Distillate quality: <500 ppm

Jet

The primary difference between the sequencing in these pipelines in 2010-2012 and 2007-

2010 is the elimination of 500 ppm fuel. However, as discussed in Section 7.1.3.2.2, there was no

net gain or loss in the size of the 500 ppm batch, as it gained fuel from the adjacent batch of 15

ppm fuel and lost the same volume of 500 ppm fuel to the adjacent batch of high sulfur heating

oil. Now, in the absence of the 500 ppm batch, the loss of 15 ppm fuel is cut directly to the

heating oil batch in 2010-2012. The quality of the distillate produced from transmix is also the

same as in 2007-2010. Thus, the volumes and quality of distillate downgrades remain unchanged

from 2007-2010.

The destination of these downgrades changes, however, due to the elimination of the 500 ppm

highway fuel market. The downgrades of jet fuel and 15 ppm fuel which are cut directly into the

heating oil batch still go directly to the heating oil market. The 500 ppm downgrade material

produced from transmix now is assumed to be used in only the NRLM markets, in proportion to

the demand for nonroad, locomotive and marine fuel in PADD 3. In most of PADD 1, the

Northeast/Mid-Atlantic Area provisions of the final rule prohibit the use of 500 ppm fuel in the

nonroad market. As the volume of downgrade produced from transmix in PADD 1 was

significantly less than L&M fuel demand, we assumed that all of the distillate produced from

transmix in PADD 1 was used in the L&M fuel market from 2010-2012. 

It should be noted that we continue to assume that 4.4% of highway diesel fuel supply will be

downgraded to protect the quality of 15 ppm diesel fuel. We do not apply the 4.4% downgrade to

the new volume of 15 ppm NRLM diesel fuel supply, because the new 15 ppm NRLM fuel is

assumed to simply increase the size of the existing batches of 15 ppm highway diesel fuel and not

increase the number of interfaces created. 
Final Regulatory Support Document

7-38

Figure 7.1-6 shows the pipeline sequence for the pipelines in PADDs 2, 4 and 5 which are not

expected to carry high sulfur heating oil in the 2010-2012 timeframe (applies to the period 2012 -

2014 period as well). 

Tier 2

Gasoline Jet

15 ppm 

Highway and 

NRLM Fuel

Figure 7.1-6 Pipeline Sequence and Fate of Interface Between Fuel Batches 

in Areas that Do Not Carry Heating Oil; After NRLM Rule: 2010-2012

Transmix

1.75% Jet

2.2% Hwy

Gasoline in equal amounts

Transmix Products

Volume = 1.75% Jet + 2.2% Hwy

Quality: <500 ppm

Segregated Interface

Distillate volume = 1.75% Jet + 2.2% Hwy + 1/3 of gasoline in transmix

Distillate quality: <500ppm

Jet

The primary difference between the sequencing in these pipelines in 2010-2012 and 2007-

2010 is again the elimination of 500 ppm fuel. Now, in the absence of the 500 ppm batch, the

interface between the batch of jet fuel and the batch of 15 ppm fuel can no longer be cut into

either fuel. The jet fuel specifications will not allow the addition of No. 2 distillate material due

its higher aromatic levels and higher boiling points. The 15 ppm cap will not allow the blending

of jet fuel with its much higher sulfur levels. Thus, this interface will have to be segregated from

both adjacent batches and stored separately at the terminal. We do not expect that this jethighway fuel interface will be mixed with other transmix which contains some gasoline. 

Transmix processors simply separate gasoline from distillate material via distillation. Adding a

mixture of jet fuel and highway fuel to a transmix distillation column will just cause all of this

material to flow to the distillate product. No separation will occur. Thus, there is no benefit to

offset the cost of shipping this distillate transmix to the transmix processor and distilling it. 

Instead we expect that the terminal will store this interface in a separate tank and sell it directly to

a market which can use 500 ppm fuel. In the 2010-2012 timeframe, this is either the NRLM fuel

market or the heating oil market. As assumed for 2007-2010 in Section 7.1.3.2.2, in PADDs 2

and 4 from 2010-2012, we assume that this 500 ppm interface will be sold first to the heating oil

market and then to the NRLM markets, in proportion to demand. In California, it will be sold to

the L&M market. In PADD 5 outside of California, it will be sold to the NRLM markets, in

proportion to demand. 
Estimated Costs of Low-Sulfur Fuels

P

 Given the low likelihood that small refiner fuel would be shipped through pipelines, it would have been more

realistic to assume that small refiner fuel produced in PADD 3 would be consumed in that region. This has no

impact on the nationwide emission reductions projected here. However, a greater volume of small refiner fuel would

have been slightly higher emissions of sulfur dioxide and sulfate PM in PADD 3 and slightly lower emissions in

PADD 1.

7-39

The volume of the downgrade from jet fuel and 15 ppm highway fuel to this 500 ppm

interface does not change from 2007-2010, as there was no net change in the size of the 500 ppm

batch in 2007-2010. The quality of the distillate produced from transmix is also the same as in

2007-2010. Thus, the volumes and quality of distillate downgrades remain unchanged from those

in 2007-2010. Table 7.1.3-15 summarizes the destination of downgrade from 2010 to 2012.

Table 7.1.3-15

Blending of Downgrade Under the NRLM Rule: 2010 to 2012

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O CA

1st Priority HO & L&M HO HO & NRLM HO NRLM L&M

2nd Priority - NRLM - NRLM - -

Finally, small refiners can produce and sell 500 ppm fuel to the NRLM markets during this

timeframe. We assume that this fuel is generally not distributed in pipelines, so it does not affect

the product shipment sequences shown in Figures 7.1-5 and 7.1-6. We expect that the volume of

this 500 ppm small refiner fuel will decrease somewhat relative to that in 2007-2010. This occurs

because we do not believe that a small refiner would invest to produce 500 ppm NRLM fuel for

four years unless they also planned to produce 15 ppm NRLM fuel after 2014. Therefore, we

assumed that only those small refiners which our cost analysis shows as competitive with other

refiners in producing 15 ppm diesel fuel would produce 500 ppm NRLM fuel in the 2010-2014

timeframe. We assume that the 500 ppm small refiner fuel which is exempted from the 15 ppm

nonroad sulfur standard is blended into the nonroad pool. As in 2007-2010, we combined small

refiner fuel production in PADDs 1 and 3 and then apportioned it to the two PADDs based on the

relative demands for NRLM fuel in each PADD.P The volume of 500 ppm small refiner fuel

expected to be exempted in each region is summarized in Table 7.1.3-16.

Table 7.1.3-16

Small Refiner Fuel Exempted by Region: 2010 - 2012 (million gallons in 2014)

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK HI CA

261 140 165 4 60 30 0 0

The final projections of production, spillover, downgrade and demand for 2010-2012 under

this final NRLM rule are shown in Table 7.1.3-17.
Final Regulatory Support Document

7-40

Table 7.1.3-17

Distillate Supply and Demand: Final Rule: 2010-2012 (million gallons in 2014)

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,056

Spillover to Non-hwy -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 15 ppm 3,498 3,477 1,215 245 200 0 39 8,674 10 8,684

Small Refiner Fuel 283 139 136 5 60 30 0 654 0 654

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 835 3,712

Jet Downgrade 0 92 85 18 115 0 0 310 0 310

Hwy Downgrade 0 427 133 93 149 0 0 801 0 801

Reproc. Downgrade 0 0 0 0 0 0 0 0 219 219

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production 500 ppm 195 723 684 74 33 5 0 1,714 0 1,714

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 76 18 43 5 14 0 0 157 144 301

Hwy Downgrade 251 85 67 28 19 0 0 450 217 667

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500 ppm 173 212 868 0 7 69 20 1,349 0 1,349

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 67 5 54 0 3 0 0 130 46 176

Hwy Downgrade 222 25 85 0 4 0 0 337 59 396

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil

Production HS 6,313 0 1,193 0 37 199 114 7,856 0 7,856

Hwy Spillover 192 436 215 53 22 0 8 734 0 734

Jet Downgrade 108 94 137 7 0 0 0 347 0 347

Hwy Downgrade 357 436 215 37 0 0 0 1,045 0 1,045

7.1.3.2.4 Final Rule Program - 2012 to 2014

Beginning in mid-2012, the sulfur cap applicable to L&M fuel changes from 500 ppm to 15

ppm. Also, 500 ppm fuel produced during shipment of 15 ppm fuel (and by small refiners or

using small refiner credits) can continue to be sold to the NRLM fuel markets outside of the

Northeast/Mid-Atlantic Area. However, within the Northeast/Mid-Atlantic Area, downgraded

distillate or small refiner fuel containing more than 15 ppm sulfur can only be sold as heating oil. 

As was the case for 2007-2010 and 2010-2012, the demand for each distillate fuel and the

spillover of highway fuel into these markets are assumed to remain unchanged from those

occurring in the Reference Case (see Table 7.1.3-5). Since we assumed that 500 ppm L&M fuel

would not be widely distributed as a fungible fuel from 2010-2012, the pipeline sequencing

described in Figures 7.1-5 and 7.1-6 continue to apply. Thus, the types and volumes of

downgrade generated in 2010-2012 will continue in 2012-2014. 
Estimated Costs of Low-Sulfur Fuels

7-41

The destination of these downgrades stays the same outside of the Northeast/Mid-Atlantic

Area, as downgraded distillate can continue to be sold to the NRLM market through 2014 (and to

the L&M fuel market thereafter). Within the Northeast/Mid-Atlantic Area, however, downgraded

distillate can no longer be sold to the L&M fuel market. Thus, starting in mid-2012, the

downgraded distillate generated in the Northeast/Mid-Atlantic Area shifts from the L&M market

to the heating oil market, where it displaces high sulfur distillate. This also causes the volume of

L&M fuel which must be produced to the 15 ppm cap to be larger than that needed under the 500

ppm cap. The small refiner fuel exempted and blended into the 15 ppm sulfur NRLM diesel fuel

pool remains the same as in 2010-2012 except for Alaska. The volume of small refiner fuel

eligible for exemptions in Alaska is limited by the volume of the 15 ppm market. The additional

production of 15 ppm fuel to satisfy the locomotive and marine market in 2012 in Alaska

increases the volume of small refiner fuel exempted there to the total production of NRLM diesel

fuel. The volume of small refiner fuel exempted is summarized in Table 7.1.3-18.

Table 7.1.3-18

Small Refiner Fuel Exempted by Region: 2012 - 2014 (million gallons in 2014)

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK HI CA

261 140 165 4 60 104 0 0

The final projections of production, spillover, downgrade and demand for 2012-2014 under

this final NRLM rule are shown in Table 7.1.3-19.
Final Regulatory Support Document

7-42

Table 7.1.3-19

Distillate Supply and Demand: Final Rule: 2012-2014 (million gallons in 2014)

Fuel Use

Category

Fuel Type PADD

AK HI US -

CA

CA US

1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,054

Spillover to Non-hw -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 15 ppm 3,574 3,506 1,278 246 209 0 39 8,851 10 8,861

Small Refiner Fuel 207 111 74 3 52 30 0 477 0 477

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 835 3,712

Jet Downgrade 0 92 85 18 115 0 0 310 0 310

Hwy Downgrade 0 427 133 93 149 0 0 801 0 801

Reproc. Downgrade 0 0 0 0 0 0 0 0 219 219

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Loco

motive

Production 15 ppm 493 701 647 73 26 0 0 1,931 0 1,931

Small Refiner Fuel 29 22 37 1 7 5 0 100 0 100

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 0 18 43 5 14 0 0 82 144 226

Hwy Downgrade 0 85 67 28 19 0 0 203 217 421

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 15 ppm 437 205 820 0 7 0 20 1,489 0 1,489

Small Refiner Fuel 25 7 48 0 3 69 0 150 0 150

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 0 6 54 0 3 0 0 63 46 109

Hwy Downgrade 0 26 85 0 4 0 0 116 59 175

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil 

Production HS 5,697 0 1,193 0 37 199 114 7,240 0 7,240

Hwy Spillover 192 184 274 53 22 0 8 734 0 734

Jet Downgrade 252 94 137 7 0 0 0 490 0 490

Hwy Downgrade 830 436 215 37 0 0 0 1,518 0 1,518

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

7.1.3.2.5 Final Rule Program - 2014 and Beyond

The primary changes occurring in 2014 are: 1) the end of the small refiner provisions and 2)

the prohibition on the use of any 500 ppm fuel in the nonroad fuel market. These changes have

no effect on fuel demand in any of the markets of interest here. Spillover of highway fuel into the

other markets is also assumed to be unaffected, with one exception, as discussed below. As

pipelines still carry the same fuels, the volume of each fuel downgraded is also unaffected. 
Estimated Costs of Low-Sulfur Fuels

7-43

Only the use of 500 ppm downgrade changes, as this fuel can no longer be sold into the

nonroad fuel market. Therefore, we assumed that it would be used in either the L&M fuel market

or the heating oil market according to the same relative priorities described in Table 7.1.3-15. In

a few cases, the volume of downgrade exceeds the demand for all L&M fuel and heating oil in a

region, considering the historical level of highway fuel spillover. In those cases, we reduced the

volume of spillover of highway fuel into these markets until demand for non-spillover fuel

equaled that of the available downgrade. If the volume of available downgrade exceeded total

demand for L&M fuel and heating oil in a region (i.e., zero spillover), we assume that the excess

downgrade fuel will be returned to a refinery and be reprocessed into 15 ppm fuel. The

projections of production, spillover, downgrade and demand for 2014 and beyond under this

NRLM rule are shown in Table 7.1.3-20. 
Final Regulatory Support Document

7-44

Table 7.1.3-20

Distillate Supply and Demand: Final Rule: 2014 and Beyond (million gallons in 2014)

Fuel Use

Category

Fuel Type PADD

AK HI US -

CA

CA US

1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,056

Spillover to Non- -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 15 ppm 3,781 4,136 1,568 321 336 30 39 10,211 10 10,221

Hwy Spillover 206 1,535 345 490 404 4 4 2,986 835 3,821

Jet Downgrade 0 0 0 0 0 0 0 0 0 0

Hwy Downgrade 0 0 0 0 0 0 0 0 0 0

Reprocessed

Downgrade

0 0 0 0 116 0 0 116 219 335

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Loco

motive

Production 15 ppm 522 142 443 0 0 5 0 1,111 0 1,111

Hwy Spillover 15 287 141 90 0 0 0 532 0 532

Jet Downgrade 1 122 137 24 46 0 0 328 144 472

Hwy Downgrade 0 563 215 122 60 0 0 960 217 1,177

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 15 ppm 462 243 894 0 0 69 20 1,687 0 1,687

Hwy Spillover 13 84 179 0 0 0 1 277 0 277

Jet Downgrade 0 0 45 0 61 0 0 105 46 151

Hwy Downgrade 0 0 70 0 78 0 0 149 59 208

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil 

Production HS 5,697 0 1,193 0 0 199 114 7,202 0 7,202

Hwy Spillover 192 184 274 53 0 0 8 712 0 712

Jet Downgrade 252 94 137 7 26 0 0 516 0 516

Hwy Downgrade 830 436 215 37 33 0 0 1,552 0 1,552

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

7.1.4 Sensitivity Cases

Distillate fuel production and demand were estimated for three sensitivity cases. The first

sensitivity case represents an indefinite 500 ppm cap on NRLM fuel that takes effect in 2007 (i.e.,

no subsequent 15 ppm cap). The second sensitivity case analyzes the proposed rule, which would

not require locomotive and marine diesel fuel be desulfurized to 15 ppm. The last sensitivity case
Estimated Costs of Low-Sulfur Fuels

7-45

analyzes the final rule, but bases the demand for nonroad fuel on information from EIA reports

rather than EPA’s draft NONROAD2004 model.

7.1.4.1 NRLM Regulated to 500 ppm Indefinitely

To support the legal justification of the 500 ppm cap on NRLM fuel in 2007, we evaluate the

costs and benefits of this standard in the absence of a subsequent 15 ppm cap on NRLM fuel. 

Here, we estimate the production and demand for the various distillate fuels in 2014 under this

indefinite 500 ppm cap on NRLM fuel. 

During the period from 2007 to 2010, distillate fuel production and demand under this

indefinite 500 ppm NRLM fuel cap are assumed to be the same as under the FRM (see Table

7.1.3-14). After 2010, the only differences are the end of the small refiner provisions for

producing high sulfur NRLM fuel and the end of the temporary compliance option under the

highway fuel program. These two changes are assumed to not affect the demand for the various

distillate fuels, nor the spillover of highway fuel into the NRLM fuel and heating oil markets. 

The types and volumes of distillate downgrade is not affected, since 500 ppm NRLM fuel will

still be carried in all pipelines. However, the disposition of this downgraded distillate is affected

slightly, since 500 ppm downgraded distillate can no longer be sold into the 500 ppm highway

market. The disposition of downgraded distillate as summarized in Tables 7.1.3-10 through

7.1.3-12 still apply except for the removal of 500 ppm highway fuel as an option for use of this

downgraded distillate. The final projections of production, spillover, downgrade and demand for

2010 and beyond under this NRLM rule are shown in Table 7.1.4-1.
Final Regulatory Support Document

7-46

Table 7.1.4-1 

Distillate Fuel Supply and Demand in 2010 and Beyond (million gallons in 2014)

NRLM at 500 ppm Indefinitely

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,056

Spillover to Non- -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 500 ppm 3,293 3,617 1,351 249 261 30 39 8,839 10 8,849

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 835 3,712

Jet Downgrade 114 92 84 18 115 0 0 424 0 424

Hwy Downgrade 375 427 133 93 149 0 0 1,177 0 1,177

Reproc. Downgrade 0 0 0 0 0 0 0 0 219 219

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production 500 ppm 454 723 685 73 33 5 0 1,973 0 1,973

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 16 18 43 5 14 0 0 98 144 242

Hwy Downgrade 52 85 67 28 19 0 0 255 217 472

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500 ppm 402 211 869 0 7 69 20 1,578 0 1,578

Hwy Spillover 13 84 179 0 9 0 1 286 53 339

Jet Downgrade 14 6 54 0 3 0 0 77 46 123

Hwy Downgrade 46 26 85 0 4 0 0 161 59 221

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

 Oil

Production HS 6,313 0 1,193 0 37 199 114 7,856 0 7,856

Hwy Spillover 192 184 274 53 22 0 8 734 0 734

Jet Downgrade 108 94 137 7 0 0 0 347 0 347

Hwy Downgrade 357 436 215 37 0 0 0 1,045 0 1,045

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

7.1.4.2 Proposed Rule - 500 ppm NRLM Cap in 2007; 15 ppm Nonroad Fuel Cap in 2010

This second sensitivity case evaluates the NRLM fuel program proposed in the NPRM. This

case is the same as that proposed, except that the Northeast/Mid-Atlantic Area provisions were

added not allowing small refiner fuel and downgrade to be used in the 15 ppm nonroad diesel fuel

pool in most of PADD 1 after 2010. Thus, from 2007 to 2012, the program is the same as the

final NRLM fuel program. After 2012, the difference is that L&M fuel remains at 500 ppm and

that the Northeast/Mid-Atlantic Area restrictions would apply to only the nonroad pool in PADD

1, not the NRLM pool as is the case for the final NRLM program. Since there are no differences

between this case and the final NRLM program during the period from 2007 to 2010 the distillate

production and demand estimates shown in Table 7.1.3-14 are assumed to apply here, as well.
Estimated Costs of Low-Sulfur Fuels

7-47

From 2010 to 2012, there are no differences in the regulatory requirements of the proposed

and final NRLM fuel programs. Thus, distillate fuel demand, spillover of highway fuel to nonhighway markets, and the types and volume of downgrade are the same under both programs. 

The small refiner fuel volume exempted from the 15 ppm sulfur standard and is blended into the

nonroad diesel fuel pool. The small refiner fuel volume is the same as that summarized in Table

7.1.3-16. Nothing changes in 2012 under the proposed NRLM program. Thus, the production,

downgrade, spillover and demand volumes are the same over the entire period from 2010 to 2014. 

The final projections of production, spillover, downgrade and demand for 2010 to 2014 under this

proposed rule sensitivity case are shown in Table 7.1.4-2. 

Table 7.1.4-2

Distillate Fuel Supply and Demand in 2010 - 2014 (million gallons in 2014)

15 ppm Nonroad Cap, 500 ppm L&M Cap

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,056

Spillover to Non-hwy -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 15 ppm 3,498 3,477 1,215 245 200 0 39 8,674 10 8,684

Small Refiner Fuel 283 139 136 5 60 30 0 654 0 654

Hwy Spillover 206 1,535 345 451 333 4 4 2,877 835 3,712

Jet Downgrade 0 92 85 18 115 0 0 310 0 310

Hwy Downgrade 0 427 133 93 149 0 0 801 0 801

Reproc. Downgrade 0 0 0 0 0 0 0 0 219 219

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production 500 ppm 195 723 684 74 33 5 0 1,714 0 1,714

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 76 18 43 5 14 0 0 157 144 301

Hwy Downgrade 251 85 67 28 19 0 0 450 217 667

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500 ppm 173 212 868 0 7 69 20 1,349 0 1,349

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 67 5 54 0 3 0 0 130 46 176

Hwy Downgrade 222 25 85 0 4 0 0 337 59 396

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil

Production HS 6,313 0 1,193 0 37 199 114 7,856 0 7,856

Hwy Spillover 192 436 215 53 22 0 8 734 0 734

Jet Downgrade 108 94 137 7 0 0 0 347 0 347

Hwy Downgrade 357 436 215 37 0 0 0 1,045 0 1,045

After 2014, the small refiner provisions end and downgraded distillate can no longer be sold

to the nonroad fuel market. Downgrade can only be used in the L&M and heating oil markets. 
Final Regulatory Support Document

7-48

The final projections of production, spillover, downgrade and demand for 2014 and beyond for

the proposed rule are shown in Table 7.1.4-3.

Table 7.1.4-3

Distillate Fuel Supply and Demand in 2014 and Beyond (million gallons in 2014)

15 ppm Nonroad Cap, 500 ppm L&M Cap

Fuel Type

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,825 18,487 9,527 2,981 3,254 161 60 50,294 4,760 55,056

Spillover to Non-hwy -425 -2,090 -939 -633 -404 -4 -13 -4,508 -835 -5,343

Hwy Downgrade -678 -721 -378 -103 -125 0 0 -2,006 -173 -2,178

Demand 14,722 15,676 8,210 2,245 2,725 157 46 43,781 3,752 47,533

Nonroad

Production 15 ppm 3,781 4,136 1,568 323 338 30 39 10,215 10 10,225

Hwy Spillover 206 1,535 345 488 404 4 4 2,985 835 3,820

Jet Downgrade 0 0 0 0 0 0 0 0 0 0

Hwy Downgrade 0 0 0 0 0 0 0 0 0 0

Reprocessed

Downgrade

0 0 0 0 116 0 0 116 219 335

Demand 3,987 5,670 1,914 810 857 34 43 13,316 1,064 14,379

Locomotive

Production 500 ppm 195 142 443 0 0 5 0 816 0 816

Hwy Spillover 15 287 141 90 0 0 0 1,106 0 1,106

Jet Downgrade 76 122 137 24 46 0 0 399 144 543

Hwy Downgrade 251 563 215 122 60 0 0 1,183 217 1,401

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500 ppm 172 243 894 0 0 69 20 1,398 0 1,398

Hwy Spillover 13 84 179 0 0 0 1 277 0 277

Jet Downgrade 67 0 45 0 61 0 0 173 46 219

Hwy Downgrade 222 0 70 0 78 0 0 371 59 430

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

Oil

Production HS 6,313 0 1,193 0 0 199 114 7,819 0 7,819

Hwy Spillover 192 184 274 53 0 0 8 712 0 712

Jet Downgrade 108 94 137 7 26 0 0 373 0 373

Hwy Downgrade 357 436 215 37 33 0 0 1,079 0 1,079

Demand 6,970 714 1,820 98 59 199 122 9,981 0 9,981

7.1.4.3 Final NRLM Fuel Program With Nonroad Fuel Demand Derived from EIA

FOKS and AEO

This sensitivity case evaluates the final NRLM fuel program assuming a reduced level of

nonroad fuel demand. As discussed in Section 2.4.5 of the Summary and Analysis document for

this rule, a number of commenters claimed that EPA’s NONROAD model overestimates nonroad

fuel demand. To ensure that uncertainties in the level of nonroad fuel demand do not affect the

decisions being made in this NRLM rule, we evaluate the cost, emission reductions and cost

effectiveness of the final NRLM fuel program using an estimate of nonroad fuel demand derived
Estimated Costs of Low-Sulfur Fuels

7-49

from EIA’s FOKS and AEO reports. Thus, the first step in this sensitivity analysis is to derive

this lower nonroad fuel demand. Then, we will discuss how this affects spillover, downgrade and

production of the various distillate fuels.

We based nonroad fuel demand for the purpose of estimating fuel costs in the NPRM on the

information contained in EIA’s FOKS and AEO reports. The methodology used here is

essentially the same as that used in the NPRM. The primary difference is the use of more recent

EIA FOKS and AEO reports. In the NPRM, we used the 2000 FOKS and 2002 AEO reports. 

Here, we use the 2001 FOKS and 2003 AEO reports. We start with our derivation of nonroad

fuel demand in 2001 using 2001 FOKS and then adjust this estimate for growth using 2003 AEO. 

7.1.4.3.1 Nonroad Fuel Demand in 2001 Derived from EIA FOKS

This section describes our methodology for deriving nonroad fuel demand from information

collected and projections made by EIA. For a more detailed description of the EIA FOKS

information collection process and how estimates of nonroad fuel can be derived from it, the

reader is referred to the draft RIA for this rule. As described in Section 7.1.2, EIA’s FOKS

estimates distillate demand in eleven economic sectors. FOKS also breaks down the distillate

demand for several of these sectors according to the physical type of distillate used. Table 7.1.4-4

presents the “adjusted” estimated of distillate fuel demand for PADD 1 from the 2001 FOKS

report. 
Final Regulatory Support Document

7-50

Table 7.1.4-4

Nonroad Fuel Demand, PADD 1 Estimates from 2001 FOKS

End Use Fuel Grade Distillate* 

 (M gal)

Diesel

(%)

Diesel

(M gal)

Nonroad

(%)

Nonroad 

(M gal)

Farm diesel 447 100 447 100 447

distillate 41 0 0 0 0

Construction distillate 550 95 523 100 523

Other/(Logging) distillate 149 95 142 100 142

Industrial No. 2 fuel oil 226 0 0 0 0

No. 4 distillate 40 0 0 0 0

No. 1 distillate 1 40 0.4 100 0.4

No. 2 low-S diesel 118 100 118 100 118

No. 2 high-S diesel 374 100 374 100 374

Commercial No. 2 fuel oil 1,369 0 0 0 0

No. 4 distillate 200 0 0 0 0

No. 1 distillate 2 40 0.8 50 0.4

No. 2 low-S diesel 450 100 450 0 0

No. 2 high-S diesel 203 100 203 100 203

Oil Company distillate 21 50 10.5 100 11

Military diesel 45 100 45 85 38

distillate 28 0 0 0 0

Electric Utility distillate 564 100 564 0 0

Railroad distillate 506 95 481 1.0 5

Vessel Bunkering distillate 461 90 415 0 0

On-Highway diesel 10,284 100 10,284 0.7 73

Residential No. 2 fuel oil 5,464 0 0 0 0

No. 1 distillate 5 0 0 0 0

Total 21,548 - 14,058 1,934

The key step in our methodology is the estimation of the portion of each sector’s fuel demand

that is used in nonroad engines. These percentages are summarized in Table 7.1.4-4. We

describe these estimates below. 
Estimated Costs of Low-Sulfur Fuels

7-51

Farm. FOKS estimates fuel demand in this sector for two fuel grades: “diesel fuel” and

“distillate.” We assume that 100 percent of the diesel fuel represents nonroad use, and 100

percent of the distillate represents uses other than in nonroad engines, such as heating and crop

drying.

Construction/Other Off-Highway(Logging). For the construction and logging/other-nonhighway end uses, we assume that 95 percent of the total distillate sold is diesel fuel, and that 100

percent of the diesel fuel is used in nonroad engines.

Industrial. FOKS breaks down distillate sales in this sector into five individual fuel grades:

No. 1 distillate, low sulfur No. 2 diesel, high sulfur No. 2 diesel fuel, high sulfur No. 2 fuel oil

and No. 4 distillate. No. 4 distillate is not covered by the NRLM rule and is rarely used in

nonroad engines, if at all. Therefore, we exclude all sales of No. 4 distillate from our estimate of

nonroad fuel use. Since sales of No. 2 diesel fuel and No. 2 fuel oil are categorized separately,

we assume that no No. 2 fuel oil is used in diesel engines. Thus, no No. 2 fuel oil sales are

assumed to fall into nonroad fuel demand. Conversely, we assume that all No. 2 diesel fuel, lowsulfur and high-sulfur, is used in diesel engines and that all of this diesel fuel represents nonroad

use. As will be seen below, the low sulfur diesel fuel in the commercial sector is most often used

in highway vehicles owned by “commercial” entities not subject to highway excise taxes. We are

not aware of any “industrial” entities which are not subject to the excise tax. Thus, should an

industrial entity use this low sulfur diesel fuel in a highway vehicle that it owns, this use would be

included in the FOKS estimate of highway diesel fuel sales, since the latter is based on excise tax

receipts. Therefore, it is reasonable to assume that the low sulfur diesel fuel is not used in

highway vehicles. The industrial sector does not include either locomotives or marine vessels. 

Thus, the non-highway diesel engines must be either nonroad engines or stationary diesel engines

likely used for power generation. We assume that the latter use is negligible. For the remaining

category, No. 1 distillate, diesel and fuel oil are not distinguished. After consulting with EIA

staff, we estimate that 40 percent of No. 1 distillate sales represent diesel fuel, that 100 percent of

this diesel represents nonroad use, and that the remainder represents No. 1 fuel oil used in other

applications, such as space heating.

Commercial. As with the industrial end use, distillate sales in this sector are reported by fuel

grade. As in the industrial sector, we assume that none of the No. 2 fuel oil, and No. 4 fuel

represents nonroad diesel fuel. However, in the commercial sector, we assume that all low sulfur

diesel fuel sold is used in highway vehicles. This sector includes school-bus and government

(local, state and federal) fleets. Fuel used by these fleets are exempt from the federal excise tax,

as is fuel for nonroad use. Thus, we assume that none of the low-sulfur No. 2 diesel fuel sold to

this sector is used in nonroad engines. As in the industrial sector, we assume that 100 percent of

the high-sulfur No. 2 diesel fuel sold is used in nonroad engines. Also as in the industrial sector,

after consultation with EIA staff, we estimate that 40 percent of the No. 1 distillate sold is diesel

fuel. However, due to the presence of public fleet fuel use in this sector, we estimate that only 50

percent of this diesel fuel is used in nonroad engines.
Final Regulatory Support Document

7-52

Oil Company. Sales to this sector include fuel purchased for drilling and refinery operations.

We assume that 50 percent of the reported distillate is diesel fuel, and that all of this diesel fuel is

used in nonroad equipment. We assume that the remainder represents other uses such as

underground injection under pressure to fracture rock.

Military. Fuel sales to the military are reported as being either diesel fuel or distillate. We

assume that 85 percent of diesel fuel sales is used in ‘non-tactical’ nonroad equipment, and that

none of the distillate sales represents nonroad use. We assume that 15% of the diesel fuel is not

used in nonroad engines because the NONROAD model does not attempt to represent fuel use or

emissions from ‘tactical’ military equipment, such as tanks and personnel carriers because they

are not covered by EPA emission standards.

Railroad. We believe that the vast majority of fuel sales to railroads is used by locomotives. 

Based on guidance from a major railroad, we assume that a small fraction (1%) of reported fuel

sales is used in nonroad equipment operated by railroads.

Electric Utility, Vessel Bunkering and Residential., We assume that all of the fuel sold to these

sectors falls into our definition of marine fuel or heating oil and that none of it is used in nonroad

engines..

The EIA FOKS report presents fuel sales by sector for each region of interest here. Thus, we

applied the diesel fuel and nonroad percentages shown in Table 7.1.4-4 to the fuel sales in each

sector and region to estimate nonroad fuel demand. The results are summarized in Table 7.1.4-5.
Estimated Costs of Low-Sulfur Fuels

7-53

Table 7.1.4-5

2001 Nonroad Fuel Consumption Derived From EIA FOKS (million gallons) 

End Use Fuel Grade Region

1 2 3 4 5-O AK HI CA

Farm diesel 447 1,764 627 155 90 0 7 281

distillate 0 0 0 0 0 0 0 0

Construction distillate 523 572 425 118 83 7 3 251

Other/(Logging) distillate 142 66 136 21 23 3 0 17

Industrial No. 2 fuel oil 0 0 0 0 0 0 0 0

No. 4 distillate 0 0 0 0 0 0 0 0

No. 1 distillate 0.5 8 1 4 0.2 4 0 0

No. 2 low-S diesel 118 210 196 175 101 2 2 44

No. 2 high-S diesel 374 355 204 15 66 13 0.6 5

Commercial No. 2 fuel oil 0 0 0 0 0 0 0 0

No. 4 distillate 0 0 0 0 0 0 0 0

No. 1 distillate 0.5 7 0.3 2 0.4 2 0 0

No. 2 low-S diesel 0 0 0 0 0 0 0 0

No. 2 high-S diesel 203 155 71 8 19 21 3 3

Oil Company distillate 11 26 344 10 1.5 14 0 4

Military diesel 38 15 105 4 50 5 22 24

distillate 0 0 0 0 0 0 0 0

Electric Utility distillate 0 0 0 0 0 0 0 0

Railroad distillate 5 10 8 2 1 0.04 0 2

Subtotal 1,862 3,188 2,119 514 436 69 38 611

Highway (Retail

Purchases)

diesel 73 73 50 13 10 3 1 25

Total 1,934 3,261 2,169 527 446 72 39 636

Table 7.1.4-5 shows that, according to the above methodology, the farm, construction,

commercial, and industrial categories are the largest consumers of nonroad diesel fuel. Nonroad

fuel use on farms is concentrated in PADD 2 (the Midwest), while nonroad fuel demand in the

other sectors is spread out more evenly across the nation.

We replaced the year 2001 nonroad fuel demand estimates shown in Table 7.1.2-3 from

EPA’s NONROAD model with those shown in the last line of Table 7.1.4-5. We recalculated the

heating oil demand in each region so that the total fuel demand in the five categories matched the

total distillate demand shown. Table 7.1.4-6 shows the revised estimates of fuel demand by

region for each of the five usage categories.
Final Regulatory Support Document

7-54

Table 7.1.4-6

2001 Distillate Fuel Demand as Derived From EIA FOKS (million gallons)

Region

EPA Use Category 1 2 3 4 5-O AK HI CA

Highway Fuel 10,211 10,873 5,694 1,557 1,890 108 32 2,602

Nonroad Fuel 1,934 3,261 2,169 527 446 72 38 637

Locomotive Fuel 476 989 831 209 94 4 0 172

Marine Fuel 415 286 1,037 0 20 60 18 46

Heating Oil 8,512 1,682 1,202 175 249 167 125 146

Total Demand 21,549 17,092 10,932 2,468 2,700 412 214 3,604

The volume of spillover of highway fuel into the four non-highway fuel categories is the same

as that shown in Table 7.1.2-5. We considered the volume of unrefunded fuel for this case as

well. Since we are basing nonroad fuel demand in this sensitivity case on information contained

in FOKS, we adjust both the highway fuel demand and the nonroad fuel demand for unrefunded

use of highway fuel in nonroad equipment. The volume of unrefunded fuel is the same as that

used for the final rule case, shown in Table 7.1.2-2. The types and volume percentages of

downgrade of highway fuel, jet fuel and gasoline are the same as those shown in Table 7.1.2-6. 

However, we do not show a complete breakdown of production, spillover, downgrade and

demand for each usage category and region for 2001 (analogous to that shown in Table 7.1.2-8),

since these figures are not used directly in the estimates of either costs, nor emission reductions in

this sensitivity analysis.

7.1.4.3.2 Nonroad Fuel Demand in 2014 Derived from EIA AEO 2003

We developed an estimate of nonroad fuel demand in 2014 from EIA’s AEO 2003 report. We

began with a detailed set of distillate fuel consumption estimates for the various economic sectors

presented in AEO 2003. AEO 2003 presents distillate fuel consumption estimates at roughly

three levels of detail, as shown in Table 7.1.4-7 below. 
Estimated Costs of Low-Sulfur Fuels

7-55

Table 7.1.4-7

Distillate Fuel Consumption Demand within AEO 2003

First Level Second Level Third Level Nonroad Fuel Percentage

Total

Transportation

Highway 0.7%

Rail 1%

Marine 0%

Military 76%

Residential Residential 0%

Commercial Commercial 14%

Industrial

Farm 98%

Oil Company 50%

Construction 95%

Other * 82%

Electricity Generation Electricity Generation 0%

* Not explicitly shown in AEO 2003. Backcalculated from total “Industrial” fuel use.

At the third level of detail from AEO 2003, we utilized distillate fuel consumption estimates

from AEO to estimate future nonroad demand. The one exception was the “other” industrial

sector. This estimate was obtained by subtracting the demand in the farm, construction and oil

company sectors from that in the total industrial sector. We converted all these estimates of fuel

consumption from AEO from quadrillion BTU per year to gallons per year using EIA’s

conversion factor of 138,700 BTU/gal. When available, we estimated the nonroad percentage of

each sector’s total distillate fuel consumption using the same methodology which we used with

the FOKS estimates above. These estimates are available for all the sectors except commercial,

“other” industrial, farm, and military. The estimates of the nonroad portion of total distillate

demand for these four sectors depended on the type of distillate fuel consumed, such as low sulfur

diesel fuel, kerosene, etc. AEO 2003 does not provide projections broken down by the type of

distillate fuel, only total distillate. In these cases, we used the nonroad diesel fuel fractions found
Final Regulatory Support Document

Q The projection of nonroad fuel demand using the NONROAD model was already complete and subsequent

analyses of emission benefits, monetized benefits and economic impacts were underway when FOKS 2002 was

issued in late November 2003. Therefore, it was not possible to utilize FOKS 2002 for the primary estimates

presented in this Final RIA. However, it was possible to utilize this more recent information for this sensitivity

analysis.

7-56

from the analysis of the 2002 FOKS.Q All of these nonroad fuel percentages are shown in Table

7.1.4-8.

Table 7.1.4-8 presents total distillate demand by sector for 2002 and projected total distillate

demand for 2014 from AEO 2003, the percentage of each fuel demand that is assumed to be

nonroad, and the resulting 2014 nonroad fuel demand by sector.

Table 7.1.4-8

2002 and 2014 Nonroad Diesel Fuel Demand: 2003 AEO (million gallons per year)

Category Total Distillate Demand Nonroad Diesel (%)* Nonroad Diesel Fuel Demand

Year 2002 2014 2002 & 2014 2002 2014

Commercial 3244 3533 14% 458 498

Other Industrial 2653 3331 82% 2164 2717

Highway 32,242 48,839 0.7% 221 257

Oil Company 43 0 50% 22 0

Farm 3403 3843 98% 3320 3749

Railroad 3669 4196 1% 35 40

Military 800 894 76% 607 678

Construction 1687 1983 95% 1603 1884

Total --- --- --- 8428 9823

* Derived by applying EPA estimates of nonroad fuel use to FOKS 2002 fuel sales.

As shown in Table 7.1.4-8, from information contained in both FOKS 2002 and AEO 2003,

total nonroad fuel demand in 2014 is projected to be 9.82 billion gallons per year. This represents

a 17% increase over the 8.43 billion gallons demand estimated for 2002, or 1.37% per year linear

growth from a 2002 base. The growth rates embedded in AEO 2003 vary slightly from year to

year and decade to decade. However, as the purpose of this analysis is simply to evaluate the

sensitivity of the cost effectiveness of the NRLM rule to uncertainty in nonroad fuel consumption,

we have applied this 1.37% growth rate from 2001 through the final year of analysis, 2040. We

based the growth rate off of fuel consumption in 2002, rather than 2001, because FOKS 2002

shows a significant drop in distillate fuel consumption in 2002. The AEO 2003 estimates reflect

this decrease in 2002 and projects relatively steady growth starting from 2002. Thus, reflecting
Estimated Costs of Low-Sulfur Fuels

7-57

this drop in nonroad diesel fuel consumption in 2002 and steady growth thereafter better reflects

the AEO 2003 projections. Projecting growth from 2001 would have reduced the annual growth

rate considerably, over-predicting fuel consumption prior to 2014 and under-predicting fuel

consumption after 2014. 

We used the same 2001-2014 growth ratios for the other four fuel use categories as shown in

Tables 7.1.3-1 and 7.1.3-3. These growth ratios were applied to the demand volumes in Table

7.1.4-7 to estimate fuel demand in 2014. We increased the 2001 nonroad fuel consumption of

9.084 billion gallons (shown in Table 7.1.4-7) by 8.14%, which is the total increase between the

2014 fuel demand of 9.823 billion gallons shown in Table 7.1.4-8 and 2001 nonroad fuel demand. 

These volumes are summarized in Table 7.1.4-9.

Table 7.1.4-9

2014 Distillate Fuel Demand based on AEO 2003 and FOKS 2002 (million gallons)

Region

EPA Use Category 1 2 3 4 5-O AK HI CA

Highway Fuel 14,738 15,693 8,221 2,248 2,728 157 47 3,758

Nonroad Fuel 2,104 3,603 2,394 581 492 78 43 691

Locomotive Fuel 536 1114 935 236 106 5 0 194

Marine Fuel 475 327 1187 0 23 69 21 53

Heating Oil 7,898 1,561 1,115 162 231 155 116 136

The volume of spillover of highway fuel into the four non-highway fuel categories is the same

as that shown in Table 7.1.3-5. The types and volume percentages of downgrade of highway fuel,

jet fuel and gasoline are the same as those shown in Table 7.1.3-6. Jet fuel demand is the same as

shown in Table 7.1.3-7. We also used the same methodology to assign downgrade to the various

distillate markets. Finally, the volume of NRLM fuel produced by small refiners is the same as

that shown in Table 7.1.3-16.

We do not show a complete breakdown of production, spillover, downgrade and demand for

each usage category and region for 2010-2014 or 2014 and beyond in a Reference Case (which

assumes no implementation of this nonroad rule). This is not necessary because we used a

different methodology to estimate the emission reductions for this case than for the final rule case

which did not require the estimation of reference case sulfur levels. Tables 7.1.4-10 through

7.4.1-13 present the estimates of distillate demand and production for the four time periods

relevant to this nonroad rule: 2007-2010, 2010-2012, 2012-2014, and 2014 and beyond,

respectively.
Final Regulatory Support Document

R The jet and highway-based downgrade volumes shown in this table were over-estimated by 10% and 2%,

respectively. 

7-58

Table 7.1.4-10

Distillate Supply and Demand: Final Rule: 2007-2010 (million gallons in 2014)

Nonroad Fuel Demand Derived from EIA FOKS and AEO R

Fuel Use

Categor

y

Fuel Type PADD

AK HI

US -

 CA CA US

1 2 3 4 5-O

Highway

Production 15 ppm 14,347 16,382 8,589 2,601 2,882 152 56 45,030 4,547 49,577

Prod 500 ppm 860 1822 540 199 181 8 4 3595 0 3595

Spillover -388 -1798 -910 -553 -336 -3 -13 -4001 -622 -4623

Hwy Downgrade 15 -679 -717 -375 -101 -125 0 0 -1,997 -173 -2,170

Jet Downgrade 129 106 139 15 51 0 0 440 0 440

Hwy Downgrade 465 534 239 83 71 0 0 1,392 0 1,392

Demand 15 ppm 13,303 14,048 7,358 1,987 2,441 149 44 39,328 3,752 43,080

Demand 500 ppm 1,433 1,642 861 261 286 8 3 4,494 0 4,494

Nonroad

Production 500

ppm

1,825 2,606 1,807 261 139 28 41 6,706 7 6,712

Small Refiner Fuel 211 100 212 3 48 49 0 623 0 623

Hwy Spillover 143 1,025 423 335 200 3 4 2,132 614 2,746

Jet Downgrade 0 0 14 0 51 0 0 65 0 65

Hwy Downgrade 0 0 23 2 72 0 0 97 0 97

Reproc. Downgrade 0 0 0 0 0 0 0 0 95 95

Demand 2,178 3,730 2,479 601 510 81 44 9,624 715 10,339

Locomotive

Production 500

ppm

468 797 698 105 29 2 0 2,098 0 2,098

Small Refiner Fuel 54 31 82 1 10 3 0 181 0 181

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 0 0 5 0 11 0 0 16 85 102

Hwy Downgrade 0 0 9 1 15 0 0 25 110 135

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 500

ppm

414 234 886 0 6 25 20 1,585 0 1,585

Small Refiner Fuel 48 9 104 0 2 44 0 207 0 207

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 0 0 6 0 2 0 0 9 64 74

Hwy Downgrade 0 0 11 0 3 0 0 15 83 98

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating 

 Oil

Production HS 7,233 28 612 0 144 155 109 8,280 0 8,953

Hwy Spillover 217 402 168 89 87 0 8 971 8 980

Jet Downgrade 98 187 124 11 0 0 0 419 56 475
Estimated Costs of Low-Sulfur Fuels

7-59

Hwy Downgrade 351 944 212 63 0 0 0 1,569 72 1,641

Demand 7,898 1,561 1,115 162 231 155 116 11,239 136 11,375

Table 7.1.4-11

Distillate Supply and Demand: Final Rule: 2010-2012 (million gallons in 2014)

Nonroad Fuel Demand Derived from EIA FOKS and AEO

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,801 18,210 9,507 2,903 3,189 161 59 49,831 4,552 54,383

Spillover -388 -1,798 -910 -553 -336 -3 -13 -4,001 -622 -4,623

Hwy Downgrade -678 -722 -378 -103 -126 0 0 -2,008 -173 -2,180

Demand 14,735 15,690 8,219 2,247 2,727 157 47 43,822 3,757 47,579

Nonroad

Production 15 ppm 1,835 2,630 1,970 265 182 51 41 6,974 7 6,981

Small Refiner fuel 283 139 136 5 60 30 0 654 0 654

Hwy Spillover 145 1,047 431 344 280 3 4 2,256 614 2,870

Jet Downgrade 0 0 0 0 0 0 0 0 0 0

Hwy Downgrade 0 0 0 0 0 00 0 0 0

Proc. Downgrade 0 0 0 0 0 0 0 0 96 96

Demand 2,263 3,816 2,537 616 522 84 45 9,884 715 10,599

Locomotive

Production 15 ppm 195 821 589 0 0 5 0 1,610 0 1,610

Hwy Spillover 15 287 141 126 14 0 0 582 0 582

Jet Downgrade 76 1 80 18 40 0 0 215 85 300

Hwy Downgrade 250 5 126 92 52 0 0 525 110 635

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 15 ppm 173 241 747 0 0 69 20 1,250 0 1,250

Hwy Spillover 13 84 179 0 3 0 1 280 0 280

Jet Downgrade 67 0 102 0 9 0 0 178 65 244

Hwy Downgrade 222 1 160 0 11 0 0 394 84 479

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

 Oil 

Production HS 7,217 0 595 0 0 155 108 8,076 0 8,076

Hwy Spillover 217 402 168 89 44 0 8 928 8 936

Jet Downgrade 108 206 137 12 81 0 0 544 56 601

Hwy Downgrade 356 953 215 62 105 0 0 1,691 72 1,764

Demand 7,898 1,561 1,115 162 231 155 116 11,239 136 11,375
Final Regulatory Support Document

7-60

Table 7.1.4-12

Distillate Supply and Demand: Final Rule: 2012-2014 (million gallons in 2014)

Nonroad Fuel Demand Derived from EIA FOKS and AEO

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,801 18,210 9,507 2,903 3,189 161 59 49,831 4,552 54,383

Spillover -388 -1798 -910 -553 -336 -3 -13 -4001 -622 -4623

Hwy Downgrade -678 -722 -378 -103 -126 0 0 -2,008 -173 -2,180

Demand 14,735 15,690 8,219 2,247 2,727 157 47 43,822 3,757 47,579

Nonroad

Production 15 ppm 1,903 2,554 1,690 182 25 24 41 6,419 7 6,425

Small Refiner Fuel 143 100 118 3 48 53 0 455 0 455

Hwy Spillover 143 1,025 423 335 200 3 4 2,132 614 2,746

Jet Downgrade 0 9 97 13 103 0 0 222 0 222

Hwy Downgrade 0 42 152 68 133 0 0 395 0 395

Proc. Downgrade 0 0 0 0 0 0 0 0 95 95

Demand 2,178 3,730 2,479 601 510 81 44 9,624 715 9,622

Locomotive

Production 15 ppm 487 781 653 73 5 1 0 2,001 0 2,001

Small Refiner Fuel 34 31 46 1 10 3 0 125 0 125

Hwy Spillover 15 287 141 129 40 0 0 611 0 611

Jet Downgrade 0 3 38 5 22 0 0 69 85 178

Hwy Downgrade 0 13 60 28 29 0 0 129 109 322

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 15 ppm 432 229 828 0 1 22 20 1,532 -95 1,597

Small Refiner Fuel 30 9 58 0 2 47 0 147 0 147

Hwy Spillover 13 84 179 0 9 0 1 286 0 286

Jet Downgrade 0 1 47 0 5 0 0 53 65 137

Hwy Downgrade 0 4 74 0 6 0 0 84 84 137

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

 Oil 

Production HS 6,602 65 595 4 144 155 108 7,674 0 7,674

Hwy Spillover 217 402 168 89 87 0 8 971 8 979

Jet Downgrade 251 194 137 11 0 0 0 593 56 665

Hwy Downgrade 828 899 215 58 0 0 0 2,001 72 2,073

Demand 7,898 1,561 1,115 162 231 155 116 11,239 136 11,375
Estimated Costs of Low-Sulfur Fuels

7-61

Table 7.1.4-13

Distillate Supply and Demand: Final Rule: 2014 and Beyond (million gallons in 2014)

Nonroad Fuel Demand Derived from EIA FOKS and AEO

Fuel Use

Category

Fuel Type PADD

AK HI

US -

 CA CA US 1 2 3 4 5-O

Highway

Production 15 ppm 15,801 18,210 9,507 2,903 3,189 161 59 49,831 4,552 54,383

Spillover -388 -1,798 -910 -553 -336 -3 -13 -4,001 -622 -4623

Hwy Downgrade -678 -722 -378 -103 -126 0 0 -2,008 -173 -2,180

Demand 14,735 15,690 8,219 2,247 2,727 157 47 43,822 3,757 47,579

Nonroad

Production 15 ppm 2,036 2,706 2,056 260 229 77 41 7,404 7 7,411

Hwy Spillover 143 1,025 423 335 200 3 4 2,132 614 2,746

Jet Downgrade 0 0 0 0 0 0 0 0 0 0

Hwy Downgrade 0 0 0 0 0 0 0 0 0 0

Reproc. Downgrade 0 0 0 0 0 0 0 0 96 96

Demand 2,178 3,730 2,479 601 510 81 44 9,624 715 10,339

Locomotive

Production 15 ppm 522 755 443 0 0 5 0 1,723 0 1,723

Hwy Spillover 15 287 141 129 0 0 0 516 0 516

Jet Downgrade 0 13 136 18 46 0 0 214 85 298

Hwy Downgrade 0 59 215 95 60 0 0 429 110 539

Demand 536 1,114 935 236 106 5 0 2,932 194 3,126

Marine

Production 15 ppm 462 243 894 0 0 69 20 1,688 0 1,688

Hwy Spillover 13 84 179 0 0 0 1 277 0 277

Jet Downgrade 0 0 45 0 10 0 0 55 65 120

Hwy Downgrade 0 0 70 0 13 0 0 83 84 167

Demand 475 327 1,187 0 23 69 21 2,103 53 2,156

Heating

 Oil 

Production HS 6,602 66 595 4 8 155 108 7,538 0 7,538

Hwy Spillover 217 402 168 89 87 0 8 971 134 1,106

Jet Downgrade 251 194 137 11 74 0 0 667 56 723

Hwy Downgrade 828 898 215 58 95 0 0 2,095 72 2,167

Demand 7,898 1,561 1,115 162 231 155 116 11,239 136 11,375

The primary difference resulting from estimating nonroad fuel demand using FOKS and AEO

is that nonroad demand is lower (and therefore, heating oil demand is larger) in PADDs 2, 4, and

5. This eliminates the need to reprocess any downgraded fuel after 2014 when this fuel can only

be used in the L&M fuel and heating oil markets. 

7.1.5 Methodology for Annual Distillate Fuel Demand: 1996 to 2040

The environmental impact and cost-effectiveness analyses presented in this Final RIA require

estimates of fuel demand from 1996 through 2040. This section presents the methodology used to

develop these estimates. The actual levels of fuel demand are presented in Section 7.1.6 along

with the sulfur contents of the various fuels on an annual basis. 

In this section, we develop a set of year-over-year (compound) growth rates from 1996-2040

for the four non-highway fuel categories. We did not address highway fuel demand, as this is not
Final Regulatory Support Document

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affected by this NRLM rule. For nonroad, locomotive and marine fuels, we obtained annual

estimates of fuel demand for as much of this time period as was available. We then calculated

year-over-year growth rates over the period of time that the data were available. Finally, we

extrapolated or interpolated these growth rates to cover any years for which specific fuel demand

projections were not available. 

We obtained our estimates of annual fuel demand by nonroad engines from EPA’s

NONROAD emission model. These estimates of fuel demand and the resulting annual growth

rates are shown in Table 7.1.5-1. As can be seen, NONROAD projects a linear increase in fuel

consumption over time. This results in a slightly decreasing year-over-year growth rate over

time.
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Table 7.1.5-1 

Annual Growth In the Demand of Nonroad and Locomotive Fuel

Year Nonroad Fuel Demand

(million gallons)

Annual Growth Rate Locomotive Fuel Demand Annual 

(trillion btu) (million gallons) Growth Rate

1996 9,158 3072

1997 9,450 1.032 0.969

1998 9,742 1.031 0.968

1999 10,024 1.029 0.967

2000 10,319 1.030 609.2 2692 0.966

2001 10,613 1.028 628.4 1.032

2002 10,906 1.028 610.2 0.971

2003 11,200 1.027 617.0 1.011

2004 11,493 1.026 621.4 1.007

2005 11,787 1.026 626.1 1.008

2006 12,078 1.025 638.9 1.020

2007 12,370 1.024 650.2 1.018

2008 12,661 1.024 657.4 1.011

2009 12,952 1.023 666.3 1.014

2010 13,244 1.023 676.9 1.016

2011 13,537 1.022 689.7 1.019

2012 13,830 1.022 696.6 1.010

2013 14,123 1.021 702.1 1.008

2014 14,416 1.021 707.6 1.007

2015 14,709 1.020 713.5 1.008

2016 14,999 1.020 721.1 1.011

2017 15,289 1.020 727.7 1.009

2018 15,579 1.019 733.1 1.007

2019 15,869 1.019 740.3 1.010

2020 16,159 1.018 745.4 1.007

2021 16,449 1.018 749.2 1.005

2022 16,739 1.018 755.9 1.009

2023 17,029 1.017 762.6 1.009

2024 17,319 1.017 769.2 1.009

2025 17,609 1.017 776.6 1.010

2026 17,897 1.016 - 1.008

2027 18,185 1.016 - 1.008

2028 18,473 1.016 - 1.008

2029 18,761 1.016 - 1.008

2030 19,049 1.015 - 1.008

2031 19,337 1.015 - 1.008

2032 19,625 1.015 - 1.008

2033 19,912 1.015 - 1.008

2034 20,201 1.015 - 1.008

2035 20,489 1.014 - 1.008

2036 20,777 1.014 - 1.007

2037 21,065 1.014 - 1.007

2038 21,353 1.014 - 1.007

2039 21,641 1.014 - 1.007

2040 21,928 1.013 - 1.007

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Locomotive diesel fuel growth rates for the period from 1996 to 2000 were estimated from

historic estimates of fuel consumption taken from the 1996 and 2000 FOKS reports. We assume

that locomotive diesel fuel demand decreased linearly between 1996 and 2000. We assume a

constant linear growth rate for this time period, as this seemed most consistent with EIA’s

projection of growth in locomotive fuel demand in the post-2000 time period. For the period after

2000, we use the annual demand for locomotive diesel fuel projected by EIA in the AEO 2003 to

calculate year-over-year growth rates from 2000 to 2025 (the last projection year in AEO 2003). 

Beyond 2025, we assume that locomotive fuel demand grows linearly at the average rate of

growth between 2021 and 2025. The FOKS and AEO estimates of fuel demand and the yearover-year growth rates for locomotive diesel fuel are summarized in Table 7.1.5-1. 

According to EIA FOKS reports, the demand for marine diesel fuel decreased slightly

between 1996 and 2001. We estimated annual demand for marine diesel fuel for 1997-2000 by

assuming a constant compound growth rate between 1996 and 2001. (Constant compound growth

is more consistent with EIA’s projection of growth in marine fuel demand in the post-2000 time

period than constant linear growth.) For the period after 2000, we use the annual demand for

marine diesel fuel projected by EIA in the AEO 2003 to calculate a year-over-year growth rates

2000 to 2025 (the last projection year in AEO 2003). Beyond 2025, we assume that marine fuel

demand grows at a constant compound growth rate between 2001 and 2025, which was 1.3%. 

The FOKS and AEO estimates of fuel demand and the year-over-year growth rates for marine

diesel fuel are summarized in Table 7.1.5-2. 
Table 7.1.5-2

Annual Growth in the Demand for Marine Diesel Fuel

Year Marine Fuel Consumption Annual Growth Rate

AEO 2003 (trillion BTU) FOKS 2001 (million gallons)

1996 - 1960

1997 - - 0.992

1998 - - 0.992

1999 - - 0.992

2000 - - 0.992

2001 344.6 1884 0.992

2002 338.4 - 0.982

2003 342.6 - 1.012

2004 346.1 - 1.010

2005 348.4 - 1.007

2006 356.5 - 1.023

2007 361.7 - 1.015

2008 366.7 - 1.014

2009 371.1 - 1.012

2010 375.7 - 1.012

2011 381.2 - 1.015

2012 386.1 - 1.013

2013 389.6 - 1.009

2014 394.3 - 1.012

2015 398.7 - 1.011

2016 402.5 - 1.010

2017 407.0 - 1.011

2018 413.1 - 1.015

2019 420.1 - 1.017

2020 425.0 - 1.012

2021 430.2 - 1.012

2022 437.2 - 1.016

2023 442.1 - 1.011

2024 448.0 - 1.013

2025 453.2 - 1.012

2026 - - 1.013

2027 - - 1.013

2028 - - 1.013

2029 - - 1.013

2030 - - 1.013

2031 - - 1.013

2032 - - 1.013

2033 - - 1.013

2034 - - 1.013

2035 - - 1.013

2036 - - 1.013

2037 - - 1.013

2038 - - 1.013

2039 - - 1.013

2040 - - 1.013
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We applied a simpler approach to estimating the growth in the demand for heating oil for a

number of reasons. One, this rule does not regulate the sulfur content of heating oil. Two, EIA

does not present estimates of heating oil demand, as it is defined here. Three, heating oil demand

between 2001 and 2014 is very close to zero. Thus, the effect of differing assumptions regarding

the shape of this growth, such as linear versus compound, have a negligible effect on any

extrapolated growth. 

As shown in Table 7.1.3-3, heating oil demand declined by 7% from 2001 to 2014. We

assumed that this decline was occurring at a constant compound rate, which we calculated to be -

0.006% for this time period. We assumed that this decline would continue through 2040. 

7.1.6 Annual Distillate Fuel Demand and Sulfur Content

In this section we estimate the sulfur content of the various types of distillate fuel prior to this

rule and how they are affected by the NRLM rule. We then present year-by-year estimates of

both distillate fuel demand and sulfur content for the purpose of estimating the environmental

benefits of this rule. 

7.1.6.1 Sulfur Content

The sulfur content of high sulfur distillate before and after this NRLM rule is used in two

ways in this regulatory impact analysis: 1) to estimate the reductions in emissions of sulfur

dioxide and sulfate PM, and 2) to estimate the cost of desulfurizing this fuel to meet 500 and 15

ppm caps. In this section we estimate the current sulfur content of the four non-highway distillate

fuels by region. We then estimate how these sulfur contents change during the various phases of

the final NRLM fuel program. Finally, we estimate the sulfur content of these fuels for two

sensitivity cases: 1) a long-term 500 ppm sulfur NRLM program and 2) the proposed NRLM fuel

program (15 ppm nonroad fuel and 500 ppm L&M fuel in 2010).

We estimate the current sulfur content of high sulfur distillate from diesel fuel survey data

collected by TRW Petroleum Technologies (TRW) at its facility in Bartlesville, Oklahoma. This

facility was formerly known as the National Institute for Petroleum and Energy Research

(NIPER)). Surveys performed for 1999 through 2002 were published by TRW. Surveys prior to

1999 were published by the NIPER. We evaluated their survey data from 1996 through 2002. As

the methodology of conducting the surveys and the presentation of the data have not changed

over this time period, we will simply refer to these surveys as TRW surveys. 

No comments were received on our methodology for estimating the sulfur content of high

sulfur distillate for the NPRM. However, we have made three changes to that analysis which we

believe improve the estimate. The first is to include the 2002 survey data, which is now available. 

The second is to include sample data which were assigned a production volume by TRW. The

third is to adjust the sample data for the addition of downgraded jet fuel, highway diesel fuel and

heavy gasoline during distribution. 
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TRW collects sulfur data voluntarily provided by domestic refiners, including a refiner

located in the Virgin Islands. These refiners analyze the sulfur content of their diesel fuel

production and submit the results to TRW. TRW states that the survey results reflect the average

quality of distillate fuel produced at refineries for use in each geographical area. However, TRW

also states that the data may not be representative of the full range of sulfur content of these fuels

at their point of use. This appears to be due to either TRW or refiners reporting the average

quality of their high sulfur diesel fuel versus a set of individual samples, in addition to the effect

of convenience sampling. 

TRW presents survey results for five geographic regions containing 16 districts. According to

TRW, these areas are based on fuel distribution systems, refinery locations, centers of population,

temperature zones, and arteries of commerce. A map of the regions and districts is shown in

Figure 7.1-6 below. Each sample is assigned to both a region and to one or more districts. We

primarily use the TRW district assignments, as they provide a more precise indication of where

the fuel was eventually sold. A map of the Petroleum Administration Defense Districts (PADDs)

is shown for comparison in Figure 7.1-7. Since all of our estimates for distillate production and

demand were developed by PADD (with PADD 5 split up further), we assigned each TRW

district to one or more PADDs as described in Table 7.1.6-1. 

Figure 7.1-7 TRW Fuel Survey Regions and Districts
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Figure 7.1-8. Petroleum Administration for Defense Districts (PADDs)

Table 7.1.6-1

 Assignments of TRW Regions and Districts to PADDs

Region TRW District Assigned PADD

Eastern

A 1

B 1

C 1, 2

Southern D 1, 3

Central

E 2

F 2

G 2

Rocky Mountain

H 4

I 4

J 3

K 4

Western

L 5

M 5

N 5

O 5

P 5

TRW provides a rough indication of the annual volume of fuel represented by each sulfur

measurement by assigning each data point one of four numbers. Table 7.1.6-2 presents the

numbering system used by TRW and the range of diesel fuel production represented by each
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numeral assignment. In order to weight the sulfur measurements by volume, we assigned an

average volume to each range. These averages are also shown in Table 7.1.6-2.

Table 7.1.6-2

Production Volumes of Fuel Sulfur Samples

TRW Sample Quantity Number

Fuel Volume (Barrels Per Year)

TRW: Range EPA: Assumed Average Volume

1 Over 1,500,000 1,500,000

2 500,000 to 1,500,000 1,000,000

3 50,000 to 500,000 275,000

4 Under 50,000 50,000

 Within each region, the TRW reports generally list the sulfur samples by their Sample

Quantity Number, starting with 1 and moving to 2, 3, and 4. Thus, the sulfur data representing

the largest fuel batches are listed first and those representing the smallest fuel batches are listed

last. However, some sulfur data points in the TRW reports do not have a Sample Quantity

Number. These data points always appear at either top of the list or the bottom of the list. When

the data missing a Sample Quantity Number appeared at the top of the list, we assigned that data a

production volume of 2 million barrels per year. When the data appeared at the bottom of the list,

we assigned it a volume of 25,000 barrels per year. In the analysis performed for the NPRM, we

excluded this data from the analysis. 

The survey reports often list the same sample number under more than one region. Each of

these listings shows the districts in both regions. For example, Sample 45 may be listed in both

the Eastern and Central Regions. Both listing show C2 and E2, indicating that 0.5-1.0 million

barrels of fuel were shipped that year to Districts C and E. Since both districts are listed under

both regions, we assumed that this was in fact only one data point and that 0.5-1 million barrels

were shipped to District C in the Eastern Region and that 0.5-1 million barrels were shipped to

District E in the Central Region, not twice this volume. 

In this case, the numeral 2 was assigned to each district, so we assumed that 0.5-1 million

barrels of fuel were provided to each district. In some cases, two or more districts are listed with

only a single numeral following the district letter (i.e., C, E 2). In this case, we assumed that the

total volume of fuel produced was 0.5-1 million barrels and that this volume was split between

the two districts. TRW indicates that the district receiving the most fuel was listed first, etc. 

However, lacking any quantitative information about the relative volumes of fuel supplied to each

district, we simply assumed that each district received the same proportion. 

TRW segregates their reporting of fuel quality by fuel type, namely No. 1 diesel fuel, No. 2

highway diesel fuel and No. 2 off-highway diesel fuel. We focused solely on the data for No. 2

off-highway diesel fuel. However, we assumed that off-highway diesel fuel with a sulfur content
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of less than 500 ppm was highway diesel fuel "spillover." These data were excluded from this

analysis since we account for the lower sulfur content of spillover fuel separately below.

After applying the PADD assignments shown in Table 7.1.6-1, we volume weighted the sulfur

data in each PADD using the average volumes shown in Table 7.1.6-2 in order to derive a PADD

average sulfur content for each calendar year. These PADD averages are shown in Table 7.1.6-3.
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Table 7.1.6-3

 Sulfur Content of High Sulfur Diesel Fuel

PADD Year Volume (bbls/year) Sulfur (ppm) PADD Average

1

1996 7,170,833 3,482

2,925

1997 13,250,000 2,601

1998 5,887,500 2,418

1999 4,137,500 3,257

2000 10,525,000 2,691

2001 4,437,500 3,061

2002 2,662,500 4,343

2

1996 4,158,333 3,497

2,973

1997 5,100,000 3,008

1998 2,775,000 2,241

1999 2,912,500 1,717

2000 10,412,500 2,939

2001 5,212,500 3,854

2002 1,000,000 1,620

3

1996 2,420,833 4,539

3,776

1997 4,500,000 3,945

1998 2,387,500 5,004

1999 3,000,000 4,177

2000 3,387,500 4,361

2001 1,775,000 4,298

2002 2,387,500 4,359

4

1996 275,000 4,100

2,549

1997 275,000 1,000

1998 275,000 3,400

1999 275,000 2,000

2000 275,000 2,600

2001 275,000 2,340

2002 275,000 2,400

5

1996 2,050,000 3,076

2,566

1997 3,550,000 2,268

1998 1,550,000 3,077

1999 1,550,000 2,065

2000 2,175,000 * 2,566 *

2001 2,175,000 * 2,566 *

2002 2,175,000 * 2,566 *

U.S. 1996 16,075,000 3,623

3,030

1997 26,675,000 2,710

1998 12,875,000 2,669

1999 11,875,000 2,818

2000 26,775,000 2,886

2001 14,375,000 3,440

2002 8,500,000 3,510

* No data reported. Estimated from the average from 1996-1999.
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We next calculated a national average sulfur content for each year. This was done by

weighting the PADD average sulfur contents in each year by the volume of fuel represented by all

the samples in that PADD. No data were reported for the Western Region for 2000, 2001 and

2002. Thus, we substituted the 1996-1999 average production volume and sulfur content for

these missing years when calculating the national average for 1999-2002. These national

averages are also shown in Table 7.1.6-3. It should be noted that these national average sulfur

contents were not used in either the emissions nor cost analysis. The emission and cost analyses

used the PADD average sulfur contents. However, we present them here for illustrative purposes

and to simply the evaluation of the presence of any temporal trends in the sulfur content of high

sulfur diesel fuel.

We examined the annual average sulfur contents for possible trends. However, as indicated

by the national averages shown in Table 7.1.6-3, the sulfur content of high sulfur diesel fuel

seems to vary randomly. Therefore, we average the data once more across calendar years, again

using the fuel volumes represented by all the samples from each year. As shown in Table 7.1.6-3,

this overall average sulfur content is 3030 ppm. 

While the TRW reports indicate that the sulfur data was supplied by refiners, we assume that

these sulfur levels are actually those existing at the point-of-use (i.e. retail). Thus, this average

sulfur content of 3030 ppm is used in Chapter 3 to project emissions of sulfur dioxide and sulfate

PM from the burning of NRLM fuel and heating oil. Because of the absence of a trend in the

1996-2002 data, we assume that these sulfur contents will not change in the future, absent NRLM

fuel standards. 

In order to project desulfurization costs, however, an estimate of the current sulfur content of

NRLM fuel at the refinery is needed. As discussed in Sections 7.1.2 and 7.1.3, small volumes of

jet fuel, highway diesel fuel and heavy gasoline become mixed with high sulfur distillate during

pipeline shipment. These other fuels generally contain less sulfur than high sulfur diesel fuel, so

the sulfur content of high sulfur diesel fuel actually decreases during shipment. In order to better

estimate desulfurization costs, we estimated the sulfur content of high sulfur diesel fuel prior to

this mixing during shipment.

The volumes of high sulfur distillate produced at refineries and the volume of material

downgraded to high sulfur distillate is estimated in Sections 7.1.2 and 7.1.3 (see, for example,

Tables 7.1.2-8 and 7.1.3-8). Here, we estimate the sulfur content of these various materials so

that the combination matches the PADD average sulfur contents shown in Table 7.1.6-3. 

Table 7.1.2-6 shows the types of downgrades and their volumes and destinations. This table

shows that 1.75% of jet fuel demand, 2.2% of highway diesel fuel production, and a volume of

heavy gasoline equivalent to 0.58% of jet fuel demand and 0.73% of highway diesel fuel

production is shifted to high sulfur distillate during pipeline shipment. We estimate that jet fuel

averages 550 ppm sulfur.14 From the Final RIA for the highway diesel rule, highway diesel fuel

averages 340 ppm sulfur. The sulfur level of today’s gasoline, before the Tier 2 rule has been

implemented, averages about 300 ppm. The vast majority of this sulfur is contained in the
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S

 The distillate sulfur contents presented at the end of this section for 1996-2006 assume that jet-based

downgrade contains 700 ppm rather than 638 ppm and that highway-based downgrade contains 560 ppm rather than

480 ppm. These errors have a very small effect on the final sulfur content of high sulfur distillate fuels during these

years. As the NRLM fuel program has no effect during these years, neither the costs nor benefits associated with

this rule are affected.

7-74

naphtha produced in the fluidized catalytic cracker (FCC naphtha). The sulfur content of FCC

naphtha increases significantly with distillation temperature. Therefore, we estimate that the

heaviest one-third of gasoline distilled into transmix contains essentially all the sulfur in the

whole gasoline. Thus, we estimate the sulfur level of the heaviest one-third of gasoline to be

about 900 ppm. 

As described in Section 7.1.2, to simplify the analysis of downgrade distillate volume, we

combined the jet fuel downgrade with the portion of the heavy gasoline downgrade which was

dependent on jet fuel demand. Of this jet-based downgrade, jet fuel represents 75%

(1.75/(1.75+0.58)) and heavy gasoline represents 25% (0.58/(1.75+0.58)). Weighting the sulfur

content of jet fuel and heavy gasoline by these percentages produces an average sulfur content of

638 ppm. 

Likewise, we combined the highway diesel fuel downgrade with the portion of the heavy

gasoline downgrade which was dependent on highway diesel fuel production. Of this highwaybased downgrade, highway diesel fuel represents 75% (2.2/(2.2+0.73)) and heavy gasoline

represents 25% (0.73/(2.2+0.73)). Weighting the sulfur content of jet fuel and heavy gasoline by

these percentages produces an average sulfur content of 480 ppm.S

 

Table 7.1.6-4 presents the levels of high sulfur distillate production and demand, as well as

the volumes of downgraded material which are added to this fuel during distribution. All of these

figures were taken directly from Table 7.1.2-8. Table 7.1.6-4 also shows the sulfur content of

high sulfur diesel fuel at retail (from Table 7.1.6-3) and of the two types of downgrade, as

discussed above. We determined the sulfur content of high sulfur distillate at the refinery which,

when combined with the volumes and sulfur content of the two types of downgrade, matched the

sulfur content from the TRW surveys. The sulfur content of high sulfur distillate at the refinery

gate in each PADD are shown in Table 7.1.6-4. Because there are no product pipelines in Alaska

and Hawaii, we assume that there is no downgrade in these areas. Also, because we assumed

100% spillover into the high sulfur distillate market in California, there is no high sulfur distillate

in California pipelines to receive this downgrade. Distillate downgrade is assumed to be used

directly as L&M fuel. Thus, we assume that the sulfur content of 2,570 ppm for high suflur

distillate in PADD 5 applies at both retail and the refinery in Alaska, Hawaii, and California. 
Estimated Costs of Low-Sulfur Fuels

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Table 7.1.6-4

Sulfur Content of High Sulfur Diesel Fuel at Refineries in 2001

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5-O AK, HI, CA

High Sulfur Distillate Fuel Volume 

Demand 10,955 4,562 4,407 408 497 486

Jet-Based Downgrade 95 80 123 12 51 0

Highway-Based Downgrade 327 387 202 64 68 0

Refinery Production 10,533 4,095 4,082 332 378 486

High Sulfur Distillate Sulfur Content (ppm)

At Retail 2,930 2,970 3,780 2,550 2,570 2,570

Jet-Based Downgrade 638 638 638 638 638 638

Highway-Based Downgrade 480 480 480 480 480 480

Sulfur level of HS Dist Pool at

Refineries

3,041 3,295 4,059 3,102 3,280 2,570

As can be seen, downgrade occurring in pipelines decreases the sulfur content of high sulfur

distillate by as little as 111 ppm in PADD 1 and as much as 710 in PADD 5-O. The difference is

due to the very small volume of downgrade relative to the demand for high sulfur distillate in

PADD 1, with the opposite being true in PADD 5-O.

After completion of this analysis, we discovered that the TRW data represented sulfur levels

at the refinery and not downstream. Thus, the TRW sulfur levels should have been used to

estimate desulfurization costs in Section 7.2.2 and the adjustments shown in Table 7.1.6-4 should

have been used to estimate lower sulfur levels downstream. The result of this error is an

overestimation of the baseline sulfur content of high sulfur distillate by roughly 150 ppm on

average. Given the limited data set and the resulting year-to-year variation, the resulting estimate

is still well within the range of possible actual sulfur levels. This 150 ppm difference, if real,

results in an overestimation of the cost to produce 500 ppm NRLM fuel of roughly 0.02 cent per

gallon (i.e., roughly 1%) and an overestimation of the sulfur dioxide and sulfate PM emission

reductions due to the 500 ppm NRLM fuel cap of roughly 4-5%. 

The next step in this analysis is to project the sulfur content of the various distillate fuels

during the various phases of the final NRLM fuel program, as well as under the two sensitivity

cases. We assume that the sulfur content of NRLM fuel produced under 15 and 500 ppm caps

will be the same as those we estimate for highway diesel fuel produced under the same standards. 

Thus, we assume that NRLM fuel produced to meet a 500 ppm cap will contain 340 ppm sulfur. 

We assume that NRLM fuel produced to meet a 15 ppm cap will contain 7 ppm sulfur at the

refinery. However, as discussed in the Final RIA for the highway diesel rule, we assume that this

fuel will contain 11 ppm at the time of final sale. This increase of 4 ppm is due to very small
Final Regulatory Support Document

T

 The distillate sulfur contents presented at the end of this section assume that jet-based downgrade in this time

period contains 400 ppm rather than 435 ppm and that highway-based downgrade contains 35 ppm rather than 31

ppm. The net effect of these partially offsetting errors on the final sulfur content of high sulfur distillate fuels in the

base case is very minor.

U TRW also surveys the quality of distillate fuel oil. These surveys which we received after completion of this

analysis, show national average sulfur levels of roughly 2200 ppm, versus 3000 ppm for high sulfur diesel fuel. 

However, it is not clear how much distillate actually burned in heating oil uses is defined as heating oil at the

refinery and how much is defined as diesel fuel. Thus, we chose not to use the heating oil survey results here. 

However, given that at least a portion of the heating oil market must meet state sulfur caps of 2000-4000 ppm,

extrapolation of the diesel fuel survey results to heating oil probably over-estimates the sulfur content to some

degree. Given that the sulfurous emission reductions from heating oil are only ancillary to the benefits of this rule,

this likely small degree of overestimation is not critical. However, the heating oil related benefits are a large portion

7-76

volumes of higher sulfur fuel being incorporated into batches of 15 ppm diesel fuel during

shipment. This volume is by necessity very small compared to the volume of pipeline interface. 

Thus, this 4 ppm increase in 15 ppm fuel during shipment does not affect our estimation of the

creation and disposition of downgrade created in the pipeline during shipment. 

As just mentioned, highway fuel in the pipeline will contain between 7 and 11 ppm sulfur. 

We assume that the highway fuel contributing to interface contains 11 ppm sulfur. We assume

that the sulfur content of jet fuel will remain 550 ppm in the future. Under the Tier 2 standards,

gasoline will average 30 ppm sulfur. With this degree of sulfur control, essentially all the sulfur

in gasoline will be in the heavy portion of FCC naphtha. Thus, we apply the same factor of 3

discussed above and estimate that the heaviest one-third of gasoline will contain 90 ppm sulfur. 

Prior to the NRLM rule, the volume of jet-based downgrade stays the same as that shown in

Table 7.1.6-4 (compare the jet-based downgrade in Table 7.1.2-6 (2001) to that in Table 7.1.3-6

(2014 prior to the NRLM rule)). Only the sulfur levels change. A 75%/25% weighting of the

sulfur content of jet fuel (550 ppm) and heavy gasoline (90 ppm) produces an average sulfur

content of 435 ppm. 

As indicated in Table 7.1.3-6, the volume of highway-based downgrade increases

significantly with the onset of the 15 ppm highway program, due to the need to make more

protective interface cuts to maintain the quality of this fuel. As described in Table 7.1.3-6, 2.2%

of highway diesel fuel supply will be cut directly into high sulfur distillate fuel. We assume that

this highway fuel contains 11 ppm sulfur. Also, 2.2% of highway fuel supply plus a volume of

heavy gasoline equivalent to 0.73% of highway fuel supply will be processed as transmix and

added to the 500 ppm highway fuel supply. This downgrade will have an average sulfur content

of 31 ppm (25% of 90 ppm plus 75% of 11 ppm).T

Under the NRLM fuel program, after 2007, some pipelines are projected to continue carrying

heating oil, while others are expected to drop this fuel. For those pipelines still carrying heating

oil (PADDs 1 and 3), the sulfur content of jet-based downgrade will continue to be 435 ppm, as

described above. The sulfur content of the highway-based downgrade to high sulfur distillate and

500 ppm diesel fuel will continue to be 11 ppm and 31 ppm, respectively, as described above.U 
Estimated Costs of Low-Sulfur Fuels

of the incremental benefits of associated with the 15 ppm cap for L&M fuel. Thus, we address the possibility of a

lower sulfur content for heating oil in Section 8.3, where we evaluate the incremental cost effectiveness of the 15

ppm cap for L&M fuel. 

V The distillate sulfur contents presented at the end of this section assume that jet-based downgrade in this time

period contains 470 ppm rather than 485 ppm and that highway-based downgrade contains 25 ppm rather than 22

ppm. The net effect of these partially offsetting errors on the final sulfur content of high sulfur distillate fuels in the

base case is minor.

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For those pipelines not carrying heating oil, the nature of the downgrade and its disposition

changes, as shown in Table 7.1.3-12. For these pipelines (all PADDs except 1 and 3), all of the

jet-based downgrade is combined, as is the highway-based downgrade. The total jet-based

downgrade consists of 3.5% of jet fuel demand and a volume of heavy gasoline equivalent to

0.58% of jet fuel demand. This is a 6:1 ratio of jet fuel to gasoline. With jet fuel at 550 ppm and

heavy gasoline at 90 ppm, the average sulfur content of the jet-based downgrade is 485 ppm. 

Similarly, the total highway-based downgrade consists of 4.4% of highway fuel supply and a

volume of heavy gasoline equivalent to 0.73% of highway fuel supply. This is a 6:1 ratio of

highway fuel to gasoline. With highway fuel at 11 ppm and heavy gasoline at 90 ppm, the

average sulfur content of the highway-based downgrade is 22 ppm.V While the disposition of

this downgrade changes during the various phases of the NRLM fuel program, the sulfur content

of these two types of downgrade remain the same.

7.1.4.2 Distillate Fuel Demand and Sulfur Content by Year

We present the final estimates of distillate fuel demand and sulfur content for each year from

1996-2040 in this section. We develop these estimates by combining:

1) The sulfur contents developed in Section 7.1.4.1 with 

2) The sources of each distillate fuel’s supply in 2014 developed in Sections 7.1.2 (Reference

Case), 7.1.3 (after implementation of the final NRLM fuel program), and 7.1.4 (sensitivity

cases), and 

3) The growth in distillate fuel demand developed in Section 7.1.5. 

We did this for the entire U.S. (50-state) and for 48 states (the U.S. minus the states of Alaska

and Hawaii). The results are summarized in Tables 7.1.6-5 to 7.1.6-12. In all cases, we assume

that a new sulfur standard becomes effective on June 1. Therefore, the average sulfur levels in

any transition year is a 5:7 weighting of the previous year’s sulfur level and the following year’s

sulfur level.
Table 7.1.6-5 Annual Distillate Fuel Demand and Sulfur Content for the Reference Case; 

U.S. minus AK and HI (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,087 2,283 3,065 2,454 1,878 2,918 4,943 2,641 10,715 2,871

1997 9,376 2,283 2,971 2,454 1,863 2,918 4,834 2,641 10,654 2,871

1998 9,665 2,283 2,876 2,454 1,849 2,918 4,725 2,641 10,593 2,871

1999 9,945 2,283 2,782 2,454 1,834 2,918 4,616 2,641 10,532 2,871

2000 10,238 2,283 2,687 2,454 1,820 2,918 4,507 2,641 10,471 2,871

2001 10,530 2,283 2,772 2,454 1,805 2,918 4,577 2,637 10,411 2,871

2002 10,821 2,283 2,692 2,454 1,773 2,918 4,465 2,638 10,352 2,871

2003 11,112 2,283 2,722 2,454 1,795 2,918 4,517 2,638 10,292 2,871

2004 11,403 2,283 2,741 2,454 1,813 2,918 4,554 2,639 10,233 2,871

2005 11,694 2,283 2,762 2,454 1,825 2,918 4,587 2,639 10,174 2,871

2006 11,983 2,243 2,818 2,437 1,868 2,904 4,686 2,623 10,116 2,860

2007 12,272 2,214 2,868 2,424 1,895 2,893 4,763 2,611 10,058 2,853

2008 12,562 2,214 2,900 2,424 1,921 2,893 4,821 2,611 10,000 2,853

2009 12,851 2,214 2,939 2,424 1,944 2,893 4,883 2,611 9,943 2,853

2010 13,140 2,159 2,986 2,254 1,968 2,712 4,954 2,436 9,886 2,722

2011 13,430 2,120 3,043 2,133 1,997 2,583 5,039 2,312 9,829 2,628

2012 13,721 2,120 3,073 2,133 2,023 2,583 5,096 2,312 9,772 2,628

2013 14,012 2,120 3,097 2,133 2,041 2,583 5,138 2,312 9,716 2,628

2014 14,302 2,120 3,121 2,133 2,066 2,583 5,187 2,312 9,661 2,628

2015 14,593 2,120 3,148 2,133 2,089 2,583 5,236 2,313 9,605 2,628

2016 14,881 2,120 3,181 2,133 2,109 2,583 5,290 2,313 9,550 2,628

2017 15,169 2,120 3,210 2,133 2,132 2,583 5,342 2,313 9,495 2,628

2018 15,456 2,120 3,234 2,133 2,164 2,583 5,398 2,314 9,441 2,628

2019 15,744 2,120 3,266 2,133 2,201 2,583 5,466 2,314 9,386 2,628

2020 16,032 2,120 3,288 2,133 2,226 2,583 5,515 2,315 9,333 2,628

2021 16,319 2,120 3,305 2,133 2,254 2,583 5,559 2,316 9,279 2,628

2022 16,607 2,120 3,335 2,133 2,290 2,583 5,625 2,316 9,226 2,628

2023 16,895 2,120 3,364 2,133 2,316 2,583 5,680 2,317 9,173 2,628

2024 17,183 2,120 3,393 2,133 2,347 2,583 5,740 2,317 9,120 2,628

2025 17,470 2,120 3,426 2,133 2,374 2,583 5,800 2,317 9,068 2,628

2026 17,756 2,120 3,453 2,133 2,405 2,583 5,858 2,318 9,016 2,628

2027 18,042 2,120 3,481 2,133 2,436 2,583 5,917 2,319 8,964 2,628

2028 18,328 2,120 3,508 2,133 2,467 2,583 5,976 2,319 8,913 2,628

2029 18,613 2,120 3,536 2,133 2,499 2,583 6,035 2,320 8,861 2,628

2030 18,899 2,120 3,564 2,133 2,532 2,583 6,095 2,320 8,811 2,628

2031 19,185 2,120 3,591 2,133 2,564 2,583 6,155 2,321 8,760 2,628

2032 19,470 2,120 3,619 2,133 2,598 2,583 6,216 2,321 8,710 2,628

2033 19,756 2,120 3,646 2,133 2,631 2,583 6,277 2,322 8,660 2,628

2034 20,042 2,120 3,674 2,133 2,665 2,583 6,339 2,322 8,610 2,628

2035 20,328 2,120 3,701 2,133 2,700 2,583 6,401 2,323 8,561 2,624

2036 20,613 2,120 3,729 2,133 2,735 2,583 6,463 2,324 8,511 2,628

2037 20,899 2,120 3,756 2,133 2,770 2,583 6,526 2,324 8,463 2,628

2038 21,185 2,120 3,784 2,133 2,806 2,583 6,590 2,325 8,414 2,628

2039 21,470 2,120 3,811 2,133 2,842 2,583 6,653 2,325 8,366 2,628

2040 21,756 2,120 3,839 2,133 2,879 2,583 6,718 2,326 8,318 2,628

Table 7.1.6-6 Annual Distillate Fuel Demand and Sulfur Content: Final NRLM Rule: 

U.S. minus AK and HI (million gallons and ppm) 

Nonroad Locomotive Marine L&M Heating Oil
Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,087 2,283 3,065 2,454 1,878 2,918 4,943 2,641 10,715 2,871

1997 9,376 2,283 2,971 2,454 1,863 2,918 4,834 2,641 10,654 2,871

1998 9,665 2,283 2,876 2,454 1,849 2,918 4,725 2,641 10,593 2,871

1999 9,945 2,283 2,782 2,454 1,834 2,918 4,616 2,641 10,532 2,871

2000 10,238 2,283 2,687 2,454 1,820 2,918 4,507 2,641 10,471 2,871

2001 10,530 2,283 2,772 2,454 1,805 2,918 4,577 2,637 10,411 2,871

2002 10,821 2,283 2,692 2,454 1,773 2,918 4,465 2,638 10,352 2,871

2003 11,112 2,283 2,722 2,454 1,795 2,918 4,517 2,638 10,292 2,871

2004 11,403 2,283 2,741 2,454 1,813 2,918 4,554 2,639 10,233 2,871

2005 11,694 2,283 2,762 2,454 1,825 2,918 4,587 2,639 10,174 2,871

2006 11,983 2,243 2,818 2,435 1,868 2,902 4,686 2,621 10,116 2,860

2007 12,272 1,127 2,868 1,225 1,895 1,469 4,763 1,321 10,058 2,667

2008 12,562 330 2,900 361 1,921 445 4,821 394 10,000 2,530

2009 12,851 330 2,939 361 1,944 445 4,883 394 9,943 2,530

2010 13,140 155 2,986 177 1,968 208 4,954 189 9,886 2,424

2011 13,430 30 3,043 45 1,997 39 5,039 43 9,829 2,349

2012 13,721 30 3,073 45 2,023 39 5,096 43 9,772 2,349

2013 14,012 19 3,097 45 2,041 39 5,138 43 9,716 2,349

2014 14,302 11 3,121 61 2,066 33 5,187 49 9,661 2,336

2015 14,593 11 3,148 72 2,089 28 5,236 54 9,605 2,327

2016 14,881 11 3,181 72 2,109 28 5,290 54 9,550 2,327

2017 15,169 11 3,210 72 2,132 28 5,342 54 9,495 2,327

2018 15,456 11 3,234 72 2,164 28 5,398 54 9,441 2,327

2019 15,744 11 3,266 72 2,201 28 5,466 54 9,386 2,327

2020 16,032 11 3,288 72 2,226 28 5,515 54 9,333 2,327

2021 16,319 11 3,305 72 2,254 28 5,559 54 9,279 2,327

2022 16,607 11 3,335 72 2,290 28 5,625 54 9,226 2,327

2023 16,895 11 3,364 72 2,316 28 5,680 54 9,173 2,327

2024 17,183 11 3,393 72 2,347 28 5,740 54 9,120 2,327

2025 17,470 11 3,426 72 2,374 28 5,800 54 9,068 2,327

2026 17,756 11 3,453 72 2,405 28 5,858 54 9,016 2,327

2027 18,042 11 3,481 72 2,436 28 5,917 54 8,964 2,327

2028 18,328 11 3,508 72 2,467 28 5,976 54 8,913 2,327

2029 18,613 11 3,536 72 2,499 28 6,035 54 8,861 2,327

2030 18,899 11 3,564 72 2,532 28 6,095 54 8,811 2,327

2031 19,185 11 3,591 72 2,564 28 6,155 54 8,760 2,327

2032 19,470 11 3,619 72 2,598 28 6,216 54 8,710 2,327

2033 19,756 11 3,646 72 2,631 28 6,277 54 8,660 2,327

2034 20,042 11 3,674 72 2,665 28 6,339 54 8,610 2,327

2035 20,328 11 3,701 72 2,700 28 6,401 54 8,561 2,327

2036 20,613 11 3,729 72 2,735 28 6,463 54 8,511 2,327

2037 20,899 11 3,756 72 2,770 28 6,526 54 8,463 2,327

2038 21,185 11 3,784 72 2,806 28 6,590 54 8,414 2,327

2039 21,470 11 3,811 72 2,842 28 6,653 54 8,366 2,327

2040 21,756 11 3,839 72 2,879 28 6,718 54 8,318 2,327

Table 7.1.6-7 Annual Distillate Fuel Demand and Sulfur Content: NRLM to 500 ppm in 2007, no

15 ppm Step; U.S. minus AK and HI (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,087 2,283 3,065 2,454 1,878 2,918 4,943 2,641 10,715 2,871
1997 9,376 2,283 2,971 2,454 1,863 2,918 4,834 2,641 10,654 2,871

1998 9,665 2,283 2,876 2,454 1,849 2,918 4,725 2,641 10,593 2,871

1999 9,945 2,283 2,782 2,454 1,834 2,918 4,616 2,641 10,532 2,871

2000 10,238 2,283 2,687 2,454 1,820 2,918 4,507 2,641 10,471 2,871

2001 10,530 2,283 2,772 2,454 1,805 2,918 4,577 2,637 10,411 2,871

2002 10,821 2,283 2,692 2,454 1,773 2,918 4,465 2,638 10,352 2,871

2003 11,112 2,283 2,722 2,454 1,795 2,918 4,517 2,638 10,292 2,871

2004 11,403 2,283 2,741 2,454 1,813 2,918 4,554 2,639 10,233 2,871

2005 11,694 2,283 2,762 2,454 1,825 2,918 4,587 2,639 10,174 2,871

2006 11,983 2,242 2,818 2,435 1,868 2,902 4,686 2,621 10,116 2,860

2007 12,272 1,126 2,868 1,225 1,895 1,469 4,763 1,323 10,058 2,667

2008 12,562 330 2,900 361 1,921 445 4,821 394 10,000 2,530

2009 12,851 330 2,939 361 1,944 445 4,883 394 9,943 2,530

2010 13,140 276 2,986 293 1,968 348 4,954 315 9,886 2,526

2011 13,430 237 3,043 245 1,997 280 5,039 259 9,829 2,523

2012 13,721 237 3,073 245 2,023 280 5,096 259 9,772 2,523

2013 14,012 237 3,097 245 2,041 280 5,138 259 9,716 2,523

2014 14,302 237 3,121 245 2,066 280 5,187 259 9,661 2,523

2015 14,593 237 3,148 245 2,089 280 5,236 259 9,605 2,523

2016 14,881 237 3,181 245 2,109 280 5,290 259 9,550 2,523

2017 15,169 237 3,210 245 2,132 280 5,342 259 9,495 2,523

2018 15,456 237 3,234 245 2,164 280 5,398 259 9,441 2,523

2019 15,744 237 3,266 245 2,201 280 5,466 259 9,386 2,523

2020 16,032 237 3,288 245 2,226 280 5,515 259 9,333 2,523

2021 16,319 237 3,305 245 2,254 280 5,559 259 9,279 2,523

2022 16,607 237 3,335 245 2,290 280 5,625 259 9,226 2,523

2023 16,895 237 3,364 245 2,316 280 5,680 259 9,173 2,523

2024 17,183 237 3,393 245 2,347 280 5,740 259 9,120 2,523

2025 17,470 237 3,426 245 2,374 280 5,800 259 9,068 2,523

2026 17,756 237 3,453 245 2,405 280 5,858 259 9,016 2,523

2027 18,042 237 3,481 245 2,436 280 5,917 259 8,964 2,523

2028 18,328 237 3,508 245 2,467 280 5,976 259 8,913 2,523

2029 18,613 237 3,536 245 2,499 280 6,035 259 8,861 2,523

2030 18,899 237 3,564 245 2,532 280 6,095 259 8,811 2,523

2031 19,185 237 3,591 245 2,564 280 6,155 259 8,760 2,523

2032 19,470 237 3,619 245 2,598 280 6,216 259 8,710 2,523

2033 19,756 237 3,646 245 2,631 280 6,277 259 8,660 2,523

2034 20,042 237 3,674 245 2,665 280 6,339 259 8,610 2,523

2035 20,328 237 3,701 245 2,700 280 6,401 259 8,561 2,523

2036 20,613 237 3,729 245 2,735 280 6,463 259 8,511 2,523

2037 20,899 237 3,756 245 2,770 280 6,526 260 8,463 2,523

2038 21,185 237 3,784 245 2,806 280 6,590 260 8,414 2,523

2039 21,470 237 3,811 245 2,842 280 6,653 260 8,366 2,523

2040 21,756 237 3,839 245 2,879 280 6,718 260 8,318 2,523
Table 7.1.6-8 Proposed Rule Program: NRLM to 500 ppm in 2007, 

Nonroad Only to 15 ppm in 2010; U.S. minus AK and HI (million gallons and ppm) 

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,087 2,283 3,065 2,454 1,878 2,918 4,943 2,641 10,715 2,871

1997 9,376 2,283 2,971 2,454 1,863 2,918 4,834 2,641 10,654 2,871

1998 9,665 2,283 2,876 2,454 1,849 2,918 4,725 2,641 10,593 2,871

1999 9,945 2,283 2,782 2,454 1,834 2,918 4,616 2,641 10,532 2,871

2000 10,238 2,283 2,687 2,454 1,820 2,918 4,507 2,641 10,471 2,871

2001 10,530 2,283 2,772 2,454 1,805 2,918 4,577 2,637 10,411 2,871

2002 10,821 2,283 2,692 2,454 1,773 2,918 4,465 2,638 10,352 2,871

2003 11,112 2,283 2,722 2,454 1,795 2,918 4,517 2,638 10,292 2,871

2004 11,403 2,283 2,741 2,454 1,813 2,918 4,554 2,639 10,233 2,871

2005 11,694 2,283 2,762 2,454 1,825 2,918 4,587 2,639 10,174 2,871

2006 11,983 2,242 2,818 2,437 1,868 2,904 4,686 2,623 10,116 2,860

2007 12,272 1,127 2,868 1,226 1,895 1,469 4,763 1,323 10,058 2,667

2008 12,562 330 2,900 361 1,921 445 4,821 394 10,000 2,530

2009 12,851 330 2,939 361 1,944 445 4,883 394 9,943 2,530

2010 13,140 152 2,986 293 1,968 343 4,954 313 9,886 2,526

2011 13,430 25 3,043 245 1,997 270 5,039 255 9,829 2,523

2012 13,721 25 3,073 245 2,023 270 5,096 255 9,772 2,523

2013 14,012 25 3,097 245 2,041 270 5,138 255 9,716 2,516

2014 14,302 17 3,121 200 2,066 259 5,187 224 9,661 2,512

2015 14,593 11 3,148 168 2,089 252 5,236 202 9,605 2,512

2016 14,881 11 3,181 168 2,109 252 5,290 202 9,550 2,512

2017 15,169 11 3,210 168 2,132 252 5,342 202 9,495 2,512

2018 15,456 11 3,234 168 2,164 252 5,398 202 9,441 2,512

2019 15,744 11 3,266 168 2,201 252 5,466 202 9,386 2,512

2020 16,032 11 3,288 168 2,226 252 5,515 202 9,333 2,512

2021 16,319 11 3,305 168 2,254 252 5,559 202 9,279 2,512

2022 16,607 11 3,335 168 2,290 252 5,625 202 9,226 2,512

2023 16,895 11 3,364 168 2,316 252 5,680 202 9,173 2,512

2024 17,183 11 3,393 168 2,347 252 5,740 202 9,120 2,512

2025 17,470 11 3,426 168 2,374 252 5,800 203 9,068 2,512

2026 17,756 11 3,453 168 2,405 252 5,858 203 9,016 2,512

2027 18,042 11 3,481 168 2,436 252 5,917 203 8,964 2,512

2028 18,328 11 3,508 168 2,467 252 5,976 203 8,913 2,512

2029 18,613 11 3,536 168 2,499 252 6,035 203 8,861 2,512

2030 18,899 11 3,564 168 2,532 252 6,095 203 8,811 2,512

2031 19,185 11 3,591 168 2,564 252 6,155 203 8,760 2,512

2032 19,470 11 3,619 168 2,598 252 6,216 203 8,710 2,512

2033 19,756 11 3,646 168 2,631 252 6,277 203 8,660 2,512

2034 20,042 11 3,674 168 2,665 252 6,339 203 8,610 2,512

2035 20,328 11 3,701 168 2,700 252 6,401 204 8,561 2,512

2036 20,613 11 3,729 168 2,735 252 6,463 204 8,511 2,512

2037 20,899 11 3,756 168 2,770 252 6,526 204 8,463 2,512

2038 21,185 11 3,784 168 2,806 252 6,590 204 8,414 2,512

2039 21,470 11 3,811 168 2,842 252 6,653 204 8,366 2,512

2040 21,756 11 3,839 168 2,879 252 6,718 204 8,318 2,512
Table 7.1.6-9 Annual Distillate Fuel Demand and Sulfur Content for the Reference Case; 

U.S. (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,136 2,284 3,072 2,455 1,960 2,902 5,032 2,640 11,071 2,859

1997 9,426 2,284 2,977 2,455 1,945 2,902 4,922 2,640 11,088 2,859

1998 9,717 2,284 2,882 2,455 1,929 2,902 4,811 2,640 10,945 2,859

1999 9,999 2,284 2,787 2,455 1,914 2,902 4,701 2,640 10,882 2,859

2000 10,293 2,284 2,691 2,455 1,899 2,902 4,590 2,640 10,819 2,859

2001 10,586 2,284 2,776 2,455 1,884 2,902 4,660 2,635 10,757 2,859

2002 10,879 2,284 2,696 2,455 1,850 2,902 4,546 2,637 10,695 2,859

2003 11,172 2,284 2,726 2,455 1,873 2,902 4,599 2,637 10,634 2,859

2004 11,465 2,284 2,745 2,455 1,892 2,902 4,637 2,637 10,573 2,859

2005 11,757 2,284 2,766 2,455 1,905 2,902 4,671 2,637 10,512 2,859

2006 12,048 2,244 2,823 2,437 1,949 2,888 4,772 2,621 10,452 2,849

2007 12,339 2,214 2,873 2,424 1,977 2,878 4,850 2,609 10,392 2,842

2008 12,629 2,214 2,904 2,424 2,005 2,878 4,909 2,609 10,332 2,842

2009 12,920 2,214 2,944 2,424 2,029 2,878 4,972 2,609 10,273 2,842

2010 13,210 2,160 2,990 2,255 2,054 2,705 5,044 2,438 10,214 2,712

2011 13,503 2,121 3,047 2,134 2,084 2,581 5,131 2,316 10,155 2,624

2012 13,795 2,121 3,077 2,134 2,111 2,581 5,188 2,316 10,097 2,624

2013 14,087 2,121 3,102 2,134 2,130 2,581 5,232 2,316 10,039 2,624

2014 14,379 2,121 3,126 2,134 2,156 2,581 5,282 2,316 9,982 2,624

2015 14,672 2,121 3,152 2,134 2,180 2,581 5,332 2,317 9,924 2,624

2016 14,961 2,121 3,186 2,134 2,200 2,581 5,386 2,317 9,867 2,624

2017 15,250 2,121 3,215 2,134 2,225 2,581 5,440 2,317 9,811 2,624

2018 15,539 2,121 3,239 2,134 2,258 2,581 5,497 2,318 9,754 2,624

2019 15,829 2,121 3,271 2,134 2,297 2,581 5,567 2,318 9,698 2,624

2020 16,118 2,121 3,293 2,134 2,323 2,581 5,617 2,319 9,643 2,624

2021 16,407 2,121 3,310 2,134 2,352 2,581 5,662 2,320 9,587 2,624

2022 16,986 2,121 3,339 2,134 2,390 2,581 5,730 2,320 9,532 2,624

2023 17,275 2,121 3,369 2,134 2,417 2,581 5,786 2,321 9,478 2,624

2024 17,564 2,121 3,398 2,134 2,449 2,581 5,847 2,321 9,423 2,624

2025 17,852 2,121 3,431 2,134 2,478 2,581 5,909 2,321 9,369 2,624

2026 18,139 2,121 3,458 2,134 2,510 2,581 5,968 2,322 9,315 2,624

2027 18,426 2,121 3,486 2,134 2,542 2,581 6,028 2,322 9,262 2,624

2028 18,714 2,121 3,514 2,134 2,575 2,581 6,089 2,323 9,209 2,624

2029 19,001 2,121 3,541 2,134 2,608 2,581 6,150 2,324 9,156 2,624

2030 19,575 2,121 3,569 2,134 2,642 2,581 6,211 2,324 9,103 2,624

2031 19,288 2,121 3,596 2,134 2,676 2,581 6,273 2,325 9,051 2,624

2032 19,575 2,121 3,624 2,134 2,711 2,581 6,335 2,325 8,999 2,624

2033 19,863 2,121 3,651 2,134 2,746 2,581 6,497 2,326 8,947 2,624

2034 20,150 2,121 3,679 2,134 2,781 2,581 6,460 2,326 8,896 2,624

2035 20,437 2,121 3,707 2,134 2,817 2,581 6,524 2,327 8,845 2,624

2036 20,724 2,121 3,734 2,134 2,854 2,581 6,588 2,328 8,794 2,624

2037 21,012 2,121 3,762 2,134 2,891 2,581 6,652 2,328 8,744 2,624

2038 21,299 2,121 3,789 2,134 2,928 2,581 6,717 2,329 8,694 2,624

2039 21,586 2,121 3,817 2,134 2,966 2,581 6,783 2,329 8,644 2,624

2040 21,873 2,121 3,844 2,134 3,004 2,581 6,849 2,330 8,594 2,624
Table 7.1.6-10 Annual Distillate Fuel Demand and Sulfur Content: Final NRLM Rule: 

U.S. (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,136 2,284 3,072 2,455 1,960 2,902 5,032 2,640 11,071 2,859

1997 9,426 2,284 2,977 2,455 1,945 2,902 4,922 2,640 11,088 2,859

1998 9,717 2,284 2,882 2,455 1,929 2,902 4,811 2,640 10,945 2,859

1999 9,999 2,284 2,787 2,455 1,914 2,902 4,701 2,640 10,882 2,859

2000 10,293 2,284 2,691 2,455 1,899 2,902 4,590 2,640 10,819 2,859

2001 10,586 2,284 2,776 2,455 1,884 2,902 4,660 2,635 10,757 2,859

2002 10,879 2,284 2,696 2,455 1,850 2,902 4,546 2,637 10,695 2,859

2003 11,172 2,284 2,726 2,455 1,873 2,902 4,599 2,637 10,634 2,859

2004 11,465 2,284 2,745 2,455 1,892 2,902 4,637 2,637 10,573 2,859

2005 11,757 2,284 2,766 2,455 1,905 2,902 4,671 2,637 10,512 2,859

2006 12,048 2,242 2,823 2,435 1,949 2,886 4,772 2,620 10,452 2,849

2007 12,339 1,130 2,873 1,228 1,977 1,500 4,850 1,340 10,392 2,662

2008 12,629 335 2,904 364 2,005 512 4,909 425 10,332 2,529

2009 12,920 335 2,944 364 2,029 512 4,972 425 10,273 2,529

2010 13,210 157 2,990 178 2,054 242 5,044 204 10,214 2,420

2011 13,503 30 3,047 46 2,084 49 5,131 47 10,155 2,343

2012 13,795 30 3,077 46 2,111 49 5,188 47 10,097 2,343

2013 14,087 30 3,102 46 2,130 49 5,232 47 10,039 2,343

2014 14,379 19 3,126 61 2,156 36 5,282 51 9,982 2,337

2015 14,672 11 3,152 71 2,180 27 5,332 53 9,924 2,333

2016 14,961 11 3,186 71 2,200 27 5,386 53 9,867 2,333

2017 15,250 11 3,215 71 2,225 27 5,440 53 9,811 2,333

2018 15,539 11 3,239 71 2,258 27 5,497 53 9,754 2,333

2019 15,829 11 3,271 71 2,297 27 5,567 53 9,698 2,333

2020 16,118 11 3,293 71 2,323 27 5,617 53 9,643 2,333

2021 16,407 11 3,310 71 2,352 27 5,662 53 9,587 2,333

2022 16,697 11 3,339 71 2,390 27 5,730 53 9,532 2,333

2023 16,986 11 3,369 71 2,417 27 5,786 53 9,478 2,333

2024 17,275 11 3,398 71 2,449 27 5,847 53 9,423 2,333

2025 17,564 11 3,431 71 2,478 27 5,909 53 9,369 2,333

2026 17,852 11 3,458 71 2,510 27 5,968 53 9,315 2,333

2027 18,139 11 3,486 71 2,542 27 6,028 53 9,262 2,333

2028 18,426 11 3,514 71 2,575 27 6,089 53 9,209 2,333

2029 18,714 11 3,541 71 2,608 27 6,150 53 9,156 2,333

2030 19,001 11 3,569 71 2,642 27 6,211 53 9,103 2,333

2031 19,288 11 3,596 71 2,676 27 6,273 53 9,051 2,333

2032 19,575 11 3,624 71 2,711 27 6,335 53 8,999 2,333

2033 19,863 11 3,651 71 2,746 27 6,497 53 8,947 2,333

2034 20,150 11 3,679 71 2,781 27 6,460 52 8,896 2,333

2035 20,437 11 3,707 71 2,817 27 6,524 52 8,845 2,333

2036 20,724 11 3,734 71 2,854 27 6,588 52 8,794 2,333

2037 21,012 11 3,762 71 2,891 27 6,652 52 8,744 2,333

2038 21,299 11 3,789 71 2,928 27 6,717 52 8,694 2,333

2039 21,586 11 3,817 71 2,966 27 6,783 52 8,644 2,333

2040 21,873 11 3,844 71 3,004 27 6,849 52 8,594 2,333
Table 7.1.6-11 Annual Distillate Fuel Demand and Sulfur Content: NRLM to 500 ppm in 2007, no

15 ppm Step; U.S. (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,136 2,284 3,072 2,455 1,960 2,902 5,032 2,640 11,071 2,859

1997 9,426 2,284 2,977 2,455 1,945 2,902 4,922 2,640 11,088 2,859

1998 9,717 2,284 2,882 2,455 1,929 2,902 4,811 2,640 10,945 2,859

1999 9,999 2,284 2,787 2,455 1,914 2,902 4,701 2,640 10,882 2,859

2000 10,293 2,284 2,691 2,455 1,899 2,902 4,590 2,640 10,819 2,859

2001 10,586 2,284 2,776 2,455 1,884 2,902 4,660 2,635 10,757 2,859

2002 10,879 2,284 2,696 2,455 1,850 2,902 4,546 2,637 10,695 2,859

2003 11,172 2,284 2,726 2,455 1,873 2,902 4,599 2,637 10,634 2,859

2004 11,465 2,284 2,745 2,455 1,892 2,906 4,637 2,637 10,573 2,859

2005 11,757 2,284 2,766 2,455 1,905 2,906 4,671 2,637 10,512 2,859

2006 12,048 2,242 2,823 2,435 1,949 2,886 4,772 2,620 10,452 2,849

2007 12,339 1,130 2,873 1,227 1,977 1,502 4,850 1,340 10,392 2,662

2008 12,629 335 2,904 364 2,005 512 4,909 425 10,332 2,529

2009 12,920 335 2,944 364 2,029 512 4,972 425 10,273 2,529

2010 13,210 278 2,990 295 2,054 378 5,044 329 10,214 2,525

2011 13,503 237 3,047 245 2,084 282 5,131 260 10,155 2,522

2012 13,795 237 3,077 245 2,111 282 5,188 260 10,097 2,522

2013 14,087 237 3,102 245 2,130 282 5,232 260 10,039 2,522

2014 14,379 237 3,126 245 2,156 282 5,282 260 9,982 2,522

2015 14,672 237 3,152 245 2,180 282 5,332 260 9,924 2,522

2016 14,961 237 3,186 245 2,200 282 5,386 260 9,867 2,522

2017 15,250 237 3,215 245 2,225 282 5,440 260 9,811 2,522

2018 15,539 237 3,239 245 2,258 282 5,497 260 9,754 2,522

2019 15,829 237 3,271 245 2,297 282 5,567 260 9,698 2,522

2020 16,118 237 3,293 245 2,323 282 5,617 260 9,643 2,522

2021 16,407 237 3,310 245 2,352 282 5,662 260 9,587 2,522

2022 16,697 237 3,339 245 2,390 282 5,730 260 9,532 2,522

2023 16,986 237 3,369 245 2,417 282 5,786 260 9,478 2,522

2024 17,275 237 3,398 245 2,449 282 5,847 260 9,423 2,522

2025 17,564 237 3,431 245 2,478 282 5,909 260 9,369 2,522

2026 17,852 237 3,458 245 2,510 282 5,968 260 9,315 2,522

2027 18,139 237 3,486 245 2,542 282 6,028 261 9,262 2,522

2028 18,426 237 3,514 245 2,575 282 6,089 261 9,209 2,522

2029 18,714 237 3,541 245 2,608 282 6,150 261 9,156 2,522

2030 19,001 237 3,569 245 2,642 282 6,211 261 9,103 2,522

2031 19,288 237 3,596 245 2,676 282 6,273 261 9,051 2,522

2032 19,575 237 3,624 245 2,711 282 6,335 261 8,999 2,522

2033 19,863 237 3,651 245 2,746 282 6,497 261 8,947 2,522

2034 20,150 237 3,679 245 2,781 282 6,460 261 8,896 2,522

2035 20,437 237 3,707 245 2,817 282 6,524 261 8,845 2,522

2036 20,724 237 3,734 245 2,854 282 6,588 261 8,794 2,522

2037 21,012 237 3,762 245 2,891 282 6,652 261 8,744 2,522

2038 21,299 237 3,789 245 2,928 282 6,717 261 8,694 2,522

2039 21,586 237 3,817 245 2,966 282 6,783 261 8,644 2,522

2040 21,873 237 3,844 245 3,004 282 6,849 261 8,594 2,522
Table 7.1.6-12 Annual Distillate Fuel Demand and Sulfur Content: Proposed Rule Program: 500

ppm NRLM ppm in 2007, 15 ppm Nonroad Only in 2010; U.S. (million gallons and ppm)

Nonroad Locomotive Marine L&M Heating Oil

Year Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur Demand Sulfur

1996 9,136 2,284 3,072 2,455 1,960 2,902 5,032 2,640 11,071 2,859

1997 9,426 2,284 2,977 2,455 1,945 2,902 4,922 2,640 11,088 2,859

1998 9,717 2,284 2,882 2,455 1,929 2,902 4,811 2,640 10,945 2,859

1999 9,999 2,284 2,787 2,455 1,914 2,902 4,701 2,640 10,882 2,859

2000 10,293 2,284 2,691 2,455 1,899 2,902 4,590 2,640 10,819 2,859

2001 10,586 2,284 2,776 2,455 1,884 2,902 4,660 2,635 10,757 2,859

2002 10,879 2,284 2,696 2,455 1,850 2,902 4,546 2,637 10,695 2,859

2003 11,172 2,284 2,726 2,455 1,873 2,902 4,599 2,637 10,634 2,859

2004 11,465 2,284 2,745 2,455 1,892 2,902 4,637 2,637 10,573 2,859

2005 11,757 2,284 2,766 2,455 1,905 2,902 4,671 2,637 10,512 2,859

2006 12,048 2,242 2,823 2,435 1,949 2,888 4,772 2,621 10,452 2,849

2007 12,339 1,130 2,873 1,228 1,977 1,502 4,850 1,340 10,392 2,662

2008 12,629 335 2,904 364 2,005 512 4,909 425 10,332 2,529

2009 12,920 335 2,944 364 2,029 512 4,972 425 10,273 2,529

2010 13,210 163 2,990 295 2,054 373 5,044 326 10,214 2,525

2011 13,503 40 3,047 245 2,084 273 5,131 256 10,155 2,522

2012 13,795 40 3,077 245 2,111 273 5,188 256 10,097 2,522

2013 14,087 40 3,102 245 2,130 273 5,232 256 10,039 2,522

2014 14,379 23 3,126 200 2,156 255 5,282 223 9,982 2,516

2015 14,672 11 3,152 169 2,180 242 5,332 199 9,924 2,511

2016 14,961 11 3,186 169 2,200 242 5,386 199 9,867 2,511

2017 15,250 11 3,215 169 2,225 242 5,440 199 9,811 2,511

2018 15,539 11 3,239 169 2,258 242 5,497 199 9,754 2,511

2019 15,829 11 3,271 169 2,297 242 5,567 199 9,698 2,511

2020 16,118 11 3,293 169 2,323 242 5,617 199 9,643 2,511

2021 16,407 11 3,310 169 2,352 242 5,662 199 9,587 2,511

2022 16,697 11 3,339 169 2,390 242 5,730 199 9,532 2,511

2023 16,986 11 3,369 169 2,417 242 5,786 199 9,478 2,511

2024 17,275 11 3,398 169 2,449 242 5,847 199 9,423 2,511

2025 17,564 11 3,431 169 2,478 242 5,909 199 9,369 2,511

2026 17,852 11 3,458 169 2,510 242 5,968 199 9,315 2,511

2027 18,139 11 3,486 169 2,542 242 6,028 199 9,262 2,511

2028 18,426 11 3,514 169 2,575 242 6,089 200 9,209 2,511

2029 18,714 11 3,541 169 2,608 242 6,150 200 9,156 2,511

2030 19,001 11 3,569 169 2,642 242 6,211 200 9,103 2,511

2031 19,288 11 3,596 169 2,676 242 6,273 200 9,051 2,511

2032 19,575 11 3,624 169 2,711 242 6,335 200 8,999 2,511

2033 19,863 11 3,651 169 2,746 242 6,497 200 8,947 2,511

2034 20,150 11 3,679 169 2,781 242 6,460 200 8,896 2,511

2035 20,437 11 3,707 169 2,817 242 6,524 200 8,845 2,511

2036 20,724 11 3,734 169 2,854 242 6,588 200 8,794 2,511

2037 21,012 11 3,762 169 2,891 242 6,652 200 8,744 2,511

2038 21,299 11 3,789 169 2,928 242 6,717 201 8,694 2,511

2039 21,586 11 3,817 169 2,966 242 6,783 201 8,644 2,511

2040 21,873 11 3,844 169 3,004 242 6,849 201 8,594 2,511
Final Regulatory Support Document

7-86

7.2 Refining Costs

The most significant cost involved in providing diesel fuel meeting more stringent sulfur

standards is the cost of removing the sulfur at the refinery. In this section, we describe the

methodology used and present the estimated costs for refiners to:

• comply with the 2007 Nonroad, Locomotive, and Marine (NRLM) 500 ppm diesel fuel sulfur

standards and the 15 ppm nonroad diesel fuel standard in 2010 and the 15 ppm L&M

standard in 2012, 

• comply with other NRLM diesel fuel sulfur sensitivity cases considered, and 

• comply with the 2006 sulfur standards already adopted for highway diesel fuel (an update of

a previous cost analysis).

Finally, we compare our estimated costs with those developed by Mathpro (for the Engine

Manufacturers Association) and Baker and O’Brien (for the American Petroleum Institute). 

7.2.1 Methodology

7.2.1.1 Overview

This section describes the methodology used to estimate the refining cost of reducing diesel

fuel sulfur content. Costs are estimated based on two distinct desulfurization technologies:

conventional hydrotreating and the Process Dynamics IsoTherming process. Conventional

hydrotreating cost estimates were based on information from two vendors, while the cost

estimates for the more advanced process was made from information provided by the respective

vendor. For both technologies, costs are estimated for each U.S. refinery currently producing

distillate fuel. Conventional hydrotreating technology was projected to be used to desulfurize

distillate to meet a 500 ppm sulfur cap. A mix comprised of advanced desulfurization

technology with some conventional hydrotreating technology was projected to be used to meet

the 15 ppm sulfur cap. This mix of technology varied depending on the timing of the 15 ppm

sulfur standard. To meet the 500 ppm and 15 ppm sulfur standards, refiners are expected to

desulfurize to 340 ppm and 7 ppm, respectively.

Refining costs were developed for revamping existing hydrotreaters that produce low-sulfur

diesel fuel, as well as new, grass roots desulfurization units. The lower revamped costs were

primarily used when streams or parts of streams were already desulfurized (i.e., highway), while

the grassroots costs applied normally for untreated streams (mostly nonroad). In both cases,

costs were developed for our refinery cost model and used to estimate the desulfurization cost

for each refinery in the United States producing distillate fuel in 2001. These refinery-specific

costs consider the volume of distillate fuel produced, the composition of this distillate fuel, and

the location of the refinery (e.g., Gulf Coast, Rocky Mountain region, etc.). The estimated

composition of each refinery’s distillate included the fraction of hydrotreated and

nonhydrotreated straight-run distillate, light cycle oil (LCO), other cracked stocks (coker,

visbreaker, thermal cracked) and hydrocracked distillate, and the cost to desulfurize each of

those stocks. The cost information provided by the various vendors was used to develop the

desulfurization cost for each blendstock; however, when lacking, engineering judgment was used

to develop the needed specific cost estimate. The average desulfurization cost for each refinery
Estimated Costs of Low-Sulfur Fuels

7-87

was based on the volume-weighted average of desulfurizing each of those blendstocks. The

production volumes used were those indicative of 2014, a midyear of the estimated 15 year

project life of the year 2007 capital investments by the refining industry. 

7.2.1.2 Basic Cost Inputs for Specific Desulfurization Technologies

To obtain a comprehensive basis for estimating the cost of desufurizing diesel fuel, over the

past few years we have held meetings with a large number of vendors of desulfurization

technologies. These firms include: Criterion Catalyst, UOP, Akzo Nobel, Haldor Topsoe, and

Process Dynamics. We have also met with numerous refiners of diesel fuel considering the use

of these technologies and reviewed the literature on this subject. The information and estimates

described below represent the culmination of these efforts. See Chapter 5 of the RIA for a more

complete discussion of conventional hydrotreating and Process Dynamics Isotherming, as well

as other desulfurization technologies evaluated in the course of this rulemaking.

The information used in our refinery cost model for estimating the cost of meeting 500 and

15 ppm sulfur caps using conventional hydrotreating is presented first. The cost methodology

for conventional hydrotreating was developed for the HD2007 rulemaking for highway diesel

fuel. Only the final process-design parameters are presented here. For a complete description of

the methodology used to develop the cost estimates for conventional hydrotreating, consult

Chapter 5 of the HD2007 Regulatory Impact Analysis.15 The few variations from the HD2007

methodology are described below.

Next we present the methodology and resulting cost information used for developing the

refinery costs for the Process Dynamics IsoTherming processs. In this case, we begin by

presenting the estimates of the process-design parameters provided by the developers of this

process. These projections are then evaluated to produce sets of process-design parameters that

can be used to estimate the cost of meeting 500 ppm and 15 ppm NRLM diesel fuel standards for

each domestic refiner. The resulting refining cost projections are presented and discussed in

Section 7.2.2.

7.2.1.2.1 Conventional Desulfurization Technology

The cost of desulfurizing diesel fuel includes the capital cost related to designing and

constructing the desulfurization unit, as well as the cost of operating the unit. We were able to

obtain fairly complete sets of such process-design parameters from two out of the five or six

licensors of conventional desulfurization technologies16,17,18. These designs addressed the

production of 15 ppm diesel fuel by retrofitting existing hydrotreaters originally designed to

produce 500 ppm diesel fuel, as well as building new, grass roots units. These two sets of

process-design parameters were also used to estimate the cost of hydrotreating high-sulfur diesel

fuel down to 500 ppm.

In addition to the information obtained from these two vendors, we reviewed similar

information submitted to the National Petroleum Council (NPC) by Akzo Nobel, Criterion,

Haldor Topsoe, UOP and IFP for its study of diesel fuel desulfurization costs and discussed them
Final Regulatory Support Document

7-88

with the vendors.19 These submissions were generally not as comprehensive as those provided

by the two vendors mentioned above. In all cases, these submissions corroborated the costs from

the two vendors.

All the vendors identified operating pressures sufficient to produce fuel meeting a 15 ppm

sulfur cap under 900 psi. Most of the vendors projected that 650 psi is sufficient, while others

indicated that pressures well below 1000 psi are sufficient. A contractor for API indicated that

they believe a 850 psi unit is enough to meet a 15 ppm cap, though lower-pressure units would

not be sufficient. We therefore based our estimate of capital cost on two different vendor

submissions based on units operating at 650 and 900 psi.

Based on the information obtained from the two vendors of conventional hydrotreating

technologies, as well as that obtained from Process Dynamics, we project that refiners will use

conventional hydrotreating to produce NRLM diesel fuel meeting the 500 ppm standard in 2007. 

This unit would include heat exchangers, a fired pre-heater, a reactor, a hydrogen compressor

and a make up compressor, and both high-pressure and low-pressure strippers. The refinery

would also need a source of new hydrogen, an amine scrubber and a sulfur plant. Most refineries

already have sources of hydrogen, an amine scrubber and a sulfur plant. However, considering

the hydrogen demand for complying with Tier 2 sulfur standards for gasoline and the 15 ppm

cap on highway diesel sulfur, no residual refinery production hydrogen is expected to exist. We

therefore project that any new hydrogen demand will likely be produced from the addition of a

new steam reforming hydrogen plant using natural gas as the feedstock, either on-site or by a

third party. Likewise, a refinery’s amine scrubber and sulfur plant would need modest

expansion.

Producing diesel fuel meeting a 15 ppm standard generally requires much greater reactor

volume and a larger hydrogen capacity, both in terms of compressor capacity and ability to

introduce this hydrogen into the reactor, than are required to meet a 500 ppm cap. Since the 15

ppm sulfur cap for nonroad diesel fuel follows the 500 ppm NRLM sulfur cap by only three

years and L&M by 5 years, we project that refiners will design any new hydrotreaters built for

2007 to be easily retrofitted with additional equipment, such as a second reactor, a hydrogen

compressor, a recycle scrubber, an inter-stage stripper and other associated process hardware. 

The technical approach described by each vendor to achieve a 15 ppm sulfur cap (average level

of 7-8 ppm) is summarized in Table 7.2.1-1.
Estimated Costs of Low-Sulfur Fuels

7-89

Table 7.2.1-1

Modifications Necessary to Reduce 500 ppm Sulfur Levels to 15 ppm

Diesel Fuel

Sulfur Level

Vendor A Vendor B

7-8 ppm 

(15 ppm cap)

Change to a more active catalyst

Install recycle gas scrubber 

Modify compressor

Install a second reactor, high pressure (900 psi)

Use existing hot oil separator for inter-stage

stripper 

Change to a more active catalyst

Install a recycle gas scrubber

Install a second reactor (650 psi) 

Install a color reactor 

Install an interstage stripper

It is important to note that back when the highway rulemaking was being promulgated, the

vendors of conventional hydrotreating technology believed that a high pressure interstage

stripper was needed for each hydrotreating unit to meet the 15 ppm sulfur cap standard, and

included the costs for such a unit in their cost estimates. However, since that time the vendors

are no longer recommending that the 15 ppm hydrotreaters include such a stage in the

desulfurization process thus negating the need for the associated piece of capital. Our costs

estimates are nevertheless still based on the vendor capital cost estimates which include the

interstage stripper. Thus, the capital costs on which this rulemaking is based are, with respect to

this single factor, somewhat conservative compared to the costs which refiners would likely

incur to comply with the 15 ppm sulfur standard.

The vendors assumed that the existing highway desulfurization unit in place could be utilized

(revamped) to comply with the 15 ppm sulfur standards. This includes hydrotreater sub-units

necessary for desulfurization. Revamping the highway unit saves on both capital and operating

costs for a two-stage revamp compared with whole new grassroots unit. These sub-units include

heat exchangers, a heater, a reactor filled with catalyst, two or more vessels used for separating

hydrogen and any light ends produced by cracking during the desulfurization process, a

compressor, and sometimes a hydrogen recycle gas scrubber. The desulfurization subunits listed

here are discussed in detail in Chapter 5.

To estimate the cost of meeting the NRLM diesel fuel sulfur standards, it was necessary to

evaluate three situations refiners may face: (1) producing NRLM diesel fuel meeting a 15 ppm

cap from diesel fuel already being hydrotreated to meet a 500 ppm cap (i.e., a highway revamp),

(2) producing NRLM diesel fuel meeting a 15 ppm cap from high-sulfur distillate (i.e., grass

roots 15 ppm hydrotreater), and (3) producing 15 ppm NRLM diesel fuel meeting a 500 ppm cap

by replacing the existing hydrotreater with a grass roots 15 ppm hydrotreater. Sets of processdesign parameters for the first two of these desulfurization configurations were developed for the

HD2007 rule and summarized in the Regulatory Impact Analysis.20 As discussed above, only

the results of the previous derivations are presented below. The third configuration was not

addressed for the highway diesel fuel rule, as highway diesel fuel was already meeting a 500

ppm cap. The section that develops the process-design parameters for this third configuration

includes a short description of the methodology used in its development, as it is very similar to

those used to develop the first two sets of process-design parameters.
Final Regulatory Support Document

W Capital costs are also affected, as a higher starting sulfur level requires a larger reactor to provide a greater

residence time to remove the sulfur and a larger compressor for the greater volume of hydrogen which must be fed to

the reactor.

7-90

One straightforward adjustment was made to all the capital costs developed for the HD2007

rule. The capital costs developed for that rule were in terms of 1999 dollars. These costs were

updated to represent 2002 dollars by increasing them by 2.5 percent to reflect inflation in

construction costs occurring between 1999 and 2002.21

7.2.1.2.1.1 Revamping to Process 500 ppm Diesel Fuel to Meet a 15 ppm Cap

The process-design projections developed in this section apply to a revamp of an existing

desulfurization unit with additional hardware to enable the combined older and new unit to meet

a 15 ppm sulfur cap. The portion of these projections that apply to operating costs are also

relevant if a refiner decides to replace an existing diesel fuel desulfurization unit with a new

grassroots unit. In this case, the entire capital cost of the grass roots unit is incurred. However,

the incremental operating costs would be those of the new grass roots unit, less those of the

existing hydrotreater (which are developed in this section).

The process-design parameters shown below were taken directly from those shown in the

HD2007 Regulatory Impact Analysis, with two adjustments. The first adjustment relates to the

amount of desulfurization required from the current low sulfur diesel pool, while the second

adjustment relates to the amount of fuel gas consumed in the process. 

Diesel fuel complying with the current 500 ppm sulfur standard typically contains 340 ppm

sulfur. We expect refiners complying with the 500 ppm NRLM diesel fuel sulfur cap also to

desulfurize down to roughly 340 ppm sulfur. Thus, in revamping an existing 500 ppm

hydrotreater to comply with a 15 ppm cap, refiners will have to desulfurize from about 340 ppm

down to 7 ppm. This is analogous to what we assumed in the analysis for the HD2007 rule. 

After the highway diesel fuel rule was finalized, however, it became evident that the vendor

projections assumed a starting sulfur level of 500 ppm and not 340 ppm. Thus, the vendor

projections assumed more desulfurization would be needed than is the case here. Based on a

curve of hydrogen consumption versus initial and final sulfur level developed in the Regulatory

Impact Analysis supporting the proposed HD2007 program, reducing the initial sulfur level from

500 ppm to 340 ppm reduces hydrogen consumption by 3.5 percent.22 We assumed that all costrelated parameters (capital cost,W catalyst cost, yield losses, and utilities) will be reduced by the

same 3.5 percent. 

For the second adjustment, the fuel gas rates were adjusted to account for the heat produced

by the saturation of the aromatic compounds that occurs during desulfurization. In the Draft RIA

for the NPRM, we presumed that the highly aromatic blendstocks, which are LCO and coker,

would consume more fuel gas than straight run distillate, which has much less aromatics. 

However, because the aromatic compounds are exothermic in the hydrotreating reactor, they

actually contribute some heat which lowers the heat load compared to straight run distillate. 

Furthermore, when updating the fuel gas consumption values, we found and corrected an error in
Estimated Costs of Low-Sulfur Fuels

7-91

our interpretation of fuel gas consumption information from one of the two vendors which

provided us with the unit operations information for their diesel fuel desulfurization technology. 

The error was that we had interpreted that vendor’s information to read as thousands of British

thermal units (BTUs) per day instead of millions of BTUs per day.

Some of the information from one of the two vendors (which was referred to as Vendor A in

the 2007 Highway Final Rule) was used to estimate the relative heat demand for the two mixed

distillate streams. The heat demand information was presented as million BTU per hour a

25,000 bbl/day grassroots unit producing 15 ppm diesel. We converted this estimate to BTU/bbl

and summarized the values in Table 7.2.1-2. 

Table 7.2.1-2

Fuel Gas Demand for a 15 ppm Grassroots Unit (BTU/bbl)

67% cracked stocks, 33% SR 1100

20% cracked stocks, 80% SR 1480

The above table shows a 380 btu/bbl difference in heat consumption between the two feeds

for a grassroots unit. Based on this information, we were able to estimate that cracked stocks

require only 56 percent of the heat input of straight run stocks. The fuel gas consumption

estimate for the cracked stocks (LCO and coker light gas oil) is 920 btu/bbl while the fuel gas

consumption for straight run gas oil is 1640 btu/bbl. Since this is the heat consumption for only

Vendor A, it was necessary to merge the fuel gas consumption information from Vendor B. 

Vendor B reported fuel gas consumption of 16,000 btu/bbl. This value is much higher probably

because it incorporates the fuel gas used to generate steam for pumping. Because both vendors

were providing cost estimates on the same feeds (69 percent straight run 31 percent cracked

stocks) to achieve the same desulfurization target, it is likely that both were assuming similar

levels of aromatics saturation, thus we assume that both vendors would estimate a similar

absolute difference in heat consumption between the different blendstocks. To estimate an

average heat consumption representing the heat consumption estimates from both vendors, we

averaged the average heat for the two vendors (assuming an average of 1320 btu/bbl for Vendor

A) resulting in an average heat consumption of 8660 btu/bbl. Assuming that the heat consumed

by each blendstock maintains the same differential as that calculated based on Vendor A’s

information alone, the heat consumed is 8880 btu/bbl for straight run and 8160 for cracked

stocks which maintains the same 720 btu/bbl difference from above.

Since we need to estimate the incremental fuel gas demand for a unit treating diesel fuel

meeting a 500 ppm cap standard to comply with a 15 ppm cap standard for this section, the fuel

consumption information from Vendors A and B was evaluated for this sulfur reduction

increment. Both vendors show essentially zero fuel gas consumption for this interval, yet

aromatics are still being saturated similar to about half the increment of going from untreated to

15 ppm sulfur. Thus, half the difference in fuel gas consumed for cracked stocks and straight run

was assumed for this interval with a typical blend of diesel fuel (69 percent straight run and 31
Final Regulatory Support Document

7-92

percent cracked stocks) having a zero net fuel gas consumption. Thus, cracked stocks are

estimated to require -250 btu/bbl of fuel gas and straight run is estimated to require 110 btu/bbl

of fuel gas for a difference of 360 scf/bbl or half of that for a grassroots unit. 

Table 7.2.1-3 presents the process-design parameters for desulfurizing 500 ppm sulfur diesel

fuel to meet a 15 ppm standard.

Table 7.2.1-3

Process Projections for Revamping an Existing Diesel Fuel Hydrotreater Desulfurizing 

Diesel Fuel Blendstocks from 500 ppm Cap to 15 ppm Cap

Straight-Run Other Cracked Stocks Light Cycle Oil

Capacity (BPSD) 25,000 25,000 25,000

Capital Cost (ISBL) ($million) 16 19 22

Liquid Hour Space Velocity (hr-1) 1.25 0.7 0.6

Hydrogen Consumption (scf/bbl) 96 230 375

Electricity (kW-hr/bbl) 0.4 0.7 0.8

HP Steam (lb/bbl) - - -

Fuel Gas (BTU/bbl) 110 -250 -250

Catalyst Cost ($/BPSD) 0.2 0.4 0.5

Yield Loss (wt%)

Diesel

Naphtha

LPG

Fuel Gas

1.0

-0.7

-0.04

-0.04

1.9

-1.3

-0.07

-0.11

2.1

-1.4

-0.08

-0.13

7.2.1.2.1.2 Process-Design Projections for a Grassroots Unit Producing 15 ppm Fuel

The process-design parameters presented in this section were taken directly from those

derived in the HD2007 Regulatory Impact Analysis. These costs apply primarily to refineries

currently producing only, or predominantly, high-sulfur diesel fuel. In addition, the capital cost

portion of these costs apply to a refinery replacing an existing hydrotreater with a grassroots unit

instead of revamping their existing hydrotreater. In this case, these refiners would incur the

capital costs outlined here, but their operating costs would be based on a revamp, as described

above. Most refineries currently producing high-sulfur distillate fuel also produce some

highway diesel fuel. In this case, we project costs reflecting those of a revamp and a grass roots

unit. The methodology for this merging of the two costs is described in Section 7.2.1.5 below.

Table 7.2.1-4 presents the process-design parameters for desulfurizing high-sulfur distillate

fuel to meet a 15 ppm standard in a grassroots unit.
Estimated Costs of Low-Sulfur Fuels

7-93

Table 7.2.1-4

Process Projections for Installing a New Grassroots Unit for Desulfurizing

Untreated Distillate Fuel Blendstocks to Meet a 15 ppm Standard

Straight-Run Other Cracked Stocks Light Cycle Oil

Capacity BPSD

(bbl/day)

25,000 25,000 25,000

Capital Cost (ISBL)

(MM$)

32 38 43

Liquid Hour Space Velocity

(Hr-1) 

0.8 0.5 0.4

Hydrogen Consumption

(SCF/bbl)

240 850 1100

Electricity

(KwH/bbl)

0.6 1.1 1.2

HP Steam

(Lb/bbl)

---

Fuel Gas

(BTU/bbl)

8880 8160 8160

Catalyst Cost

($/BPSD)

0.3 0.6 0.8

Yield Loss (%)

Diesel

Naphtha

LPG

Fuel Gas

1.5

-1.1

-0.06

-0.06

2.9

-2.0

-0.11

-0.17

3.3

-2.3

-0.12

-0.20

Unlike processing highway diesel fuel, which is assumed to contain 340 ppm sulfur, the

sulfur content of high-sulfur distillate fuel can vary dramatically from refinery to refinery and

region to region. To account for varying starting sulfur levels, an adjustment in hydrogen

consumption. The basis for the amount of sulfur needing to be removed is that the starting feed,

comprised of 69 percent straight-run, 23 percent LCO and 8 percent cracked stocks, contains

9000 ppm sulfur (0.9 weight percent). However, as described below in Section 7.2.1.3, the

average concentration of sulfur in the overall distillate pool, and especially the untreated part of

the pool, varies by PADD. After estimating this sulfur level, we adjusted the hydrogen

consumption for this varying sulfur level. (According to Vendor B, removing sulfur from diesel

fuel consumes 125 scf/bbl for each weight percent of sulfur removed.23) We did not adjust the

hydrogen consumption for the other qualities, mono- and poly-aromatics and olefins, but

assumed that the hydrogen consumption from saturating olefins and aromatics, or from breaking

aromatic rings would depend more on whether the feedstock had been previously hydrotreated or

not, and less on whether the starting sulfur level was 5000 or 8000 ppm. Since sulfur removal

consumes less than half the hydrogen of desulfurizing from untreated 9000 ppm sulfur
Final Regulatory Support Document

X Much of the hydrogen consumption is due to the saturation of olefins, or partial saturation of aromatics.

7-94

feedstocks to 15 ppm,X the adjustment is always less than 50 percent. The adjustment is applied

as an adjustment ratio to each untreated blendstock type for a refinery with a distillate

hydrotreater. The adjustment ranged from 0.80 for PADD 5, which has an estimated untreated

distillate sulfur level of 3010 ppm, to 1.0 for PADD 3, which has an estimated untreated

distillate sulfur level of 9,350 ppm. No adjustment was necessary for the already hydrotreated

part of the distillate pool since this subpool is always assumed to contain 340 ppm sulfur.

For refineries without a distillate hydrotreater, our adjustment to account for differing

starting sulfur levels assumes that they currently blend only unhydrotreated blendstocks into the

distillate that comprises the high-sulfur pool. Thus, we are making our adjustments based on a

lower starting sulfur level. Our adjustment for these refineries ranged from 0.79 for PADD 4,

which has an estimated untreated sulfur level of 2550 ppm, to 0.83 for PADD 3, which has a

starting sulfur level of 3780 ppm. The various hydrogen consumption adjustment values are

summarized in Table 7.2.1-5.

Table 7.2.1-5

Hydrogen Consumption Adjustment Factors: Grassroots Units

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5

Refinery with Distillate HT 0.84 0.89 1.0 0.81 0.80

No Distillate HT 0.80 0.80 0.83 0.79 0.79

7.2.1.2.1.3 Desulfurizing High-Sulfur Distillate Fuel to a 500 ppm Cap

Finally, we needed to provide inputs for our cost model for desulfurizing untreated, highsulfur distillate to meet a 500 ppm sulfur standard, which is the first step of our two-step

program. These inputs are estimated by simply subtracting the inputs for the revamped unit for

desulfurizing 500 ppm diesel fuel down to 15 ppm from the inputs for a grassroots unit for

desulfurizing untreated diesel fuel down to 15 ppm. The untreated to 500 ppm inputs for our

refinery cost model are summarized in Table 7.2.1-6.
Estimated Costs of Low-Sulfur Fuels

7-95

Table 7.2.1-6

Process Projections for Installing a New Unit for Desulfurizing

Untreated Diesel Fuel Blendstocks to Meet a 500 ppm Sulfur Standard

Straight-Run Coker Distillate Light Cycle Oil

Capacity BPSD

(bbl/day)

25,000 25,000 25,000

Capital Cost (ISBL)

(MM$)

15 18 21

Liquid Hour Space Velocity

(Hr-1)

2.4 1.9 1.3

Hydrogen Consumption

(SCF/bbl)

144 620 725

Electricity

(KwH/bbl)

0.2 0.4 0.4

HP Steam

(Lb/bbl)

---

Fuel Gas

(BTU/bbl)

8770 8410 8410

Catalyst Cost

($/BPSD)

0.1 0.2 0.3

Yield Loss (%) 

Diesel

Naphtha

LPG

Fuel Gas

0.5

-0.4

-0.02

-0.02

1.1

-0.7

-0.04

-0.06

1.2

-0.8

-0.04

-0.07

Again, a hydrogen consumption adjustment was made for starting sulfur levels that differ

from 9000 ppm. In this case, the hydrogen adjustment ended up being larger than the grassroots

desulfurization unit as the adjustment to the hydrogen consumption for going from untreated to

500 ppm comprises a larger percentage of the total hydrogen consumption. This adjustment is

for a refinery with a distillate hydrotreater. The adjustment is applied as an adjustment ratio to

each unhydrotreated blendstock type and it ranged from 0.69 for PADD 5, which has an

estimated untreated distillate sulfur level of 3010 ppm, to 1.0 for PADD 3, which has an

estimated untreated distillate sulfur level of 9,350 ppm. No adjustment was necessary for the

already hydrotreated part of the distillate pool since this subpool is always assumed to contain

340 ppm sulfur.

For refineries without a distillate hydrotreater, our analysis does not assume that they

currently hydrotreat any of the distillate that comprises the high-sulfur pool. Thus, we estimate a

somewhat lower starting sulfur level. Our adjustment for these refineries ranged from 0.67 for

PADD 4, which has an estimated untreated sulfur level of 2550 ppm, to 0.73 for PADD 3, which
Final Regulatory Support Document

7-96

has a starting sulfur level of 3780 ppm. The various hydrogen consumption adjustment values

are summarized in Table 7.2.1-7.

Table 7.2.1-7

Hydrogen Consumption Adjustment Factors: High Sulfur to 500 ppm

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5

Refinery with Distillate HT 0.75 0.83 1.0 0.70 0.69

No Distillate HT 0.69 0.69 0.73 0.67 0.67

7.2.1.2.1.4 Hydrocrackate Processing and Tankage Costs

We believe refineries with hydrocrackers will have to invest some capital and incur some

operating costs to ensure that recombination reactions at the exit of the second stage of their

hydrocracker do not cause the diesel fuel being produced by their hydrocracker to exceed the

standard. The hydrocracker is a very severe hydrotreating unit capable of hydrotreating its

product from thousands of ppm sulfur to nearly zero ppm sulfur; however, hydrogen sulfide

recombination reactions that occur at the end of the cracking stage, and fluctuations in unit

operations, such as temperature and catalyst life, can result in the hydrocracker diesel product

having up to 30 ppm sulfur in its product stream.24 25 Thus, refiners may need to install a

finishing reactor for the diesel stream produced by the hydrocracker. According to vendors, this

finishing reactor is a low-temperature, low-pressure hydrotreater that can desulfurize the simple

sulfur compounds formed in the cracking stage of the hydrocracker.

Additionally, since the 15 ppm diesel sulfur standard is very stringent, we take into account

tankage that will likely be needed. We believe refiners could store high-sulfur batches of

highway diesel fuel or nonroad diesel fuel during a shutdown of the diesel fuel hydrotreater. 

Diesel fuel production would cease in the short term, but the rest of the refinery could remain

operative. To account for this, we provided for the cost of installing a tank that would store ten

days of 15 ppm sulfur diesel production, sufficient for a ten-day emergency turnaround, which is

typical for the industry; the estimated cost for a 270,000 barrel storage tank is $3 million.26 The

cost of the land needed for this tank is assumed to be negligible relative to the cost of the tank. 

This amount of storage should be adequate for most unanticipated turnarounds. We presumed

that each refinery will need to add such storage, though for some refineries, off-spec diesel fuel

could also be sold as high-sulfur heating oil or fuel oil.

The cost inputs for the storage tank and the finishing reactor are summarized in Table 7.2.1-

8.
Estimated Costs of Low-Sulfur Fuels

7-97

Table 7.2.1-8

Process Operations Information for Additional

Units used in the Desulfurization Cost Analysis

Diesel 

Storage Tank

Distillate Hydrocracker 

Post Treat Reactor

Capacity 50,000 bbls 25,000 (bbl/day)

Capital Cost

(MM$)

0.75 5.727

Electricity

(KwH/bbl

— 0.98

HP Steam

(Lb/bbl)

— 4.2

Fuel Gas

(BTU/bbl)

— 18

Cooling Water

(Gal/bbl)

— 5

Operating Cost

($/bbl)

nonea

 see above

a

 No operating costs are estimated directly; however both the ISBL to OSBL factor and the capital contingency

factor used for desulfurization processes is used for the tankage as well, which we believe to be excessive

for storage tanks so it is presumed to cover the operating cost.

Refiners will also likely invest in a diesel fuel sulfur analyzer.28 A sulfur analyzer at the

refinery provides nearly real-time information regarding the sulfur levels of important streams in

the refinery and facilitate operational modifications to prevent excursions above the sulfur cap. 

Based on information from a manufacturer of such an analyzer, the analyzer costs about $50,000,

with an additional $5,000 estimated for installation.29 Compared with the capital and operating

cost of desulfurizing diesel fuel, the cost for this instrumentation is far below 1 percent of the

total cost of this program. Because the cost is so small, the cost of an analyzer was assumed

covered as a cost contingency described in Section 7.2.1.4.1.

7.2.1.2.2 Process Dynamics IsoTherming

Process Dynamics has licensed a technology called IsoTherming, which is designed to

desulfurize both highway and non-highway distillate fuel. At our request, Process Dynamics

provided basic design parameters that can be used to project the cost of using their process to

meet tighter sulfur caps,30 which is summarized in the process information table. Subsequently,

EPA spoke to a Linde engineer responsible for implementing the IsoTherming unit at the Giant

refinery.31 The hydrogen and utility consumption information obtained earlier from Process

Dynamics was adjusted based on these comments, as described in the text further below. 
Final Regulatory Support Document

7-98

Specifically, Process Dynamics provided design parameters for a revamp of an existing

highway desulfurization unit to meet a 15 ppm standard. The revamp involves putting an

IsoTherming unit upstream of the existing highway diesel fuel hydrotreater. Thus, when

applying the Process Dynamics unit in our cost estimates for meeting the 15 ppm standard, the

new Process Dynamics unit itself is assumed to be used as a first stage. As described in more

detail in Chapter 5 of the RIA, this configuration takes the most advantage of the inherent

benefits of the Process Dynamics IsoTherming desulfurization process. 

Process Dynamics provided to EPA process information for the IsoTherming process based

on three revamp situations. In the first revamp design, the feedstock consisted of 60 percent

straight-run and 40 percent LCO. The unhydrotreated sulfur level was just under 2000 ppm and

both the existing hydrotreater and the IsoTherming unit operated at 600 psi. In the second

design, the feedstock consisted of 60 percent straight-run, 30 percent LCO and 10 percent lightcoker gas oil with an unhydrotreated sulfur level of 9950 ppm. The existing hydrotreater and the

IsoTherming unit operated at 950 psi. In the third design, the feedstock was the same as in the

second, but the IsoTherming unit was designed to operate at 1500 psi, while the conventional

hydrotreating unit operated at 950 psi.

We largely based our cost projections for the IsoTherming process on the second design. 

The unhydrotreated sulfur level of more than 9000 ppm is more typical for most refiners than

2000 ppm. The 950 psi design pressure for the IsoTherming unit was also thought to preferable

to 1500 psi for most refiners. The higher-pressure unit reduces capital and catalyst costs, but

higher hydrogen consumption offsets much of the cost savings. The higher-pressure reactors and

compressors also have a longer delivery time and there would likely be fewer fabricators. Thus,

given that the savings associated with the higher pressure unit were small, we decided to focus

on the 950 psi design.

The information provided by Process Dynamics for the 950 psi IsoTherming desulfurization

unit is summarized in Table 7.2.1-9. The operation and product quality of the IsoTherming unit

is shown separatly from those for the existing conventional hydrotreater. Again, prior to the

revamp, the conventional hydrotreater would have processed this feedstock down to roughly 340

ppm sulfur. 
Estimated Costs of Low-Sulfur Fuels

7-99

Table 7.2.1-9

Process Dynamics IsoTherming Revamp 

Design Parameters to Produce 10 ppm Sulfur Diesel Fuel

Feed Quality IsoTherming Unit and its

Product Quality

Conventional Hydrotreater and

Final Product Quality

LCO vol % 30

Straight-Run vol % 60

Light-Coker Gas Oil vol% 10

Sulfur ppm 9950 850 10

Nitrogen 340 38 2

API gravity (degrees) 33.98 34.42 35.84

Cetane Index 44.5 48.5 50.8

H2 Consumption (scf/bbl) 320 100

Relative H2 Consumption 75 25

LHSV (hr-1) 15/15 3

Relative Catalyst Volume 45 100

Reactor Delta T 15 15

H2 Partial Pressure 950 950

Electricity (kW) 1525

Natural Gas (mmbtu/hr) 0

Steam (lb/hr) 0

7.2.1.2.2.1 Hydrotreating High-Sulfur Distillate Fuel to 15 ppm 

The design parameters provided by Process Dynamics involve the revamp of an existing

conventional hydrotreater currently producing highway diesel fuel (i.e., less than 500 ppm

sulfur) to produce diesel fuel with a sulfur level well below 15 ppm. Before addressing this

situation, however, we will use the Process Dynamics revamp design to project the costs of an

IsoTherming unit that processes unhydrotreated distillate fuel (e.g., 3400-10,000 ppm sulfur)

down to 7-8 ppm sulfur. This type of unit was not projected to be used under the two-step fuel

program. However, we considered such a sulfur reduction step for alternative programs, for

which costs are also estimated later in this chapter. 

Also, as was done for conventional hydrotreating, we develop cost estimates for applying the

IsoTherming process to three individual blendstocks—straight-run, LCO and light-coker gas

oil—to be able to project desulfurization costs for individual refineries whose diesel fuel

compositions vary dramatically.
Final Regulatory Support Document

7-100

We have broken down the derivation of the cost of a stand-alone IsoTherming unit capable of

producing 15 ppm diesel fuel into four parts: hydrogen consumption, utilities and yield losses,

catalyst cost and capital cost.

Hydrogen Consumption: In this section, we estimate the hydrogen consumption to process

individual refinery streams from their uncontrolled levels down to 7-8 ppm sulfur. Process

Dynamics provided hydrogen consumption estimates for desulfurizing a mixed feedstock of 60

percent straight-run, 30 percent LCO and 10 percent coker distillate, but not for specific refinery

streams. Additionally, Process Dynamics provided information for a hybrid desulfurization unit

comprised of a Process Dynamics IsoTherming unit revamping a conventional highway

hydrotreater. For the proposed rule, we used the hydrogen consumption values provided by

Process Dynamics to estimate the hydrogen consumption for the IsoTherming unit for the

individual diesel fuel blendstocks which we model. This information resulted in a hydrogen

consumption which was somewhat lower than that of conventional hydrotreating. After the

proposal, we asked the Linde engineers to provide their most recent estimate of the hydrogen

consumption values for the IsoTherming process based on the in-use data from their commercial

demonstration unit. The resulting hydrogen consumption estimates for the IsoTherming process

are similar to that of conventional hydrotreating. Consequently, for the final rule analysis we set

the hydrogen consumption of the Process Dynamics IsoTherming process to be the same as

conventional hydrotreating. The resulting hydrogen consumptions were 1100 scf/bbl for LCO,

850 scf/bbl for other cracked stocks, and 240 scf/bbl for straight-run.

Consistent with the methodology used for conventional hydrotreating, we developed

adjustments to each blendstock hydrogen consumption values to reflect differing unhydrotreated

sulfur levels. We assumed that the hydrogen consumption for IsoTherming process varied in the

same proportions as those for conventional hydrotreating because the treated feed sulfur levels

were about the same. Thus, the same hydrogen adjustment factors were used as for conventional

hydrotreating, and they can be found in Table 7.2.1-5 and Table7.2.1-7.

Utilities and Yield Losses: We next established the IsoTherming utility inputs for individual

blendstocks. The Process Dynamics IsoTherming process saves a substantial amount of heat

input by conserving the heat of reaction that occurs in the IsoTherming reactors. This conserved

energy is used to heat the feedstock to the unit. This differs from conventional hydrotreating that

normally rejects much of this energy to avoid coking the catalyst. According to Process

Dynamics, this allows the IsoTherming process to operate with negligible external heat input. In

the highway hydrotreater revamp, which is the source of the information provided by Process

Dynamics, the existing heater for the highway hydrotreater was hardly needed after the

IsoTherming process was added. However, there is still the need for a small heater to heat up the

feedstock during unit startup. This affects capital costs. However, when averaged over

production between start-ups (generally at least two years), the little amount of fuel used during

start-up is negligible. Thus, we estimate no need for either fuel or steam with the IsoTherming

process.

As shown in Table 7.2.1-9, Process Dynamics estimated electricity demand to be 1525

kilowatts per 20,000 bbl/day unit in their early estimate of the demands for their unit. However,
Estimated Costs of Low-Sulfur Fuels

7-101

since the commercial demonstration unit has been operating, Process Dynamics has collected

information on the actual electrical consumption of the IsoTherming unit. Process Dynamics

engineers estimate that the electrical consumption is about that same as conventional

hydrotreating. Thus, for desulfurizing untreated diesel fuel down to 15 ppm, we set the

electricity demand as the same as conventional hydrotreating. Thus, we estimate electricity

demand at 0.6, 1.1 and 1.2 kW-hr/bbl for straight-run, light-coker gas oil, and LCO, respectively.

This is a decline in electricity consumption compared to the values which Process Dynamics

reported in their original document. That the IsoTherming unit would consume the same (or

potentially less) electricity as conventional hydrotreating is reasonable considering that no

recycle compressor is needed with this technology because large excesses of hydrogen are not

fed to the IsoTherming reactor. Recycle compressors are a large electricity consumer. This

electricity savings is somewhat offset because of the increased liquid pumping demands required

to recycle the diesel fuel through the reactors. While some savings are likely, Process Dynamics

suggested we assume that the electricity costs are about the same as conventional hydrotreating. 

Process Dynamics did not estimate the specific yield losses for the IsoTherming process. On

our request for further information, Process Dynamics indicated that their process causes slightly

less than half of the yield loss of conventional hydrotreating. Thus, the yield loss of the Process

Dynamics unit was projected to be 50 percent that of conventional hydrotreating, which is

proportional to the relative catalyst volume. The resulting projected yield losses are shown in

Table 7.2.1-10 below:

Table 7.2.1-10

Estimated Yield Loss for a Process Dynamics IsoTherming Grassroots Unit

Fuel Type Straight Run Light Coker Gas Oil Light Cycle Oil

Diesel Fuel 0.75 1.45 1.65

Naphtha -0.55 -1.00 -1.15

LPG -0.03 -0.055 -0.06

Fuel Gas -0.03 -0.085 -0.10

Catalyst Costs: The catalyst cost for the Process Dynamics process was estimated based on

the relative catalyst volume compared with conventional hydrotreating. As shown in

Table 7.2.1-9, Process Dynamics indicated that the catalyst volume for the new IsoTherming

reactors contained only 45 percent of the volume of the new conventional hydrotreating reactors

that Process Dynamics projects would be needed to revamp the existing hydrotreater to produce

10 ppm fuel. We assumed that this same relationship holds for a stand-alone IsoTherming unit. 

Thus, we multiplied the catalyst costs for conventionally hydrotreating specific blendstocks

(shown in Table 7.2.1-4) by 45 percent. The resulting IsoTherming catalyst costs were 0.14,

0.27 and 0.36 $/BPSD for straight-run, light-coker gas oil and LCO, respectively.
Final Regulatory Support Document

7-102

Capital Costs: The last aspect of the IsoTherming process to be determined on a perblendstock basis is its capital cost. Process Dynamics’s initial submission of process-design

parameters did not include an estimate of the capital cost. We developed our own estimate from

the process equipment included, compared with those involved in conventional hydrotreating. 

As indicated in Table 7.2.1-9, the catalyst volume of the two IsoTherming reactors unit

(combined LHSV of 7.5) is roughly 8 times smaller than that of a conventional hydrotreating

revamp (LHSV of 0.9 per LHSVs for individual blendstocks from Table 7.2.1-4). Also, because

the IsoTherming reactors use a much higher flowrate and is a totally liquid process (no need for

both gas and liquid in the reactor), it eliminates the need for an expensive distributor. As

mentioned above, the feed pre-heater can be much smaller and less durable, since it is required

only for startup. Finally, the IsoTherming process does not require an amine scrubber to scrub

the H2S from the recycle hydrogen stream. 

Based on these differences, we estimated that the total capital cost of a stand-alone

IsoTherming unit is two-thirds that for a conventional hydrotreater. Thus, the capital costs for a

25,000 bbl per day conventional hydrotreater were reduced by one-third. The resulting

IsoTherming capital costs for a 25,000 BPSD unit were $21, $25, and $29 million for treating

straight-run, light-coker gas oil and LCO, respectively. The estimated overall capital cost for the

specific feed composition shown in Table 7.2.1-9 is $900 per BPSD for the IsoTherming unit,

versus $1400 per BPSD for a conventional hydrotreater. More recently, Linde indicated that the

capital cost will be roughly $800 per barrel for a 25,000 bbl per day unit.32 For this analysis, we

consequently retained the two-thirds factor relative to conventional hydrotreating ($900 per

BPSD). 

Summary of Process-Design Parameters: Table 7.2.1-11 summarizes the design parameters

used for using the Process Dynamics IsoTherming process to desulfurize untreated distillate fuel

to 10 ppm. 
Estimated Costs of Low-Sulfur Fuels

7-103

Table 7.2.1-11 

Process Parameters for a Stand-Alone IsoTherming 

25,000 BPSD Unit to Produce 10 ppm Sulfur Fuel from Untreated Distillate Fuel 

Straight-Run (SR) Other Cracked Stocks Light Cycle Oil (LCO)

Capital Cost ($MM) 21 25 29

Hydrogen Demand (scf/bbl) 240 850 1100

Electricity Demand (kwh/bbl) 0.6 1.1 1.2

Fuel Gas Demand (btu/bbl) 220 -500 -500

Catalyst Cost ($/bpsd) 0.15 0.29 0.44

Yield Loss (wt%): Diesel

Naphtha

LPG

Fuel Gas

0.75

-0.55

-0.03

-0.03

1.45

-1.00

-0.055

-0.085

1.65

-1.15

-0.06

-0.10

7.2.1.2.2.2 Desulfurizing 500 ppm Sulfur Diesel Fuel to Meet a 15 ppm Sulfur Cap

The derivation of process design parameters for a IsoTherming unit revamp of a conventional

hydrotreater is much more straightforward than that of a stand-alone IsoTherming unit, as the

design parameters provided by Process Dynamics in Table 7.2.1-9 were for a revamp. The

revamp would occur by placing the new Process Dynamics IsoTherming unit as a first stage

(uncontrolled to under 500 ppm), before the existing highway highway, thus converting the

highway hydrotreater to treating diesel fuel from several hundred ppm to under 15 ppm. Similar

to how we characterized the cost inputs above, we have broken down the derivation of the cost

of a stand-alone IsoTherming unit capable of producing 15 ppm diesel fuel into four parts: 

hydrogen consumption, utilities and yield losses, catalyst cost and capital cost.

Hydrogen Consumption: Determining the incremental hydrogen consumption of a Process

Dynamics IsoTherming revamp of a conventional hydrotreater requires that the existing

hydrogen consumption of the existing conventional hydrotreater be accounted for. As described

above, we now estimate that the hydrogen consumption of the Process Dynamics unit to be the

same as the conventional hydrotreating unit for the same service. Thus, there would be no

change in hydrogen consumption when the Process Dynamics unit replaces the conventional

hydrotreating unit for treating diesel fuel from uncontrolled levels down to 500 ppm sulfur. The

conventional hydrotreater’s new role would be to desulfurize 500 ppm sulfur down to 15 ppm

sulfur. The new service of the conventional hydrotreater will define the hydrogen consumption

for this Process Dynamics IsoTherming revamp of the conventional hydrotreater unit. The

hydrogen consumption of a conventional hydrotreater for treating 500 ppm diesel fuel down to

15 ppm is contained in Table 7.2.1-6 above, which is 96, 230 and 375 standard cubic feet per

minute of hydrogen for straight run, coker, and LCO, respectively. 
Final Regulatory Support Document

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Utilities and Yield Losses: The electricity consumption for a Process Dynamics IsoTherming

revamp of a conventional hydrotreater follows the same logic as that for hydrogen. Again the

Process Dynamics unit is assumed to have the same electrical demand as the conventional

hydrotreater for desulfurizing untreated diesel fuel down to 500 ppm. Thus, the incremental

electricity demand for this revamp is the electrical demand for the conventional hydrotreater in

its new 500 ppm to 15 ppm service. The electric demand of a conventional hydrotreater for

treating 500 ppm diesel fuel down to 15 ppm is contained in Table 7.2.1-6 above, which is 0.4,

0.7 and 0.8 kilowatt hours per barrel for straight run, coker, and LCO, respectively. 

Estimating fuel gas consumption for a Process Dynamics revamp of a conventional

hydrotreater is more complex because the Process Dynamics unit’s fuel gas consumption is not

the same as a conventional hydrotreater for desulfurizing undesulfurized diesel fuel down to 500

ppm. This calculation is best shown in Table 7.2.1-12. The table shows the addition of the

Process Dynamics unit for desulfurizing each undesulfurized blendstock to 500 ppm, the

subtraction of the conventional hydrotreater for the same increment of sulfur control for each

blendstock, the addition of the conventional hydrotreater now treating 500 ppm diesel fuel down

to 15 ppm for each blendstock, and the net change in fuel gas consumption. 

Table 7.2..1-12

Estimate of Fuel Gas Consumption of an IsoTherming Revamp; 500 ppm to 15 ppm

Straight Run Coker LCO

IsoTherming Unit: High Sulfur

to 500 ppm (added)

110 -250 -250

Conv. HT: High Sulfur to 500

ppm (subtracted)

8770 8410 8410

Conv. HT 500 ppm to 15 ppm

(added)

110 -250 -250

Net Fuel Gas Consumption -8550 -8910 -8910

As mentioned above, Process Dynamics did not provide estimates of yield losses for the

IsoTherming process. Using engineering judgement based on the relative exposure to the

catalyst (the Process Dynamics unit only uses 45 percent of the catalyst as a conventional

hydrotreater), we estimated that a stand-alone IsoTherming unit would reduce yield losses by 45

percent compared to a stand-alone convention hydrotreater. We applied this factor to the

conventional hydrotreater yield loss to estimate the Process Dynamics yield loss. Table 7.2.1-6

shows that the yield loss for straight run feed is 1.0 percent for a conventional hydrotreating

revamp (500 ppm to 15 ppm) and Table 7.2.1-4 shows a 1.5 percent loss for a grass roots

conventional hydrotreater (uncontrolled to 15 ppm). Thus, the original highway fuel

hydrotreater (uncontrolled to 500 ppm) has a yield loss of 0.5 percent for straight run, consistent

with that shown in Table 7.2.1-3. 
Estimated Costs of Low-Sulfur Fuels

7-105

If the IsoTherming revamp reduces the yield loss by 45 percent, its yield loss for straight run

is 55 percent of 1.5 percent, or 0.82 percent. Subtracting out the 0.5 percent loss of the original

highway hydrotreater means that the IsoTherming revamp had an incremental yield loss of 0.32

percent, or 32 percent of the 1.0 percent yield loss projected for the conventional hydrotreating

revamp. Thus, we projected that all of the yield losses shown in Table 7.2.1-13 for a

conventional hydrotreating revamp would be only 32 percent as large for an IsoTherming

revamp. 

Table 7.2.1-13

Estimated Yield Loss for a Process Dynamics IsoTherming Revamp

Fuel Type Straight Run Light Coker Gas Oil Light Cycle Oil

Diesel Fuel 0.32 0.61 0.70

Naphtha -0.22 -0.42 -0.48

LPG -0.01 -0.02 -0.03

Fuel Gas -0.01 -0.035 -0.04

Catalyst Costs: Consistent with the relative catalyst cost for a stand-alone IsoTherming unit,

we project that the catalyst cost for an IsoTherming revamp would be 45 percent of that for a

conventional hydrotreating revamp.

Capital Costs: Consistent with the relative capital cost for a stand-alone IsoTherming unit,

we project that the capital cost for an IsoTherming revamp would be 45 percent of that for a

conventional hydrotreating revamp.

Summary of Process Design Parameters: The inputs into our cost model for treating already

treated non-highway diesel fuel by the individual refinery streams which is presumed to be 340

ppm is summarized in Table 7.2.1-14.
Final Regulatory Support Document

7-106

Table 7.2.1-14

Process Projections for an IsoTherming Revamp 

of a Conventional Hydrotreater to Meet a 15 ppm Cap Standard

Straight Run (SR) Other Cracked Stocks Light Cycle Oil (LCO)

Capital Cost ($MM) 10.6 12.5 14.5

Unit Size (bbl/stream Day) 25,000 25,000 25,000

Hydrogen Demand (scf/bbl) 96 230 375

Electricity Demand (kwh/bbl) 0.4 0.7 0.8

Fuel Gas Demand (btu/bbl) -8550 -8910 -8910

Catalyst Cost ($/bpsd) 0.09 0.18 0.23

Yield Loss (wt%)

Diesel

Naphtha

LPG

Fuel Gas

0.25

-0.18

-0.01

-0.01

0.48

-0.33

-0.02

-0.03

0.55

-0.38

-0.02

-0.03

7.2.1.2.3 Characterization of Vendor Cost Estimates

Applicability to Specific Refineries: The information provided by the vendors is based on

typical diesel fuels or diesel fuel blendstocks. However, in reality, diesel fuel (especially LCO,

and to a lesser degree other cracked stocks) varies in desulfurization difficulty based on the

amount of sterically hindered compounds present in the fuel, which is determined by the

endpoint of diesel fuel, and also by the type of crude oil being refined and other unit processes. 

The vendors provided cost information based on diesel fuels with T-90 distillation points which

varied from 605 /F to 630 /F, which would roughly correspond to distillation endpoints of 655 /F

to 680 /F. These endpoints can be interpreted to mean that the diesel fuel would, as explained in

Chapter V above, contain sterically hindered compounds. Other diesel fuels or diesel fuel

blendstocks, such as a straight run diesel fuel with a lower end boiling point, are lighter and

would not contain sterically hindered compounds. However, a summer time diesel fuel survey

for 1997 shows that the endpoint of highway diesel fuel varies from 600 /F to 700 /F, thus the

lighter diesel fuels would contain no sterically hindered compounds, and the heavier diesel fuels

would contain more.33 Our analysis attempts to capture the cost for each refinery to produce

highway diesel fuel which meets the 15ppm cap sulfur standard, however, we do not have

specific information for how the highway diesel endpoints vary from refinery to refinery, or from

season to season. Similarly, we do not have information on what type of crude oil is being

processed by each refinery as the quality of crude oil being processed by a refinery affects the

desulfurization difficulty of the various diesel fuel blendstocks. Diesel fuel processed by a

particular refiner can either be easier or more difficult to treat than what we estimate depending

on how their diesel fuel endpoint compares to the average endpoint of the industry, and

depending on the crude oil used. For a nationwide analysis, we believe it is appropriate to base

our cost analysis for each refinery on what we estimate would be typical or average qualities for
Estimated Costs of Low-Sulfur Fuels

7-107

each diesel fuel blendstock. Some estimates of individual refinery costs will be high, others will

be low, but be representative on average.

Accuracy of Vendor Estimates: We have heard from refiners in the past that the vendor

costs are optimistic and need to be adjusted higher to better assess the costs. While the vendors

costs may be optimistic, we believe that there are a multitude of reasons why the cost estimates

could be optimistic and adjusting these estimates isn’t necessary.

First, in specific situations, capital costs can be lower than what the vendors project for a

generic refinery. Many refiners own used reactors, compressors, and other vessels which can be

employed in a new or revamped diesel hydrotreating unit. We do not know to what extent that

additional hydrotreating capacity can be met by employing used vessels, however, we believe

that at least a portion of the capital costs can be offset by used equipment. Additionally, the

vendors of conventional hydrotreating which provided cost estimate information for our analysis

based their capital costs on the inclusion of an interstage stripper to strip out the hydrogen

sulfide between the first and second reactor stages (see Chapter 5 of the RIA). However,

vendors today are saying that interstage strippers are not necessary. Thus, the capital costs upon

which our conventional hydrotreating costs are based are conservative, which offsets optimism

on the part of the vendors.

There are also operational changes which refiners can make to reduce the difficulty and the

cost of desulfurizing highway diesel fuel. Based on the information which we received from

vendors and as made apparent in our cost analysis which follows, refiners with LCO in their

diesel fuel would need to hydrotreat their highway diesel pool more severely resulting in a

higher cost to meet the cap standard. We believe that these refiners could potentially avoid some

or much of this higher cost by pursuing two specific options. The first option which we believe

these refiners would consider would be to shift LCO to heating oil which does not face such

stringent sulfur control. The more lenient sulfur limits which regulate heating oil provide room

for blending in substantial amounts of LCO. The refineries which could take advantage of

shifting LCO to the heating oil pool are those in the Northeast and on the Gulf Coast which have

access to the large heating oil market in the Northeast. If refiners could not shift all the LCO to

the heating oil pool because of market limitations, refiners could distill its LCO into light and

heavy fractions and only shift the heavy fraction to the heating oil pool. Essentially all of the

sterically hindered compounds distill above 630°F, so if refiners undercut their LCO to omit

these compounds, they would cut out about 30 percent of their LCO. We expect that refiners

could shift the same volume of non-LCO distillate from these other distillate pools to the NRLM

pool to maintain current production volumes of all fuels. The T-90 maximum established by

ASTM may limit the amount of LCO, and especially heavy LCO, which can be moved from

NRLM diesel fuel into the heating oil pool. Another option, of course, would be to move this

dirty distillate fraction into number 4 or number 6 marine bunker fuel. For those refineries

which could trade the heavy portion of LCO with other blendstocks in the heating oil pool from

their own refinery or other refineries, we presume that those refiners could make the separations

cheaply by using a splitting column for separating the undercut LCO from the uncracked heavy

gasoil in the FCC bottoms. 
Final Regulatory Support Document

7-108

Another option for refineries which are faced with treating LCO in its nonroad diesel fuel

would be to sell off or trade their heavy LCO to refineries with a distillate hydrocracker. This is

a viable option only for those refineries which are located close to another refinery with a

distillate hydrocracker. The refinery with the distillate hydrocracker would upgrade the

purchased LCO into gasoline or high quality diesel fuel. To allow this option, there must be a

way to transfer the heavy LCO from the refinery with the unwanted LCO to the refinery with the

hydrocracker, such as a pipeline or some form of water transport. We asked a refinery

consultant to review this option. The refinery consultant corroborated the idea, but commented

that the trading of blendstocks between refineries is a complicated business matter which is not

practiced much outside the Gulf Coast, and that the refineries with hydrocrackers that would buy

up and process this low quality LCO may have to modify their distillate hydrocrackers.34 The

modification which may be needed would be due to the more exothermic reaction temperature of

treating LCO which could require refiners to install additional quenching in those hydrocrackers. 

Additionally, LCO can demand 60 to 80 percent more hydrogen for processing than straight run

material. The refiners which could potentially take advantage of selling or trading their LCO to

these other refineries are mostly located in the Gulf Coast where a significant number of

refineries have hydrocrackers and such trading of blendstocks is common. However, there are

other refineries outside of the Gulf Coast which could take advantage of their very close location

to another refinery with a distillate hydrocracker. Examples for these refining areas where a

hydrocracker could be shared include the Billings, Montana area and Ferndale, Washington.

As we summarized in Chapter 5, catalysts are improving and expected to continue to

improve. Our costs are based on vendor submissions and incorporate the most advanced new

catalysts available at that time. However, there are several new lines of catalysts available now

which are more active than the previous lines of catalysts upon which our costs are based. As

catalysts continue to improve, the cost of desulfurizing diesel fuel will continue to decrease.

In summary, while some contend that the vendor cost estimates are optimistically low, there

are a number of reasons why we believe the cost of desulfurizing diesel fuel to meet the 15 ppm

cap standard may be even lower than estimated. Vendors are expected to continue to improve

their desulfurization technology such as the activity of their catalysts. Also, refiners have

several cost cutting options at their disposal, such as using existing spare equipment, to lower

their capital costs which is not considered here. Also, refiners may be able to resort to either of

two operational options to reduce the amount of LCO in their highway diesel fuel.

We are aware that there are potentially other capital and operating costs in the refinery which

would contribute the projected cost of desulfurizing diesel fuel beyond that provided to us by the

vendors. For example, refiners may need to expand their amine plant or their sulfur plant to

enable the processing of the sulfur compounds removed from diesel fuel. Then the small amount

of additional sulfur compounds treated would incur additional operating costs. Thus, as

described below, we adjusted the projected capital and operating costs upward to account for

these other potential costs which we have not accounted for explicitly.
Estimated Costs of Low-Sulfur Fuels

7-109

7.2.1.3 Refinery-Specific Inputs

There are a number of reasons why we estimated refining costs on a refinery-specific basis. 

First, it provides more precise and realistic estimates of desulfurization costs, as some

differences between individual refineries can be represented (e.g., distillate fuel composition,

production volumes, etc.). These costs are approximate, as we do not have precise data on the

distillate composition for all U.S. refineries. While we do know historic distillate production

levels, we do not know how these will change in the future. Still, the distribution of costs across

refineries facillitated by the factors developed in this section will provide much more insight into

how desulfurization costs can vary between refineries. The alternative would be to estimate

desulfurization costs for the average U.S. refinery and assume that this cost applied to all

refineries. Given the wide range in refinery capacities and their relative production of highway

diesel fuel and high sulfur distillate, the national average approach would be overly simplistic. 

Second, a refinery specific approach to costs allows us to better represent the potential

interactions between the 15 ppm cap for highway diesel fuel and the NRLM sulfur caps

associated with this rule. We recently received refiners’ plans regarding their compliance with

the 15 ppm highway diesel fuel sulfur cap. Being projections, these plans are subject to change. 

However, these projections allow us to reasonably estimate the ways in which refiners might

take advantage of efforts to comply with the highway fuel standards in complying with the

NRLM standards.

Third, the refinery specific costs can be combined into a distribution of costs for the entire

refining industry. This distribution of costs allows us to better estimate the number of refineries

likely to be affected by this rule. It also provides insight into the range of costs likely to be

experienced by refineries, particularly the difference in costs between those facing the lowest

costs and those facing the highest costs. This will also provide greater insight into how NRLM

diesel fuel prices might be affected by this rule, as well as refiners’ ability to recover capital

costs. 

Fourth, the development of refinery specific costs allows us to better estimate how small

refiners might be affected by this rule, in particular how their costs differ from their larger

competitors. 

Of the many factors which affect desulfurization costs, there are four which vary

significantly from refinery to refinery and which we have estimated quantitatively: 

1) the composition of its no. 2 distillate pool (e.g., the percentages of LCO and other

cracked stocks), 

2) the percentage of its no. 2 distillate which is already being hydrotreated, 

3) the volume of no. 2 distillate

4) which specific refineries are most likely to produce lower sulfur NRLM fuel. 

The following four subsections discuss how we developed refinery-specific factors for each

of these four factors.

7.2.1.3.1 Composition of Distillate Fuel by Refinery
Final Regulatory Support Document

7-110

In section 7.2.1.2, we developed desulfurization costs as a function of the blend stocks

comprising the diesel fuel being processed, as well as other factors. In this section, we describe

how we estimated each refinery’s distillate blendstock diesel composition. 

Refiners do not publish blendstock composition data, nor do they submit it to regulators as

part of any regulatory requirements. The only available information is an industry survey

conducted in 1996, which published compositional data for all the surveyed refiners within a

PADD. Thus, we developed a methodology to estimate each refinery’s diesel fuel composition

from the aggregated data available from 1996. We then revised these compositions to reflect

changes in the capacities of those types of equipment which produce distillate blendstock which

have occurred since that time. Finally, we applied one further change to the compositional data

which we believe will occur as a result of the 15 ppm highway fuel cap. 

The only available data on the composition of diesel blend stocks is from a survey conducted

by API and NPRA in 1996. This survey was sent to all domestic refiners and the responses

covered 79 percent of the total distillate produced by domestic refineries in 1996. The

blendstock composition of highway diesel fuel and No. 2 high sulfur distillate fuel were

surveyed separately. The blendstock composition of the combined pool can also be estimated by

volume weighting the compositions of the two distillate pools. 

Table 7.2.1-15 summarizes the survey results for highway diesel fuel, high sulfur distillate

fuel and the combined distillate pool for refiners outside of California. California refiners were

excluded due to the unique specifications which California distillate must meet, namely low

aromatics and high cetane limits. Also, due to the fact that California has already passed

regulations requiring 15 ppm nonroad fuel, this NRLM rule will have a small impact on

California refiners. The survey also included whether or not the particular blendstock was

hydrotreated. This hydrotreating information will be used in the next section which addresses

the hydrotreated fraction of each refinery’s distillate. According to the cost estimation

methodology described above, desulfurization costs depend on blendstock composition and

overall hydrotreated fraction, but not on the specific blendstocks which are hydrotreated. 

Therefore, we do not consider whether the particular blendstock has been hydrotreated here. 

Table 7.2.1-15

Distillate Composition (Excluding California Refiners): 1996 API/NPRA Survey (vol%)

Highway Diesel Fuel High Sulfur Distillate All No. 2 Distillate

Straight Run 64% 63% 64%

LCO 23% 22% 22%

Other Cracked Stocks 9% 5% 8%

Hydrocrackate 4% 10% 6%

As can be seen, the composition of national average highway fuel and high sulfur distillate

are quite similar. This led us to assume, for the purpose of this analysis, that each refinery sent
Estimated Costs of Low-Sulfur Fuels

Y This assumes that both the FCC unit and the hydrocracker operate at the same percent of capacity, which is

reasonable.

7-111

the same fraction of LCO and other cracked stocks to its highway fuel and high sulfur distillate

pools. This same information was used as the basis for our cost projections presented in the

NPRM for this rule.

The next step in this analysis was to determine how each refinery’s distillate pool might

differ in composition. For example, some refineries do not have an FCC unit. Thus, their

distillate would contain no LCO. Others do not have cokers, hydrocrackers, etc. Thus, we

allocated the volume of each blendstock in the national distillate pool to each refinery in

proportion to the capacity of its equipment which produces each blendstock. As described in

Section 5.1, LCO is produced in FCC units, hydrocrackate is produced by hydrocrackers and

other cracked stocks are primarily produced by cokers, as well as other thermal cracking units. 

While general rules of thumb are available which estimate the volume of distillate produced

in each of these units, in most cases, we have sufficient information available to estimate, on a

national average basis, these conversion factors. EIA’s Petroleum Supply Annual for 1996 states

that domestic refiners produced a total of 3.06 million barrels per day of No. 2 distillate in 1996. 

By multiplying this volume by the percentages of LCO, other cracked stocks, and hydrocrackate

in all No. 2 distillate from Table 7.2.1-15 above, we can estimate the total volume of each of

these blendstocks which was produced in 1996. EIA also publishes the capacity of each

refinery’s processing units. By summing these up, we can estimate the total FCC, coker and

thermal cracking and hydrocracker units existing in domestic refineries in 1996. 

The situation with cokers and other thermal crackers is somewhat more complex, as the

conversion of feedstock into distillate does not tend to be the same in these units. Thus, their

capacities cannot simply be summed and assumed to have the same conversion rate. One

industry consultant estimated that delayed cokers tend to convert 30 percent of their feedstock

into distillate, while fluidized cokers, visbreakers, and other thermal crackers are less efficient in

this regard, converting only 15 percent. Thus, we assumed that the conversion rate for other

thermal crackers was half that of cokers. Practically, we effected this assumption by discounting

the capacity of other thermal crackers by a factor of two before adding them to coking capacity.

Prior to making this comparison, however, one more adjustment must be made. Refiners

outside of California with hydrocrackers typically feed LCO and other cracked stocks to their

hydrocracker. Straight run distillate might also be fed to a hydrocracker which produces

gasoline blendstock. However, we believe that after 2006, the 15 ppm highway diesel fuel cap

will encourage refiners to shift as much LCO and other cracked stocks as possible to their

hydrocrackers. Thus, for refineries with hydrocrackers and FCC units, we assumed that any

LCO produced would be sent to the hydrocracker, up to the capacity of the hydrocracker.Y

Similarly, for refiners with hydrocrackers and cokers or other thermal crackers, we assumed that

any other cracked stocks produced would be sent to the hydrocracker, up to the capacity of the
Final Regulatory Support Document

7-112

hydrocracker minus any LCO sent to the hydrocracker. Table 7.2.1-16 summarizes this

information. 

Table 7.2.1-16

Conversion of Heavy Oils to Distillate in 1996

Total U.S. Refining

Capacity (BPD)

Total Distillate Blendstock

Produced (BPD)

Percentage of Capacity

Converted to Blendstock

FCC Units (LCO)

Total 4,936,940 1,053,610 ---

After Shift to

Hydrocrackers

2,951,287 643,043 22%

Coking and other thermal crackers * (Other cracked stocks)

Total 2,664,400 400,193 ---

After Shift to

Hydrocrackers

1,771,505 256,728 15%

Hydrocracker

(hydrocrackate)

927,390 177,265 19%

* 100% of coker capacity plus 50% of the capacity of other thermal crackers 

By taking the ratio of the volume of distillate blendstock produced to the total capacity of the

type of equipment which produces it, we can estimate the percentage of this capacity which is

converted into each type of blendstocks. These percentage are also shown in Table 7.2.1-16. It

should be noted that these figures are likely lower than the conversions which would be actually

seen during unit operation. The conversions shown in Table 7.2.1-16 are based on rated unit

capacity and actual distillate production. Units typically operate at less than capacity over the

course of a year. This utilization percentage does not need to be explicitly considered here as the

unit capacity for each refinery and that for the nation as a whole are both on a nameplate rating

basis. Use of a capacity utilization rate would simply adjust both figures and cancel out within

the methodology.

Since we know the capacity of the various unit in each refinery in 1996, we could estimate

the volume of each blendstock produced by each U.S. refinery in 1996 by multiplying these

capacities by the above conversion factors. However, many refineries have increased the

capacities of various units since 1996. As we are using these blendstock compositions to project

desulfurization costs in 2007 and beyond, it would be desirable to reflect the impact of these

changes in capacity in our analysis. The latest data are from 2002. Thus, we multiplied each

refinery’s 2002 unit capacities (per EIA) by the above conversion factors to estimate the volume

of each blendstock produced by each refinery in this year. 

This is a marked improvement from the NPRM analysis. In the NPRM, we used refinery

unit capacities existing in the year 2000 (as estimated in the Oil and Gas Journal). These 2000
Estimated Costs of Low-Sulfur Fuels

Z

FCC conversion is defined as the volume percent of FCC feed throughput that is converted to products lighter

than LCO and clarified oil/slurry oil, ((FCC feed - LCO product-slurry oil product)/ FCC feed )*100, per volume

basis.

7-113

capacities were combined with the 1996 API/NPRA survey results and distillate production data

from 2000 to develop an analogous set of conversion factors. The use of 1996 unit capacities to

develop the conversion factors is more consistent with the survey results. The use of 2002 unit

capacities incorporates two additional years of changes in refinery configurations into the

analysis.

We also decided to use unit capacities as estimated by EIA in lieu of those published by the

Oil and Gas Journal. Reviewing both sets of unit capacities, particularly that for hydrotreating

capacity used in Section 7.2.1.3.2 below, we found greater consistency between the production

volumes of various distillate fuels, as well as between the capacities of the various units, with the

EIA estimates than with those published by the Oil and Gas Journal. Therefore, we decided to

use the EIA estimates for this final NRLM rule analysis. Also, in the NPRM, the use of distillate

compositions from 1996 and unit capacities from 2000 was inconsistent to some degree and the

above methodology eliminates this problem. 

In addition, the use of 2002 unit capacities provides an automatic adjustment for changes in

refinery configurations from 1996 to 2002. In the NPRM, our methodology basically assumed

that the overall distillate composition in 1996 continued unchanged into the future. One of the

comments we received on the NPRM cost estimates was that we had under-estimated

desulfurization costs by assuming that the 1996 distillate composition was not changing over

time. The commenters pointed out that the average crude oil being processed in domestic

refineries was getting heavier (lower API gravity) and more sour (higher sulfur) over time,

which would negatively affect distillate composition from the point of view of desulfurization. 

They suggested that we should adjust our mix of blendstocks and the amount of sulfur needing to

be removed to account for this trend.

We reviewed the quality of the U.S. crude oil slate between 1996 and 2002 and indeed found

that the API gravity of average crude oil had decreased by 2.3 percent from 31.1 to 30.4. (The

sulfur content of crude oil also increased, but this will be considered in Section 7.2.1.3.2 below

when we estimate the percentage of NRLM fuel which is hydrotreated prior to this rule.) 

Heavier crude oils tend to produce heavier feedstocks to the FCC, coker and hydrocrackers,

which can affect the conversion of these feedstocks into distillate. The yield of LCO from an

FCC unit tends to vary inversely with conversion,Z

 with higher volumes of LCO produced at

lower conversion rates. Heavier crude oils generally produce a heavier FCC feed stock which

lowers FCC conversion. This would tend to increase the production of LCO from FCC units. 

The same would be generally true for cokers and other thermal cracking units.

 However, since 1996 refiners have made several process changes which tend to increase

FCC conversion. Since 1996, FCC feed hydrotreating capacity has increased by 24 percent,

while FCC capacity only increased by 6 percent.35 FCC feed hydrotreating reduces the density

(increases the API gravity) of the FCC feedstock, which increases conversions and decreases
Final Regulatory Support Document

7-114

LCO yields in the FCC unit. Also, hydrocracking capacity has increased by 20 percent. Since

these units can process poor quality LCO, this mitigates the effect of heavier crude oils. 

According to several FCC technology licensors, refiners are also using more active FCC

catalysts and have added or upgraded their FCC process technologies since 1996. These changes

should also increase FCC conversions and decreases LCO yields. Thus, changes have occurred

since 1996 which both increase and decrease the production of LCO from FCC units. It is not

possible to quantitatively estimate the impact of each of these changes, nor the net change in

LCO yield. In general, we believe that the impact of heavier crude oil is smaller than the impact

of newer FCC technology and increased FCC hydrotreating capacity. Thus, the inability to

quantitatively account for these changes should not lead to an under-estimation of

desulfurization costs. However, due to the compensating nature of these changes, we believe

that the overall change in the quantity and quality of LCO and other cracked stocks being

produced today is small and would not significantly affect desulfurization costs. 

Also, the processing of heavier crude oil has led the U.S. refining industry to increase

capacity of cokers and hydrocrackers relative to crude oil processing capacity. As mentioned

above, our methodology automatically adjusted distillate composition for this trend. Thus, we

believe that our current methodology reflects current crude oil quality as much as possible using

available information. While our methodology does not account for future changes in crude oil

quality, the changes seen below between 1996 and 2002 are quite small and indicate that changes

likely in the future would also be very small.

Table 7.2.1-17 shows how updating these estimates from 1996 to 2002 affected national

average distillate composition outside of California.

Table 7.2.1-17

National Average Distillate Composition Excluding California (Vol%)

1996 2002

Straight Run 65% 62%

LCO 21% 21%

Other Cracked Stocks 8% 10%

Hydrocrackate 6% 7%

We made one last adjustment to distillate composition to reflect a shift we believe will occur

when the 15 ppm sulfur cap begins to apply to highway diesel fuel in 2006. As shown in Table

7.2.1-17 above, the API/NPRA survey found that the hydrocrackate fraction of high sulfur

distillate was much greater than that in highway diesel fuel. The reason for this is not obvious,

as the low sulfur level of hydrocrackate would presumably been valuable in producing 500 ppm

highway fuel. It may be that most highway fuel has be hydrotreated regardless of the percentage

of hydrocrackate added, and the use of hydrocrackate in high sulfur distillate allows a significant

portion of this fuel to avoid hydrotreating. In any event, the primary properties which differ
Estimated Costs of Low-Sulfur Fuels

7-115

between highway diesel fuel and high sulfur distillate are sulfur content and cetane number and

refiners can use a wide range of blendstock compositions to meet these specification. 

When the 15 ppm cap starts to apply to highway diesel fuel, however, the economic incentive

to blend hydrocrackate into highway diesel fuel will increase dramatically. Thus, we believe that

refiners will shift hydrocrackate from high sulfur distillate to highway diesel fuel. However,

most high sulfur distillate is either NRLM diesel fuel or sold as either NRLM fuel or heating oil. 

Thus, it must have a minimum cetane number of 40. Therefore, we did not believe that it would

be feasible for a refiner to shift unhydrotreated LCO or other cracked stocks from highway diesel

fuel to high sulfur distillate. Therefore, we assumed that refiners would only shift hydrotreated

blendstocks to compensate for the hydrocrackate shift. We assumed that the composition of this

shift would reflect the refinery’s average distillate composition (i.e., percentage of straight run,

LCO and other cracked stocks). We assumed that a refiner would shift all of their hydrocrackate

to highway diesel fuel as long as there was sufficient hydrotreated material to shift from highway

fuel to high sulfur distillate. (The hydrotreated fraction of each refinery’s distillate is discussed

in the next section.) For all except five refineries, all of the hydrocrackate was shifted to

highway fuel. Three refiners lacked sufficient volume of hydrotreated blendstocks for all their

hydrocrackate to be shifted. Two refiners produced less highway diesel fuel than their estimated

production of hydrocrackate. Overall, the hydrocrackate portion of highway diesel fuel

increased to 8.9 percent, while that for high sulfur distillate decreased to 1.6 percent.

The final compositions of highway and high sulfur distillate after implementation of the 15

ppm sulfur cap on highway fuel, but prior to this NRLM rule are shown below in Table 7.2.1-18. 

These national averages were calculated by 1) applying the above conversion factors to each

refinery’s unit capacities to estimate the volume of each blendstock being produced by that

refinery, 2) spreading the volume of each blendstock to the refinery’s highway diesel fuel and

high sulfur distillate fuel pools in proportion to the refinery’s production of each of the two fuels

pool (as estimated in Section 7.2.3.3 below), 3) shifting hydrocrackate to highway fuel in return

for other hydtrotreated blendstocks, as discussed above, 4) summing the volumes of each

blendstock type in each fuel pool across all refineries and 5) dividing these blendstock volumes

by the total production of highway and high sulfur fuel, respectively. We used each refinery’s

projected distillate composition to estimate its cost of meeting the 500 and 15 ppm NRLM sulfur

caps, not the national average composition. 

Table 7.2.1-18

Distillate Composition: After Implementation of the 15 ppm Highway Fuel Sulfur Cap*

Highway Diesel Fuel High Sulfur Distillate All No. 2 Distillate

Straight Run 61% 66% 62%

LCO 20% 23% 21%

Other Cracked Stocks 10% 9% 10%

Hydrocrackate 9% 2% 7%

*excludes California.
Final Regulatory Support Document

7-116

In order to provide an indication of the range of distillate compositions which we projected

using this methodology, we developed distributions of the percentages of LCO and other cracked

stocks in various refiners distillate. These are shown in Table 7.2.1-19 below.

Table 7.2.1-19

 Distribution of LCO and Other Cracked Stocks in High Sulfur Distillate Prior to the NRLM

Rule (U.S. Refineries Producing High Sulfur Distillate)

Percentage of LCO and Other Cracked Stocks in the Distillate Pool

0% <10% <20% <25% <30% <40% <50% <80% 100%

LCO

Number of Refineries 47 48 53 60 76 92 96 99 101

Cumulative % of High

Sulfur Distillate

Volume

35 36 45 49 71 87 94 98 100

Other Cracked Stocks

Number of Refineries 71 73 79 87 92 97 101 101 101

Cumulative % of High

Sulfur Distillate

Volume

53 61 66 85 88 90 100 100 100

As shown above, in 2002, high sulfur distillate fuel produced by U.S. refineries contains

between zero to over 80 percent LCO. Forty-seven U.S. refineries, which produce about 35

percent of the high sulfur distillate in the U.S., blend no LCO into their distillate. The high

sulfur distillate from the remaining 54 refineries averages about 33 percent LCO by volume. On

average, high sulfur distillate contains 21.1 percent LCO in 2002 versus 21.3 percent in 1996. 

This reflects the fact that FCC unit capacity grew slightly less between 1996 and 2002 than total

domestic distillate production volume.

Similarly, we estimate that about half of the high sulfur distillate fuel in the U.S, which is

produced by 71 refineries, does not contain any other cracked stocks from cokers, visbreakers

and thermal crackers. Of the refineries which produce other cracked stocks, their distillate fuel

contains an average of 20.0 percent of other cracked stocks in 2002. On average, the estimated

percentage of other cracked stocks being blended into high sulfur distillate increased slightly

from 9.2 percent in 1996 to 9.4 percent in 2002. Thus, coking capacity increased slightly faster

than total distillate production. 

7.2.1.3.2 Sulfur Content and Hydrotreated Fraction of High Sulfur Distillate 

Like distillate composition, per the cost methodology developed above, the sulfur content

and hydrotreated fraction of high sulfur distillate affects the cost of desulfurization. There are

two effects. One relates to the amount of hydrogen consumed in hydrotreating. The other

relates to the capital cost of a hydrotreater. 

Regarding hydrogen consumption, in addition to removing sulfur, hydrotreating also

saturates olefins and most poly-nuclear aromatics. These latter effects occur almost regardless of
Estimated Costs of Low-Sulfur Fuels

7-117

the degree of sulfur reduction. Thus, distillate which is being hydrotreated today has already had

its olefins and poly-nuclear aromatics removed. Thus, subsequent hydrotreating of already

hydrotreated blendstocks to reduce sulfur further in response to this NRLM rule does not

consume hydrogen related to olefin or poly-nuclear aromatic saturation. The other effect relates

to the capital investment needed to meet the 500 ppm NRLM cap in 2007. Material that is

already being hydrotreated to 500 ppm or less need not be treated at all during the first step of

the NRLM fuel program. 

As mentioned in Section 7.2.1.2.1.2, we were not able to incorporate the change in hydrogen

consumption due to olefin and poly-nuclear aromatic saturation associated with changing

degrees of current hydrotreating. Differences in total hydrogen consumption between various

refineries should only be a few tenths of a penny per gallon. Thus, the use of an average level of

olefin and poly-nuclear aromatic saturation lessened the refinery-specific nature of our estimates

to a slight degree. 

Regarding capital costs, we were able to incorporate differences in expected capital

investment needed to desulfurize unhydrotreated and hydrotreated blendstocks to meet the 2007

500 ppm NRLM cap. This improved our ability to predict overall desulfurization costs, the

number of refineries affected by the NRLM rule and how small refiners might be differentially

impacted by the rule. 

In addition to whether a blendstock has been previously hydrotreated or not, the starting

sulfur content also affects the volume of hydrogen needed to reduce sulfur to meet a 500 ppm

cap. In the NPRM, we started with the 1996 API/NPRA fuel quality survey to obtain estimates

of the portion of highway and high sulfur distillate which receives at least some hydrotreating. 

We then used in-use fuel survey data to estimate the sulfur level of high sulfur distillate

produced in 1996. Assuming that the sulfur content of the hydrotreated portion of this fuel was

the same as that for highway diesel fuel (340 ppm), we then back-calculated the sulfur content of

the non-hydrotreated portion of high sulfur distillate, so that the blend matched the in-use sulfur

level of finished high sulfur distillate. We then assumed that these 1996 estimates also applied

to current and future high sulfur distillate prior to the NRLM rule. 

We received comment on the NPRM that the sulfur content of crude oil had been increasing

since the 1996 API/NPRA survey was conducted. The commenters argued that this would

increase the sulfur content of high sulfur distillate and increase desulfurization costs. Therefore,

we have expanded the methodology used in the NPRM analysis to estimate both the sulfur

content and hydrotreated fraction of high sulfur distillate. 

We first reviewed data on the sulfur content of crude oils processed by U.S. refineries and

found that sulfur content had indeed increased. We have incorporated this increase in crude oil

sulfur content into the estimates developed in this section. However, as described in Section 7.1

above, there is no evidence so suggest that the sulfur content of high sulfur distillate has

increased since 1996. Thus, it is likely that a greater percentage of the volume of high sulfur

distillate blendstocks are being hydrotreating than was the case in 1996. We have incorporated a

change in the hydrotreated fraction from 1996 into this analysis, as well. Finally, we also
Final Regulatory Support Document

7-118

reviewed the hydrotreating and hydrocracking capacities of U.S. refineries in 1996 and 2002, as

well as the relative production of highway diesel fuel and high sulfur distillate to confirm that

sufficient hydrotreating capacity exists to hydrotreat a greater fraction of high sulfur distillate

blendstocks. 

Table 7.2.1-20 presents many of the primary inputs for our analysis. These estimates are

intended to represent high sulfur distillate produced in the year 2002, but without consideration

of an increase in crude oil sulfur content. Due to the significant differences in hydrotreating

percentages seen across PADDs, we incorporated these PADD-specific estimates as much as

possible. 

Table 7.2.1-20

Quality of High Sulfur Distillate from 

Non-California Refineries: “2002" Prior to Consideration of Increased Crude Oil Sulfur

 PADD

1 2 345

High Sulfur Distillate Pool

 Sulfur content (ppm) 2925 2973 3776 2549 2566

 % Hydrotreated * 27 31 44 17 2

High Sulfur Distillate Produced by Refineries with Hydrotreaters

 % of high sulfur distillate pool 81 70 95 40 48

 % Hydrotreated 33 45 46 43 4

 Sulfur content of portion not

 hydrotreated (ppm)

4214 5081 6739 4237 2646

* Assumed to be the same as in 1996 API/NPRA survey.

The sulfur content of the high sulfur distillate pool in each PADD were taken from Table 7.1-

40 in Section 7.1 above. A direct estimate of the portion of the 2002 distillate pool which is

hydrotreated is not available. Therefore, we assumed that this figure has not changed since the

API/NPRA survey. This necessitates the consideration of increased sulfur content between 1996

and 2002, which is addressed below. As can be seen, a significant percentage of high sulfur

distillate received some hydrotreating in 1996, despite the fact that the final sulfur level is 2000

ppm or more. This is likely necessary to improve the stability of untreated LCO, as well as meet

applicable cetane and sulfur specifications with blend stocks which can exceed 10,000 ppm

sulfur and have a cetane number of less than 15 prior to hydrotreating. The PADD with the

highest percentage of hydrotreated high sulfur distillate is PADD 3, while the lowest is PADD 5

(outside of California). Within PADD 5, Alaska’s refineries are believed to have the lowest

hydrotreated percentage (zero), since none of the Alaskan refineries have distillate hydrotreaters.

The hydrotreated blendstocks sent to the high sulfur distillate pool are assumed to be part of

a larger pool of hydrotreated blendstocks also used to produce highway diesel fuel. We believe

that this is reasonable because many refiners likely only have a single hydrotreater and they are

simply blending more hydrotreated material into their highway diesel fuel than into their high
Estimated Costs of Low-Sulfur Fuels

7-119

sulfur distillate. In this case, we assume that all of the hydrotreated material contains 340 ppm

sulfur, the current average sulfur level for highway diesel fuel. Some larger refiners likely have

two or more hydrotreaters which could be treating highway diesel fuel blendstocks and high

sulfur distillate blendstocks differently. However, in this case, we have no way of estimating the

sulfur levels of either the hydrotreated or non-hydrotreated portions of the high sulfur distillate. 

Thus, we assumed that the 340 ppm sulfur content applied to all hydrotreated blendstocks.

Overall, this assumption has little effect on the estimation of NRLM desulfurization costs. As

will be seen below, we have estimates of both the hydrotreated fraction of high sulfur distillate

and of its final sulfur level. If the sulfur level of hydrotreated blendstocks going to the high

sulfur distillate pool contain more than 340 ppm sulfur, the the sulfur content of the nonhydrotreated portion of the pool much contain less sulfur than estimated below. The total

amount of sulfur requiring removal is the same in either case. 

Some refiners do not have a distillate hydrotreater. Therefore, the percentage of their high

sulfur distillate which is hydrotreated is zero. In order for the entire high sulfur distillate pool to

be hydrotreated to the degree shown in Table 7.2.1-17, the portion of distillate produced by

refiners with distillate hydrotreaters must be higher. In order to estimate these percentages, we

reviewed EIA data for both distillate production and distillate hydrotreating capacity. The

former data are confidential and were received directly from EIA. The latter came from their

2002 Petroleum Supply Annual. For each PADD, we determined the percentage of all high

sulfur distillate produced by refiners with distillate hydrotreaters. These figures are shown in

Table 7.2.1-20 above. We calculated the percentage of the high sulfur distillate pool produced

by refineries with hydrotreaters by dividing the hydrotreated percentage for the entire pool by

the percentage of distillate produced by refineries with hydrotreaters. These higher hydrotreated

percentages are shown on the second to the last line of Table 7.2.1-20.

As discussed above, we assume that the sulfur content of the hydrotreated portion of high

sulfur distillate is the same as that of highway diesel fuel, or 340 ppm. As discussed in Chapter

5, the sulfur content of hydrocrackate is very low, less than 50 ppm. Knowing the final sulfur

level and the percentage of hydrotreated blendstock in high sulfur distillate from Table 7.2.1-20

above (which includes hydrocrackate) and the percentage of hydrocrackate from Table 7.2.1-18,

we can back-calculate the sulfur content of the unhydrotreated blendstocks comprising the rest of

the high sulfur distillate pool. These sulfur levels are also shown in Table 7.2.1-20. 

The final step is to incorporate the effect of an increase in crude oil sulfur content. Table

7.2.1-21 shows the average sulfur content of crude oil processed in each PADD in both 1996 and

2002. As can be seen, crude oil became more sour in all but PADD 1. 
Final Regulatory Support Document

AA Petroleum Refining Fourth Edition, Gary Handewerk, 2001, pages 41 to 45.

7-120

Table 7.2.1-21

Sulfur Content of Crude Oil Processed by U.S. Refineries (weight %)

PADD 1996 2002 Percent Change

1 0.94 0.86 -8.5

2 1.08 1.31 21.3

3 1.22 1.65 35.3

4 1.31 1.40 6.9

5 (Non-California) 1.14 1.22 7.0

Overall 1.15 1.41 22.6

* Annual crude properties from EIA’s Petroleum Supply Annual 1996 and 2002

We next used published information to estimate how changes in crude oil sulfur content

would impact the sulfur level of unhydrotreated distillate blendstocks.AA Table 7.2.1-22 depicts

estimated sulfur contents for straight run distillate for a variety of crude oils containing both 1.15

and 1.41 weight percent sulfur. 

Table 7.2.1-22

Straight Run Middle Distillate Sulfur Content (ppm) *

Crude Oil

Sulfur Content

Sweet U.S.

Crude Oil

West Texas

Crude Oil

California

Crude Oil

Middle East

Crude Oil

Venezuelan 

Crude Oil

Average of

All Crude

Oils

1.15 wt % 4400 6400 7800 4500 3500 5330

1.41 wt % 5400 7800 9800 5300 4400 6540

Change in 

Distillate

Sulfur

22.7% 21.9% 25.6% 17.7% 25.7% 22.7%

* Middle distillate assumed to have mid-boiling point of 500 F. 

As can be seen, the 22.6 percent increase in crude oil sulfur content is estimated to increase

the sulfur content of straight run distillate by 17.7-25.7 percent, with an average increase of 22.7

percent. Thus, on average, the sulfur content of straight run distillate increases to essentially the

same degree as that of the crude oil. Therefore, it is reasonable to assume that the increases in

crude oil sulfur content shown in Table 7.2.1-21 above increased the sulfur content of straight

run distillate proportionally. In addition, we assume that the sulfur content of the other

blendstocks, namely LCO and other cracked stocks, also increased to the same degree.

As discussed in Section 7.1 above, the average sulfur content of high sulfur distillate does

not appear to have changed substantially since 1996. A significant portion of this distillate is
Estimated Costs of Low-Sulfur Fuels

7-121

produced by refineries without distillate hydrotreating, where an increase in crude oil sulfur

would by necessity have been reflected in their distillate production. This implies that the

increases in crude oil sulfur content occurred primarily at refineries with distillate hydrotreating

capacity. To account for this, we adjusted the changes in crude oil sulfur shown for the

percentage of high sulfur distillate produced by refiners with hydrotreaters. For example, crude

oil sulfur in PADD 2 increased by 21.3 percent. Of all the distillate produced in PADD 2, 70

percent was produced by refineries with distillate hydrotreaters. Therefore, if the crude oil sulfur

at the refineries producing the other 30 percent of high sulfur distillate did not change, the crude

oil sulfur at refineries with hydrotreaters increased by 30 percent (21.3/0.7). The results for all

five PADDs are shown in Table 7.2.1-23 below.

Table 7.2.1-23

Quality of High Sulfur Distillate from Non-California Refineries: 2002 and Beyond

 PADD

1 2 3 4 5 

High Sulfur Distillate Pool

 Sulfur content (ppm) 2925 2973 3776 2549 2566

 % Hydrotreated 20 41 58 21 83

High Sulfur Distillate Produced by Refineries with Hydrotreaters

 Increase in crude oil sulfur content -11% 30% 37% 17% 15%

 % of high sulfur distillate pool 81 70 95 40 48

 % Hydrotreated 25 58 61 52 17

 Sulfur content of portion not

 hydrotreated (ppm)

3771 6623 9248 4964 3034

The next step was to increase the sulfur content of the unhydrotreated distillate at refineries

with hydrotreaters by the same percentage that crude oil sulfur increased. For example, in

PADD 2, the sulfur content of 5081 ppm was increased by 30 percent to yield a final nonhydrotreated distillate sulfur content of 6623 ppm. The sulfur content of the 2002 high sulfur

distillate is the same as that shown in Table 7.2.1-23 and the sulfur content of the hydrotreated

distillate is 340 ppm. Therefore, the percentage of high sulfur distillate at these refineries which

is hydrotreated can be calculated. For example, in PADD 2, a mix of 42 percent hydrotreated

distillate at 340 ppm and 58 percent unhydrotreated distillate at 6623 produces a pool of high

sulfur distillate at 2973 ppm. Finally, given the percent of all high sulfur distillate being

produced by refineries with hydrotreaters (for PADD 2, 70 percent), the portion of the entire

high sulfur distillate pool which is hydrotreated can be calculated. For example, for PADD 2,

the portion of the entire high sulfur distillate pool which is hydrotreated is 41 percent, the

product of the the percent of all high sulfur distillate being produced by refineries with

hydrotreaters (70 percent) and the hydrotreated percentage of high sulfur distillate at those

refineries with hydrotreaters (58 percent). These figures are summarized in Table 7.2.1-23

above. 
Final Regulatory Support Document

7-122

High sulfur distillate produced by refineries without hydrotreaters is assumed to have sulfur

contents equal to the average high sulfur distillate produced in that PADD. High sulfur distillate

produced by refineries with hydrotreaters is a mix of unhydrotreated blendstocks at the sulfur

levels shown in Table 7.2.1-23 and hydrotreated blendstock containing 340 ppm sulfur. The

average sulfur content of this distillate is also the average sulfur content of the high sulfur

distillate produced in that PADD. We assume that these hydrotreated percentages and sulfur

contents remain constant beyond 2002. 

A comparison of the hydrotreated portion of all high sulfur distillate in 1996 (Table 7.2.1-20)

and 2002 (Table 7.2.1-23) shows that except in PADD 1, we are projecting that a significant

increase in the degree of hydrotreating has occurred. This implies that refiners built new

hydrotreaters or expanded existing hydrotreaters during this time period. We desired to confirm

that this in fact occured. The first step in this confirmation was to estimate the increased

capacity of distillate hydrotreating. The second step was to show that this increase was sufficient

to provide for the increased production of highway diesel fuel, as well as the increase in the

hydrotreated percentage of high sulfur distillate.

Table 7.2.1-24 presents hydrotreating and hydrocracking capacity at U.S. refineries located

outside of California in 1996 and 2002, according to EIA’s Petroleum Supply Annual reports

from these two years (assuming an annual average utilization rate of 90 percent). Both processes

produce distillate blendstocks which likely meet the 500 ppm highway fuel cap and which have

had their olefins and some aromatics removed, reducing the cost of further hydrotreating. As

described above, hydrocrackers are assumed to convert roughly 21 percent of their feed to

distillate. 

Table 7.2.1-24

Effective Non-California Distillate Hydrotreating and Hydrocracker Capacity 1996 to 2002

Distillate Hydrotreating Hydrocrackers

1996 Capacity 3,108,285 834,651

2002 Capacity 3,380,323 1,003,050

Increase in capacity 272,038 168,399

Increase in low sulfur distillate 272,038 35,869*

* 90 percent of rated capacity. Hydrocrackers assumed to convert 21 percent of feedstock to distillate.

As can be seen, the total capacities of both processes increased substantially. In total, these

capacity expansions increased the production capacity of low sulfur distillate by 307,900 barrels

per day.

Table 7.2.1-25 shows the distillate fuel production in 1996 and 2002, again from EIA’s

Petroleum Supply Annual reports. We show the production of jet fuel and kerosene, since much
Estimated Costs of Low-Sulfur Fuels

7-123

of the volume of these No. 1 distillate fuels is also hydrotreated and the above distillate

hydrotreating capacities do not distinguish between No. 1 and No. 2 distillates. 

Table 7.2.1-25

Non-California Distillate Production (BPD)

Jet Fuel and Kerosene * Highway Diesel Fuel High Sulfur Distillate

1996 1,577,000 1,842,797 1,213,490

2002 1,571,000 2,298,507 964,184

Increase -6,000 455,710 -249,307

* Jet fuel includes production from California refineries.

As can be seen, the production of jet fuel and kerosene was essentially constant in 1996 and

2002. Thus, we assume that no additional hydrotreating capacity was used in the production of

jet fuel and kerosene in 2002 versus 1996. It is possible that the increased sulfur content of

crude oil occurring over this 6 year period caused refiners to increase a greater percentage of the

No. 1 distillate blendstocks used to produce these two fuels. However, no data are available to

estimate this effect. Since the sulfur standards for these No.1 distillate fuels are not stringent, the

overall change in hydrotreating should be small. 

As also shown in Table 7.2.1-25, the production of highway diesel fuel increased by nearly

25 percent, while the production of high sulfur distillate decreased by 20 percent. As described

above, the hydrotreated fraction of highway fuel was 83.8 percent in 1996. Thus, the production

of 455,710 barrels per day more highway diesel fuel likely utilized 382,000 (455,710 * 0.838)

barrels per day of effective hydrotreating or hydrocracking capacity. However, as discussed

below, crude oil sulfur levels increased between 1996 and 2002 by nearly 20 percent. Thus, to

be conservative, we will also consider the possibility that 100 percent of this additional

production of highway diesel fuel was hydrotreated. Thus, we estimate that the production of

455,710 barrels per day more highway diesel fuel might have utilized as much as 455,710 barrels

per day of effective hydrotreating or hydrocracking capacity. Combining these two estimates to

produce a range, the additional production of highway diesel fuel utilized 74,100-147,810 more

barrels per day of effective hydrotreating and hydrocracking capacity than the 307,000 barrels

per day of effective capacity which was added between 1996 and 2002.

Regarding the production of high sulfur distillate, two factors changed, volume and

percentage which was hydrotreated. In 1996, 1.213 million BPD of high sulfur distillate was

produced, 34 percent of which was hydrotreated. In 2002, 0.964 million BPD of high sulfur

distillate was produced, 41 percent of which was hydrotreated. This implies a net reduction of

hydrotreated volume of 20,300 BPD. This provides some but not all of the hydrotreating

capacity needed to produce the additional highway fuel. The shortfall ranges from 53,800-

127,510 barrels per day of effective hydrotreating capacity.
Final Regulatory Support Document

7-124

We believe that this remaining hydrotreating capacity needed to produce the additional

highway diesel fuel likely came from an increase in the utilization of hydrotreating capacity

between 1996 and 2002. The API/NPRA survey showed that only 78 percent of the total rated

hydrotreating capacity was utilized in 1996. We believe that full utilization can be closer to 90

percent. (Crude oil utilization rates today are over 95 percent.) A 12 percent increase in the

utilization rate of hydrotreating capacity in 1996 would be 373,000 barrel per day. This far

exceeds the 53,800-127,510 barrel per day shortfall estimated above. Thus, we conclude that the

increase in overall hydrotreating percentage of high sulfur distillate are reasonable.

7.2.1.3.3 Refinery Specific Distillate Production Volumes 

In the NPRM, we projected refinery’s volumes of no. 2 distillate fuel in two steps. First, we

obtained each refinery’s production of no. 2 distillate fuel in 2000 from EIA. (This data is

considered confidential and is based on information which refiners are required to submit to EIA

periodically.) These production volumes include a breakdown of how much fuel was certified to

meet the 500 ppm highway fuel sulfur cap and how much fuel was not so certified. Second,

these year 2000 production volumes were increased to represent 2008 production using EIA

projections from their 2002 AEO report. We applied separate growth rates for highway diesel

fuel and high sulfur distillate. We assumed that refineries would not change their relative

production of highway diesel fuel and high sulfur distillate except as reflected in the distinct

national average growth projections for the two fuels. 

For the final rule, we have made a number of changes to improve this portion of our cost

analysis. First, since the NPRM analysis was conducted, we received refiners’ projection of the

volume of 15 and 500 ppm highway diesel fuel which they plan to produce in 2006-2010. In

some cases, these volumes differ significantly from their historic production of highway diesel

fuel. Thus, we have incorporated these projections into our projection of refineries’ relative

production of highway diesel fuel and high sulfur distillate prior to the implementation of this

rule. Second, we have shifted our base year for historic production volumes from 2000 to 2002

to reflect more recent data available from EIA. Third, we have shifted the future year for which

we project desulfurization costs from 2008 to 2014. Fourth, and finally, we are using EIA

projections of distillate production growth from their 2003 AEO report36, instead of their 2002

AEO report. The methodology for estimating refinery specific production volumes of highway

diesel fuel and high sulfur distillate is described in more detail below, as well as the results of

this analysis. 

As described above, the first step was to estimate each refinery’s historic production volumes

of highway diesel fuel and high sulfur distillate. Except for using more recent 2002 data from

EIA, versus 2000 in the NPRM, this step was identical to that performed in the NPRM analysis.

The second step increased these 2002 production volumes of highway and high sulfur

distillate fuel to represent growth through 2014. We chose 2014, because it represents the midpoint of the life of the desulfurization equipment build in response to this rule (per IRS rules, this

equipment has a 15 year life). We obtained EIA’s projected growth factors for domestic

production of these two fuels over this time period, which were consistent with those underlying
Estimated Costs of Low-Sulfur Fuels

7-125

their 2003 AEO projections. EIA projects that highway fuel production will increase 42.1

percent over this time period, while production of high sulfur distillate will only increase 8.1

percent. Each refinery’s 2002 production volumes of these two fuels werw increases by these

percentages to represent their likely production in 2014. The sum of the production volumes for

the two fuels was taken to be each refinery’s total distillate production in 2014. It should be

noted that the combination of these two growth rates results in a greater increase in the

production of distillate fuel from domestic refineries than indicated by the growth in crude oil

consumption by these refineries (typically assumed to be the driver of increased fuel production). 

This difference occurs because EIA projects that domestic refiners will increasingly process

heavy oils in addition to virgin crude oils. This step was analogous to that performed in the

NPRM, with the exception that growth was projected to 2014 instead of 2008. The historic and

future production volumes by PADD are shown in Table 7.2.1-26. 

Table 7.2.1-26

U.S. Distillate Fuel Production: AEO 2003 (BPSD) *

2002 2014 

Highway

Fuel

High Sulfur

Distillate

Total

Distillate

Highway

Fuel 

High Sulfur

Distillate

Total

Distillate

PADD 1 239,375 223,063 462,438 337,936 241,161 579,098

PADD 2 647,170 159,688 806,858 913,637 172,644 1,086,281

PADD 3 1,245,605 520,142 1,765,747 1,758,473 562,345 2,320,818

PADD 4 129,397 29,973 159,370 182,676 32,404 215,080

PADD 5 396,475 95,775 492,250 559,720 103,546 663,266

Total 2,658,022 1,028,641 3,686,663 3,752,442 1,112,100 4,864,542

* Growth from AEO 2003 Table 17. Includes U.S. Virgin Island refineries.

The third step differed from the NPRM analysis in that we utilized refiners’ confidential

projections of how they planned to produce highway diesel fuel in 2006-2010 under the

upcoming 2007 highway diesel fuel program. Under this program, refiners must submit their

projected production volumes of 15 and 500 ppm diesel fuel to EPA every year starting in 2003

(called a pre-compliance report). EPA would then publish aggregated results to help refiners

optimize their compliance plans and better ensure sufficient supply of highway diesel fuel under

the rule. Shell oil’s refinery in Bakersfield, California and Carribean Petroleum’s refinery in

Puerto Rico were removed from the analysis due to recent shutdowns or plans to shut down.

The highway diesel fuel program begins to take effect in June 2006. Some refiners

submitted 2006 production volumes on an annualized basis, while others submitted volumes for

just the seven months affected by the program. To avoid these differences, we focused on

refiners’ projections for 2007, the first full calendar year affected by the program. We assumed

these projections, made by refiners, represented the best estimate of future production levels of
Final Regulatory Support Document

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highway diesel fuel on a refinery-specific basis. While refiners projected their production

volumes for highway diesel fuel, they did not have to submit their plans for producing high

sulfur distillate. Therefore, we estimated their production of high sulfur distillate subtracting

their production of highway diesel fuel from our estimate of the refinery’ total production of No.

2 distillate from step two above. 

The fourth and final step was to put refiner’s projected 2007 highway diesel fuel production

volumes on the same basis as these 2014 total distillate volumes in order to back-calculate a high

sulfur distillate volume. To do this, we assumed that the refiners’ highway pre-compliance

reports represented the absolute volumes which they planned to produce in 2007 including any

increases in total distillate production which might occur due to refinery debottlenecking, new or

expanded heavy oil processing capacity, etc. Using information supplied in a number of these

reports, it appeared that some refiners simply estimated their 2007 production volumes by

applying some fraction to their historical 2002 production volumes. However, it is possible that

other refiners did include such planned capacity increases. Overall, our methodology could

under-estimate highway fuel production in 2007 to some degree, but we believe that the degree

of this under-estimation should be small. We then increased these 2007 highway fuel production

volumes by EIA’s projected increase in total domestic highway diesel fuel production between

2007 and 2014, which is 14.5 percent

We then compared the total projected production of highway diesel fuel in 2007 in each

PADD to the projected demand for highway diesel fuel developed in section 7.1 above. Again,

in both cases, the volumes are representative of those expected for 2014. The highway diesel

fuel sulfur standards are those representative of 2007 prior to this NRLM rule. Production and

demand for PADDs 1 and 3 were combined, due to the large volume of fuel which PADD 3

refiners ship to PADD 1. The results are shown in Table 7.2.1-27.
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Table 7.2.1-27

Projected Production of Highway Fuel in 2007 (Thousand BPD in 2014) 

PADD’s 1 & 3 PADD 2 PADD 4 PADD 5

Required Highway Fuel Production * 1,588.3 1,162.4 187.5 530.9

Projected Production: 15 ppm Highway Fuel 1,878.0 914.8 148.4 468.2

Projected Production: 500 ppm Highway Fuel 62.5 49.5 4.1 20.3

Projected Production: All Highway Fuel 1940.5 964.3 152.5 488.5

Shortfall -352.2 198.1 35.0 42.4

Additional Production of Highway Fuel

Current highway fuel refiners with excess 500 ppm

capacity

0 0 0 2.2 (1)

15 ppm highway fuel produced from high sulfur distillate 0 0 41.8 (4)** 40.5 (4)

Final 15 ppm Highway Fuel Production 1,723.9 914.8 190.2 508.7

Final 500 ppm Highway Fuel Production 62.5 49.5 4.1 22.5

Final Total Highway Fuel Production 1,786.4 964.3 194.3 531.2

* Demand from highway vehicles, spillover of highway fuel to other markets plus highway fuel lost during distribution.

** Number of refineries producing this fuel is shown in parenthesis. 

As can be seen, projected 2007 production of highway diesel fuel in PADDs 1 and 3

significantly exceeds projected demand, while the opposite is true in PADDs 2, 4 and 5. PADD

3 refiners currently supply much of PADD 2's diesel fuel consumption. A comparison of current

shipments from PADD 3 to PADD 2 shows that these shipments far exceed the 198,000 barrel

per day shortfall projected for PADD 2. Therefore, we assumed that PADD 3 refineries would

balance demand for highway fuel in PADD 2. However, PADD 3 currently supplies little or no

fuel to PADDs 4 and 5. Therefore, we assumed that additional refineries would have to produce

highway diesel fuel in 2007 to satisfy demand. A comparison of 2002 production of highway

diesel fuel and refiners’ projected production in 2007 revealed one refinery in PADD 5 which

had excess capacity to produce 500 ppm diesel fuel using its current hydrotreater. Therefore, we

assumed that this refinery would likely produce 500 ppm highway diesel fuel in 2007 by

purchasing credits from other refiners. We projected that the remaining shortfalls would be

made up by refiners constructing new desulfurization capacity to process high sulfur distillate to

15 ppm. We assumed that these refineries would go straight to 15 ppm for two reasons. First, as

long as they were investing to produce highway diesel fuel, they would likely design their

equipment to meet the 15 ppm cap, which would affect all highway fuel in 2010. Second,

whether or not these refiners invested to produce 500 ppm highway diesel fuel in 2006 and

revamped this equipment in 2010 to produce 15 ppm highway diesel fuel has no effect on the

cost of other refiners producing NRLM fuel under this NRLM fuel rule. It was simpler to

assume these refiners invested in one step rather than two. 
Final Regulatory Support Document

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This left an excess highway fuel production of 154,100 barrels per day in PADDs 1 and 3

beyond that necessary to meet the shortfall in PADD 2. We assumed that refiners would adjust

their plans to produce 15 ppm highway diesel fuel in 2007 based on the results of the refiners’

pre-compliance reports. Therefore, we assumed that this excess production would not in fact

occur. To represent this on a refinery specific basis, we assumed that the refiners estimated to

have the highest cost of producing 15 ppm fuel in PADDs 1 and 3 would decide not to produce

this fuel until the 154,100 barrel per day excess was eliminated. We also assumed that this

excess production capacity would be available to produce 500 ppm NRLM fuel in 2007 with

only incremental operation costs, no capital cost. This would be the case for excess 15 ppm fuel

capacity deriving from a revamp of an existing hydrotreater. However, it would not be the case

for grass roots 15 ppm fuel capacity which never was built. Thus, this assumption might have

led to a slight underestimation of the cost of 500 ppm NRLM fuel from 2007-2010. We believe

that the degree of this underestimation is small.

Having developed refinery-specific projections of both total and highway distillate

production, we assumed that the difference was high sulfur distillate. The resulting total

production volumes for 2007 (projected to year 2014) by PADD and for the nation are shown in

Table 7.2.1-28. 

Table 7.2.1-28

“2007" Refiner’s Production of Distillate Fuels (Thousand BPD in 2014) *

PADD Highway Fuel High Sulfur Distillate Total Distillate

1&3 1,786 1,116 2,903

2 964 122 1,086

4 194 21 215

5 531 132 663

Total 3,476 1,391 4,867

* Growth from AEO 2003 Table 17. Includes U.S. Virgin Island refineries.

We repeated this analysis using refiners’ projections of their production of highway diesel

fuel in 2010. One limitation in doing so is that the refiners’ pre-compliance reports for 2010

only apply to the first half of 2010 when they can still use banked credits to produce some 500

ppm highway fuel. We are more interested here in the last half of 2010, when all highway fuel

must meet a 15 ppm cap and NRLM fuel will also have to meet a 15 ppm cap under the final

NRLM program. To accommodate this difference, we assumed that refiners would simply

continue producing 15 ppm fuel at the same rate as they did in the first half of 2010. We also

assumed that refiners would convert production of 500 ppm highway fuel to high sulfur distillate

starting on June 1, 2010 absent the NRLM fuel standards contained in this rule. 
Estimated Costs of Low-Sulfur Fuels

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As was done for the 2007 projections, we then increased these 2010 highway fuel production

volumes by EIA’s projected increase in total domestic highway diesel fuel production between

2010 and 2014, which is 11.0 percent. The results are shown in Table 7.2.1-29 below. 

Table 7.2.1-29

Projected Production and Demand for Highway Fuel in 2010 (Thousand BPD in 2014) 

PADD’s 1 & 3 PADD 2 PADD 4 PADD 5

Required Highway Fuel Production * 1,651.9 1,205.3 194.2 567.2

Projected 15 ppm Highway Fuel Production 2008.3 959.5 153.7 474.1

Shortfall -356.4 245.8 40.6 93.2

Additional Production of 15 ppm Highway Fuel

Produced from high sulfur distillate 41.8 (4) ** 93.2 (7)

Final Production of 15 ppm Highway Fuel 1942.4 914.8 195.5 567.3

* Demand from highway vehicles, spillover of highway fuel to other markets plus highway fuel lost during distribution.

** Number of refineries producing this fuel is shown in parenthesis. 

As for 2007, the projected volume of highway diesel fuel in 2010 by PADD 1 and 3 refiners

exceeds projected demand (plus downgrades in the distribution system), while those of the other

PADDs are less than projected demand. In PADDs 4 and 5, we again assumed that additional

refineries would produce 15 ppm highway diesel fuel from their high sulfur distillate. The

number of PADD 4 refiners was the same as in 2007. In PADD 5, seven additional refineries

were assumed to produce 15 ppm highway diesel fuel, three more than in 2007. 

PADD 2's shortfall was again assumed to be supplied from PADD 3. Again, we assumed

that a number of PADD 1 and 3 refiners would decide not to produce 15 ppm highway fuel so

that these PADD’s production would match demand, after supplanting PADD 2's supply. In

doing this, we also assumed that one PADD 2 refinery would decide not to produce 15 ppm

highway fuel due its much higher desulfurization costs compared to other PADD 2 refineries and

PADD 3 refineries able to supply that area via pipeline transport. 

Having the refinery-specific projections of both total and highway distillate production, we

assumed that the difference was high sulfur distillate. The resulting total production volumes for

2010 (grown to year 2014) by PADD and for the nation are shown in Table 7.2.1-30 below.
Final Regulatory Support Document

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Table 7.2.1-30

“2010" Refiner’s Production of Distillate Fuels Projected (Thousand BPD in 2014) 

Highway Fuel High Sulfur Distillate Total Distillate

PADD’s 1&3 1,942 960 2,903

PADD 2 915 172 1,086

PADD 4 196 20 215

PADD 5 567 96 663

Total 3,620 1,247 4,867

* Growth from AEO 2003 Table 17. Includes U.S. Virgin Island refineries.

Note that we made no changes in the production volumes of distillate fuel to account for any

reduction in wintertime blending of kerosene that might occur as a result of the 15 ppm highway

or NRLM sulfur caps. Kerosene added to 15 ppm diesel fuel must itself meet a 15 ppm sulfur. 

Sometimes, kerosene is added at the refinery and the winterized diesel fuel is sold or shipped

directly from the refinery. At other times, the kerosene blending is done at the terminal,

downstream of the refinery. The former approach may mean adding kerosene to more diesel fuel

than actually requires it. The latter approach requires that a distinct 15 ppm kerosene grade be

produced and distributed. Much of this 15 ppm kerosene might be used in applications not

requiring 15 ppm sulfur content. Adding pour point depressant is an alternative to blending

kerosene. This can be done very flexibly at the terminals in areas facing very cold weather. 

Thus, we expect that the use of pour point depressants will increase and the terminal blending of

kerosene will decrease. For kerosene blended into winter diesel fuel, the kerosene can simply be

added to the distillate being fed to the hydrotreater and desulfurized along with the rest of the 15

ppm diesel fuel pool.

In summary, the primary purpose of developing these future production volumes is to

reasonably project the economies of scale of the desulfurization equipment being constructed in

response to the NRLM fuel program, including the interaction of this program with the 2007

highway fuel program. Larger capacity equipment costs more than smaller equipment in total,

but is less expensive on a per gallon basis. Operating costs are not affected, as these are

proportional to volume. In the NPRM we projected production volumes for calendar year 2008,

as this was the first full year that the NRLM sulfur caps were effective. However, we now

believe that 2014 is more reasonable, because the assumed life of desulfurization equipment is

15 years and 2014 marks the mid-point of the life of equipment built in 2007. 

7.2.1.3.4 Selection of Refineries Producing 500 and 15 ppm NRLM Fuel

We used two basic criteria to select those refineries most likely to produce 500 and 15 ppm

NRLM fuel under this NRLM rule. The first criterion was refineries’ ability to avoid producing
Estimated Costs of Low-Sulfur Fuels

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lower sulfur NRLM fuel (i.e., continue producing high sulfur heating oil). The second criterion

was the estimated cost of compliance. We assumed that those refineries facing the lowest

desulfurization costs in a given region would be the most likely to invest. A key factor in

estimating desulfurization costs on a refinery specific basis is whether the refinery: 1) would be

able to produce 500 or 15 ppm NRLM fuel with its existing hydrotreater, 2) would be able to

revamp an existing hydrotreater to produce NRLM fuel, or 3) would have to build a grass roots

hydrotreater to produce NRLM fuel. These three factors are described below.

7.2.1.3.4.1 Geographic and Logistic Limitations Affecting the Production of Heating Oil

It goes without saying that refiners have to be able to market the fuels which they produce. 

That is the nature of business. This includes the No. 2 distillate that they produce. Most No. 2

distillate volume comes directly from the crude oil itself. It is not feasible, or economical, to

convert all this distillate fuel to other products. Thus, under this NRLM rule, refiners basically

have three choices for this distillate; produce 15 ppm highway diesel fuel, produce 500 and 15

ppm NRLM fuel (depending on the time period) or produce high sulfur heating oil. Producing

high sulfur heating oil should require no change in current refinery configurations, as all of the

No. 2 distillate produced today essentially meets heating oil specifications. 

However, as alluded to above, refiners must be able to deliver their fuel to the geographical

market where it is consumed. The market for high sulfur distillate will decrease by 50 percent

upon the implementation of this NRLM rule. Over two-thirds of all high sulfur distillate use

after 2010 will be concentrated in the Northeast. Thus, PADD 1 refineries should have no

difficulty in selling high-sulfur distillate to this market if they desired. Likewise, PADD 3

refineries which are connected to one of the two large pipelines running from the Gulf Coast to

the Northeast (Plantation and Colonial) or which have access to ocean transport should also be

able to market high sulfur distillate. In addition, selected markets in PADD 5, such as Hawaii,

also have significant heating oil demand, so some PADD 5 refineries were also assumed to have

the flexibility to continue producing high-sulfur distillate if they desired. 

As discussed in Section 7.1 above, however, the heating oil markets in PADDs 2 and 4 will

be very small after the NRLM rule takes effect. Thus, we believe that it is unlikely that pipelines

in these PADDs will continue to carry heating oil as a fungible product. Therefore, we do not

believe that refineries located in PADDs 2 and 4 will have the option of choosing to avoid

complying with the NRLM fuel program by producing high sulfur distillate. To the degree that

they are not already producing 15 ppm highway diesel fuel, they will have to take steps to

produce 500 ppm and 15 ppm NRLM fuel. The same is true for refineries located in PADDs 3

and 5 which do not have access to a large local market for heating oil or which are not connected

to efficient transport to the Northeast. The final NRLM rule does not require that these refineries

produce NRLM fuel, per se. We simply believe that this is a reasonable assumption for costestimation purposes. 

We reviewed the geographical location of each domestic refinery and those of pipelines

serving the Northeast and identified those falling into the two groups described above. The

number of refineries projected to have no choice but to produce NRLM diesel fuel is shown in
Final Regulatory Support Document

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Table 7.2.1-31 along with the total number of refineries projected to produce high-sulfur

distillate fuel after implementation of the 2007 highway diesel rule. These projections consider

the small refiner provisions included in the NRLM final rule. These provisions reduce the

number of refineries projected to have to produce 500 ppm NRLM fuel in 2007, as small refiners

are assumed to be able to sell high sulfur diesel fuel to the NRLM market.

Table 7.2.1-31

Number of Refineries Lacking the Option to Produce Heating Oil

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5

Prior to NRLM Rule Implementation considering Fully Implemented Highway Diesel Program

Refineries Producing Some High-Sulfur

Distillate Fuel 

13 17 37 8 17

Starting June 1, 2007 (Considers Small Refiner Provisions)

Must produce 500 NRLM fuel 0 14 4 7 0

Refineries Producing Some High-Sulfur

Distillate Fuel 

13 3 33 1 17

Starting June 1, 2010 (Considers Small Refiner Provisions)

Must produce 15 Nonroad fuel 0 6 0 3 0

Must produce 500 NRLM fuel 1 11 9 5 5

Refineries Producing Some High-Sulfur

Distillate Fuel 

12 0 28 0 12

Starting June 1, 2012 (Considers Small Refiner Provisions)

Must produce 15 NRLM fuel 0 14 4 7 0

Must produce 500 NRLM fuel 1 3 5 1 5

Refineries Producing Some High-Sulfur

Distillate Fuel 

12 0 28 0 12

We repeated this analysis for 2010. The number of refineries producing some high sulfur

distillate fuel in 2010 is less than in 2007, as additional refineries produce either 15 or 500 ppm

NRLM fuel. The number of refineries projected to have to produce NRLM fuel in 2010 due to

distribution system constraints increases over that in 2007 due to the expiration of the small

refiner provisions. While we project that the vast majority of 15 ppm nonroad fuel will be

produced by those refineries facing the lowest desulfurization costs, we project that a few

refineries will have to invest to produce 15 ppm nonroad fuel because of limited ability to

distribute higher sulfur fuel to the L&M and heating oil markets. These refineries produce a

large volume of 500 ppm NRLM fuel in 2007 and are not directly connected to a pipeline or

navigable waterway. Given the volume of fuel involved, we decided that shipping all of it via

rail was also not economically feasible long term. The number of these constrained refineries is
Estimated Costs of Low-Sulfur Fuels

7-133

much fewer than those which we project will be unable to distribute all of their distillate fuel to

the heating oil market and thus had to produce make 500 ppm NRLM fuel in 2007. 

In 2012, the number of refineries that must produce NRLM fuel is the same as 2010. 

However in 2012, the non-small refineries that we project have to produce 500 ppm L&M fuel in

2010 invest further to produce 15 ppm L&M fuel. 

In 2014, the only change is the expiration of the small refiner provisions. The small

refineries producing 500 ppm nonroad fuel in 2012 invest to produce 15 ppm NRLM fuel. The

refinery estimates for years 2007-2012 are shown in Table 7.2.1-31. 

Table 7.2.1-32 shows how the NRLM fuel volume produced by these refineries compares

with the total required NRLM fuel production volume during the 2007-2010 period. This table

starts with the total demand for NRLM fuel, as well as the volume of highway fuel used in the

NRLM fuel markets as developed in Section 7.1. Table 7.2.1-32 also shows the volume of high

sulfur distillate projected for small refiners which are able to sell high sulfur diesel fuel to the

NRLM market during this period. Subtracting the volumes of highway spillover and small

refiner fuel from total demand results in the net volume of 500 ppm NRLM fuel which needs to

be produced in response to this NRLM rule. The 500 ppm fuel volumes from refineries having

to produce this fuel are then shown, along with any remaining volume. It should be noted that

we have excluded demand for NRLM fuel in California from Table 7.2.1-32 and the analogous

tables for 2010, 2012 and 2014. Nonroad fuel sold in California is already required to meet a 15

ppm cap in this timeframe per State regulation. L&M fuel demand in California is totally

satisfied by spillover of highway fuel and downgrade. Thus, we project no on-purpose

production of L&M fuel for use in California. However, distillate production from two

California refineries which current produce high sulfur distillate fuel is considered in satisfying

NRLM fuel demand in PADD 5.

Table 7.2.1-32

500 ppm NRLM Fuel Production: 2007-2010 (million gallons per year in 2014) *

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

Total NRLM Fuel Demand 9,034 7,111 1,046 1,159 18,350

Highway Fuel Spillover 898 1,906 580 381 3,765

Fuel Produced Under Small

Refiner Provisions

671 139 5 165 980

NRLM Requiring Desulfurization 7,465 5,066 461 613 13,605

Refineries Having to Produce 500

ppm NRLM Fuel

281 2,549 303 0 3,133

Remaining Production of 500

ppm NRLM Diesel Fuel

7,184 2,517 158 613 10,472

* Excludes NRLM fuel demand in California.
Final Regulatory Support Document

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As can be seen, more than enough 500 ppm fuel will be produced in PADDs 2 and 4 by

refineries having to produce this fuel. This is a direct result of assuming that no refinery in

either of these PADDs will be able to market all of their current high sulfur distillate fuel solely

as heating oil. Significant volumes of 500 ppm NRLM fuel will still have to be produced by

PADD 1, 3 and 5 refineries. As discussed above, we assume that the refineries facing the lowest

desulfurization costs in each PADD will choose to invest to produce any remaining fuel demand

in that PADD. 

It should be noted that we evaluated small refiners’ ability to distribute their production

volume of high-sulfur NRLM diesel fuel, even if they do not have access to a common carrier

pipelines carrying this fuel. Starting with the total demand for NRLM diesel fuel in each PADD

in 2014 from Section 7.1 above, we divided this demand by the square mileage of each PADD to

estimate NRLM diesel fuel demand per square mile. We then determined the area over which

each small refiner would have to distribute its high-sulfur NRLM fuel to maintain its current

high sulfur distillate production level. In all cases, assuming a circular shaped area, the radius of

the circle was 100 miles or less. As this is easily within trucking distance, we concluded that it

was reasonable to assume that all small refiners can continue selling all their high-sulfur

distillate fuel as either high-sulfur distillate fuel or heating oil, and delay producing any 500 ppm

NRLM diesel fuel until at least 2010.

Table 7.2.1-33 presents the same breakdown of nonroad fuel supply for the period 2010-

2012, with the implementation of the 15 ppm cap. Just over 20% of nonroad fuel demand is

satisfied by highway spillover and just under 10% by distribution downgrade. Small refiner 500

ppm fuel supplies roughly 5% of the market, with the remainder being new 15 ppm fuel

production. Less than 10% of the new 15 ppm nonroad fuel production is by refineries having

no economic choice but to do so, the vast majority of 15 ppm nonroad fuel is produced by

refineries with the lowest cost of production. The volume of 15 ppm nonroad fuel that has to be

produced by refineries with no other economic choice is significantly than was the case for 500

ppm NRLM fuel in 2007. This occurs, because the L&M market is much larger than the heating

oil market in PADDs 2, 4 and 5 and most refineries can ship their fuel via pipeline or waterway

to the L&M market. 
Estimated Costs of Low-Sulfur Fuels

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Table 7.2.1-33

15 ppm Nonroad Fuel Production: 2010-2012 (million gallons per year in 2014) *

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

Total Nonroad Fuel Demand 5901 5,670 810 934 13,315

Highway Spillover 551 1,535 451 341 2,878

Distribution Downgrade 217 519 111 264 1,111

Small Refiner Volume (500 ppm nonroad fuel) 419 139 5 165 728

New Production of 15 ppm Nonroad Fuel 4,714 3,477 243 164 8,598

Refineries Having to Produce 15 ppm Nonroad

Fuel

0 631 157 0 728

Remaining Production of 15 ppm Nonroad Fuel 4,714 2,846 86 164 7,810

* Excludes NRLM fuel demand in California.

Table 7.2.1-34 presents the same breakdown of L&M fuel supply for the period 2010-2012. 

Just under 20% of nonroad fuel demand is satisfied by highway spillover and another 20% by

distribution downgrade. We project that small refiner 500 ppm fuel will be used in the nonroad

fuel market, where it has an economic advantage. Distribution of this fuel should be

economically feasible, given the small volumes involved and the ubiquitous nature of the

nonroad fuel market. Thus, no L&M fuel is supplied by small refiners during this time frame. 

Thus, roughly 60% of 500 ppm L&M fuel is being produced for the L&M market. Nearly 80%

of this 500 ppm L&M fuel production is by refineries which are unable to economically

distribute heating oil, so they have to produce a lower sulfur fuel. In PADDs 2 and 4, the

volume of 500 ppm fuel produced by refineries with no other economic choice is greater than the

remaining demand for L&M fuel. We assumed that the excess production of 500 ppm fuel

refineries in the eastern and southern regions of PADD 2 could be satisfy L&M demand in

PADDs 1 and 3, respectively. This still leaves a significant volume of 500 ppm L&M fuel

needing to be produced by refineries in PADDs 1 and 3. We assumed that excess 500 ppm fuel

in PADD 4 would be used in the heating oil market. As usual, we assumed that refineries with

the lowest desulfurization costs in PADDs 1,3 and 5 would invest to produce the remaining 500

ppm fuel demand.
Final Regulatory Support Document

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Table 7.2.1-34

500 ppm NRLM Fuel Production: 2010-2012 (million gallons per year in 2014) *

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

Total L&M Fuel Demand 3,133 1,441 236 224 5,034

Highway Fuel Spillover 347 371 129 50 897

Distribution Downgrade 866 134 33 40 1,073

NRLM Requiring Desulfurization 1,920 936 74 134 3,064

Refineries Having to Produce 500

ppm L&M Fuel

281 1,918 153 0 2,352

Remaining Production of 500

ppm NRLM Diesel Fuel

1,639 (982) (79) 134 712

500 ppm Nonroad Fuel Produced

by Small Refiners 

419 139 5 165 728

Total New 500 ppm Production 2,058 (843) (74) 299 1,440

* Excludes NRLM fuel demand in California.

Table 7.2.1-35 presents the same breakdown of 15 ppm NRLM fuel volumes for the period

2012-2014 when the L&M standard goes to 15 ppm. 

Table 7.2.1-35

15 ppm NRLM Fuel Production: 2012-2014 (million gallons per year in 2014) *

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

Total NRLM Fuel Demand 9,034 7,111 1,046 1,159 18,350

Highway Spillover 898 1,906 579 390 3,773

Distribution Downgrade 467 685 147 304 1,603

Fuel Produced Under Small Refiner Provisions 419 139 5 165 728

Production of 15 ppm NRLM Fuel 7,250 4,381 316 300 12,247

Refineries Having to Produce 15 ppm NRLM Fuel 281 2,549 310 0 3,140

Remaining Production of 15 ppm NRLM Fuel 6,969 1,832 6 300 9,107

* Excludes NRLM fuel demand in California.

Finally, Table 7.2.1-36 presents the same breakdown of 15 ppm NRLM fuel volumes for the

2014 and beyond. The required production volumes of 15 ppm NRLM fuel in 2014 are larger

than those in 2012, as the small refiner provisions expire and downgraded 15 ppm fuel can no

longer be sold to the nonroad fuel market. 
Estimated Costs of Low-Sulfur Fuels

7-137

Table 7.2.1-36

15 ppm Nonroad Fuel Production: 2014 and Beyond (million gallons per year in 2014) *

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

Total NRLM Fuel Demand 9,034 7,111 1,046 1,159 18,350

Highway Spillover 898 1,906 579 390 3,773

Downgraded “500 ppm” NRLM Fuel 467 685 146 246 1,544

Fuel Produced Under Small Refiner Provisions 0 0 0 0 0

New Volume of 15 ppm Nonroad Fuel 7,668 4,520 321 523 13,032

Refineries Having to Produce 15 ppm NRLM Fuel 701 2,688 315 165 3,869

Remaining Production of 15 ppm NRLM Fuel 6,967 1,832 6 358 9,163

* Excludes NRLM fuel demand in California.

Sensitivity Case: Long-Term 500 ppm NRLM cap. Table 7.2.1-37 presents an analogous

set of 500 ppm NRLM production volumes for 2010 assuming that no 15 ppm NRLM fuel cap

was implemented. (This situation is analyzed to allow the long-term analysis of the 500 ppm

NRLM diesel fuel cap independent of the 15 ppm nonroad diesel fuel cap). The primary

difference between these volumes and those for 2007 above is the absence of the small-refiner

volume and fuel to the NRLM pool from distribution downgrade.

Table 7.2.1-37

500 ppm NRLM Fuel Production: 2010 and beyond* (million gallons per year in 2014) 

PADDs 1 & 3 PADD 2 PADD 4 PADD 5 U.S.

NRLM Diesel Fuel Demand 9,034 7,111 1,046 1,159 18,350

Distribution Downgrade 1,084 685 147 304 2,220

Highway Spillover 898 1,906 579 390 3,773

Base High-Sulfur NRLM Demand 7,052 4,520 320 465 12,357

Fuel Produced Under Small Refiner Provisions 0 0 0 0 0

Volume Having to Produce 500 ppm NRLM Fuel 701 2,688 315 165 3,869

Remaining Demand for 500 ppm NRLM Diesel Fuel 6,351 1,832 5 300 8,488

a

 After all small refiner provisions have expired.

Sensitivity Case: 15 ppm Nonroad and 500 ppm L&M Fuel

This case examines the proposed fuel control program, which is identical to that being

promulgated, except that locomotive and marine fuel remains at 500 ppm indefinitely. The only

difference in the geographical constraints assumed to exist is that PADD 2 refiners were allowed
Final Regulatory Support Document

7-138

to continue producing 500 ppm locomotive and marine fuel in 2010 and beyond. The result was

that some 15 ppm nonroad fuel being consumed in PADD 2 is being produced in PADD 3. This

shipment of 15 ppm fuel from PADD 3 to PADD 2 occurs under the final NRLM fuel program,

as well.

7.2.1.3.4.2 Low Sulfur NRLM Fuel Via Existing, Revamped or Grass Roots Hydrotreater

This section presents the methodology that we used to determine what actions refiners would

likely take to produce 500 and 15 ppm NRLM diesel fuel during the implementation of the

NRLM diesel fuel program. The timing of the various steps in both the highway and NRLM fuel

programs are summarized in Table 7.2.1-38.

Table 7.2.1-38

Sequence of Sulfur Caps for Highway and NRLM Fuel

Highway Fuel

Non-Small Refiners

Small Refiners Nonroad Fuel L&M Fuel

June 1, 2006 - May 31, 2007 80 vol% 15 ppm

20 vol% 500 ppm

High Sulfur High Sulfur High Sulfur

June 1, 2007- May 31, 2010 80 vol% 15 ppm

20 vol% 500 ppm

500 ppm 500 ppm High Sulfur

June 1, 2010 - May 31, 2012 15 ppm 15 ppm 500 ppm 500 ppm

June 1, 2012 - May 31, 2014 15 ppm 15 ppm 15 ppm 500 ppm

June 1, 2014 and beyond 15 ppm 15 ppm 15 ppm 15 ppm

In Section 7.2.1.3.3, we describe how we coupled refiners’ projected highway fuel volumes

with historic total distillate production fuel volumes and EIA future growth rates for highway

and high sulfur distillate fuels to project each refinery’s production of highway and high sulfur

distillate fuel prior to this NRLM fuel program. The issue in this section is the steps which

refiners have to take to produce 15 and 500 ppm NRLM fuel beyond this baseline to comply

with the NRLM standards. The primary question answered in this section is whether they will

be able to revamp an existing hydrotreater, or must build a new hydrotreater. For 15 ppm

highway fuel, we basically assumed, as we did in the Final RIA for the 2007 highway fuel

program, that 80 percent of 15 ppm highway fuel volume would be produced using revamped

hydrotreaters. The remaining 20 percent would be produced with new, grass-roots units. The

remainder of this section develops analogous projections for the production of 500 ppm and 15

ppm NRLM fuel during the various steps of the NRLM fuel program.

To facilitate this discussion, we divided refineries which are projected to produce some high

sulfur distillate after 2010 into three categories:
Estimated Costs of Low-Sulfur Fuels

BB We also included a few refineries which project producing 15 ppm highway fuel in 2010,

but whose highway fuel is not needed to fulfill highway fuel demand in 2010. 

7-139

1) “Highway” refineries: refineries which produce 95 percent or more of their total distillate

production as 15 ppm highway diesel fuel;BB

2) “High Sulfur” refineries: refineries which produce 90 percent or more of their total

distillate production as high sulfur distillate; 

3) “Mix” refineries: refineries which produce some high sulfur distillate and which do not

fall into categories one or two above.

Table 7.2.1-39 presents the percentages of high-sulfur distillate fuel production that falls in

the categories described above. The number of refineries in each category is further broken

down as to whether or not it currently has a distillate hydrotreater. This latter aspect is relevant

to desulfurization costs as discussed in Section 7.2.1.3.2 above. 

Table 7.2.1-39

Distribution of High-Sulfur Distillate Production (%) a

High-Sulfur

Refineries

Mixed Refineries

Producing 15 ppm

Highway Fuel in 2006

Mixed Refineries

Producing 15 ppm

Highway in 2010

Highway Refineries

W/Dist

HT

No Dist

HT

W/Dist

HT

No Dist

HT

W/Dist

HT

No Dist

HT

W/Dist

HT

No Dist

HT

Number of

Refineries

10 25 37 11 1 0 7 1

Percent of

Nonroad Fuel

31 15 38 14 1 0 1 0

a

 “ W/Dist HT” means refineries currently having a distillate hydrotreater

 “No Dist HT means refineries that do not currently have a distillate hydrotreater

The next three sub-sections address how we project that each of these groups of refineries

could produce either 500 or 15 ppm NRLM fuel. The final sub-section summarizes the results.

Highway Refineries: This category primarily includes refineries which are projected to

produce 95 percent or more of their the No. 2 distillate fuel in 2010 to the 15 ppm highway

standard prior to this NRLM rule. Refineries producing 100 percent highway fuel have no

distillate fuel left from which to produce 500 or 15 ppm NRLM fuel. Thus, with one exception,

they are ignored in this analysis. The exception is that the refiners’ pre-compliance reports

showed an excess supply of 15 ppm highway fuel in PADDs 1 and 3. Production of NRLM fuel

by highway refineries presumed to supply this excess is addressed slightly differently below.

Refineries in this category produce a very small amount of high-sulfur distillate fuel

compared with their volume of highway diesel fuel. This small volume of high-sulfur distillate

fuel is likely either off-specification diesel fuel or opportunistic sales to the non-highway diesel
Final Regulatory Support Document

7-140

fuel market because of advantageous prices, market relationships, etc. Thus, we assumed that

the refinery could incorporate this high-sulfur distillate into its highway hydrotreater design. 

The incremental capital cost assigned to the NRLM diesel fuel program was assumed to be the

difference between the capital cost associated with a grass-roots hydrotreater sized to process all

the refinery’s distillate fuel and that for a grass-roots hydrotreater sized to treat just the highway

diesel fuel volume. Thus, this approach assumed that the incremental cost of this small increase

in capacity could occur at a high degree of economy of scale, but would also encompass the full

cost of hydrotreating from uncontrolled levels to 7 ppm. We did this because it seems

reasonable to assume that a refinery producing so much highway fuel would design its 15 ppm

hydrotreater in such a way that it could be modified to process all the refinery’s distillate. This

is particularly true given the public attention given to the need for 15 ppm nonroad diesel fuel

over the past few years. 

This approach is applied to both the production of 500 and 15 ppm NRLM fuel. While

incorporating the production of 500 ppm NRLM fuel into a 15 ppm highway fuel hydrotreater is

not necessarily straightforward, the net effect of our assumption here is that roughly half the

capital cost to produce 15 ppm NRLM fuel at these refineries is required to produce 500 ppm

NRLM fuel. This seems reasonable. Also, this assumption only affects capital costs, not

operating costs, as the latter are only a function of the distillate composition and refinery

location (i.e., PADD). 

As described in Section 7.2.1.3.3 above, the highway pre-compliance reports showed that an

excess of 15 ppm fuel capacity was likely in PADD 3 in 2007. Thus, we assumed that this

capacity could supply 500 ppm NRLM to PADDs 1, 2 and 3 through 2010 at a relatively low

cost. To approximate these “low” costs we assumed that 500 ppm NRLM fuel could be

produced by these hydrotreaters at the national average cost of the remainder of the 500 ppm

NRLM fuel. 

Figure 7.2-6 presents a flowchart of this process for highway refineries.
Estimated Costs of Low-Sulfur Fuels

7-141

Hwy

Refineries -

3

Minor

Hwy HT

Revamp - 2

Minor

Hwy HT

Revamp -

3

2

Figure 7.2-6

“Highway” Refineries NRLM Hydrotreater Modifications

500 ppm

 NRLM

in 2007

15 ppm

NRLM

in 2010

HT = Hydrotreater

Hwy = Highway

Number in box equals number of refineries.

Mix Refineries: Mix refineries produce substantial volumes of both highway and high

sulfur distillate fuels prior to the NRLM rule. Because of the substantial volumes of both fuels

being produced, we assumed that the 15 ppm hydrotreater being used to produce highway fuel

could not be revamped to incorporate production of 500 or 15 ppm NRLM fuel. Thus, with one

exception, we assumed that the production of 500 ppm NRLM fuel by mix refineries would

require would require a grass roots hydrotreater. The later production of 15 ppm NRLM fuel

was assumed to be a revamp of this 500 ppm hydrotreater, given that the 500 ppm unit was

designed knowing that the nonroad and L&M caps would soon be 15 ppm. Thus, with two
Final Regulatory Support Document

CC The calculation of incremental capital costs in this situation is not straightforward. We

provided an example calculation below to better explain our methodology in Section 7.2.1.5.3 of

the Draft RIA to this rule. The reader interested in the details of this calculation is referred to

that discussion.

7-142

exceptions, there are no presumed synergies between the highway and NRLM fuel programs for

these refineries.

One exception to this assumption involved the way certain refineries are expected to produce

their 15 ppm highway fuel. As described above, we project that 80 percent of 15 ppm highway

fuel can be produced via a revamp of the existing highway fuel hydrotreater. The remaining 20

percent of highway fuel volume will be produced with a new grass roots hydrotreater. In these

latter cases, the current highway hydrotreater will be available to produce 500 ppm NRLM fuel

at no capital cost. 

We did not attempt to identify the specific refineries which were likely to build a new grass

roots hydrotreater for 15 ppm highway fuel production. This decision depends on many factors,

most of which involve proprietary data. Thus, we assumed that 20 percent of the highway fuel

from highway refiners and 20 percent of the highway fuel from mix refiners was being produced

with a new grass roots unit. We assumed that 20 percent of the high sulfur distillate production

from mix refiners could be produced with these hydrotreaters at no capital cost. Then in 2010

and 2012, new grass roots units would be required to produce 15 ppm nonroad and 15 ppm L&M

fuel, as was assumed for the other mix refineries.

The other exception was a single refinery which projected that they would not begin

producing 15 ppm highway diesel until 2010. In this case, there would be sufficient leadtime for

these refineries to combine their plans to produce 15 ppm highway fuel with those to produce 15

ppm NRLM fuel.CC This provides an opportunity for economy of scale by combining both

highway and NRLM fuel volumes in a single process unit, as well as affording an opportunity

for the use of advanced desulfurization technology. 

Figure 7.2-7 presents a flowchart of this process for mix refineries.
Estimated Costs of Low-Sulfur Fuels

7-143

2006 Mix

Refineries -

41

New

500 ppm HT19

Use Existing

Hwy HT4

Revamp to

15 ppm11

New

15 ppm HT9

New 500

ppm HT4

Revamp to

15 ppm5

New

15 ppm HT1

1 1

11

4

6

2010 Mix

Refineries -

1

New

500 ppm HT1

Minor Hwy

HT Revamp1

500 ppm

NRLM

in 2010

15 ppm

L&M

in 2012

500 ppm

NRLM

in 2007

15 ppm

NRLM

in 2010

HT = Hydrotreater

Hwy = Highway

L&M = Locomotive and Marine diesel fuel

Number in box equals number of refineries.

Figure 7.2-7

“Mix” Refineries NRLM Hydrotreater Modifications

None - High Sulfur

NRLM Fuel7

Exits

Market2

1

2

Revamp to

15 ppm7 7

4

New

15 ppm HT6 4

2

15 ppm

NRLM

In 2014
Final Regulatory Support Document

7-144

High Sulfur

Refineries -

24

New 500 ppm

HT8 *

Use Existing

Hwy HT2

New 15

ppm HT2

Revamp to

15 ppm6

New 500

ppm HT9

New 15

ppm HT1

Revamp to

15 ppm9

Exits

Market -

1

2

Figure 7.2-8

“High Sulfur” Refineries NRLM Hydrotreater Modifications

HT = Hydrotreater

Hwy = Highway

L&M = Locomotive and Marine diesel fuel

Number in box equals number of refiners.

* One refinery installs a new HT and also uses it’s existing Highway HT

 to make 500 ppm fuel.

500 ppm

NRLM

in 2010

15 ppm

L&M

in 2012

500 ppm

 NRLM

in 2007

15 ppm

NRLM

in 2010

Exits

Market3

None High Sulfur

NRLM Fuel12

9

1

1

2

1

Revamp to

15 ppm2

2

15 ppm

NRLM

In 2014
Estimated Costs of Low-Sulfur Fuels

7-145

High Sulfur Refineries: These refineries are projected to produce little or no 15 ppm highway

fuel in 2010 in response to the 2007 highway diesel rule. Therefore, we assume that any 500

ppm NRLM fuel produced would require a grass-roots hydrotreater. The production of 15 ppm

NRLM fuel was assumed to be a revamp of this 500 ppm hydrotreater, given that the 500 ppm

unit was designed knowing that the nonroad and L&M caps would soon be 15 ppm. Thus, there

are no presumed synergies between the highway and NRLM fuel programs for these refineries.

One exception to this approach is a set of three refineries which currently produce highway

diesel fuel, but project in their pre-compliance reports to cease highway fuel production in 2006. 

Because they produce no highway fuel after 2006, by definition these refineries fall into the high

sulfur refinery category. However, they clearly have the hydrotreating capacity to produce 500

ppm fuel up to their current highway fuel production. We assumed that this hydrotreating

capacity was available at no capital cost to produce 500 ppm NRLM fuel in 2007. We also

assumed that a grass roots hydrotreater would be needed to produce 15 ppm fuel in either 2010

for nonroad or for 2012 for L&M, as these refiners’ decisions to leave the highway market likely

indicated an inability to produce 15 ppm fuel via a revamp. As it turns out, only two of these

three refineries had sufficient hydrotreating capacity from the highway hydrotreater to treat all

their distillate production. Thus, we assumed that the third refiner would have to construct a new

grass roots hydrotreater to produce 500 ppm NRLM fuel.

Figure 7.2-8 presents a flowchart of this process for high sulfur refineries.

We presume that these refineries must build a new hydrotreater in 2007 to desulfurize their

current high-sulfur distillate to 500 ppm. However, due to the significant amount of lead time

available, we project that these refiners can design a revamp to desulfurize all their distillate fuel

to 15 ppm in 2010 or 2012 if they choose to do so.

Summary of Results: Overall, for the final NRLM fuel program, we project that 63

refineries will invest to make 15 NRLM diesel fuel by 2014. Table 7.2.1-40 summarizes the

steps which we expect refineries affected by the NRLM rule to take in meeting the highway and

NRLM sulfur caps in the relevant time periods. We have separated refineries into three

categories, depending on the relative proportion of highway and high sulfur distillate fuel that

they produce after the 2007 highway fuel program, but prior to this NRLM fuel rule. 
Table 7.2.1-40

Interaction Between Compliance with the 2007 Highway and Final NRLM Fuel Programs:

Refiners Projected to Produce Some High Sulfur Distillate Fuel in 2007 Prior to the NRLM Fuel P

Refineries that 

Year and 

Fuel Control

Highway

Refiners

Mix 2006 Refinersa Mix 2010 Refinersa High Sulfur 

Units New

Units

Revamp

Units

None New

Units

Revamp

Units

None New

Units

Reva

Un

Modifications tocomply with the 15ppm HighwayStandard (Baseline)*

2006 3 13(6)a 26

2010 0 1

Total 3 39 1 22 

New Modificationsto comply withNRLM Standards.

2007 

500 ppm NRLM

2 19(2) 0 4 1(1) 0 0 8 0 

2010

500 ppm NRLM

0 4(2) 0 0 0 0 0 9 0 

2010

15 ppm NR

3 9(1) 11(3) 0 0 0 1 2 6 

2012

15 ppm L&M

0 6(0) 7(0) 0 0 0 1 0 2 

2014

15 ppm NRLM

0 1(0) 5(2) 0 0 0 0 1 9 

a Numbers in parentheses are a subset for each category and represent mix refineries that currently have no highway diesel fuel hydrotreater.b Two high sulfur refiners use their “idled” hwy hydrotreater to make 500 ppm NRLM fuel and exit the NRLM market when the NRLM sulfu

ppm.
Estimated Costs of Low-Sulfur Fuels

7-147

As shown in Table 7.2.1-40, we project that 36 refiners would produce 500 ppm NRLM fuel

in 2007. Of these 36 refineries:

- 28 will install new hydrotreaters

- 2 “highway” refiners would perform a relatively minor revamp to their highway distillate

hydrotreaters, and

- 7 refineries could produce 500 ppm NRLM diesel fuel with an “idled” highway

hydrotreater..

Twenty-six of the refineries that produce 500 ppm NRLM fuel have indicated that they will

produce 15 ppm highway fuel in 2006 and are categorized as follows; twenty-three 2006 mix

refineries, 2 highway refineries and one 2010 mix refinery. The seven refiners who use their

“idled” treaters to produce NRLM are categorized as follows; four were projected to build a new

hydrotreater to produce 15 ppm highway diesel fuel and will use their old highway treater to

produce 500 ppm NRLM fuel. The other three refineries currently produce 500 ppm highway

fuel, but indicated in their pre-compliance report that they would no longer produce highway

diesel fuel starting in 2006. (Thus, these refineries were categorized as high sulfur refineries for

the purpose of this analysis). One of these three refineries was also projected to install a new

hydrotreater to process additional high sulfur distillate, as the capacity of their existing

hydrotreater was not sufficient to process all their high sulfur distillate volume. 

For all of the refineries using their “idled” highway unit, we used their operating cost to

desulfurize each refineries high sulfur distillate to 500 ppm as the cost for complying with

NRLM standard. Additionally, four refineries in PADD’s 1&3 were assumed to invest to fulfill

supply shortfalls in PADD 2. We also assumed that excess hydrotreater capacity from the

highway fuel program in PADD’s 1&3 is used to supply 500 ppm NRLM volume demand. This

amounted to about 20 percent of the national NRLM demand.

In 2010, we project that 32 refineries will produce 15 ppm nonroad fuel while 26 refineries

will produce 500 ppm NRLM (one refinery produces 15 ppm nonroad and 500 ppm L&M fuel). 

Thus, a total of 57 refineries produce NRLM fuel which is 21 more than produced 500 ppm

NRLM fuel in 2007, despite the volume of fuels being similar. There are two reason for the

additional refinery participation in 2010. One, the increase in the number of refineries affected

is the availability of idled “highway” hydrotreaters for 500 ppm fuel production in 2007. The

capacity of these hydrotreaters is relatively large, so a few of these refineries can produce a large

volume of 500 ppm NRLM fuel in 2007. However, these refineries’ costs to produce 15 ppm is

not always competitive with other refineries in their PADD. Thus, many of these refineries are

not projected to produce 15 ppm nonroad fuel in 2010. Their volume of nonroad fuel is replaced

by other refineries producing less volume per refinery. Two, small refineries invest to produce

500 ppm NRLM fuel due to the expiration of the small refiners provisions which allow high

sulfur distillate to be sold to the 500 ppm NRLM market. Thus, the total number of refineries

producing 15 nonroad fuel and 500 ppm L&M in 2010 increases. 

In 2012, we project that an additional 15 refineries will invest to produce 15 ppm fuel when

the L&M sulfur cap is lowered to 15 ppm. This is 15 additional refineries producing 15 ppm

fuel than in 2010. Fifteen refineries continue to produce 500 ppm NRLM fuel.
Final Regulatory Support Document

DD The capital cost is estimated at this other throughput using an exponential equation termed the “six-tenths

rule.” The equation is as follows: (Sb/Sa)e

×Ca=Cb, where Sa is the size of unit quoted by the vendor, Sb is the size

of the unit for which the cost is desired, e is the exponent, Ca is the cost of the unit quoted by the vendor, and Cb is

the desired cost for the different sized unit. The exponential value “e” used in this equation is 0.9 for splitters and

0.65 for desulfurization units (Peters and Timmerhaus, 1991).

7-148

In 2014, with the expiration of the small refiner provisions, and additional 16 refineries

invest to produce 15 ppm NRLM fuel.

7.2.1.4 Summary of Cost Estimation Factors

This section presents a variety of costs, such as those for electricity and natural gas, as well

as cost adjustment factors.

7.2.1.4.1 Capital Cost Adjustment Factors

Unit Capacity: The capital costs supplied by the vendors of desulfurization technologies

apply to a particular volumetric capacity. We adjust these costs to represent units with lower or

higher volumetric capacity using the “sixth tenths rule.”DD According to this rule, commonly

used in the refining industry, the capital cost of a piece of equipment varies in proportion to the

ratio of the new capacity to the base capacity taken to some power, typically 0.6. This allows us

to estimate how the capital cost might vary between refineries due to often large differences in

the amount of distillate fuel they are desulfurizing.

Stream Day Basis: The EIA data for the production of distillate by various refineries are on

a calendar basis. In other words, it is simply the annual distillate production volume of the

period of interest divided by the number of days in the period. However, refining units are

designed on a stream day basis. A stream day is a calendar day in which the unit is operational,

or is expected to be operational. Refining units must be able to process more than the average

daily throughput due to changes in day-to-day operations, to be able to handle seasonal

difference in diesel fuel production and to be able to re-treat off-specification batches. The

capital costs for the desulfurization technologies were provided on a stream day basis. 

Actual refining units often operate 90 percent of the time, or in other words, can process 90

percent of their design capacity over the period of a year. However, when designing a new unit,

it is typical to assume a lower operational percentage. We assumed that a desulfurization unit

will be designed to meet its annual production target while operating only 80 percent of the time. 

This means that the unit capacity in terms of stream days must be 20 percent greater than the

required calendar day production. 

Off-site and Construction Location Costs: The capital costs provided by vendors do not

include off-site costs, such as piping, tankage, wastewater treatment, etc. They also generally

assume construction on the Gulf Coast, which are the lowest in the nation. Off-site costs are

typically assumed to be a set percentage of the on-site costs. 
Estimated Costs of Low-Sulfur Fuels

7-149

The off-site cost factors and construction location cost factors used in this analysis were

taken from Gary and Handewerk.37 The offsite factors provided by Gary and Handewerk apply

to a new desulfurization unit. Off-site costs are much lower for a revamped unit, as the existing

unit is already connected to the other units of the refinery, utilities, etc. Thus, we reduced the

off-site factors for revamped units by 50 percent.38 

The off-site factors vary by refinery capacity, while the construction location factors vary

between regions of the country.39 In our analysis of the costs for the Tier 2 gasoline sulfur rule,

we estimated the average of each factor for each PADD. There, all the naphtha desulfurization

units were new units. Thus, the PADD-average off-site factors developed for that rule were

simply divided by two to estimate PADD-average factors for revamped units here. The resulting

factors are summarized in Table 7.2.1-41. 

Table 7.2.1-41

Offsite and Construction Location Factors 

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5

Offsite Factor

- New Unit

- Revamped Unit

1.26

1.13

1.26

1.13

1.20

1.10

1.30

1.15

1.30

1.15

Construction Location Factor 1.5 1.3 1 1.4 1.2

Additional Capital Costs: There are also likely some capital costs associated with equipment

not included in either the vendor’s estimates, nor the general off-sites. Examples include

expansions of the amine and sulfur plants to address the additional sulfur removed, a new sulfur

analyzer. Additionally, there are other capital costs that occur due to unpredictable events, such

as material and product price changes, cost data inaccuracies, errors in estimation and other

unforseen expenses. In the NPRM, we accounted for these costs, by increasing the capital costs

(after off-sites adjustment) by 18 percent. A factor of 15 percent is often used for this type of

analysis.40 However, we increased this factor to 18 percent to include the costs of starting up a

new unit.41

We received comment that this factor was not sufficient to include the more sizeable

increases in sulfur plant capacity associated with this NRLM sulfur control. In several recently

developed fuel programs, such as the Tier 2 gasoline and 2007 highway diesel fuel programs, the

sulfur reduction per gallon was only roughly 300 ppm. Here, the reduction is more than 3000

ppm. Therefore, the cost of expanded sulfur processing capacity was sufficient small in these

previous programs to be appropriately accounted for within the 18 percent factor. In this rule,

much more sulfur is being removed from the fuel in the form of hydrogen sulfide, which needs to

be converted to elemental sulfur in the refinery. In Section 6.2 of the Summary and Analysis of

Comments, we evaluated the cost of sulfur plant expansions and developed a new set of capital

cost contingency factors which more appropriately account for these costs. These revised

contingency factors are shown in Table 7.2.1-42 below.
Final Regulatory Support Document

EE The capital amortization factor is applied to a one-time capital cost to create an amortized annual capital cost

that occurs each year for the 15 years of the economic and project life of the unit. This implicitly assumes that

refiners will reinvest in desulfurization capacity after 15 years at the same capital cost, amortized annual cost, and

amortized cost per gallon.

7-150

Table 7.2.1-42

Final Capital Cost Contingency Factors (% of Hydrotreater Costs Including Off-Sites) 

Capital Contingency Factor for

Debottleneck Sulfur Plant

Capital Contingency Factor for New

Sulfur Plant 

NRLM fuel Desulfurized from Uncontrolled Sulfur to 500 ppm Standard

Conventional - New Unit 29 53

Process Dynamics - New Unit 34 69

NRLM fuel Desulfurized from Uncontrolled Sulfur to 15 ppm Standard

Conventional - New Unit 22 38

Process Dynamics - New Unit 26 49

NRLM fuel Desulfurized from 500ppm to 15 ppm Standard

Conventional - Revamped Unit 18 25

Conventional - New Unit * 17 21

Process Dynamics - Revamp Unit 18 31

* Current highway hydrotreater was used to produce 500 ppm NRLM Fuel

We applied the above contingency factors to each refinery depending on whether or not it

had an existing sulfur plant. We obtained this information from the 2002 EIA Petroleum Supply

Annual. 

Capital Amortization: The economic assumptions used to amortize capital costs over

production volume and the resultant capital amortization factors are summarized below in

Table 7.2.1-43.42 These inputs to the capital amortization equation are used in the following

section on the cost of desulfurizing diesel fuel to convert the capital cost to an equivalent pergallon cost.EE

Table 7.2.1-43

Economic Cost Factors Used in Calculating the Capital Amortization Factor

Amortization

Scheme

Depreciation

Life 

Economic and

Project Life

Federal and

State Tax Rate

Return on

Investment

(ROI)

Resulting Capital

Amortization

Factor

Societal Cost 10 Years 15 Years 0 % 7% 0.11

Capital Payback 10 Years 15 Years 39 % 6%

10% 

0.12

0.16

The capital amortization scheme labeled Societal Cost is used most often in our estimates of

cost made below. It excludes the consideration of taxes. The other two cost amortization

schemes include corporate taxes, to represent the cost as the regulated industry might view it. 

The lower rate of return, 6 percent, represents the rate of return for the refining industry over the
Estimated Costs of Low-Sulfur Fuels

7-151

past 10 to 15 years. The higher rate of return, 10 percent, represents the rate of return expected

for an industry having the general aspects of the refining industry.

7.2.1.4.2 Fixed Operating Costs

Operating costs based on the cost of capital are called fixed operating costs. These costs are

termed fixed, because they are normally incurred whether or not the unit is operating or

shutdown. Fixed operating costs normally include maintenance needed to keep the unit

operating, building costs for the control room and any support staff, supplies stored such as

catalyst, property taxes and insurance.

We included fixed operating costs equal to 6.7 percent of the otherwise fully adjusted capital

cost (i.e., including offsite costs and adjusting for location factor and including the capital cost

contingency) and this factor was adjusted upwards using the operating cost contingency factor.43

The breakdown of the base fixed operating cost percentage is as follows:

Maintenance costs: 3 percent

Buildings: 1.5 percent 

Land: 0.2 percent 

Supplies: 1 percent 

Insurance: 1 percent. 

Annual labor costs were taken from the refinery model developed by the Oak Ridge National

Laboratory (ORNL).44 This model has often been used by the Department of Energy to estimate

transportation fuel quality and the impact of changes in fuel quality on refining costs. Labor

costs are very small, on the order of one thousandth of a cent per gallon.

7.2.1.4.3 Utility and Fuel Costs

Utility and fuel costs, which comprise the bulk of what is usually called variable operating

costs, only accrue as the unit is operating and are zero when the unit is not operating. These

costs are usually based on calendar day capacity and include utility and fuel costs associated

with operating a hydrotreater. Additionally, we assign diesel product losses (diesel that is

cracked to gas and gasoline) that occur during hydrotreating to the variable operating costs. 

These losses where described in Section 7.2.1.2 above along with the other aspects of

conventional and IsoTherming hydrotreating technologies.

We received comments that the utility and fuels (primarily natural gas) prices did not reflect

future prices that will likely exist due to the changing supply and demand balance for ths fuel. In

the NPRM, we based future natural gas prices on the five year average price between 1995 and

2001. It now appears that the high natural gas prices existing over the past few years are likely

to remain, at least to some degree. Prices have shifted from the $1.5-2.25 per mmBTU range

existing during the 1990's to much higher levels. 

Thus, for the final rule, we decided to base natural gas prices, as well as those for other fuels

and utilities on EIA’s price projections contained in their 2003 AEO. These price projections are
Final Regulatory Support Document

FF Table EN-1 EIA Petroleum Marketing Annual 2002. 

7-152

based on long term economic modeling and consider various market impacts of supply and

demand dynamics on fuels and utility prices, i.e. growth in GDP, known fuels regulations, costs

of refining products, increased industrial uses, etc. AEO 2003 presents these prices for every

year from 2000 to 2025. For simplicity, we chose to use 2014 as a reasonable approximation of

the range of prices likely to occur throughout the period of this analysis. This is also the same

year for which we project refinery fuel production volumes. Table 7.2.1-44 presents these AEO

prices.

Table 7.2.1-44

Fuel and Utility Prices in 2014: 2003 AEO

2003 AEO - Future Prices

Fuel and Utility Price AEO Table No.

LPG $35.49 per bbl 12

Gasoline $1.406 per gallon * 12

Highway Diesel $1.390 per gallon * 12

High Sulfur Diesel $0.865 per gallon 12

Electricity $0.0440 per kilowatt-hour 8

Natural Gas $4.15 per mmBTU 3

* Includes excise taxes.

These fuel and utility prices represent national averages. The highway fuels include excise

taxes. We removed these taxes in our analysis.FF Also, we desired to reflect differences in fuel

and utility costs across the various PADDs. Therefore, we developed a methodology to adjust

these national average prices to reflect this variability, while still producing the same national

average price when re-averaged across the U.S. 

To do this, we evaluated how prices (excluding taxes) varied by PADD in 2001. For LPG,

gasoline and diesel fuels, this information was available by PADD. However, for natural gas

and electricity, it was available by state. Thus, for these two fuels, we averaged the prices for all

the states within each PADD. In all cases, we then assumed that these PADD-specific variations

would be maintained in the future on a relative basis. 

For LPG, motor gasoline and diesel fuels, we obtained prices (excluding taxes) from EIA’s

2001 Petroleum Marketing Annual. Table 7.2.1-45 provides a summary of the specific places

within the EIA 2001 report where we obtained the 2001 pricing information. Future prices were

determined assuming that each PADD’s price in 2001 would change in direct proportion to the

change in the AEO national average price (including taxes) from 2001 to 2014. The results are

presented in Table 7.2.1-45.
Estimated Costs of Low-Sulfur Fuels

GG Table 7.4 and Figure 7.7.

HH Industrial prices. 

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Table 7.2.1-45

2001 Fuel Prices: Petroleum Marketing Annual: 2001 ($/gallon)

LPG Gasoline Highway Diesel

Fuel

High Sulfur Diesel

Fuel

PMA Table No. 38 (Industrial Users) 31 (Sales for Resale) 41 (Sales for Resale) 41 (Sales for Resale)

PADD 1 0.626 0.862 0.768 0.761

PADD 2 0.589 0.898 0.829 0.820

PADD 3 0.502 0.814 0.742 0.730

PADD 4 0.588 0.943 0.875 0.851

PADD 5 0.658 1.003 0.826 0.794

National Avg. 0.556 0.888 0.794 0.771

We also obtained state-specific electricity prices and natural gas prices data from the EIA. 

Electricity prices were obtained from EIA’s Electricity Power Annual, 2000 and 2001.GG

Natural gas prices were obtained EIA’s Natural Gas Navigator.HH In order to smooth out

significant price volatility between various regions, we averaged electricity prices across two

years (2000-2001) and averaged natural gas prices across 5 years (1997-2001). We estimated

the average price for refineries in each PADD by weighting the state-specific prices by the

volume of crude oil that refiners process in each state. This approach reflects geographic

breakdown of the relative electricity and natural gas usage that would occur from additional

hydrotreating. We obtained refinery raw crude throughput from EIA’s 2001 Petroleum Supply

Annual. We assumed that these historical PADD-specific price differentials would be

maintained in the future. The PADD-specific historical prices for electricity and natural gas are

summarized in Table 7.2.1-46.
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Table 7.2.1-46

Historical Fuel Prices: EIA

Electricity (c/kW-hr) Natural Gas ($ per mmBTU)

PADD 1 6.4 4.65

PADD 2 4.4 4.64

PADD 3 4.6 3.33

PADD 4 3.7 4.16

PADD 5 6.6 4.39

National Avg. 5.1 3.96

The national average fuel and utility prices shown in Table 7.2.1-47 below were then

multiplied by the ratios of the historical PADD-specific differences to the historical national

average price shown in Tables 7.2.1-45 and 7.2.1-46.

Finally, we assumed that steam was generated from natural gas at an efficiency of 50

percent.45 We assumed that natural gas feedstocks costs dominated the overall cost, so that on a

BTU basis steam cost twice that of natural gas. The steam cost per pound was estimated by

dividing this cost per mmBTU by the heat content of steam at 300 psi (809 BTU per pound). 

The resultant PADD-specific future fuel and utility prices are shown in Table 7.2.1-47.

Table 7.2.1-47

Summary of 2014 Fuel and Utility Prices for Variable Operating Cost Estimations

PADD 1 PADD 2 PADD 3 PADD 4 PADD 5

Electricity (cents per kilowatt-hour) 5.51 3.78 3.99 3.24 5.77

LPG (dollars per barrel) 20.98 19.74 16.82 19.71 22.05

Highway Diesel (cents per gallon) 79.1 85.4 76.4 90.1 85.1

Non-highway Diesel (cents per gallon) 72.4 78.1 69.5 81.1 75.6

Gasoline (dollars per barrel) 31.9 33.7 31.2 35.6 41.5

Steam (cents per pound @ 300 psi) 0.35 0.35 0.25 0.31 0.33

Natural Gas ($/Mmbtu) 4.9 4.8 3.5 4.4 4.6

* Prices using EIA’s AEO 2003.

7.2.1.4.4 Hydrogen Costs

Hydrogen costs were estimated for each PADD based on the capital and operating costs of

installing or revamping a hydrogen plant fueled with natural gas. The primary basis for these
Estimated Costs of Low-Sulfur Fuels

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costs is a technical paper published by Air Products, which is a large provider of hydrogen to

refineries and petrochemical plants.46 The particular design evaluated was a 50 million scf/day

steam methane reforming hydrogen plant installed on the Gulf Coast. The capital cost includes a 

20 percent factor for offsites. The process design parameters from this paper are summarized in

the Table 7.2.1-48.

Table 7.2.1-48

Process Design Parameters for Hydrogen Production *

Cost Component Dollars per thousand standard cubic feet ($/MSCF)

Natural Gas 1.18

Utilities

 Electricity

 Water

 Steam

0.03

0.03

-0.07

Capital/Fixed Operating Charges 0.83

Total Product Cost 2.00

* Natural Gas @ $2.75/MMBTU; Steam @ $4.00/M lbs; Electricity @ $0.045 KWH

The estimates shown in Table 7.2.1-48 were adjusted to reflect natural gas and utility costs in

each PADD (shown in Table 7.2.1-46). Changes in the value of steam production and the cost of

water were ignored, as these costs are very small. The capital cost and fixed operating costs

were increased by 8 percent to reflect inflation from 1998 to 2001.

We also adjusted the capacity of the hydrogen plant to reflect the capacity which would be

typical for each PADD. The hydrogen plant capacity for PADD 3 represents the average of the

existing hydrogen plants in the PADD and several third party units producing 100 million

scf/day of hydrogen. For other PADDs, the average plant size was based on the average of

refinery-based hydrogen plants within that PADD, obtained from the Oil and Gas Journal.47 We

incorporated PADD-specific offsite and construction location factors from Table 7.2.1-41, again

assuming a 50-50 mix of new and revamped units. Table 7.2.1-49 summarizes the average plant

size and the offsite and location factors for the installation of hydrogen plant capital for each

PADD.
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Table 7.2.1-49

Summary of Capital Cost Factors used for Estimating Hydrogen Costs by PADD

PADD Capacity (million

scf/day)

Offsite Factor Construction Location

Factor

1 15 1.19 1.5

2 34 1.19 1.3

3 65 1.15 1.0

4 19 1.38 1.4

5 Excluding CA

and AK

15 1.23 1.2

Alaska 15 1.23 2.0

The adjusted hydrogen costs in each PADD are summarized in Table 7.2.1-50.

Table 7.2.1-50

Estimated Hydrogen Costs by PADD

PADD Cost ($/1000 scf)

1 3.56

2 3.01

3 2.09

4 3.33

5 Excluding CA and AK 3.19

AK 3.97

7.2.1.4.5 Other Operating Cost Factors

Similar to the 15 percent contingency factor for capital costs, we included a 10 percent

contingency factor to account for operating costs beyond those directly related to operating the

desulfurization unit.48 This factor accounts for the operating cost of processing additional

hydrogen sulfide in the amine plant, additional sulfur in the sulfur plant, and other costs that may

be incurred but not explicitly accounted for in our cost analysis. We then increased this factor by

2 percent to account for reprocessing of off-specification material (actual “off-spec” allowance is

1/2-1 percent). We adjusted the operating costs to account for as much as 5 percent of all

batches to be re-processed. However, this is a conservative assumption for this cost analysis. 

Furthermore, since this material will have been desulfurized to a level close to the 15 ppm cap,

the operating costs for reprocessing it should be much lower the second time around.
Estimated Costs of Low-Sulfur Fuels

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We also believe refinery managers will have to place a greater emphasis on the proper

operation of other units within their refineries, not just the new diesel fuel desulfurization unit, to

consistently deliver diesel fuel under the new standards. For example, meeting a stringent sulfur

requirement will require that the existing diesel hydrotreater and hydrocracker units operate as

expected. Also, the purity and volume of hydrogen coming off the reformer and the hydrogen

plant are important for effective desulfurization. Finally, the main fractionator of the FCC unit

must be carefully controlled to avoid significant increases in the distillation endpoint, as this can

increase the amount of sterically hindered compounds sent to the diesel hydrotreater. 

Improved control of each of these units may involve enhancements to computer-control

systems, as well as improved maintenance practices.49 Refiners may be able to recoup some or

all of these costs through improved throughput. However, even if they cannot do so, these costs

are expected to be less than 1 percent of those estimated below for diesel fuel desulfurization.50 51

No costs were included in the cost analysis for these potential issues.

7.2.1.5 Projected Use of Advanced Desulfurization Technologies

In Chapter 5, we projected the mix of technologies used to comply with a program being

implemented in any year. This projection took into account the factors that affect the decisions

by refiners in choosing a new technology. The projected mix of technologies for certain

important years is summarized in Table 7.2.1-51 for the reader’s benefit.

Table 7.2.1-51

Projected Use of Advanced Desulfurization Technologies for Future Years

2007 2010 2012+

Conventional Technology 100 40 40

Process Dynamics Isotherming 0 60 60

7.2.2 Refining Costs

In this section, we present the refining costs for the final NRLM diesel fuel program. As

described in Section 7.2.1, the costs to produce 500 ppm fuel were estimated using conventional

technology, while those for 15 ppm fuel were projected using both conventional and advanced

desulfurization technologies. All costs assume the economies of scale for the production of

refineries projected to exist in 2014. Each refinery’s projected costs consider their projected

production of highway diesel fuel under the 2007 highway fuel program, as well as estimates of

its distillate blendstock composition and location (i.e., PADD). Per gallon refining costs assume

a 7 percent before tax rate of return on capital. The sensitivity of these costs to 6 percent and 10

percent after tax rates of return are also evaluated.

The refining costs for the 15 ppm sulfur cap on highway diesel fuel are presented first. 

While the determination of most of the refineries projected to produce highway fuel was made
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using the refiners’ highway fuel pre-compliance reports, additional highway fuel was needed in

PADDs 4 and 5. This was determined using the projected refinery-specific costs of producing

15 ppm fuel. As these costs incorporate several updates since the publication of the Final RIA

for the 2007 highway diesel rule, we thought it appropriate to summarize these updated costs

here. 

The next section presents refining costs for the final NRLM fuel program. First, the overall

costs of the program are summarized. Then, refining costs for the four main time periods of the

program are presented: 1) 2007-2010, 2) 2010-2012, 3) 2012-2014, and 4) 2014 and beyond. All

of these costs are based on NRLM fuel production volumes expected to exist in 2014, the midpoint of the life of desulfurization equipment built in 2007. All per gallon costs presented in this

section are then applied to the volume of NRLM diesel fuel actually being desulfurized under the

final fuel program. These costs would not apply to NRLM diesel fuel already meeting highway

diesel fuel sulfur standards (i.e., spillover fuel). 

In addition, we also present refining costs for a number of sensitivity cases:

1) Increasing the rate of return on capital to 6-10 percent after taxes, 

2) No assumed use of advanced desulfurization technology, 

3) A long term 500 ppm cap for NRLM fuel (i.e., no subsequent 15 ppm cap),

4) Nonroad fuel at 15 ppm and locomotive and marine fuel at 500 ppm indefinitely, and

5) The final NRLM fuel program with lower NRLM fuel demand.

Finally, we present the stream of capital costs which would be required by the NRLM fuel

program, in the context of other environmental requirements facing refiners in the same

timeframe, due to the Tier 2 gasoline sulfur program and the 2007 highway diesel fuel program. 

7.2.2.1 15 ppm Highway Diesel Fuel Program

The refining costs associated with compliance with the 15 ppm highway diesel cap were

estimated for 2006 and 2010. As the methodology used to project these costs differs somewhat

from that used in the Final RIA for the 2007 highway diesel rule, the costs presented here also

differ and represent an update to those costs. The projected costs for producing 15 ppm highway

diesel fuel are summarized in Table 7.2.2-1.
Estimated Costs of Low-Sulfur Fuels

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Table 7.2.2-1

Highway Diesel Desulfurization Costs to Meet a 15 ppm Cap Standard 

($2002, 7% ROI before taxes)*

Refineries Initially Producing 15 ppm Fuel in: All

Refineries

2006 2010

Number of Refineries 96 4 100

15 ppm Fuel Production (million gal/yr in 2014) 53,495 2,022 55,517

Total Capital Cost ($Million) 6,060 120 6,180

Average Capital Cost per Refinery ($Million) 63.1 30.9 61.8

Average Operating Cost per Refinery ($Million/yr) 15.3 10.6 15.1

Total Cost (c/gal) 4.0 3.2 4.0

* Includes impact of highway fuel that is down graded in the distribution system.

As can be seen, we project that 96 refiners will invest to produce 15 ppm highway fuel in

2006, with a total capital cost of $6.06 billion ($63.1 million per refinery). The average cost to

produce 15 ppm highway diesel fuel is 4.0 cents per gallon. These costs assume that all the 15

ppm fuel is being produced using conventional hydrotreating. 

We project that 4 additional refineries will invest to produce 15 ppm highway diesel fuel in

2010, as the temporary compliance option expires. The required capital cost will be $120

million ($30.9 million per refinery). The average cost for 15 ppm fuel newly produced in 2010

is 3.2 cents per gallon, which is 0.8 cents lower than 15 ppm fuel first produced in 2006. The

use of advanced technology acts to lower the cost of refiners initially entering the market in

2010. Additionally, 3 of the 4 refineries entering in 2010 desulfurize their high sulfur distillate

and existing highway diesel volume in a single hydrotreater, resulting in lower costs due to

economies of scale.

Overall, 100 refineries produce the 15 ppm diesel fuel under the 2007 highway diesel fuel

program, with a total capital cost of $6.18 billion ($61.8 million per refinery). The average

refining cost in 2010 will be 4.0 cents per gallon of fuel.

7.2.2.2 Costs for Final Two Step Nonroad Program

The final NRLM fuel program requires that NRLM fuel meet a 500 ppm sulfur cap in 2007,

with a further reduction to 15 ppm in 2010 for nonroad and 2012 for L&M. Small refiners have

until 2010 to meet the 500 ppm cap, and until 2014 to meet the 15 ppm cap for NRLM fuels. 

However, “small refiner” fuel cannot be sold in a designated region basically comprising the

Northeast and Mid-Atlantic regions. Small refiners can also choose to produce NRLM fuel

which meets the above standards on time and sell “credits” to other refiners, who can then sell

NRLM fuel under the delayed standards. Also, 15 ppm fuel which is contaminated during
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distribution and still meets a 500 ppm cap can be sold to the NRLM market through 2014, and to

the locomotive and marine fuel markets indefinitely. 

In this section, we first present an overall summary of the costs of the entire final NRLM fuel

program. Then we present in greater detail the refining costs for the four distinct time periods of

the final NRLM fuel program: 1) the 500 ppm NRLM cap in 2007, 2) the 15 ppm nonroad cap

and 500 ppm L&M cap in 2010 (and 500 ppm cap for small refiner nonroad fuel), 3) 15 ppm

NRLM cap in 2012 (and 500 ppm ppm cap for small refiners), and 4) the 15 ppm NRLM diesel

fuel program in 2014. Following these presentations, we present projected costs for the various

sensitivity cases.

Overall, for the final NRLM fuel program, we project that 63 refineries will invest to make

15 NRLM diesel fuel by 2014. A summary of the projected refining costs for the various steps

in the final NRLM fuel program is presented in Table 7.2.2-2. 

Table 7.2.2-2

Number of Refineries and Refining Costs for the Final NRLM Program

Year of

Program

500 ppm Fuel 15 ppm Fuel 

All Refineries Small

Refineries

All

Refineries

Small

Refineries

Number of Refineries Producing

500 or 15 ppm NRLM Diesel

Fuel

2007-2010 36a 000

2010-2012 26 13 32 2

2012-2014 15 13 47 2

2014-2020 0 0 63 15

Production Volume 

(Million gallons per year in 2014)

2007-2010 13,327 0 0 0

2010-2012 3,792 393 8,598 335

2012-2014 728 393 12,247 335

2014-2020 0 0 13,030 728

Refining Costs (c/gal) 2007-2010 1.9a 000

2010-2012 2.7 3.7 5.0 5.2

2012-2014 2.9 3.7 5.6 5.2

2014-2020 0 0 5.8 6.9

a In 2007-10, refinery counts do not include 500 ppm NRLM fuel from excess capacity in 15 ppm highway

hydrotreaters, and a few idled highway hydrotreaters. However, refining costs do include this fuel.

As can be seen, the per gallon cost of producing 500 ppm and 15 ppm diesel fuels throughout

the various phases of the NRLM fuel program will be 1.9-2.9 and 5.0-5.8 cents, respectively. 

We project that the cost of the 500 ppm cap for small refiners will be 3.7 cents per gallon, or 28
Estimated Costs of Low-Sulfur Fuels

7-161

percent greater than that for the average refiner. We project that the cost of the 15 ppm cap for

small refiners will be 6.9 cents per gallon, or 19 percent greater than that for the average refiner. 

Table 7.2.2-3 presents a summary of the capital and annual costs for average and small refiners.

Table 7.2.2-3

 Refining Costs for the Final NRLM Program Fully Implemented in 2014 

($2002, 7% ROI before taxes)

All Refineries Small Refineries

Number of Refineries 63 15

Total Refinery Capital Cost ($Million)

 2007

 2010

 2012

 2014

 

2,280

310

1,170

590

210

250

0

150

0

100

Average Refinery Capital Cost ($Million) 36.2 16.7

Average Refinery Operating Cost ($Million/yr) 8.1 2.2

As can be seen, total capital costs would be $2,280 million for the entire final 15 ppm

NRLM fuel program (average of $36.2 million per refinery). Total capital costs for the 15 small

refineries would be $250 million (average of $16.7 million per refinery).

7.2.2.2.1 Refining Costs in Year 2007

We project that 36 refiners would produce 500 ppm NRLM fuel in 2007. The cost of the 500

ppm NRLM cap in 2007 is summarized in Table 7.2.2-4 below.
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Table 7.2.2-4

Refining Costs in 2007 for 500 ppm NRLM Diesel Fuel

 ($2002, 7% ROI before taxes)a

All Refineries

Number of Refineries 36

Total Refinery Capital Cost ($Million) 310

Average Refinery Capital Cost ($Million) 8.6

Average Refinery Operating Cost ($Million/yr) 4.9

Amortized Capital Cost (c/gal) 0.3

Operating Cost (c/gal) 1.6

Cost Per Affected Gallon (c/gal) 1.9

We project that the total capital cost will be $310 million (an average of $10.3 million for

each of the 30 refineries actually building new equipment). The total refining cost for the 500

ppm NRLM diesel fuel sulfur cap is 1.9 cents per gallon of affected fuel volume, including both

operating and amortized capital costs. 

7.2.2.2.2 Refining Costs in Year 2010

We project that 32 refineries will produce 15 ppm nonroad fuel in 2010. This is four fewer

refineries than produced 500 ppm NRLM fuel in 2007, as some refineries continue to produce

500 ppm L&M fuel. The total refining costs to produce 15 ppm nonroad fuel in 2010 are

presented in Table 7.2.2-5. Separate costs are shown for all refineries, refineries not owned by

small refiners, and for those owned by small refiners. 
Estimated Costs of Low-Sulfur Fuels

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Table 7.2.2-5

Total Refining Costs in 2010 for 15 ppm Nonroad Diesel Fuel 

($2002, 7% ROI before taxes)

All Refineries Non-small

Refineries

Small Refinery

Number of Refineries 32 30 2

Incremental Capital Cost ($Million) 1,090 1,030 59

Average Refinery Capital Cost ($Million) 34 32.2 30

Average Refinery Operating Cost ($Million/yr) 9.0 8.7 10.8

Capital Cost (c/gal) 1.6 1.6 1.9

Operating Cost (c/gal) 3.4 3.4 3.3

Cost Per Affected Gallon (c/gal) 5.0 5.0 5.2

The incremental capital cost in 2010 to produce 15 ppm nonroad fuel is $1,090 million. The

average cost of producing 15 ppm nonroad diesel fuel is 5.0 cents per gallon. This is 3.1 cents

per gallon more than the average cost to produce 500 ppm NRLM fuel in 2007. This

incremental cost of 3.1 cents per gallon is lower than the 4.0 cent per gallon cost estimated

above for the 15 ppm highway diesel fuel cap. This difference is due to several factors which

have opposing impacts. There are three factors that tend to increase the cost of 15 ppm nonroad

fuel compared to that of 15 ppm highway fuel. One, the vast majority of relatively inexpensive

hydrocrackate was assumed to used in the highway diesel pool. Two, refiners projecting to

produce 15 ppm highway fuel based on pre-compliance report data and cost projections tend to

be those that face lower costs (greater economies of scale, low LCO fractions, etc.). Three, 80

percent of current 500 ppm highway fuel hydrotreaters assumed to be revamped to produce 15

ppm diesel fuel, while the figure is lower for nonroad fuel. While we project that all the new

hydrotreaters built in 2007 to produce 500 ppm NRLM fuel can be revamped to 15 ppm fuel

production, we assume that none of the existing highway hydrotreaters producing 500 ppm

NRLM fuel in 2007 can be revamped to produce 15 ppm fuel. This lowers the overall revamp

percentage to less than 80 percent. However, balancing these factors is our projection that a

significant percentage of refiners will use the Process Dynamics and other advanced

desulfurization technologies in 2010, versus 2006 when the vast majority of 15 ppm highway

fuel will first be produced. This one factor essentially compensates for the other three factors in

the other direction.

As implied in Table 7.2.2-5, most small refiners participating in the NRLM fuel market

produced 500 ppm NRLM fuel in 2010. However, two small refiner’s costs for producing 15

ppm fuel were competitive with the other refineries in producing sufficient volumes of fuel to

satisfy market demand. These small refiners were assumed to sell their credits to non-small

refineries, allowing them to produce 500 ppm nonroad fuel in 2010. 
Final Regulatory Support Document

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A significant volume of 500 ppm nonroad fuel will also be produced in 2010 under the small

refiner provisions. The remaining 500 ppm fuel production is for the L&M fuel market. The

costs of producing 500 ppm diesel fuel in 2010 are presented in Table 7.2.2-6. 

Table 7.2.2-6

 Refining Costs in 2010 for 500 ppm NRLM Fuel

($2002, 7% ROI before taxes)

 All

Refineries

in 2010

NonSmall

Refineries

in 2010

 Small

Refineries

in 2010

Number of Refineries 26 13 13

Total Refinery Capital Cost ($Million) 197 107 90

Average Refinery Capital Cost ($Million) 7.6 8.3 6.9

Average Refinery Operating Cost ($Million/yr) 3.7 6.7 0.8

Capital Cost (c/gal) 0.5 0.3 1.9

Operating Cost (c/gal) 2.2 2.3 2.1

Cost Per Affected Gallon (c/gal) 2.7 2.6 3.7

We project that 26 refineries will produce 500 ppm NRLM fuel in 2010 at an average cost of

2.7 cents per gallon. Thirteen of these refineries are owned by small refiners and are the only

refineries that newly invest in 2010 for new hydrotreaters to produce 500 ppm fuel. Thirteen

non-small refineries who produce 500 ppm NRLM fuel in 2007 would continue to produce 500

ppm NRLM fuel in 2010. Two of these non-small refiners produce 500 ppm fuel using credits

generated by small refiners producing 15 ppm nonroad fuel in 2010. The small refiners per

gallon costs are 37 percent more than the average of refiners producing fuel in 2010. The costs

for refiners that enter the market in 2010 are lowered by the non-small refineries.

7.2.2.2.3 Refining Costs in Year 2012

In 2012, L&M fuel produced or imported must meet a 15 ppm cap. However, 500 ppm fuel

produced during the distribution of cleaner fuels can be sold to the NRLM markets which

reduces the volume of fuel that must be desulfurized to a 15 ppm standard. Additionally, the

provisions that allow small refiners to sell 500 ppm fuel into the NRLM markets also continue. 

The cost of producing 15 ppm NRLM fuel in 2012 is shown in Table 7.2.2-7.
Estimated Costs of Low-Sulfur Fuels

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Table 7.2.2-7

Total Refinery Costs in 2012 to Produce 15 ppm NRLM Fuel

($2002, 7% ROI before taxes)

All Refineries Non-small

Refineries

 Small

Refineries

Number of Refineries 47 45 2

Total Refinery Capital Cost ($Million) 1,980 1,920 59

Average Refinery Capital Cost ($Million) 42.1 42.7 30

Average Refinery Operating Cost ($Million/yr) 9.6 9.8 5.5

Capital Cost (c/gal) 1.8 1.8 1.9

Operating Cost (c/gal) 3.8 3.8 3.3

Cost Per Affected Gallon (c/gal) 5.6 5.6 5.2

We project that 47 refineries would produce 15 ppm NRLM fuel, or 15 more than in 2010. 

The total refining cost measured from today’s high sulfur level would be 5.6 cents per gallon, or

0.6 cent per gallon more than in 2010. Small refineries would have average cost of 5.2 cents per

gallon, or 7 percent lower than the average non-small refineries. 

The 15 ppm costs for the 15 refineries first producing 15 ppm L&M in 2012 are presented in

Table 7.2.2-8. All of these 15 refineries are non-small refineries and have an incremental capital

investment of $590 million. The average cost of producing 15 ppm L&M diesel fuel is 7.3 cents

per gallon. This is 5.4 cents per gallon more than the average cost to produce 500 ppm NRLM

fuel in 2007. This incremental cost of 5.4 cents per gallon is higher than the 4.0 cent per gallon

cost estimated above for the 15 ppm highway diesel fuel cap. As mentioned for the 2010 15 ppm

nonroad costs, several factors tend to increase the cost to desulfurize NRLM fuels to a 15 ppm

standard compared to that of 15 ppm highway fuel. The incremental desulfurization costs are

higher for L&M fuel because a large portion of the lowest cost refiners were selected to invest in

2010 for 15 ppm nonroad fuel production leaving higher costs refiners producing L&M and high

sulfur distillate fuels. Thus in 2012, L&M 15 ppm fuel is produced from these remaining

refineries with higher desulfurization costs. 
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Table 7.2.2-8

Refining Costs for 15 ppm L&M Fuel for Refiners Initially Complying in 2012 

($2002, 7% ROI before taxes)

All Refineries (Non-small)

Total

Number of Refineries 15

Incremental Refinery Capital Cost ($Million) 590

Average Refinery Capital Cost ($Million) 39.1

Average Refinery Operating Cost ($Million/yr) 11.5

Capital Cost (c/gal) 1.9

Operating Cost (c/gal) 5.1

Cost Per Affected Gallon (c/gal) 7.0

Of the 15 additional refineries producing 15 ppm L&M fuel in 2012, six will install a new

grass roots hydrotreater as they did not invest to make 500 ppm L&M fuel prior to this time. 

The remaining 9 refineries will revamp their new nonroad hydrotreater built in 2007 or 2010. 

The average refinery that produces 15 ppm L&M diesel fuel for the first time in 2012 will make

a capital investment of $39.1 million.

7.2.2.2.4 Refining Costs in Year 2014

In 2014, all NRLM diesel fuel produced must meet a 15 ppm cap. Additionally in 2014, the

provisions allowing 15 ppm fuel that is downgraded to 500 ppm sulfur level in the distribution

system to be sold to the nonroad fuel market expire, though this fuel can continue to be sold into

the locomotive and marine market. Thus, the volume of 15 ppm NRLM diesel fuel produced

increases over the total volume of 15 and 500 ppm NRLM fuel produced in 2010. The cost of

producing 15 ppm NRLM fuel in 2014 is shown in Table 7.2.2-9.
Estimated Costs of Low-Sulfur Fuels

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Table 7.2.2-9

Total Refinery Costs in 2014 to Produce 15 ppm NRLM Fuel

($2002, 7% ROI before taxes)

All Refineries Non-small

Refineries

 Small

Refineries

Number of Refineries 63 48 15

Total Refinery Capital Cost ($Million) 2,280 2,030 250

Average Refinery Capital Cost ($Million) 36.2 42.5 16.5

Average Refinery Operating Cost ($Million/yr) 8.1 10.6 2.2

Capital Cost (c/gal) 1.9 1.7 3.1

Operating Cost (c/gal) 3.9 4.0 3.8

Cost Per Affected Gallon (c/gal) 5.8 5.7 6.9

We project that 63 refineries would produce 15 ppm NRLM fuel, or 16 more than in 2010. 

The total refining cost measured from today’s high sulfur level would be 5.8 cents per gallon, or

0.2 cent per gallon more than in 2010. Small refineries would have an average cost of 6.9 cents

per gallon, or 19 percent higher than the average non-small refineries. 

The 15 ppm costs for the 16 refineries first producing 15 ppm nonroad fuel in 2014 are

presented in Table 7.2.2-10. The incremental capital investment for these 16 refineries in 2014

was $210 million. Of this $210 million, $100 million will be spent by small refiners.

Table 7.2.2-10

Refining Costs for 15 ppm NRLM Fuel for Refiners Initially Complying in 2014 

($2002, 7% ROI before taxes)

All

Refineries

Non-small

Refineries

Small

Refineries

Total Total Total

Number of Refineries 16 3 13

Total Refinery Capital Cost ($Million) 300 110 190

Average Refinery Capital Cost ($Million) 18.9 36.9 14.6

Average Refinery Operating Cost ($Million/yr) 4.5 16.5 1.7

Capital Cost (c/gal) 2.4 1.4 3.9

Operating Cost (c/gal) 5.2 5.8 4.0

Cost Per Affected Gallon (c/gal) 7.6 7.2 7.9

Of the 16 additional refineries producing 15 ppm NRLM fuel in 2014, 13 are owned by small

refiners. Two of the 16 refineries will install a new grass roots hydrotreater as they did not
Final Regulatory Support Document

7-168

invest to make 500 ppm NRLM fuel prior to this time. The remaining 14 of 16 refineries will

revamp their new nonroad hydrotreater built in 2007 or 2010. The average refinery that

produces 15 ppm nonroad diesel fuel for the first time in 2014 faces a capital investment of

$18.9 million, while the investment for the average small refiner is smaller at $14.6 million.

7.2.2.3 Refining Costs for Sensitivity Cases

7.2.2.3.1 Total Refining Costs at Different Rates of Return on Investment

The costs presented in the previous section all assumed a 7 percent before tax rate of return

on investment. We also estimated total refining costs for the final NRLM fuel program using

two alternative rates of return on investment: 1) 6 percent per year after taxes, and 2) 10 percent

per year after taxes. The 6 percent rate is indicative of the economic performance of the refining

industry over the past 10-15 years. The 10 percent rate is indicative of economic performance of

an industry like refining which would attract additional capital investment. The total per gallon

cost of producing 15 ppm NRLM fuel in 2014 using all three rates of return are shown in Table

7.2.2-11.

Table 7.2.2-11

Refining Costs in 2014 for 15 ppm NRLM Fuel in 2014 (cents per gallon, $2002)

Societal Cost: 7% ROI before Taxes 5.8

Capital Payback: (6% ROI, after Taxes) 6.1

Capital Payback: (10% ROI, after Taxes) 6.9

As can be seen, the difference in the assumed rate of return on investment increases the

societal cost by 0.3-1.1 cents per gallon.

7.2.2.3.2 15 ppm Nonroad Diesel Fuel with Conventional Technology

The use of advanced technology is expected to reduce the cost of producing 15 ppm diesel

fuel compared to conventional hydrotreating. To determine the sensitivity of our cost estimates

to the level of advanced technology projected, we developed costs for producing 15 ppm NRLM

diesel fuel with only the use of conventional hydrotreating. We did not vary the specific

refineries projected to produce 15 ppm NRLM fuel in 2014 from those described in the previous

section. Total refining costs to produce 15 ppm NRLM diesel fuel in 2014 using conventional

technology are shown in Table 7.2.2-12.
Estimated Costs of Low-Sulfur Fuels

7-169

Table 7.2.2-12

Total Refining Costs in 2014 to Produce 15 ppm NRLM Diesel Fuel

with Conventional Technology ($2002, 7% ROI before taxes)

All Refineries Small Refineries

Number of Refineries 63 15

Total Refinery Capital Cost ($Million) 2,730 290

Average Refinery Capital Cost ($Million) 42.7 19.2

Average Refinery Operating Cost ($Million/yr) 10.6 2.6

Capital Cost (c/gal) 2.2 3.7

Operating Cost (c/gal) 4.9 4.5

Cost Per Affected Gallon Cost (c/gal) 7.1 8.2

The total cost to produce 15 ppm nonroad diesel fuel in 2014 with conventional technology

would be 7.1 cents per gallon, or 22 percent higher than the 5.8 cent per gallon cost with a mix

of conventional and advanced technology. Total capital costs would be $2,730 million with

conventional technology, about 20 percent higher than the $2,286 million investment including

use of advanced technology (see Table 7.2-40). Operating costs would be 16 percent higher with

conventional technology, $10.0 million as compared to $8.6 million with use of advanced

technology. The same relative comparisons apply to the impact of advanced technology on the

capital costs faced by small refiners. All of these figures represent the total cost of producing 15

ppm diesel fuel from high sulfur diesel fuel. 

7.2.2.3.3 Proposed Two Step NRLM Program: Nonroad Fuel to 15 ppm in 2010 and

Locomotive and Marine at 500 ppm Indefinitely

This section presents the refining costs of the NRLM program which EPA proposed: nonroad

fuel at 15 ppm and locomotive and marine fuel at 500 ppm. The refining impacts of this

program are shown in Tables 7.2.2-13. 
Final Regulatory Support Document

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Table 7.2.2-13

Refining Impacts for the Proposed Two Step NRLM Fuel Program a

15 ppm Nonroad Fuel in 2010 and 500 ppm Locomotive and Marine Fuel Indefinitely

Year of

Program

500 ppm Fuel b 15 ppm Fuel 

All Refineries Small

Refineries

All

Refineriesa

Small

Refineries

Number of Refineries Producing

500 or 15 ppm NRLM Diesel

Fuel

2007-2010 36 0 0 0

2010-2014 26 13 32 2

2014+ 20 8 40 7

Refining Costs (c/gal) 2007-2010 1.9 0 0 0

2010-2014 2.7 3.7 5.0 5.2

2014+ 2.7 3.0 5.2 7.0

a

 Includes small refiners.

b In 2007-10, refinery counts do not include 500 ppm NRLM fuel from excess 15 ppm highway hydrotreaters,

and a few idled highway hydrotreaters. However, refining costs do include this fuel. One refiner produces 15 & 500

ppm fuel. 

Under this sensitivity case, we project that 59 refineries would eventually invest to make

either 15 ppm nonroad or 500 ppm locomotive and marine fuel by 2014. The total cost of

producing 500 ppm NRLM fuel in 2007 is the same as that under the final NRLM program, as

the two programs are identical. In 2014, the cost of 500 ppm locomotive and marine fuel would

be 2.7 cents per gallon, or sightly higher than the range for 500 ppm NRLM fuel under the final

NRLM program (1.9-2.4 cents per gallon).

The total cost for producing 15 ppm fuel in this program are lower than the final NRLM

program costs (5.8 cents per gallon in 2014). Less volume of 15 ppm fuel is produced and the

incremental per gallon costs are less than the final programs per gallon cost. This lowers the

average cost. 

Table 7.2.2-14 presents a side-by-side comparison of some of the key refining impacts of the

proposed and final NRLM fuel programs.
Estimated Costs of Low-Sulfur Fuels

7-171

Table 7.2.2-14

Refining Costs for Two Step Program with 500 ppm Locomotive and Marine fuel versus Final

NRLM Program ($2002, 7% ROI before taxes)

Two Step Program with 15 ppm

Nonroad Fuel and 500 ppm

Locomotive and Marine Fuel

Final NRLM program 

All Refineries Small

Refineries

All

Refineries

 Small

Refineries

Number of Refineries 60 15 63 15

Total Refinery Capital Cost ($Million)

 2007

 2010

 2012

 2014

1,680

310

1,240

0

130

180

0

140

0

40

2,280

310

1,170

590

210

250

0

150

0

100

Average Refinery Capital Cost ($Million) 28.5 12.1 36.2 16.7

Average Refinery Operating Cost ($Million/yr) 6.8 1.6 8.1 2.2

Overall, the 15 ppm cap on locomotive and marine fuel in our final NRLM fuel program

increases total capital investment by $600 million and increases the cost of the incremental

volume of L&M fuel by 5.2 cents per gallon (from 2.7 to 7.9 cents per gallon). Table 7.2.2-15

presents the incremental refining impacts of the 15 ppm cap on locomotive and marine fuel over

those of the 500 ppm cap.

Table 7.2.2-15

Refinery Impacts in 2014 for a 15 ppm Versus 500 ppm Cap on Locomotive and Marine Fuel

($2002, 7% ROI before taxes)

 All

Refineries

Number of Affected Refiners 23

Total Incremental Capital, $MM 600

Incremental Fuel Cost 500ppm to 15 ppm, (c/gal) 5.2

Total Fuel Cost , (c/gal) 7.9

The 5.2 cent per gallon cost to reduce L&M fuel sulfur from 500 to 15 ppm is higher than the

3.5 cent per gallon cost for nonroad fuel, because we assumed that the refiners facing the lowest

desulfurization costs would produce 15 ppm nonroad fuel, if L&M fuel sulfur remained at 500

ppm. Thus, 15 ppm L&M fuel is produced from the remaining refineries that are projected to

face higher desulfurization costs.
Final Regulatory Support Document

7-172

7.2.2.3.4 Refining Costs for a 500 ppm NRLM Only Program

This section presents refining costs for a long-term 500 ppm cap on NRLM fuel (i.e., no

subsequent 15 ppm cap). We evaluated costs in 2010, after any small refiner provisions would

have expired. These costs are summarized in Table 7.2.2-16.

Table 7.2.2-16

Refining Costs for a Stand-alone 500 ppm NRLM Diesel Fuel Standard

($2002, 7% ROI before taxes)a

All 

Refineries

Nonsmall

Refineries

Small

Refineries

Number of Refineries 57 41 16

Total Refinery Capital Cost ($Million) 480 360 120

Average Refinery Capital Cost ($Million) 8.4 8.8 7.7

Average Refinery Operating Cost ($Million/yr) 3.6 4.7 1.0

Capital Cost (c/gal) 0.4 0.3 1.5

Operating Cost (c/gal) 1.6 1.6 1.7

Cost Per Affected Gallon (c/gal) 2.0 1.9 3.2

a

 Equivalent to the costs of the 500 ppm NRLM cap in 2010 without the 15 ppm nonroad cap.

The overall refining cost of a 500 ppm NRLM fuel cap would be 2.0 cents per gallon. We

project that 57 refineries would produce this fuel with a total capital investment of $480 million. 

On average, the refining cost for small refiners would be about 60 percent higher than that of

non-small refiners at 3.2 cents per gallon. 

7.2.2.3.5 EIA-Based Demand for NRLM Fuel 

 In Chapter 2 of the Summary and Analysis of Comments, we discuss the uncertainty in

current and future demand for NRLM fuel, particularly that used in land-based nonroad

equipment. While we base our primary cost estimates on fuel demands as predicted by EPA’s

NONROAD emission model, we decided to evaluate the sensitivity of both costs and benefits to

an alternative level of fuel demand. Here, we present the refining costs assuming that the EIAbased fuel demands are more accurate than those from NONROAD. 

The total refining costs to produce 500 and 15 ppm NRLM diesel fuel from 2007-2014 for

the two sets of fuel demands are summarized in Table 7.2.2-17. 
Estimated Costs of Low-Sulfur Fuels

7-173

Table 7.2.2-17

Total Refining Costs of NRLM Fuel from 2007-2014 With Varying Fuel Demands

 (Cents per gallon, $2002, 7% ROI before taxes)

EIA-Based Fuel Demand EPA NONROAD Fuel Demand

500 ppm NRLM fuel: 2007-2010 1.9 1.9

500 ppm NRLM fuel: 2010-2012 2.8 2.7

500 ppm NRLM fuel: 2012-2014 3.0 2.9

15 ppm Nonroad fuel: 2010-2012 5.0 5.0

15 ppm NRLM fuel: 2012-2014 5.6 5.6

15 ppm NRLM fuel: 2014+ 5.7 5.8

As can be seen, reducing NRLM fuel demand has little impact on per gallon refining costs. 

The only differences shown are a slight increase in 500 ppm costs from 2010-2014 and a slight

decrease in 15 ppm fuel costs after 2014. The former effect occurs because the incremental 500

ppm NRLM fuel volume is coming from relatively low cost Gulf Coast refineries. While the

same effect exists in 2014 with respect to 15 ppm fuel costs, the effect of the reduced demand in

reducing costs in other refining areas is larger. Table 7.2.2-18 provides a more detailed

breakdown of the final refining impacts of the 15 ppm NRLM cap in 2014 for the two sets of

fuel demands.

Table 7.2.2-18

Refining Impacts of 15 ppm NRLM Fuel in 2014 With Varying Fuel Demands

 ($2002, 7% ROI before taxes)

EIA-Based Fuel Demand EPA NONROAD Fuel Demand

# of Refiners 55 63

Total Refinery Capital Cost ($Million) 1,870 2,280

Average Capital Cost ($Million) 33.9 36.2

Operating Cost ($Million/yr) 7.5 8.1

Capital Cost (c/gal) 1.9 1.9

Operating Cost (c/gal) 3.8 3.9

Cost Per Gallon (c/gal) 5.7 5.8
Final Regulatory Support Document

II Regulatory Impact Analysis - Control of Air Pollution from New Motor Vehicles: The Tier 2 Motor Vehicle

Emissions Standards and Gasoline Sulfur Control Requirements, U.S. EPA, December 1999, EPA 420-R-99-023. 

Adjusted to 2002 dollars using Chemical Engineering Plant Cost Index.

7-174

As the EIA-based methodology reduces NRLM fuel demand, only 55 refineries would invest

to produce NRLM fuel in 2014 versus 63 using the EPA NONROAD Model estimates. The total

15 ppm NRLM fuel cost would be 5.7 cents per gallon, or 0.1 cents per gallon less than that to

satisfy NONROAD fuel demand. Total capital costs would be $1,870 million, or about 18

percent less than the $2,280 million investment needed to produce the additional fuel volume.

7.2.2.4 Capital Investments by the Refining Industry

Refiners must raise capital to invest in new desulfurization equipment to produce the 500

ppm and 15 ppm diesel fuel which would be required under the final NRLM fuel program. The

previous sections estimated the total capital cost associated with the final and various sensitivity

cases. Refiners expend this capital over a several year period prior to the time which the new

equipment must be used. This section estimates how much capital would have to be expended in

specific years under the final and alternative programs. These yearly expenditures are then

added to those required by other fuel quality programs being implemented in the same timeframe

and compared to historic capital expenditures made by the refining industry.

Two fuel quality regulations are being implemented in the same timeframe as this NRLM

fuel program: The Tier 2 gasoline sulfur program and the 2007 highway diesel fuel sulfur

program. In the Tier 2 gasoline sulfur control rule, we estimated the expenditure of capital for

gasoline desulfurization by year according to the phase in schedule promulgated in the rule.II

The 2007 highway diesel rule modified that phase in schedule by provided certain refiners more

time to meet the Tier 2 gasoline sulfur standards. In the 2007 highway diesel rule, we projected

the stream of capital investments required by the U.S. refining industry for both the modified

Tier 2 standards and the 15 ppm highway diesel fuel sulfur program. We updated the allocation

and amount of capital expenditures for the highway diesel rule to reflect when each refiner

would invest. The new total capital costs for the 2007 highway diesel fuel program are

discussed in section 7.2.2.1 above. In projecting the stream of capital expended for a particular

project, we assume that the capital investment would be spread evenly over a 24 month period

prior to the date on which the unit must be on-stream. The stream of projected capital

investment related to the Tier 2 gasoline sulfur program and the 2007 highway diesel fuel

program rule are shown in Table 7.2.2-19.
Estimated Costs of Low-Sulfur Fuels

7-175

Table 7.2.2-19

Capital Expenditures for Gasoline and Highway Diesel Fuel Desulfurization

($Billion, $2002)a

Calendar

Year

Tier 2 Gasoline

Sulfur Program

2007 Highway

Diesel Program Total

2002 1.76 1.76

2003 1.15 1.15

2004 0.88 1.82 2.70

2005 0.61 3.03 3.64

2006 0.16 1.21 1.37

2007 0.06 0.06

2008 0.06 0.43 0.49

2009 0.02 0.71 0.73

2010 0.28 0.28

a

2002 dollars obtained by use of Chemical Engineering Plant Annual Cost Index to adjust capital costs 

for Tier 2 gasoline program (1997 dollars) and highway diesel capital program (1999 dollars).

The two diesel fuel programs have implementation dates of June 1 of various years for fuel

leaving the refinery. For this start up date, we assumed that 30 percent of the capital cost was

expended in the calendar year two years prior to start up, 50 percent was expended in the year

prior to start up and the remaining 20 percent was expended in the year of start up. We repeated

this analysis for the final NRLM program. The results are summarized in Table 7.2.2-20 below.
Final Regulatory Support Document

7-176

Table 7.2.2-20

 Capital Expenditures for the Final NRLM Fuel Program with

Tier 2 Gasoline Sulfur and 2007 Highway Diesel Fuel Programs 

($Billion, $2002)

Calendar Year

Final NRLM Fuel Program

Tier 2 and Highway

Diesel

NRLM Program Totala

2002 1.76 1.76

2003 1.15 1.15

2004 2.70 2.70

2005 3.64 0.09 3.75

2006 1.37 0.16 1.53

2007 0.06 0.06 0.12

2008 0.49 0.35 0.84

2009 0.73 0.59 1.32

2010 0.28 0.41 0.69 

2011 0.29 0.29

2012 0.18 0.18

2013 0.11 0.11

2014 0.04 0.04

a

2002 dollars obtained by use of Chemical Engineering Plant Annual Cost Index to adjust capital costs for Tier 2

gasoline program (1997 dollars) and highway diesel capital program (1999 dollars).

As can be seen, capital investments peak in 2005 for the Tier 2 and Highway diesel

programs. The final NRLM program increases this peak by just $90 million, or about 2 percent. 

Thereafter, capital requirements drop dramatically but peak a second time in year 2009 due to

the 15 ppm highway and nonroad standard. The second peak is less than 36 percent of the

capital outlays that occur in year 2005. Considering all programs, when capital investment

requirements are the highest, they are caused by the Tier 2 gasoline sulfur and 2007 highway

diesel fuel programs. Compared to Tier 2 and the hwy diesel program, the capital investment

requirements for the final NRLM fuel program are much smaller and are more spread out over

time.

Estimates of previous capital investments by the oil refining industry for the purpose of

environmental control are available from two sources: the Energy Information Administration

(EIA) and the American Petroleum Institute (API). According to EIA, capital investment by the

24 largest oil refiners for environmental purposes peaked at $2 billion per year during the early
Estimated Costs of Low-Sulfur Fuels

JJ “The Impact of Environmental Compliance Costs on U.S. Refining profitability,” EIA, May 16, 2003.

KK U. S. Petroleum Refining, Assuring the Adequacy and Affordability of Cleaner Fuels, A Report by the

National Petroleum Council, June 2000.

7-177

1990's.JJ Total capital investment by refiners for other purposes was in the $2-3 billion per year

range during this time frame. API estimates somewhat higher capital investments for

environmental purposes, with peaks of about $3 billion in 1992-1993.KK Based on these two

sources, during the early 90's, the US refining industry invested over 20 billion dollars in capital

for environmental controls for their refining and marketing operations, representing about one

half of the total capital expenditures made by refiners for operations.

The capital required for the Tier 2 gasoline, 2007 highway diesel fuel and the final NRLM

fuel program is about 73 percent of the historic peak level of investment for meeting

environmental programs experienced during 1992-1994.52 Additionally, most of the capital

outlays for all of the about mentioned fuels programs are spread out over an eight year time

period. Given that the capital required by the final NRLM fuel program contributes less than 2

percent to the required investment in the peak year of 2005, we do not expect that the industry

would have difficulty raising this amount of capital, although we recognize that it does require

the need to continue to raise and devote capital over a longer period of time.

7.2.2.5 Other Cost Estimates for Desulfurizing Highway Diesel Fuel

Two other studies have estimated a cost of producing 15 ppm NRLM fuel, one by Mathpro

and another by Baker and O’Brien (BOB). These two studies are discussed below.

Mathpro: For the Engine Manufacturers Association and with input by the American

Petroleum Institute, Mathpro used a notional refinery model to estimate the national average

costs of desulfurizing nonroad diesel fuel after implementation of the 15 ppm standard for

highway diesel fuel. The cost estimate from this study is presented here and compared with our

costs.

In a study conducted for the EMA, MathPro, Inc. first estimated the cost of desulfurizing

diesel fuel to meet a 15 ppm highway diesel fuel sulfur standard followed by two-step nonroad

standards of 500 ppm and 15 ppm.53, 54 MathPro assumed that desulfurization will occur entirely

with conventional hydrotreating, and refining operations and costs were modeled using their

ARMS modeling system with technical and cost data provided by Criterion Catalyst Company

LP, Akzo-Nobel Chemicals Inc., and Haldor Topsoe, Inc. The Mathpro refinery model

estimated costs based on what Mathpro terms a “notional” refinery. The notional refinery is

configured to be typical of the refineries producing highway diesel fuel for PADDs 1, 2, and 3,

and also represent the desulfurization cost for those three PADDs based on the inputs used in the

refinery model. The Mathpro notional refinery model maintained production of highway diesel

fuel at their base levels.
Final Regulatory Support Document

7-178

Mathpro made several estimates in their study to size their diesel desulfurization units for

estimating the capital cost, and these estimates were similar to those included in our

methodology. The calendar day volume was adjusted to stream day volume using a 10 percent

factor to account for variances in day-to-day operations, and another 10 percent to account for

variance in seasonal demand. In addition, Mathpro applied a factor that falls somewhere in the

range of 1 to 8 percent for sizing the desulfurization unit larger for reprocessing off-spec

material to meet different sulfur targets. Since meeting a 500 ppm standard is not very stringent,

Mathpro likely assumed that a desulfurization unit will be sized larger by 1 to 4 percent. For

meeting the 15 ppm standard, which is relatively stringent compared with the 500 ppm sulfur

level studied, Mathpro likely assumed the desulfurization unit would be sized larger by 5 to 8

percent. On-site investment was adjusted to include offsite investment using a factor of 1.4. In

the final report, capital costs were amortized at a 15 percent after-tax rate of return.

The Mathpro cost study analyzed the costs to comply with the highway program based on 5

different investment scenarios. Before deriving the best nonroad desulfurization cost estimate

using the Mathpro cost study, we must describe the various investment scenarios. The titles of

the scenarios are listed here:

1. No Retrofitting - Inflexible

2. No Retrofitting - Flexible

3. Retrofitting - De-rate/Parallel

4. Retrofitting - Series

5. Economies of Scale

Scenarios 1 and 2 do not allow retrofitting, which means the existing highway diesel

hydrotreater must be removed from service and a new grassroots unit desulfurizing untreated

distillate down to under 15 ppm takes its place. The difference between scenarios 1 and 2 is that

scenario 1 does not allow some flexibilities that may be available to the refining industry. One

flexibility is that the volume of hydrocracker units is not limited to the used capacity as listed in

the 1997 API/NPRA survey, but instead the throughput can be as much as 8 percent higher,

which is half the available capacity available in the API/NPRA survery. Another flexibility is

that jet fuel exceeds specifications and instead of limiting the qualities to current levels, they are

instead allowed to become heavier by 0.5 API or by 3 points on the E375 distillation curve and

stay within the jet fuel specifications. Allowing jet fuel to get heavier allows the refinery model

to bring some of these lighter jet fuel blendstocks into the highway diesel fuel pool, which

lowers the desulfurization cost. The flexibilities are allowed in the rest of the scenarios as well.

Scenarios 3 and 4 allow taking advantage of the existing highway desulfurization unit by

keeping it in place and installing additional capital including additional reactor volume, which

allows the combined used and new capital to achieve the 15 ppm standard. 

The difference between scenarios 3 and 4 is that Scenario 3 derates the existing hydrotreater,

which reduces the volume treated by that unit so it can achieve 15 by itself; another unit being

fed by a low throughput is then added in parallel, which allows it to meet the 15 ppm standard. 

Scenario 4 installs the new capital in series with the existing hydrotreater with both units

handling the entire feed rate.
Estimated Costs of Low-Sulfur Fuels

7-179

Scenario 5 allows the debottlenecking of existing capacity to treat a larger volume while

producing the same specifications. Scenario 5 also allows a single unit to be installed to handle

the desulfurization of multiple refineries in refining centers, which provides an important

economy of scale for the desulfurization investment costs to that group of refineries.

While these various investment scenarios were devised to show how different investment

scenarios affect the cost for the HD2007 rule, they have implications for the nonroad rule as

well. For meeting the standard for nonroad diesel fuel of 500 ppm, the used highway units freed

up in Scenarios 1 and 2 can thus be converted over to nonroad service, which dramatically

reduces the capital cost of compliance; this supplements the existing nonroad capacity. 

However, for Scenario 2, the installed grassroots capacity installed for the HD2007 rule

decreased after the capital was already installed and a larger volume of existing hydrotreating

capacity removed from highway desulfurization service was put into place to supplement the

nonroad hydrotreating capacity already in place. For Scenario 3, the needed nonroad capacity is

formed by adding grassroots capacity. For Scenario 4, the necessary nonroad hydrotreating

capacity is formed by increasing the existing unit capacity used, relying on some expansion of

existing units and adding some processing unit capacity in series with existing capacity. The

nonroad hydrotreating capacity for meeting the 500 ppm standard is realized for Scenario 5

similar to Scenario 4, except no expansion of existing units occurs, but instead more capacity

from existing highway units is relied upon.

For meeting the 15 ppm cap sulfur standard for nonroad diesel fuel, the refinery model

invested in nonroad capital either along the same lines as the 500 ppm case, or else invested

much differently. For Scenario 1 and 2, the refinery model installed grassroots units only, even

replacing some existing hydrotreating capacity that was likely being used for some mild

desulfurization of nonroad diesel fuel. For Scenario 2, the volume of grassroots desulfurization

capacity was slightly lower than Scenario 1, probably due to the increased flexibility granted by

the refinery model. For Scenario 3, the refinery model added some new grassroots unit capacity

compared with the 500 ppm case, probably derating the capacity of the remaining 500 ppm and

new 500 ppm capacity. For Scenario 4, the refinery model added more series unit capacity and

more expansion capacity. Finally for Scenario 5, the refinery model increased the series

processing unit capacity and added some expansion capacity.

The new or existing hydrotreating capacity used for meeting the 500 ppm and 15 ppm

nonroad standards incremental to meeting the highway 15 ppm sulfur standard is shown in

Table 7.2.2-21.
Final Regulatory Support Document

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Table 7.2.2-21

Mathpro Capital Investments (bbl/day) for Desulfurizing Highway and Nonroad Diesel Fuel

No Retr

Inflex

No Retr 

Flex

Retr 

De-rate

Retr 

Series

Econ of

Scale 

Reference Case Existing Cap 34.9 34.9 34.9 34.9 34.9

Highway 15 ppm

Cap Std

Existing Unit 8.2 8.2 31.1 31.1

Expansion

De-rated 17.8

Series Unit 15.4 29.4 29.4

Grassroot Unit 30.2 29.3

Nonroad Meeting

a 500 ppm

Standard

Existing Unit 16.5 19.4 35.0 38.0

Expansion 2.9

De-rated 17.8

Series Unit 34.1 34.0

Grassroot Unit 30.1 27.6 23.7

Nonroad Meeting

a 15 ppm Standard

Existing Unit 35.0 38.0

Expansion 4.9 1.9

De-rated 17.8

Series Unit 39.1 39.1

Grassroot Unit 50.4 49.3 26.5

We next determined which Mathpro case best approximated the investment scenarios we are

using in our 500 ppm cost analysis, but we will summarize first summarize how our cost model

estimates investments will occur. As described earlier in this section, some refineries will

comply with the highway HD2007 rule in 2006 by putting in a new hydrotreater and thus idling

an existing hydrotreater (i.e., 20 percent of the mixed highway and nonroad refineries that have a

distillate hydrotreater and comply with the highway requirements in 2006). Other refiners have

said that they will exit the highway market altogether, thus freeing up their existing 500 ppm

treater. We believe that the refineries exiting the highway market would use these treaters to

desulfurize NRLM diesel fuel. Adding up the volumes from these two sources of existing

hydrotreating capacity, we estimate that 30 percent of NRLM will be desulfurized with existing

hydrotreaters. Furthermore, we estimated that 39 percent of NRLM fuel is already hydrotreated

and blended into high sulfur distillate. We project that this hydrotreating will continue with the

use of existing hydrotreaters. Thus, the fraction of NRLM diesel fuel meeting the 500 ppm

sulfur standard in 2007 with the use of existing capital is expected to be 69 percent. The balance

of the NRLM volume, which comprises 31 percent, is expected to be desulfurized with a new

hydrotreater installed for startup in 2007. 
Estimated Costs of Low-Sulfur Fuels

7-181

We examined the Mathpro investment cases to match the investment scenarios in our cost

analysis. There were no cases that matched our scenario exactly, but we found two Mathpro

cases that, together, roughly matched our investment scenario. The first is the No Retrofit

Inflexible case, which met the nonroad requirements exclusively through using existing capacity

(with half of it already in place before the standard applied, which matches our investment

scenario). The second case is the Retrofitting Derating case, which met the nonroad

requirements through new capital investment. Our analysis for complying with the 500 ppm

sulfur standard was based on 69 percent of the nonroad volume being produced by refineries

using existing hydrotreaters and 31 percent with new units, so the Mathpro costs were weighted

69 percent No Retrofit Inflexible costs and 31 percent Retrofit DeRate costs.

We then examined the Mathpro 15 ppm cases to determine which would best match our 15

ppm scenario. Since we already described the Mathpro cases for estimating the incremental cost

for going from meeting the 500 ppm standard to meeting the 15 ppm sulfur standard, we needed

identify the case which best matches our 500 ppm to 15 scenario. As discussed earlier in this

section, our 15 ppm scenario has new nonroad diesel fuel hydrotreating units being installed in

2010. Since we estimated that 31 percent of the volume of NRLM in 2007 is complied with

using new units, we project that 31 percent of the NRLM diesel fuel would meet the 15 ppm

sulfur by revamping their new 2007 treaters. The balance of the NRLM volume are projected to

comply with the 15 ppm standard with grassroots units which are installed to desulfurize

uncontrolled distillate fuel down to 15 ppm, with an operating cost credit for the uncontrolled to

500 ppm step. Of the Mathpro cases summarized above, the first two cases, which don’t allow

revamps and either allow or don’t allow operational flexibility, install grassroots units for

obtaining the 15 ppm standard. We decided to use Mathpro’s case one, since the second

Mathpro case apparently allowed backsliding in the highway grassroots units needed for

complying with the HD2007 rule when the 500 ppm standard was being met, which we don’t

think is possible because the highway investments will be too far along before the nonroad

program is finalized.

Case one, however, needed to be adjusted to better model our projections on how refiners

would invest. Mathpro’s case one was associated with the replacement of the existing

hydrotreating capacity, all of which was likely used by the refinery model for desulfurizing

nonroad down to 500 ppm. However, we believe 31 percent of the existing nonroad

desulfurization capacity can be revamped instead of having to be replaced. Thus, we adjusted

the Mathpro capital costs to remove 31 percent of the grassroots hydrotreating capacity which

we believe would be revamped instead. We accomplished this by estimating what percent of the

capital costs is necessary for complying with 15 ppm standard and which portion was necessary

for replacing the expected portion of existing nonroad desulfurization capital. The nonroad

diesel fuel volume needed to be treated in Mathpro’s notional refinery model is 9 thousand

barrels per day. According to Mathpro, the capital needed to be installed to treat the nonroad

pool down to 15 ppm is increased by 10 percent to handle peak throughput rates, and then by

another 10 percent to handle peak seasonal rates and then by another 8 percent to handle

reprocessing of off-spec batches. Thus, the 9,000 barrels per day nonroad volume is increased to

about 11,800 barrels per day, which represents Mathpro’s estimated capital capacity. We

subtracted 11,800 bpd from the total volume of grassroots capacity added, which was 20,300
Final Regulatory Support Document

LL A transfer payment is when money changes hands, but no real resources (labor, natural resources,

manufacturing etc.) are consumed.

7-182

bpd, to yield a total of 8,500 barrels per day of replaced capital capacity; we assumed this will be

untreated to 500 ppm nonroad hydrotreated capacity. Since we projected that 69 percent of this

existing capacity to be replaced, with the 31 percent being new units in 2007 and not replaced,

we maintained 69 percent of 8,500 bpd, or an additional 5,865 barrels of the new nonroad

hydrotreating capacity. We therefore maintained 17,665 bpd of the original 20,300 bpd of

additional capacity added in Mathpro case one. To estimate a revised cost for Mathpro’s case

one we multiplied the capital charge by a ratio of 17,665/20,300. No adjustment was necessary

for the variable operating cost.

In addition to the differences and adjustments as described above, there are several other

differences between our cost analysis and the cost analysis made by Mathpro that were adjusted

or deserve mentioning. First, the MathPro costs as reported in their final report are based on a 15

percent return on investment (ROI) after taxes. As stated above, our costs are calculated based

on a 7 percent ROI before taxes, so to compare our cost analysis with the cost analysis made by

Mathpro, we adjusted the Mathpro costs to reflect the rate of return on capital investment that we

use. Second, the MathPro estimate includes a cost add-on (called an ancillary cost) for

reblending and reprocessing offspec diesel fuel or for storing nontreated diesel fuel. While this

is conceptually an appropriate adjustment to estimate the cost to the refining industry, it appears

that some of the reblending costs in the MathPro study appear to be transfer payments,LL not

costs. We did not include these costs in our cost comparison. Third, MathPro assumed that all

new hydrogen demand is met with new hydrogen plants installed in the refinery, which does not

consider the advantage of hydrogen purchased from a third party that can be produced cheaper in

many cases. As a result, their hydrogen cost may be exaggerated, which would tend to increase

costs. In fact, Mathpro’s hydrogen is priced at $3.60 per million standard cubic feet ($/MSCF). 

However the hydrogen costs in our analysis is about $2.70 per MSCF. Finally, we note that the

MathPro study took into consideration the need for lubricity additives, but did not address costs

that might be incurred in the distribution system. When we compared out costs with Mathpro’s,

we did not include any costs that would be incurred in the distribution system not even lubricity

additive costs. For comparing the aggregate capital costs, the Mathpro aggregate capital costs

for the chosen cases were adjusted using the undesulfurized nonroad, locomotive, and marine

diesel fuel volumes for 2007 and for undesulfurized nonroad diesel fuel for 2010. The

undesulfurized volumes we used for making the adjustments are presented in Section 7.1. A

comparison of Mathpro’s costs and our costs to desulfurize highway diesel fuel to meet a 500

ppm sulfur standard and then a 15 ppm sulfur standard is shown below in Table 7.2.2-22.
Estimated Costs of Low-Sulfur Fuels

MM BOB assumed that refiners producing diesel fuel for Texas would have to produce the same fuel as currently

being produced in California. In addition, they assumed that 100 percent of highway fuel sold in both states would

have to meet a 15 ppm cap starting in mid-2006.

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Table 7.2.2-22

Comparison of Mathpro’s and EPA’s Refining Costs for Meeting a 

500 ppm and a 15 ppm Nonroad Diesel Fuel Sulfur Standard 

(7% ROI before taxes, no lubricity additive costs nor distribution costs included)

Fuel Standard Type of Cost

Mathpro’s Costs EPA’s Costs

No Advanced

Tech

Advanced Tech

in 2010

No Advanced

Tech

500 ppm Cap Std. Per-gallon Cost (c/gal) 2.1 2.2 2.2

Total Capital Cost (billion$) 580 310 310

15 ppm Cap Std.

Incremental to 500 ppm

Std. *

Per-gallon Cost (c/gal) 3.9 3.6 4.9

Total Capital Cost (billion$) 2300 1970 2420

Uncontrolled to 15 ppm Per-gallon Cost (c/gal) 6.0 5.8 7.1

Total Capital Cost (billion$) 2870 2280 2730

* Fully phased-in costs in 2014

Baker and O’Brien Study: The Baker and O’Brien (BOB) study was conducted for API to

estimate the costs and supply impacts of two possible NRLM fuel control programs. BOB first

estimated how refiners would respond to future diesel fuel requirements absent any NRLM fuel

controls. These requirements included EPA’s 2007 highway fuel program and the California and

Texas fuel programs.MM This was referred to as the Base Case in the report. The two NRLM

fuel programs evaluated were: 

1) Study Case- One step NRLM fuel program: 

15 ppm cap for all NRLM fuel in 2008

2) Sensitivity Case- Two step NRLM fuel program: 

500 ppm cap for all NRLM fuel by 2008 

15 ppm cap for nonroad fuel in 2010

BOB initiated their study prior to the NPRM, so they did not know exactly what NRLM fuel

program would be proposed. Their two cases were designed to bracket what they believed were

likely possible proposals. As it turns out, the final NRLM fuel program reflects portions of both

cases. The final NRLM fuel program is a two step program, like the sensitivity case. The final

15 pm cap applies to all NRLM fuel like the study case, though in the final NRLM fuel program,

significant volumes of NRLM fuel can be 500 ppm fuel resulting from contamination in the

distribution system. 
Final Regulatory Support Document

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The fuel supply impacts of the BOB study are addressed in Section 4.6.3.1 of the Summary

and Analysis of Comments document. The focus here is on their projected cost to produce low

sulfur NRLM fuel. BOB did not estimate the cost of producing 500 ppm NLRM fuel under the

Sensitivity Case. They only stated that roughly 300,000 bbl per day of 500 ppm diesel fuel

could be produced essentially for free from idled highway hydrotreaters. This is very similar to

our findings in Section 7.2.1 above. The primary difference is that we only consider the capital

cost to be free, since these hydrotreaters would not be operated (i.e., zero operating cost) absent

this NRLM fuel program. 

BOB developed cost estimates for 15 ppm NRLM fuel, but not for 15 ppm fuel produced

under the highway program. BOB did not use projected costs per gallon of producing 15 ppm

fuel to predict which refineries would likely produce 15 ppm fuel under either the highway or

NRLM programs. Instead, as outlined in their report, BOB made first assumed that refiners

would defer USLD capital investment whenever they had a reasonable alternative, such as

selling heating oil or exporting high sulfur diesel fuel. BOB also assumed that some refiners

would not be able to raise or justify the capital expenditures for ULSD and would discontinue

operations. In addition, BOB predicted that a sizeable number of domestic refineries would

close as a result of the highway and NRLM fuel programs. As a result of these assumptions,

BOB projected that domestic refiners would only produce 200,000-300,000 bbl per day of 15

ppm NRLM fuel out their estimated demand of 700,000 bbl per day. 

BOB presented their cost estimates for 15 ppm NRLM for both the study and sensitivity

cases. As the study case most closely approximates the fully implemented final NRLM program,

we chose to compare our fully implemented NRLM costs to those of BOB’s study case. As

BOB only presented per gallon costs graphically, we present both sets of cost estimates in

graphical form in Figure 7.2.2.5-1.
Estimated Costs of Low-Sulfur Fuels

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Figure 7.2.2-8-1

Comparison of EPA and O'Brien NRLM Desulfurization Costs to a 15 ppm 

Standard

0

2

4

6

8

10

12

14

16

18

20

0 100 200 300 400 500 600 700 800 900

MBPSD

Cents Per Gallon

EPA OBRIEN

As mentioned above, BOB projects relatively little 15 ppm NRLM fuel production compared

to demand, and compared to that projected by EPA. From the BOB report, the difference in

volume is caused by sizeable exports of high sulfur distillate from coastal refineries and a

number of refinery shutdowns in the Midwest and Mountain regions of the U.S. From the

information provided in the report, we cannot determine which refineries were projected to

export or close. Therefore, we cannot perform any more precise comparison of per gallon costs

than that provided in Figure 7.2.2.5-1. From this comparison, it is quite possible that BOB and

EPA are projecting roughly similar costs for many individual refineries. In this case, the

difference between the two cost curves would be the removal of a number of larger refineries

with EPA-projected costs in the 4-8 cent per gallon range. This would compress the EPA cost

curve into something more like the BOB cost curve. Even with this assumption, it appears that

BOB is projecting that some refineries with NRLM production volumes of 10-15,000 bbl per day

have costs in the 10-17 cent per gallon range. While above 10 cents per gallon, all the refineries

in the EPA analysis have very small NRLM production volumes. 

While BOB does not present any further detail regarding their per gallon costs, they do

provide additional detail regarding their capital and operating costs. Regarding capital costs,

BOB’s projected capital investments by domestic refiners are summarized in Table 7.2.2-23. 
Final Regulatory Support Document

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Table 7.2.2-23

BOB and EPA Capital Cost of Desulfization

Capital Investment

($ billion)

Production Volume

(1000 bbl per day) *

Investment per

bbl/day production

BOB

Highway 7.15 2934 $2437

15 ppm NRLM

(Study Case)

0.55 208 $2644

EPA

Highway 6.18 3605 $1714

15 ppm NRLM 2.28 841 $2711

* BOB volumes are in 2010, EPA volumes are in 2014

The primary figures is this table that we want to focus on are those in the last column, which

show the capital cost to add one barrel per day of 15 ppm fuel production capacity. As can be

seen, BOB projects significantly higher costs for 15 ppm highway fuel. This is likely due to

different assumptions regarding the probability that refiners will be able to revamp their existing

500 ppm hydrotreater to produce 15 ppm fuel. However, this difference will not be discussed

further, as the cost of 15 ppm highway fuel is not the focus of this comparison. 

Moving to NRLM fuel, BOB’s estimated capital cost for 15 ppm NRLM fuel production are

within a few percent of EPA’s projection on a per barrel of production basis. BOB assumes that

all refiners will use conventional hydrotreating technology to produce 15 ppm highway and

NRLM fuel. EPA projects that roughly 60 percent of the volume of 15 ppm NRLM fuel

produced will utilize advanced technology for the step from 500 ppm to 15 ppm. This would

tend to reduce EPA’s projected capital costs relative to those of BOB. However, our capital

costs include the cost of new hydrogen plants and expanded sulfur plant capacity. BOB treated

hydrogen as a utility and simply included the full cost of producing hydrogen (operating plus

capital costs) in the price that refiners would have to pay. This difference would tend to increase

our capital costs relative to those of BOB. Finally, BOB’s source of capital costs was a study by

the National Energy Technology Laboratory for EIA. NETL used many of the same sources

which we cite in Section 7.2.1 for the capital cost of conventional hydrotreating. However,

NETL increased their capital cost projections from these sources by 33 percent, based on

discussions with refiners. (The details of these discussions were not provided, so no comment

can be made about the appropriateness of this adjustment.) Therefore, it is likely that BOB’s

primary capital cost inputs for conventional hydrotreating are roughly 33 percent higher than

those described in Section 7.2.1 above. As the NETL study dates from mid-2001, it was unable

to incorporate later information, such as the successful operation of the Process Dynamics

IsoTherming demonstration unit. Overall, we believe that our capital cost estimates are
Estimated Costs of Low-Sulfur Fuels

7-187

reasonable in light of the BOB analysis. First, for conventional hydrotreating, we used the same

primary cost inputs. Second, the 33 percent adjustment by NETL was based on discussions with

refiners which we cannot evaluate. Third, it is appropriate to include advanced technologies

which have been demonstrated at the commercial level. Fourth, the inclusion of capital costs for

hydrogen plants and expanded sulfur plants provides a more complete estimate of the total

capital investment required by the refining industry and their suppliers.

Regarding operating costs, hydrogen costs tend to dominate these costs. Thus, we will focus

our comparison there. Hydrogen costs are a function of the volume of hydrogen needed to

desulfurize a gallon of diesel fuel and the price of hydrogen. Regarding the former, BOB based

their hydrogen consumption estimates on a number of studies, including one which we cite in

Section 7.2.1 (Figures 31 in the BOB report). One of these estimates, that made by IFP, projects

hydrogen consumptions over twice those of the other studies. We evaluated this estimate in our

Draft and Final RIAs for the 2007 highway diesel rule, along with a number of other estimates.

There, based on changes in other fuel properties, we determined that this estimate was based on

very conservative assumptions concerning the level of aromatic saturation and modest cracking

that would occur when desulfurizing diesel fuel to 7 ppm sulfur and decided not to use it any

further. As four out of five vendors projected that this level of saturation would not be

necessary, we decided not to incorporate this estimate into our cost methodology. 

The IFP estimates appear to have a significant impact on the BOB hydrogen consumption

estimates, as BOB’s hydrogen consumption model over-predicts all of the other data used to

develop the model. Also, subsequent discussions with IFP staff indicate that their more recent

estimates (the original estimate was made prior to 2000) are more in line with those of the other

vendors. 

In Figure 9 of the BOB study, they present their estimated hydrogen consumption for three

different diesel fuel compositions for a grass roots conventional hydrotreater designed to produce

15 ppm diesel fuel. We used our methodology developed in Section 7.2.1 to estimate hydrogen

consumption for these same feeds for a grass roots hydrotreater. Table 7.2.2-24 shows both the

EPA and BOB estimates of hydrogen consumption. 

Table 7.2.2-24

EPA and BOB 15 ppm Hydrogen Consumption: Grassroots Diesel Hydrotreater 

BOB Feed

Case

Feed Composition Hydrogen Consumption, scf/bbl 

EPA BOB

1 100% Straight Run 240 510

2 50% Straight Run, 35% LCO

15% LCGO 

582 778

3 70% LCO, 30% LCGO 1025 1091
Final Regulatory Support Document

7-188

As can be seen, the BOB estimates are significantly higher than our estimates, particularly

for the 100 percent straight run distillate. We compared BOB’s 510 scf/bbl estimate for this case

with the hydrogen consumptions which BOB presents in an appendix where it compares the

predictions of its hydrogen model to the vendor estimates (Figure 31 in the BOB report). There,

BOB shows five cases where the diesel fuel being hydrotreated is 100 percent straight run. BOB

shows that its hydrogen model predicts hydrogen consumptions of 244-268 scf/bbl for these

feedstocks. This is roughly half that which they show in Figure 9. No explanation for this

discrepancy is presented in the report. However, if the hydrogen consumptions shown in BOB’s

Figure 9 were actually used in their cost estimations, then they appeared to have over-estimated

hydrogen costs even compared to their own model validations. 

With respect to hydrogen costs, BOB assumed that hydrogen would cost twice the cost of

natural gas. They did not state whether this was on a Btu basis, or a scf basis. Other information

presented in the study implies that it was on a scf basis. As BOB projected future natural gas

prices of roughly $3 per mmBTU (equivalent to $3 per 1000 scf), this implies that BOB

projected hydrogen costs of $6 per 1000 scf. In Section 7.2.1, we describe how we estimate

hydrogen costs. There, we use a future natural gas price of $4.15 per mmBtu, well above that

used by BOB. However, using this natural gas price, we estimate hydrogen costs of $2.20-3.90

per 1000 scf. As described in Section 7.2.1, we base these costs on a new hydrogen plant typical

of the size of hydrogen plants in the region today, or by an even mix of new plants or third party

plats for the hydrogen supplied in the Gulf Coast. We also adjusted for variations in natural gas

costs, typical plant capacities, location factors and off-site factors all differing according to the

region of the country in which the refinery is located. It is unclear where BOB obtained its rule

of thumb on hydrogen prices. It may have been accurate when natural gas prices were much

lower than today and capital costs comprised a much larger percentage of total costs. However,

this rule of thumb does not appear to be appropriate at today’s natural gas prices. Thus, it

appears, though one cannot be sure given the lack of detail in the report, that BOB significantly

over-estimated hydrogen costs.

7.3 Cost of Lubricity Additives

Our evaluation of the potential impact of the non-highway diesel sulfur standards on fuel

lubricity is described in Section 5.9. We conclude that the increased need for lubricity additives

resulting from the these sulfur standards will be similar to that for highway diesel fuel meeting

the same sulfur standard. In the HD2007 rule, we conservatively estimated that all diesel fuel

meeting a 15 ppm sulfur standard will use lubricity additives at a cost of 0.2 cents per gallon.55

Consistent with the estimated cost from the increased use of lubricity additives in 15 ppm

highway diesel fuel, we have included a charge of 0.2 cents per gallon in our cost calculation to

account for the increased use of lubricity additives in 15 ppm NRLM diesel fuel. This lubricity

additive cost applies to the affected NRLM diesel fuel pool beginning in 2010.

In estimating lubricity additive costs for 500 ppm diesel fuel, we conservatively assumed that

if diesel fuel is required to have its lubricity improved through the use of additives, that the same

additive concentration will be needed both for 15 ppm and for 500 ppm diesel fuel. However,

the vast majority of 500 ppm diesel fuel does not require the use of lubricity additives. We
Estimated Costs of Low-Sulfur Fuels

7-189

assumed that 5 percent of all 500 ppm diesel fuel would need a lubricity additive. Based on

these assumptions, we estimate that the cost of additional lubricity additives for the affected 500

ppm NRLM diesel fuel is 0.01 cents per gallon. The amount of lubricity additive needed

increases substantially as diesel fuel is desulfurized to lower levels. Also, based on the industry

input (see Section 5.9) it is likely that substantially less than 5 percent of 500 ppm diesel fuel

outside of California requires a lubricity additive. We therefore believe 0.01 cents per gallon

represents a conservatively high estimate of the cost of lubricity additives for affected volume of

500 ppm nonroad, locomotive, and marine diesel fuel. Although the actual cost will likely be

considerably less, we have no information to better quantify the percentage of 500 ppm diesel

fuel currently treated with a lubricity additive or the appropriate additive treatment rate. The

0.01 cents per gallon cost for a lubricity additive applies to the affected non-highway diesel pool

(NRLM) until the 15 ppm sulfur standard takes effect in 2010. 

EIA FOKS/AEO NRLM Fuel Demand Scenario: 

As discussed in Section 5.9, lubricity costs vary primarily with sulfur level, as the sulfur

level affects the degree of hydrotreating applied, which in turn results in changes to other fuel

properties which affect lubricity. Thus, lubricity costs do not vary with implementation date or

type of diesel fuel market (i.e., highway, nonroad, locomotive or marine). Thus, as the sulfur

level of various diesel fuels change under the alternative control options, the lubricity costs vary

accordingly. However, the cost per gallon for 500 ppm fuel will remain 0.01 cent per gallon and

the cost for 15 ppm fuel will remain 0.2 cent per gallon.

7.4 Cost of Distributing Non-Highway Diesel Fuel

A summary of the distribution costs that we project will result from the implementation of

the NRLM sulfur standards is contained in Table 7.4.-1. How we arrived at these cost estimates

is described in the following sections. 
Final Regulatory Support Document

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TABLE 7.4.-1 

SUMMARY OF DISTRIBUTION COSTS (CENTS PER GALLON) *

Cause of Increase in Distribution

Costs

Time Period Over Which Costs Apply

2007-2010 2010-2012 2012-2014 After 2014

Distribution of Additional NRLM

Volume to Compensate for Reduction

in Volumetric Energy Content

0.08 0.1 0.1 0.1

Distillate Interface Handling 0 0.4 0.4 0.8

New Product Segregation as Bulk

Plants 

0.1 0.1 0.1 0.1

Heating Oil and L&M Fuel Marker 0.01 0.02 0.01 0.01

Total 0.2 0.6 0.6 1.0

* Costs have been rounded to one significant figure.

7.4.1 New Production Segregation at Bulk Plants 

Section 5.4.1. evaluates the potential for additional product segregation in each segment of

the distribution system. As discussed in Section 5.5.1.2., approximately 1,000 bulk plants could

add an additional storage tank and demanifold their delivery truck(s) to handle an additional

diesel product.

In its comments to the government/industry panel convened in accordance with the Small

Business Regulatory Enforcement Act (SBREFA), the Petroleum Marketers Association of

America (PMAA) stated that, depending on the location, the cost of installing a new diesel

storage tank at a bulk plant ranges from $70,000 to $100,000. To provide a conservatively high

estimate of the cost to bulk plant operators, we used an average cost of $90,000. This is

consistent with the information we obtained from a contractor working for EPA (ICF Kaiser) on

the installed cost of a 20,000-gallon storage tank, which is the typical tank size at bulk plant

facilities. Demanifolding of the bulk plant operators delivery truck involves installing an

internal bulkhead to make two tank compartments from a single compartment. To help control

contamination concerns, we also estimated that an additional fuel delivery system will be

installed on the tank truck (i.e., that there will be a separate delivery system for each fuel carried

by the delivery truck). The cost of demanifolding a tank truck and installing an additional fuel

delivery system is estimated at $10,000, of which $6,000 is the cost of installing a new fuel

delivery system.56 

In the NPRM, we estimated that each bulk plant that needed to install a new storage tank

would need to demanifold a single tank truck. Thus, the NPRM estimated the cost per bulk plant

would be $100,000. Fuel distributors stated that the assumptions and calculations made by EPA
Estimated Costs of Low-Sulfur Fuels

NN To avoid sulfur contamination of NRLM fuel, the tank compartment would need to be flushed with some

NRLM fuel prior to switching from carrying heating oil to NRLM fuel.

7-191

in characterizing costs for bulk plant operators seem reasonable. However, they also stated that

our estimate that a single tank truck would service a bulk plant is probably not accurate. No

suggestion was offered regarding what might be a more appropriate estimate other than the

number is likely to be much greater. Part of the reason why we estimated that only a single tank

truck would need to be demanifolded, is that we expected that due to the seasonal nature of the

demand for heating oil versus nonroad fuel, it would primarily only be at the juncture of these

two seasons that both fuels would need to be distributed in substantial quantities. We also

expected that the small demand for heating oil in the summer and the small demand for nonroad

fuel in the winter could be serviced using a single demanifolded truck. The primary fuel

distributed during a given season would be distributed by single compartment tank trucks. 

During the crossover between seasons, bulk plant operators would switch the fuel to which such

single compartment tank trucks are used from nonroad to heating oil and back again.NN

Nevertheless, we agree that some of the subject bulk plant operators would likely be compelled

to demanifold more that a single tank truck. Lacking additional specific information, we believe

that assuming that each bulk plant operator demanifolds three tank trucks will provide a

conservatively high estimate of the cost to bulk plant operators due to this rule.

If all 1,000 bulk plants were to install a new tank and demanifold three tank trucks, the cost

for each bulk plant would be $120,000, and the total one-time capital cost would be

$120,000,000. To provide a conservatively high estimate of the costs to bulk plant operators, we

are assuming that all 1,000 bulk plants will do so. Amortizing the capital costs over 20 years,

results in a estimated cost for tankage at such bulk plants of 0.1 cents per gallon of affected

NRLM diesel fuel supplied. Although the impact on the overall cost of the program is small, the

cost to those bulk plant operators who need to put in a separate storage tank may represent a

substantial investment. Thus, we believe many of these bulk plants will search out other

arrangements to continue servicing both heating oil and NRLM markets such as an exchange

agreement between two bulk plants that serve a common area.

The need for additional storage tanks at terminals to handle products produced from pipeline

interface is discussed in Section 7.4.1.2. of this RIA. Aside from the costs described above for

bulk plant operators, and those discussed in Section 7.4.1.2, we project that there will be no

substantial need for additional storage tanks or other facility changes to segregate additional

products. 

EIA FOKS/AEO Nonroad Fuel Volume Scenario: 

Using EIA nonroad fuel volumes rather than our primary fuel volume scenario which utilized

the EPA NONROAD model for nonroad fuel consumption does not affect our assessment of

product distribution patterns on which the above estimate of the costs to bulk plant operators are

based. Therefore, our estimate of the costs to bulk plant operators under the EIA nonroad fuel

volume scenario is the same as that under our primary fuel volume scenario. However, the
Final Regulatory Support Document

7-192

volume of affected NRLM to which these costs are attributed is reduced somewhat under the

EIA nonroad volume scenario, and consequently the cost per gallon is directionally higher than

under our primary fuel volume scenario. Nevertheless, because the costs are small, this does not

result in a material change to our estimate of 0.1 cents per gallon of affected NRLM diesel fuel

supplied.

Because our assessment of product distribution patterns is not different under the EIA

nonroad volume scenario from that under our primary scenario, we also project that aside from

the costs described above for bulk plant operators, and those discussed in Section 7.4.1.2, there

will be no substantial need for additional storage tanks or other facility changes to segregate

additional products.

7.4.2 Reduction in Fuel Volumetric Energy Content

We project that desulfurizing diesel fuel to 500 ppm will reduce volumetric energy content

(VEC) by 0.7 percent. The cost of which is equivalent to 0.08 cent per gallon of affected NRLM

fuel. We project that desulfurizing diesel fuel to 15 ppm will reduce volumetric energy content

by an additional 0.5 percent. This will increase the cost of distributing fuel by an additional 0.05

cents per gallon, for a total cost of 0.13 cents per gallon of affected 15 ppm NRLM fuel. 

Following is a discussion of how we arrived at these estimated costs.

The reduction in VEC due to desulfurization of NRLM fuel to meet the standards in this rule

depends on the desulfurization process used. We project that conventional hydrotreating will be

the desulfurization process used to desulfurize NRLM to meet the 500 ppm sulfur standard. 

However, as discussed in Chapter 5, we project that new technology (Process Dynamics

Isotherming) will be used as well to desulfurize NRLM to meet the 15 ppm standard. These

processes have different projected impacts on VEC, as discussed in Chapter 5.2. and shown in

Table 7.4-2.

Table 7.4-2 

Impact of Desulfurization on the Volumetric Energy Content of Diesel Fuel 

Process NRLM Fuel Volume Processed Reduction in VEC

High Sulfur to 500

ppm

Reduction in VEC

500 ppm to 15 ppm

500 ppm

Standard

15 ppm

Standard

Hydrodesulfurization 100 % 40 % 0.7% 0.7%

Process Dynamics

Isotherming

0 % 60 % NA 0.4%

Overall for NRLM Pool - - 0.7% 0.5%

The difference between the price of non-highway diesel fuel to end-users and the price to

resellers provides an appropriate estimate of the cost of distributing non-highway diesel fuel. 

The Energy Information Administration (EIA) publishes data regarding the price excluding taxes

of high-sulfur No. 2 diesel fuel to end-users versus the price to resellers. We used the five-year
Estimated Costs of Low-Sulfur Fuels

7-193

average of the difference between these two prices to arrive at an estimated typical cost of

distributing NRLM fuel to the end-user. In the NPRM, we used data from 1995 through 1999 to

arrive at an estimated distribution cost of 10 cents per gallon. For this final rule, we used 1997

through 2001 data to update this analysis. The EIA data that we used to estimate the cost of

distributing NRLM fuel is presented in Table 7.4-3.

Table 7.4-3

Cost of Distributing High-Sulfur No. 2 Diesel Fuela (cents per gallon, excluding taxes)

Year Sales to Resellers Sales to End Users Difference Between Sales to End Users 

and Sales to Resellers

1995 52.4 61.4 9.0

1996 63.9 73.2 9.3

1997 60.2 69.8 9.6

1998 43.7 55.5 11.8

1999 51.9 62.0 10.1

2000 87.5 98.1 10.6

2001 77.1 89.2 12.1

Average of 

5 Most Recent Years

54.4 64.4 10.8

a

 Energy Information Administration, Annual Energy Review 2003

Based on the information in Table 7.4-3, we assumed a 10.8 cent per gallon cost of

distributing diesel for the purposes of estimating the increased distribution costs due to reduced

VEC. We derived our estimates of the increase in distribution costs under each step of the

NRLM sulfur program by multiplying the applicable percent reduction in VEC by 10.8 cents per

gallon.

Since the difference in price at the refiner rack versus that at retail also includes some profit

for the distributor and retailer, its use provides a conservatively high estimate of distribution

costs. The fact that a slightly less dense (lighter, less viscous) fuel requires slightly less energy

to be distributed also indicates that this estimate is conservative.

EIA FOKS/AEO Nonroad Fuel Volume Scenario: 

Using EIA nonroad fuel volumes rather than our primary fuel volume scenario which utilized

the EPA NONROAD model for nonroad fuel consumption does not affect our estimate of the

increased distribution costs related to the reduction in VEC. Thus, the 0.08 and 0.13 cent per

gallon costs for 500 ppm and 15 ppm fuel do change. 
Final Regulatory Support Document

OO Normally, one thinks of transmix processing as separating transmix back into its original gasoline and

distillate components. However, the lighter compounds in original distillate fuel inevitably mix with the heavier

compounds in the original gasoline and lower the octane of this heavy gasoline dramatically. Due to the cost of

making up for this octane loss, transmix processors typically send the heavier gasoline compounds to the distillate

half of their product..

7-194

7.4.3 Handling of Distillate Fuel Produced from Pipeline Interface

As discussed in Section 5.1, the shipment of 30 ppm gasoline, 15 ppm diesel fuel, jet fuel

and, in some cases, 500 ppm locomotive and marine fuel and high sulfur heating oil, will

produce commingled distillate fuel at the interfaces of each batch. In Section 5.1, we estimate

the volumes of each interface and how the fuel distribution system could dispose of each

interface in order to maximize profits (i.e., minimize costs). Basically, interfaces containing

some gasoline are presumed to go to existing transmix facilities. The distillate fuel produced by

these transmix processors will contain a mixture of heavy naphtha, jet fuel and 15 ppm diesel

fuel. We project that this mixture will contain 500 ppm sulfur or less and can thus be sold as 500

ppm diesel fuel of high sulfur heating oil.

The other interface which will not be able to be blended into either of the adjacent batches is

that between jet fuel and 15 ppm diesel fuel. In the Northeast and along the Colonial and

Plantation pipelines, we assume that this distillate interface will be added to the heating oil tank,

which will continue to be distributed throughout the distribution system. Elsewhere, we do not

believe that heating oil will be distributed in pipelines. We assume the interface containing jet

fuel and 15 ppm diesel fuel will not be shipped to transmix processors. Interface processors

basically distill transmix into a lighter than average naphtha component and a lighter than

average distillate component.OO This distillate contains all of the original jet fuel and No. 2

distillate (both highway and high sulfur) fuel. Adding an interface consisting of jet fuel and No.

2 distillate to the current transmix tank and running this through a distillation column would only

result in all of this jet-distillate interface flowing to the bottoms of the column. The additional

distillate would also affect the operation of the distillation column, as they are typically designed

for a certain fraction of the feedstock going overhead. Thus, we believe that it would be more

economical for terminals to segregate this No. 1/No. 2 distillate interface from transmix in a

separate storage tank. As described in Section 7.1, we estimate that this interfacial material will

likewise meet a 500 ppm sulfur cap. Thus, the terminal can ship this interface to consumers in

either the 500 ppm diesel fuel or heating oil markets. 

The disposition of this 500 ppm interface fuel is described in Section 5.1. Generally, we

assumed that this material would be sold to the heating oil first, then into the 500 ppm highway

fuel market (through 2010), to the 500 ppm NRLM market (the nonroad fuel market through

2014), and finally into the L&M diesel market (after 2014). An exception to this applies in the

Northeast/Mid-Atlantic Area, where this interface cannot be sold into the nonroad fuel market

after 2010, nor into the L&M fuel market after 2012. If the volume of this 500 ppm interface

exceeds the demand for 500 ppm diesel fuel and heating oil, then we assumed that it would have

to be shipped back to a refiner and reprocessed to meet the 15 ppm cap. 
Estimated Costs of Low-Sulfur Fuels

7-195

The cost of disposing of this 500 ppm distillate material will likely vary geographically,

depending on the size of the heating oil market. In the Northeast, the only cost of disposing of

this interface will be the value lost by selling former jet fuel and 15 ppm diesel fuel as heating

oil. This cost is already included in our refining costs, as there, we increased the volume of 15

ppm diesel fuel which had to be processed due to losses during distribution. We estimate that

about 80% of the diesel fuel shipped to PADD 1 is sold in areas with large heating oil markets. 

In the remainder of the country, the heating oil market is more limited. Matching any high sulfur

heating oil and users of this fuel will be more difficult and costly in terms of transportation. 

Prior to mid-2010, 500 ppm interface can simply be added to the 500 ppm NRLM fuel

storage tank, which should exist at most terminals, or the 500 ppm highway fuel storage tank, if

this fuel is being stored at that terminal. Thus, there should be essentially no cost related to

disposing of this interface material. 

From mid-2010 through 2012, 500 ppm fuel can no longer be sold to the highway fuel

market. Also, we do not expect that small refiner 500 ppm nonroad fuel and 500 ppm L&M fuel

will be widely distributed. Thus, this interface material will require its own storage tank. The

500 ppm interface can be sold to users of NRLM fuel, as well as heating oil. The only restriction

is that it cannot be used in nonroad equipment equipped with emission controls requiring 15 ppm

fuel, nor in nonroad engines in general within the Northeast/Mid-Atlantic Area. Most nonroad

fuel users only have one fuel storage tank on-site. Or, if they have more than one tank, it is

because their operations cover long distances (e.g., farms, quarries, etc.) and multiple tanks

reduce the time it takes to move the equipment to the refueling station. Thus, nonroad

equipment users which have purchased even one new piece of equipment requiring 15 ppm fuel

will often desire to purchase 15 ppm fuel for all their equipment. Thus, the number of NRLM

fuel users willing to accept 500 ppm fuel will gradually diminish from 2010 to 2014. This will

increase the distance that the fuel will have to be shipped to find a purchaser. 

We estimate that the cost to store this 500 ppm fuel at a terminal will vary by terminal. At

those terminals able to receive jet fuel and 15 ppm diesel fuel from the heart of the pipeline

batches passing by it, the only distillate-distillate interface will be from washing lines to protect

jet fuel and diesel fuel quality. This material might be stored in a small tank, but will most likely

simply be added to the existing transmix tank. Thus, incremental storage costs will likely be

negligible, but transmix volume will increase. Terminals near the end of pipeline or pipeline

branch will receive a relatively large volume of distillate-distillate interface. Some of these

terminals will likely be able to use the tank that was previously used to hold heating oil or 500

ppm NRLM fuel or the tank used to hold 500 ppm L&M diesel fuel from 2010-2012. However,

in other cases it may require some new tankage. Economics will likely encourage the offloading at terminals with existing tankage. However, proximity to a large 500 ppm market

(L&M fuel, heating oil) will also likely be a factor. 

Depending on the size of the tank, storage costs vary substantially. Smaller tanks can cost $5

per gallon of capacity, while very large tanks might only cost $20 per barrel ($0.5 per gallon). 

Amortizing these costs over 15 years of weekly shipments of 60% of capacity at a 7% rate of

return, storage costs range from 0.2-1.6 cents per gallon in those cases requiring a new tank. It is
Final Regulatory Support Document

PP Trucking and rail costs of 0.035 and 0.012-0.2 cent per gallon, respectively from: “Costs/Impacts of

Distributing Potential Ultra Low Sulfur Diesel”, Robert E. Cunningham, Thomas R. Hogan, Joseph A. Loftus, and

Charles L. Miller, Turner and Mason and Co. Consulting Engineers, February 2000.

7-196

not possible to estimate a precise distribution of tank sizes and thus, costs. We assume that the

availability of existing tankage will balance the need for smaller tanks on average and that the

average storage cost will be near the lower end of this range, 0.4 cents per gallon. In addition,

there is an inventory cost to have this stored fuel on hand. At a 7% rate of return, assuming that

the tank is half full on average, for fuel at $1 per gallon, the carrying cost is 0.1 cent per gallon. 

Thus, the total storage cost is roughly 0.5 cent per gallon.

There is also the potential for increased storage costs at transmix processing facilities. The

increased volume of distillate-distillate interface added to transmix will likely be very small

relative to the total volume of gasoline-distillate interface. Thus, existing tankage should be

sufficient. However, currently, transmix processors often ship their distillate production into

tankage at terminals which are usually located adjacent to the processing facility. After 2010,

the only 500 ppm fuel that would be stored at most of these terminals would be interface, and all

terminals after 2012, as discussed above. These terminals may have to increase their storage

capacity beyond that necessary to handle interface received directly from the pipeline and line

washing. We project that the incremental cost to store this transmix interface will be the same

0.5 cent per gallon as that projected above for non-transmix interface. Since all the distillatedistillate interface will either be stored as a distinct fuel at the terminal or combined with

transmix and processed, the overall storage cost for all distillate-distillate interface is 0.5 cent per

gallon. 

We expect that there will be an additional cost of shipping this 500 ppm fuel to those who

can use it. Nonroad fuel markets will likely be served by truck, as is the case today. Locomotive

and most marine markets will likely be served by rail. Shipping this 500 ppm fuel will not have

the economies of scale of the current nonroad market or the future 15 ppm nonroad market. 

Trucks will have to spend more time driving between stops or a smaller compartment will have

to be added to the tank. In either case, costs will increase. Rail shipments will also be smaller

than today, increasing handling costs. We estimate that the additional cost of delivering 500

ppm interface to these NRLM users without 2011 and later nonroad equipment will cost 1.5

cents per gallon. This cost is equivalent to increasing the shipping distance by 45 miles by truck

and 100 miles by rail.PP Combined with storage costs, distributing this fuel to NRLM users will

cost 2.0 cents per gallon. 

In those cases where the 500 ppm interface is sold to the heating oil markets outside of the

Northeast, we expect that the costs will be larger. Heating oil users outside of the Northeast are

not evenly distributed geographically. The interface will also not be evenly distributed

geographically. Thus, the interface may not be removed from the pipeline near the users of

heating oil. Also, we expect that this fuel will have to be transported by truck. We project that

the additional mileage will be roughly 85 miles and cost 3.0 cents per gallon. Combined with

storage costs, distributing this fuel to heating oil users outside of the Northeast will cost 3.5 cents

per gallon.
Estimated Costs of Low-Sulfur Fuels

7-197

Finally, there are some PADDs where the NRLM and heating oil markers are not large

enough to handle all of the 500 ppm interface generated. In these cases, the interface will have

to be shipped back to a refinery by truck, reprocessed through the refiner’s hydrotreater and

shipped back to the fuel market with the rest of the refiner’s production. The storage cost of 0.5

cent per gallon at terminals and transmix operators will still apply, since it will still likely to be

less costly to keep this interface segregated from gasoline-distillate transmix. (Transmix will be

sent to transmix processors, while the jet-distillate interface will have to be sent to refineries

with excess hydrotreating capacity.) We estimate that most of this distillate will be shipped

roughly 200 miles by rail and cost 3.0 cents per gallon. Desulfurizing this material to 15 ppm

will be technically simple, since it will consist of heavy naphtha, jet fuel and 15 ppm diesel fuel. 

The two lighter fuels do not contain any stearically hindered molecules. However, refiners

generally do not add material into the middle of their distillate production train. There will

likely be a tank storing diesel fuel prior to desulfurization, where straight run, LCO and other

cracked stocks are mixed. However, there might not be easy access to this tank from outside of

the refinery. Thus, we expect that the handling costs will far exceed the desulfurization costs. 

We project a total cost for reprocessing of 4.5 cents per gallon. Finally, this re-processed fuel

must be shipped out again, usually via pipeline. We project this last distribution cost to be 2

cents per gallon. Thus, the total cost for interface which must be reprocessed is 10 cents per

gallon. 

From mid-2012 through 2014, very little changes from 2010-2012. The only change is that

downgraded distillate can no longer be sold to the L&M fuel market in the Northeast/MidAtlantic Area. Instead this fuel shifts to the heating oil market. As this is a minor change, we

assume that all of the costs of distributing the downgraded distillate to the various markets from

2012-2014 remain the same as in 2010-2014. 

In 2014, when 500 ppm fuel can no longer be sold to nonroad equipment users, we project

that the transportation distance to L&M fuel users will nearly double, as will the transportation

cost, to 2.5 cents per gallon. Outside of PADDs 1 and 3, we estimate that the downgraded

material will comprise 70-100% of the L&M market, so, given the above methodology, the

downgraded material will have to move to nearly every L&M refueling site. With storage costs

of 0.5 cents per gallon, the total cost of distributing downgraded material to the L&M fuel

market will be 3.0 cents per gallon.

Likewise, we project that the transportation distance to heating oil users will also increase. 

However, we do not believe that these distances will double, because the increase in downgraded

material going to the heating oil market is smaller on a relative basis than for the L&M fuel

market. Thus, we project that the transportation distance to heating oil users will increase to

roughly 130 miles and cost 4.5 cents per gallon. With storage costs of 0.5 cents per gallon, the

total cost of distributing downgraded material to the heating oil market will be 5.0 cents per

gallon. The cost to reprocess distillate to meet a 15 ppm cap will remain at 10 cents per gallon.

In Section 7.1, we estimated the volume of downgraded jet fuel and diesel fuel which would

be sold to the nonroad, L&M and heating oil markets prior to the NRLM rule (Table 7.1.3-9),
Final Regulatory Support Document

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from 2007-2010 (Table 7.1.3-14), from 2010-2012 (Table 7.1.3-17), from 2013-2014 (Table

7.1.3-18) and in 2014 and beyond (Table 7.1.3-19). We likewise estimate the volumes of fuel

which must be reprocessed to meet a 15 ppm cap. These volumes are summarized in Table

7.4.4, along with the cost per gallon of storing and shipping this interface to the various fuel

markets.

Table 7.4.4

Annual Costs Associated With Distribution of Distillate Interface

Jet-Distillate

Interface Sent to:

Volume Affected

(million gallons/yr)

Cost per Gallon Annual Cost

(million)

Baseline

NRLM Market 247 2.0 cents $5

Heating Oil Market 219 3.5 cents $8

Reprocessed 0 10.0 cents 0

Total --- --- $13

2010-2012

NRLM Market 1,395 2.0 cents $30

Heating Oil Market 1,045 3.5 cents $32

Reprocessed 0 10.0 cents 0

Total --- --- $63

2012-2014

NRLM Market 1,395 2.0 cents $28

Heating Oil Market 1,045 3.5 cents $37

Reprocessed 0 10.0 cents 0

Total --- --- $65

2014 and beyond

NRLM Market 1,336 3.0 cents $40

Heating Oil Market 885 5.0 cents $44

Reprocessed 335 10.0 cents $34

Total --- --- $118

Table 7.4.4 also shows the annual cost associated with each fuel market, which is simply the

product of the fuel volume and the cost per gallon (converted from cents to dollars). The annual

cost due to the NRLM rule from 2007-2010 is $47 million, which is the total cost of $61 million

less the $14 million cost occurring prior to the rule. Likewise, the cost due to the NRLM rule in
Estimated Costs of Low-Sulfur Fuels

QQ The increase in cost in 2014 is due to the inability to use downgraded material in the nonroad market. If the

$105 million cost in 2014 is spread only over the nonroad fuel market, the cost per gallon is 1.0 cents.

7-199

2010-2012, 2012-2014 and 2014 and beyond is $63, $65, and $102 million, respectively. The

total affected NRLM fuel volume is 12.4 billion gallons in 2010, 12.8 billion gallons in 2012 and

13.4 billion gallons in 2014 (all three figures represent fuel production and demand grown to

2014). Thus, these annual costs represent incremental costs of 0.40, 0.41 and 0.79 cent per

gallon from 2010-2012, 2012-2014, and 2014 and beyond, respectively.QQ 

We anticipate that there will be no other significant distribution costs associated with the

NRLM sulfur standards in this rule beyond those described in Sections 7.4.1, 7.4.2, and 7.4.3. 

We do not expect the need for additional storage tanks beyond that discussed in Sections 7.4.1.,

and 7.4.3., or a significant increase in pipeline downgrade or transmix volumes beyond the

modest potential increase in tranmix volume discussed in Section 7.4.3. As discussed in Section

7.4.5., we are projecting costs associated with the need to install fuel marker injection equipment

at a limited number of refineries, transmix processors, and terminals

Operators of bulk plants and tank trucks who previously handled only high-sulfur diesel fuel

will need to begin observing practices to limit sulfur contamination during the distribution of 500

ppm and 15 ppm diesel fuel. However, these practices are either well established or will be for

compliance with the 15 ppm highway standard in 2006. Furthermore, they are primarily

associated with purging storage tanks and fuel delivery systems of high-sulfur diesel fuel before

handling 500 ppm and 15 ppm diesel fuel. Training employees will be necessary to stress the

importance of consistently and carefully observing practices to limit sulfur contamination. 

However, we estimate the associated costs will be minimal. In addition, we are estimating that

most of the affected bulk plant operators will install dedicated storage tanks and truck delivery

systems. This obviates the need for much of the cautionary actions necessary to limit sulfur

contamination when both low and high-sulfur diesel fuel is carried by the same marketer.

As discussed in Section 5.6, the vast majority of the fuel distribution system (primarily

pipeline and terminal facilities) will already have optimized their facilities and procedures to

limit sulfur contamination for distributing 15 ppm sulfur fuel due to the need to comply with the

highway diesel fuel program in 2006. The costs associated with this optimization process were

accounted for in the HD2007 Regulatory Impact Analysis.57 Highway diesel fuel and nonroad

diesel fuel meeting a 15 ppm sulfur specification will share the same distribution system until

nonroad diesel fuel is dyed to meet IRS requirements as it leaves the terminal. We therefore do

not expect any additional actions or costs to optimize the distribution system to limit sulfur

contamination during the distribution of 15 ppm nonroad diesel fuel.

EIA FOKS/AEO Nonroad Fuel Volume Scenario: We followed the same methodology for

estimating downgrade-related distribution costs for this scenario as our primary fuel volume

scenario which utilized the EPA NONROAD model for nonroad fuel consumption. Using EIA

nonroad fuel volumes, as described in Section 7.1 above, reduces the volume of NRLM fuel

demanded in each PADD, except PADD 3. Consequently, the volumes of heating oil consumed
Final Regulatory Support Document

RR The costs of the marker requirement for L&M diesel fuel are discussed at the end of this section.

7-200

increase everywhere except PADD 3. This reduces the contribution of the volume of

downgraded material to the NRLM and heating oil markets substantially. Particularly in PADD

2, instead of downgraded material comprising a major portion of the NRLM and heating oil

markets, it comprises roughly 33%. We believe that this will make it easier for terminals to find

heating oil consumers and reduce the transport distance to these users. Thus, for PADD 2, we

reduced the cost of distributing interface to the heating oil market to that of the NRLM or L&M

markets (depending on the time period), or 2 cents per gallon. However, the volume of NRLM

fuel over which the increased transportion costs are spread also decreases. The net result is that

the cost of distributing interface material from 2010-2014 remains unchanged at 0.4 cent per

gallon. However, the cost after 2014 decreases from 0.79 to 0.56 cents per gallon. 

7.4.4 Fuel Marker Costs

In the NPRM we estimated that the cost to blenders of the heating oil marker in bulk

quantities would translate to 0.2 cents per gallon of fuel treated with the marker. This estimate

was based on the fee charged by a major pipeline to inject red dye at the IRS concentration into

its customers diesel fuel. Conversations with marker manufactures prior to the publication of the

NRLM indicated that the cost to treat fuel with either of the markers considered in the NPRM

would be lower than the costs to treat non-highway diesel fuel with red dye to meet IRS

requirements. We used this estimate because we lacked specific cost information on the

proposed marker, there was uncertainty regarding the specific marker that we would require, and

we believed that it provided a conservatively high estimate of cost for any of the markers under

consideration. Since the proposal, we received input from a major distributor of fuel markers

and dyes, regarding the cost of bulk deliveries of the specified fuel marker (solvent yellow 124)

to terminals which translates to a cost of 0.03 cents per gallon of fuel treated with the marker. 

The volume of heating oil that we expect will need to be marked has also decreased substantially

from that estimated in the NPRM due to the provisions applicable in the Northeast/Mid-Atlantic

Area and Alaska. We estimate that 1.4 billion gallons of heating oil will be marked annually, for

an annual marker cost of $425,000.RR In the NPRM, this marker cost applied to heating oil for

just three years, but then continued on for another four years for locomotive and marine diesel

fuel. Under this final rule, the marker requirement for locomotive and marine diesel fuel is

applicable only from 2010 though 2012, and only outside of the Northeast/Mid-Atlantic Area

and Alaska. However, the marker requirements for heating oil continues indefinitely.

The NPRM projected that there would be no capital costs associated with the proposed

marker requirement. We proposed that the marker would be added at the refinery gate, and that

the current requirement that non-highway fuel be dyed red at the refinery gate be made

voluntary. Thus, we believed that the refiner’s additive injection equipment that is currently

used to inject red dye into off-highway diesel fuel could instead be used to inject the fuel marker. 

As a result of the allowance provided in this final rule that the marker may be added at the

terminal rather than the refinery gate, and our reevaluation of the conditions for dye injection at
Estimated Costs of Low-Sulfur Fuels

SSA refinery rack functions similar to a terminal in that it distributes fuel by truck to wholesale purchaser

consumers and retailers.

7-201

the refinery, we are now assessing capital costs for terminals and refiners related to compliance

with the marker requirements.

Except for fuel that is distributed directly from a refiner’s rack, this final rule allows the

marker to be added at the terminal rather than at the refinery (see Section IV.D. of the preamble

for a discussion of the fuel marker requirements).SS We expect that except for fuel dispensed

directly from the refinery rack, the fuel marker will be added to at the terminal to avoid the

potential for marked fuel to contaminate jet fuel in during distribution by pipeline. Terminals

that need to inject the fuel marker will need to purchase a new injection system, including a

marker storage tank and a segregated line and injector for each truck loading station at which

fuel that is required to contain the marker is dispensed. Terminals will still be subject to IRS red

dye requirements, and thus will not be able to rededicate such injection equipment to inject the

fuel marker. Due to concerns regarding the need to maintain a visible evidence of the presence

of the fuel marker, this final rule also contains a requirement that any fuel which contains the

fuel marker also contains visible evidence of red dye. Furthermore, there is little chance to adapt

parts of the red dye injection system (such as the feed lines and injectors) for the alternate

injection of red dye and the fuel marker due to concerns that fuel which must not contain the

marker might become contaminated with the marker.

We received information from various sources to estimate the cost of installing new injection

equipment to handle the heating oil marker. Our first source of information was the Independent

Fuel Terminal Operators Association (IFTOA). IFTOA stated that the cost for new additive

injection equipment would be $40,000 per loading arm used to deliver heating oil to tank trucks

with the cost for some terminals being as much as $250,000 (for 6-7 loading arms).

We also sought information from manufacturers of additive injection equipment. Titan

industries and Lubrizol, leading manufacturers of such equipment, provided information on the

uninstalled cost of the necessary hardware which is summarized in the following Table 7.4.5.58.

Table 7.4.5 

Uninstalled Cost of Additive Injection Hardware

Item Cost

500 gallon Skid Storage Tank $3,700 - $8,000

Rack Mounted Pump Assembly $5,000 - $9,0001

Chemical Injector $2,500-$2,900

Total $11,200-$19,900

1. Depending on whether a single or a double pump assembly is used. The second pump serves

as a back-up.
Final Regulatory Support Document

TTSmall refiner and credit high sulfur NRLM will not be permitted to be sold in the area where terminals are not

required to add the fuel marker to heating oil and 500 ppm sulfur L&M diesel fuel produced by refiners or imported

(the "Northeast/Mid-Atlantic Area"). See Section IV.D. of the preamble. See Section 5.5.1.4 regarding our

determination of the boundary of the Northeast/Mid-Atlantic Area to minimize the number of facilities that would

need in to install new injection equipment for the fuel marker and to limit the volume of fuel that will need to be

marked. 

7-202

The lower end tank cost was more consistent with our previous experience regarding tank

costs. Consequently we elected to use $4,000 as a reasonable estimate of the uninstalled cost of

an additive storage tank. We elected to use the higher cost estimate of $9,000 for the pump

assembly because we believe that many additive blenders would wish to have a double pump

assembly to prevent their fueling arm from being shut down when maintenance must be

performed on the primary pump. This also provides something of a conservatively high cost

estimate. We also elected to use $3,000 as the estimated uninstalled cost of an injector unit for

this same reason. This results in an total uninstalled cost of $16,000 for the equipment necessary

to equip one injection loading arm: $13,000 for the tank and pump, and $3,000 for each injector. 

We estimated the installed costs by two means. Our primary means was to apply the rule for

such projects of multiplying the equipment costs by 2 to arrive at the installed cost and then by

increasing this result by an additional 50 percent to ensure that the estimated cost would be

sufficient to account for areas in the U.S. where labor costs are higher that the average (such as

the Northeast). Since the Northeast/Mid-Atlantic Area was defined to exclude terminals in the

Northeast from the marker requirement, this step might be expected to provide a conservatively

high estimate of installation costs for those facilities that do need to install new injection

equipment. Following this method results in an estimated installed cost of the equipment

necessary to provide marker injection at one loading arm of $50,000 ($40,000 for the tank and

pump assembly, and $10,000 for the injector assembly. Thus, for each additional loading arm at

a terminal the cost would increase by $10,000. As a double check on these results we employed

an in-house expert to estimate the time required of various skilled tradesmen at their respective

hourly pay rates: e.g. instrumentation specialist, welder, welder’s helper, concrete installer,

engineer, and laborers. The estimate that we arrived at using this means supported the estimates

described above. We believe that these estimates are more accurate than those provided by

IFTOA, and therefore are using them to calculate the costs under this rule.

Terminal operators expressed concern regarding the potential burden of installing new

additive injection equipment. In response to these comments, this rule includes provisions that

exempt terminal operators from the fuel marker requirements in a geographic “Northeast/MidAtlantic Area” and Alaska.TT These provisions provide that any heating oil or 500 ppm sulfue

L&M diesel fuel produced by a refiner or imported that is delivered to a retailer or wholesalepurchaser consumer inside the Northeast/Mid-Atlantic Area and Alaska does not need to contain

the marker. The Northeast/Mid-Atlantic Area was defined to include the region where the

majority of heating oil in the country is projected to continue to be supplied though the bulk

distribution system (the Northeast and Mid-Atlantic). The vast majority of heating oil

consumption in the U.S. will be within the Northeast/Mid-Atlantic Area. Outside of the
Estimated Costs of Low-Sulfur Fuels

UU Fuel sold as heating oil outside of the Northeast/Mid-Atlantic Area will primarily be generated as a byproduct of the distribution of 15 ppm diesel fuel by pipeline. 

7-203

Northeast/Mid-Atlantic Area, we expect that only limited quantities of heating oil will be

supplied, primarily from certain refiner’s racks. Based on our analysis of the number of

refineries that we expect will continue to produce heating oil and information from transmix

processors on the number of such facilities, we estimate that 30 refineries and transmix processor

facilities outside of the Northeast/Mid-Atlantic Area will distribute heating oil from their racks

(in limited volumes) on a sufficiently frequent basis to warrant the installation of a marker

injection system at a total one time cost of $1,500,000.

Terminals outside of the Northeast/Mid-Atlantic Area will mostly be located in areas without

continued production and/or bulk shipment of heating oil. Consequently, any high sulfur diesel

fuel they sell will typically be NRLM. Terminals located within the Northeast/Mid-Atlantic

Area will not need to mark their heating oil, except for those few that choose to ship heating oil

outside of the Northeast/Mid-Atlantic Area. The terminals most likely to install marker injection

equipment will therefore be those in states outside the Northeast/Mid-Atlantic Area with modest

markets for heating oil after the implementation of this program.

A few terminals inside the Northeast/Mid-Atlantic Area and near the border may choose to

install marker injection equipment so that they can serve customers outside of the

Northeast/Mid-Atlantic Area. However, based on our review of the proximity of terminals

inside the Northeast/Mid-Atlantic Area to potential heating oil markets outside of the

Northeast/Mid-Atlantic Area, we project that no more than 15 terminals will be induced to do so. 

Given the relatively low level of the potential demand for marked heating oil, we believe that the

boundary area terminals that install marker injection equipment would provide for the loading of

marked heating oil into trucks at only one loading bay (at $50,000 per terminal).

Some terminals outside of the Northeast/Mid-Atlantic Area that are supplied by the pipeline

system which supplies the Northeast/Mid-Atlantic Area are likely to carry heating oil. 

Considering the relatively low volume of heating oil demand in the states in which these

terminals are located, we estimate that only 15 terminals in this area will choose to install marker

injection equipment so they can handle heating oil. We believe that such terminals would likely

feel the need to have two loading bays at which marked heating oil could be delivered to a truck. 

Considering the added cost of a second injection station, the cost of new injection equipment

would be $60,000 for each of these terminals. Except for heating oil distributed from these

terminals, we project that the small quantities of fuel that are sold as heating oil outside of the

Northeast/Mid-Atlantic Area will often meet a 500 ppm sulfur specification.UU Therefore, we

expect that the other terminals outside of the Northeast/Mid-Atlantic Area will typically not need

to distribute marked heating oil. For the infrequent instances in where terminals do receive >500

ppm fuel that they wish to distribute as heating oil (rather than blending it down to meet a 500

ppm standard using 15 ppm diesel fuel) we except that the terminal operator will elect to add the

marker by hand, thereby avoiding the cost of installing new additive injection equipment. 

However, to provide a conservatively high estimated cost, we assumed that an additional 30
Final Regulatory Support Document

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terminals outside of the Northeast/Mid-Atlantic Area will install new equipment to allow the

injection of fuel marker at one truck loading bay (at $50,000 per terminal).

In analyzing the various situations as discussed above, we project that fewer than 60

terminals nationwide will choose to install injection equipment to add the marker to heating oil

at a total cost of $4,150,000. The total capital cost to refiners and terminals to install injection

equipment to add the marker to heating oil is estimated to be $5,650,000. Thus, the

Northeast/Mid-Atlantic Area provisions in this rule minimize the number of terminals that will

need to install additive injection equipment and its associated cost to comply with the fuel

marker requirements.

Because heating oil is being marked to prevent its use in NRLM engines, for the purposes of

estimating the impact of the marker requirement on the cost of the NRLM program we have

spread the cost of adding the marker to heating oil over NRLM diesel fuel. Amortizing the

capital costs of marker injection equipment over 20 years, results in an estimated cost of just

0.006 cents per gallon of affected NRLM diesel fuel supplied. Spreading the cost of the marker

for heating oil over the volume of affected NRLM fuel results in an estimated cost of 0.003

cents per gallon of affected NRLM fuel. Adding the amortized cost of the injection equipment

and the cost or the marker results in a total estimated cost of the marker requirement for heating

oil in this rule of 0.01 cents per gallon of affected NRLM fuel.

In addition to heating oil, 500 ppm L&M fuel produced at refineries must also be marked

from 2010 to 2012. As discussed in Section 7.2.2, we project that 6 refineries will produce this

fuel. These refineries will have to install equipment to mark the fuel, unless they already have

the equipment to mark heating oil. We assume that all 6 refineries will have to install new

equipment. We do not expect that 500 ppm L&M fuel will be distributed by common carrier

pipeline. Thus, it can be marked at the refinery and shipped to the final user by rail, truck or

barge already marked. Therefore, we expect that very few terminals will add marking equipment

exclusively for this fuel. To cover the few terminals that could do so, we have increased the

number of new marking installations to 15. At $60,000, the total capital cost is $900,000. The

cost of the marker is 0.03 cent per gallon of marked fuel. As described in Appendix 8B, we

estimate that 2.975 billion gallons of 500 ppm L&M fuel will be produced in 2011. Thus, the

cost of marking two years of 500 ppm L&M fuel production will be $1.875 million. Amortizing

the $900,000 capital cost over 2 years of 15 and 500 ppm NRLM fuel production at 7 percent

before taxes and adding in the marker costs yields a cost of 0.01 cents per gallon of NRLM fuel

over this two year period for the marker requirement for L&M diesel fuel.

EIA FOKS/AEO Nonroad Fuel Volume Scenario: 

Since using EIA nonroad fuel volumes rather than our primary fuel volume scenario (which

utilized the EPA NONROAD model for nonroad fuel consumption) does not affect our

assessment of product distribution patterns, our projections of the number of facilities that will

need to install new injection equipment is the same under both scenarios. However, there are

two factors that do have the potential to affect our per gallon cost estimate. The heating oil

volume under the EIA nonroad volume scenario is greater than that under our primary volume
Estimated Costs of Low-Sulfur Fuels

7-205

scenario and the NRLM volume is smaller than under our primary volume scenario. The greater

volume of heating oil under the EIA volume scenario means that it is likely that the volume of

heating oil marked would be larger relative to our primary scenario, and the volume of NRLM to

which this cost (and the capitol cost of the injection equipment) would be attributed would be

smaller. Both of these criteria directionally increase the per gallon marker costs under the EIA

volume scenario relative to our primary volume scenario. Because of these changes, the cost of

adding the marker increases to 0.02 cent per gallon of affected NRLM diesel fuel supplied. The

cost of marking L&M fuel stays at 0.01 cent per gallon from 2010-2012.

7.4.5 Distribution and Marker Costs Under Alternative Sulfur Control Options

EIA FOKS/AEO Nonroad Fuel Volume Scenario: 

The distribution and marker costs assuming a reduced volume of nonroad fuel demand,

resulting from deriving this demand from information in EIA’s FOKS and AEO 2003 reports are

summarized in Table 7.4-6 below. The derivation of each cost component was discussed in the

previous sub-sections of Section 7.4. 

TABLE 7.4-6 

DISTRIBUTION COSTS FOR EIA FOKS/AEO FUEL DEMAND SCENARIO (CENTS PER GALLON)

*

Cause of Increase in Distribution Costs

Time Period Over Which Costs Apply

2007-2010 2010-2014 After 2014

New Product Segregation as Bulk Plants 0.1 0.1 0.1

Distribution of Additional NRLM Volume to

Compensate for Reduction in Volumetric

Energy Content

0.08 0.1 0.1

Distillate Interface Handling 0 0.4 0.6

Heating Oil and L&M Fuel Marker 0.03 0.03 0.03

Total 0.2 0.6 0.8

* Costs have been rounded to one significant figure.

Other Fuel Control Options: The other fuel control options analyzed in this Final RIA are: 1)

500 ppm NRLM cap in 2007 with no subsequent control to 15 ppm, and 2) the proposed fuel

program of 500 ppm NRLM in 2007 and 15 ppm nonroad fuel in 2010. The distribution costs

for the 500 ppm NRLM only program are the same as those for the final NRLM fuel program in

2007. 
Final Regulatory Support Document

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Under the proposed fuel program, the distribution costs are essentially the same as those for

the final rule when the costs are spread over all NRLM fuel. However, when the costs of

distributing downgraded distillate are assigned to the only 15 ppm nonroad cap, as this is the

incremental step in fuel control which causes these costs, the cost per gallon is of higher. In this

case, the cost from 2010-2014 and in 2014 and beyond increase to 0.54 and 1.0 cent per gallon,

respectively. In this case, the cost assigned to L&M fuel of distributing downgraded distillate is

zero. 

7.5 Total Cost of Supplying NRLM Fuel Under the Two-Step Program

The estimated refining, additive, and distribution costs from Sections 7.2 - 7.4 for the final

NRLM fuel program and the other fuel control options considered are summarized in Table 7.5-

1. Estimated costs during the various phases of these programs are also shown. Note that these

fuel costs include the impacts of the small-refiner provisions. Also, in the case of the final

NRLM fuel program, we spread the downgrade distribution costs across all NRLM fuel from

2010-2012, even though L&M fuel is still at 500 ppm. We did so to avoid a higher apparent cost

of 15 ppm nonroad fuel from 2010-2012 than from 2012-2014. However, in the case of the

proposed NRLM fuel program, we assigned all of the downgrade distribution cost to nonroad

fuel, since the long term standard for L&M fuel is 500 ppm in this scenario. These cost

estimates do not include the costs associated with testing, labeling, reporting, and recordkeeping

to satisfy the compliance assurance provisions of the final rule, but these costs are small enought

such that they would not change the values in Table 7.5-1 due to round-off.
Estimated Costs of Low-Sulfur Fuels

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Table 7.5-1

Summary of Fuel Costs for NRLM Fuel Control Options (cents per gallon, $2002)

Option Specification Year Refining

Costs

(c/gal)

Distribution &

Additive Costs

(c/gal)

Total

Costs

(c/gal)

Final Rule 500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm NRLM 2010-12 2.7 0.6 3.3

500 ppm NRLM 2012-14 2.9 0.6 3.5

15 ppm Nonroad 2010-12 5.0 0.8 5.8

15 ppm NRLM 2012-14 5.6 0.8 6.4

15 ppm NRLM 2014+ 5.8 1.2 7.0

Proposed NRLM

Program: 500 ppm

NRLM in 2007, 15 ppm

Nonroad in 2010

500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm L & M 2010-14 2.7 0.2 2.9

500 ppm L & M 2014+ 2.7 0.2 2.9

15 ppm Nonroad 2010-14 5.0 1.0 6.0

15 ppm Nonroad 2014+ 5.2 1.4 6.6

500 ppm NRLM in 2007

only (no 15 ppm fuel

control)

500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm NRLM 2010+ 2.0 0.2 2.2

Final Rule with NRLM

Volume Derived from

EIA FOKS/AEO

Reports

500 ppm NRLM 2007-10 1.9 0.2 2.1

500 ppm NRLM 2010-12 2.8 0.6 3.4

500 ppm NRLM 2012-14 3.0 0.6 3.6

15 ppm Nonroad 2010-12 5.0 0.8 5.8

15 ppm NRLM 2012-14 5.6 0.8 6.4

15 ppm NRLM 2014+ 5.7 1.2 6.9
Final Regulatory Support Document

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Our projected total cost for supplying 500 ppm fuel is slightly less than the historical price

differential between 500 ppm highway diesel fuel and uncontrolled high-sulfur diesel fuel. This

differential has averaged about 2.5 cents per gallon for the five-year period from 1995 to 1999. 

Market prices may be either higher or lower than the societal costs estimated here as discussed in

the next section. Thus, such comparisons can only be considered approximate. The primary

reason that our projected costs for 500 ppm NRLM fuel might be lower than those for highway

fuel is the ability to use existing hydrotreaters which are no longer being used to produce 500

ppm highway fuel in the 2007-2010 timeframe. 

7.6 Potential Fuel Price Impacts

Transportation fuel prices are dependent on a wide range of factors, such as world crude oil

prices, economic activity at the national level, seasonal demand fluctuations, refinery capacity

utilization levels, processing costs (including fuel-quality specifications), and the cost of

alternative energy sources (e.g., coal, natural gas). Only a few of these factors, namely fuel

processing costs and refinery capacity utilization, may be affected by the NRLM fuel program.

Fuel processing and distribution costs will clearly be affected due to the cost of desulfurizing

NRLM diesel fuel to either the 500 or 15 ppm sulfur cap. Refinery utilization levels may be

affected as the capacity to produce 500 ppm or 15 ppm NRLM diesel fuel will depend on

refiners’ investment in desulfurization capacity. The potential impact of increased fuel

processing and distribution costs on the prices is assessed below. The impact of the NRLM fuel

program on refinery utilization levels is beyond the scope of this analysis. In the long run,

refiners will clearly invest to produce adequate volumes of NRLM diesel fuels, as well as other

distillate fuels. In the shorter term, the issue of refiners’ adequate investment in desulfurization

capacity is addressed in Section 5.9.

Two approaches to projecting future price impacts are evaluated here. The most direct

approach to estimating the impact of the NRLM fuel program on prices is to observe the price

premiums commanded by similar products in the marketplace. This is feasible for 500 ppm

NRLM diesel fuel, as both 500 ppm highway diesel fuel and high-sulfur diesel fuel are both

marketed today. As discussed in Section 7.2.2 above, the historical price premium of 500 ppm

highway diesel fuel is 2.5 cents per gallon over that of high-sulfur distillate. As this premium is

almost identical to our projected average total cost of the supplying 500 ppm NRLM diesel fuel,

it represents one reasonable estimate of the future price impact of the 500 ppm NRLM diesel fuel

standard. 

It is not possible to use this methodology to project the price impact of the 15 ppm nonroad

diesel fuel cap. Only a very limited amount of diesel fuel meeting a 15 ppm sulfur cap is

currently marketed in the United States. This fuel is designed to be used in vehicle fleets

retrofitted with particulate traps. The fuel is produced in very limited quantities using equipment

designed to meet the current EPA and California highway diesel fuel standards. It is also much

more costly to distribute due to its extremely low volume. Thus, the current market prices for 15

ppm diesel fuel in the United States are not at all representative of what might be expected in

2010 and 2012 under the NRLM program.
Estimated Costs of Low-Sulfur Fuels

7-209

A greater volume, though still not large quantities, of 10 ppm sulfur diesel fuel is currently

being sold in Europe. The great majority of this fuel is Swedish Class 1 (so-called City) diesel

fuel, which is effectively a number one diesel fuel with very low aromatic content. The low

aromatic specification significantly affects the cost of producing this fuel. Also, this fuel is

generally produced using equipment not originally designed to produce 10 to 15 ppm sulfur fuel. 

Thus, as in the United States, the prices paid for this fuel are not representative of what will

occur in the United States in 2010 and 2012. We therefore did not attempt to use current fuels,

which have sulfur levels similar to the standards in this final rule, to evaluate our cost estimate

for meeting the 15 ppm standard. 

The other approach to project potential price impacts utilizes the projected costs to meet the

500 ppm and 15 ppm NRLM fuel sulfur caps. Both sulfur caps will affect fuel processing and

distribution costs across the nation. (The exception will be California, where we presume that

sulfur caps at least as stringent as those in this final rule will already be in effect.) However,

these costs appear to vary significantly from region to region. Because of the cost of fuel

distribution and limited pipeline capacities (pipelines are the most efficient means of transporting

fuel), the NRLM fuel markets (and those for other transportation fuels) are actually regional in

nature. Price differences can and usually do exist between the various regions of the country. 

Because of this, we have performed our assessment of potential price impacts on a regional

basis. For the regions in our analysis, we have chosen PADDs. Practically speaking, there are

probably more than five fuel markets in the United States with distinct prices. However,

analyzing five distinct refining regions appears to provide a reasonable range of price impacts

without adding precision that significantly exceeds our ability to project costs.

We made one exception to the PADD structure. PADD 3 (the Gulf Coast) supplies more

high-sulfur distillate to PADD 1, particularly the Northeast, than is produced by PADD 1

refineries. Two large pipelines connect PADD 3 refineries to the Northeast, the Colonial and the

Plantation. Because of this low-cost transportation connection, prices between the two PADDs

are closely linked. We therefore combined our price analysis for PADDs 1 and 3.

As mentioned above, it is very difficult to predict fuel prices, either in the short term or long

term. Over the past three years, transportation fuel prices (before excise taxes) have varied by a

factor of two. Therefore, we have avoided any attempt to project absolute fuel prices. Because

of the wide swings in absolute fuel prices, it is very difficult to assess the impact of individual

factors on fuel price. The one exception is the price of crude oil, for two reasons. One, the cost

of crude oil is the dominant factor in the overall cost of producing transportation fuels. Two, the

pricing of almost all crude oils is tied to the “world” market price of crude oil. While the cost of

producing crude oil in each region of the world is independent of those of other crude oil,

contract prices are tied to crude oils traded on the open market, such as West Texas Intermediate

and North Sea Brent crude oils. Thus, as the price of world crude oil climbs, the price of

gasoline and diesel fuel climb across the United States, and vice versa. There is also a very

rough correlation between refinery capacity utilization levels and fuel price. However, an

unusually high availability of imports can cause prices to be relatively low despite high refinery

capacity utilization rates in the United States.
Final Regulatory Support Document

VV Theoretically, some refiners might recover all their invested capital if their operating costs were sufficiently

lower than those of the high cost refiner. However, practically, in the case of desulfurizing NRLM diesel fuel, this is

highly unlikely.

7-210

For example, fuel prices, as a function of crude oil price, have varied widely over the past

decade. Refiner records supplied to EIA indicate that refiners’ net refining margin has ranged

from a low of $0.45 per barrel in 1992 to a high of 2.78 per barrel in 2001.59 Thus, fuel prices

have varied between being so low that refineries are barely covering their cash expenses to high

enough to justify moderate cost increases in refining capacity (but not new refineries). The

NRLM program will very unlikely have a major impact on factors such as these. Thus,

projecting the likely price impact of the NRLM program is highly speculative. The best that can

be done is to develop a wide range of potential price impacts indicative of the types of conditions

that have existed in the past.

In order to do this, we developed three projections for the potential impact of the NRLM

program on fuel prices. The lower end of the range assumes a very competitive NRLM fuel

market with excess refining capacity. In this case, fuel prices within a PADD are generally low

and reflect only incremental operating costs. Consistent with this assumption, we project that the

price of NRLM diesel fuel within a PADD will increase by the operating cost of the refinery

with the highest operating cost in that PADD. This assumes that the refinery facing the highest

operating cost in producing NRLM diesel fuel is setting the price of NRLM diesel fuel before

this rule. This may or may not be the case. If not, the price increase may be even lower than that

projected below. Under this “low -cost” set of assumptions, the refiner with the highest

operating cost will not recover any of his invested capital related to desulfurizing NRLM diesel

fuel, but all other refiners will recover some of their investment.VV Note that this scenario is only

viable in the short run, since refineries need to recover both operating and fixed costs in the long

run.

The mid-range estimate of price impacts can be termed the “full-cost” scenario. It assumes

that prices within a PADD increase by the average refining and distribution cost within that

PADD, including full recovery of capital (at the societal rate of return of 7 percent per annum

before taxes). This scenario represents a case where there is full cost pass through to consumers

under a competitive market setting. It should be noted that there are instances when this full-cost

scenario produces lower costs than the maximum operating cost scenario. This occurs when the

bulk of the low sulfur fuel can be produced at a relatively low cost compared to a few refineries

facing relatively high operating costs. 

Under this full-cost price scenario, lower cost refiners will recover their capital investment

plus economic profit, while those with higher than average costs will recover some of their

invested capital, but not all of it (i.e., at a rate of return lower than 7 percent annually).

The high-end estimate of price impacts assumes a NRLM fuel market that is constrained with

respect to fuel production capacity. Prices rise to the point necessary to encourage additional

desulfurization capacity. Also, prices are assumed to remain at this level in the long term,

meaning that any additional desulfurization capacity barely fulfills demand and does not create
Estimated Costs of Low-Sulfur Fuels

7-211

an excess in capacity that would tend to reduce prices. However, prices should not increase

beyond this level in the long run, as this would encourage the construction of additional

desulfurization capacity, lowering prices. Consistent with this, prices within a PADD increase

by the maximum total refining and distribution cost of any refinery within that PADD, including

full recovery of capital (at 7 percent per annum before taxes). All other refiners will recover

more than their capital investment.

Table 7.6-1 presents the refining costs for the four phases of the NRLM fuel program under

the three potential price scenarios.

Table 7.6-1

NRLM Fuel Refining Costs by Region (cents per gallon)

Maximum Operating Cost Average Total Cost Maximum Total Cost

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2007-2010)

PADDs 1 and 3 2.7 1.6 4.3

PADD 2 2.8 2.8 3.6

PADD 4 3.5 3.3 5.9

PADD 5 1.0 1.3 1.3

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2010-2012)

PADDs 1 and 3 2.3 3.7 5.0

PADD 2 2.9 2.9 3.8

PADD 4 3.9 8.9 8.9

PADD 5 1.6 2.8 2.9

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2012-2014)

PADDs 1 and 3 2.7 2.5 5.9

PADD 2 2.7 3.7 5.7

PADD 4 3.9 9.0 9.0

PADD 5 2.2 3.5 4.2

15 ppm Sulfur Cap: NRLM Fuel (2010-2012

PADDs 1 and 3 4.7 4.6 8.5 

PADD 2 5.0 7.1 8.5

PADD 4 7.1 11.6 12.7

PADD 5 3.6 4.3 4.3

15 ppm Sulfur Cap: NRLM Fuel (2012-2014)

PADDs 1 and 3 4.8 4.8 8.6 

PADD 2 6.4 7.8 10.0

PADD 4 7.0 11.7 12.7

PADD 5 3.6 4.3 4.3

15 ppm Sulfur Cap: NRLM Fuel (fully implemented program: 2014 +)

PADDs 1 and 3 6.5 5.1 8.6

PADD 2 6.4 7.8 10.0

PADD 4 7.0 11.8 12.7

PADD 5 3.9 5.6 6.0
Final Regulatory Support Document

7-212

Table 7.6-2 shows these same cost projections including distribution and lubricity additive

costs. The wholesale price of high-sulfur distillate fuel has varied widely even over the past

twelve months. The March 2003 heating oil futures price alone has ranged from 60-110 cents

per gallon since early 2002. Assuming a base cost of NRLM fuel of one dollar per gallon, the

increase in NRLM fuel prices will be equivalent to the price increase in terms of cents per gallon

shown below.

Table 7.6-2

Range of Possible Total Diesel Fuel Price Increases (cents per gallon)a

Maximum Operating Cost Average Total Cost Maximum Total Cost

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2007-2010)

PADDs 1 and 3 2.9 1.8 4.5

PADD 2 3.0 2.5 3.8

PADD 4 3.7 3.5 6.1

PADD 5 1.2 1.5 1.5

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2010-2012)

PADDs 1 and 3 2.9 4.3 5.6

PADD 2 3.5 3.5 4.4

PADD 4 4.5 9.5 9.5

PADD 5 2.2 3.4 3.5

500 ppm Sulfur Cap: Nonroad, Locomotive and Marine Diesel Fuel (2012-2014)

PADDs 1 and 3 3.3 3.1 6.5

PADD 2 3.3 4.3 6.3

PADD 4 4.5 9.6 9.6

PADD 5 2.8 4.1 4.8

15 ppm Sulfur Cap: NRLM Fuel (2010-2012

PADDs 1 and 3 5.5 5.4 9.3 

PADD 2 5.8 6.8 9.3

PADD 4 7.9 12.4 13.5

PADD 5 4.4 5.1 5.1

15 ppm Sulfur Cap: NRLM Fuel (2012-2014)

PADDs 1 and 3 5.6 5.6 9.4 

PADD 2 7.2 8.5 10.8

PADD 4 7.8 12.5 13.5

PADD 5 4.4 5.1 5.1

15 ppm Sulfur Cap: NRLM Fuel (fully implemented program: 2014 +)

PADDs 1 and 3 7.7 6.3 9.8

PADD 2 7.6 7.9 11.2

PADD 4 8.2 13.0 13.9

PADD 5 5.1 6.8 7.2

Notes: a

 At a wholesale price of approximately $1.00 per gallon, these values also represent the percentage

increase in diesel fuel price.
Estimated Costs of Low-Sulfur Fuels

WW “Potential Impacts of Environmental Regulations on Diesel Fuel Prices,” NERA, for AAM, December

2000.

7-213

There are a number of assumptions inherent in these price projections. First, both the lower

and upper limits of the projected price impacts described above assume that the refinery facing

the highest compliance costs is currently the price setter in their market. If this is not the case,

the price impacts would be lower than those shown in the previous tables. Many factors affect a

refinery’s total costs of fuel production. Most of these factors, such as crude oil cost, labor costs,

age of equipment, etc., are not considered in projecting the incremental costs associated with

lower NRLM diesel fuel sulfur levels. Thus, current prices may very well be set in any specific

market by a refinery facing lower incremental compliance costs than other refineries. This point

was highlighted in a study by the National Economic Research Associates (NERA) for AAM of

the potential price impacts of EPA’s 2007 highway diesel fuel program.WW In that study, NERA

criticized the above referenced study performed by Charles River Associates, et. al. for API,

which projected that prices will increase nationwide to reflect the total cost faced by the U.S.

refinery with the maximum total compliance cost of all the refineries in the U.S. producing

highway diesel fuel. To reflect the potential that the refinery with the highest projected

compliance costs under the maximum price scenario is not the current price setter, we included

the mid-point price impacts above. It is possible that even the lower limit price impacts are too

high, if the conditions exist where prices are set based on operating costs alone. However, these

price impacts are sufficiently low that considering even lower price impacts was not considered

critical to estimating the potential economic impact of this rule. 

Second, we assumed in some cases that a single refinery’s costs could affect fuel prices

throughout an entire PADD. While this is a definite improvement over analyses which assume

that a single refinery’s costs could affect fuel prices throughout the entire nation, it is still

conservative, since one refinery’s fuel can rarely have such a widespread influence. For

example, Chicago and Detroit have experienced unusually high gasoline prices at times over the

past 4 years, but prices in St. Louis, Cincinnati, Minneapolis, etc. were not similarly affected. 

High cost refineries are more likely to have a more limited geographical impact on market

pricing than an entire PADD. In many cases, high cost refiners are able to operate profitably

because they are in a niche location where transportation costs limit competition.

Third, by focusing solely on the cost of desulfurizing NRLM diesel fuel, we assume that the

production of NRLM diesel fuel is independent of the production of other refining products,

such as gasoline, jet fuel and highway diesel fuel. However, this is clearly not the case. Refiners

have some flexibility to increase the production of one product without significantly affecting

the others, but this flexibility is quite limited. It is possible that the relative economics of

producing other products could influence a refiner’s decision to increase or decrease the

production of NRLM diesel fuel under the fuel program in this rule. It is this price response that

causes fuel supply to match fuel demand. And, this response in turn could increase or decrease

the price impact relative to those projected above. 
Final Regulatory Support Document

XX “Cost of Diesel Fuel Desulfurization In Asian Refineries,” Estrada International Ltd., for the Asian

Development Bank, December 17, 2002.

7-214

Fourth, all three of the above price projections are based on the projected cost for U.S.

refineries of meeting the NRLM fuel sulfur caps. Thus, these price projections assume that

imports of NRLM fuel, which are currently significant in the Northeast, are available at roughly

the same cost as those for U.S. refineries in PADDs 1 and 3. We have not performed any

analysis of the cost of lower sulfur caps on diesel fuel produced by foreign refiners. However,

there are reasons to believe that imports of 500 and 15 ppm NRLM diesel fuel will be available

at prices in the ranges of those projected for U.S. refiners. 

One recent study analyzed the relative cost of lower sulfur caps for Asian refiners relative to

those in the U.S., Europe and Japan.XX It concluded that costs for Asian refiners will be

comparatively higher, due to the lack of current hydrotreating capacity at Asian refineries. This

conclusion is certainly valid when evaluating lower sulfur levels for highway diesel fuels which

are already at low levels in the U.S., Europe and Japan and for which refineries in these areas

have already invested in hydrotreating capacity. It appears to be less valid when assessing the

relative cost of meeting lower sulfur standards for NRLM fuels and heating oils which are

currently at much higher sulfur levels in the U.S., Europe and Japan. All refineries face

additional investments to remove sulfur from these fuels and so face roughly comparable control

costs on a per gallon basis. 

One factor arguing for competitively priced imports is the fact that refinery utilization rates

are currently higher in the U.S. and Europe than in the rest of the world. The primary issue is

whether overseas refiners will invest to meet tight sulfur standards for U.S., European and

Japanese markets. Many overseas refiners will not invest, instead focusing on local, higher

sulfur markets. However, many overseas refiners focus on exports. Both Europe and the U.S.

are moving towards highway and nonroad diesel fuel sulfur caps in the 10-15 ppm range. 

Europe is currently and projected to continue to need to import large volumes of highway diesel

fuel. Thus, it seems reasonable to expect that a number of overseas refiners will invest in the

capacity to produce some or all of their diesel fuel at these levels. Many overseas refiners also

have the flexibility to produce 10-15 ppm diesel fuel from their cleanest blendstocks, as most of

their available markets have less stringent sulfur standards. Thus, there are reasons to believe

that some capacity to produce 10-15 ppm diesel fuel will be available overseas at competitive

prices. If these refineries were operating well below capacity, they might be willing to supply

complying product at prices which only reflect incremental operating costs. This could hold

prices down in areas where importing fuel is economical. However, it is unlikely that these

refiners could supply sufficient volumes to hold prices down nationwide. Despite this

expectation, to be conservative, in the refining cost analysis conducted earlier in this chapter, we

assumed no imports of 500 ppm or 15 ppm NRLM diesel fuel. All 500 ppm and 15 ppm NRLM

fuel was produced by domestic refineries. This raised the average and maximum costs of 500

ppm and 15 ppm NRLM diesel fuel and increased the potential price impacts projected above

beyond what would have been projected had we projected that 5-10 percent of NRLM diesel fuel

will be imported at competitive prices. 
Estimated Costs of Low-Sulfur Fuels

7-215
Final Regulatory Support Document

7-216

1. Fuel Oil and Kerosene Sales 2001, Energy Information Administration, Office of Oil and Gas,

November 2002.

2. NESCAUM, Characterization of Construction Equipment Activity, Assistance Agreement No.

X-991575-01, unpublished draft data. 

3. Office of Highway Information Management, A Guide to Reporting Highway Statistics,

Federal Highway Administration, U.S. Department of Transportation, 1997.

4. Personal communication with Ralph Erickson, Office of Highway Policy Information, Federal

Highway Administration, U.S. Department of Transportation, August 2001.

5. Personal communication with Dan Walzer, Energy Information Administration, September

2001. 

6. Personal communication with Dan Walzer, Energy Information Administration, September

2001. 

7. Personal communication with Mark Stehly, Assistant Vice President Environmental,

Burlington Northern Santa Fe Railroad, September 2001.

8. Personal communication with Dan Walzer, Energy Information Administration, September

2001. 

9. Petroleum Marketing Annual 2001, Energy Information Administration, Office of Oil and

Gas, September 2002.

10. U.S. Petroleum Refining: Assuring the Adequacy and Affordability of Cleaner Fuels,

National Petroleum Council Committee on Refining, June 2000.

11. Confidential discussion with pipeline companies, October 2003.

12. Annual Energy Outlook 2003, Energy Information Administration, Office of Integrated

Analysis and Forecasting, January 2003.

13. “Summary and Analysis of the Highway Diesel Fuel 2003 Pre-compliance Reports”, EPA

420-R-03-103, October 2003.

14. Johnson, Jeff, Boeing Company, “Sulfur in Jet Fuel,” Presentation to the Sulfur Workshop,

QinetiQ and Farnborough, September 2 & 3, 2002. 

15. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” EPA420-R-00-026, December 2000, Docket A-2001-

28, Document No. II-A-01.

Chapter 7 References
Estimated Costs of Low-Sulfur Fuels

7-217

16.Confidential Information Submission from Diesel Desulfurization Vendor A, August 1999. 

17.UOP Information Submission to the National Petroleum Council, August 1999.

18.“The Lower it Goes, The Tougher it Gets,” Bjorklund, Bradford L., UOP, Presentation at the

National Petroleum Council Annual Meeting, March 2000.

19.U.S. Petroleum Refining Draft Report, Appendix H, National Petroleum Council, March 30,

2000.

20. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” EPA420-R-00-026, December 2000, Docket A-2001-

28, Document No. II-A-01.

21. Chemical Engineering Plant Cost Index, Chemical Engineering, February 2003.

22. Interpolation of the hydrogen consumption from the desulfurization data by Vendors A and

B.

23.Conversation with Jim Kennedy, Manager Project Sales, Distillate and Resid Technologies,

UOP, November 2000.

24.Conversation with Tim Heckel, Manager of Distillate Technologies Sales, UOP, March 2000.

25.Conversation with Tom W. Tippett et al, Refining Technology Division, Haldor Topsoe,

March 2000.

26.Very-Low-Sulfur Diesel Distribution Cost, Engine Manufacturers Association, August 1999.

27.Moncrief, T. I., Mongomery, W. D., Ross, M.T., Charles River Associates, Ory, R. E.,

Carney, J. T., Baker and O’Brien Inc., Ann Assessment of the Potential Impacts of Proposed

Environmental Regulations on U.S. Refinery Supply of Diesel Fuel, Charles River and Baker

and O’Brien for the American Petroleum Institute, August 2000.

28. Christie, David A., Advanced Controls Improve Reformulated Fuel Yield and Quality, Fuel

Reformulation, July/August 1993.

29. Personal conversation with Debbie Pack, ABB Process Analytics Inc., November 1998.

30. Ackerson, Michael; Skeds, Jon, Presentation to the Clean Diesel Independent Review Panel,

Process Dynamics and Linde Process Plants, July 30, 2002.

31. Conversation with Jon Skeds, Director of Refining, Linde BOC Process Plants, August 26,

2003. 

32.Conversation with Jon Skeds of Linde Process Plants at the 2002 National Petrochemical and

Refiners Association Question and Answer Meeting, October, 2002.
Final Regulatory Support Document

7-218

33.American Automobile Manufacturers Association Diesel Fuel Survey, Summer 1997.

34.Conversation with Cal Hodge, A Second Opinion, February 2000.

35. EIA Petroleum Supply Annual, 2002, excluding California refineries.

36..Energy Information Agency 2003 Annual Energy Outlook, Table PSA17.

37.Gary, James H., Handwerk, Glenn E., Petroleum Refining: Technology and Economics,

Marcel Dekker, New York (1994).

38.Conversation with Lyondel-Citgo refinery staff, April 2000.

39.Gary, James H., Handwerk, Glenn E., Petroleum Refining: Technology and Economics,

Marcel Dekker, New York (1994).

40.Peters, Max S., Timmerhaus, Klaus D., Plant Design and Economics for Chemical Engineers,

Third Edition, McGraw Hill Book Company, 1980.

41.Waguespack, Kevin, Review of DOE/Ensys Reformulated Diesel Study-Draft for Discussion,

Price-Waterhouse Coopers for the American Automobile Manufacturers, October 5, 2000.

42.U.S. Petroleum Refining, Meeting Requirements for Cleaner Fuels and Refineries, Volume V

- Refining Capability Appendix, National Petroleum Council, 1993.

43.Waguespack, Kevin, Review of DOE/Ensys Reformulated Diesel Study-Draft for Discussion,

Price-Waterhouse Coopers for the American Automobile Manufacturers, October 5, 2000.

44.Hadder, Gerry and Tallet, Martin; Documentation for the Oak Ridge National Laboratory

Refinery Yield Refinery Model (ORNL-RYM), 2001. 

45.Perry, Robert H., Chilton, Cecil H., Chemical Engineer’s Handbook, McGraw Hill 1973.

46. Hydrogen and Utility Supply Optimization, Shahani, Gouton et al, Technical Paper by Air

Products presented at the National Petrochemical and Refiners Assoc. 1998 Annual Meeting

(AM-98-60).

47.1999 Worldwide Refining Survey, Oil and Gas Journal, December 20, 1999.

48.Peters, Max S., Timmerhaus, Klaus D., Plant Design and Economics for Chemical Engineers,

Third Edition, McGraw Hill Book Company, 1980.

49.Jena, Rabi, Take the PC-Based Approach to Process Control, Fuel Reformulation,

November/December 1995.

50.Sutton, I.S., Integrated Management Systems Improve Plant Reliability, Hydrocarbon

Processing, January 1995.
Estimated Costs of Low-Sulfur Fuels

7-219

51.King, M. J., Evans, H. N., Assessing your Competitors’ Application of CIM/CIP,

Hydrocarbon Processing, July 1993.

52.U. S. Petroleum Refining, Assuring the Adequacy and Affordability of Cleaner Fuels, A

Report by the National Petroleum Council, June 2000.

53. “Refining Economics of Diesel Fuel Sulfur Standards,” study performed for the Engine

Manufacturers Association by MathPro, Inc. October 5, 1999.

54. “Refining Economics of Diesel Fuel Sulfur Standards, Supplemental Analysis of 15 ppm

Sulfur Cap,” study performed for the Engine Manufacturers Association by Mathpro Inc.,

August 16, 2000.

55. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” Section V.C.4, EPA420-R-00-026, December 2000,

Docket A-2001-28, Document No. II-A-01.

56. Phone conversation in mid-2002 with Massey’s Truck and Tank Repair, Pheonix Arizona.

57. “Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway

Diesel Fuel Sulfur Control Requirements,” EPA420-R-00-026, December 2000, Docket A-2001-

28, Document No. II-A-01.

58. Letter from Titan Industries Inc. to Jeff Herzog, EPA, November 21, 2003. Phone

conversation with Ron Wilson, Lubrizol Additive Injection Equipment, November 21, 2003

59. The Impact of Environmental Compliance Costs on U.S. Refining Profitability 1995-2001,

Table A2, Energy Information Administration, May 16, 2003.
CHAPTER 8: Estimated Aggregate Cost and Cost per Ton of Reduced Emissions

8.1 Projected Sales and Cost Allocations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-2

8.2 Aggregate Engine Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-3

8.2.1 Aggregate Engine Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-3

8.2.2 Aggregate Engine Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-7

8.3 Aggregate Equipment Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

8.3.1 Aggregate Equipment Fixed Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-11

8.3.2 Aggregate Equipment Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-13

8.4 Aggregate Fuel Costs and Other Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-15

8.4.1 Aggregate Fuel Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-16

8.4.2 Aggregate Oil-Change Maintenance Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18

8.4.3 Aggregate CDPF Maintenance, CDPF Regeneration, and CCV Maintenance Costs

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-20

8.4.4 Summary of Aggregate Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-22

8.4.5 Summary of Aggregate Operating Costs Associated with a Fuel-only Scenario 8-24

8.5 Summary of Aggregate Costs of the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-26

8.6 Emission Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-29

8.7 Cost per Ton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-30

8.7.1 Cost per Ton for the NRT4 Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-30

8.7.2 Cost per Ton for the NRLM Fuel-only Scenario . . . . . . . . . . . . . . . . . . . . . . . . 8-34

8.7.3 Costs and Costs per Ton for Other Control Scenarios . . . . . . . . . . . . . . . . . . . . 8-37

8.7.3.1 Costs and Costs per Ton of a 500 ppm NRLM Fuel-only Scenario . . . . . 8-37

8.7.3.2 Costs and Costs per Ton of the 15 ppm L&M Fuel Increment . . . . . . . . . 8-42

8.7.4 Costs per Ton Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-63

Appendix 8A: Estimated Aggregate Cost and Cost per Ton of Sensitivity Analyses . . . . . . . 8-65

Appendix 8B: Fuel Volumes used throughout Chapter 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-89
Aggregate Cost and Cost per Ton

8-1

CHAPTER 8: Estimated Aggregate Cost and Cost per Ton

of Reduced Emissions

This chapter aggregates the estimated incremental engine costs, operating costs, equipment

costs, and fuel costs of the final rule. This chapter also presents detailed information on the

calculation for the cost per ton of pollutant. Chapter 6 details the estimated fixed and variable

costs for modifying new nonroad engines and equipment to meet new emission standards;

Chapter 6 also discusses the effects of the new low-sulfur diesel fuels on operating costs for

land-based nonroad diesel engines, locomotive engines, and marine diesel engines. Chapter 7

describes our estimates of the costs associated with the fuel requirements in this final rule.

We have calculated the cost per ton of emission reductions for this final rule based on the net

present value of all costs incurred and all emission reductions generated over a 30-year time

window after the program takes effect. This approach captures all the costs and emission

reductions from the final rule, including those costs incurred and emission reductions generated

by the existing fleet. The point of comparison for this evaluation is the existing set of fuel and

engine standards (i.e., unregulated fuel and the Tier 2/Tier 3 program). The 30-year time

window is meant to capture both the early period of the program when there are a small number

of compliant engines in the fleet, and the later period when there is nearly complete turnover to

compliant engines. Note that all costs and emission reductions presented here are 30-year

numbers (the net present values in 2004 of the stream of costs/reductions occurring from 2007

through 2036, expressed in $2002).

While there is a broad consensus among economists that future benefits and costs of

regulatory programs should be discounted, there is no consensus in the literature regarding the

most appropriate discounting concept and rate to apply. In particular, the theoretical literature is

divided between two alternative approaches. The first approach is referred to as the “demandside approach” (see Arrow et al, 1996), which defines the appropriate discount rate as the rate at

which society would collectively trade off current versus future consumption. This rate is

difficult to establish empirically, but estimates in the literature commonly range from 1 to 4

percent. EPA’s economic Guidelines suggest using a value of two to three percent.1

 The second

approach is referred to as the “cost-side approach” (see Lind, 1982), and discount rates

associated with this concept reflect trade-offs between current and future consumption derived

by market rates driven by the marginal productivity of capital. This rate is also difficult to derive

from empirical data, but estimates typically fall in the range of 4 to 10 percent. OMB’s circular

A-94 expresses a preference for the cost-side approach and specifies a seven percent rate.

Given both the lack of consensus in the literature on the most appropriate concept and the

uncertainty surrounding the associated empirical estimates, EPA’s Economic Guidelines and the

two key outside expert groups which advise EPA on economic analytical issues all recommend

evaluating benefits and costs using a range of discount rates. Consistent with this advice, we

have analyzed the benefits and costs of the nonroad Tier 4 rule using both a three percent rate
Final Regulatory Impact Analysis

A A CDPF is a catalyzed diesel particulate filter; a DOC is a diesel oxidation catalyst; CCV is a closed crankcase

ventilation system; Regen is short for regeneration; EGR is exhaust gas recirculation; NRLM refers to nonroad,

locomotive, and marine.

8-2

and a seven percent rate. We present the results based on a three percent discount rate as our

primary estimates.

8.1 Projected Sales and Cost Allocations

Projected nonroad engine and equipment sales estimates are used in several portions of this

analysis. We have used two sources for our projected sales numbers—the PSR database for the

2000 model year, and our Nonroad Model.2, 3 The PSR database has been used as the basis for

our current fleet mix; i.e., which equipment types were sold in 2000 and with engines from

which power category. The sales estimates and growth rates used throughout this analysis are

shown in Table 8.1-1.4

Table 8.1-1

Estimated 2000 Engine Sales and Future Sales Growth

Power range 2000 Model Year

Sales

Annual Growth in

Engines Sold

Linear Growth Rate

0<hp<25 119,159 4,116 3.5%

25#hp<50 132,981 3,505 2.6%

50#hp<75 93,914 2,046 2.2%

75#hp<100 68,665 1,499 2.2%

100#hp<175 112,340 2,321 2.1%

175#hp<300 61,851 1,414 2.3%

300#hp<600 34,095 436 1.3%

600#hp#750 2,752 50 1.8%

hp>750 2,785 51 1.8%

Total 628,542 15,438 2.5%

Because the new emission standards will reduce emissions of several different pollutants

(i.e., NOx, PM, NMHC, and SOx), we have attempted to allocate the estimated costs to emission

reductions of specific pollutants. This apportionment of costs by pollutant allows us to calculate

the average cost per ton of emission reduction resulting from this rule. Table 8.1-2 summarizes

the allocations we have used in the final rule. Deciding how to apportion costs can be difficult

even in the case of technologies that, on the surface, seem to have an obvious split by which their

costs should be attributed. For instance, we have apportioned 100 percent of the cost for CDPF

technology to PM even though CDPFs are expected to reduce NMHC emissions significantly.A

For fuel-related costs where no technology enablement occurs (i.e., fuel-derived emissions
Aggregate Cost and Cost per Ton

B A 50/50 split between PM/SOx could be argued, but that seems inappropriate given that 98 percent of fuel borne

sulfur is exhausted as SOx and only two percent is exhausted as PM. Given that, a 2/98 split between PM/SOx could be

argued, but that seems inappropriate given the importance of PM reductions—which have much higher human health

benefits—relative to SOx reductions. The 33/67 split between PM/SOx that we have chosen here seems to provide an

appropriate balance.

C We have estimated a “recovered” cost for all engine and equipment fixed costs to present a per-production-unit

analysis of the cost of the final rule (see Section 6.4.3 or Chapter 10 for our estimate of engine costs on a per-unit basis). 

In general, in environmental economics, it is more conventional to simply count the total costs of the program (i.e.,

opportunity costs) in the year they occur. However, this approach does not directly estimate a per-unit cost, since fixed

costs occur before the standards take effect, resulting in costs that do not correspond to units certified to the new emission

standards. As a result, we grow fixed costs until they can be “recovered” on complying units. Note that the approach

used here results in a higher estimate of the total costs of the program, since the recovered costs include a seven percent

interest rate to reflect the time value of money (i.e., the lost opportunity cost of that capital).

8-3

reductions where no new engine standards exist that rely on the new fuel), we have apportioned

one-third of the costs to PM and two-thirds to SOx. This is different than how we allocated costs

in the proposal where we allocated 100 percent of such costs to SOx control. We believe the

allocation used here is more appropriate given that the lower sulfur fuel provides for substantial

PM reductions even without new engine standards.B The estimated costs for 15 ppm fuel are

apportioned one-half to technology enablement (i.e., engine-derived emissions reductions) and

one-half to fuel-derived emissions reductions. Respectively, these halves are allocated 50%/50%

to NOx+NMHC/PM and 33%/67% to PM/SOx. This latter split is consistent with the fuelderived allocation described above. This is different than the proposal where we allocated 15

ppm costs entirely to technology enablement. We believe the allocations used here in the final

rule are more appropriate given the substantial PM and SOx reductions that occur solely because

the fuel sulfur level has been reduced. We note throughout the discussion to which pollutant we

have attributed costs.

8.2 Aggregate Engine Costs

This section presents aggregate engine fixed costs (recovered costs) and variable costs. 

These costs are discussed in detail in Section 6.2.

8.2.1 Aggregate Engine Fixed Costs

Chapter 6 presents the aggregate engine fixed costs, along with our best estimate of how

those costs might be recovered (i.e., on which engines), for engine R&D, tooling, and

certification, respectively (see Tables 6.2-4, 6.2-6, and 6.2-8).C Table 8.2-1 presents the

combined total of all engine fixed costs in the indicated years for each power category. Table

8.2-2 shows to what pollutant the total costs by year are allocated. Note that the cost allocations

shown in Table 8.2-1 are not generated assuming any simple split of costs between NOx and PM

control. Some engine fixed costs are solely attributed to PM control (for example, costs

associated with the 2008 standards and costs associated with the 2013 standards for 50 to 75 hp

engines). Therefore, the costs presented in Table 8.2-2 for PM do not represent the total fixed

costs of the program if there were no new NOx standards; the same is true of NOx costs if there
Final Regulatory Impact Analysis

8-4

were no new PM standards. Refer to Section 6.2 for detail on how we have estimated engine

fixed costs and their recovery, and to Table 8.1-2 for how they are allocated among each

pollutant.
8-5

Table 8.1-2

Summary of How Cost are Allocated Among Pollutants under the NRT4 Final Program

Item NOx+NMHC PM SOx

Fuel Costs – incremental cent/gallon 500 ppm Affected NRLM 33% 67%

15 ppm Affected NR 50% of 50% 50% of 50%

33% of 50% 67% of 50%

15 ppm Affected L&M 33% 67%

Operating Costs – Oil-Change Savings 500 ppm Affected NRLM 33% 67%

15 ppm Affected NR 50% of 50% 50% of 50%

33% of 50% 67% of 50%

15 ppm Affected L&M 33% 67%

Operating Costs – CDPF Maintenance 15 ppm NR in new CDPF engines 100%

Operating Costs – CDPF Regen (FE impact) 15 ppm NR in new CDPF engines 100%

Operating Costs – CCV Maintenance All NR in new CCV engines 50% 50%

Engine Variable Costs CDPF System 100%

NOx Adsorber System 100%

DOC 100%

Fuel-Injection System 50% 50%

Regeneration System 100%

Cooled EGR 100%

Closed Crankcase Ventilation Sys 50% 50%

Engine Fixed Costs – R&D CDPF+NOx Adsorber 67% 33%

CDPF-only 100%

DOC-only 100%

Engine Fixed Costs – Tooling CDPF+NOx Adsorber 50% 50%

CDPF-only 100%

DOC-only 100%

Cooled EGR 100%

Engine Fixed Costs – Certification <75 hp 2008 100%

25-50 hp 2013 50% 50%

50-75 hp 2013 100%

75-750 hp at start of phase-in 50% 50%

75-750 hp at end of phase-in 100%

>750 hp 50% 50%

Equipment Variable Costs <25 hp; 25-75 hp 2008-2012 100%

25-50 hp 2013+ 50% 50%

50-75 hp 2013+ 100%

75-750 hp at start of phase-inb 25% 75%

75-750 hp at end of phase-in 50% 50%

>750 hp 100%

Equipment Fixed Costs <75 hp 2008 standards 100%

25-75 hp 2013 standards 50% 50%

75-750 hp at start of phase-in 50% 50%

75-750 hp at end of phase-in 100%

>750 hp 2011 100%

>750 hp 2015 100%

b All engines meet the new PM standard and half meet the new NOx standard. For NOx phase-in engines, the allocation is 50/50 to

PM/NOx. For PM-only engines, the allocation is 100% PM. The resultant allocation is 75/25 to PM/NOx. 
8.2-1

Aggregate Engine Fixed Costs by Power Category

($Millions of 2002 dollars)

Year 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=750 

2008 $ 5.8 $ 8.0 $ 5.5 $ - $ - $ - $ - $ - $ 2009 $ 5.8 $ 8.0 $ 5.5 $ - $ - $ - $ - $ - $ 2010 $ 5.8 $ 8.0 $ 5.5 $ - $ - $ - $ - $ - $ 2011 $ 5.8 $ 8.0 $ 5.5 $ - $ - $ 17.4 $ 20.5 $ 3.8 $ 2012 $ 5.8 $ 8.0 $ 5.5 $ 6.9 $ 10.9 $ 17.4 $ 20.5 $ 3.8 $ 2013 $ - $ 13.3 $ 9.2 $ 6.9 $ 10.9 $ 17.4 $ 20.5 $ 3.8 $ 2014 $ - $ 13.3 $ 9.2 $ 9.6 $ 15.4 $ 23.7 $ 29.5 $ 5.6 $ 2015 $ - $ 13.3 $ 9.2 $ 9.6 $ 15.4 $ 23.7 $ 29.5 $ 5.6 $ 2016 $ - $ 13.3 $ 9.2 $ 9.6 $ 15.4 $ 6.3 $ 9.0 $ 1.8 $ 2017 $ - $ 13.3 $ 9.2 $ 2.7 $ 4.5 $ 6.3 $ 9.0 $ 1.8 $ 2018 $ - $ - $ - $ 2.7 $ 4.5 $ 6.3 $ 9.0 $ 1.8 $ 2019 $ - $ - $ - $ - $ - $ - $ - $ - $ 2020 $ - $ - $ - $ - $ - $ - $ - $ - $ Total $ 28.8 $ 106.1 $ 73.5 $ 48.2 $ 77.0 $ 118.3 $ 147.7 $ 28.1 $ 

30 Yr NPV at 3% $ 24.2 $ 81.3 $ 56.3 $ 35.3 $ 56.4 $ 88.7 $ 110.3 $ 21.0 $ 30 Yr NPV at 7% $ 19.3 $ 58.3 $ 40.4 $ 23.7 $ 37.9 $ 61.5 $ 76.2 $ 14.5 $ 
Aggregate Cost and Cost per Ton

8-7

Table 8.2-2

Aggregate Engine Fixed Costs by Pollutant

 ($Millions of 2002 dollars)

Year Recovery of PM

Costs

Recovery of

NOx Costs

Recovery of

Fixed Costs

2008 $ 19.3 $ - $ 19.3 

2009 $ 19.3 $ - $ 19.3 

2010 $ 19.3 $ - $ 19.3 

2011 $ 40.9 $ 22.0 $ 62.9 

2012 $ 49.8 $ 30.9 $ 80.7 

2013 $ 51.3 $ 32.5 $ 83.8 

2014 $ 51.3 $ 56.9 $ 108.2 

2015 $ 54.1 $ 57.3 $ 111.4 

2016 $ 32.5 $ 35.3 $ 67.8 

2017 $ 23.6 $ 26.4 $ 50.0 

2018 $ 2.8 $ 24.8 $ 27.6 

2019 $ 2.8 $ 0.4 $ 3.2 

2020 $ - $ - $ - 

Total $ 366.9 $ 286.4 $ 653.4 

30 Yr NPV at 3% $ 281.6 $ 210.3 $ 491.8 

30 Yr NPV at 7% $ 201.8 $ 141.9 $ 343.6 

We have assumed that all engine R&D expenditures occur over a five-year span preceding

the first year any emission-control device is introduced into the market, with the exception of

R&D for the 2008 standards which occurs over a four-year span preceding the standards as

described in Chapter 6. Where a phase-in exists (for example, for NOx standards on engines

between 75 and 750 hp), expenditures are assumed to occur over the five years preceding the

first year that NOx adsorbers will be introduced, then continuing during the phase-in years; the

expenditures will be incurred consistent with the phase-in of the standard. All R&D

expenditures are then recovered by the engine manufacturer over an identical time span

following the introduction of the technology. We include a cost of seven percent when

amortizing engine R&D expenditures.

We have assumed that all tooling and certification costs are incurred one year in advance of

the new standard and are recovered over a five-year period after the new standards take effect;

we include a cost of seven percent when amortizing engine tooling costs.

We have calculated the net present value of the engine fixed costs over the 30-year period

following implementation of the program as $492 million. This value assumes a three percent

social discount rate.

8.2.2 Aggregate Engine Variable Costs

Engine variable costs are discussed in detail in Section 6.2.2. As explained there, we have

generated cost estimation equations to calculate engine variable costs. These cost estimation

equations are summarized in Table 6.4-2. Using these equations, we have calculated the engine
Final Regulatory Impact Analysis

8-8

variable costs during the years 2008 through 2036 as shown in Tables 8.2-3 and 8.2-4 (refer to

Table 8.1-2 for how costs have been allocated to PM and NOx). Because of their nature,

variable costs are proportional to engine sales and are projected to increase in the future as

engine sales increase. We have calculated the net present value of the engine variable costs over

the 30-year period following implementation of the program as $13.6 billion. This value

assumes a three percent social discount rate.
8-9

Table 8.2-3 

Aggregate Engine Variable Costs by Power Category ($Millions of 2002 dollars)

Year 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=750 >7

2008 $ 19.7 $ 23.7 $ 18.4 $ - $ - $ - $ - $ - $ 2009 $ 20.2 $ 24.2 $ 18.8 $ - $ - $ - $ - $ - $ 2010 $ 19.7 $ 23.4 $ 18.0 $ - $ - $ - $ - $ - $ 2011 $ 20.2 $ 23.9 $ 18.4 $ - $ - $ 153.4 $ 101.5 $ 16.3 $ 2012 $ 20.7 $ 24.4 $ 18.7 $ 98.2 $ 192.8 $ 156.2 $ 102.6 $ 16.6 $ 2013 $ 21.2 $ 158.4 $ 100.9 $ 99.9 $ 196.0 $ 123.2 $ 80.4 $ 13.0 $ 2014 $ 21.7 $ 161.5 $ 102.6 $ 100.6 $ 195.6 $ 158.1 $ 102.3 $ 16.6 $ 2015 $ 22.2 $ 125.3 $ 79.3 $ 102.2 $ 198.8 $ 160.9 $ 103.4 $ 16.8 $ 2016 $ 22.7 $ 127.7 $ 80.6 $ 103.9 $ 201.9 $ 163.6 $ 104.5 $ 17.1 $ 2017 $ 23.2 $ 130.0 $ 81.9 $ 105.6 $ 205.0 $ 166.3 $ 105.6 $ 17.3 $ 2018 $ 23.7 $ 132.4 $ 83.2 $ 107.3 $ 208.2 $ 169.1 $ 106.7 $ 17.6 $ 2019 $ 24.2 $ 134.8 $ 84.5 $ 109.0 $ 211.3 $ 171.8 $ 107.8 $ 17.8 $ 2020 $ 24.7 $ 137.1 $ 85.8 $ 110.7 $ 214.4 $ 174.6 $ 109.0 $ 18.0 $ 2021 $ 25.2 $ 139.5 $ 87.1 $ 112.3 $ 217.6 $ 177.3 $ 110.1 $ 18.3 $ 2022 $ 25.7 $ 141.9 $ 88.4 $ 114.0 $ 220.7 $ 180.0 $ 111.2 $ 18.5 $ 2023 $ 26.2 $ 144.2 $ 89.7 $ 115.7 $ 223.8 $ 182.8 $ 112.3 $ 18.8 $ 2024 $ 26.8 $ 146.6 $ 91.0 $ 117.4 $ 227.0 $ 185.5 $ 113.4 $ 19.0 $ 2025 $ 27.3 $ 149.0 $ 92.3 $ 119.1 $ 230.1 $ 188.2 $ 114.5 $ 19.2 $ 2026 $ 27.8 $ 151.3 $ 93.6 $ 120.7 $ 233.2 $ 191.0 $ 115.6 $ 19.5 $ 2027 $ 28.3 $ 153.7 $ 94.9 $ 122.4 $ 236.4 $ 193.7 $ 116.7 $ 19.7 $ 2028 $ 28.8 $ 156.1 $ 96.2 $ 124.1 $ 239.5 $ 196.5 $ 117.8 $ 20.0 $ 2029 $ 29.3 $ 158.4 $ 97.5 $ 125.8 $ 242.6 $ 199.2 $ 118.9 $ 20.2 $ 2030 $ 29.8 $ 160.8 $ 98.8 $ 127.5 $ 245.8 $ 201.9 $ 120.1 $ 20.4 $ 2031 $ 30.3 $ 163.2 $ 100.1 $ 129.2 $ 248.9 $ 204.7 $ 121.2 $ 20.7 $ 2032 $ 30.8 $ 165.5 $ 101.4 $ 130.8 $ 252.0 $ 207.4 $ 122.3 $ 20.9 $ 2033 $ 31.3 $ 167.9 $ 102.7 $ 132.5 $ 255.2 $ 210.2 $ 123.4 $ 21.2 $ 2034 $ 31.8 $ 170.3 $ 104.0 $ 134.2 $ 258.3 $ 212.9 $ 124.5 $ 21.4 $ 2035 $ 32.3 $ 172.6 $ 105.3 $ 135.9 $ 261.5 $ 215.6 $ 125.6 $ 21.6 $ 2036 $ 32.8 $ 175.0 $ 106.6 $ 137.6 $ 264.6 $ 218.4 $ 126.7 $ 21.9 $ 

30 Yr NPV at 3% $ 435.7 $ 2,089.2 $ 1,315.1 $ 1,627.3 $ 3,151.4 $ 2,670.3 $ 1,650.1 $ 274.9 $ 30 Yr NPV at 7% $ 236.9 $ 1,057.6 $ 672.3 $ 812.0 $ 1,574.6 $ 1,359.6 $ 849.2 $ 140.6 $ 
8-10

Table 8.2-4

 Aggregate Engine Variable Costs by Technology and by Pollutant ($Millions of 2002 dollar

Year Fuel System Cooled EGR CCV DOC CDPF System CDPF Regen

System

NOx Adsorber

System

Total PM Costs To

NOx+

Co

2008 $ - $ - $ 0.5 $ 61.2 $ - $ - $ - $ 61.5 $ 2009 $ - $ - $ 0.6 $ 62.6 $ - $ - $ - $ 62.9 $ 2010 $ - $ - $ 0.4 $ 60.7 $ - $ - $ - $ 60.9 $ 2011 $ - $ 6.2 $ 7.1 $ 62.0 $ 168.8 $ 28.7 $ 67.4 $ 263.1 $ 2012 $ - $ 6.3 $ 13.4 $ 63.3 $ 338.4 $ 73.2 $ 142.1 $ 481.7 $ 2013 $ 53.3 $ 29.2 $ 11.8 $ 21.2 $ 414.1 $ 137.4 $ 131.2 $ 605.3 $ 2014 $ 54.3 $ 29.8 $ 10.3 $ 21.7 $ 380.3 $ 128.8 $ 239.3 $ 563.1 $ 2015 $ 41.6 $ 24.4 $ 10.4 $ 22.2 $ 381.3 $ 115.6 $ 243.0 $ 545.1 $ 2016 $ 42.4 $ 24.8 $ 10.6 $ 22.7 $ 387.3 $ 117.5 $ 246.8 $ 554.0 $ 2017 $ 43.1 $ 25.2 $ 10.8 $ 23.2 $ 388.0 $ 118.9 $ 250.5 $ 557.0 $ 2018 $ 43.8 $ 25.7 $ 10.9 $ 23.7 $ 393.9 $ 120.8 $ 254.2 $ 565.8 $ 2019 $ 44.6 $ 26.1 $ 11.1 $ 24.2 $ 399.8 $ 122.8 $ 257.9 $ 574.6 $ 2020 $ 45.3 $ 26.5 $ 11.2 $ 24.7 $ 405.7 $ 124.7 $ 261.6 $ 583.4 $ 2021 $ 46.1 $ 27.0 $ 11.4 $ 25.2 $ 411.7 $ 126.6 $ 265.4 $ 592.3 $ 2022 $ 46.8 $ 27.4 $ 11.6 $ 25.7 $ 417.6 $ 128.5 $ 269.1 $ 601.1 $ 2023 $ 47.6 $ 27.8 $ 11.7 $ 26.2 $ 423.5 $ 130.5 $ 272.8 $ 609.9 $ 2024 $ 48.3 $ 28.3 $ 11.9 $ 26.8 $ 429.5 $ 132.4 $ 276.5 $ 618.7 $ 2025 $ 49.1 $ 28.7 $ 12.0 $ 27.3 $ 435.4 $ 134.3 $ 280.2 $ 627.5 $ 2026 $ 49.8 $ 29.2 $ 12.2 $ 27.8 $ 441.3 $ 136.2 $ 284.0 $ 636.3 $ 2027 $ 50.5 $ 29.6 $ 12.4 $ 28.3 $ 447.3 $ 138.2 $ 287.7 $ 645.1 $ 2028 $ 51.3 $ 30.0 $ 12.5 $ 28.8 $ 453.2 $ 140.1 $ 291.4 $ 653.9 $ 2029 $ 52.0 $ 30.5 $ 12.7 $ 29.3 $ 459.1 $ 142.0 $ 295.1 $ 662.8 $ 2030 $ 52.8 $ 30.9 $ 12.8 $ 29.8 $ 465.1 $ 143.9 $ 298.8 $ 671.6 $ 2031 $ 53.5 $ 31.3 $ 13.0 $ 30.3 $ 471.0 $ 145.8 $ 302.6 $ 680.4 $ 2032 $ 54.3 $ 31.8 $ 13.2 $ 30.8 $ 476.9 $ 147.8 $ 306.3 $ 689.2 $ 2033 $ 55.0 $ 32.2 $ 13.3 $ 31.3 $ 482.8 $ 149.7 $ 310.0 $ 698.0 $ 2034 $ 55.8 $ 32.7 $ 13.5 $ 31.8 $ 488.8 $ 151.6 $ 313.7 $ 706.8 $ 2035 $ 56.5 $ 33.1 $ 13.6 $ 32.3 $ 494.7 $ 153.5 $ 317.5 $ 715.6 $ 2036 $ 57.2 $ 33.5 $ 13.8 $ 32.8 $ 500.6 $ 155.5 $ 321.2 $ 724.4 $ 

30 Yr NPV at 3% $ 657.0 $ 391.7 $ 175.8 $ 611.1 $ 6,127.5 $ 1,860.1 $ 3,738.8 $ 9,015.3 $ 430 Yr NPV at 7% $ 323.5 $ 194.8 $ 90.7 $ 377.0 $ 3,102.8 $ 933.3 $ 1,849.0 $ 4,620.3 $ 2
Aggregate Cost and Cost per Ton

8-11

8.3 Aggregate Equipment Costs

This section aggregates the amortized fixed and variable cost for equipment estimated in

Section 6.3.

8.3.1 Aggregate Equipment Fixed Costs

In Table 6.3-4 we presented the aggregate equipment fixed costs, along with our best

estimate of how those costs might be recovered, for equipment redesign and revisions to product

literature. Table 8.3-1 presents aggregate equipment fixed costs and Table 8.3-2 shows to what

pollutant these costs are attributed. Note that the cost allocations shown in Table 8.3-2 are not

generated assuming any simple split of costs between NOx and PM control. Some equipment

fixed costs are solely attributed to PM control (for example, costs associated with the 2008

standards and costs associated with the 2013 standards for 50 to 75 hp engines). The costs

presented in Table 8.3-1 for PM therefore do not represent the total fixed costs of the program if

there were no new NOx standards; the same is true of NOx costs if there were no new PM

standards. Refer to Section 6.3 for detail on how we have estimated equipment fixed costs and

their recovery, and to Table 8.1-2 for how they are allocated among each pollutant.

We have assumed that all equipment fixed costs (redesign and product literature) occur over

a two-year span preceding the first year any emission-control device is introduced into the

market. Where a phase-in exists (for example, for NOx standards on engines over 75 hp

engines), expenditures are assumed to occur over the two years preceding the first year that NOx

adsorbers will be introduced, then continuing during the phase-in years; the expenditures will be

incurred consistent with the phase-in of the standard. All expenditures are then recovered by the

equipment manufacturer over 10 years following the introduction of the technology. We include

a cost of seven percent when amortizing equipment fixed costs.

We have calculated the net present value of the equipment fixed costs over the 30-year

period following implementation of the program as $847 million. This value assumes a three

percent social discount rate.
Table 8.3-1

Aggregate Equipment Fixed Costs by Power Range ($Millions of 2002 dollars)

Year Recovered 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=75

2008 $ 2.3 $ 1.3 $ 0.9 $ - $ - $ - $ - $ - 2009 $ 2.3 $ 1.3 $ 0.9 $ - $ - $ - $ - $ - 2010 $ 2.3 $ 1.3 $ 0.9 $ - $ - $ - $ - $ - 2011 $ 2.3 $ 1.3 $ 0.9 $ - $ - $ 23.4 $ 20.6 $ 4.0 2012 $ 2.3 $ 1.3 $ 0.9 $ 9.4 $ 23.9 $ 23.4 $ 20.6 $ 4.0 2013 $ 2.3 $ 7.5 $ 5.3 $ 9.4 $ 23.9 $ 23.4 $ 20.6 $ 4.0 2014 $ 2.3 $ 7.5 $ 5.3 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2015 $ 2.3 $ 7.5 $ 5.3 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2016 $ 2.3 $ 7.5 $ 5.3 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2017 $ 2.3 $ 7.5 $ 5.3 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2018 $ - $ 6.2 $ 4.4 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2019 $ - $ 6.2 $ 4.4 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2020 $ - $ 6.2 $ 4.4 $ 11.9 $ 30.0 $ 29.4 $ 25.8 $ 5.0 2021 $ - $ 6.2 $ 4.4 $ 11.9 $ 30.0 $ 6.0 $ 5.2 $ 1.0 2022 $ - $ 6.2 $ 4.4 $ 2.4 $ 6.1 $ 6.0 $ 5.2 $ 1.0 2023 $ - $ - $ - $ 2.4 $ 6.1 $ 6.0 $ 5.2 $ 1.0 2024 $ - $ - $ - $ - $ - $ - $ - $ - Total $ 23.0 $ 75.0 $ 52.9 $ 118.6 $ 299.7 $ 293.6 $ 258.0 $ 50.1 

30 Yr NPV at 3% $ 18.0 $ 51.9 $ 36.6 $ 81.3 $ 205.5 $ 206.1 $ 181.2 $ 35.2 30 Yr NPV at 7% $ 13.2 $ 32.8 $ 23.1 $ 50.5 $ 127.7 $ 132.3 $ 116.3 $ 22.6 
Aggregate Cost and Cost per Ton

8-13

Table 8.3-2

Aggregate Equipment Fixed Costs by Pollutant

 ($Millions of 2002 dollars)

Year Recovery of

PM Costs

Recovery of

NOx+NMHC

Costs

Recovery of

Fixed Costs

2008 $ 4.5 $ - $ 4.5 

2009 $ 4.5 $ - $ 4.5 

2010 $ 4.5 $ - $ 4.5 

2011 $ 28.5 $ 24.6 $ 53.1 

2012 $ 45.1 $ 41.2 $ 86.4 

2013 $ 50.4 $ 46.5 $ 97.0 

2014 $ 50.4 $ 67.3 $ 117.7 

2015 $ 54.7 $ 67.3 $ 122.0 

2016 $ 54.7 $ 67.3 $ 122.0 

2017 $ 54.7 $ 67.3 $ 122.0 

2018 $ 50.2 $ 67.3 $ 117.5 

2019 $ 50.2 $ 67.3 $ 117.5 

2020 $ 50.2 $ 67.3 $ 117.5 

2021 $ 26.2 $ 42.7 $ 68.9 

2022 $ 9.6 $ 26.0 $ 35.6 

2023 $ 4.3 $ 20.7 $ 25.0 

2024 $ 4.3 $ - $ 4.3 

Total $ 547.3 $ 672.5 $ 1,219.9 

30 Yr NPV at 3% $ 384.9 $ 462.2 $ 847.2 

30 Yr NPV at 7% $ 247.9 $ 288.7 $ 536.6 

8.3.2 Aggregate Equipment Variable Costs

The equipment variable costs, such as sheet metal costs, mounting hardware, and labor, were

estimated by power category in Section 6.3. The aggregate equipment variable costs through

2036 are presented in Table 8.3-3. Table 8.3-4 shows the total aggregate equipment variable

costs allocated by pollutant (refer to Table 8.1-2 for how costs have been allocated to PM and

NOx). We have calculated the net present value of the equipment variable costs over the 30-year

period following implementation of the program as $434 million. This value assumes a three

percent social discount rate.
Table 8.3-3

Aggregate Equipment Variable Costs by Power Category ($Millions of 2002 dollars)

Year 0<hp<25 25<=hp<50 50<=hp<75 75<=hp<100 100<=hp<175 175<=hp<300 300<=hp<600 600<=hp<=750 

2008 $ - $ - $ - $ - $ - $ - $ - $ - $ 2009 $ - $ - $ - $ - $ - $ - $ - $ - $ 2010 $ - $ - $ - $ - $ - $ - $ - $ - $ 2011 $ - $ - $ - $ - $ - $ 4.5 $ 4.3 $ 0.4 $ 2012 $ - $ - $ - $ 3.9 $ 6.4 $ 4.6 $ 4.3 $ 0.4 $ 2013 $ - $ 3.6 $ 2.5 $ 4.0 $ 6.5 $ 3.7 $ 3.5 $ 0.3 $ 2014 $ - $ 3.7 $ 2.6 $ 4.3 $ 7.1 $ 5.0 $ 4.7 $ 0.4 $ 2015 $ - $ 3.0 $ 2.1 $ 4.4 $ 7.2 $ 5.1 $ 4.8 $ 0.4 $ 2016 $ - $ 3.1 $ 2.1 $ 4.5 $ 7.3 $ 5.2 $ 4.8 $ 0.4 $ 2017 $ - $ 3.1 $ 2.2 $ 4.5 $ 7.4 $ 5.3 $ 4.9 $ 0.4 $ 2018 $ - $ 3.2 $ 2.2 $ 4.6 $ 7.6 $ 5.4 $ 4.9 $ 0.5 $ 2019 $ - $ 3.3 $ 2.2 $ 4.7 $ 7.7 $ 5.5 $ 5.0 $ 0.5 $ 2020 $ - $ 3.3 $ 2.3 $ 4.7 $ 7.8 $ 5.6 $ 5.0 $ 0.5 $ 2021 $ - $ 3.4 $ 2.3 $ 4.8 $ 7.9 $ 5.6 $ 5.1 $ 0.5 $ 2022 $ - $ 3.4 $ 2.3 $ 4.9 $ 8.0 $ 5.7 $ 5.1 $ 0.5 $ 2023 $ - $ 3.5 $ 2.4 $ 5.0 $ 8.1 $ 5.8 $ 5.2 $ 0.5 $ 2024 $ - $ 3.5 $ 2.4 $ 5.0 $ 8.2 $ 5.9 $ 5.2 $ 0.5 $ 2025 $ - $ 3.6 $ 2.4 $ 5.1 $ 8.3 $ 6.0 $ 5.3 $ 0.5 $ 2026 $ - $ 3.7 $ 2.5 $ 5.2 $ 8.5 $ 6.1 $ 5.3 $ 0.5 $ 2027 $ - $ 3.7 $ 2.5 $ 5.3 $ 8.6 $ 6.2 $ 5.4 $ 0.5 $ 2028 $ - $ 3.8 $ 2.5 $ 5.3 $ 8.7 $ 6.3 $ 5.4 $ 0.5 $ 2029 $ - $ 3.8 $ 2.6 $ 5.4 $ 8.8 $ 6.3 $ 5.5 $ 0.5 $ 2030 $ - $ 3.9 $ 2.6 $ 5.5 $ 8.9 $ 6.4 $ 5.5 $ 0.5 $ 2031 $ - $ 3.9 $ 2.7 $ 5.5 $ 9.0 $ 6.5 $ 5.6 $ 0.5 $ 2032 $ - $ 4.0 $ 2.7 $ 5.6 $ 9.1 $ 6.6 $ 5.6 $ 0.5 $ 2033 $ - $ 4.1 $ 2.7 $ 5.7 $ 9.3 $ 6.7 $ 5.7 $ 0.5 $ 2034 $ - $ 4.1 $ 2.8 $ 5.8 $ 9.4 $ 6.8 $ 5.7 $ 0.5 $ 2035 $ - $ 4.2 $ 2.8 $ 5.8 $ 9.5 $ 6.9 $ 5.8 $ 0.6 $ 2036 $ - $ 4.2 $ 2.8 $ 5.9 $ 9.6 $ 7.0 $ 5.8 $ 0.6 $ 

30 Yr NPV at 3% $ - $ 47.8 $ 32.6 $ 69.3 $ 113.5 $ 84.2 $ 75.0 $ 7.0 $ 

30 YR NPV at 7% $ - $ 23.4 $ 16.0 $ 34.5 $ 56.5 $ 42.7 $ 38.4 $ 3.6 $ 
Aggregate Cost and Cost per Ton

8-15

Table 8.3-4

Aggregate Equipment Variable Costs by Pollutant

 ($Millions of 2002 dollars)

Year PM Costs NOx Costs Total Variable

Costs

2008 $ - $ - $ - 

2009 $ - $ - $ - 

2010 $ - $ - $ - 

2011 $ 6.8 $ 2.3 $ 9.1 

2012 $ 14.7 $ 4.9 $ 19.6 

2013 $ 19.7 $ 4.5 $ 24.2 

2014 $ 17.1 $ 10.8 $ 27.9 

2015 $ 16.5 $ 11.0 $ 27.5 

2016 $ 16.8 $ 11.1 $ 27.9 

2017 $ 17.0 $ 11.3 $ 28.2 

2018 $ 17.2 $ 11.4 $ 28.7 

2019 $ 17.5 $ 11.6 $ 29.1 

2020 $ 17.7 $ 11.8 $ 29.5 

2021 $ 18.0 $ 11.9 $ 29.9 

2022 $ 18.3 $ 12.1 $ 30.4 

2023 $ 18.5 $ 12.3 $ 30.8 

2024 $ 18.8 $ 12.4 $ 31.2 

2025 $ 19.0 $ 12.6 $ 31.6 

2026 $ 19.3 $ 12.8 $ 32.1 

2027 $ 19.6 $ 12.9 $ 32.5 

2028 $ 19.8 $ 13.1 $ 32.9 

2029 $ 20.1 $ 13.3 $ 33.4 

2030 $ 20.4 $ 13.4 $ 33.8 

2031 $ 20.6 $ 13.6 $ 34.2 

2032 $ 20.9 $ 13.8 $ 34.6 

2033 $ 21.1 $ 13.9 $ 35.1 

2034 $ 21.4 $ 14.1 $ 35.5 

2035 $ 21.7 $ 14.3 $ 35.9 

2036 $ 21.9 $ 14.4 $ 36.3 

30 Yr NPV at 3% $ 268.9 $ 165.3 $ 434.2 

30 Yr NPV at 7% $ 136.3 $ 81.1 $ 217.4 

8.4 Aggregate Fuel Costs and Other Operating Costs

Aggregate costs presented here are used in the calculation of costs per ton of emission

reductions resulting from this final rule. This includes a two-step fuel sulfur control program

consisting of a NRLM sulfur cap of 500 ppm beginning in 2007 to be followed by a nonroad

(NR) sulfur cap of 15 ppm beginning in 2010 and a locomotive and marine (L&M) sulfur cap of

15 ppm beginning in 2012. Refer to Chapters 5 and 7 for more information about the fuel

program and how the costs for that portion of the NRT4 final rule were estimated. 

As noted, the second step in the fuel program limits NR sulfur levels to 15 ppm beginning in

2010. This fuel program enables the introduction of advanced emission-control

technologies—CDPFs and NOx adsorbers—that will enable nonroad engines to meet the new

Tier 4 standards, and it also achieves additional emissions reductions from the fuel control itself

(i.e., independent of new engine standards). The combination of the two-step NRLM fuel
Final Regulatory Impact Analysis

8-16

program and the new diesel engine standards represents the full engine and fuel program (i.e.,

the NRT4 final rule). Section 8.4.1 presents our estimate of the aggregate fuel costs associated

with the NRT4 final rule. Sections 8.4-2 through 8.4-4 present estimates of other operating

costs—CDPF and CCV maintenance, fuel economy impacts, and oil change

maintenance—associated with the NRT4 final rule. Section 8.4-5 presents the cost of the fuel

program absent any new engine standards. These costs differ from the costs associated with the

fuel program costs of the NRT4 final rule in that no CDPF and CCV maintenance costs, and no

fuel economy impacts would be realized. We present these costs because they are used in

calculations of $/ton associated with such a “fuel-only” scenario.

8.4.1 Aggregate Fuel Costs

Fuel costs, described in detail in Chapter 7, are developed on a cent-per-gallon basis. Table

8.4-1 summarizes cent-per-gallon fuel costs (see Table 7.5-1), estimated fuel volumes for NR,

L&M, and the resultant annual fuel costs associated with the two-step NRT4 final rule fuel

program. Table 8.4-1 shows that the 30-year net present value of the new lower sulfur

requirements is estimated at $16.3 billion. This assumes a three percent social discount rate. 

Note that the affected fuel volumes presented in Table 8.4-1 are gallons consumed in both new

and existing engines since both new and existing engines will have to pay for the higher cost

fuel. We have not included spillover gallons or other such gallons that would have entered the

NRLM fuel pool with a sulfur level below the new cap absent the new requirements since these

gallons do not represent an incremental increase in costs associated with the NRT4 final rule.
Table 8.4-1

Aggregate Fuel Costs of the Two-Step Fuel Program ($2002)

Year Affected NR Affected L&M Fuel Cost* NR Fuel Costs L&

500 ppm (106 gallons) 15 ppm (106 gallons) 500 ppm (106 gallons) 15 ppm (106 gallons) 500 ppm ($/gal) 15 ppm ($/gal) 500 ppm (106 dollars) 15 ppm (106 dollars) Total (106 dollars) 500 ppm (106 dollars) 

2007 4,790 - 1,990 - $ 0.021 $ - $ 101 - $ 101 $ 42 2008 8,406 - 3,454 - $ 0.021 $ - $ 177 - $ 177 $ 73 2009 8,599 - 3,498 - $ 0.021 $ - $ 181 - $ 181 $ 73 2010 4,014 6,189 3,185 0 $ 0.028 $ 0.058 $ 112 359 $ 471 $ 89 2011 614 8,145 2,975 0 $ 0.033 $ 0.058 $ 20 472 $ 493 $ 98 2012 528 8,420 1,396 1,965 $ 0.034 $ 0.062 $ 18 518 $ 536 $ 48 2013 468 8,671 247 3,397 $ 0.035 $ 0.064 $ 16 555 $ 571 $ 9 2014 199 9,713 104 3,081 $ 0.035 $ 0.068 $ 7 656 $ 663 $ 4 2015 - 10,539 - 2,860 $ 0.070 $ - 738 $ 738 $ - 2016 - 10,747 - 2,888 $ 0.070 $ - 752 $ 752 $ - 2017 - 10,955 - 2,918 $ 0.070 $ - 767 $ 767 $ - 2018 - 11,162 - 2,953 $ 0.070 $ - 781 $ 781 $ - 2019 - 11,370 - 2,995 $ 0.070 $ - 796 $ 796 $ - 2020 - 11,578 - 3,024 $ 0.070 $ - 810 $ 810 $ - 2021 - 11,786 - 3,052 $ 0.070 $ - 825 $ 825 $ - 2022 - 11,994 - 3,093 $ 0.070 $ - 840 $ 840 $ - 2023 - 12,201 - 3,125 $ 0.070 $ - 854 $ 854 $ - 2024 - 12,409 - 3,161 $ 0.070 $ - 869 $ 869 $ - 2025 - 12,617 - 3,195 $ 0.070 $ - 883 $ 883 $ - 2026 - 12,823 - 3,230 $ 0.070 $ - 898 $ 898 $ - 2027 - 13,030 - 3,265 $ 0.070 $ - 912 $ 912 $ - 2028 - 13,236 - 3,301 $ 0.070 $ - 927 $ 927 $ - 2029 - 13,442 - 3,336 $ 0.070 $ - 941 $ 941 $ - 2030 - 13,649 - 3,371 $ 0.070 $ - 955 $ 955 $ - 2031 - 13,855 - 3,406 $ 0.070 $ - 970 $ 970 $ - 2032 - 14,061 - 3,441 $ 0.070 $ - 984 $ 984 $ - 2033 - 14,268 - 3,476 $ 0.070 $ - 999 $ 999 $ - 2034 - 14,474 - 3,512 $ 0.070 $ - 1,013 $ 1,013 $ - 2035 - 14,680 - 3,547 $ 0.070 $ - 1,028 $ 1,028 $ - 2036 - 14,887 - 3,582 $ 0.070 $ - 1,042 $ 1,042 $ - 

30 Yr NPV at 3% 24,054 180,224 14,363 44,087 $ 547 $ 12,360 $ 12,907 $ 368 30 Yr NPV at 7% 20,174 92,196 11,729 22,124 $ 456 $ 6,261 $ 6,717 $ 297 

* Fuel costs are relative to uncontrolled fuel and assume that, during the transitional years of 2010, 2012, & 2014, the first 5 months are at the previous year's cost anext year's cost.See Appendix 8B for how these fuel volumes were developed.
Final Regulatory Impact Analysis

8-18

8.4.2 Aggregate Oil-Change Maintenance Savings

Maintenance savings associated with extended oil-change intervals are developed on a centper-gallon basis, as described in Section 6.2.3.1. The cent-per-gallon savings for nonroad

engines is the fleet weighted value for nonroad engines presented in Section 6.2.3.1. This fleet

weighted value is derived using data presented in Table 6.2-28 as discussed in that section. The

cent-per-gallon savings for locomotive and marine engines is taken directly from Table 6.2-28. 

Table 8.4-2 summarizes the annual maintenance savings and associated fuel volumes for

nonroad, locomotive, and marine engines. Note that the fuel volumes used for oil change

maintenance savings are the same affected volumes presented in Table 8.4-1. We have not

included savings associated with unaffected gallons (i.e., low sulfur gallons that would have

entered the NRLM fuel pool absent the new requirements) since we assume that engines

consuming those gallons benefit from the low sulfur fuel absent the NRT4 final rule. As shown

in Table 8.4-2, the net present value of the oil change maintenance savings is estimated at $7.1

billion. This assumes a three percent social discount rate.
Table 8.4-2

Oil-Change Maintenance Savings Associated with the Two-Step Fuel Program ($2002)

Year Affected NR Affected L&M NR Savings L&M Saving

500 ppm 

(106 gallons)

15 ppm 

(106 gallons)

500 ppm 

(106 gallons)

15 ppm 

(106 gallons)

savings=$0.029/gal

(106 dollars)

savings=$0.032/gal

(106 dollars)

savings=$0.010/gal

(106 dollars)

savi

2007 4,790 - 1,990 - $ 140 $ - $ 21 $ 2008 8,406 - 3,454 - $ 246 $ - $ 36 $ 2009 8,599 - 3,498 - $ 251 $ - $ 37 $ 2010 4,014 6,189 3,185 0 $ 117 $ 198 $ 33 $ 2011 614 8,145 2,975 0 $ 18 $ 261 $ 31 $ 2012 528 8,420 1,396 1,965 $ 15 $ 270 $ 15 $ 2013 468 8,671 247 3,397 $ 14 $ 278 $ 3 $ 2014 199 9,713 104 3,081 $ 6 $ 311 $ 1 $ 2015 - 10,539 - 2,860 $ - $ 338 $ - $ 2016 - 10,747 - 2,888 $ - $ 344 $ - $ 2017 - 10,955 - 2,918 $ - $ 351 $ - $ 2018 - 11,162 - 2,953 $ - $ 358 $ - $ 2019 - 11,370 - 2,995 $ - $ 364 $ - $ 2020 - 11,578 - 3,024 $ - $ 371 $ - $ 2021 - 11,786 - 3,052 $ - $ 377 $ - $ 2022 - 11,994 - 3,093 $ - $ 384 $ - $ 2023 - 12,201 - 3,125 $ - $ 391 $ - $ 2024 - 12,409 - 3,161 $ - $ 397 $ - $ 2025 - 12,617 - 3,195 $ - $ 404 $ - $ 2026 - 12,823 - 3,230 $ - $ 411 $ - $ 2027 - 13,030 - 3,265 $ - $ 417 $ - $ 2028 - 13,236 - 3,301 $ - $ 424 $ - $ 2029 - 13,442 - 3,336 $ - $ 431 $ - $ 2030 - 13,649 - 3,371 $ - $ 437 $ - $ 2031 - 13,855 - 3,406 $ - $ 444 $ - $ 2032 - 14,061 - 3,441 $ - $ 450 $ - $ 2033 - 14,268 - 3,476 $ - $ 457 $ - $ 2034 - 14,474 - 3,512 $ - $ 464 $ - $ 2035 - 14,680 - 3,547 $ - $ 470 $ - $ 2036 - 14,887 - 3,582 $ - $ 477 $ - $ 

30 Yr NPV at 3% 24,054 180,224 14,363 44,087 $ 703 $ 5,772 $ 150 $ 30 Yr NPV at 7% 20,174 92,196 11,729 22,124 $ 590 $ 2,953 $ 123 $ 
Final Regulatory Impact Analysis

8-20

8.4.3 Aggregate CDPF Maintenance, CDPF Regeneration, and CCV Maintenance Costs

Costs associated with CDPF maintenance and CCV maintenance are developed on a centper-gallon basis as described in Section 6.2.3. Table 8.4-3 summarizes the CDPF maintenance

and CDPF regeneration costs associated with the NRT4 fuel program. The fuel volumes shown

in Table 8.4-3 differ from those shown in Tables 8.4-1 through 8.4-2 because here we want only

those gallons consumed in new CDPF equipped engines. Therefore, fuel consumed in existing

engines and fuel consumed in new engines not yet equipped with a CDPF are not included in

Table 8.4-3. 

The cent-per-gallon costs shown for CDPF maintenance are taken from data presented in

Table 6.2-29. As engines in different power categories add CDPFs, the weighted $/gallon

number changes until all new engines have added a CDPF and the fleet weighted average

becomes the 0.6 cents/gallon value presented in Section 6.2.3.2. The cent-per-gallon costs

shown for CDPF regeneration are taken from information presented in Section 6.2.3.3.2. The

weighted value shown accounts for the 60 cent/gallon base fuel cost for diesel fuel and the NOx

phase-in on different engines—engines equipped with a CDPF and no NOx adsorber incur a 2%

fuel economy impact associated with regeneration while engines equipped with both a CDPF and

a NOx adsorber incur a 1% fuel economy impact. This weighted number also accounts for the

different 15 ppm fuel cost during the years 2010-2014 and then for 2015 and later.

As shown in Table 8.4-3, the 30-year net present value of these two CDPF-related operating

costs is estimated at $2.3 billion. This assumes a three percent social discount rate.
Aggregate Cost and Cost per Ton

8-21

Table 8.4-3

CDPF Maintenance and CDPF Regeneration Costs Associated with the Two-Step Fuel Program

($2002)

Year Fuel Consumed in New

CDPF Equipped Engines 

(106

 gallons)

Weighted

Maintenance

Cost

 ($/gal)

Weighted

Regeneration

Cost

 ($/gal)

 CDPF Maintenance

Cost

 (106

 dollars)

CDPF Regeneration

Cost 

 (106 dollars)

Total Costs

(106

 dollars)

2007 - $ - $ - $ - $ - $ - 

2008 - $ - $ - $ - $ - $ - 

2009 - $ - $ - $ - $ - $ - 

2010 - $ - $ - $ - $ - $ - 

2011 559 $ 0.002 $ 0.010 $ 1 $ 6 $ 6 

2012 1,543 $ 0.003 $ 0.010 $ 5 $ 15 $ 20 

2013 2,774 $ 0.005 $ 0.010 $ 14 $ 28 $ 42 

2014 4,010 $ 0.006 $ 0.007 $ 23 $ 30 $ 53 

2015 5,343 $ 0.006 $ 0.008 $ 31 $ 41 $ 73 

2016 6,630 $ 0.006 $ 0.008 $ 40 $ 52 $ 92 

2017 7,842 $ 0.006 $ 0.008 $ 47 $ 62 $ 110 

2018 8,966 $ 0.006 $ 0.008 $ 55 $ 72 $ 127 

2019 10,006 $ 0.006 $ 0.008 $ 61 $ 81 $ 142 

2020 10,975 $ 0.006 $ 0.008 $ 67 $ 89 $ 156 

2021 11,848 $ 0.006 $ 0.008 $ 72 $ 97 $ 169 

2022 12,631 $ 0.006 $ 0.008 $ 77 $ 103 $ 180 

2023 13,358 $ 0.006 $ 0.008 $ 82 $ 109 $ 191 

2024 14,044 $ 0.006 $ 0.008 $ 86 $ 114 $ 200 

2025 14,697 $ 0.006 $ 0.008 $ 90 $ 120 $ 210 

2026 15,304 $ 0.006 $ 0.008 $ 94 $ 125 $ 218 

2027 15,852 $ 0.006 $ 0.008 $ 97 $ 129 $ 226 

2028 16,351 $ 0.006 $ 0.008 $ 100 $ 133 $ 234 

2029 16,825 $ 0.006 $ 0.008 $ 103 $ 137 $ 240 

2030 17,277 $ 0.006 $ 0.008 $ 106 $ 141 $ 247 

2031 17,704 $ 0.006 $ 0.008 $ 109 $ 144 $ 253 

2032 18,116 $ 0.006 $ 0.008 $ 111 $ 148 $ 259 

2033 18,521 $ 0.006 $ 0.008 $ 113 $ 151 $ 264 

2034 18,913 $ 0.006 $ 0.008 $ 116 $ 154 $ 270 

2035 19,287 $ 0.006 $ 0.008 $ 118 $ 157 $ 275 

2036 19,645 $ 0.006 $ 0.008 $ 120 $ 160 $ 280 

30 Yr NPV at 3% 164,697 $ 997 $ 1,343 $ 2,340 

30 Yr NPV at 7% 74,092 $ 445 $ 605 $ 1,050 

* Note that fuel used in CDPF engines includes some highway spillover fuel.

**Weighted Regeneration Cost ($/gal) changes year-to-year due to different fuel economy impacts with a NOx adsorber (1 percent)

and without a NOx adsorber (2 percent) matched with the phase-in schedules of the emission standards.

The cent-per-gallon costs for CCV maintenance are taken from data presented in Table 6.2-

30. Table 8.4-4 presents the annual costs associated with CCV maintenance. The gallons shown

in Table 8.4-4 are gallons of fuel consumed in engines in power ranges for which the new CCV

requirements have gone into effect. However, these are not necessarily equal to the gallons

consumed in new CCV equipped engines since only the turbocharged engines will be adding a

CCV system. Therefore, the cent-per-gallon costs in early years is essentially zero since so few

engines in the <75hp range are turbocharged and, hence, so few are adding a CCV system and

incurring the associated maintenance costs. As shown in Table 8.4-4, the 30-year net present

value of the CCV maintenance costs are estimated at $275 million. This assumes a three percent

social discount rate.
Final Regulatory Impact Analysis

8-22

Table 8.4-4

CCV Maintenance Costs Associated with the Two-Step Fuel Program

($2002)

Year Fuel Consumed in Power

Categories Adding CCV

System

 (106

 gallons)

Weighted

Maintenance

Cost

 ($/gal)

Total Costs

(106

 dollars)

2007 - $ - $ - 

2008 242 $ 0.000 $ 0 

2009 248 $ 0.000 $ 0 

2010 254 $ 0.000 $ 0 

2011 927 $ 0.001 $ 1 

2012 2,023 $ 0.001 $ 3 

2013 3,369 $ 0.002 $ 5 

2014 4,716 $ 0.002 $ 7 

2015 6,160 $ 0.002 $ 9 

2016 7,552 $ 0.002 $ 11 

2017 8,857 $ 0.002 $ 13 

2018 10,042 $ 0.002 $ 15 

2019 11,139 $ 0.002 $ 17 

2020 12,161 $ 0.002 $ 18 

2021 13,084 $ 0.002 $ 20 

2022 13,913 $ 0.002 $ 21 

2023 14,680 $ 0.002 $ 22 

2024 15,402 $ 0.002 $ 23 

2025 16,088 $ 0.002 $ 24 

2026 16,724 $ 0.002 $ 25 

2027 17,301 $ 0.002 $ 26 

2028 17,827 $ 0.002 $ 27 

2029 18,327 $ 0.002 $ 28 

2030 18,805 $ 0.002 $ 28 

2031 19,258 $ 0.002 $ 29 

2032 19,695 $ 0.002 $ 30 

2033 20,125 $ 0.002 $ 30 

2034 20,543 $ 0.002 $ 31 

2035 20,940 $ 0.002 $ 32 

2036 21,323 $ 0.002 $ 32 

30 Yr NPV at 3% 182,540 $ 275 

30 Yr NPV at 7% 82,865 $ 124 

* Weighted Maintenance Cost ($/gal) changes year-to-year due to the

implementation schedule for engines adding the CCV system.

8.4.4 Summary of Aggregate Operating Costs

The net operating costs include the incremental costs for fuel (Table 8.4-1), cost savings

from reduced oil changes (Table 8.4-2), costs for CDPF maintenance and regeneration (Table

8.4-3), and costs for CCV maintenance (Table 8.4-4). The results of this summation for the twostep NRT4 program are shown in Table 8.4-5. The oil-change maintenance savings, CDPF

maintenance and regeneration costs, and the CCV maintenance costs are added together in Table

8.4-5 and presented as “Other Operating Costs.” The other operating costs are presented as

negative values because the oil change maintenance savings (negative costs) outweigh the other
Aggregate Cost and Cost per Ton

8-23

operating costs and, thus, their summation represents a net savings. The “Net Operating Cost” is

the sum of the incremental fuel costs shown in Table 8.4-1 and the other operating costs shown

in Tables 8.4-2 through 8.4-4. As shown in Table 8.4-5, the 30-year net present value of the net

operating costs is estimated at $11.8 billion consisting of the $16.3 billion fuel cost and the $4.5

billion savings associated with other operating costs. These net present values assume a three

percent social discount rate.

Also included in Table 8.4-5 are the costs by pollutant (refer to Table 8.1-2 for how these

costs have been allocated). The sum of the SOx cost, the PM cost, and the NOx+NMHC cost is

the value presented in the “Net Operating Cost” column. 

Table 8.4-5

Aggregate Net Operating Costs and Costs by Pollutant

Associated with the NRT4 Program

($2002)

Year Fuel Costs

(106

 dollars)

Other Operating

Costs

 (106

 dollars)

Net Operating

Costs

 (106

 dollars)

SOx Related

Costs

 (106

 dollars)

PM Related

Costs

 (106

 dollars)

NOx+HC

Related Costs

(106

 dollars)

2007 $ 142 $ (161) $ (18) $ (12) $ (6) $ - 

2008 $ 249 $ (282) $ (33) $ (22) $ (11) $ 0 

2009 $ 254 $ (288) $ (34) $ (23) $ (11) $ 0 

2010 $ 561 $ (349) $ 212 $ 88 $ 84 $ 40 

2011 $ 591 $ (302) $ 289 $ 117 $ 118 $ 54 

2012 $ 704 $ (299) $ 406 $ 172 $ 170 $ 64 

2013 $ 797 $ (286) $ 512 $ 217 $ 223 $ 72 

2014 $ 874 $ (294) $ 581 $ 232 $ 259 $ 90 

2015 $ 938 $ (288) $ 650 $ 245 $ 300 $ 105 

2016 $ 954 $ (274) $ 680 $ 249 $ 324 $ 108 

2017 $ 971 $ (261) $ 710 $ 253 $ 347 $ 111 

2018 $ 988 $ (250) $ 738 $ 257 $ 368 $ 114 

2019 $ 1,006 $ (240) $ 766 $ 261 $ 389 $ 116 

2020 $ 1,022 $ (231) $ 791 $ 265 $ 408 $ 119 

2021 $ 1,039 $ (224) $ 815 $ 268 $ 425 $ 122 

2022 $ 1,056 $ (219) $ 838 $ 272 $ 441 $ 124 

2023 $ 1,073 $ (214) $ 859 $ 276 $ 456 $ 127 

2024 $ 1,090 $ (210) $ 880 $ 280 $ 470 $ 129 

2025 $ 1,107 $ (207) $ 900 $ 284 $ 484 $ 132 

2026 $ 1,124 $ (204) $ 920 $ 288 $ 497 $ 134 

2027 $ 1,141 $ (202) $ 938 $ 292 $ 509 $ 137 

2028 $ 1,158 $ (201) $ 956 $ 296 $ 521 $ 139 

2029 $ 1,174 $ (201) $ 974 $ 300 $ 532 $ 141 

2030 $ 1,191 $ (201) $ 991 $ 304 $ 543 $ 144 

2031 $ 1,208 $ (201) $ 1,007 $ 308 $ 553 $ 146 

2032 $ 1,225 $ (201) $ 1,024 $ 312 $ 563 $ 148 

2033 $ 1,242 $ (202) $ 1,040 $ 316 $ 573 $ 151 

2034 $ 1,259 $ (203) $ 1,056 $ 320 $ 583 $ 153 

2035 $ 1,276 $ (204) $ 1,072 $ 324 $ 593 $ 155 

2036 $ 1,293 $ (205) $ 1,088 $ 328 $ 602 $ 157 

30 Yr NPV at 3% $ 16,326 $ (4,517) $ 11,809 $ 3,934 $ 6,091 $ 1,784 

30 Yr NPV at 7% $ 8,538 $ (2,745) $ 5,793 $ 1,976 $ 2,928 $ 889 
Final Regulatory Impact Analysis

8-24

8.4.5 Summary of Aggregate Operating Costs Associated with a Fuel-only Scenario

The aggregate operating costs of a fuel-only scenario would be essentially the same as those

presented above for the full NRT4 program with the exception of those operating costs

associated with maintenance or regeneration of new engine hardware. These operating cost

elements would not be incurred because without new engine standards the new engine hardware

would not be added. However, the oil change maintenance savings would still be realized just as

they would under the full NRT4 program.

As noted several times throughout this chapter, Table 8.1-2 shows how we allocated costs to

each pollutant under the full engine and fuel program. However, the allocations shown in that

table assume an engine program to which a portion of the fuel-related costs are allocated. 

Specifically, the 15 ppm NR fuel, which enables aftertreatment devices and, thus, new NR

engine standards, is split evenly between engine derived benefits and fuel derived benefits. 

Subsequently, the costs allocated to fuel derived benefits were split one-third to PM and twothirds to SOx. 

Under the fuel-only scenario, there are no new engine standards. As a result, all the fuel

costs are allocated to fuel-derived benefits. Consistent with the approach taken in the full engine

and fuel program, we have allocated one-third of those costs to PM and two-thirds of those costs

to SOx. Table 8.4-6 shows the cost allocations under the fuel-only scenario.

Table 8.4-6

Cost Allocations under the Fuel-only Scenario

Item NOx+HC PM SOx

Fuel Costs – incremental cent/gallon 500 ppm Affected NRLM

33% 67%

15 ppm Affected NR

15 ppm Affected L&M

Operating Costs – Oil-Change Savings 500 ppm Affected NRLM

15 ppm Affected NR

15 ppm Affected L&M

Operating Costs – CDPF Maintenance

Operating Costs – CDPF Regen (FE impact) None

Operating Costs – CCV Maintenance

Note that there are no costs associated with CDPF and CCV maintenance or with CDPF

regeneration since there would be no new engine standards under the fuel-only scenario. Note

also that the oil change maintenance savings would still be realized absent any new engine

standards.

Table 8.4-7 presents the net operating costs associated with a fuel-only scenario. The costs

presented in Table 8.4-7 include the incremental costs for fuel (Table 8.4-1) and costs for oilchange maintenance savings (Table 8.4-2). The oil-change maintenance savings are presented in

the table as “Other Operating Costs,” and, thus represent a net savings. The “Net Operating
Aggregate Cost and Cost per Ton

8-25

Cost” is the sum of the incremental fuel costs and the other operating costs. Table 8.4-7 also

presents these costs by pollutant (refer to Table 8.4-6 for how these costs have been allocated). 

Since there are no new engine standards under a fuel-only scenario there are no costs associated

with technology enablement and, hence, no costs allocated to NOx+NMHC. As shown in Table

8.4-7, the 30-year net present value of costs associated with a fuel-only scenario is estimated at

$9.2 billion consisting of the $16.3 billion fuel cost and a $7.1 billion savings associated with oil

change maintenance. These values assume a three percent social discount rate.

Table 8.4-7

Aggregate Net Operating Costs and Costs by Pollutant

Associated with a Fuel-Only Scenario

($2002)

Year Fuel Costs

(106

 dollars)

Other Operating

Costs

 (106

 dollars)

Net Operating

Costs

 (106 dollars)

SOx Related

Costs

 (106 dollars)

PM Related

Costs

 (106 dollars)

NOx+HC Related

Costs

 (106 dollars)

2007 $ 142 $ (161) $ (18) $ (12) $ (6) $ - 

2008 $ 249 $ (282) $ (33) $ (22) $ (11) $ - 

2009 $ 254 $ (288) $ (34) $ (23) $ (11) $ - 

2010 $ 561 $ (349) $ 212 $ 141 $ 71 $ - 

2011 $ 591 $ (310) $ 281 $ 187 $ 94 $ - 

2012 $ 704 $ (322) $ 382 $ 255 $ 127 $ - 

2013 $ 797 $ (333) $ 464 $ 310 $ 155 $ - 

2014 $ 874 $ (353) $ 521 $ 347 $ 174 $ - 

2015 $ 938 $ (370) $ 568 $ 378 $ 189 $ - 

2016 $ 954 $ (377) $ 577 $ 385 $ 192 $ - 

2017 $ 971 $ (384) $ 587 $ 391 $ 196 $ - 

2018 $ 988 $ (391) $ 597 $ 398 $ 199 $ - 

2019 $ 1,006 $ (399) $ 607 $ 405 $ 202 $ - 

2020 $ 1,022 $ (406) $ 617 $ 411 $ 206 $ - 

2021 $ 1,039 $ (412) $ 626 $ 417 $ 209 $ - 

2022 $ 1,056 $ (420) $ 636 $ 424 $ 212 $ - 

2023 $ 1,073 $ (427) $ 646 $ 431 $ 215 $ - 

2024 $ 1,090 $ (434) $ 656 $ 437 $ 219 $ - 

2025 $ 1,107 $ (441) $ 666 $ 444 $ 222 $ - 

2026 $ 1,124 $ (448) $ 676 $ 451 $ 225 $ - 

2027 $ 1,141 $ (455) $ 686 $ 457 $ 229 $ - 

2028 $ 1,158 $ (462) $ 696 $ 464 $ 232 $ - 

2029 $ 1,174 $ (469) $ 706 $ 470 $ 235 $ - 

2030 $ 1,191 $ (476) $ 716 $ 477 $ 239 $ - 

2031 $ 1,208 $ (483) $ 725 $ 484 $ 242 $ - 

2032 $ 1,225 $ (490) $ 735 $ 490 $ 245 $ - 

2033 $ 1,242 $ (497) $ 745 $ 497 $ 248 $ - 

2034 $ 1,259 $ (504) $ 755 $ 503 $ 252 $ - 

2035 $ 1,276 $ (511) $ 765 $ 510 $ 255 $ - 

2036 $ 1,293 $ (518) $ 775 $ 517 $ 258 $ - 

30 Yr NPV at 3% $ 16,326 $ (7,132) $ 9,194 $ 6,130 $ 3,065 $ - 

30 Yr NPV at 7% $ 8,538 $ (3,919) $ 4,618 $ 3,079 $ 1,539 $ - 
Final Regulatory Impact Analysis

8-26

8.5 Summary of Aggregate Costs of the Final Rule

Table 8.5-1 presents a summary of all the costs presented above for the NRT4 final rule

engine and fuel program. Engine costs are the summation of costs presented in Tables 8.2-1 and

8.2-3, equipment costs are the summation of costs presented in Tables 8.3-1 and 8.3-3, and fuel

costs, other operating costs, and net operating costs are presented in Table 8.4-5. The “Total

Program Costs” are the summation of engine costs, equipment costs, and net operating costs. As

shown, the 30-year net present value of the NRT4 program is estimated at $27.1 billion

consisting of $14.1 billion in engine costs, $1.3 billion in equipment costs, $16.3 billion in fuel

costs, and a savings of $4.5 billion in other operating costs. These values assume a three

percent social discount rate.

Table 8.5-2 presents the summary of all the costs presented above by pollutant (refer to Table

8.1-2 for how we have allocated costs among the various pollutants).

Note that a similar summary of aggregate costs associated with a fuel-only scenario are

presented in full in Table 8.4-6 since there are no new engine or equipment costs associated with

that scenario.
Aggregate Cost and Cost per Ton

8-27

Table 8.5-1

Summary of Aggregate Costs for the NRT4 Final Engine and Fuel Program

($Millions of 2002 dollars)

Year Engine

Costs

Equipment

Costs

Fuel Costs Other

Operating

Costs

Net

Operating

Costs

Total

Annual

Costs

2007 $ - $ - $ 142 $ (161) $ (18) $ (18)

2008 $ 81 $ 5 $ 249 $ (282) $ (33) $ 53 

2009 $ 82 $ 5 $ 254 $ (288) $ (34) $ 53 

2010 $ 80 $ 5 $ 561 $ (349) $ 212 $ 297 

2011 $ 403 $ 62 $ 591 $ (302) $ 289 $ 754 

2012 $ 718 $ 106 $ 704 $ (299) $ 406 $ 1,229 

2013 $ 882 $ 121 $ 797 $ (286) $ 512 $ 1,515 

2014 $ 973 $ 146 $ 874 $ (294) $ 581 $ 1,699 

2015 $ 950 $ 149 $ 938 $ (288) $ 650 $ 1,749 

2016 $ 920 $ 150 $ 954 $ (274) $ 680 $ 1,750 

2017 $ 910 $ 150 $ 971 $ (261) $ 710 $ 1,770 

2018 $ 901 $ 146 $ 988 $ (250) $ 738 $ 1,785 

2019 $ 890 $ 147 $ 1,006 $ (240) $ 766 $ 1,802 

2020 $ 900 $ 147 $ 1,022 $ (231) $ 791 $ 1,838 

2021 $ 913 $ 99 $ 1,039 $ (224) $ 815 $ 1,827 

2022 $ 927 $ 66 $ 1,056 $ (219) $ 838 $ 1,830 

2023 $ 940 $ 56 $ 1,073 $ (214) $ 859 $ 1,855 

2024 $ 954 $ 36 $ 1,090 $ (210) $ 880 $ 1,869 

2025 $ 967 $ 32 $ 1,107 $ (207) $ 900 $ 1,899 

2026 $ 980 $ 32 $ 1,124 $ (204) $ 920 $ 1,932 

2027 $ 994 $ 33 $ 1,141 $ (202) $ 938 $ 1,965 

2028 $ 1,007 $ 33 $ 1,158 $ (201) $ 956 $ 1,997 

2029 $ 1,021 $ 33 $ 1,174 $ (201) $ 974 $ 2,028 

2030 $ 1,034 $ 34 $ 1,191 $ (201) $ 991 $ 2,059 

2031 $ 1,048 $ 34 $ 1,208 $ (201) $ 1,007 $ 2,089 

2032 $ 1,061 $ 35 $ 1,225 $ (201) $ 1,024 $ 2,119 

2033 $ 1,074 $ 35 $ 1,242 $ (202) $ 1,040 $ 2,149 

2034 $ 1,088 $ 35 $ 1,259 $ (203) $ 1,056 $ 2,179 

2035 $ 1,101 $ 36 $ 1,276 $ (204) $ 1,072 $ 2,209 

2036 $ 1,115 $ 36 $ 1,293 $ (205) $ 1,088 $ 2,239 

30 Yr NPV at 3% $ 14,054 $ 1,281 $ 16,326 $ (4,517) $ 11,809 $ 27,144 

30 Yr NPV at 7% $ 7,215 $ 754 $ 8,538 $ (2,745) $ 5,793 $ 13,762 
Final Regulatory Impact Analysis

8-28

Table 8.5-2

Summary of Aggregate Costs for the NRT4 Final Engine 

and Fuel Program by Pollutant

($Millions of 2002 dollars)

Year PM Costs NOx+NMHC

Costs

SOx Costs Total Costs

2007 $ (6) $ - $ (12) $ (18)

2008 $ 74 $ 0 $ (22) $ 53 

2009 $ 75 $ 0 $ (23) $ 53 

2010 $ 169 $ 40 $ 88 $ 297 

2011 $ 458 $ 179 $ 117 $ 754 

2012 $ 761 $ 296 $ 172 $ 1,229 

2013 $ 949 $ 348 $ 217 $ 1,515 

2014 $ 940 $ 526 $ 232 $ 1,699 

2015 $ 970 $ 534 $ 245 $ 1,749 

2016 $ 982 $ 519 $ 249 $ 1,750 

2017 $ 999 $ 518 $ 253 $ 1,770 

2018 $ 1,004 $ 524 $ 257 $ 1,785 

2019 $ 1,034 $ 507 $ 261 $ 1,802 

2020 $ 1,059 $ 515 $ 265 $ 1,838 

2021 $ 1,061 $ 497 $ 268 $ 1,827 

2022 $ 1,070 $ 488 $ 272 $ 1,830 

2023 $ 1,088 $ 490 $ 276 $ 1,855 

2024 $ 1,112 $ 477 $ 280 $ 1,869 

2025 $ 1,130 $ 484 $ 284 $ 1,899 

2026 $ 1,153 $ 491 $ 288 $ 1,932 

2027 $ 1,174 $ 498 $ 292 $ 1,965 

2028 $ 1,195 $ 506 $ 296 $ 1,997 

2029 $ 1,215 $ 513 $ 300 $ 2,028 

2030 $ 1,235 $ 520 $ 304 $ 2,059 

2031 $ 1,254 $ 527 $ 308 $ 2,089 

2032 $ 1,273 $ 534 $ 312 $ 2,119 

2033 $ 1,292 $ 541 $ 316 $ 2,149 

2034 $ 1,311 $ 548 $ 320 $ 2,179 

2035 $ 1,330 $ 555 $ 324 $ 2,209 

2036 $ 1,348 $ 562 $ 328 $ 2,239 

30 Yr NPV at 3% $ 16,041 $ 7,169 $ 3,934 $ 27,144 

30 Yr NPV at 7% $ 8,134 $ 3,652 $ 1,976 $ 13,762 
Aggregate Cost and Cost per Ton

8-29

8.6 Emission Reductions

Table 8.6-1 presents the emission reductions estimated to result from the fuel program in

conjunction with the new engine standards. Also presented are reductions associated with a fuelonly scenario. A complete discussion of these emission reductions and how they were generated

can be found in Chapter 3.

Table 8.6-1

Emission Reductions Associated with the NRT4 Final Fuel and Engine Program

and the Fuel-only Scenario (tons)

Year NRT4 Fuel and Engine Program NRLM Fuel-only Program

PM NOx+NMHC SOx PM SOx

2007 10,700 0 133,000 10,700 133,000

2008 19,500 200 235,400 19,000 235,400

2009 20,400 400 240,100 19,400 240,100

2010 22,300 700 255,500 20,600 255,500

2011 25,900 19,100 268,600 21,600 268,600

2012 32,100 49,600 277,800 22,400 277,700

2013 39,200 84,400 285,700 23,000 285,500

2014 46,900 143,600 291,600 23,500 291,500

2015 54,900 203,000 297,400 24,000 297,300

2016 62,400 261,100 302,600 24,400 302,400

2017 69,600 316,900 307,700 24,800 307,500

2018 76,400 368,500 312,900 25,200 312,700

2019 82,800 417,300 318,300 25,600 318,000

2020 88,800 463,000 323,300 26,000 323,100

2021 94,400 504,400 328,300 26,400 328,000

2022 99,700 542,400 333,600 26,900 333,400

2023 104,600 578,100 338,800 27,300 338,500

2024 109,400 611,100 344,000 27,700 343,700

2025 113,900 642,300 349,200 28,100 348,900

2026 118,200 671,400 354,400 28,500 354,100

2027 122,300 698,200 359,600 28,900 359,300

2028 125,900 723,200 364,800 29,400 364,500

2029 129,500 746,900 370,000 29,800 369,700

2030 132,900 768,500 375,300 30,200 374,900

2031 136,000 788,800 380,500 30,600 380,100

2032 139,100 808,400 385,800 31,000 385,400

2033 142,100 827,300 391,000 31,500 390,600

2034 145,000 845,600 396,300 31,900 395,900

2035 147,800 863,100 401,600 32,300 401,200

2036 150,500 880,100 406,900 32,700 406,400

30 Yr NPV at 3% 1,430,500 7,077,900 5,725,900 461,000 5,722,100 

30 Yr NPV at 7% 690,800 3,142,700 3,164,100 254,800 3,162,300 

b

 Note that the SOx reductions for the Final program and the fuel-only scenario are

nearly identical while the PM reductions are very different. This is a result of there being

no new engine standards under the fuel-only scenario and, therefore, no CDPFs added

to new engines. 
Final Regulatory Impact Analysis

8-30

8.7 Cost per Ton

We have calculated the cost per ton of the final rule based on the net present value of all

costs incurred and all emission reductions generated over a 30-year time window following

implementation of the program. This approach captures all the costs and emission reductions

from the final rule, including costs incurred and emission reductions generated by both the new

and the existing fleet. 

The baseline (i.e., the point of comparison) for this evaluation is the existing set of engine

standards (i.e., the Tier 2/Tier 3 program) and fuel standards (i.e., unregulated sulfur level). The

30-year time window is meant to capture both the early period of the program when there are a

small number of compliant engines in the fleet, and the later period when there is nearly

complete turnover to compliant engines. The final rule also requires reduced sulfur content in

NRLM diesel fuel with a 500 ppm cap beginning in 2007, a 15 ppm NR cap beginning in 2010,

and a 15 ppm L&M cap beginning in 2012.

In Section 8.7.1 we present the cost per ton for the NRT4 final engine and fuel

program—this represents the cost per ton of this final rule including all costs and emissions

reductions associated with the new fuel standards and the new engine standards. In Section 8.7.2

we present the cost per ton for the fuel-only scenario—this scenario would include the same fuel

standards as the full engine and fuel program but no new engine standards. In Section 8.7.3 we

present two different sets of cost per ton information—cost per ton of a 500 ppm fuel scenario

should it remain in place forever with no new engine standards, and the incremental cost per ton

of the 15 ppm L&M portion of the fuel program. In Section 8.7.4, we summarize all the cost per

ton calculations presented in Sections 8.7.1 through 8.7.3. In Appendix 8A, we present the cost

per ton of two sensitivity cases—the case 1 sensitivity shows the cost per ton using future

projections of fuel demand developed by the Energy Information Administration; and, the case 2

sensitivity shows the cost per ton if we increase the percentage of mobile versus stationary

generator sets (i.e., increase the number of generator sets that will meet the new standards) and

increase the usage rates for some >750hp equipment. The rationale for choosing these two

sensitivity cases is presented in section 8A.1.

8.7.1 Cost per Ton for the NRT4 Final Rule

The NRT4 final rule adopts fuel requirements in two steps—reducing NRLM sulfur levels

from current uncontrolled levels to 500 ppm in 2007 and then controlling NR fuel and L&M fuel

to 15 ppm in 2010 and 2012, respectively. Beginning June 1, 2007, refiners must produce

NRLM diesel fuel that meets a maximum sulfur level of 500 ppm. Then, beginning in June 1,

2010, NR fuel must meet a maximum sulfur level of 15 ppm and, beginning in June 1, 2012,

L&M fuel must meet a maximum sulfur level of 15 ppm. This program also adopts new Tier 4

engine standards for nonroad diesel engines that begin in different years for different power

categories. See Table 1 in the Executive Summary for details on the new engine standards and

when they are implemented. All nonroad diesel-fueled engines with a CDPF must be refueled

with the new 15 ppm diesel fuel.
Aggregate Cost and Cost per Ton

8-31

The costs of the final rule include costs associated with both steps in the fuel program (500

ppm and 15 ppm) and costs for the engine standards including equipment modifications. 

Maintenance costs and savings realized by both the existing fleet (nonroad, locomotive, and

marine), future locomotive and marine engines, and the new fleet of nonroad engines complying

with the new emissions standards are included. Figure 8.7-1 presents in graphic form the cost of

the final rule. These costs are summarized in Table 8.5-1. The cost streams include the

amortized capital (fixed) costs and variable costs.

Figure 8.7-1

Estimated Aggregate Cost of the NRT4 Final Rule

-$1,000

-$500

$0

$500

$1,000

$1,500

$2,000

$2,500

2004 2008 2012 2016 2020 2024 2028 2032 2036

Year

Program Costs ($Millions)

Engine Costs Equipment Costs Fuel Costs Other Operating Costs Total Program Costs

Figure 8.7-1 shows that total annual costs are estimated to be $50 million in the first year the

new engine standards apply, increasing to $2.2 billion in 2036 as increasing numbers of engines

become subject to the new standards and an ever increasing amount of fuel is consumed. As

shown in Table 8.5-1, the 30-year net present value of the costs for this program is estimated as

$27.1 billion using a three percent discount rate.
Final Regulatory Impact Analysis

8-32

The calculations of cost per ton of each emission reduced under the final program divides the

net present value of the annual costs assigned to each pollutant (see Table 8.5-2 for costs by

pollutant and Table 8.1-2 for how we have allocated costs by pollutant) by the net present value

of the total annual reductions of each pollutant – NOx+NMHC, PM and SOx (see Table 8.6-1).

The net present value of the costs associated with each pollutant, calculated with a three

percent discount rate, are shown in Table 8.5-1 as $7.2 billion for NOx+NMHC, $16.0 billion for

PM and $3.9 billion for SOx. The 30-year net present value, with a three percent discount rate,

of emission reductions are 7.1 million tons for NOx+NMHC, 1.4 million tons for PM and 5.7

million tons for SOx (see Table 8.6-1). Our air quality analysis, emissions reduction analysis,

and benefits analysis are found in Chapters 2, 3, and 9, respectively.

The cost per ton of emissions reduced for the NRT4 final rule is calculated by dividing the

net present value of the annualized costs of the program through 2036 by the net present value of

the annual emission reductions through 2036. These results are shown in Table 8.7-1.
Aggregate Cost and Cost per Ton

8-33

Table 8.7-1

Aggregate Costs and Costs per Ton for the NRT4 Final Rule

30-year Net Present Values at a 3% and 7% Discount Rate ($2002)

Item Units 3% discount rate 7% discount rate Source

500ppm at $0.021/gal, 2007-2010 (106 gallons) 29,690 25,207 Table 8.4-1

500ppm at $0.033/gal, 2010-2012 (106

 gallons) 7,068 5,500 Table 8.4-1

500ppm at $0.035/gal, 2012-2014 (106 gallons) 1,660 1,196 Table 8.4-1

15ppm at $0.058/gal, 2010-2012 (106 gallons) 15,223 11,715 Table 8.4-1

15ppm at $0.064/gal, 2012-2014 (106 gallons) 17,998 12,800 Table 8.4-1

15ppm at $0.070/gal, 2014+ (106

 gallons) 191,091 89,805 Table 8.4-1

500ppm Fuel Cost ($million) $915 $753 Table 8.4-1

15ppm Fuel Cost ($million) $15,411 $7,785 Table 8.4-1

Other Operating Costs* ($million) -$4,517 -$2,745 Table 8.4-5

Engine Costs ($million) $14,054 $7,215 Table 8.5-1

Equipment Costs ($million) $1,281 $754 Table 8.5-1

Total Program Costs ($million) $27,144 $13,762 Table 8.5-1

NOx+NMHC Costs ($million) $7,169 $3,652 Table 8.5-2

PM Costs ($million) $16,041 $8,134 Table 8.5-2

SOx Costs ($million) $3,934 $1,976 Table 8.5-2

NOx+NMHC Reduction (106

 tons) 7.1 3.1 Table 8.6-1

PM Reduction (106

 tons) 1.4 0.7 Table 8.6-1

SOx Reduction (106 tons) 5.7 3.2 Table 8.6-1

Cost per Ton NOx+NMHC ($/ton) $1,010 $1,160 Calculated

Cost per Ton PM ($/ton) $11,200 $11,800 Calculated

Cost per Ton ($/ton) $690 $620 Calculated

* Other operating costs include oil change maintenance savings, CDPF and CCV maintenance costs, and CDPF

regeneration costs.

We have also calculated the cost per ton of emissions reduced in the year 2030 using the

annual costs and emission reductions in that year alone. This number, shown in Table 8.7-2,

approaches the long-term cost per ton of emissions reduced after all fixed costs of the program

have been recovered by industry leaving only the variable costs of control (and maintenance

costs), and after most (though not all) of the pre-control fleet has been retired.
Final Regulatory Impact Analysis

8-34

Table 8.7-3

Long-Term Cost per Ton of the NRT4 Final Rule 

Annual Values without Discounting ($2002)

Pollutant Long-Term Cost per Ton in 2030

NOx+NMHC $680

PM $9,300

SOx $810

8.7.2 Cost per Ton for the NRLM Fuel-only Scenario

The costs of the fuel-only scenario include costs associated with both steps in the fuel

program absent any new engine standards. Oil change maintenance savings would be realized

by both the existing fleet and the new fleet of engines as these savings are not dependent on any

new engine standards. Figure 8.7-2 presents in graphic form the cost of the fuel-only scenario. 

These costs are summarized in Table 8.4-7. The cost streams include the amortized capital

(fixed) costs and variable costs.
Aggregate Cost and Cost per Ton

8-35

Figure 8.7-2

Estimated Aggregate Cost of the NRLM Fuel-only Scenario

$(1,000)

$(500)

$-

$500

$1,000

$1,500

$2,000

$2,500

2004 2008 2012 2016 2020 2024 2028 2032 2036

Year

Program Costs ($Million)

Fuel Costs Other Operating Costs Net Costs

Figure 8.7-2 shows that total annual costs are estimated to be -$33 million in the first full

year of the new fuel standards (i.e., a $33 million savings), increasing to $775 million in 2036 as

an ever increasing amount of fuel is consumed. As shown in Table 8.4-7, the 30-year net present

value of the fuel-only scenario is estimated as $9.2 billion using a three percent discount rate.

The calculations of cost per ton of each emission reduced under the fuel-only scenario

divides the net present value of the annual costs assigned to each pollutant (see Table 8.4-7 for

costs by pollutant and Table 8.4-6 for how we have allocated costs by pollutant) by the net

present value of the total annual reductions of each pollutant. The 30-year net present value of

the costs associated with each pollutant, calculated with a three percent discount rate, are shown

in Table 8.4-7 as $3.1 billion for PM and $6.1 billion for SOx. If we exclude the oil change

maintenance savings, the costs of the fuel-only scenario would be $5.4 billion for PM and $10.9

billion for SOx. The 30-year net present value, with a three percent discount rate, of emission

reductions are 461 thousand tons for PM and 5.7 million tons for SOx. Our air quality analysis,

emissions reduction analysis, and benefits analysis are found in Chapters 2, 3, and 9,
Final Regulatory Impact Analysis

8-36

respectively. Table 8.7-4 presents the cost per ton results for the fuel-only scenario including the

oil change maintenance savings and excluding those savings.

Table 8.7-4

Aggregate Costs and Costs per Ton for the Fuel-only Scenario

30-year Net Present Values at a 3% and 7% Discount Rate ($2002)

Item Units 3% discount

rate

7% discount

rate

Source

500ppm at $0.021/gal, 2007-2010 (106

 gallons) 29,690 25,207 Table 8.4-1

500ppm at $0.033/gal, 2010-2012 (106

 gallons) 7,068 5,500 Table 8.4-1

500ppm at $0.035/gal, 2012-2014 (106 gallons) 1,660 1,196 Table 8.4-1

15ppm at $0.058/gal, 2010-2012 (106

 gallons) 15,223 11,715 Table 8.4-1

15ppm at $0.064/gal, 2012-2014 (106 gallons) 17,998 12,800 Table 8.4-1

15ppm at $0.070/gal, 2014+ (106

 gallons) 191,091 89,805 Table 8.4-1

500ppm Fuel Cost ($million) $915 $753 Table 8.4-1

15ppm Fuel Cost ($million) $15,411 $7,785 Table 8.4-1

Other Operating Costs* ($million) -$4,517 -$2,745 Table 8.4-7

Total Costs (w/ maintenance savings) ($million) $9,194 $4,618 Table 8.4-7

Total Costs (w/o maintenance savings) ($million) $16,326 $8,538 Table 8.4-7

PM Costs (w/ maintenance savings) ($million) $3,065 $1,539 Table 8.4-7

PM Costs (w/o maintenance savings) ($million) $5,442 $2,846 Calculated**

SOx Costs (w/ maintenance savings) ($million) $6,130 $3,079 Table 8.4-7

SOx Costs (w/o maintenance savings) ($million) $10,884 $5,692 Calculated**

PM Reduction (106

 tons) 0.46 0.26 Table 8.6-1

SOx Reduction (106

 tons) 5.7 3.2 Table 8.6-1

Cost per Ton PM (w/ maintenance savings) ($/ton) $6,600 $6,000 Calculated

Cost per Ton PM (w/o maintenance savings) ($/ton) $11,800 $11,200 Calculated

Cost per Ton SOx (w/ maintenance savings) ($/ton) $1,070 $970 Calculated

Cost per Ton Sox (w/o maintenance savings) ($/ton) $1,900 $1,800 Calculated

* Other operating costs include oil change maintenance savings.

** Calculated as one-third (PM) or two-thirds (SOx) of the Total Scenario Costs w/o maintenance savings.

We have also calculated the cost per ton of emissions reduced in the year 2030 using the

annual costs and emission reductions in that year alone. This number, shown in Table 8.7-5,

approaches the long-term cost per ton of emissions reduced.
Aggregate Cost and Cost per Ton

8-37

Table 8.7-5

Long-Term Cost per Ton of the NRT4 Fuel-only Scenario 

Annual Values without Discounting ($2002)

Pollutant Long-Term Cost per Ton in 2030

PM (with maintenance savings) $7,900

PM (without maintenance savings) $13,200

SOx (with maintenance savings) $1,270

SOx (without maintenance savings) $2,100

8.7.3 Costs and Costs per Ton for Other Control Scenarios

Here we look at the costs and costs per ton of other control scenarios. Specifically, we look

at the cost per ton of the 500 ppm NRLM fuel scenario should it continue forever without any

new engine standards. We also look at the incremental cost per ton of the 15 ppm L&M fuel

scenario.

8.7.3.1 Costs and Costs per Ton of a 500 ppm NRLM Fuel-only Scenario

A 500 ppm NRLM fuel-only scenario would mirror the fuel-only scenario discussed above

with the exception that no 15 ppm fuel step would occur. The incremental fuel cost would be

$0.021 per gallon during the years 2007 through 2010 and then $0.022 per gallon thereafter (see

Table 7.5-1). The oil change maintenance savings would be $0.029 per gallon for NR and

$0.010 per gallon for L&M (see Table 8.4-2). Tables 8.7-6 and 8.7-7 present the fuel costs and

oil change maintenance savings, respectively, associated with a 500 ppm NRLM fuel-only

scenario.
Final Regulatory Impact Analysis

8-38

Table 8.7-6

Aggregate Fuel Costs of a 500 ppm NRLM Fuel-only Scenario ($2002)

Year Affected NR Fuel Affected L&M Fuel Fuel Cost* NRLM Fuel Costs

(106 500 ppm dollars)

(106

 gallons)

500 ppm

(106 gallons)

500 ppm

($/gal)

2007 4,790 1,990 $ 0.021 $ 142 

2008 8,406 3,454 $ 0.021 $ 249 

2009 8,599 3,498 $ 0.021 $ 254 

2010 8,400 3,457 $ 0.022 $ 256 

2011 8,300 3,450 $ 0.022 $ 258 

2012 8,479 3,489 $ 0.022 $ 263 

2013 8,659 3,518 $ 0.022 $ 268 

2014 8,839 3,552 $ 0.022 $ 273 

2015 9,018 3,586 $ 0.022 $ 277 

2016 9,196 3,623 $ 0.022 $ 282 

2017 9,374 3,659 $ 0.022 $ 287 

2018 9,552 3,699 $ 0.022 $ 292 

2019 9,730 3,747 $ 0.022 $ 296 

2020 9,907 3,781 $ 0.022 $ 301 

2021 10,085 3,812 $ 0.022 $ 306 

2022 10,263 3,859 $ 0.022 $ 311 

2023 10,441 3,897 $ 0.022 $ 315 

2024 10,619 3,939 $ 0.022 $ 320 

2025 10,797 3,980 $ 0.022 $ 325 

2026 10,973 4,022 $ 0.022 $ 330 

2027 11,150 4,064 $ 0.022 $ 335 

2028 11,326 4,106 $ 0.022 $ 340 

2029 11,503 4,148 $ 0.022 $ 344 

2030 11,679 4,190 $ 0.022 $ 349 

2031 11,856 4,232 $ 0.022 $ 354 

2032 12,032 4,275 $ 0.022 $ 359 

2033 12,209 4,318 $ 0.022 $ 364 

2034 12,386 4,360 $ 0.022 $ 368 

2035 12,562 4,403 $ 0.022 $ 373 

2036 12,739 4,447 $ 0.022 $ 378 

30 Yr NPV at 3% 179,520 68,639 $ 5,428 

30 Yr NPV at 7% 99,928 38,879 $ 3,027 

* Fuel costs are relative to uncontrolled fuel and assume that, during the transitional years of 2010 & 2014, the first 5

months are at the previous year's cost and the remaining 7 months are at the next year's cost.

See Appendix 8B for how these fuel volumes were developed.
Aggregate Cost and Cost per Ton

8-39

Table 8.7-7

Oil-Change Maintenance Savings Associated with a 500 ppm NRLM Fuel-only Scenario

($2002)

Year

Affected NR Fuel Affected L&M Fuel NR Savings L&M Savings NRLM

Total Savings

(106

 dollars) 500 ppm

(106

 gallons)

500 ppm

(106 gallons)

savings=$0.029/gal

(106 dollars)

savings=$0.010/gal

(106 dollars)

2007 4,790 1,990 $ 140 $ 21 $ 161 

2008 8,406 3,454 $ 246 $ 36 $ 282 

2009 8,599 3,498 $ 251 $ 37 $ 288 

2010 8,400 3,457 $ 246 $ 36 $ 282 

2011 8,300 3,450 $ 243 $ 36 $ 279 

2012 8,479 3,489 $ 248 $ 37 $ 284 

2013 8,659 3,518 $ 253 $ 37 $ 290 

2014 8,839 3,552 $ 258 $ 37 $ 296 

2015 9,018 3,586 $ 264 $ 38 $ 301 

2016 9,196 3,623 $ 269 $ 38 $ 307 

2017 9,374 3,659 $ 274 $ 38 $ 312 

2018 9,552 3,699 $ 279 $ 39 $ 318 

2019 9,730 3,747 $ 284 $ 39 $ 324 

2020 9,907 3,781 $ 290 $ 40 $ 329 

2021 10,085 3,812 $ 295 $ 40 $ 335 

2022 10,263 3,859 $ 300 $ 40 $ 340 

2023 10,441 3,897 $ 305 $ 41 $ 346 

2024 10,619 3,939 $ 310 $ 41 $ 352 

2025 10,797 3,980 $ 316 $ 42 $ 357 

2026 10,973 4,022 $ 321 $ 42 $ 363 

2027 11,150 4,064 $ 326 $ 43 $ 369 

2028 11,326 4,106 $ 331 $ 43 $ 374 

2029 11,503 4,148 $ 336 $ 43 $ 380 

2030 11,679 4,190 $ 341 $ 44 $ 385 

2031 11,856 4,232 $ 347 $ 44 $ 391 

2032 12,032 4,275 $ 352 $ 45 $ 397 

2033 12,209 4,318 $ 357 $ 45 $ 402 

2034 12,386 4,360 $ 362 $ 46 $ 408 

2035 12,562 4,403 $ 367 $ 46 $ 413 

2036 12,739 4,447 $ 372 $ 47 $ 419 

30 Yr NPV at 3% 179,520 68,639 $ 5,248 $ 719 $ 5,967 

30 Yr NPV at 7% 99,928 38,879 $ 2,921 $ 407 $ 3,328 

Table 8.7-8 presents the annual net operating costs (Tables 8.7-6 and 8.7-7) along with the

costs by pollutant associated with a 500 ppm NRLM fuel-only scenario. Because a 500 ppm

NRLM fuel-only scenario is analogous to the NRT4 fuel-only scenario discussed above (i.e., no

new engine standards and, thus, only fuel-derived benefits will occur), we would allocate costs

to PM and SOx the same way as the NRT4 fuel-only scenario (see Table 8.4-6) except that costs

for 15 ppm fuel would clearly be zero. Table 8.7-8 also presents the emission reductions that

would result from a 500 ppm NRLM fuel-only scenario.
Final Regulatory Impact Analysis

8-40

Table 8.7-8

Aggregate Net Operating Costs, Costs by Pollutant, and Emissions Reductions

Associated with a 500 ppm NRLM Fuel-only Scenario ($2002)

Year Fuel Costs

($million)

Other Operating

Costs ($million)

Net Operating

Costs ($million)

SOx Costs

($million)

PM Costs

($million)

PM Reduction

(tons)

SOx Reduction

(tons)

2007 $ 142 $ (161) $ (18) $ (12) $ (6) 10,700 133,000 

2008 $ 249 $ (282) $ (33) $ (22) $ (11) 19,000 235,400 

2009 $ 254 $ (288) $ (34) $ (23) $ (11) 19,400 240,100 

2010 $ 256 $ (282) $ (26) $ (17) $ (9) 19,700 244,000 

2011 $ 258 $ (279) $ (20) $ (14) $ (7) 20,000 248,500 

2012 $ 263 $ (284) $ (21) $ (14) $ (7) 20,400 253,100 

2013 $ 268 $ (290) $ (22) $ (15) $ (7) 20,800 257,600 

2014 $ 273 $ (296) $ (23) $ (15) $ (8) 21,100 262,200 

2015 $ 277 $ (301) $ (24) $ (16) $ (8) 21,500 266,700 

2016 $ 282 $ (307) $ (25) $ (17) $ (8) 21,900 271,300 

2017 $ 287 $ (312) $ (26) $ (17) $ (9) 22,200 275,800 

2018 $ 292 $ (318) $ (26) $ (18) $ (9) 22,600 280,400 

2019 $ 296 $ (324) $ (27) $ (18) $ (9) 23,000 285,200 

2020 $ 301 $ (329) $ (28) $ (19) $ (9) 23,300 289,700 

2021 $ 306 $ (335) $ (29) $ (19) $ (10) 23,700 294,200 

2022 $ 311 $ (340) $ (30) $ (20) $ (10) 24,100 299,000 

2023 $ 315 $ (346) $ (31) $ (20) $ (10) 24,500 303,600 

2024 $ 320 $ (352) $ (31) $ (21) $ (10) 24,800 308,200 

2025 $ 325 $ (357) $ (32) $ (21) $ (11) 25,200 312,900 

2026 $ 330 $ (363) $ (33) $ (22) $ (11) 25,600 317,500 

2027 $ 335 $ (369) $ (34) $ (23) $ (11) 25,900 322,200 

2028 $ 340 $ (374) $ (35) $ (23) $ (12) 26,300 326,800 

2029 $ 344 $ (380) $ (35) $ (24) $ (12) 26,700 331,500 

2030 $ 349 $ (385) $ (36) $ (24) $ (12) 27,100 336,200 

2031 $ 354 $ (391) $ (37) $ (25) $ (12) 27,400 340,800 

2032 $ 359 $ (397) $ (38) $ (25) $ (13) 27,800 345,500 

2033 $ 364 $ (402) $ (39) $ (26) $ (13) 28,200 350,200 

2034 $ 368 $ (408) $ (39) $ (26) $ (13) 28,600 354,900 

2035 $ 373 $ (413) $ (40) $ (27) $ (13) 29,000 359,700 

2036 $ 378 $ (419) $ (41) $ (27) $ (14) 29,300 364,400 

30 Yr NPV at 3% $ 5,428 $ (5,967) $ (539) $ (359) $ (180) 419,800 5,210,600 

30 Yr NPV at 7% $ 3,027 $ (3,328) $ (301) $ (201) $ (100) 233,800 2,901,700 

The calculations of cost per ton of each emission reduced under the 500 ppm NRLM fuelonly scenario divides the net present value of the annual costs assigned to each pollutant (see

Table 8.7-8) by the net present value of the total annual reductions of each pollutant (Table 8.7-

8). The 30-year net present value of the costs (remember that negative costs are actually

savings) associated with each pollutant, calculated with a three percent discount rate, are shown

in Table 8.7-8 as -$107 million for PM and -$213 million for SOx. If we exclude the oil change

maintenance savings, the costs of the fuel-only scenario would be $1.9 billion for PM and $3.8

billion for SOx. The 30-year net present value, with a three percent discount rate, of emission

reductions are 420 thousand tons for PM and 5.2 million tons for SOx. Our air quality analysis,
Aggregate Cost and Cost per Ton

8-41

emissions reduction analysis, and benefits analysis are found in Chapters 2, 3, and 9,

respectively. Table 8.7-9 presents the cost per ton results for the 500 ppm NRLM fuel-only

scenario including the oil change maintenance savings and excluding those savings.

Table 8.7-9

Aggregate Cost per Ton for the 500 ppm NRLM Fuel-only Scenario

30-year Net Present Values at a 3% and 7% Discount Rate ($2002)

Item Units 3% discount

rate

7% discount

rate

Source

500ppm at $0.021/gal, 2007-2010 (106 gallons) 31,316 26,500 Table 8.7-6

500ppm at $0.022/gal, 2010+ (106 gallons) 216,843 112,307 Table 8.7-6

500ppm Fuel Cost ($million) $5,428 $3,027 Table 8.7-6

Other Operating Costs* ($million) -$5,967 -$3,328 Table 8.7-7

Total Costs (w/ maintenance savings) ($million) -$539 -$301 Table 8.7-7

Total Costs (w/o maintenance savings) ($million) $5,428 $3,027 Table 8.7-7

PM Costs (w/ maintenance savings) ($million) -$180 -$100 Table 8.7-8

PM Costs (w/o maintenance savings) ($million) $1,809 $1,009 Calculated**

SOx Costs (w/ maintenance savings) ($million) -$359 -$201 Table 8.7-8

SOx Costs (w/o maintenance savings) ($million) $3,619 $2,018 Calculated**

PM Reduction (106

 tons) 0.42 0.23 Table 8.7-8

SOx Reduction (106 tons) 5.2 2.9 Table 8.7-8

Cost per Ton PM (w/ maintenance savings) ($/ton) -$400 -$400 Calculated

Cost per Ton PM (w/o maintenance savings) ($/ton) $4,300 $4,400 Calculated

Cost per Ton SOx (w/ maintenance savings) ($/ton) -$70 -$70 Calculated

Cost per Ton Sox (w/o maintenance savings) ($/ton) $690 $700 Calculated

* Other operating costs include oil change maintenance savings.

** Calculated as one-third (PM) or two-thirds (SOx) of the Total Scenario Costs w/o maintenance savings.

We have also calculated the cost per ton of emissions reduced in the year 2030 using the

annual costs and emission reductions in that year alone. This number, shown in Table 8.7-10,

approaches the long-term cost per ton of emissions reduced.
Final Regulatory Impact Analysis

8-42

Table 8.7-10

Long-Term Cost per Ton of the 500 ppm NRLM Fuel-only Scenario 

Annual Values without Discounting ($2002)

Pollutant Long-Term Cost per Ton in 2030

PM (with maintenance savings) -$400

PM (without maintenance savings) $4,300

SOx (with maintenance savings) -$70

SOx (without maintenance savings) $690

8.7.3.2 Costs and Costs per Ton of the 15 ppm L&M Fuel Increment

In this section, we evaluate the incremental cost per ton of the 15 ppm L&M fuel cap in 2012

(final NRLM program) relative to retaining the 500 ppm cap on L&M fuel (the proposed NRLM

program) indefinitely. Nonroad diesel fuel is assumed to be subject to a 15 ppm cap starting in

2010 in both cases. We assume that the emission standards applicable to nonroad engines are

the same regardless of the sulfur cap applicable to L&M fuel. Therefore, the only differences

between the 500 and 15 ppm cap on L&M fuel are in emissions of SO2 and sulfate PM, fuel costs

and engine maintenance savings. The cost of complying with emission standards for land-based

nonroad equipment, as well as HC, NOx, and non-sulfate PM emissions from this equipment are

unaffected. 

The difference in costs between the two L&M fuel caps are primarily related to the

production 15 ppm L&M fuel. The differences in sulfurous emissions arise from differences in

the sulfur content of both L&M fuel and, in the Northeast/Middle Atlantic area, heating oil. 

While the difference in heating oil sulfur content is a direct result of the final NRLM fuel

provisions for the Northeast/Middle Atlantic area, heating oil sulfur content is not directly

regulated by this final rule. Therefore, we develop estimates of the incremental cost

effectiveness of the 15 ppm L&M fuel cap both with and without the changes in heating oil

sulfur. However, we believe that the most appropriate estimate of the incremental cost

effectiveness of the 15 ppm L&M fuel cap is that including the change in heating oil sulfur

content. 

The key inputs to this sensitivity analysis are: 1) the volumes and sulfur contents of each type

of distillate fuel being produced and consumed in the 2012-2036 timeframe, and 2) the cost of

supplying these fuels over the same timeframe. The fuels produced prior to June 1, 2012 are

identical under the two scenarios being evaluated here. Thus, we ignore all emissions and costs

prior to June 1, 2012. This incremental analysis models the U.S. minus California., although it

would also apply for the total U.S. as well since California’s fuel quality is not expected to

change with the requirement that L&M fuel meet a 15 ppm cap. 
Aggregate Cost and Cost per Ton

8-43

The process for estimating the annual production volumes of each fuel was described in

Chapter 7. The first step in the process was to develop a comprehensive description of fuel

production and demand in 2001 for non-highway and highway diesel fuel which accounted for

the spillover of low sulfur, highway fuel into the non-highway markets. The analysis also

considered the downgrade of jet fuel and highway diesel fuel, along with some gasoline, to lower

quality fuels during pipeline distribution. 

We then developed a set of analogous estimates for 2014, starting with demand. Fuel

demand in 2014 was projected using the EPA draft NONROAD2004 model and EIA’s AEO

2003. We also estimated the volume of highway diesel fuel demand considering the highway

diesel fuel requirements being implemented in 2006 and 2010. Spillover of highway fuel into

the non-highway markets was assumed to remain constant (in terms of the percentage of each

non-highway market represented by spillover). The volume of gasoline, jet fuel and highway

diesel fuel in 2014 downgraded to 500 ppm and high sulfur distillate was projected to increase in

proportion to the growth in jet fuel demand and the supply of highway diesel fuel. This

downgraded fuel was first distributed to the non-highway fuel markets assuming sulfur controls

on highway fuel only, followed by the 500 ppm standard on NRLM fuel in 2007 and subsequent

15 ppm standards on nonroad fuel and L&M fuel in 2010 and 2012, respectively. NRLM fuel

not already complying with the required sulfur limit prior to the NRLM rule from spillover of

highway fuel or downgrade, had to be desulfurized at refineries. 

We then used these 2014 estimates of fuel production, downgrade and spillover to develop

similar estimates for individual calendar years starting with 2007 and going through 2040

consistent with the phase of NRLM program in place at the time. These individual, annual

estimates were based on a slightly more approximate methodology which assumed that the

fraction of each non-highway distillate fuel’s market demand represented by spillover and

downgrade remained constant at its 2014 level. Regarding spillover, this is the same assumption

made in developing our estimate of spillover in 2014. However, with respect to downgrade, this

assumption differs from that used in the more comprehensive 2014 analysis. Because the

demand for jet fuel and highway diesel fuel is projected to grow faster than that for NRLM fuel

and heating oil, the percentage of downgrade in the NRLM and heating oil markets is higher in

2014 than in 2001. Thus, the net effect of assuming that the percentage of downgrade remains

constant at 2014 levels underestimates the percentage of downgrade in the non-highway fuel

markets after 2014, and overestimates it prior to 2014. 

The effect of assuming constant downgrade percentages in the non-highway markets on the

estimated costs and benefits of the overall rule is very small, given that it affects only a small

portion of the overall fuel demanded, that none of the benefits of the engine emission standards

are involved and that the changes in costs and benefits are offsetting. However, it has a larger

impact on this incremental analysis, as about half of the 30-year sulfur dioxide emission benefits

of the 15 ppm L&M cap are due to a shift in downgrade from the L&M fuel market to the

heating oil market in the Northeast/Middle Atlantic area. Thus, for this incremental analysis, we

revised the assumption that the downgrade fraction of the demand for the various non-highway

fuels for years other than 2014 will remain constant at their 2014 levels. Instead, we estimated

the volume of downgrade generated each year, based on future highway diesel fuel supply and
Final Regulatory Impact Analysis

8-44

jet fuel demand. We made one simplifying assumption: that highway diesel fuel supply grew at

the same rate as highway fuel demand. Highway fuel supply includes spillover to the nonhighway fuel markets. While nonroad fuel demand is projected to grow at roughly the same rate

as highway fuel, L&M fuel and heating oil demand are expected to grow much more slowly. 

Thus, this simplifying assumption overestimates highway fuel supply. However, the degree of

overestimation is slight, since only about 10% of highway diesel fuel supply is spillover to the

non-highway pool, and about 70% of that goes to the nonroad fuel market. 

Estimates of the demand for highway and jet fuel through 2025 are taken from EIA’s AEO

2003. After 2025 the yearly projected demand for both highway diesel fuel and jet fuel are

estimated from the average projected growth from AEO 2003 between 2020 and 2025. The

year-over-year growth rates for highway and jet fuel from 2020 to 2025 were 1.019 and 1.021,

respectively. The annual demand for highway and jet fuel from 2012 to 2036 and the volume

ratios to the projected 2014 volumes are summarized in Table 8.7-11. In last column of Table

8.7-11 an average set of volume ratios are shown which represents the combined growth for

highway and jet-based downgrade in heating oil. The relative volume of highway and jet-based

downgrade was similar in NRLM diesel fuel, so these volume ratios were used for estimating

non-2014 downgrade volumes for NRLM diesel fuel as well. 
Aggregate Cost and Cost per Ton

8-45

Table 8.7-11

Projected Highway Diesel Fuel and Jet Fuel Demand - AEO 2003 (Trillion BTU)

Year Highway Jet Fuel Avg Ratio to

2014 Fuel Demand Ratio to 2014 Fuel Demand Ratio to 2014

2012 7,500 0.957 4,140 0.945 0.954

2013 7,670 0.978 4,260 0.973 0.977

2014 7,840 1.000 4,380 1.000 1.000

2015 7,980 1.018 4,500 1.027 1.020

2016 8,110 1.034 4,620 1.055 1.039

2017 8,250 1.052 4,730 1.080 1.059

2018 8,390 1.070 4,860 1.110 1.079

2019 8,560 1.092 4,970 1.135 1.102

2020 8,700 1.110 5,090 1.162 1.122

2021 8,850 1.129 5,200 1.187 1.142

2022 9,020 1.151 5,310 1.212 1.165

2023 9,200 1.173 5,430 1.240 1.189

2024 9,400 1.199 5,540 1.265 1.214

2025 9,580 1.222 5,660 1.292 1.238

2026 9,762 1.245 5,780 1.319 1.262

2027 9,947 1.269 5,900 1.347 1.287

2028 10,140 1.293 6,020 1.375 1.312

2029 10,330 1.317 6,150 1.404 1.338

2030 10,530 1.343 6,280 1.434 1.364

2031 10,730 1.368 6,410 1.464 1.390

2032 10,930 1.394 6,550 1.495 1.417

2033 11,140 1.421 6,680 1.526 1.445

2034 11,350 1.447 6,820 1.558 1.473

2035 11,560 1.475 6,970 1.591 1.502

2036 11,780 1.503 7,110 1.624 1.531

The next step is to estimate the annual demand, spillover, downgrade and production

volumes for NRLM fuel from 2012 to 2036 for both the proposed and final rule NRLM

programs. Starting with the proposed NRLM fuel program, we estimated the jet and highwaybased downgrade in the nonroad, locomotive and marine fuel markets from mid-2012 to mid2014 by multiplying the 2014 highway and jet-based downgrade volumes shown in Table 7.1.4-1

by the ratio of highway and jet fuel demand in each year to 2014 from Table 8.7-11,

respectively. For the years following 2014, we multiplied the 2014 highway and jet-based

downgrade volumes shown in Table 7.1.4-2 by the ratio of highway and jet fuel demand in each

year to 2014 from Table 8.7-11, respectively. Annual demand for NRLM fuel, and the

contribution of spillover and small refiner fuel to these markets, were estimated by multiplying

the 2014 estimates of these volumes in Tables 7.1.4-1 (for 2012-2014) and 7.1.4-2 (for 2015 and

beyond) by the growth in NRLM fuel demand contained in Tables 7.1.5-1 (for nonroad and

locomotive fuel) and 7.1.5-2 (for marine fuel). Annual production volumes of NRLM fuel were
Final Regulatory Impact Analysis

8-46

estimated by subtracting the downgrade, spillover and small refiner fuel volumes from total

demand. The resulting estimates of downgrade, spillover, small refiner fuel, and 15 and 500

ppm production volumes for nonroad, locomotive and marine diesel fuel for the proposed rule

program are summarized in Tables 8.7-12, 8.7-13 and 8.7-14, respectively. The highway-based

and jet fuel-based downgrade volumes are combined together into one column. 

Table 8.7-12

Nonroad Fuel Supply Under the Proposed NRLM Fuel Program With 

the Shift of Downgrade to the Heating Oil Market (million gallons) *

Year Downgrade Small Refiner Fuel Spillover New 15 ppm Fuel Total Volume

2012 1,061 627 2,760 8,327 12,774

2013 1,085 640 2,818 8,501 13,045

2014 463 272 2,940 9,641 13,316

2015 0 0 3,047 10,539 13,586

2016 0 0 3,107 10,747 13,854

2017 0 0 3,167 10,955 14,122

2018 0 0 3,227 11,162 14,390

2019 0 0 3,288 11,370 14,658

2020 0 0 3,352 11,578 14,926

2021 0 0 3,408 11,786 15,193

2022 0 0 3,468 11,993 15,461

2023 0 0 3,528 12,201 15,729

2024 0 0 3,588 12,409 15,997

2025 0 0 3,648 12,616 16,265

2026 0 0 3,708 12,823 16,531

2027 0 0 3,767 13,029 16,797

2028 0 0 3,827 13,236 17,063

2029 0 0 3,887 13,443 17,329

2030 0 0 3,946 13,649 17,595

2031 0 0 4,006 13,855 17,861

2032 0 0 4,066 14,062 18,127

2033 0 0 4,125 14,268 18,393

2034 0 0 4,185 14,474 18,659

2035 0 0 4,245 14,681 18,925

2036 0 0 4,304 14,887 19,191

* Excludes NRLM fuel demand in California
Aggregate Cost and Cost per Ton

8-47

Table 8.7-13

Locomotive Volumes Under the Proposed NRLM Fuel Program With the Shift of Downgrade to

the Heating Oil Market (million gallons) *

Year Downgrade New 500 ppm Fuel Spillover Total Volume 

2012 579 1,705 602 2,886 

2013 593 1,710 607 2,909 

2014 1,176 1,190 566 2,932 

2015 1,614 804 539 2,956 

2016 1,644 800 544 2,988 

2017 1,675 791 549 3,015 

2018 1,707 777 554 3,038 

2019 1,743 766 559 3,067 

2020 1,775 751 563 3,089 

2021 1,807 731 566 3,104 

2022 1,843 719 571 3,132 

2023 1,881 703 576 3,160 

2024 1,921 686 581 3,187 

2025 1,959 673 586 3,218 

2026 1,997 656 591 3,244 

2027 2,036 638 596 3,270 

2028 2,076 619 601 3,295 

2029 2,116 600 605 3,321 

2030 2,157 580 610 3,347 

2031 2,199 559 615 3,373 

2032 2,242 537 619 3,399 

2033 2,286 515 624 3,425 

2034 2,330 491 629 3,450 

2035 2,376 467 634 3,476 

2036 2,422 442 638 3,502 

* Excludes NRLM fuel demand in California
Final Regulatory Impact Analysis

8-48

Table 8.7-14

Marine Volumes Under the Proposed NRLM Fuel Program With the Shift of Downgrade to the

Heating Oil Market (million gallons) *

Year Downgrade New 500 ppm Fuel Spillover Total Volume

2012 446 1,333 280 2,059 

2013 456 1,338 283 2,078 

2014 451 1,369 281 2,103 

2015 436 1,409 280 2,126 

2016 445 1,419 283 2,146 

2017 453 1,431 286 2,170 

2018 462 1,451 290 2,203 

2019 471 1,473 295 2,240 

2020 480 1,488 299 2,266 

2021 489 1,503 302 2,294 

2022 498 1,526 307 2,331 

2023 509 1,538 311 2,357 

2024 519 1,555 315 2,389 

2025 530 1,568 319 2,417 

2026 540 1,585 323 2,448 

2027 551 1,602 327 2,479 

2028 561 1,618 331 2,510 

2029 572 1,634 335 2,542 

2030 583 1,650 339 2,573 

2031 595 1,666 343 2,604 

2032 606 1,682 347 2,635 

2033 618 1,697 352 2,667 

2034 630 1,712 356 2,698 

2035 642 1,727 360 2,729 

2036 655 1,742 364 2,760 

* Excludes NRLM fuel demand in California

Annual estimates of downgrade, spillover, small refiner fuel, and 15 and 500 ppm production

volumes under the final NRLM fuel program in years other than 2014 were estimated from the

estimates for 2014 in the same manner. The only difference is a new set of 2014 estimates. The

2014 estimates of downgrade, spillover, small refiner fuel, and total demand for NRLM fuel for

mid-2012 to mid-2014 were taken from Table 7.1.3-19. The 2014 estimates of downgrade,

spillover, small refiner fuel, and total demand for NRLM fuel for 2015 and beyond were taken

from Table 7.1.3-20. The resulting estimates of downgrade, spillover, small refiner fuel, and 15

and 500 ppm production volumes for nonroad, locomotive and marine diesel fuel for the

proposed rule program are summarized in Tables 8.7-15, 8.7-16 and 8.7-17, respectively.
Aggregate Cost and Cost per Ton

8-49

Table 8.7-15

Nonroad Fuel Supply Under the Final Rule Fuel Program With the Shift of Downgrade to the

Heating Oil Market (million gallons) *

Year Downgrade Small Refiner Fuel Spillover New 15 ppm Fuel Total Volume 

2012 1,061 528 2,760 8,426 12,774 

2013 1,085 468 2,818 8,674 13,045 

2014 463 199 2,941 9,713 13,316 

2015 - - 3,047 10,539 13,586 

2016 - - 3,107 10,747 13,854 

2017 - - 3,167 10,955 14,122 

2018 - - 3,227 11,162 14,390 

2019 - - 3,288 11,370 14,658 

2020 - - 3,352 11,578 14,926 

2021 - - 3,408 11,786 15,193 

2022 - - 3,468 11,993 15,461 

2023 - - 3,528 12,201 15,729 

2024 - - 3,588 12,409 15,997 

2025 - - 3,648 12,616 16,265 

2026 - - 3,708 12,823 16,531 

2027 - - 3,767 13,029 16,797 

2028 - - 3,827 13,236 17,063 

2029 - - 3,887 13,443 17,329 

2030 - - 3,946 13,649 17,595 

2031 - - 4,006 13,855 17,861 

2032 - - 4,066 14,062 18,127 

2033 - - 4,125 14,268 18,393 

2034 - - 4,185 14,474 18,659 

2035 - - 4,245 14,681 18,925 

2036 - - 4,304 14,887 19,191 

* Excludes NRLM fuel demand in California
Final Regulatory Impact Analysis

8-50

Table 8.7-16

Locomotive Fuel Supply Under the Final Rule Fuel Program With the Shift of Downgrade to the

Heating Oil Market (million gallons) *

Year Downgrade Small Refiner Fuel Spillover New 15 ppm Fuel Total Volume 

2012 397 761 602 1,127 2,841 

2013 274 99 607 1,930 2,909 

2014 849 42 589 1,476 2,932 

2015 1,281 - 577 1,099 2,956 

2016 1,304 - 583 1,100 2,988 

2017 1,329 - 589 1,098 3,015 

2018 1,355 - 593 1,090 3,038 

2019 1,383 - 599 1,086 3,067 

2020 1,408 - 603 1,069 3,089 

2021 1,434 - 606 1,053 3,104 

2022 1,462 - 611 1,058 3,132 

2023 1,492 - 617 1,051 3,160 

2024 1,524 - 622 1,041 3,187 

2025 1,554 - 628 1,035 3,218 

2026 1,585 - 633 1,026 3,244 

2027 1,616 - 638 1,016 3,270 

2028 1,647 - 643 1,005 3,295 

2029 1,679 - 648 994 3,321 

2030 1,712 - 653 982 3,347 

2031 1,745 - 658 969 3,373 

2032 1,779 - 663 956 3,399 

2033 1,814 - 668 942 3,425 

2034 1,849 - 674 928 3,450 

2035 1,885 - 679 912 3,476 

2036 1,922 - 684 897 3,502 

* Excludes NRLM fuel demand in California
Aggregate Cost and Cost per Ton

8-51

Table 8.7-17

Marine Fuel Supply Under the Final Rule Fuel Program With the Shift of Downgrade to the

Heating Oil Market (million gallons) *

Year Downgrade Small Refiner Fuel Spillover New 15 ppm Fuel Total Volume

2012 285 636 280 874 2,059 

2013 173 148 283 1,474 2,078 

2014 155 62 281 1,605 2,103 

2015 141 - 280 1,705 2,126 

2016 143 - 283 1,720 2,146 

2017 146 - 286 1,738 2,170 

2018 149 - 290 1,763 2,203 

2019 152 - 295 1,793 2,240 

2020 155 - 299 1,813 2,266 

2021 158 - 302 1,834 2,294 

2022 161 - 307 1,863 2,331 

2023 164 - 311 1,883 2,357 

2024 168 - 315 1,906 2,389 

2025 171 - 319 1,927 2,417 

2026 174 - 323 1,951 2,448 

2027 178 - 327 1,975 2,479 

2028 181 - 331 1,998 2,510 

2029 185 - 335 2,022 2,542 

2030 188 - 339 2,046 2,573 

2031 192 - 343 2,069 2,604 

2032 196 - 347 2,092 2,635 

2033 199 - 352 2,116 2,667 

2034 203 - 356 2,139 2,698 

2035 207 - 360 2,162 2,729 

2036 211 - 364 2,185 2,760 

* Excludes NRLM fuel demand in California
Final Regulatory Impact Analysis

8-52

The cost of supplying NRLM fuel under the final NRLM program and for the proposed

NRLM program are developed in Chapter 7 and summarized in Table 7.5-1. The engine

maintenance savings associated with reduced sulfur contents are developed in Chapter 6 and

summarized in Table 6.2-29. We assume that the per gallon costs developed for 2014 apply

through 2036. With the increase in downgrade volume, the cost of reprocessing downgrade

which occurs in some regions would increase. However, this increase occurs both with and

without the 15 ppm L&M fuel cap. Thus, we did not update the estimated cost of reprocessing

downgrade. The per gallon costs and savings under both L&M fuel caps are summarized here in

Table 8.7-18.

Table 8.7-18

Total Diesel Fuel Costs Under 500 and 15 ppm L&M Fuel Caps*

Refining

Cost 

Additive and

Distribution Cost

Maintenance

Savings 

Total w/o

Maintenance Savings

Total with

Maintenance Savings

Final NRLM Fuel Program

2012-2014

15 ppm Nonroad 5.6 0.8 -3.2 6.4 3.2

Small Refiner 500

ppm Nonroad 

2.9 0.2 -2.9 3.1 0.2

Small Refiner 500

ppm L&M

2.9 0.2 -1 3.1 2.1

2014 +

15 ppm Nonroad 5.8 1.2 -3.2 7 3.8

15 ppm L&M 5.8 1.2 -1.1 7 5.9

500 ppm NRLM Fuel Cap in 2007 and 15 ppm Nonroad Fuel Cap in 2010 (proposed rule program)

2012-2014

15 ppm Nonroad 5 0.8 -3.2 5.8 2.6

Small Refiner 500

ppm Nonroad

2.7 0.2 -2.9 2.9 0

500 ppm L&M 2.7 0.3 -1.0 3 2.0

2014 +

15 ppm NR 5.2 1.2 -3.2 6.4 3.2

500 ppm L&M 2.7 0.2 -1.0 2.9 1.9

* Fuel costs are relative to uncontrolled fuel and assume that, during the transitional years of 2012 & 2014, the first 5

months are at the previous year's cost and the remaining 7 months are at the next year's cost.

We then multiplied the production volume of each fuel in a given calendar year by the net

cost of using that fuel from Table 8.7-18. For this incremental analysis, we only present

estimated annual costs including the maintenance savings because, on the increment, these

maintenance savings are minor (0.1 c/gal) compared to the incremental cost of producing 15 ppm

L&M fuel. Little information would be gained from presenting costs without the maintenance

savings, as is done for the final rule analysis and the other sensitivity cases. We do present the
Aggregate Cost and Cost per Ton

8-53

final discounted costs without the maintenance savings, as well as the cost-effectiveness based

on the costs without maintenance savings, in Table 8.7-24. The resulting annual costs are shown

in Table 8.7-19.

Table 8.7-19

Annual Fuel Costs & Oil Change Maintenance Savings With the Shift of Downgrade to the

Heating Oil Market ($2002 million)

 Year Final NRLM Fuel

Program 

 15 ppm NR Cap

 and 500 ppm L&M Cap 

 15 ppm L&M 

Incremental Costs 

2012 $ 268 $ 162 $ 107 

2013 $ 472 $ 282 $ 190 

2014 $ 524 $ 337 $ 187 

2015 $ 566 $ 379 $ 187 

2016 $ 575 $ 386 $ 189 

2017 $ 583 $ 393 $ 191 

2018 $ 592 $ 400 $ 193 

2019 $ 602 $ 406 $ 195 

2020 $ 610 $ 413 $ 197 

2021 $ 618 $ 420 $ 198 

2022 $ 628 $ 426 $ 202 

2023 $ 637 $ 433 $ 203 

2024 $ 645 $ 440 $ 206 

2025 $ 654 $ 446 $ 208 

2026 $ 663 $ 453 $ 210 

2027 $ 671 $ 459 $ 212 

2028 $ 680 $ 466 $ 214 

2029 $ 688 $ 473 $ 216 

2030 $ 697 $ 479 $ 218 

2031 $ 705 $ 486 $ 220 

2032 $ 714 $ 492 $ 222 

2033 $ 722 $ 499 $ 224 

2034 $ 731 $ 505 $ 226 

2035 $ 739 $ 511 $ 227 

2036 $ 747 $ 518 $ 229 

Total 30-Year Costs (2007-2036)

 Undiscounted $ 15,731 $ 10,664 $ 5,068 

 30 Yr NPV at 3% $ 8,640 $ 5,829 $ 2,811 

 30 Yr NPV at 7% $ 4,249 $ 2,847 $ 1,402 

The absence of the shift of downgrade to the heating oil market in the Northeast/Middle

Atlantic area has no impact on the supply of NRLM fuel under the proposed NRLM fuel

program. Thus, the various volumes of NRLM fuel shown in Tables 8.7-12 through 8.7-14 still

apply. Without the shift of downgrade to heating oil, the production volumes of NRLM fuel

under the final NRLM fuel program become very similar to those for the proposed NRLM fuel

program, except that L&M fuel produced after mid-2012 would have to meet a 15 ppm cap

instead of a 500 ppm cap. The volumes of spillover, downgrade and demand are identical. The

only difference is that the volume of 500 ppm, small refiner fuel is slightly greater with a longterm 500 ppm L&M fuel cap than with a 15 ppm cap. Thus, the incremental volume of 15 ppm

fuel from mid-2012 to mid-2014 under the 15 ppm L&M fuel cap is slightly higher than simply
Final Regulatory Impact Analysis

D The reduced volume of 15 ppm L&M fuel under the final NRLM fuel program could

reduce the per gallon cost of 15 ppm fuel, as those refiners facing the highest costs might be the

first to avoid producing this fuel. However, as indicated by the sensitivity analysis of potentially

lower nonroad fuel demand (Case 1 Sensitivity) discussed in Section 3 of Appendix 8A,

significantly lowering the demand for 15 ppm NRLM fuel has little effect on the cost per gallon. 

8-54

the volume of 500 ppm L&M fuel which must be produced under the 500 ppm L&M cap. Table

8.7-20 shows the breakdown of nonroad, locomotive and marine fuel supply for the final NRLM

fuel program without a shift in downgrade to heating oil.

Table 8.7-20

NRLM Fuel Supply Under the Final NRLM Fuel Program Without a Downgrade Shift 

to Heating Oil (million gallons) *

Year Downgrade Small Refiner Fuel Spillover New 15 ppm Fuel Total Volume

Nonroad Diesel Fuel

2012 1,061 528 2,760 8,426 12,774 

2013 1,085 468 2,818 8,674 13,045 

2014 463 199 2,940 9,713 13,316 

2015 + Same as for Proposed NRLM Fuel Program

Locomotive Diesel Fuel

2012 579 761 602 944 2,886 

2013 593 99 607 1610 2,909 

2014 1,176 42 566 1148 2,932 

2015 + Same as for Proposed NRLM Fuel Program

Marine Diesel Fuel

2012 446 636 280 697 2,059 

2013 456 148 283 1191 2,078 

2014 451 62 280 1310 2,103 

2015 + Same as for Proposed NRLM Fuel Program

* Excludes NRLM fuel demand in California

The per gallon costs shown in Table 8.7-19 are unaffected by the absence of a shift in

downgrade to the heating oil market.D Thus, the annual costs with a 500 ppm L&M cap are the

same as before. The annual costs under the final NRLM program decrease slightly, as 15 ppm

L&M fuel does not need to replace downgrade shifted from the L&M market to the heating oil

market in the Northeast/Middle Atlantic exclusion area. The annual costs under both programs

are shown in Table 8.7-21.
Aggregate Cost and Cost per Ton

8-55

Table 8.7-21

Annual Fuel Costs & Oil Change Maintenance Savings Without Shift of Downgrade to the

Heating Oil Market ($2002 million)

 Year Final NRLM Fuel

Program

Proposed NRLM Fuel

Program

Incremental Cost of 15 ppm L&M

Cap

2012 $249 $162 $88

2013 $432 $282 $150

2014 $488 $337 $151

2015 $531 $379 $152

2016 $539 $386 $153

2017 $547 $393 $155

2018 $556 $400 $156

2019 $564 $406 $158

2020 $572 $413 $159

2021 $580 $420 $160

2022 $588 $427 $162

2023 $596 $433 $163

2024 $604 $440 $164

2025 $612 $446 $165

2026 $619 $453 $166

2027 $627 $460 $168

2028 $635 $466 $169

2029 $643 $473 $170

2030 $650 $479 $171

2031 $658 $486 $172

2032 $665 $492 $173

2033 $673 $499 $174

2034 $680 $505 $175

2035 $687 $512 $176

2036 $695 $518 $177

Total 30-Year Costs (2007 - 2036)

Undiscounted $14,690 $10,665 $4,025

30-Year NPV at 3% $8,070 $5,830 $2,240

30-Year NPV at 7% $3,969 $2,847 $1,121

Moving to emission reductions, we used the methodology used in the draft 2004 NONROAD

model to estimate SO2 and sulfate PM emissions from NRLM engines (Section 3.1 of the Final

RIA). To calculate the emission reductions, we needed estimates for the sulfur levels for

nonroad, locomotive and marine diesel fuel. 

In Section 7.1.6 of the Final RIA, we present our estimate of the sulfur levels of on-purpose

produced diesel fuel, spillover, and downgrade. These sulfur levels, spillover (11 ppm), small

refiner fuel (340 ppm), and non-small refiner fuel (either 340 or 11 ppm), are unaffected by

changing the volume of downgrade projected to be generated during fuel distribution. For

downgrade, in Section 7.1, we estimated that jet-based downgrade contained 400-470 ppm sulfur

and highway-based downgrade contained 25-35 ppm sulfur. The relative volumes of these

downgrades varies by region. We calculated a national average sulfur content for combined
Final Regulatory Impact Analysis

E

 The downgrade comprised of highway diesel fuel and jet fuel likely changes in sulfur level throughout the

period as the relative volume of highway and jet fuel varies relative to each other. However, the growth of highway

diesel fuel and jet fuel is very similar so very little change is expected throughout the analysis period. Thus, this

assumption seems reasonable.

8-56

highway-based and jet-based downgrade used in the L&M markets by weighting the sulfur

contents of each downgrade type in each region. The result was an average downgrade sulfur

content of 101 ppm for the proposed NRLM program and 172 ppm for the final NRLM program. 

These sulfur levels were used for downgrade volumes for all the years of the incremental

analysis.E

 We also applied these downgrade sulfur contents to the small volume of downgrade

used in the nonroad fuel market from mid-2012 to mid-2014. The resulting overall sulfur levels

for NRLM fuel are summarized in Table 8.7-22. 
Aggregate Cost and Cost per Ton

8-57

Table 8.7-22

Sulfur Levels of NRLM Diesel Fuel Based on Revised Downgrade Estimates (million gallons)

48 State Analysis 50 State Analysis

Year Proposed Rule Final Rule Proposed Rule Final Rule

NR L&M NR L&M NR L&M NR L&M

2012 36 236 32 122 36 237 33 125

2013 36 235 29 43 36 237 30 47

2014 21 215 19 49 22 214 19 51

2015 11 201 11 55 11 198 11 54

2016 11 200 11 55 11 197 11 54

2017 11 199 11 55 11 196 11 54

2018 11 198 11 56 11 195 11 55

2019 11 198 11 56 11 194 11 55

2020 11 197 11 56 11 194 11 55

2021 11 195 11 57 11 192 11 56

2022 11 193 11 57 11 190 11 56

2023 11 192 11 57 11 189 11 57

2024 11 191 11 58 11 188 11 57

2025 11 190 11 58 11 187 11 57

2026 11 189 11 59 11 186 11 58

2027 11 188 11 59 11 185 11 58

2028 11 187 11 59 11 184 11 59

2029 11 187 11 60 11 183 11 59

2030 11 186 11 60 11 182 11 59

2031 11 185 11 61 11 181 11 60

2032 11 184 11 61 11 180 11 60

2033 11 183 11 62 11 179 11 61

2034 11 181 11 62 11 178 11 61

2035 11 180 11 62 11 177 11 62

2036 11 179 11 63 11 176 11 62

2037 11 178 11 63 11 175 11 62

2038 11 177 11 64 11 174 11 63

2039 11 176 11 64 11 173 11 63

2040 11 175 11 65 11 171 11 64

We developed these for 50-state and 48-state regions, as this was done for the other

alternatives evaluated in Chapter 3. We use the 50-state sulfur levels here, even though the

volumes developed above are for the U.S. excluding California. Thus, the total sulfur dioxide

and sulfate PM emissions resulting from combining the fuel volumes with the sulfur contents are

not correct. However, as the 15 ppm L&M cap has no impact on sulfur levels in California, the

difference in sulfurous emissions between the two L&M fuel caps is correct. To avoid any

possible mis-use of the absolute emissions under either L&M cap, we only present the

differential emission estimates below.
Final Regulatory Impact Analysis

8-58

In Section 7.1.6, we also estimate the sulfur content of heating oil by assuming that heating

oil has the same sulfur content as NRLM fuel prior to the final NRLM rule. That is acceptable

for the analysis of the overall NRLM rule, since the emission reductions related to changes in the

sulfur content of heating oil are minor relative to emission reductions related to changes in sulfur

content of NRLM. However, in analyzing the incremental step of reducing L&M fuel sulfur

from 500 to 15 ppm, heating oil related emission represent a significant portion of the emission

reductions and therefore warrant closer scrutiny. The impacts on the sulfur content of heating oil

occur in the overall program primarily as a result of changes in where spillover and downgrade

are projected to be used. With the imposition of the 15 ppm limit, downgrade product in

particular is forced from other markets into the heating oil market. When this downgraded

distillate cannot be used in NR or in L&M fuel, it will shift to the heating oil market. The main

impact of this is felt as the last increment of diesel fuel, the L&M portion, is required to meet a

15 ppm limit, and primarily in the Northeast and Mid-Atlantic area where the majority of heating

oil is marketed, and when under the provisions of the final rule downgraded material cannot

continue to be sold into the NRLM markets. The downgrade contains between 31 (highwaybased) and 435 ppm (jet-based) sulfur, well below that of heating oil. Thus, the sulfur content of

heating oil decreases significantly in the Northeast/Mid-Atlantic area with a 15 ppm cap on

L&M fuel. 

In the Northeast and Middle Atlantic area of the U.S., certain states regulate the sulfur

content of heating oil, so some of the heating oil in this area contains much less sulfur than

NRLM fuel. As a result, the sulfur level estimates based on high sulfur diesel fuel may not be

entirely accurate for representing the sulfur level of heating oil, particularly in this area of the

country. Given that the majority of the impact on emissions from heating oil for analyzing the

L&M increment to 15 ppm are in this part of the country, we looked to see what other data might

be available to better assess the sulfur levels. We obtained heating oil surveys from TRW 5,6. 

TRW surveys covers heating oil produced in the U.S. TRW’s districts A and B match the

Northeast/Mid-Atlantic area area quite closely. In 2001 and 2002, heating oil produced by

refineries for this market averaged 1385 ppm sulfur. (As was described in Section 7.1.6, we

exclude sulfur measurements less than 500 ppm, as these likely represent spillover from the

highway fuel supply.) This is less than half that of average NRLM fuel in PADD 1 (2925 ppm,

see Table 7.1.6-3). 

One difficulty in using the heating oil survey results directly is that the heating oil may be

marketed as a single high sulfur distillate fuel to both the diesel fuel and heating oil markets. 

Thus, much of the intended sales for heating oil purposes could have been used as diesel fuel. 

The TRW surveys for both diesel fuel and heating oil cover only a small fraction of the total

volume of fuel sold in the U.S. It is not clear whether the heating oil not covered by the data

submitted by refiners to TRW resembles the high sulfur diesel fuel containing roughly 2900 ppm

sulfur or the heating oil containing roughly 1400 ppm sulfur. Because of this uncertainty, we

assume that the average heating oil in the Northeast/Mid-Atlantic Area contains 2155 ppm

sulfur, the average of the TRW survey estimates for high sulfur diesel fuel and heating oil. 

With the imposition of the 15 ppm L&M standard in 2012, and because of the

Northeast/Mid-Atlantic area provisions of the final NRLM fuel program, 616 million gallons of
Aggregate Cost and Cost per Ton

8-59

downgrade is shifted from the NRLM market to the heating oil market in 2014. Of this, 143

million gallons is jet-based downgrade and 473 million gallons is highway-based downgrade. In

PADD 1, jet-based downgrade is estimated to contain 470 ppm sulfur, while highway-based

downgrade contains 35 ppm sulfur. Thus, the average sulfur content of both downgrades is 129

ppm. Shifting this downgrade from the NRLM fuel market to the heating oil market reduces the

sulfur content of the 616 million gallons of heating oil by 2026 ppm (2155 ppm minus 129 ppm). 

The volume of downgrade used in heating oil is estimated for the years before and after 2014

using the overall downgrade growth rates shown in Table 8.7-11. The resulting incremental

volume of downgrade estimated to be shifted over to heating oil from 2012 to 2036 due to the

final NRLM program is summarized in Table 8.7-23. The same 2026 ppm sulfur reduction due

to the shift of downgrade to the heating oil pool is used for all the years. 

Table 8.7-23

Incremental Volume of Downgrade Forced into Heating Oil by the Final NRLM Program

(Million gallons)

Year Volume

2012 343

2013 602

2014 616

2015 628

2016 640

2017 652

2018 665

2019 679

2020 691

2021 704

2022 718

2023 732

2024 748

2025 763

2026 778

2027 793

2028 808

2029 824

2030 840

2031 856

2032 873

2033 890

2034 907

2035 925

2036 943
Final Regulatory Impact Analysis

F

 As described in Chapter 3, sulfur dioxide has twice the mass of sulfur contained within it. Diesel fuel and heating

oil are both assumed to have a density of 7.1 pounds per gallon. Thus, the formula for calculating the sulfur dioxide

emission reduction from heating oil consumption in 2014 is: 616 million gallons * 7.1 lb/gal * 2026 parts sulfur per

million parts heating oil by mass * 99% conversion of sulfur to SO2 * 2 lbs SO2 per lb sulfur / 2000 lb/ton. Sulfate PM in

the atmosphere is estimated to have 7 times the mass of the sulfur contained within it. Thus, the formula for calculating

the sulfate PM emission reduction from heating oil consumption in 2014 is: 616 million gallons * 7.1 lb/gal * 2026 parts

sulfur per million parts heating oil by mass * 1% conversion of sulfur to sulfate PM * 7 lbs sulfate PM per lb sulfur /

2000 lb/ton. 

8-60

We estimate that 99% of the sulfur in heating oil is emitted in the form of sulfur dioxide and

1% in the form of sulfate PM.7

 Otherwise, the reductions in sulfur dioxide and sulfate PM

emissions due to this shift of downgrade to the PADD 1 heating oil market were estimated using

the formula described in Chapter 3.F

 Table 8.7-16 presents the annual sulfur dioxide and sulfate

PM emission reductions from NRLM fuel and heating oil. The reductions in NRLM emissions

represent the difference in sulfur dioxide and sulfate PM emissions under the proposed and final

NRLM fuel programs. These emissions under each fuel program are derived from combining

the sulfur contents shown in Table 8.7-24 for the 50-state region with the NRLM fuel demands

shown in Tables 8.7-12 through 8.7-17. 
Aggregate Cost and Cost per Ton

G We ignored the small change in L&M fuel sulfur content which would occur if the

downgrade remained in the L&M market. 

8-61

Table 8.7-24

Annual Sulfur Dioxide and Sulfate PM Emission Reductions: 15 ppm Versus 500 ppm L&M

Cap (tons per year)

Year Sulfur Dioxide Sulfate PM 

NRLM Fuel Heating Oil Total NRLM Fuel Heating Oil Total

2012 4,305 4,884 9,189 372 173 545

2013 7,450 8,572 16,022 709 303 1012

2014 6,264 8,772 15,036 580 310 890

2015 5,319 8,944 14,263 415 316 731

2016 5,332 9,108 14,440 416 322 738

2017 5,342 9,276 14,618 417 328 745

2018 5,353 9,453 14,806 418 334 752

2019 5,381 9,649 15,030 420 341 761

2020 5,385 9,822 15,207 420 347 767

2021 5,346 9,999 15,345 417 354 771

2022 5,327 10,195 15,522 416 360 776

2023 5,309 10,404 15,713 414 368 782

2024 5,310 10,627 15,937 414 376 790

2025 5,310 10,836 16,146 414 383 797

2026 5,309 11,046 16,355 414 391 805

2027 5,311 11,261 16,572 414 398 812

2028 5,305 11,479 16,784 414 406 820

2029 5,300 11,702 17,002 414 414 828

2030 5,294 11,929 17,223 413 422 835

2031 5,283 12,160 17,443 412 430 842

2032 5,274 12,396 17,670 412 438 850

2033 5,258 12,637 17,895 410 447 857

2034 5,245 12,882 18,127 409 455 864

2035 5,226 13,132 18,358 408 464 872

2036 5,209 13,387 18,596 407 473 880

30-Year (2007-2036) Emission Reduction 

Undiscounted 134,700 264,600 399,300 10,760 9,350 20,100

30 Yr NPV at 3% 76,800 144,600 221,400 6,180 5,110 11,300

30 Yr NPV at 7% 39,700 70,800 110,500 3,230 2,500 5,730

If no shift in downgrade to heating oil is assumed, the sulfur dioxide and sulfate PM emission

reductions due to the 15 ppm L&M fuel cap are simply the differences in the emissions in the

two columns of Table 8.7-24 labeled NRLM fuel.G

The 30-year cost effectiveness of the 15 ppm L&M cap is the ratio of the 30-year costs

shown in Tables 8.7-19 and 8.7-21 divided by the 30-year emission reductions of sulfur dioxide

and sulfate PM shown in Table 8.7-24. We have allocated 67 percent of the costs to sulfur

dioxide emission control and 33 percent to sulfate PM control consistent with our allocation of
Final Regulatory Impact Analysis

8-62

costs associated with fuel-derived benefits throughout our analysis. The results are presented in

Table 8.7-25.

Table 8.7-25

Incremental Cost Effectiveness of the 15 ppm L&M Fuel Sulfur Cap 

30-year Net Present Values at a 3% Discount Rate ($2002)

3% Discount Rate 7% Discount Rate

SOx PM SOx PM

With Shift of Downgrade to Heating Oil

Cost ($ million) $ 1,870 $ 940 $ 935 $ 467

Emissions Reduction (tons) 221,400 11,300 110,500 5,730

Cost per ton ($/ton) $ 8,450 $ 83,200 $ 8,460 $ 81,500

Without Shift of Downgrade to Heating Oil

Cost ($ million) $1,493 $747 $747 $374

Emissions Reduction (tons) 76,800 6,180 39,700 3,230

Cost per ton ($/ton) $ 19,400 $ 120,700 $ 18,800 $ 115,800

As can be seen, the incremental cost effectiveness of the 15 ppm L&M fuel cap worsens

without the shift in downgrade to the heating oil market. This indicates that the cost

effectiveness of shifting downgrade from the L&M market to the heating oil market and

replacing it with 15 ppm L&M fuel is more cost effective than simply reducing L&M fuel sulfur

from 500 ppm to 15 ppm. The shift in downgrade itself is environmentally neutral from sulfur

perspective, since all of the sulfur is emitted regardless of whether it is burned in a locomotive or

marine diesel engine or a furnace or stationary diesel engine. The conversion of sulfur to PM is

less for heating oil, but as the majority of the sulfur is emitted as sulfur dioxide in either case,

sulfur dioxide emissions are the same. The difference is that, with the downgrade shift to

heating oil, the new 15 ppm L&M fuel replaces high sulfur heating oil. Without the shift, the

new 15 ppm L&M fuel replaces 500 ppm L&M fuel. The cost of producing 15 ppm L&M fuel

from high sulfur fuel are higher than from 500 ppm fuel, 8.3 cents per gallon versus 3.1 cents per

gallon. However, the sulfur reduction is also higher and to a much greater degree. With heating

oil at 2155 ppm, the in-use reduction is 2144 ppm, while that from 500 ppm L&M fuel is only

329 ppm. Thus, the sulfur benefits are a factor of seven time higher, while costs are less than a

factor of three higher.

While we evaluate the incremental cost effectiveness of the 15 ppm L&M cap with and

without the shift of downgrade to the heating oil market, we believe that the former is the most

appropriate way to evaluate this fuel control step as it is consistent with the design of the

program which reflects the characteristics of the distribution system. The prohibition on using

downgrade in the NRLM markets in the Northeast/Middle Atlantic area eliminates the marking

of the significant volume of heating oil in this area beginning in 2007. This is an important and
Aggregate Cost and Cost per Ton

H The cost allocations used in the proposal differed slightly in that costs associated with fuel-derived benefits were

allocated entirely to SOx (FRM allocations split them one-third to PM and two-thirds to SOx) and costs of 15 ppm fuel

were allocated entirely to engine-derived benefits (FRM allocations split them one-half to fuel-derived benefits and onehalf to engine-derived benefits).

8-63

valuable aspect of the final NRLM fuel program which was made regardless of any decision to

control L&M fuel to 15 ppm. Thus, it is appropriate to include the effect of this provision on the

cost effectiveness of 15 ppm L&M fuel control.

8.7.4 Costs per Ton Summary

Table 8.7-26 presents a summary of the cost per ton calculations presented in Sections 8.7.1

through 8.7.4.

As noted in section 8.1, we have allocated costs slightly differently in the final analysis than

we did in the proposed analysis.H Table 8.7-27 presents the costs per ton using the allocations

used in the proposal. To clarify, Table 8.7-27 does not present the costs per ton from the

proposed analysis. Instead, the values presented in Table 8.7-27 are the costs per ton using the

final rule’s costs and emissions reductions but allocating the costs using the method used in the

proposal. As such, Table 8.7-27 provides a comparison of how the new cost allocations affect

the costs per ton and does not provide a comparison of the final costs per ton to the proposed

costs per ton.
Final Regulatory Impact Analysis

8-64

Table 8.7-26

Summary of Costs and Cost per Ton Estimates based on 30 Year NPVs

($2002)

NRT4 Full Program 3% discount rate 7% discount rate

NPV of Total Cost ($millions) $ 27,100 $ 13,800 

$/ton PM $ 11,200 $ 11,800 

$/ton NOx+NMHC $ 1,010 $ 1,160 

$/ton SOx $ 690 $ 620 

15ppm NRLM Fuel-only Scenario

NPV of Total Cost w/ Savings ($millions) $ 9,200 $ 4,600 

NPV of Total Cost w/o Savings ($millions) $ 16,300 $ 8,500 

$/ton PM w/ Savings $ 6,600 $ 6,000 

$/ton PM w/o Savings $ 11,800 $ 11,200 

$/ton SOx w/ Savings $ 1,070 $ 970 

$/ton SOx w/o Savings $ 1,900 $ 1,800 

500ppm NRLM Fuel-only Scenario

NPV of Total Cost w/ Savings ($millions) $ (500) $ (300)

NPV of Total Cost w/o Savings ($millions) $ 5,400 $ 3,000 

$/ton PM w/ Savings $ (400) $ (400)

$/ton PM w/o Savings $ 4,300 $ 4,300 

$/ton SOx w/ Savings $ (70) $ (70)

$/ton SOx w/o Savings $ 690 $ 700 

15 ppm L&M Fuel-only Scenario (Increment) *

NPV of Incremental Cost w/ Savings ($millions) $ 2,810 $ 1,400

$/ton PM w/ Savings (incremental) $ 83,200 $ 81,500

$/ton SOx w/ Savings (incremental) $ 8,450 $ 8,460

* Includes shift of downgrade to heating oil in the Northeast/Middle Atlantic area

Table 8.7-27

Costs and Costs per Ton of the NRT4 Full Program

 using the Proposal’s Cost Allocations

30 Year NPVs using a 3% Discount Rate ($2002)

NRT4 Full Program 3% discount rate

NPV of Total Cost ($millions) $ 27,100 

$/ton PM $ 11,000 

$/ton NOx+NMHC $ 1,250 

$/ton SOx $ 460 
Aggregate Cost and Cost per Ton

8-65

Appendix 8A: Estimated Aggregate Cost and Cost per Ton

of Sensitivity Analyses

8A.1 What Sensitivity Analyses Have Been Performed?

This Appendix contains two sensitivity analyses EPA performed regarding the emissions

inventory predictions from the NONROAD model, as well as cost and cost per ton analysis

which correspond to these two NONROAD model sensitivities. In the NONROAD model

sensitivity Case 1, we have adjusted the emissions predictions so that NONROAD’s fuel

consumption estimates match the predictions of fuel volume from the Energy Information

Agency. In the NONROAD model sensitivity Case 2, we have increased the fraction of diesel 

generators sold in the U.S. which are considered “mobile” (and therefore decreased the

percentage which are “stationary”) and we have increased the annual hours of use for several

categories of nonroad equipment in the >750 hp category. 

In the remainder of section 8A.1, we describe why we have included these sensitivity

analyses in the final rule. In section 8A.2, we describe what changes were made to the

NONROAD model, how each of the sensitivities were performed, and the emission inventory

impacts of Case 1 and Case 2. In section 8A.3, we describe how we have altered our engine and

fuel program cost methodology to match Case 1 and Case 2, what the resulting program cost

estimates are using Case 1 and Case 2, and finally what the cost-per-ton estimates are for Case 1

and Case 2. In section 8A.4, we summarize the results presented in sections 8A.1 through 8A.3.

8A.1.1 What is the Case 1 Sensitivity Analysis?

The Case 1 sensitivity analysis results from comments we received on the proposal which

suggested that the NONROAD model over-predicts the growth rate of the nonroad fleet. The

commenters suggested that the NONROAD model’s growth rates should be adjusted downward

so that overall fuel consumption matches the predictions made by the Department of Energy’s

Energy Information Agency (EIA). As described in detail in the Summary and Analysis of

Comments for this rule, we disagree with these comments and we have not made a change to the

NONROAD model as a result of these comments (see section 2.3.2.2.3 of the Summary and

Analysis of Comments document for this final rule). However, we are performing a sensitivity

analysis (Case 1) which estimates what the impact of such a change would have on our estimates

of the emissions reduction of this rule, the costs of this rule, and our cost-per-ton estimates.

8A.1.2 What is the Case 2 Sensitivity Analysis?

The Case 2 sensitivity analysis results from information we received during the development

of the rule on two issues which indicates NONROAD is under-predicting emissions from some

nonroad engines. One of these issues is the partitioning of generator sets into mobile and

stationary. The second issue is the annual hours of use estimates for large engines (those >750

hp).
Final Regulatory Impact Analysis

8-66

8A.1.2.1 Information Regarding Mobile & Stationary Generator Sets

During our discussions with several engine manufacturers who produce the >750 hp diesel

engines, three manufacturers (who together represent a majority of the market), provided EPA

with recent year sales estimates of engines used in mobile machines in the >750 hp category

(e.g., mining trucks, dozers, wheel loaders, etc.) and generator sets. These manufacturers

produce engines for generator sets which are certified to the existing Tier 1 nonroad standards, as

well as engines which are not certified to the nonroad standards because the engines are designed

for stationary power generation and therefore are not subject to EPA’s nonroad standards. Many

of the >750 hp nonroad certified engines which are used in generator sets are used in

applications such as the large portable power generators that are contained in a Class 8 truck

trailer, where power generation ratings of 1, 1.5 and 2 megawatts are common. These products

are designed to be portable and are used by rental companies and in other industries where large

amounts of power are needed for a relatively short duration of time. The data from the engine

manufacturers indicates that approximately 30 percent of the >750 hp diesel generator sets sold

in the U.S. are portable and subject to EPA nonroad diesel standards. In addition, manufacturers

build some stationary engines to nonroad certified configurations to simplify their product base

and thus the nonroad engine standards yield an added indirect, yet real, emission benefit.

The data which is used to estimate the nonroad equipment population in NONROAD comes

from the PSR database. This database does not distinguish between mobile and stationary diesel

generator sets. As documented in EPA report EPA420-P-02-004, we estimate for all of the

diesel generators what percent of the PSR database diesel generator sets are mobile (and

therefore subject to the EPA’s nonroad standards) and what percent is stationary. These

estimates vary by power range, with the percent that are considered stationary increasing with

increasing rated power. For example, for <25 hp engines we estimate 10 percent are stationary,

and for >600 hp, we estimate that 100 percent are stationary. Once these percentages are

applied to the PSR database data to remove the estimated stationary generator sets, the remaining

generator set data is used to estimate the population of generator sets in NONROAD.

The recent information we received from the engine manufacturers (~ 30 percent of

generator sets >750 hp are mobile/portable) is substantially different from the current

assumptions which go into NONROAD (no generators >600 hp are mobile/portable). Because at

this time we do not have reference-able industry-wide information on this issue, we have not

performed a new analysis to update NONROAD. However, it is clear that the recent confidential

information from the engine companies indicates NONROAD is underestimating the number of

nonroad diesel generators. As discussed in Chapter 8A.2, we have performed a sensitivity

analysis which includes a higher percentage of mobile diesel generator sets based on the

information we received from the engine manufacturers.

8A.1.2.2 Information Regarding Usage Factors for >750hp Mobile Machines and

Generators

As discussed in the preamble for this final rule, we have recognized some of the unique

features of the >750 hp mobile machines. Most of the >750 hp engines used in the mobile
Aggregate Cost and Cost per Ton

8-67

machine category are used in mining applications, such as mining trucks, dozers, excavators and

loaders. As part of our feasibility analysis, we spent a considerable amount of time with a

number of engine manufacturers and equipment manufacturers to understand the applications

these large engines are used in. In addition, several manufacturers provided EPA with data

regarding the >750 hp mobile machine applications. One of the pieces of data which we noticed

was the high annual hours of use for this equipment, which in some cases was greater than 4,000

hours per year. During our discussions with both engine and equipment manufacturers,

companies made the point these large pieces of equipment are very expensive (in excess of $1

million), and that mining operations are often run 7 days a week, “around the clock”. Because of

these two factors, the large mobile machines are operated at higher annual usage rates than most

nonroad applications.

While we received this type of information from multiple companies, the most convincing

data we received came from one of the industry’s larger equipment companies. This equipment

company provided EPA with confidential data for mobile machines >750 hp which included

sales and annual hours of use estimates. The equipment types covered by the data included

applications such as off-highway trucks, dozers, wheel loaders, and off-highway tractors. The

data was representative of 10 years worth of sales, and several thousand pieces of equipment. 

On average, the manufacturer estimated the annual hours of use for this equipment was > 3,500

hours per year. We also received information from several engine and equipment companies

which indicates the annual hours of use for >750 portable generator sets are on the order of 1,000

hours per year.

The NONROAD model contains estimates of annual hours of use which are used in the

process of estimating annual emissions. The annual hours of use values are documented in EPA

report EPA420-P-02-014. The annual hours of use do not vary by power category, therefore the

estimate for a 250 hp dozer is the same as the estimate for a 1,000 hp dozer. For the >750 hp

applications on which we received new data, the highest annual hours of use value in

NONROAD is 1,641 hours/year for off-highway trucks, and for generator sets the value is 338

hours/year. These values are substantially lower than the usage information we received from

engine and equipment manufacturers. While we now believe NONROAD underestimates the

emissions impact of the >750hp equipment based on the new information we have received, we

have not changed NONROAD at this time. The information we received, though useful for this

sensitivity analysis, is not adequately reference-able and may not be sufficiently representative. 

In addition, while we believe it is directionally correct, we have not had an opportunity to

independently verify the information or collect additional data from other sources. As a result,

though not reflected in the NONROAD model results for this final rule, the Case 2 sensitivity

analysis does include higher annual hours of use values for several categories of mobile

machines >750hp and for generator sets >750hp, which is based on the information we received

from engine and equipment companies.
Final Regulatory Impact Analysis

8-68

8A.2 What Emissions Modeling was Done?

8A.2.1 Case 1: Inventories Adjusted to Match Fuel Consumption Derived from EIA

Sources

To represent the emissions inventory for Case 1, we did not perform additional NONROAD

runs. Rather, we adjusted the NONROAD fuel consumption and emissions estimates so that

estimated fuel consumption matched fuel consumption estimates derived from EIA sources. We

performed the adjustment by applying ratios to the NONROAD fuel consumption and emissions

outputs. Specifically,, we calculated an adjustment ratio r as

where FNONROAD,y is a national fuel consumption estimate as generated by Draft NONROAD2004

for year y, and FEIA,y is a corresponding estimate derived from EIA’s Annual Energy Outlook

2003 (AEO 2003). These reports provide distillate fuel consumption projections by economic

sector.

The derivation of FEIA is based on a linear projection of nonroad diesel fuel consumption

from 2002 to 2040, as described below. To establish a basis for estimaton of a growth rate, we

derived estimates for the years 2002 and 2014 from AEO 2003, the derivation of which is

described in Chapter 7.1 of the RIA. These two estimates, along with corresponding estimates

from Draft NONROAD2004, are shown in Table 8A.2-1. 

Table 8A.2-1

Nonroad Fuel Consumption: Draft NONROAD2004 and Estimates derived from EIA Sources

(Million gallons per year)

Year Draft NONROAD2004 Derived from EIA Sources

2002 10,625 8,428

2014 14,433 9,814

Using the following equation, we estimated a 1.4%/year average linear growth rate (without

compounding) in fuel consumption gEIA over this 12-year period:

Using the resulting growth rate (0.014/year), we projected fuel consumption from 2002 to 2040,

based on the expression

r

F

F y

y

y

= NONROAD

EIA

,

,

g

F F

F EIA

EIA EIA

EIA,2002 2014 2002 = −

−





 



 , , 2014 2002 1

FF y g EIA EIA EIA , , y = +− ( ) ( ) 2002 1 2002
Aggregate Cost and Cost per Ton

8-69

The resulting EIA-derived fuel consumption estimates are shown in Table 8A.2-2, along with

fuel consumption estimates from Draft NONROAD2004. The ratio of the two fuel consumption

estimates in each year are also shown.

Table 8A.2-3 shows projected land-based nonroad diesel fuel consumption and associated

emissions inventories (NOx, SO2, PM10) at the national level for selected years between 2001 and

2040, as estimated by NONROAD and from EIA sources. Results are shown for both the base

and control cases. These results are also presented graphically in Figures 8A.2-1 - 8A.2-4.
Final Regulatory Impact Analysis

8-70

Table 8A.2-2

2001-2040 Nonroad Fuel Consumption (Million gallons per year)

Calendar Year Draft NONROAD2004

(FNONROAD)

EIA FOKS/AEO Derived

(FEIA)

Ratio

(r)

2001 10,625 9,080 1.170 

2002 10,919 8,428 1.296 

2003 11,213 8,544 1.312 

2004 11,507 8,659 1.329 

2005 11,801 8,775 1.345 

2006 12,092 8,890 1.360 

2007 12,384 9,006 1.375 

2008 12,676 9,121 1.390 

2009 12,968 9,237 1.404 

2010 13,259 9,352 1.418 

2011 13,553 9,468 1.431 

2012 13,846 9,583 1.445 

2013 14,139 9,699 1.458 

2014 14,433 9,814 1.471 

2015 14,726 9,930 1.483 

2016 15,016 10,045 1.495 

2017 15,307 10,160 1.507 

2018 15,597 10,276 1.518 

2019 15,887 10,391 1.529 

2020 16,178 10,507 1.540 

2021 16,468 10,622 1.550 

2022 16,759 10,738 1.561 

2023 17,049 10,853 1.571 

2024 17,339 10,969 1.581 

2025 17,630 11,084 1.591 

2026 17,918 11,200 1.600 

2027 18,206 11,315 1.609 

2028 18,495 11,431 1.618 

2029 18,783 11,546 1.627 

2030 19,071 11,662 1.635 

2031 19,360 11,777 1.644 

2032 19,648 11,892 1.652 

2033 19,936 12,007 1.660 

2034 20,225 12,123 1.668 

2035 20,513 12,239 1.676 

2036 20,801 12,354 1.684 

2037 21,090 12,470 1.691 

2038 21,378 12,585 1.699 

2039 21,666 12,701 1.706 

2040 21,955 12,816 1.713 
Aggregate Cost and Cost per Ton

8-71

Table 8A.2-3

Case 1: Adjustment to Match EIA Projections

Projected Nonroad Diesel Emissions Inventories

Year (y) National Emissions Inventory (thousand tons)

NOx SO2 PM10

Base Control Base Control Base Control

2002 1,184 1,184 133 133 128 128 

2005 1,096 1,096 139 139 111 111 

2010 906 906 140 10.7 94.0 82.4

2015 781 650 145 0.673 87.9 55.4

2020 731 442 154 0.644 86.8 33.7

2025 722 334 162 0.644 88.1 21.2

2030 733 282 171 0.660 90.2 13.7

2035 754 259 179 0.684 92.8 9.5

2040 780 251 188 0.712 96.3 7.5
Final Regulatory Impact Analysis

8-72

8A.2.2 Case 2: Large Equipment Population and Activity

To represent Case 2, we performed NONROAD runs with modified inputs for selected

equipment types. Specifically, we used modified activity for large equipment (>750 hp) in five

equipment types, as shown in Table 8A.2-4. This change represents the use of large equipment

on a continuous shift basis. Additionally, we modified the fractions of generators assumed to be

mobile, as opposed to stationary equipment, as shown in Table 8A.2-5. The modified fractions

increased populations for generators of size 100 hp and greater, resulting in an increase in the

total generator population of approximately 135,000 pieces. As in Case 1, we repeated the

analysis for both the base and control cases.

Table 8A.3-6 shows projected land-based nonroad diesel fuel consumption and associated

emissions inventories (NOx, SO2, PM10) at the national level for selected years between 2001 and

2040, for both the base and control cases. These results are also presented graphically in Figures

8A.2-1 - 8A.2-4.

Table 8A.2-4

Case 2: Large Equipment Population and Activity

Annual Activity Estimates for Large Equipment (>750 hp)

Equipment Type Activity (hours/year)

FRM Base Sensitivity Case

Excavators 1,092 3,800

Off-Highway Trucks 1,641 3,800

Rubber Tire Loaders 761 3,800

Crawler Tractors/Dozers 936 3,800

Off-Highway Tractors 855 3,800

Generators 338 1,000
Aggregate Cost and Cost per Ton

8-73

Table 8A.2-5

Case 2: Large Equipment Population and Activity

Modified Mobile-Equipment Population Fractions for Diesel Generators

Hp Class FRM Base Sensitivity Case

Mobile Fraction Mobile Population Mobile Fraction Mobile Population

< 25 0.90 240,180 0.90 240,180

25-40 0.90 121,050 0.90 121,050

40-50 0.70 16,530 0.70 16,530

50-75 0.70 61,000 0.70 61,000

75-100 0.70 74,240 0.70 74,240

100-175 0.20 25,340 0.62 78,560

175-300 0.15 14,090 0.54 50,720

300-600 0.10 7,320 0.46 33,660

600-750 0.0 0 0.38 6,260

> 750 0.0 0 0.30 12,290

Total 559,750 694,490
Table 8A.2-6

Case 2: Large Equipment Population and Activity:

Projected Nonroad Diesel Fuel Consumption and Emissions Inventories

Year (y) Fuel Consumption (million gal) National Emissions Inventory (thousand to

NONROAD

FRM 50-state

Base

NONROAD

Sensitivity-Case

NOx SO2 

Base Control Base Control 

2001 10,630 12,550 1,817 1,817 198 198 2005 11,800 13,960 1,759 1,759 220 220 2010 13,260 15,710 1,519 1,518 234 17.9 2015 14,730 17,470 1,409 1,132 256 1.15 2020 16,180 19,220 1,393 848 282 1.16 2025 17,630 20,970 1,434 692 307 1.21 2030 19,070 22,710 1,502 916 333 1.28 2035 20,510 24,440 1,585 595 358 1.37 2040 21,950 26,180 1,678 594 384 1.45 
Aggregate Cost and Cost per Ton

8-75

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

2005 2010 2015 2020 2025 2030

Time (years)

NOx Emissions (tons)

FRM: Base

Case 2: Base

Case 1: Base

FRM: Control

Case 2: Control

Case 1: Control

Figure 8A.2-2. Projected land-based nonroad NOx inventories at the national level for the

FRM base and two sensitivity cases. Case 1 represents Draft NONROAD2004 estimates

adjusted to match EIA-based projections; Case 2 represents modified population and activity

estimates for large equipment (>750 hp).

5,000

10,000

15,000

20,000

25,000

30,000

2005 2010 2015 2020 2025 2030

Time (years)

Fuel Consumption (million gallons)

FRM: Base

Case 2: Large Equipment

Case 1: Adjustment to EIA

Figure 8A.2-1. Projected land-based nonroad diesel fuel consumption at the national level for the FRM

base and two sensitivity cases. Case 1 represents Draft NONROAD2004 estimates adjusted to match

EIA-based projections; Case 2 represents modified population and activity estimates for large

equipment (>750 hp).
Final Regulatory Impact Analysis

8-76

50,000

100,000

150,000

200,000

2005 2010 2015 2020 2025 2030

Time (years)

PM Emissions (Tons)

FRM: Base

Case 2: Base

Case 1: Base

FRM: Control

Case 2: Control

Case 1: Control

Figure 8A.2-4. Projected land-based nonroad PM10 inventories at the national level for the FRM base

and two sensitivity cases. Case 1 represents Draft NONROAD2004 estimates adjusted to match EIAbased projections; Case 2 represents modified population and activity estimates for large equipment

(>750 hp).

50,000

100,000

150,000

200,000

250,000

300,000

350,000

2005 2010 2015 2020 2025 2030

Time (years)

SO2 Emissions (tons)

FRM: Base

Case 2: Base

Case 1: Base

FRM: Control

Case 2: Control

Case 1: Control

Figure 8A.2-3. Projected land-based nonroad SO2 inventories at the national level for the FRM base and

two sensitivity cases. Case 1 represents Draft NONROAD2004 estimates adjusted to match EIA-based

projections; Case 2 represents modified population and activity estimates for large equipment (>750 hp).
Aggregate Cost and Cost per Ton

8-77

8A.3 What Are the Costs and Costs per Ton?

Here we look at the cost per ton of two sensitivity cases—a Case 1 sensitivity using future

fuel consumption projections developed by the Energy Information Administration (EIA); and, a

Case 2 sensitivity that incorporates more generator sets in both the costs and emissions

reductions estimates than are incorporated under NRT4 full engine and fuel program (i.e., the

NRT4 final rule estimates).

8A.3.1 Costs and Costs per Ton for the Case 1 Sensitivity

Under the Case 1 sensitivity we use future fuel projections developed by EIA rather than

using the projections generated in our NONROAD model as discussed in Section 8A.1. Doing

this results in lower fuel-related costs (including all operating costs expressed throughout this

Regulatory Impact Analysis on a cent-per-gallon basis) since the EIA projections are lower than

our model’s projections. Doing this also results in lower emissions reductions as discussed in

Section 8A.2. The engine and equipment costs under the Case 1 sensitivity would be identical to

those under the full engine and fuel program since all engine standards would still be

implemented. Tables 8A.3-1 though 8A.3-4 show all fuel-related costs associated with the Case

1 sensitivity. All these tables are analogous to Tables 8.4-1 through 8.4-4 presented above for

the NRT4 final program. The cent per gallon fuel costs are presented in Table 7.5-1.
Table 8A.3-1

Aggregate Fuel Costs of the Case 1 Sensitivity ($2002)

Year Affected NR Fuel Affected L&M Fuel Fuel Cost * NR Fuel Costs L

500 ppm (106 gallons) 15 ppm (106 gallons) 500 ppm (106 gallons) 15 ppm (106 gallons) 500 ppm ($/gal) 15 ppm ($/gal) 500 ppm (106 dollars) 15 ppm (106 dollars) Total (106 dollars) 500 ppm (106 dollars) 

2007 3,671 - 1,981 - $ 0.021 $ - $ 77 - $ 77 $ 42 2008 6,373 - 3,438 - $ 0.021 $ - $ 134 - $ 134 $ 72 2009 6,454 - 3,483 - $ 0.021 $ - $ 136 - $ 136 $ 73 2010 3,086 3,873 3,069 - $ 0.029 $ 0.058 $ 88 225 $ 313 $ 88 2011 631 6,721 2,785 - $ 0.034 $ 0.058 $ 21 390 $ 411 $ 95 2012 531 6,574 1,243 2,116 $ 0.035 $ 0.062 $ 18 404 $ 423 $ 43 2013 460 6,488 120 3,657 $ 0.036 $ 0.064 $ 16 415 $ 431 $ 4 2014 194 7,153 50 3,527 $ 0.036 $ 0.067 $ 7 479 $ 485 $ 2 2015 - 7,662 - 3,441 $ 0.069 $ - 529 $ 529 $ - 2016 - 7,751 - 3,476 $ 0.069 $ - 535 $ 535 $ - 2017 - 7,840 - 3,511 $ 0.069 $ - 541 $ 541 $ - 2018 - 7,929 - 3,551 $ 0.069 $ - 547 $ 547 $ - 2019 - 8,018 - 3,598 $ 0.069 $ - 553 $ 553 $ - 2020 - 8,107 - 3,632 $ 0.069 $ - 559 $ 559 $ - 2021 - 8,196 - 3,663 $ 0.069 $ - 566 $ 566 $ - 2022 - 8,285 - 3,709 $ 0.069 $ - 572 $ 572 $ - 2023 - 8,374 - 3,747 $ 0.069 $ - 578 $ 578 $ - 2024 - 8,464 - 3,788 $ 0.069 $ - 584 $ 584 $ - 2025 - 8,553 - 3,828 $ 0.069 $ - 590 $ 590 $ - 2026 - 8,642 - 3,868 $ 0.069 $ - 596 $ 596 $ - 2027 - 8,731 - 3,909 $ 0.069 $ - 602 $ 602 $ - 2028 - 8,820 - 3,949 $ 0.069 $ - 609 $ 609 $ - 2029 - 8,909 - 3,989 $ 0.069 $ - 615 $ 615 $ - 2030 - 8,998 - 4,029 $ 0.069 $ - 621 $ 621 $ - 2031 - 9,087 - 4,070 $ 0.069 $ - 627 $ 627 $ - 2032 - 9,176 - 4,110 $ 0.069 $ - 633 $ 633 $ - 2033 - 9,265 - 4,150 $ 0.069 $ - 639 $ 639 $ - 2034 - 9,354 - 4,190 $ 0.069 $ - 645 $ 645 $ - 2035 - 9,444 - 4,231 $ 0.069 $ - 652 $ 652 $ - 2036 - 9,533 - 4,271 $ 0.069 $ - 658 $ 658 $ - 

30 Yr NPV at 3% 18,602 124,895 13,818 52,202 $ 430 $ 8,447 $ 8,877 $ 354 30 Yr NPV at 7% 15,567 64,783 11,317 26,078 $ 357 $ 4,342 $ 4,698 $ 287 

*Fuel costs are relative to uncontrolled fuel and assume that, during the transitional years of 2010, 2012, & 2014, the first 5 months are at the previous yemonths are at the next year’s cost.See Appendix 8B for information on how these fuel volumes were developed.
Table 8A.3-2

Oil Change Maintenance Savings Associated with the Case 1 Sensitivity ($2002)

Year Affected NR Fuel Affected L&M Fuel NR Savings L&M Sav

500 ppm 

(106 gallons)

15 ppm 

(106 gallons)

500 ppm 

(106 gallons)

15 ppm 

(106 gallons)

savings=$0.029/gal

(106 dollars)

savings=$0.032/gal

(106 dollars)

savings=$0.010/gal

(106 dollars)

2007 3,671 - 1,981 - $ 107 $ - $ 21 2008 6,373 - 3,438 - $ 186 $ - $ 36 2009 6,454 - 3,483 - $ 189 $ - $ 36 2010 3,086 3,873 3,069 - $ 90 $ 124 $ 32 2011 631 6,721 2,785 - $ 18 $ 215 $ 29 2012 531 6,574 1,243 2,116 $ 16 $ 211 $ 13 2013 460 6,488 120 3,657 $ 13 $ 208 $ 1 2014 194 7,153 50 3,527 $ 6 $ 229 $ 1 2015 - 7,662 - 3,441 $ - $ 245 $ - 2016 - 7,751 - 3,476 $ - $ 248 $ - 2017 - 7,840 - 3,511 $ - $ 251 $ - 2018 - 7,929 - 3,551 $ - $ 254 $ - 2019 - 8,018 - 3,598 $ - $ 257 $ - 2020 - 8,107 - 3,632 $ - $ 260 $ - 2021 - 8,196 - 3,663 $ - $ 263 $ - 2022 - 8,285 - 3,709 $ - $ 265 $ - 2023 - 8,374 - 3,747 $ - $ 268 $ - 2024 - 8,464 - 3,788 $ - $ 271 $ - 2025 - 8,553 - 3,828 $ - $ 274 $ - 2026 - 8,642 - 3,868 $ - $ 277 $ - 2027 - 8,731 - 3,909 $ - $ 280 $ - 2028 - 8,820 - 3,949 $ - $ 282 $ - 2029 - 8,909 - 3,989 $ - $ 285 $ - 2030 - 8,998 - 4,029 $ - $ 288 $ - 2031 - 9,087 - 4,070 $ - $ 291 $ - 2032 - 9,176 - 4,110 $ - $ 294 $ - 2033 - 9,265 - 4,150 $ - $ 297 $ - 2034 - 9,354 - 4,190 $ - $ 300 $ - 2035 - 9,444 - 4,231 $ - $ 302 $ - 2036 - 9,533 - 4,271 $ - $ 305 $ - 

30 Yr NPV at 3% 18,602 124,895 13,818 52,202 $ 544 $ 4,000 $ 145 30 Yr NPV at 7% 15,567 64,783 11,317 26,078 $ 455 $ 2,075 $ 118 
Final Regulatory Impact Analysis

8-80

Table 8A.3-3

CDPF Maintenance and CDPF Regeneration Costs Associated with the Case 1 Sensitivity

($2002)

Year Fuel Consumed in New

CDPF Equipped

Engines

 (106

 gallons)

Weighted

Maintenance

Cost

 ($/gal)

Weighted

Regeneration

Cost

 ($/gal)

 CDPF Maintenance

Cost 

 (106

 dollars)

CDPF Regeneration

Cost 

 (106 dollars)

Total Costs

(106

 dollars)

2007 - $ - $ - $ - $ - $ - 

2008 - $ - $ - $ - $ - $ - 

2009 - $ - $ - $ - $ - $ - 

2010 - $ - $ - $ - $ - $ - 

2011 461 $ 0.002 $ 0.010 $ 1 $ 5 $ 5 

2012 1,204 $ 0.003 $ 0.010 $ 4 $ 12 $ 16 

2013 2,076 $ 0.005 $ 0.010 $ 10 $ 21 $ 32 

2014 2,953 $ 0.006 $ 0.007 $ 17 $ 22 $ 39 

2015 3,885 $ 0.006 $ 0.008 $ 23 $ 30 $ 53 

2016 4,782 $ 0.006 $ 0.008 $ 29 $ 38 $ 66 

2017 5,612 $ 0.006 $ 0.008 $ 34 $ 45 $ 79 

2018 6,369 $ 0.006 $ 0.008 $ 39 $ 51 $ 90 

2019 7,056 $ 0.006 $ 0.008 $ 43 $ 57 $ 100 

2020 7,685 $ 0.006 $ 0.008 $ 47 $ 62 $ 110 

2021 8,239 $ 0.006 $ 0.008 $ 50 $ 67 $ 118 

2022 8,726 $ 0.006 $ 0.008 $ 53 $ 71 $ 124 

2023 9,168 $ 0.006 $ 0.008 $ 56 $ 75 $ 131 

2024 9,579 $ 0.006 $ 0.008 $ 59 $ 78 $ 137 

2025 9,962 $ 0.006 $ 0.008 $ 61 $ 81 $ 142 

2026 10,314 $ 0.006 $ 0.008 $ 63 $ 84 $ 147 

2027 10,622 $ 0.006 $ 0.008 $ 65 $ 87 $ 152 

2028 10,896 $ 0.006 $ 0.008 $ 67 $ 89 $ 156 

2029 11,151 $ 0.006 $ 0.008 $ 68 $ 91 $ 159 

2030 11,390 $ 0.006 $ 0.008 $ 70 $ 93 $ 163 

2031 11,612 $ 0.006 $ 0.008 $ 71 $ 95 $ 166 

2032 11,823 $ 0.006 $ 0.008 $ 72 $ 96 $ 169 

2033 12,027 $ 0.006 $ 0.008 $ 74 $ 98 $ 172 

2034 12,224 $ 0.006 $ 0.008 $ 75 $ 100 $ 174 

2035 12,407 $ 0.006 $ 0.008 $ 76 $ 101 $ 177 

2036 12,579 $ 0.006 $ 0.008 $ 77 $ 102 $ 180 

30 Yr NPV at 3% 111,737 $ 675 $ 911 $ 1,587 

30 Yr NPV at 7% 50,796 $ 305 $ 415 $ 720 

* Note that fuel used in CDPF engines includes some highway spillover fuel.

**Weighted Regeneration Cost ($/gal) changes year-to-year due to different fuel economy impacts with a NOx adsorber (1 percent)

and without a NOx adsorber (2 percent) matched with the phase-in schedules of the emission standards.
Aggregate Cost and Cost per Ton

8-81

Table 8A.3-4

CCV Maintenance Costs Associated with the Case 1 Sensitivity

($2002)

Year Fuel Consumed in

Engines Adding CCV

System

 (106

 gallons)

Weighted

Maintenance

Cost

 ($/gal)

Total Costs

(106

 dollars)

2007 - $ - $ - 

2008 183 $ 0.000 $ 0 

2009 186 $ 0.000 $ 0 

2010 173 $ 0.000 $ 0 

2011 778 $ 0.001 $ 1 

2012 1,606 $ 0.001 $ 2 

2013 2,561 $ 0.002 $ 4 

2014 3,496 $ 0.002 $ 5 

2015 4,478 $ 0.002 $ 7 

2016 5,447 $ 0.002 $ 8 

2017 6,339 $ 0.002 $ 10 

2018 7,133 $ 0.002 $ 11 

2019 7,855 $ 0.002 $ 12 

2020 8,516 $ 0.002 $ 13 

2021 9,099 $ 0.002 $ 14 

2022 9,612 $ 0.002 $ 14 

2023 10,076 $ 0.002 $ 15 

2024 10,505 $ 0.002 $ 16 

2025 10,905 $ 0.002 $ 16 

2026 11,271 $ 0.002 $ 17 

2027 11,593 $ 0.002 $ 18 

2028 11,879 $ 0.002 $ 18 

2029 12,146 $ 0.002 $ 18 

2030 12,398 $ 0.002 $ 19 

2031 12,631 $ 0.002 $ 19 

2032 12,853 $ 0.002 $ 19 

2033 13,069 $ 0.002 $ 20 

2034 13,277 $ 0.002 $ 20 

2035 13,471 $ 0.002 $ 20 

2036 13,654 $ 0.002 $ 21 

30 Yr NPV at 3% 124,105 $ 187 

30 Yr NPV at 7% 56,982 $ 86 

* Weighted Maintenance Cost ($/gal) changes year-to-year due to the

implementation schedule for engines adding the CCV system.

Using Tables 8A.3-1 through 8A.3-4 and Table 8.2-2 (engine fixed costs by pollutant), Table

8.2-4 (engine variable costs by pollutant), Table 8.3-2 (equipment fixed costs by pollutant), and

Table 8.3-4 (equipment variable costs) we can generate the annual costs and costs by pollutant

for the Case 1 sensitivity. Table 8A.3-5 shows these results (this table is analogous to Tables

8.5-1 and 8.5-2 for the NRT4 final program). Note that the pollutant allocations for the Case 1

sensitivity are identical to those used for the NRT4 final program (see Table 8.1-2). Also shown

in Table 8A.3-5 are the emissions reductions associated with the Case 1 sensitivity (these values

are analogous to Table 8.6-1 for the NRT4 final program).
Table 8A.3-5

Summary of Aggregate Costs, Costs by Pollutant, and Emissions Reductions Associated with the Case 1 Se

Year Engine Costs

($million)

Equipment

Costs

($million)

Fuel Costs

($million)

Other Operating

Costs 

($million)

Net Operating

Costs 

($million)

Total Annual

Costs 

($million)

PM Costs

($million)

NOx+NMHC

Costs

($million)

SOx Costs

($million)

2007 $ - $ - $ 119 $ (128) $ (9) $ (9) $ (3) $ - $ (6) 2008 $ 81 $ 5 $ 206 $ (222) $ (16) $ 69 $ 80 $ 0 $ (11) 2009 $ 82 $ 5 $ 209 $ (225) $ (16) $ 71 $ 81 $ 0 $ (11) 2010 $ 80 $ 5 $ 401 $ (246) $ 154 $ 239 $ 145 $ 25 $ 69 2011 $ 403 $ 62 $ 506 $ (256) $ 250 $ 715 $ 441 $ 170 $ 104 2012 $ 718 $ 106 $ 596 $ (245) $ 351 $ 1,174 $ 735 $ 282 $ 157 2013 $ 882 $ 121 $ 670 $ (229) $ 440 $ 1,444 $ 912 $ 330 $ 201 2014 $ 973 $ 146 $ 723 $ (232) $ 491 $ 1,610 $ 893 $ 501 $ 215 2015 $ 950 $ 149 $ 766 $ (225) $ 541 $ 1,640 $ 911 $ 503 $ 226 2016 $ 920 $ 150 $ 775 $ (214) $ 561 $ 1,631 $ 914 $ 487 $ 229 2017 $ 910 $ 150 $ 783 $ (203) $ 580 $ 1,640 $ 924 $ 485 $ 231 2018 $ 901 $ 146 $ 792 $ (194) $ 598 $ 1,645 $ 922 $ 489 $ 234 2019 $ 890 $ 147 $ 802 $ (186) $ 615 $ 1,652 $ 944 $ 471 $ 237 2020 $ 900 $ 147 $ 810 $ (179) $ 631 $ 1,678 $ 962 $ 477 $ 239 2021 $ 913 $ 99 $ 818 $ (173) $ 645 $ 1,657 $ 957 $ 458 $ 241 2022 $ 927 $ 66 $ 828 $ (169) $ 659 $ 1,651 $ 959 $ 448 $ 244 2023 $ 940 $ 56 $ 836 $ (165) $ 671 $ 1,667 $ 972 $ 448 $ 247 2024 $ 954 $ 36 $ 845 $ (162) $ 683 $ 1,672 $ 989 $ 433 $ 250 2025 $ 967 $ 32 $ 854 $ (159) $ 695 $ 1,694 $ 1,002 $ 439 $ 252 2026 $ 980 $ 32 $ 863 $ (157) $ 706 $ 1,719 $ 1,019 $ 445 $ 255 2027 $ 994 $ 33 $ 872 $ (155) $ 717 $ 1,743 $ 1,035 $ 451 $ 258 2028 $ 1,007 $ 33 $ 881 $ (154) $ 727 $ 1,767 $ 1,050 $ 457 $ 260 2029 $ 1,021 $ 33 $ 890 $ (153) $ 737 $ 1,791 $ 1,065 $ 463 $ 263 2030 $ 1,034 $ 34 $ 899 $ (153) $ 746 $ 1,814 $ 1,080 $ 469 $ 265 2031 $ 1,048 $ 34 $ 908 $ (153) $ 755 $ 1,837 $ 1,094 $ 474 $ 268 2032 $ 1,061 $ 35 $ 917 $ (153) $ 764 $ 1,860 $ 1,109 $ 480 $ 271 2033 $ 1,074 $ 35 $ 926 $ (153) $ 773 $ 1,882 $ 1,123 $ 486 $ 273 2034 $ 1,088 $ 35 $ 935 $ (153) $ 781 $ 1,905 $ 1,137 $ 492 $ 276 2035 $ 1,101 $ 36 $ 944 $ (154) $ 790 $ 1,927 $ 1,151 $ 497 $ 279 2036 $ 1,115 $ 36 $ 952 $ (154) $ 798 $ 1,949 $ 1,165 $ 503 $ 281 

30 Yr NPV at 3% $ 14,054 $ 1,281 $ 12,801 $ (3,514) $ 9,286 $ 24,622 $ 14,505 $ 6,590 $ 3,527 

30 Yr NPV at 7% $ 7,215 $ 754 $ 6,762 $ (2,143) $ 4,619 $ 12,588 $ 7,429 $ 3,372 $ 1,787 
Aggregate Cost and Cost per Ton

I Note that the emissions reductions shown in Table 8A.3-5 are not identical to the reductions one would get using

the inventories presented in Table 8A.2-3. The emissions inventories in Table 8A.2-3 are for land based nonroad engines

only and do not include emissions associated with locomotive and marine engines. To make the comparison between the

Case 1 $/ton and the NRT4 full program $/ton, the Case 1 locomotive and marine emissions reductions are included with

the Case 1 nonroad land based emissions reductions. Because the emissions reductions associated with locomotive and

marine engines are directly proportional to gallons of fuel consumed (because no new emission control hardware is being

added to those engines), we have calculated the locomotive and marine emissions reductions by taking the ratio of the

Case 1 locomotive and marine gallons consumed to the NRT4 full program locomotive and marine gallons consumed and

multiplied that ratio by the NRT4 locomotive and marine emissions reductions to arrive at the Case 1 locomotive and

marine emissions reductions. These Case 1 locomotive and marine emissions reductions were then added to the Case 1

nonroad land based emissions reductions to arrive at the Case 1 emissions reductions shown in Table 8A.3-5. 

8-83

The calculations of cost per ton of each emission reduced under the Case 1 sensitivity divides

the net present value of the annual costs assigned to each pollutant (Table 8A.3-5) by the net

present value of the total annual reductions of each pollutant (Table 8A.3-5). The 30-year net

present value of the costs associated with each pollutant, calculated with a three percent discount

rate, are shown in Table 8A.3-5 as $6.6 billion for NOx+NMHC, $14.5 billion for PM, and $3.5

billion for SOx with the total cost of the program estimated at $24.6 billion. The 30-year net

present value, with a three percent discount rate, of emission reductions are estimated at 4.4

million tons of NOx+NMHC, 919 thousand tons of PM and 4.0 million tons of SOx (see Table

8A.3-5). How these emissions reductions were developed is described in Section 8A.2 (see

Table 8A.2-3).I The results of the cost per ton calculations are shown in Table 8A.3-6.

Table 8A.3-6

Aggregate Cost per Ton for the Case 1 Sensitivity

30-year Net Present Values at a 3% and 7% Discount Rate ($2002)

Item 3% discount rate 7% discount rate Source

Cost per Ton NOx+NMHC $1,490 $1,700 Calculated

Cost per Ton PM $15,800 $16,500 Calculated

Cost per Ton SOx $870 $800 Calculated

We have also calculated the cost per ton of emissions reduced in the year 2030 using the

annual costs and emission reductions in that year alone. This number, shown in Table 8A.3-7,

approaches the long-term cost per ton of emissions reduced.
Final Regulatory Impact Analysis

8-84

Table 8A.3-7

Long-Term Cost per Ton of the Case 1 Sensitivity 

Annual Values without Discounting ($2002)

Pollutant Long-Term Cost per Ton in 2030

NOx+NMHC $1,000

PM $13,200

SOx $1,050

8A.3.2 Costs and Costs per Ton of the Case 2 Sensitivity

Under the Case 2 sensitivity, more generator sets are assumed to be mobile than are assumed

under NRT4 full engine and fuel program, as described in Section 8A.1. This results in higher

engine and equipment variable costs since more generator sets (gensets) add NOx adsorbers and

CDPFs and more equipment fixed costs since more machines must undergo redesign and product

support literature changes. Engine fixed costs would not change since we believe that the R&D

work estimated for the NRT4 full program would cover these additional gensets. Fuel-related

costs would also increase because more machines would incur CDPF and CCV maintenance

costs and CDPF regeneration costs. Increased costs for the incrementally higher cost fuel and

savings associated with that fuel should not change since our earlier calculations for the NRT4

full engine and fuel program would have included these costs (i.e., those costs and savings are

included in the NRT4 final rule).

We have calculated the increased engine variable costs using the equations shown in Table

6.4-2 and have applied those costs to the same nonroad engine fleet with the exception that more

gensets are included. Likewise, we followed the same process for developing equipment costs as

described in Chapter 6 to generate the higher equipment fixed and variable costs.

Because more machines are adding the new engine hardware (CDPFs and NOx adsorbers),

the emissions reductions associated with the Case 2 sensitivity would be higher than under the

NRT4 final program. These higher emissions reductions were generated using our NONROAD

model as discussed in section 8A.2.2. These emissions reductions are directly proportional to

the increased amount of fuel that would be consumed in these additional engines and, likewise,

to the increased fuel-related costs under this sensitivity. Using that direct relationship, we can

estimate the incremental fuel-related costs by calculating the ratio of fuel-related costs under the

full engine and fuel program to the emissions reductions under the full engine and fuel program

and then applying that ratio to the emissions reductions under the Case 2 sensitivity. Table

8A.3-8 presents the annual costs, the costs by pollutant, and the emissions reductions of the Case

2 sensitivity. Note that costs have been allocated as done under the NRT4 full engine and fuel

program (see Table 8.1-2). Note also that the emissions reductions shown in Table 8A.3-8

include the higher reductions from gensets and the nonroad, locomotive, and marine reductions

that would occur under the full engine and fuel program.
Table 8A.3-8

Summary of Aggregate Costs, Costs by Pollutant, and Emissions Reductions Associated with the Case 2 Se

Year Engine Costs

($million)

Equipment

Costs

($million)

Fuel Costs

($million)

Other Operating

Costs ($million)

Net Operating

Costs ($million)

Total Annual

Costs

($million)

PM Costs

($million)

NOx+NMHC

Costs

($million)

SOx Costs

($million)

2007 $ - $ - $ 161 $ (181) $ (21) $ (21) $ (7) $ - $ (14) 2008 $ 81 $ 5 $ 281 $ (318) $ (37) $ 49 $ 73 $ 0 $ (25) 2009 $ 82 $ 5 $ 286 $ (324) $ (38) $ 49 $ 74 $ 0 $ (26) 2010 $ 80 $ 5 $ 602 $ (375) $ 228 $ 312 $ 179 $ 34 $ 99 2011 $ 423 $ 67 $ 811 $ (415) $ 396 $ 885 $ 486 $ 267 $ 133 2012 $ 745 $ 111 $ 902 $ (383) $ 520 $ 1,376 $ 803 $ 377 $ 195 2013 $ 906 $ 126 $ 984 $ (352) $ 631 $ 1,663 $ 996 $ 421 $ 246 2014 $ 1,000 $ 151 $ 1,041 $ (349) $ 691 $ 1,842 $ 987 $ 591 $ 264 2015 $ 989 $ 157 $ 1,103 $ (339) $ 764 $ 1,910 $ 1,037 $ 596 $ 278 2016 $ 959 $ 158 $ 1,113 $ (319) $ 793 $ 1,911 $ 1,052 $ 576 $ 282 2017 $ 947 $ 158 $ 1,124 $ (302) $ 822 $ 1,927 $ 1,070 $ 571 $ 287 2018 $ 939 $ 154 $ 1,136 $ (287) $ 849 $ 1,941 $ 1,075 $ 574 $ 292 2019 $ 928 $ 155 $ 1,149 $ (274) $ 875 $ 1,958 $ 1,105 $ 556 $ 296 2020 $ 939 $ 155 $ 1,162 $ (262) $ 900 $ 1,994 $ 1,130 $ 563 $ 301 2021 $ 953 $ 103 $ 1,177 $ (254) $ 923 $ 1,979 $ 1,132 $ 542 $ 305 2022 $ 967 $ 70 $ 1,193 $ (247) $ 946 $ 1,984 $ 1,140 $ 533 $ 310 2023 $ 981 $ 60 $ 1,210 $ (241) $ 969 $ 2,010 $ 1,160 $ 535 $ 315 2024 $ 995 $ 39 $ 1,227 $ (237) $ 991 $ 2,025 $ 1,184 $ 522 $ 319 2025 $ 1,009 $ 33 $ 1,245 $ (233) $ 1,012 $ 2,054 $ 1,201 $ 529 $ 324 2026 $ 1,023 $ 33 $ 1,263 $ (229) $ 1,034 $ 2,090 $ 1,224 $ 537 $ 329 2027 $ 1,037 $ 34 $ 1,281 $ (227) $ 1,054 $ 2,125 $ 1,247 $ 545 $ 333 2028 $ 1,051 $ 34 $ 1,300 $ (226) $ 1,074 $ 2,159 $ 1,268 $ 552 $ 338 2029 $ 1,065 $ 34 $ 1,318 $ (225) $ 1,093 $ 2,192 $ 1,290 $ 560 $ 343 2030 $ 1,079 $ 35 $ 1,337 $ (225) $ 1,112 $ 2,226 $ 1,311 $ 568 $ 347 2031 $ 1,093 $ 35 $ 1,356 $ (225) $ 1,130 $ 2,259 $ 1,331 $ 576 $ 352 2032 $ 1,107 $ 36 $ 1,374 $ (226) $ 1,149 $ 2,291 $ 1,351 $ 583 $ 357 2033 $ 1,121 $ 36 $ 1,393 $ (227) $ 1,167 $ 2,324 $ 1,372 $ 591 $ 361 2034 $ 1,135 $ 37 $ 1,412 $ (228) $ 1,185 $ 2,356 $ 1,392 $ 599 $ 366 2035 $ 1,149 $ 37 $ 1,431 $ (229) $ 1,202 $ 2,389 $ 1,412 $ 606 $ 371 2036 $ 1,163 $ 38 $ 1,450 $ (230) $ 1,220 $ 2,421 $ 1,431 $ 614 $ 375 

30 Yr NPV at 3% $ 14,628 $ 1,344 $ 18,772 $ (5,236) $ 13,535 $ 29,507 $ 17,040 $ 7,988 $ 4,479 

30 Yr NPV at 7% $ 7,502 $ 791 $ 9,891 $ (3,198) $ 6,693 $ 14,986 $ 8,635 $ 4,102 $ 2,248 
Final Regulatory Impact Analysis

J Note that the emissions reductions shown in Table 8A.3-8 are not identical to the reductions one would get using

the inventories presented in Table 8A.2-6. The emissions inventories in Table 8A.2-6 are for land based nonroad engines

only and do not include emissions associated with locomotive and marine engines. To make the comparison between the

Case 2 $/ton and the NRT4 full program $/ton, the Case 2 locomotive and marine emissions reductions are included with

the Case 2 nonroad land based emissions reductions. The Case 2 locomotive and marine emissions reductions would be

identical to those under the NRT4 full program since nothing about the Case 2 sensitivity would impact emissions

reductions from locomotive and marine engines. Therefore, the NRT4 full program locomotive and marine emissions

reductions have been added to the Case 2 nonroad land based emissions reductions to arrive at the Case 2 emissions

reductions shown in Table 8A.3-8.

8-86

The calculations of cost per ton of each emission reduced under the Case 2 sensitivity divides

the net present value of the annual costs assigned to each pollutant (Table 8A.3-8) by the net

present value of the total annual reductions of each pollutant (Table 8A.3-8). The 30-year net

present value of the costs associated with each pollutant, calculated with a three percent discount

rate, are shown in Table 8A.3-8 as $8.0 billion for NOx+NMHC, $17.0 billion for PM, and $4.5

billion for SOx, with the total cost of the program estimated at $29.5 billion. The 30-year net

present value, with a three percent discount rate, of emission reductions are estimated at 8.7

million tons of NOx+NMHC, 1.6 million tons of PM, and 6.5 million tons of SOx (see Table

8A.3-8). How these emissions reductions were developed is described in Section 8A.2 (see

Table 8A.2-6).J The results of the cost per ton calculations are shown in Table 8A.3-9.

Table 8A.3-9

Aggregate Cost per Ton for the Case 2 Sensitivity

30-year Net Present Values at a 3% and 7% Discount Rate ($2002)

Item 3% discount rate 7% discount rate Source

Cost per Ton NOx+NMHC $920 $1,050 Calculated

Cost per Ton PM $10,800 $11,200 Calculated

Cost per Ton SOx $690 $630 Calculated

We have also calculated the cost per ton of emissions reduced in the year 2030 using the

annual costs and emission reductions in that year alone. This number, shown in Table 8A.3-10,

approaches the long-term cost per ton of emissions reduced.

Table 8A.3-10

Long-Term Cost per Ton of the Case 2 Sensitivity 

Annual Values without Discounting ($2002)

Pollutant Long-Term Cost per Ton in 2030

NOx+NMHC $620

PM $9,000

SOx $810
Aggregate Cost and Cost per Ton

8-87

8A.4 Summary of the Sensitivity Analyses Results

We present here a summary of the results of the Case 1 and Case 2 sensitivity analyses, and

we compare these results to the NRT4 full engine and fuel program (i.e., the NRT4 Final Rule).

Table 8A.4-1 shows the emission reduction comparison between the NRT4 full program and

the sensitivity cases for PM and NOx. As can be seen, the Case 1 sensitivity results in a

decrease in both PM and NOx emissions reductions on the order of 35 to 40 percent. The Case 2

sensitivity results in an increase in PM reductions on the order of 10 percent and an increase in

NOx reductions on the order of 20 percent.

Table 8A.4-1

Emissions Reduction* Comparison for Case 1 and Case 2 Sensitivity Analyses

30 Year Net Present Values at a 3% Discount Rate

Baseline/Control Scenario NOx+NMHC

(tons)

Percent

Relative to

NRT4 FRM

PM

(tons)

Percent

Relative to

NRT4 FRM

Nonroad Tier 4 Final Rule 7,077,900 - 1,430,500 -

Case 1 Sensitivity Analysis 4,421,600 -38% 919,400 -36%

Case 2 Sensitivity Analysis 8,662,500 22% 1,584,300 11%

* See Tables 8.6-1, 8A.3-5, and 8A.3-8, respectively.

Table 8A.4-2 summarizes the results of the two sensitivity cases with respect to costeffectiveness for NMHC+NOx, PM, and SOx, and compares these values to the final NRT4

program. As can be seen, the Case 1 sensitivity analysis results in an increase in the $/ton

estimates for all pollutants. However, in all cases, these estimates are still within the range of

previous mobile source control programs for NMHC+NOx and PM, and for SOx on the same

order as stationary control programs for acid rain (see Tables VI.D-3, -4, and -5 of the preamble

for this final rule). For the Case 2 sensitivity analysis, Table 8A.4-2 shows that the costeffectiveness for NOx+NMHC and for PM are lower than for the final Tier 4 program, and for

SOx the cost-effectiveness is the same as for the final Tier 4 program.
Final Regulatory Impact Analysis

8-88

Table 8A.4-2

Comparison of Aggregate Cost per Ton Estimates: NRT4 Final Rule, Case 1 Sensitivity

Analysis, and Case 2 Sensitivity Analysis

30-year Net Present Values at a 3 percent Discount Rate ($2002)

Pollutant Nonroad Tier 4

Final Rule

Case 1

 Sensitivity

Analysis

Case 2

 Sensitivity

Analysis

NOx+NMHC ($/ton) $1,010 $1,490 $920

PM ($/ton) $11,200 $15,800 $10,800

SOx ($/ton) $690 $870 $690
Aggregate Cost and Cost per Ton

8-89

Appendix 8B: Fuel Volumes used throughout Chapter 8

The volumes in this Appendix were developed from the information contained in Section 7.1

of Chapter 7 of the RIA. Demand volumes are estimated for each EPA use category, including

nonroad, locomotive, marine, and highway diesel fuel, and heating oil, for 2014. The 2014

estimated volumes of pipeline downgrade and highway diesel fuel spillover are apportioned to

various EPA use categories depending on the regulatory scenario. By default, this analysis

estimates the volume of fuel which must be desulfurized for supplying the overall demand of

each EPA use category. The regulatory scenarios modeled for their volumes for this Chapter

include the Final Rule Program and several sensitivity cases which are summarized here. For

each case, the table which summarizes the 2014 volumes is listed along with the case

description.

Final Rule Program:

- Period from 2007 to 2010 - NRLM must meet a 500 ppm sulfur cap standard. Small refiners

are exempted and are assumed to produce high sulfur distillate and sell that fuel into the

NRLM diesel fuel pool (Table 7.1.3-14). 

- Period from 2010 to 2012 - nonroad must meet a 15 ppm sulfur cap standard and locomotive

and marine must meet a 500 ppm sulfur cap. Small refiners are exempted and can sell

exempted fuel into the nonroad diesel fuel pool, except for most of PADD 1, providing that

they produce 500 ppm fuel (Table 7.1.3-17).

- Period from 2012 to 2014 - NRLM must meet a 15 ppm sulfur cap standard. Small refiners

are exempted and can sell exempted fuel into the NRLM diesel fuel pool, except for most of

PADD 1, providing that they produce 500 ppm fuel (Table 7.1.3-19).

- Period from 2014 and thereafter - The small refiner provisions have expired (Table 7.1.3-20).

NRLM to 500 ppm only:

- Period from 2007 to 2010 - Same as Final Rule Program above for the period 2007 to 2010

(Table 7.1.3-14).

- Period after 2010 - NRLM fuel remains at 500 ppm (Table 7.1.4-1). 

Final Rule Program, EIA nonroad volumes:

- Same as Final Rule Program except that the nonroad volumes were developed using EIA

information instead of using NONROAD (Tables 7.1.4-10, 7.1.4-11, 7.1.4-12, and 7.1.4-13 ).

All the volume streams in each case were apportioned into specific families of similar fuels

depending on the quality of the specific volume stream and whether it was regulated under the

NRLM Program. These fuel families and the streams which comprise them are summarized in

the following table.
Final Regulatory Impact Analysis

8-90

Fuel Families and the Fuels They Represent*

Fuel Family

High Sulfur Old 500 ppm New 500

ppm

Old 15 ppm Reprocessed

Downgrade

New 15 ppm Total

Volume

High Sulfur

(3000 ppm)

distillate fuel

including

NRLM and

heating oil

Small refiner

fuel from

2007 to 2010 

500 ppm

diesel fuel

meeting the

Highway

Diesel Fuel

Program

requirements

500 ppm

diesel fuel

meeting the

Nonroad

Diesel Fuel

Program

requirements 

Small refiner

fuel from

2010 to 2014 

15 ppm

diesel fuel

meeting the

Highway

Diesel Fuel

Program

requirements

Oversupply of

downgrade

into a market

which must be

reprocessed to

15 ppm

15 ppm diesel

fuel meeting

the Nonroad

Diesel Fuel

Program

requirements

Total of

these

various

volumes.

* California gallons are not included. “Affected” 500 ppm gallons are labeled here as “New 500 ppm” and “Affected” 15

ppm gallons are the summation of the columns labeled “Reprocessed Downgrade” and “New 15 ppm.”

The 2014 volumes are adjusted to estimate the volumes in each year from 2007 to 2040 using

growth ratios compared to 2014 based on the growth rate factors in Tables 7.1.5-1 and 7.1.5-2. 

Analyzing and categorizing the volumes in this fashion resulted in the development of the

input volumes used in this chapter. For a more complete summary of how the volumes were

calculated consult Section 7.1 of Chapter 7 of the RIA. The following tables summarize this

information. 
Aggregate Cost and Cost per Ton

8-91

Table 8B-1

Nationwide Nonroad Volumes Under the NRT4 Final Rule Fuel Program

Year High Sulfur 

(million gallons)

Old 500 ppm 

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 4,027 239 4,790 2,369 - - 11,426 

2008 584 179 8,406 2,526 - - 11,695 

2009 597 183 8,599 2,585 - - 11,964 

2010 255 673 4,014 2,643 - 6,189 12,233 

2011 - 1,043 614 2,701 - 8,145 12,504 

2012 - 1,066 528 2,760 - 8,420 12,774 

2013 - 1,088 468 2,818 - 8,671 13,045 

2014 - 463 199 2,941 68 9,645 13,316 

2015 - - - 3,047 118 10,421 13,586 

2016 - - - 3,107 121 10,626 13,854 

2017 - - - 3,167 123 10,832 14,122 

2018 - - - 3,227 125 11,037 14,390 

2019 - - - 3,288 127 11,243 14,658 

2020 - - - 3,352 130 11,448 14,926 

2021 - - - 3,408 132 11,654 15,193 

2022 - - - 3,468 134 11,859 15,461 

2023 - - - 3,528 137 12,064 15,729 

2024 - - - 3,588 139 12,270 15,997 

2025 - - - 3,648 141 12,475 16,265 

2026 - - - 3,708 144 12,679 16,531 

2027 - - - 3,767 146 12,883 16,797 

2028 - - - 3,827 148 13,088 17,063 

2029 - - - 3,887 151 13,292 17,329 

2030 - - - 3,946 153 13,496 17,595 

2031 - - - 4,006 155 13,700 17,861 

2032 - - - 4,066 158 13,904 18,127 

2033 - - - 4,125 160 14,108 18,393 

2034 - - - 4,185 162 14,312 18,659 

2035 - - - 4,245 165 14,516 18,925 

2036 - - - 4,304 167 14,720 19,191 
Final Regulatory Impact Analysis

8-92

Table 8B-2

Nationwide Locomotive Volumes Under the NRT4 Final Rule Fuel Program 

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 968 45 1,141 539 - - 2,694 

2008 138 40 1,978 568 - - 2,724 

2009 140 40 2,005 576 - - 2,761 

2010 59 356 1,805 585 - - 2,805 

2011 - 591 1,671 596 - - 2,858 

2012 - 410 761 602 - 1,114 2,841 

2013 - 278 99 607 - 1,925 2,909 

2014 - 849 42 589 - 1,476 2,932 

2015 - 1,266 - 577 - 1,154 2,956 

2016 - 1,279 - 583 - 1,166 2,988 

2017 - 1,291 - 589 - 1,177 3,015 

2018 - 1,301 - 593 - 1,186 3,038 

2019 - 1,313 - 599 - 1,197 3,067 

2020 - 1,322 - 603 - 1,205 3,089 

2021 - 1,329 - 606 - 1,212 3,104 

2022 - 1,341 - 611 - 1,222 3,132 

2023 - 1,353 - 617 - 1,233 3,160 

2024 - 1,365 - 622 - 1,244 3,187 

2025 - 1,378 - 628 - 1,256 3,218 

2026 - 1,389 - 633 - 1,266 3,244 

2027 - 1,400 - 638 - 1,276 3,270 

2028 - 1,411 - 643 - 1,286 3,295 

2029 - 1,422 - 648 - 1,296 3,321 

2030 - 1,433 - 653 - 1,306 3,347 

2031 - 1,444 - 658 - 1,316 3,373 

2032 - 1,455 - 663 - 1,327 3,399 

2033 - 1,466 - 668 - 1,337 3,425 

2034 - 1,477 - 674 - 1,347 3,450 

2035 - 1,488 - 679 - 1,357 3,476 

2036 - 1,500 - 684 - 1,367 3,502 
Aggregate Cost and Cost per Ton

8-93

Table 8B-3

Nationwide Marine Volumes Under the NRT4 Final Rule Fuel Program 

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 806 21 849 252 - - 1,929 

2008 190 23 1,476 266 - - 1,955 

2009 192 23 1,494 269 - - 1,979 

2010 81 269 1,380 273 - 0 2,003 

2011 - 452 1,304 277 - 0 2,033 

2012 - 292 636 280 - 851 2,059 

2013 - 175 148 283 - 1,472 2,078 

2014 - 222 62 281 - 1,605 2,103 

2015 - 257 - 280 - 1,706 2,126 

2016 - 259 - 283 - 1,722 2,146 

2017 - 262 - 286 - 1,741 2,170 

2018 - 266 - 290 - 1,768 2,203 

2019 - 271 - 295 - 1,798 2,240 

2020 - 202 - 299 - 1,818 2,266 

2021 - 152 - 302 - 1,841 2,294 

2022 - 154 - 307 - 1,871 2,331 

2023 - 156 - 311 - 1,892 2,357 

2024 - 158 - 315 - 1,917 2,389 

2025 - 160 - 319 - 1,939 2,417 

2026 - 162 - 323 - 1,964 2,448 

2027 - 164 - 327 - 1,989 2,479 

2028 - 166 - 331 - 2,014 2,510 

2029 - 168 - 335 - 2,039 2,542 

2030 - 170 - 339 - 2,065 2,573 

2031 - 172 - 343 - 2,090 2,604 

2032 - 175 - 347 - 2,115 2,635 

2033 - 177 - 352 - 2,140 2,667 

2034 - 179 - 356 - 2,165 2,698 

2035 - 181 - 360 - 2,190 2,729 

2036 - 183 - 364 - 2,215 2,760 
Final Regulatory Impact Analysis

8-94

Table 8B-4

Nationwide Nonroad Volumes Under the 500ppm NRLM Scenario

Year High Sulfur 

(million gallons)

Old 500 ppm (million

gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 4,027 239 4,790 2,369 - - 11,426 

2008 584 179 8,406 2,526 - - 11,695 

2009 597 183 8,599 2,585 - - 11,964 

2010 255 936 8,400 2,643 - - 12,233 

2011 - 1,503 8,300 2,701 - - 12,504 

2012 - 1,535 8,479 2,760 - - 12,774 

2013 - 1,568 8,659 2,818 - - 13,045 

2014 - 1,600 8,839 2,877 - - 13,316 

2015 - 1,633 9,018 2,935 - - 13,586 

2016 - 1,665 9,196 2,993 - - 13,854 

2017 - 1,697 9,374 3,051 - - 14,122 

2018 - 1,729 9,552 3,109 - - 14,390 

2019 - 1,762 9,730 3,166 - - 14,658 

2020 - 1,794 9,907 3,224 - - 14,926 

2021 - 1,826 10,085 3,282 - - 15,193 

2022 - 1,858 10,263 3,340 - - 15,461 

2023 - 1,890 10,441 3,398 - - 15,729 

2024 - 1,923 10,619 3,456 - - 15,997 

2025 - 1,955 10,797 3,514 - - 16,265 

2026 - 1,987 10,973 3,571 - - 16,531 

2027 - 2,019 11,150 3,629 - - 16,797 

2028 - 2,051 11,326 3,686 - - 17,063 

2029 - 2,083 11,503 3,744 - - 17,329 

2030 - 2,115 11,679 3,801 - - 17,595 

2031 - 2,147 11,856 3,859 - - 17,861 

2032 - 2,179 12,032 3,916 - - 18,127 

2033 - 2,210 12,209 3,973 - - 18,393 

2034 - 2,242 12,386 4,031 - - 18,659 

2035 - 2,274 12,562 4,088 - - 18,925 

2036 - 2,306 12,739 4,146 - - 19,191 
Aggregate Cost and Cost per Ton

8-95

Table 8B-5

Nationwide Locomotive Volumes Under the 500ppm NRLM Scenario

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 968 45 1,141 539 - - 2,694 

2008 138 40 1,978 568 - - 2,724 

2009 140 40 2,005 576 - - 2,761 

2010 59 211 1,950 585 - - 2,805 

2011 - 339 1,923 596 - - 2,858 

2012 - 342 1,942 602 - - 2,886 

2013 - 345 1,958 607 - - 2,909 

2014 - 347 1,973 611 - - 2,932 

2015 - 350 1,990 616 - - 2,956 

2016 - 354 2,011 623 - - 2,988 

2017 - 357 2,029 629 - - 3,015 

2018 - 360 2,044 633 - - 3,038 

2019 - 364 2,064 640 - - 3,067 

2020 - 366 2,079 644 - - 3,089 

2021 - 368 2,089 647 - - 3,104 

2022 - 371 2,108 653 - - 3,132 

2023 - 374 2,127 659 - - 3,160 

2024 - 378 2,145 664 - - 3,187 

2025 - 381 2,166 671 - - 3,218 

2026 - 385 2,184 677 - - 3,244 

2027 - 388 2,202 682 - - 3,270 

2028 - 391 2,220 688 - - 3,295 

2029 - 394 2,239 694 - - 3,321 

2030 - 398 2,258 699 - - 3,347 

2031 - 401 2,277 705 - - 3,373 

2032 - 404 2,296 711 - - 3,399 

2033 - 408 2,315 717 - - 3,425 

2034 - 411 2,334 723 - - 3,450 

2035 - 415 2,354 729 - - 3,476 

2036 - 418 2,374 735 - - 3,502 
Final Regulatory Impact Analysis

8-96

Table 8B-6

Nationwide Marine Volumes Under the 500ppm NRLM Scenario

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 806 21 849 252 - - 1,929 

2008 190 23 1,476 266 - - 1,955 

2009 192 23 1,494 269 - - 1,979 

2010 81 142 1,508 273 - - 2,003 

2011 - 229 1,527 277 - - 2,033 

2012 - 232 1,546 280 - - 2,059 

2013 - 234 1,560 283 - - 2,078 

2014 - 237 1,579 286 - - 2,103 

2015 - 240 1,597 289 - - 2,126 

2016 - 242 1,612 292 - - 2,146 

2017 - 245 1,630 295 - - 2,170 

2018 - 249 1,654 300 - - 2,203 

2019 - 253 1,682 305 - - 2,240 

2020 - 256 1,702 309 - - 2,266 

2021 - 259 1,723 312 - - 2,294 

2022 - 263 1,751 317 - - 2,331 

2023 - 266 1,770 321 - - 2,357 

2024 - 270 1,794 325 - - 2,389 

2025 - 273 1,815 329 - - 2,417 

2026 - 276 1,838 333 - - 2,448 

2027 - 280 1,862 337 - - 2,479 

2028 - 283 1,885 342 - - 2,510 

2029 - 287 1,909 346 - - 2,542 

2030 - 290 1,932 350 - - 2,573 

2031 - 294 1,956 355 - - 2,604 

2032 - 297 1,979 359 - - 2,635 

2033 - 301 2,003 363 - - 2,667 

2034 - 305 2,026 367 - - 2,698 

2035 - 308 2,050 372 - - 2,729 

2036 - 312 2,073 376 - - 2,760 
Aggregate Cost and Cost per Ton

8-97

Table 8B-7

Nationwide Nonroad Volumes Under the Case 1 Sensitivity

Year High Sulfur 

(million gallons)

Old 500 ppm

 (million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 2,996 444 3,671 1,959 - - 9,070 

2008 592 153 6,373 2,067 - - 9,186 

2009 600 155 6,454 2,093 - - 9,302 

2010 253 66 3,086 2,141 - 3,873 9,419 

2011 - - 631 2,183 - 6,721 9,535 

2012 - 358 531 2,188 - 6,574 9,651 

2013 - 621 460 2,198 - 6,488 9,767 

2014 - 262 194 2,275 - 7,153 9,884 

2015 - - - 2,338 - 7,662 10,000 

2016 - - - 2,366 - 7,751 10,116 

2017 - - - 2,393 - 7,840 10,233 

2018 - - - 2,420 - 7,929 10,349 

2019 - - - 2,447 - 8,018 10,465 

2020 - - - 2,474 - 8,107 10,581 

2021 - - - 2,502 - 8,196 10,698 

2022 - - - 2,529 - 8,285 10,814 

2023 - - - 2,556 - 8,374 10,930 

2024 - - - 2,583 - 8,464 11,047 

2025 - - - 2,610 - 8,553 11,163 

2026 - - - 2,638 - 8,642 11,279 

2027 - - - 2,665 - 8,731 11,395 

2028 - - - 2,692 - 8,820 11,512 

2029 - - - 2,719 - 8,909 11,628 

2030 - - - 2,746 - 8,998 11,744 

2031 - - - 2,774 - 9,087 11,861 

2032 - - - 2,801 - 9,176 11,977 

2033 - - - 2,828 - 9,265 12,093 

2034 - - - 2,855 - 9,354 12,210 

2035 - - - 2,882 - 9,444 12,326 

2036 - - - 2,910 - 9,533 12,442 
Final Regulatory Impact Analysis

8-98

Table 8B-8

Nationwide Locomotive Volumes Under the Case 1 Sensitivity

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 910 116 1,129 539 - - 2,694 

2008 162 37 1,957 568 - - 2,724 

2009 164 38 1,983 576 - - 2,761 

2010 70 426 1,741 569 - - 2,805 

2011 - 715 1,575 568 - - 2,858 

2012 - 410 732 590 - 1,155 2,886 

2013 - 188 120 607 - 1,995 2,909 

2014 - 455 50 584 - 1,842 2,932 

2015 - 651 - 570 - 1,735 2,956 

2016 - 658 - 576 - 1,754 2,988 

2017 - 664 - 581 - 1,770 3,015 

2018 - 669 - 586 - 1,783 3,038 

2019 - 675 - 591 - 1,801 3,067 

2020 - 680 - 595 - 1,813 3,089 

2021 - 684 - 599 - 1,822 3,104 

2022 - 690 - 604 - 1,838 3,132 

2023 - 696 - 609 - 1,855 3,160 

2024 - 702 - 614 - 1,871 3,187 

2025 - 709 - 620 - 1,889 3,218 

2026 - 714 - 625 - 1,904 3,244 

2027 - 720 - 630 - 1,919 3,270 

2028 - 726 - 635 - 1,934 3,295 

2029 - 731 - 640 - 1,950 3,321 

2030 - 737 - 645 - 1,965 3,347 

2031 - 743 - 650 - 1,980 3,373 

2032 - 748 - 655 - 1,995 3,399 

2033 - 754 - 660 - 2,010 3,425 

2034 - 760 - 665 - 2,025 3,450 

2035 - 766 - 670 - 2,041 3,476 

2036 - 771 - 675 - 2,056 3,502 
Aggregate Cost and Cost per Ton

8-99

Table 8B-9

Nationwide Marine Volumes Under the Case 1 Sensitivity

Year High Sulfur 

(million gallons)

Old 500 ppm

(million gallons)

New 500 ppm

(million gallons)

Old 15 ppm

(million gallons)

Reprocessed

Downgrade

(million gallons)

New 15 ppm

(million gallons)

Total Volume

(million gallons)

2007 757 67 853 252 - - 1,929 

2008 186 22 1,482 266 - - 1,955 

2009 188 22 1,499 269 - - 1,979 

2010 79 326 1,328 269 - - 2,003 

2011 - 551 1,210 271 - - 2,033 

2012 - 309 511 278 - 961 2,059 

2013 - 133 - 283 - 1,662 2,078 

2014 - 136 - 281 - 1,685 2,103 

2015 - 140 - 280 - 1,706 2,126 

2016 - 141 - 283 - 1,722 2,146 

2017 - 143 - 286 - 1,742 2,170 

2018 - 145 - 290 - 1,768 2,203 

2019 - 147 - 295 - 1,798 2,240 

2020 - 149 - 299 - 1,819 2,266 

2021 - 151 - 302 - 1,841 2,294 

2022 - 153 - 307 - 1,871 2,331 

2023 - 155 - 311 - 1,892 2,357 

2024 - 157 - 315 - 1,917 2,389 

2025 - 159 - 319 - 1,939 2,417 

2026 - 161 - 323 - 1,964 2,448 

2027 - 163 - 327 - 1,989 2,479 

2028 - 165 - 331 - 2,015 2,510 

2029 - 167 - 335 - 2,040 2,542 

2030 - 169 - 339 - 2,065 2,573 

2031 - 171 - 343 - 2,090 2,604 

2032 - 173 - 347 - 2,115 2,635 

2033 - 175 - 352 - 2,140 2,667 

2034 - 177 - 356 - 2,165 2,698 

2035 - 179 - 360 - 2,190 2,729 

2036 - 181 - 364 - 2,215 2,760 
Final Regulatory Impact Analysis

8-100

1. “Guidelines for Preparing Economic Analyses,” U.S. Environmental Protection Agency, EPA

240-R-00-003, September 2000.

2. Power Systems Research, OELink Sales Version, 2002.

3. Nonroad Engine Growth Estimate, Report No. NR-008b, Docket Item II-A-32.

4. “Engine Sales Used in Proposed Nonroad Tier 4 Cost Analysis,” memorandum from Todd

Sherwood to Public Docket No. A-2001-28, Docket Item II-B-37.

5. Dickson, Cheryl, “Heating Oils, 2001,” TRW Petroleum Technologies, TRW-221 PPS, 01/4,

July 2001. 

6. Dickson, Cheryl, “Heating Oils, 2002,” TRW Petroleum Technologies, TRW-226 PPS,

2002/4, September, 2002.

7. Batey, John E. and Roger McDonald, “Advantages of Low Sulfur Home Heating Oil - Interim

Report of Complied Research, Studies, and Data Resources, ” National Oilheat Research

Alliance and the Department of Energy, December 2002.

Chapter 8 References
CHAPTER 9: Cost-Benefit Analysis

9.1 Time Path of Emission Changes for the Final Standards . . . . . . . . . . . . . . . . . . . . . . . 9-8

9.2 Development of Benefits Scaling Factors Based on Differences in Emission Impacts

Between the Final Standards and Modeled Preliminary Control Options . . . . . . . . . . 9-11

9.3 Summary of Modeled Benefits and Apportionment Method . . . . . . . . . . . . . . . . . . . 9-12

9.3.1 Overview of Analytical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-16

9.3.2 Air Quality Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-17

9.3.2.1 PM Air Quality Modeling with REMSAD . . . . . . . . . . . . . . . . . . . . . . . . 9-17

9.3.2.2 Ozone Air Quality Modeling with CAMx . . . . . . . . . . . . . . . . . . . . . . . . . 9-18

9.3.3 Health Impact Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-19

9.3.4 Economic Values for Health Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-23

9.3.5 Welfare Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-24

9.3.5.1 Visibility Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-24

9.3.5.2 Agricultural Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-25

9.3.5.3 Other Welfare Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-26

9.3.6 Treatment of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-28

9.3.7 Model Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-29

9.3.8 Apportionment of Benefits to NOx, SO2, and Direct PM Emissions Reductions 9-39

9.4 Estimated Benefits of Final Nonroad Diesel Engine Standards in 2020 and 2030 . . . 9-42

9.5 Development of Intertemporal Scaling Factors and Calculation of Benefits Over Time

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-48

9.6 Comparison of Costs and Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-53

APPENDIX 9A: Benefits Analysis of Modeled Preliminary Control Option . . . . . . . . . . 9-77

APPENDIX 9B: Supplemental Analyses Addressing Uncertainties in the ConcentrationResponse and Valuation Functions for Particulate Matter Health Effects . . . . . . . . 9-205

APPENDIX 9C: Sensitivity Analyses of Key Parameters in the Benefits Analysis . . . . 9-250

APPENDIX 9D: Visibility Benefits Estimates for Individual Class I Areas . . . . . . . . . 9-269
Cost-Benefit Analysis

AEmissions from nonroad diesel engines include directly emitted fine particles (carbon and sulfates) as well as

gaseous pollutants that react in the atmosphere to form fine particles. This final rule will results in reductions in

ambient PM particle levels due to reductions in both directly emitted particles as well as reductions in PM precursor

emissions, including NOx and SO2.

B

As discussed in Chapter 2, because of the long lead times to conduct complex photochemical air quality

modeling at the national scale, decisions must be made early in the process about the scenarios to be modeled. 

Based on updated information and public comment, EPA has made changes to the final control program, which

results in changes in emissions as detailed in Chapter 3, section 3.6. 

CNote that the methodology for estimating visibility benefits is unchanged from proposal. The documents

related to the IAQR can be found at OAR Docket number 2003-0053.

9-1

CHAPTER 9: Cost-Benefit Analysis

This chapter reports EPA’s analysis of the public health and welfare impacts and associated

monetized benefits to society of the final Nonroad Diesel Engines Tier 4 Standards. EPA is

required by Executive Order 12866 to estimate the costs and benefits of major new pollution

control regulations. Accordingly, the analysis presented here attempts to answer three questions:

(1) what are the physical health and welfare effects of changes in ambient air quality resulting

from reductions in nitrogen oxides (NOx), sulfur dioxide (SO2), non-methane hydrocarbons

(NMHC), carbon monoxide (CO) and direct diesel particulate matter (PM2.5)

A emissions?; (2)

how much are the changes in these effects attributable to the final rule worth to U.S. citizens as a

whole in monetary terms?; and (3) how do the monetized benefits compare to the costs over

time? It constitutes one part of EPA’s thorough examination of the relative merits of this

regulation. In Chapter 12, of the Draft RIA, we provided an analysis of the benefits of several

alternatives to the selected standards to examine their relative benefits and costs for public

comment. 

For the final rulemaking, we rely on the air quality modeling conducted for the proposed

rule, documented in the Regulatory Impact Analysis (U.S. EPA, 2003a), available at

http://www.epa.gov/nonroad.

B

 To estimate the benefits of the final rule, we use a set of scaling

factors which separately estimate a set of emission reduction profiles for NOx, SO2, and directly

emitted diesel PM2.5. For this analysis of the final rule, we conduct a benefits transfer analysis

using those same scaling factors, applied to the updated results of the modeled preliminary

control option which accounts for changes in the health benefits methodology adopted during the

recent proposed Interstate Air Quality Rule (IAQR) analysis.C These methodological changes

are reflected both in the detailed estimates for 2020 and 2030 and in the time stream of total

monetized benefits. The methodological changes are summarized in this chapter and described

in detail in Appendix 9A. 

EPA has used the best available information and tools of analysis to quantify the expected

changes in public health, environmental and economic benefits for the modeled option. We
Final Regulatory Impact Analysis

9-2

summarize the results of that analysis in section 9.3, and present details in Appendix 9A, directly

following this chapter. The standards we are finalizing in this rulemaking are slightly different

in the amount of emission reductions expected to be achieved in 2020 and 2030 relative to both

the proposed standards and the preliminary modeled option. As such, we determined that

benefits would need to be scaled to reflect the differences in emission reductions between the

modeled and final standards. The results of that scaling analysis are the focus of this chapter.

In order to characterize the benefits attributable to the Nonroad Diesel Engines standards,

given the constraints on time and resources available for the analysis, we use a benefits transfer

method to scale the benefits of the modeled preliminary control options to reflect the differences

in emission reductions. We also apply intertemporal scaling factors to examine the stream of

benefits over the rule implementation period. The benefits transfer method used to estimate

benefits for the final rule is similar to that used to estimate benefits in the recent analysis of the

Large SI/Recreational Vehicles standards (see U.S. EPA 2002, Docket A-2000-01, Document VB-4). A similar method has also been used in recent benefits analyses for the proposed Clean

Air Act Section 112 Utility Mercury Emission Reduction rule, the proposed Industrial Boilers

and Process Heaters National Emissions Standards for Hazardous Air Pollutants (NESHAP)

standards (Docket numbers OAR-2003-A-96-47) and the Reciprocating Internal Combustion

Engines NESHAP standards (Docket numbers OAR-2002-0059 and A-95-35). One significant

limitation to this method is the inability to scale ozone-related benefits. Because ozone is a

homogeneous gaseous pollutant formed through complex atmospheric photochemical processes,

it is not possible to apportion ozone benefits to the precursor emissions of NOx and VOC. 

Coupled with the potential for NOx reductions to either increase or decrease ambient ozone

levels, this prevents us from scaling the benefits associated with a particular combination of

VOC and NOx emissions reductions to another (a more detailed discussion is provided below). 

Because of our inability to scale ozone benefits, we provide the ozone benefits results for the

modeled preliminary control options as a referent, but do not include ozone benefits as part of

the monetized benefits of the standards. For the most part, quantifiable ozone benefits do not

contribute significantly to the monetized benefits: thus, their omission will not materially affect

the conclusions of the benefits analysis. 

Table 9-1 lists the known quantifiable and unquantifiable effects considered for this analysis. 

We quantify benefits for the contiguous 48 states. Note that this table categorizes ozone-related

benefits as unquantified effects. Furthermore, we quantify benefits for the contiguous 48 states. 

We have quantified ozone-related benefits in our modeling of the preliminary control option,

summarized in Section 9.3 and detailed in Appendix 9A. However, as noted above, we are

unable to quantify ozone-related benefits for the final standards. It is important to note that there

are significant categories of benefits which can not be monetized (or in many cases even

quantified), resulting in a significant limitation to this analysis. Also, EPA currently does not

have appropriate tools for modeling changes in ambient concentrations of CO or air toxics input

into a national benefits analysis. Although these pollutants have been linked to numerous

adverse health effects, we are unable to quantify the CO- or air toxics-related health or welfare

benefits of the final rule at this time. We also omitted the significant SO2 reductions from lower

sulfur in home heating oil in the Northeast.
Cost-Benefit Analysis

9-3

The benefit analysis that we performed for our rule can be thought of as having seven parts,

each of which will be discussed separately in the Sections that follow. These seven steps include

the following:

1. Identification of final standards and calculation of the impact that the standards will have

on the nationwide inventories for NOx, non-methane hydrocarbons (NMHC), SO2, and

PM emissions throughout the rule implementation period;

2. Calculation of scaling factors relating emissions changes resulting from the final

standards to emissions changes from a set of preliminary control options that were used

to model air quality and benefits (see Appendix 9A for full details).

3. Apportionment of modeled benefits of preliminary control options to NOx, SO2, and

diesel PM emissions (see Appendix 9A for a complete discussion of the modeling of the

benefits for the preliminary set of standards, including updates in the benefits

methodology since the time of proposal).

4. Application of scaling factors to apportioned modeled benefits associated with NOx, SO2,

and PM in 2020 and 2030.

5. Development of intertemporal scaling factors based on 2020 and 2030 modeled air

quality and benefits results.

6. Application of intertemporal scaling factors to the yearly emission changes expected to

result from the standards from 2010 through 2030 to obtain yearly monetized benefits.

7. Calculation of present value of stream of benefits.

This analysis presents estimates of the potential benefits from the final Nonroad Diesel

Engine rule occurring in future years. The predicted emissions reductions that will result from

the rule have yet to occur, and therefore the actual changes in human health and welfare

outcomes to which economic values are ascribed are predictions. These predictions are based on

the best available scientific evidence and judgment, but there is unavoidable uncertainty

associated with each step in the complex process between regulation and specific health and

welfare outcomes. Uncertainties associated with projecting input and parameter values into the

future may contribute significantly to the overall uncertainty in the benefits estimates. However,

we make these projections to more completely examine the impact of the program as the

equipment fleet turns over. 

In general, the chapter is organized around the seven steps laid out above. In Section 1, we

identify the potential standard to analyze, establish the timeframe over which benefits are

estimated, and summarize emissions impacts. In Section 2, we summarize the changes in

emissions that were used in the preliminary modeled benefits analysis and develop the ratios of

the emissions reductions under the final standards to preliminary emissions reductions that are

used to scale modeled benefits. In Section 3, we summarize the modeled benefits associated with

the emissions changes for the preliminary control options and apportion those benefits to the

individual emission species (NOx, SO2, and PM2.5). In Section 4, we estimate the benefits in

2020 and 2030 for the final standards, based on scaling of the modeled benefits of the

preliminary control options. In Section 5, we develop intertermporal scaling factors based on the

ratios of yearly emission changes to the emission changes in 2020 and 2030 and estimate yearly

benefits of the final standards, based on scaling of the benefits in 2020 and 2030. Finally, in
Final Regulatory Impact Analysis

9-4

Section 6, we compare the estimated streams of benefits and costs over the full implementation

period, 2007 to 2030, to calculate the present value of net benefits for the final standards.
9-5

Table 9-1

Health and Welfare Effects of Pollutants Affected by the Final Nonroad Diesel Engine Rul

Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or

Monetized Effects in

Sensitivity Analyses

 Unquantified Effects

PM/Health Premature mortality in adults

Infant mortalityBronchitis - chronic and acuteHospital admissions - respiratory

and cardiovascular

Emergency room visits for asthmaNon-fatal heart attacks (myocardial

infarction)

Asthma exacerbations (asthmatic

population)

Lower and upper respiratory illnessRespiratory symptoms (asthmatic

population)

Minor restricted activity daysWork loss days

Low birth weightChanges in pulmonary functionChronic respiratory diseases other than chronic Morphological changesAltered host defense mechanismsNon-asthma respiratory emergency room visitsPM reductions associated with reductions in sul

PM/Welfare Visibility in California,

Southwestern, and SoutheasternClass I areas

Visibility in Northeastern, Northwestern, and MVisibility in residential and non-Class I areasHousehold soilingSulfate PM reductions associated with reductionheating oil
Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or

Monetized Effects in

Sensitivity Analyses

 Unquantified Effects

9-6

Ozone/Health Increased airway responsiveness to stimuli

Inflammation in the lungChronic respiratory damagePremature aging of the lungsAcute inflammation and respiratory cell damageIncreased susceptibility to respiratory infectionNon-asthma respiratory emergency room visitsHospital admissions - respiratory Emergency room visits for asthmaMinor restricted activity daysSchool loss daysChronic AsthmaaAsthma attacksCardiovascular emergency room visitsPremature mortality – acute exposuresb

Acute respiratory symptoms

Ozone/Welfare Decreased commercial forest productivity

Decreased yields for fruits and vegetablesDecreased yields for commercial and non-commDamage to urban ornamental plantsImpacts on recreational demand from damaged Damage to ecosystem functions Decreased outdoor worker productivity

Nitrogen andSulfateDeposition/Welfare

Costs of nitrogen controls to reduce eutrophicati

estuaries

Impacts of acidic sulfate and nitrate deposition oImpacts of acidic deposition on commercial fresImpacts of acidic deposition on recreation in terImpacts of nitrogen deposition on commercial fi

forests

Impacts of nitrogen deposition on recreation in eReduced existence values for currently healthy e

SO2/Health Hospital admissions for respiratory and cardiac 

Respiratory symptoms in asthmatics 
Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or

Monetized Effects in

Sensitivity Analyses

 Unquantified Effects

9-7

NOx/Health Lung irritation

Lowered resistance to respiratory infectionHospital Admissions for respiratory and cardiac 

CO/Health Premature mortality

Behavioral effectsHospital admissions - respiratory, cardiovasculaOther cardiovascular effectsDevelopmental effectsDecreased time to onset of angina

NMHCs cHealth

Cancer (diesel PM, benzene, 1,3-butadiene, formAnemia (benzene)Disruption of production of blood components (Reduction in the number of blood platelets (benExcessive bone marrow formation (benzene)Depression of lymphocyte counts (benzene)Reproductive and developmental effects (1,3-buIrritation of eyes and mucous membranes (formRespiratory and respiratory tractAsthma attacks in asthmatics (formaldehyde)Asthma-like symptoms in non-asthmatics (formIrritation of the eyes, skin, and respiratory tract Upper respiratory tract irritation & congestion (

NMHCs cWelfare

Direct toxic effects to animalsBioaccumlation in the food chainReduced odors

a While no causal mechanism has been identified linking new development of chronic asthma to ozone exposure, two epidemiological studie

association between long-term exposure to ozone and development of chronic asthma in exercising children and some non-smoking men (Mc

McDonnell, et al., 1999).

b Premature mortality associated with ozone is not separately included in the calculation of total monetized benefits.c All non-methane hydrocarbons (NMHCs) listed in the table are also hazardous air pollutants listed in Section 112(b) of the Clean Air Act.
Final Regulatory Impact Analysis

9-8

9.1 Time Path of Emission Changes for the Final Standards

The final standards have various cost and emission related components, as described earlier

in this RIA. These components would begin at various times and in some cases would phase in

over time. This means that during the early years of the program there would not be a consistent

match between cost and benefits. This is especially true for the equipment control portions and

initial fuel changes required by the program, where the full equipment cost would be incurred at

the time of equipment purchase, while the fuel and maintenance costs, along with the emission

reductions and benefits resulting from all these costs would occur throughout the lifetime of the

equipment. Because of this inconsistency and our desire to more appropriately match the costs

and emission reductions of our program, our analysis examines costs and benefits throughout the

period of program implementation. This chapter focuses on estimating the stream of benefits

over time and comparing streams of benefits and costs. Detailed information on cost estimates

can be found in chapters 6, 7 and 8 of this RIA.

For the nonroad diesel engine standards, implementation will occur in stages: reductions in

sulfur content of nonroad diesel fuel and then adoption of controls on most new nonroad engines. 

Because full turnover of the fleet of nonroad diesel engines will not occur for many years, the

emission reduction benefits of the standards will not be fully realized until several decades after

the reduction in fuel sulfur content. The timeframe for the analysis reflects this turnover,

beginning in 2007 and extending through 2030.

Chapter 3 discussed the development of the 1996, 2020 and 2030 baseline emissions

inventories for the nonroad sector and for the sectors not affected by this rule. The emission

sources and the basis for current and future-year inventories are listed in Table 9-2. Using these

modeled inventories, emissions with and without the standards are interpolated to provide

streams of emissions from the rule implementation date through full implementation in 2030. 

These streams of emissions are presented in Chapter 3. NOx and VOC contribute to ambient

ozone formation, while NOx, SO2, NMHC/VOC, and directly emitted PM2.5 emissions are

precursors to ambient PM2.5 and PM10 concentrations. Although the rule is expected to reduced

CO and air toxics emissions as well, we do not include benefits related to these reductions in the

benefits analysis due to a lack of appropriate air quality and exposure models.
Cost-Benefit Analysis

9-9

 Table 9-2 

Emissions Sources and Basis for Current and Future-Year Inventories for Air Quality Modeling

Emissions Source 1996 Base year Future-year Base Case Projections

Utilities 1996 NEI Version 3.12

(CEM data)

Integrated Planning Model (IPM)

Non-Utility Point and Area

sources

1996 NEI 

Version 3.12 (point)

Version 3.11 (area)

BEA growth projections

Highway vehicles MOBILE5b model with

MOBILE6 adjustment

factors for VOC and

NOx;

PART5 model for PM 

VMT projection data

Nonroad engines (except

locomotives, commercial

marine vessels, and

aircraft)

NONROAD2002 model BEA and Nonroad equipment

growth projections

Note: Full description of data, models, and methods applied for emissions inventory development and modeling are

provided in the Emissions Inventory TSD (U.S. EPA, 2003a).

Table 9-3 summarizes the expected changes in emissions of key species. SO2 emissions are

expected to be reduced by over 84 percent within the first two years of implementation. 

Emissions of PM2.5, NOx, and NMHC are expected to be reduced significantly over the period of

implementation from 2007 to 2030. Table 9-4 breaks out the expected changes in emissions of

key species for the components the fuel portion of the program.
Final Regulatory Impact Analysis

9-10

Table 9-3 

Summary of Reduction in 48-State Emissionsa

Attributable to Final Nonroad Diesel Engine Standards and Fuel Programs

Tons Reduced

(Percent of baseline from this category)a

Direct PM2.5 NOx SO2 VOC

2010 21,692 149 256,447 525

13% 0% 91% 0%

2015 53,072 193,431 297,513 8,318

33% 17% 99% 8%

2020 85,808 442,061 323,378 18,141

52% 39% 99% 19%

2025 110,043 613,629 349,312 25,002

64% 54% 99% 26%

2030 128,350 734,184 375,354 30,030

72% 62% 99% 31%

a

 NOx, VOC, and CO inventories are for land-based diesel engines only; PM and SO2 inventories include

land-based, recreational marine, commercial marine, and locomotive diesel engines.

Table 9-4 

Summary of Reduction in 48-State Emissions 

Attributable to Final Fuel Programs of the Nonroad Diesel Standards

Tons Direct PM2.5 and SO2 Reduced

Fuel Only Program 500 ppm NRLM Fuel

Program

15 ppm LM Fuel Program

(no home heating oil)

Direct PM2.5 SO2 Direct PM2.5 SO2 Direct PM2.5 SO2

2010 20,051 256,447 19,156 245,007 0 0

2015 23,241 297,389 20,876 267,118 428 5,318

2020 25,248 323,137 22,674 290,192 433 5,382

2025 27,265 348,994 24,482 313,367 427 5,308

2030 29,293 374,982 26,300 336,665 426 5,294
Cost-Benefit Analysis

DAs discussed in Chapter 2, emissions and air quality modeling decisions are made early in EPA’s analytical

process. Since the preliminary control scenario was developed, EPA has gathered more information regarding the

technical feasibility of the standards and considered public comment. As a result, we have revised the control

scenario as described in detail in previous chapters of this document. Section 3.6 describes the changes in the inputs

and resulting emission inventories between the preliminary baseline and control scenarios used for the air quality

modeling and the final baseline and control scenarios. 

9-11

9.2 Development of Benefits Scaling Factors Based on Differences in

Emission Impacts Between the Final Standards and Modeled Preliminary

Control Options

Based on the projected time paths for emissions reductions, we focused our detailed

emissions and air quality modeling on two future years, 2020 and 2030, which reflect partial and

close to complete turnover of the fleet of nonroad diesel engines to rule compliant engines. The

emissions changes modeled for these two years are similar to those in the final standards,

differing in the treatment of smaller engines and fuel requirements.D Table 9-5 summarizes the

reductions in emissions of NOx, SO2, and PM2.5 from baseline for the preliminary and final

standards, the difference between the two, and the ratio of emissions reductions from the final

standards to the preliminary control options. The ratios presented in the last column of Table 9-5

are the basis for the benefits scaling approach discussed below.
Final Regulatory Impact Analysis

9-12

Table 9-5 

Comparison of 48-state Emission Reductionsa, b

in 2020 and 2030 Between Preliminary and Final Standards

Emissions Species Reduction from Baseline Difference in

Reductions 

(Final minus

Preliminary)

Ratio of

Reductions 

(Final/

Preliminary) Preliminary Final

2020

NOx 663,618 442,061 221,557 0.67

SO2 414,692 323,378 91,314 0.78

PM2.5 98,121 85,808 12,313 0.87

2030

NOx 1,009,744 734,184 275,560 0.73

SO2 483,401 375,354 108,047 0.78

PM2.5 138,208 128,350 9,858 0.93

a

 Includes all affected nonroad sources: land-based, recreational marine, commercial marine, and locomotives. b

 We note that the magnitude of NOx reductions determined in the final rule analysis is somewhat less than what

was reported in the proposal's draft RIA, especially in the later years when the fleet has mostly turned over to Tier

4 designs. The greater part of this is due to the fact that we have deferred setting a long-term NOx standard for

mobile machinery over 750 hp to a later action. When this future action is completed, we would expect roughly

equivalent reductions between the proposal and the overall final program, though there are some other effects

reflected in the differing NOx reductions as well, due to updated modeling assumptions and the adjusted NOx

standards levels for engines over 750 hp. Preamble Section II.A.4 contains a detailed discussion of the NOx

standards we are adopting for engines over 750 hp, and the basis for those standards.

9.3 Summary of Modeled Benefits and Apportionment Method

As a second step in the analysis, we calculated scaling factors relating emissions changes

resulting from the final standards to emissions changes from a set of preliminary control options

that were used to model air quality and benefits (see Appendix 9A for full details). Based on the

emissions inventories developed at the time of the proposal for the preliminary control option,

we conducted a benefits analysis to determine the air quality and associated human health and

welfare benefits resulting from the reductions in emissions of NOx, SO2, NMHC/VOC, and

PM2.5. Based on the availability of air quality and exposure models, this summary focuses on

reporting the health and welfare benefits of reductions in ambient PM and ozone concentrations. 

However, health improvements may also come from reductions in exposure to CO and air toxics. 

 The full analysis is available in Appendix 9A and the benefits Technical Support Document

(TSD) (Abt Associates, 2003).

The reductions in emissions of NOx, SO2, and PM2.5 from nonroad engines in the United

States are expected to result in wide-spread overall reductions in ambient concentrations of
Cost-Benefit Analysis

E

 Reductions in NOx are expected to result in some localized increases in ozone concentrations, especially in

NOx-limited large urban areas, such as Los Angeles, New York, and Chicago. A fuller discussion of this

phenomenon is provided in Chapter 2.3. While localized increases in ozone will result in some increases in health

impacts from ozone exposure in these areas, on net, the reductions in NOx are expected to reduce national levels of

health impacts associated with ozone.

9-13

ozone and PM2.5

E

. These improvements in air quality are expected to result in substantial health

benefits, based on the body of epidemiological evidence linking PM and ozone with health

effects such as premature mortality, chronic lung disease, hospital admissions, and acute

respiratory symptoms. Based on modeled changes in ambient concentrations of PM2.5 and

ozone, we estimate changes in the incidence of each health effect using concentration-response

(C-R) functions derived from the epidemiological literature with appropriate baseline

populations and incidence rates. We then apply estimates of the dollar value of each health

effect to obtain a monetary estimate of the total PM- and ozone-related health benefits of the

rule. Welfare effects are estimated using economic models which link changes in physical

damages (e.g., light extinction or agricultural yields) with economic values.

Since the publication of the RIA for the proposed rule, EPA has received new technical

guidance and input regarding its methodology for conducting PM- and ozone-related benefits

analysis from the Health Effects Subgroup (HES) of the Science Advisory Board (SAB) Council

reviewing the 812 blueprint (SAB-HES, 2003) and the Office of Management and Budget

(OMB) through ongoing discussions regarding methods used in conducting regulatory impact

analyses (RIAs) (e.g., see OMB Circular A-4). The SAB HES recommendations include the

following (SAB-HES, 2003):

C use of the updated ACS Pope et al. (2002) study rather than the ACS Krewski et al.

study to estimate premature mortality for the primary analysis;

C dropping the alternative estimate used in earlier RIAs and instead including a primary

estimate that incorporates consideration of uncertainly in key effects categories such

as premature mortality directly into the estimates (e.g., use of the standard errors from

the Pope et al. (2002) study in deriving confidence bounds for the adult mortality

estimates);

C addition of infant mortality (children under the age of one) into the primary estimate,

based on supporting evidence from the World Health Organization Global Burden of

Disease study (World Health Organization, 2002) and other published studies that

strengthen the evidence for a relationship between PM exposure and respiratory

inflamation and infection in children leading to death; 

C inclusion of asthma exacerbations for children in the primary estimate;

C expansion of the age groups evaluated for a range of morbidity effects beyond the

narrow band of the studies to the broader (total) age group (e.g., expanding a study

population for 7 to 11 year olds to cover the entire child age range of 6 to 18 years). 
Final Regulatory Impact Analysis

F

Note that the SAB-HES comments were made in the context of a review of the methods for the Section 812

analysis of the costs and benefits of the Clean Air Act. This context is pertinent to our interpretation of the SABHES comments on the selection of effect estimates for hospital admissions associated with PM (SAB-HES, 2003). 

The Section 812 analysis is focused on a broad set of air quality changes, including both the coarse and fine fractions

of PM10. As such, impact functions that focus on the full impact of PM10 are appropriate. However, for the Nonroad

Diesel Engines rule, which is expected to affect primarily the fine fraction (PM2.5) of PM10, impact functions that

focus primarily on PM2.5 are more appropriate.

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C inclusion of new endpoints (school absences [ozone], nonfatal heart attacks in adults

[PM], hospital admissions for children under two [ozone]), and suggestion of a new

meta-analysis of hospital admissions (PM10) rather than using a few PM2.5 studies;F

and

C updating of populations and baseline incidences.

Recommendations from the Office of Management and Budget (OMB) regarding EPA’s

methods have focused on the approach used to characterize uncertainty in the benefits estimates

generated for RIAs, as well as the approach used to value premature mortality estimates. The

EPA is currently in the process of developing a comprehensive, integrated strategy for

characterizing the impact of uncertainty in key elements of the benefits modeling process (e.g.,

emissions modeling, air quality modeling, health effects incidence estimation, valuation) on the

results that are generated. A subset of this effort involved an expert elicitation designed to

characterize uncertainty in the estimation of PM-related mortality resulting from both short-term

and longer-term exposure. In its 2002 report, the NAS provides a number of recommendations

on how EPA might improve the characterization of uncertainty in its benefits analyses. One

recommendation was that “EPA should begin to move the assessment of uncertainties from its

ancillary analyses into its primary analyses by conducting probabalistic, multiple-source

uncertainty analyses. This shift will require specification of probability distributions for major

sources of uncertainty. These distributions should be based on available data and expert

judgement.” The NAS elaborated on this recommendation by suggesting a program of

methodological development involving review and critique of existing protocols for selection

and elicitation of experts by decision analysts, biostatisticians, and psychologists. They

recommended the use of formally elicited expert judgements, but noted that a number of issues

must be addressed, and that sensitivity analyses would be needed for distributions that are based

on expert judgment. They also recommended that EPA clearly distinguish between data-derived

components of an uncertainty assessment and those based on expert opinions. As a first step in

addressing the NAS recommendations regarding expert elicitation, EPA, in collaboration with

OMB, conducted a pilot expert elicitation to characterize uncertainties in the relationship

between ambient PM2.5 concentrations and premature mortality. While it is premature to include

the results of the pilot in the primary analysis for this rulemaking, EPA and OMB believe this

pilot moves toward the goal of incorporating additional uncertainty analyses in its future primary

benefits analyses. The pilot expert elicitation is described in Appendix 9B and the full report is

placed in the public docket.

We have also modified the analysis to reflect new information in the academic literature on

the appropriate characterization of the value of reducing the risk of premature mortality (value of
Cost-Benefit Analysis

GAn alternative rationale for the low end of the range could be found in some recent stated preference studies

suggesting VSL of between $1 and $5 million (Alberini et al., forthcoming).

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statistical life (VSL)). In previous analyses, we used a distribution based on 26 VSL estimates

from the economics literature. For this analysis, we are characterizing the VSL distribution in a

more general fashion, based on two recent meta-analyses of the wage-risk-based VSL literature

(Mrozek and Taylor, 2000 and Viscusi and Aldy, 2003). The new distribution is assumed to be

normal, with a mean of $5.5 million and a 95 percent confidence interval between $1 and $10

million. The $1 million lower confidence limit represents the lower end of the interquartile range

from the Mrozek and Taylor (2000) meta-analysis.G The $10 million upper confidence limit

represents the upper end of the interquartile range from the Viscusi and Aldy (2003)

meta-analysis. 

The EPA has addressed many of the comments received from the SAB-HES and OMB in

developing the analytical approach for the final rule. We use an approach consistent with the

methods used in the benefits analysis of the recently proposed Interstate Air Quality rule

(IAQR). We have also reflected advances in data and methods in air quality modeling,

epidemiology, and economics in developing this analysis. Updates to the assumptions and

methods used in estimating PM2.5-related and ozone-related benefits since completion of the

Proposed Nonroad Diesel Rule include the following:

Health Endpoints

C We incorporated updated impact functions to reflect updated time-series studies of

hospital admissions to correct for errors in application of the generalized additive

model (GAM) functions in S-plus. More information on this issue is available at

http://www.healtheffects.org.

C The primary analysis used an all-cause mortality effect estimate based on the Pope et

al. (2002) reanalysis of the ACS study data. 

C Infant mortality was included in the primary analysis.

C Asthma exacerbations were incorporated into the primary analysis. Although the

analysis of the proposed rule included asthma exacerbations as a separate endpoint

outside of the base case analysis, for the final rule, we will include asthma

exacerbations in children 6 to 18 years of age as part of the primary analysis. 

C

Valuation

C In generating the monetized benefits for premature mortality in the primary analysis,

the VSL will be entered as a mean (best estimate) of $5.5 million. Unlike the

analysis of the proposed rule, the final rule analysis will not include a value of
Final Regulatory Impact Analysis

9-16

statistical life year (VSLY) estimate. This reflects the advice of the SAB-Council and

concerns raised by commentors on the proposed rule.

The proposed Nonroad Diesel rule included an alternative estimate in addition to the primary

estimate that was intended to evaluate the impact of several key assumptions on the estimated

reductions in premature mortality and chronic bronchitis. However, reflecting comments from

the SAB-HES, rather than including an alternative estimate in the analysis of the final rule, the

EPA will investigate the impact of key assumptions on mortality and morbidity estimates

through a series of sensitivity analyses. This advice is consistent with the NAS

recommendations as well.

9.3.1 Overview of Analytical Approach

This section summarizes the three steps involved in our analysis of the modeled preliminary

control options: 1) Calculation of the impact that a set of preliminary fuel and engine standards

would have on the nationwide inventories for NOx, NMHC, SO2, and direct PM emissions in

2020 and 2030; 2) Air quality modeling for 2020 and 2030 to determine changes in ambient

concentrations of ozone and PM, reflecting baseline and post-control emissions inventories; and

3) A benefits analysis to determine the changes in human health and welfare, both in terms of

physical effects and monetary value, that result from the projected changes in ambient

concentrations of various pollutants for the modeled standards.

We follow a “damage-function” approach in calculating total benefits of the modeled

changes in environmental quality. This approach estimates changes in individual health and

welfare endpoints (specific effects that can be associated with changes in air quality) and assigns

values to those changes assuming independence of the individual values. Total benefits are

calculated simply as the sum of the values for all non-overlapping health and welfare endpoints. 

This imposes no overall preference structure, and does not account for potential income or

substitution effects, i.e. adding a new endpoint will not reduce the value of changes in other

endpoints. The “damage-function” approach is the standard approach for most cost-benefit

analyses of regulations affecting environmental quality, and it has been used in several recent

published analyses (Banzhaf et al., 2002; Levy et al., 2001; Kunzli et al., 2000; Levy et al., 1999;

Ostro and Chestnut, 1998). Time and resource constraints prevented us from performing

extensive new research to measure either the health outcomes or their values for this analysis. 

Thus, similar to these studies, our estimates are based on the best available methods of benefits

transfer. Benefits transfer is the science and art of adapting primary research from similar

contexts to obtain the most accurate measure of benefits available for the environmental quality

change under analysis.

There are significant categories of benefits that cannot be monetized (or in many cases even

quantified), and thus they are not included in our accounting of health and welfare benefits. 

These unquantified effects include low birth weight, changes in pulmonary function, chronic

respiratory diseases other than chronic bronchitis, morphological changes, altered host defense

mechanisms, non-fatal cancers, and non-asthma respiratory emergency room visits. A complete

discussion of PM -related health effects can be found in the PM Criteria Documents (U.S. EPA
Cost-Benefit Analysis

HIn the benefits analysis of the recent Heavy Duty Engine/Diesel Fuel rule, we used the Urban Airshed Model

Variable-Grid (UAM-V) to estimate ozone concentrations in the Eastern U.S. CAMx has a number of improvements

relative to UAM and has improved model performance in the Western U.S. Details on the performance of CAMx

can be found in Chapter 2 as well as the Air Quality Modeling TSD (U.S. EPA, 2003b).

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1996a, U.S. EPA, 2004) and the EPA Diesel HAD (U.S. EPA 2002). A discussion of the state of

the science as of the last NAAQS review of ozone-related effects can be found in the Ozone

Criteria Document (U.S. EPA 1996b). Since many health effects overlap, such as minor

restricted activity days and asthma symptoms, we made assumptions intended to reduce the

chances of “double-counting” health benefits, which may result in an underestimate of the total

health benefits of the pollution controls.

9.3.2 Air Quality Modeling

As described in Chapter 2 and the technical support documents (TSDs), we used a nationalscale version of the REgional Modeling System for Aerosols and Deposition (REMSAD version

7) to estimate PM air quality in the contiguous United States. We used the Comprehensive Air

Quality Model with Extensions (CAMx) to estimate ambient ozone concentrations,H using two

domains representing the Eastern and Western U.S. These models are discussed in the air

quality TSD for this rule.

9.3.2.1 PM Air Quality Modeling with REMSAD

REMSAD is appropriate for evaluating the impacts of emissions reductions from nonroad

sources, because it accounts for spatial and temporal variations as well as differences in the

reactivity of emissions. The annual county level emission inventory data described in Chapter 3

was speciated, temporally allocated and gridded to the REMSAD modeling domain to simulate

PM concentrations for the 1996 base year and the 2020 and 2030 base and control scenarios. 

Peer-reviewed for the EPA, REMSAD is a three-dimensional grid-based Eulerian air quality

model designed to estimate annual particulate concentrations and deposition over large spatial

scales (Seigneur et al., 1999). Each of the future scenarios was simulated using 1996

meteorological data to provide daily averages and annual mean PM concentrations required for

input to the concentration-response functions of the benefits analysis. Details regarding the

application of REMSAD Version 7 for this analysis are provided in the Air Quality Modeling

TSD (U.S. EPA, 2003b). This version reflects updates in the following areas to improve

performance and address comments from the 1999 peer-review:

1. Gas phase chemistry updates to “micro-CB4" mechanism including new treatment for the

NO3 and N2O5 species and the addition of several reactions to better account for the wide

ranges in temperature, pressure, and concentrations that are encountered for regional and

national applications.

2. PM chemistry updates to calculate particulate nitrate concentrations through use of the

MARS-A equilibrium algorithm and internal calculation of secondary organic aerosols

from both biogenic (terpene) and anthropogenic (estimated aromatic) VOC emissions.
Final Regulatory Impact Analysis

I

 Comments from industry have stated that EPA’s methodology form computing benefits over time is based on

unsupportable assumptions related to air quality modeling. Specifically, they state that EPA assumes that there will

be no interactions between precursors and directly emitted PM in the formation of secondary PM and that EPA

excludes consideration of non-linearities in its air quality modeling. The commentor is partially incorrect in the

statement that “EPA assumes no interactions between NOx, SO2, and direct PM in the formation of PM2.5.” In order

to estimate benefits in years other than 2020 and 2030, it was necessary to interpolate values from 2020 and 2030. 

We used sophisticated air quality modeling (using the REMSAD model) to predict changes in ambient PM2.5 in 2020

and 2030. This air quality modeling for 2020 and 2030 does incorporate the nonlinear interactions between NOx,

SO2, and direct PM. However, in order to develop the intertemporal scaling factors, we had to make some

simplifying assumptions. We assumed that the interactions between SO2 and NOx were linear over time, rather than

assuming that there was no interaction. In other words, we assumed that the rate of change in the sulfate to SO2,

nitrate to NOx, and primary PM to direct PM ratios was a linear function of time. The rate of change is driven by

differences in the baseline emissions between 2020 and 2030 and by differences in the ratio of NOx to SO2

reductions from the nonroad sector. We verified the interpolation approach by predicting 2020 benefits using

scaling factors for sulfate, nitrate, and direct PM based on the modeled 2030 benefits. Scaled benefits were within 4

percent of the actual modeled benefits for 2020.

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3. Aqueous phase chemistry updates to incorporate the oxidation of SO2 by O3 and O2 and to

include the cloud and rain liquid water content from MM5 meteorological data directly in

sulfate production and deposition calculations.

As discussed earlier in Chapter 2, the model tends to underestimate observed PM2.5

concentrations nationwide, especially over the western U.S.I

9.3.2.2 Ozone Air Quality Modeling with CAMx

We use the emissions inputs described in Chapter 3 with a regional-scale version of CAMx

to estimate ozone air quality in the Eastern and Western U.S. CAMx is an Eulerian threedimensional photochemical grid air quality model designed to calculate the concentrations of

both inert and chemically reactive pollutants by simulating the physical and chemical processes

in the atmosphere that affect ozone formation. Because it accounts for spatial and temporal

variations as well as differences in the reactivity of emissions, the CAMx is useful for evaluating

the impacts of the nonroad diesel engine rule on U.S. ozone concentrations. As discussed earlier

in Chapter 2, although the model tends to underestimate observed ozone, especially over the

western U.S., it exhibits less bias and error than any past regional ozone modeling application

conducted by EPA (i.e., Ozone Transport Assessment Group (OTAG), On-highway Tier-2

Passenger Vehicles, and Heavy Duty Engine/Diesel Fuel 2007 program).

Our analysis applies the modeling system separately to the Eastern and Western U.S. for five

emissions scenarios: a 1996 baseline projection, a 2020 baseline projection and a 2020 projection

with nonroad controls, a 2030 baseline projection and a 2030 projection with nonroad controls. 

As discussed in detail in the technical support document, a 1996 base year assessment is

necessary because the relative model predictions are used with ambient air quality observations

from 1996 to determine the expected changes in 2020 and 2030 ozone concentrations due to the

modeled emission changes (Abt Associates, 2003). These results are used solely in the benefits

analysis.
Cost-Benefit Analysis

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As discussed in more detail in Chapter 2.3, our ozone air quality modeling showed that the

NOx emissions reductions from the preliminary modeled standards are projected to result in

increases in ozone concentrations for certain hours during the year, especially in urban, NOxlimited areas. Most of these increases are expected to occur during hours where ozone levels are

low (and often below the one-hour ozone standard). However, most of the country experiences

decreases in ozone concentrations for most hours in the year.

9.3.3 Health Impact Functions

Health impact functions are derived from the epidemiology literature. A standard health

impact function has four components: an effect estimate from a particular epidemiological study,

a baseline incidence rate for the health effect (obtained from either the epidemiology study or a

source of public health statistics like the Centers for Disease Control), the affected population,

and the estimated change in the relevant PM or ozone summary measure.

A typical health impact function might look like:

∆ ∆

yy e x =⋅ − ⋅

0 ( ), 1 β

where y0 is the baseline incidence, equal to the baseline incidence rate times the potentially

affected population, $ is the effect estimate, and )x is the estimated change in the summary

PM2.5 or ozone measure. There are other functional forms, but the basic elements remain the

same. 

Integral to the estimation of the impact functions are reasonable estimates of future

population projections. The underlying data used to create county-level 2010 population

projections is based on county level allocations of national population projections from the U.S.

Census Bureau (Hollman, Mulder and Kallan, 2000). County-level allocations of populations by

age, race, and sex are based on economic forecasting models developed by Woods and Poole,

Inc (WP), which account for patterns of economic growth and migration.

The WP projections of county level population are based on historical population data from

1969-1999, and do not include the 2000 Census results. Given the availability of detailed 2000

Census data, we constructed adjusted county level population projections for each future year

using a two stage process. First, we constructed ratios of the projected WP populations in a

future year to the projected WP population in 2000 for each future year by age, sex, and race. 

Second, we multiplied the block level 2000 Census population data by the appropriate age, sex,

and race specific WP ratio for the county containing the census block, for each future year. This

results in a set of future population projections that is consistent with the most recent detailed

census data.

Specific populations matching the study populations in each epidemiological study are

constructed by accessing the appropriate age-specific projections from the overall population

database. For some endpoints, such as asthma attacks, we further limit the population by
Final Regulatory Impact Analysis

9-20

applying prevalence rates to the overall population. We do not have sufficient information to

quantitatively characterize uncertainty in the population estimates.

Fundamental to the estimation of health benefits was our utilization of the PM epidemiology

literature. We rely upon effect estimates derived from published, peer reviewed epidemiological

studies that relate health effects to ambient concentrations of PM. The specific studies from

which effect estimates are drawn are listed in Table 9-5. While a broad range of serious health

effects have been associated with exposure to elevated PM levels, we include only a subset of

health effects in this benefit analysis due to limitations in available effect estimates and concerns

about double-counting of overlapping effects (U.S. EPA, 1996). For the most part, we use the

same set of effect estimates as we used in the analysis of the proposed Nonroad Diesel Engines

rule. However, based on recent advice from the SAB, we use an updated effect estimate for

premature mortality and include two additional health effects, infant mortality and asthma

exacerbations. Because of their significance in the analysis, we provide a more detailed

discussion of premature mortality and chronic illness endpoints below. 

To generate health outcomes, projected changes in ambient PM concentrations were entered

into BenMAP, a customized geographic information system based program. BenMAP

aggregates populations to air quality model grids and calculates changes in air pollution metrics

(e.g., daily averages) for input into health impact functions. BenMAP uses grid cell level

population data and changes in pollutant concentrations to estimate changes in health outcomes

for each grid cell. Details on the BenMAP program can be found in the BenMAP User’s Manual

(Abt Associates, 2003).

The baseline incidences for health outcomes used in our analyses are selected and adapted to

match the specific populations studied. For example, we use age- and county-specific baseline

total mortality rates in the estimation of PM-related premature mortality. County-level incidence

rates are not available for other endpoints. We used national incidence rates whenever possible,

because these data are most applicable to a national assessment of benefits. However, for some

studies, the only available incidence information comes from the studies themselves; in these

cases, incidence in the study population is assumed to represent typical incidence at the national

level. Sources of baseline incidence rates are reported in Table 9-6.

In this assessment we made analytical judgements affecting both the selection of effect

estimates and the application of those estimates in formulating health impact functions. In

general, we selected effect estimates that 1) most closely match the pollutants of interest, i.e.

PM2.5) cover the broadest potentially exposed population (i.e. all ages functions would be

preferred to adults 27 to 35), 3) have appropriate model specification (e.g. control for

confounding pollutants), 4) have been peer-reviewed, and 5) are biologically plausible. Other

factors may also affect our selection of effect estimates for specific endpoints, such as premature

mortality. Some of the more important of these relating to premature mortality and chronic

illness are discussed below and are discussed in detail in Appendix 9A. Alternative assumptions

about these judgements may lead to substantially different results and they are explored using

appropriate sensitivity analyses provided in Appendix 9B.
Cost-Benefit Analysis

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While there is a consistent body of evidence supporting a relationship between a number of

adverse health effects and ambient PM levels, there is often only a single study of a specific

endpoint covering a specific age group. There may be multiple estimates examining subgroups

(i.e. asthmatic children). However, for the purposes of assessing national population level

benefits, we chose the most broadly applicable effect estimate to more completely capture health

benefits in the general population. Estimates for subpopulations are provided in Appendix 9A.

There is no consensus on whether or not there is a threshold for the health effects of PM, and

if so, what the possible threshold might be. Consistent with recent literature (Daniels et al.,

2000; Pope et al., 2002; Rossi et al., 1999; Schwartz, 2000), we chose for the purposes of this

analysis to assume that PM-related health effects occur down to natural background (i.e., there is

no health effects threshold). We assume that all of the health impact functions are continuous

and differentiable down to natural background levels. Our assumptions regarding thresholds are

considered reasonable by the National Research Council in its recent review of methods for

estimating the public health benefits of air pollution regulations. In their review, the National

Research Council concluded that there is no evidence for any departure from linearity in the

observed range of exposure to PM10 or PM2.5, nor any indication of a threshold. (NRC, 2002).

They cite the weight of evidence available from both short and long term exposure models and

the similar effects found in cities with low and high ambient concentrations of PM. We explore

this important assumption in a sensitivity analysis described in Appendix 9C.

Premature Mortality

As receommended by the NAS (2002) and the SAB-HES, and demonstrated in the Kunzli et

al. (2000) health impact assessment, we focus on the prospective cohort long-term exposure

studies in deriving the health impact function for our base estimate of premature mortality. 

Cohort analyses are better able to capture the full public health impact of exposure to air

pollution over time (Kunzli, 2001; NRC, 2002). We selected an effect estimate from the

extended analysis of the American Cancer Society (ACS) cohort (Pope et al., 2002) because it

represents the most comprehensive cohort analysis with the longest period of followup. In

addition, this study has been recommended for impact assessments by the SAB-HES (SAB-HES,

2003). This effect estimate quantifies the relationship between annual mean PM2.5 levels and allcause mortality in adults 30 and older. We selected the effect estimate estimated using the

measure of PM representing average exposure over the follow-up period, calculated as the

average of 1979-1984 and 1999-2000 PM2.5 levels. 

In previous analyses, infant mortality has not been evaluated as part of the primary analysis

due to uncertainty in the strength of the association between exposure to PM and postneonatal

mortality. Instead, benefits estimates related to reduced infant mortality have been included as

part of the sensitivity analyses. However recently published studies have strengthened the case

for an association between PM exposure and respiratory inflamation and infection leading to

premature mortality in infants under five years of age. Specifically, the SAB's HES noted the

release of the World Health Organization Global Burden of Disease Study focusing on ambient

air which cites several recently-published time-series studies relating daily PM exposure to

mortality in children. The HES also cites the study by Belanger et al., (2003) as corroborating
Final Regulatory Impact Analysis

9-22

findings linking PM exposure to increased respiratory inflamation and infections in children. 

With regard to the cohort study conducted by Woodruff et al. (1997), the HES notes several

strengths of the study including the use of a larger cohort drawn from a large number of

metropolitan areas and efforts to control for a variety of individual risk factors in children (e.g.,

maternal educational level, maternal ethnicity, parental marital status and maternal smoking

status). We follow the HES recommendation to include infant mortality in the primary benefits

estimate using the effect estimate from the Woodruff et al. (1997) study.

Chronic Illness

Although there are several studies examining the relationship between PM of different size

fractions and incidence of chronic bronchitis, we use a study by Abbey et al. (1995) to obtain our

estimate of avoided incidences of chronic bronchitis in adults aged 25 and older, because Abbey

et al. (1995) is the only available estimate of the relationship between PM2.5 and chronic

bronchitis. Based on the Abbey et al. study, we estimate the number of new chronic bronchitis

cases that will “reverse” over time and subtract these reversals from the estimate of avoided

chronic bronchitis incidences. Reversals refer to those cases of chronic bronchitis that were

reported at the start of the Abbey et al. survey, but were subsequently not reported at the end of

the survey. Since we assume that chronic bronchitis is a permanent condition, we subtract these

reversals. Given the relatively high value assigned to chronic bronchitis, this ensures that we do

not overstate the economic value of this health effect.

Non-fatal heart attacks have been linked with short term exposures to PM2.5 in the U.S.

(Peters et al., 2001) and other countries (Poloniecki et al., 1997). We use a recent study by

Peters et al. (2001) as the basis for the C-R function estimating the relationship between PM2.5

and non-fatal heart attacks in adults. Peters et al. is the only available U.S. study to provide a

specific estimate for heart attacks. Other studies, such as Samet et al. (2000) and Moolgavkar et

al. (2000) show a consistent relationship between all cardiovascular hospital admissions,

including for non-fatal heart attacks, and PM. Given the lasting impact of a heart attack on

longer-term health costs and earnings, we choose to provide a separate estimate for non-fatal

heart attacks based on the single available U.S. C-R function. The finding of a specific impact

on heart attacks is consistent with hospital admission and other studies showing relationships

between fine particles and cardiovascular effects both within and outside the U.S. These studies

provide a weight of evidence for this type of effect. Several epidemiologic studies (Liao et al.,

1999; Gold et al., 2000; Magari et al., 2001) have shown that heart rate variability (an indicator

of how much the heart is able to speed up or slow down in response to momentary stresses) is

negatively related to PM levels. Heart rate variability is a risk factor for heart attacks and other

coronary heart diseases (Carthenon et al., 2002; Dekker et al., 2000; Liao et al., 1997, Tsuji et al.

1996). As such, significant impacts of PM on heart rate variability are consistent with an

increased risk of heart attacks.

9.3.4 Economic Values for Health Outcomes

Reductions in ambient concentrations of air pollution generally lower the risk of future

adverse health affects by a fairly small amount for a large population. The appropriate 
Cost-Benefit Analysis

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economic measure is therefore willingness-to-pay (WTP) for changes in risk prior to the

regulation (Freeman, 1993). For some health effects, such as hospital admissions, WTP

estimates are generally not available. In these cases, we use the cost of treating or mitigating the

effect as a primary estimate. These costs of illness (COI) estimates generally understate the true

value of reductions in risk of a health effect, reflecting the direct expenditures related to

treatment but not the value of avoided pain and suffering from the health effect (Harrington and

Portney, 1987; Berger, 1987). Unit values for health endpoints are provided in Table 9-7. All

values are in constant year 2000 dollars.

The length of the delay between reduction in chronic PM exposures and reduction in

mortality rates is unknown and yet an important parameter in the benefits analysis. The size of

such a time lag is important for the valuation of premature mortality incidences as economic

theory suggests benefits occurring in the future should be discounted relative to benefits

occurring today. Although there is no specific scientific evidence of the size of a PM effects lag,

current scientific literature on adverse health effects associated with smoking and the difference

in the effect size between chronic exposure studies and daily premature mortality studies suggest

that all incidences of premature mortality reduction associated with a given incremental change

in PM exposure would not occur in the same year as the exposure reduction. This literature

implies that lags of a few years or longer are plausible. For our current analysis, based on

previous advice from the SAB (EPA-SAB-COUNCIL-ADV-00-001, 1999), we have assumed a

five-year distributed lag structure, with 25 percent of premature deaths occurring in the first year,

another 25 percent in the second year, and 16.7 percent in each of the remaining three years. To

account for the preferences of individuals for current risk reductions relative to future risk

reductions, we discount the value of avoided premature mortalities occurring beyond the

analytical year (2020 or 2030) using three and seven percent discount rates. 

A more recent SAB-HES report confirmed the NAS (2002) conclusion that there is little

justification for the 5-year time course used by EPA in its past assessments, and suggested that

future assessments more fully and explicitly account for the uncertainty. The SAB-HES

suggests that appropriate lag structures may be developed based on the distribution of cause

specific deaths within the overall all-cause estimate. The SAB-HES specifically noted

understanding mechanisms of damage and developing models for different cause of death

categories may be the key to characterizing more appropriate cessation lag functions. They note

that our current understanding of mechanisms suggests there are likely short-term (e.g., less than

six months for some cardiovascular effects), medium term (e.g., 2-5 years for COPD), and

longer term (e.g., 15 to 25 years for lung cancer). They noted that there is a current lack of direct

data to specify a lag function and recommended that information on the lag function be

considered in future expert elicitations and/or sensitivity analyses. While we are working to

develop the underlying data to support a more appropriate segmented lag structure, for this

analysis we maintain the 5-year lag structure used in the benefits analysis for the proposed rule. 

We have added an additional sensitivity analysis to Appendix 9C examining the impact of

assuming a segmented lag of the type suggested by the SAB-HES. The overall impact of

moving from the 5-year distributed lag to this version of a segmented lag is relatively modest,

reducing benefits by approximately 8 percent when a three percent discount rate is used and 22

percent when a seven percent discount rate is used.
Final Regulatory Impact Analysis

J

 For details of the visibility estimates discussed in this section, please refer to the benefits technical support

document for this RIA (Abt Associates 2003).

9-24

Our analysis accounts for expected growth in real income over time. Economic theory

argues that WTP for most goods (such as environmental protection) will increase if real incomes

increase. The economics literature suggests that the severity of a health effect is a primary

determinant of the strength of the relationship between changes in real income and WTP

(Alberini, 1997; Miller, 2000; Evans and Viscusi, 1993). As such, we use different factors to

adjust the WTP for minor health effects, severe and chronic health effects, and premature

mortality. We also adjust WTP for improvements in recreational visibility. Adjustment factors

used to account for projected growth in real income from 1990 to 2030 are 1.08 for minor health

effects, 1.27 for severe and chronic health effects, 1.23 for premature mortality, and 1.61 for

recreational visibility. Adjustment factors for 2020 are 1.07 for minor health effects, 1.23 for

severe and chronic health effects, 1.20 for premature mortality, and 1.52 for recreational

visibility. Note that due to a lack of reliable projections of income growth past 2024, we assume

constant WTP from 2024 through 2030. This will result in an underestimate of benefits

occurring between 2024 and 2030. Details of the calculation of the income adjustment factors

are provided in Appendix 9A.

9.3.5 Welfare Effects

Our analysis of the preliminary control option examined two categories of welfare effects:

visibility in a subset of national parks and changes in consumer and producer surplus associated

with changes in agricultural yields. There are a number of other environmental effects which

may affect human welfare, but due to a lack of appropriate physical effects or valuation methods,

we are unable to quantify or monetize these effects for our analysis of the nonroad standards.

9.3.5.1 Visibility Benefits

Changes in the level of ambient particulate matter caused by the reduction in emissions from

the preliminary control options will change the level of visibility in much of the U.S. as

discussed in Chapter 2. Visibility directly affects people’s enjoyment of a variety of daily

activities. Individuals value visibility both in the places they live, work, and recreate, in the

places they travel to for recreational purposes, and at sites of unique public value, such as the

Grand Canyon. 

For the purposes of this analysis, visibility improvements were valued only for a limited set

of mandatory federal Class I areas. Benefits of improved visibility in the places people live,

work, and recreate outside of these limited set of Class I areas were not included in our estimate

of total benefits, although they are examined in a sensitivity analysis presented in Appendix 9B.

All households in the U.S. are assumed to derive some benefit from improvements in Class I

areas, given their national importance and high visitation rates from populations throughout the

U.S. However, values are assumed to be higher if the Class I area is located close to their home.J
Cost-Benefit Analysis

9-25

We use the results of a 1988 contingent valuation survey on recreational visibility value

(Chestnut and Rowe, 1990a; 1990b) to derive values for visibility improvements. The Chestnut

and Rowe study measured the demand for visibility in Class I areas managed by the National

Park Service (NPS) in three broad regions of the country: California, the Southwest, and the

Southeast. The Chestnut and Rowe study did not measure values for visibility improvement in

Class I areas outside the three regions. Their study covered 86 of the 156 Class I areas in the

U.S. We can infer the value of visibility changes in the other Class I areas by transferring values

of visibility changes at Class I areas in the study regions. However, these values are less certain

and are thus presented only as an sensitivity estimate in Appendix 9B.

A general willingness to pay equation for improved visibility (measured in deciviews) was

developed as a function of the baseline level of visibility, the magnitude of the visibility

improvement, and household income. The behavioral parameters of this equation were taken

from analysis of the Chestnut and Rowe data. These parameters were used to calibrate WTP for

the visibility changes resulting from the Nonroad Diesel Engine rule. The method for

developing calibrated WTP functions is based on the approach developed by Smith, et al. (2002),

and is described in detail in the benefits technical support document for the proposed rule (Abt

Associates, 2003). Major sources of uncertainty for the visibility benefit estimate include the

quality of the underlying study and the benefits transfer process used. Judgments used to choose

the functional form and key parameters of the estimating equation for willingness to pay for the

affected population could have significant effects on the size of the estimates. Assumptions

about how individuals respond to changes in visibility that are either very small, or outside the

range covered in the Chestnut and Rowe study, could also affect the results. EPA is considering

next steps in improving its visibility benefits estimates.

9.3.5.2 Agricultural Benefits

Laboratory and field experiments have shown reductions in yields for agronomic crops

exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g., cotton and wheat). 

The economic value associated with varying levels of yield loss for ozone-sensitive commodity

crops is analyzed using the AGSIM© agricultural benefits model (Taylor, et al., 1993). AGSIM©

is an econometric-simulation model that is based on a large set of statistically estimated demand

and supply equations for agricultural commodities produced in the United States. 

The model employs biological exposure-response information derived from controlled

experiments conducted by the NCLAN (NCLAN, 1996). For the purpose of our analysis, we

analyze changes for the six most economically significant crops for which C-R functions are

available: corn, cotton, peanuts, sorghum, soybean, and winter wheat. For some crops there are

multiple C-R functions, some more sensitive to ozone and some less. Our base estimate assumes

that crops are evenly mixed between relatively sensitive and relatively insensitive varieties.

The measure of benefits calculated by the AGSIM© model is the net change in consumer and

producer surplus from baseline ozone concentrations to the ozone concentrations resulting from

emission reductions. Using the baseline and post-control equilibria, the model calculates the

change in net consumer and producer surplus on a crop-by-crop basis. Dollar values are
Final Regulatory Impact Analysis

9-26

aggregated across crops for each standard. The total dollar value represents a measure of the

change in social welfare associated with changes in ambient ozone.

9.3.5.3 Other Welfare Benefits

Ozone also has been shown conclusively to cause discernible injury to forest trees (US EPA,

1996; Fox and Mickler, 1996). In our previous analysis of the HD Engine/Diesel Fuel rule, we

were able to quantify the effects of changes in ozone concentrations on tree growth for a limited

set of species. Due to data limitations, we were not able to quantify such impacts for this

analysis. 

An additional welfare benefit expected to accrue as a result of reductions in ambient ozone

concentrations in the U.S. is the economic value the public receives from reduced aesthetic

injury to forests. There is sufficient scientific information available to reliably establish that

ambient ozone levels cause visible injury to foliage and impair the growth of some sensitive

plant species (US EPA, 1996c, p. 5-521). However, present analytic tools and resources

preclude EPA from quantifying the benefits of improved forest aesthetics.

Urban ornamentals represent an additional vegetation category likely to experience some

degree of negative effects associated with exposure to ambient ozone levels and likely to impact

large economic sectors. In the absence of adequate exposure-response functions and economic

damage functions for the potential range of effects relevant to these types of vegetation, no direct

quantitative economic benefits analysis has been conducted. 

The nonroad diesel standards, by reducing NOX emissions, will also reduce nitrogen

deposition on agricultural land and forests. There is some evidence that nitrogen deposition may

have positive effects on agricultural output through passive fertilization. Holding all other

factors constant, farmers’ use of purchased fertilizers or manure may increase as deposited

nitrogen is reduced. Estimates of the potential value of this possible increase in the use of

purchased fertilizers are not available, but it is likely that the overall value is very small relative

to other health and welfare effects. 

 The nonroad diesel standards are also expected to produce economic benefits in the form of

reduced materials damage. There are two important categories of these benefits. Household

soiling refers to the accumulation of dirt, dust, and ash on exposed surfaces. Criteria pollutants

also have corrosive effects on commercial/industrial buildings and structures of cultural and

historical significance. The effects on historic buildings and outdoor works of art are of

particular concern because of the uniqueness and irreplaceability of many of these objects.

Previous EPA benefit analyses have been able to provide quantitative estimates of household

soiling damage. Consistent with SAB advice, we determined that the existing data (based on

consumer expenditures from the early 1970's) are too out of date to provide a reliable enough

estimate of current household soiling damages (EPA-SAB-Council-ADV-003, 1998) to include

in our base estimate. We calculate household soiling damages in a sensitivity estimate provided

in Appendix 9C.
Cost-Benefit Analysis

9-27

EPA is unable to estimate any benefits to commercial and industrial entities from reduced

materials damage. Nor is EPA able to estimate the benefits of reductions in PM-related damage

to historic buildings and outdoor works of art. Existing studies of damage to this latter category

in Sweden (Grosclaude and Soguel, 1994) indicate that these benefits could be an order of

magnitude larger than household soiling benefits.

Reductions in emissions of diesel hydrocarbons that result in unpleasant odors may also lead

to improvements in public welfare. The magnitude of this benefit is very uncertain, however,

Lareau and Rae (1989) found a significant and positive WTP to reduce the number of exposures

to diesel odors. They found that households were on average willing to pay around $20 to $27

(2000$) per year for a reduction of one exposure to intense diesel odors per week (translating

this to a national level, for the approximately 125 million households in 2020, the total WTP

would be between $2.5 and $3.4 billion annually). Their results are not in a form that can be

transferred to the context of this analysis, but the general magnitude of their results suggests this

could be a significant welfare benefit of the rule. 

The effects of air pollution on the health and stability of ecosystems are potentially very

important, but are at present poorly understood and difficult to measure. The reductions in NOX

caused by the rule could produce significant benefits. Excess nutrient loads, especially of

nitrogen, cause a variety of adverse consequences to the health of estuarine and coastal waters. 

These effects include toxic and/or noxious algal blooms such as brown and red tides, low

(hypoxic) or zero (anoxic) concentrations of dissolved oxygen in bottom waters, the loss of

submerged aquatic vegetation due to the light-filtering effect of thick algal mats, and

fundamental shifts in phytoplankton community structure (Bricker et al., 1999). 

Direct C-R functions relating changes in nitrogen loadings to changes in estuarine benefits

are not available. The preferred WTP based measure of benefits depends on the availability of

these C-R functions and on estimates of the value of environmental responses. Because neither

appropriate C-R functions nor sufficient information to estimate the marginal value of changes in

water quality exist at present, calculation of a WTP measure is not possible. Likewise, EPA is

unable to quantify climate-change related impacts. 

If better models of ecological effects can be defined, EPA believes that progress can be made

in estimating WTP measures for ecosystem functions. For example, if nitrogen or sulfate

loadings can be linked to measurable and definable changes in fish populations or definable

indexes of biodiversity, then CV studies can be designed to elicit individuals’ WTP for changes

in these effects. This is an important area for further research and analysis, and will require

close collaboration among air quality modelers, natural scientists, and economists.

9.3.6 Treatment of Uncertainty

In any complex analysis, there are likely to be many sources of uncertainty. This analysis is

no exception. Many inputs are used to derive the final estimate of economic benefits, including

emission inventories, air quality models (with their associated parameters and inputs),

epidemiological estimates of C-R functions, estimates of values, population estimates, income
Final Regulatory Impact Analysis

9-28

estimates, and estimates of the future state of the world (i.e., regulations, technology, and human

behavior). Some of the key uncertainties in the benefits analysis are presented in Table 9-8. For

some parameters or inputs it may be possible to provide a statistical representation of the

underlying uncertainty distribution. For other parameters or inputs, the necessary information is

not available.

In addition to uncertainty, the annual benefit estimates presented in this analysis are also

inherently variable due to the truly random processes that govern pollutant emissions and

ambient air quality in a given year. Factors such as hours of equipment use and weather display

constant variability regardless of our ability to accurately measure them. As such, the estimates

of annual benefits should be viewed as representative of the magnitude of benefits expected,

rather than the actual benefits that would occur every year.

We present a primary estimate of the total benefits, based on our interpretation of the best

available scientific literature and methods and supported by the SAB-HES and the NAS (NRC,

2002). The benefits estimates generated for the final Nonroad Diesel Engine rule are subject

to a number of assumptions and uncertainties, which are discussed throughout the document. 

For example, key assumptions underlying the primary estimate for the premature mortality

which accounts for 90 percent of the total benefits we were able to quantify include the

following:

(1) Inhalation of fine particles is causally associated with premature death at concentrations

near those experienced by most Americans on a daily basis. Although biological

mechanisms for this effect have not yet been definitively established, the weight of the

available epidemiological evidence supports an assumption of causality. 

(2) All fine particles, regardless of their chemical composition, are equally potent in causing

premature mortality. This is an important assumption, because PM produced via

transported precursors emitted from EGUs may differ significantly from direct PM

released from diesel engines and other industrial sources, but no clear scientific grounds

exist for supporting differential effects estimates by particle type. 

(3) The impact function for fine particles is approximately linear within the range of ambient

concentrations under consideration. Thus, the estimates include health benefits from

reducing fine particles in areas with varied concentrations of PM, including both regions

that are in attainment with fine particle standard and those that do not meet the standard. 

(4) The forecasts for future emissions and associated air quality modeling are valid. 

Although recognizing the difficulties, assumptions, and inherent uncertainties in the

overall enterprise, these analyses are based on peer-reviewed scientific literature and

up-to-date assessment tools, and we believe the results are highly useful in assessing this

rule.

In addition, we provide sensitivity analyses to illustrate the effects of uncertainty about key

analytical assumptions. Our analysis of the preliminary control options did not include formal

integrated probabilistic uncertainty analyses, although we have conducted several sensitivity

tests based on changes to several key model parameters. The recent NAS report on estimating

public health benefits of air pollution regulations recommended that EPA begin to move the
Cost-Benefit Analysis

9-29

assessment of uncertainties from its ancillary analyses into its primary analyses by conducting

probabilistic, multiple-source uncertainty analyses. We are working to implement these

recommendations. 

In Appendix 9B, we present two types of probabilistic approaches designed to illustrate how

some aspects of the uncertainty in the C-R function could be handled in a PM benefits analysis. 

The first approach generates a probabilistic estimate of statistical uncertainty based on standard

errors reported in the underlying studies used in the benefit modeling framework. In the second

illustrative approach, EPA, in collaboration with OMB, conducted a pilot expert elicitation to

characterize uncertainties in the relationship between ambient PM2.5 and premature mortality

(IEc 2004). This pilot was designed to improve our understanding of the design and application

of expert elicitation methods to economic benefits analysis. For instance, the pilot was designed

to provide feedback on the efficacy of the protocol developed and the analytic challenges, as

well as to provide insight regarding potential implications of the results on the degree of

uncertainty surrounding the C-R function for PM2.5 mortality. The scope of the pilot was limited

in that we focused the elicitation on the C-R function of PM mass rather than on individual

issues surrounding an estimate of the change in premature mortality due to PM exposure. In

Appendix 9B we present sensitivity analyses for illustrative purposes.

9.3.7 Model Results

We summarize our preliminary control option modeling as background for calculating the

scaling factors. The scaling factors are then used to estimate the PM-related benefits of the final

rule. Insights into ozone impacts can also be discerned. As discussed in Table 9-5 above and

Table 9A-4 below, full implementation of the modeled preliminary control options is projected

in 2020 to reduce 48-state emissions of land-based nonroad NOx by 663,600 tons (58 percent of

base case), SO2 by 305,000 tons (98.9 percent), VOC by 23,200 tons (24 percent) and directly

emitted PM2.5 by 91,300 tons (71 percent). In 2030, the modeled preliminary control option is

expected to reduce 48-state emissions of NOx by 1 million tons (82 percent), SO2 by 359,800

tons (99.7 percent), VOC by 34,000 tons (35 percent) and direct PM by 138,000 tons (90

percent). 

Based on these projected emission changes, REMSAD modeling results indicate the

pollution controls generate greater absolute air quality improvements in more populated, urban

areas. The rule will reduce average annual mean concentrations of PM2.5 across the U.S. by

roughly 2.5 percent (or 0.2 μg/m3) and 3.4 percent (or 0.28 μg/m3) in 2020 and 2030,

respectively. The population-weighted average mean concentration declined by 3.3 percent (or

0.42 μg/m3) in 2020 and 4.5 percent (or 0.59 μg/m3) in 2030, which is much larger in absolute

terms than the spatial average for both years. Table 9-9 presents information on the distribution

of modeled reductions in ambient PM concentrations across populations in the U.S. By 2030,

slightly over 50 percent of U.S. populations will live in areas with reductions of greater than 0.5

μg/m3

. This information indicates how widespread the improvements in PM air quality are

expected to be.
Final Regulatory Impact Analysis

9-30

Applying the health impact functions described in Table 9-5 to the estimated changes in

PM2.5 and ozone from the preliminary modeling yields estimates of the number of avoided

incidences for each health outcome. These estimates are presented in Appendix A Table 9A-30

for the 2020 and 2030 model analysis years. To provide estimates of the monetized benefits of

the reductions in PM-related health outcomes described in Table 9A-30, we multiply the point

estimates of avoided incidences by unit values. Values for welfare effects are based on

application of the economic models described above. The estimated total monetized health and

welfare benefits for the preliminary modeled scenario are also presented in Appendix A in Table

9A-31.

The largest monetized health benefit is associated with reductions in the risk of premature

mortality, which accounts for 90 percent of total monetized health benefits. The next largest

benefit is for chronic illness reductions (chronic bronchitis and nonfatal heart attacks), although

this value is more than an order of magnitude lower than for premature mortality. Minor

restricted activity days, work loss days, and hospital admissions account for the majority of the

remaining benefits. While the other categories account for less than $100 million each, they

represent a large number of avoided incidences affecting many individuals.

Ozone benefits arising from this rule are in aggregate positive for the nation. However, due

to ozone increases occurring during certain hours of the day in some urban areas, in 2020 the net

effect is an increase in ozone-related minor restricted activity days (MRAD), which are related to

changes in daily average ozone (which includes hours during which ozone levels are low, but are

increased relative to the baseline based on the preliminary modeling). However, by 2030, there

is a net decrease in ozone-related MRAD consistent with widespread reductions in ozone

concentrations from the increased NOx emissions reductions. Note that in both years, the overall

impact of changes in both PM and ozone is a large decrease in the number of MRAD. Overall,

ozone benefits are low relative to PM benefits for similar endpoint categories because of the

increases in ozone concentrations during some hours of some days in certain urban areas. For a

more complete discussion of this issue, see Chapter 2.

Monetized and quantified welfare benefits are far outweighed by health benefits. However,

we have not been able to quantify some important welfare categories, including the value of

changes in ecosystems from reduced deposition of nitrogen and sulfur and climate impacts. The

welfare benefits we are able to quantify are dominated by the value of improved visibility. 

Visibility benefits just in the limited set of parks included in the monetized total benefit estimate

are over $1.6 billion in 2030. Agricultural benefits, while small relative to visibility benefits, are

significant relative to ozone-related health benefits, representing the largest single benefit

category for ozone.
Cost-Benefit Analysis

9-31

Table 9-6

Endpoints and Studies Used to Calculate Total Monetized Health Benefits

Endpoint Pollutant Applied

Population

Source of Effect Estimate(s) Source of Baseline

Incidence

Premature Mortality

Adults – Long-term

exposure

PM2.5 >29 years Pope, et al. (2002) CDC Wonder (1996-1998)

Infants PM2.5 <1 Woodruff et al. (1997) CDC Wonder (1996-1998)

Chronic Illness

Chronic Bronchitis PM2.5 > 26 years Abbey, et al. (1995) 1999 HIS (American Lung

Association, 2002b, Table

4); Abbey et al. (1993,

Table 3)

Non-fatal Heart

Attacks

PM2.5 Adults Peters et al. (2001) 1999 NHDS public use

data files; adjusted by 0.93

for prob. of surviving after

28 days (Rosamond et al.,

1999)

Hospital Admissions 

Respiratory O3 > 64 years Pooled estimate:

Schwartz (1995) - ICD 460-519

(all resp)

Schwartz (1994a, 1994b) - ICD

480-486 (pneumonia)

Moolgavkar et al. (1997) - ICD

480-487 (pneumonia)

Schwartz (1994b) - ICD 491-

492, 494-496 (COPD)

Moolgavkar et al. (1997) - ICD

490-496 (COPD) 

1999 NHDS public use

data files

O3 < 2 years Burnett et al. (2001) 1999 NHDS public use

data files

PM2.5 >64 years Pooled estimate:

Moolgavkar (2003) - ICD 490-

496 (COPD)

Ito (2003) - ICD 490-496

(COPD)

1999 NHDS public use

data files

PM2.5 20-64 years Moolgavkar (2000) - ICD 490-

496 (COPD)

1999 NHDS public use

data files

PM2.5 > 64 years Ito (2003) - ICD 480-486

(pneumonia)

1999 NHDS public use

data files

PM2.5 < 65 years Sheppard, et al. (2003) - ICD

493 (asthma)

1999 NHDS public use

data files

Cardiovascular PM2.5 > 64 years Pooled estimate: 1999 NHDS public use
Table 9-6

Endpoints and Studies Used to Calculate Total Monetized Health Benefits

Endpoint Pollutant Applied

Population

Source of Effect Estimate(s) Source of Baseline

Incidence

PM2.5 20-64 years Moolgavkar (2000) - ICD 390-

429 (all cardiovascular)

1999 NHDS public use

data files

Asthma-Related ER

Visits

O3 All ages Pooled estimate: Weisel et al.

(1995), Cody et al. (1992),

Stieb et al. (1996)

2000 NHAMCS public use

data files3

; 1999 NHDS

public use data files

PM2.5 0-18 years Norris et al. (1999) 2000 NHAMCS public use

data files; 1999 NHDS

public use data files

Other Health Endpoints

Acute Bronchitis PM2.5 8-12 years Dockery et al. (1996) American Lung

Association (2002a, Table

11)

Asthma Exacerbations PM2.5 6-18 yearsA Pooled estimate:

Ostro et al. (2001) Cough

Ostro et al. (2001) Wheeze

Ostro et al. (2001) Shortness of

breath

Vedal et al. (1998) Cough

Ostro et al. (2001)

Vedal et al. (1998)

Upper Respiratory

Symptoms

PM10 Asthmatics, 9-

11 years

Pope et al. (1991) Pope et al. (1991, Table 2)

Lower Respiratory

Symptoms

PM2.5 7-14 years Schwartz and Neas (2000) Schwartz (1994, Table 2)

Work Loss Days PM2.5 18-65 years Ostro (1987) 1996 HIS (Adams et al.,

1999, Table 41); U.S.

Bureau of the Census

(2000)

School Absence Days O3

9-10 years

6-11 years

Pooled estimate:

Gilliland et al. (2001)

Chen et al. (2000)

National Center for

Education Statistics (1996)

Worker Productivity O3 Outdoor

workers, 18-65

Crocker and Horst (1981) and

U.S. EPA (1984)

NA

Minor Restricted

Activity Days

PM2.5, O3 18-65 years Ostro and Rothschild (1989) Ostro and Rothschild

(1989, p. 243)

A The original study populations were 8-13 for the Ostro et al. (2001) study and 6-13 for the Vedal et al. (1998)

study. Based on advice from the SAB-HES and NRC, we have extended the applied population to 6-18, reflecting

the common biological basis for the effect in children in the broader age group.
Table 9-7. Unit Values Used for Economic Valuation of Health Endpoints (2000$)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Premature Mortality (Value of aStatistical Life)

$5,500,000 $6,600,000 $6,800,000 Point estimate is the mean of a normal distribution with a 95 percent confidence

interval between $1 and $10 million. Confidence interval is based on two metaanalyses of the wage-risk VSL literature. $1 million represents the lower end ofthe interquartile range from the Mrozek and Taylor (2000) meta-analysis. $10million represents the upper end of the interquartile range from the Viscusi andAldy (2003) meta-analysis. The VSL represents the value of a small change inmortality risk aggregated over the affected population.

Chronic Bronchitis (CB) $340,000 $420,000 $430,000 Point estimate is the mean of a generated distribution of WTP to avoid a case of

pollution-related CB. WTP to avoid a case of pollution-related CB is derived byadjusting WTP (as described in Viscusi et al., 1991) to avoid a severe case of CB

for the difference in severity and taking into account the elasticity of WTP withrespect to severity of CB. 

Nonfatal Myocardial Infarction (heartattack)

3% discount rate

Age 0-24Age 25-44Age 45-54Age 55-65Age 66 and over7% discount rateAge 0-24Age 25-44Age 45-54Age 55-65Age 66 and over

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

Age specific cost-of-illness values reflecting lost earnings and direct medicalcosts over a 5 year period following a non-fatal MI. Lost earnings estimatesbased on Cropper and Krupnick (1990). Direct medical costs based on simpleaverage of estimates from Russell et al. (1998) and Wittels et al. (1990).Lost earnings:

Cropper and Krupnick (1990). Present discounted value of 5 yrs of lostearnings:age of onset: at 3% at 7%

25-44 $8,774 $7,85545-54 $12,932 $11,57855-65 $74,746 $66,920Direct medical expenses: An average of: 1. Wittels et al., 1990 ($102,658 – no discounting)2. Russell et al., 1998, 5-yr period. ($22,331 at 3% discount rate; $21,113 at 7%discount rate)

(continued)
Table 9-7. Unit Values Used for Economic Valuation of Health Endpoints (2000$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Hospital AdmissionsChronic Obstructive Pulmonary Disease(COPD)(ICD codes 490-492, 494-496)

$12,378 $12,378 $12,378 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total COPD category illnesses) reported inAgency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Pneumonia(ICD codes 480-487)

$14,693 $14,693 $14,693 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total pneumonia category illnesses) reported

in Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Asthma admissions $6,634 $6,634 $6,634 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total asthma category illnesses) reported inAgency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

All Cardiovascular(ICD codes 390-429)

$18,387 $18,387 $18,387 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total cardiovascular category illnesses)reported in Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Emergency room visits for asthma $286 $286 $286 Simple average of two unit COI values: 

(1) $311.55, from Smith et al., 1997, and (2) $260.67, from Stanford et al., 1999.

(continued)
Table 9-7. Unit Values Used for Economic Valuation of Health Endpoints (2000$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Respiratory Ailments Not Requiring HospitalizationUpper Respiratory Symptoms (URS) $25 $27 $27 Combinations of the 3 symptoms for which WTP estimates are available that

closely match those listed by Pope, et al. result in 7 different “symptomclusters,” each describing a “type” of URS. A dollar value was derived for eachtype of URS, using mid-range estimates of WTP (IEc, 1994) to avoid eachsymptom in the cluster and assuming additivity of WTPs. The dollar value forURS is the average of the dollar values for the 7 different types of URS.

Lower Respiratory Symptoms (LRS) $16 $17 $17 Combinations of the 4 symptoms for which WTP estimates are available that

closely match those listed by Schwartz, et al. result in 11 different “symptom

clusters,” each describing a “type” of LRS. A dollar value was derived for eachtype of LRS, using mid-range estimates of WTP (IEc, 1994) to avoid eachsymptom in the cluster and assuming additivity of WTPs. The dollar value forLRS is the average of the dollar values for the 11 different types of LRS.

Asthma Exacerbations $42 $45 $45 Asthma exacerbations are valued at $42 per incidence, based on the mean of

average WTP estimates for the four severity definitions of a “bad asthma day,”described in Rowe and Chestnut (1986). This study surveyed asthmatics toestimate WTP for avoidance of a "bad asthma day,” as defined by the subjects. For purposes of valuation, an asthma attack is assumed to be equivalent to a dayin which asthma is moderate or worse as reported in the Rowe and Chestnut(1986) study.

Acute Bronchitis $360 $380 $390 Assumes a 6 day episode, with daily value equal to the average of low and high

values for related respiratory symptoms recommended in Neumann, et al. 1994.

(continued)
Table 9-7. Unit Values Used for Economic Valuation of Health Endpoints (2000$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Restricted Activity and Work/School Loss DaysWork Loss Days (WLDs) Variable Variable Variable County-specific median annual wages divided by 50 (assuming 2 weeks of

vacation) and then by 5 – to get median daily wage. U.S. Year 2000 Census,compiled by Geolytics, Inc.

School Absence Days $75 $75 $75 Based on expected lost wages from parent staying home with child. Estimated

daily lost wage (if a mother must stay at home with a sick child) is based on themedian weekly wage among women age 25 and older in 2000 (U.S. CensusBureau, Statistical Abstract of the United States: 2001, Section 12: LaborForce, Employment, and Earnings, Table No. 621). This median wage is $551. Dividing by 5 gives an estimated median daily wage of $103.The expected loss in wages due to a day of school absence in which the motherwould have to stay home with her child is estimated as the probability that themother is in the workforce times the daily wage she would lose if she missed aday = 72.85% of $103, or $75.

Worker Productivity $0.95 per

worker per 10%

change in ozone

per day

$0.95 per

worker per 10%

change in ozone

per day

$0.95 per

worker per 10%

change in ozone

per day

Based on $68 – median daily earnings of workers in farming, forestry andfishing – from Table 621, Statistical Abstract of the United States (“Full-TimeWage and Salary Workers – Number and Earnings: 1985 to 2000") (Source ofdata in table: U.S. Bureau of Labor Statistics, Bulletin 2307 and Employmentand Earnings, monthly).

Minor Restricted Activity Days(MRADs)

$51 $54 $55 Median WTP estimate to avoid one MRAD from Tolley, et al. (1986) .
Cost-Benefit Analysis

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Table 9-8 

Primary Sources of Uncertainty in the Benefit Analysis

1. Uncertainties Associated With Health Impact Functions

S The value of the ozone or PM effect estimate in each health impact function.

S Application of a single effect estimate to pollutant changes and populations in all locations.

S Similarity of future year effect estimates to current effect estimates. 

S Correct functional form of each impact function. 

S Extrapolation of effect estimates beyond the range of ozone or PM concentrations observed in the study. 

S Application of effect estimates only to those subpopulations matching the original study population.

2. Uncertainties Associated With Ozone and PM Concentrations 

S Responsiveness of the models to changes in precursor emissions resulting from the control policy.

S Projections of future levels of precursor emissions, especially ammonia and crustal materials.

S Model chemistry for the formation of ambient nitrate concentrations.

S Lack of ozone monitors in rural areas requires extrapolation of observed ozone data from urban to rural areas.

S Use of separate air quality models for ozone and PM does not allow for a fully integrated analysis of pollutants and

their interactions.

S Full ozone season air quality distributions are extrapolated from a limited number of simulation days.

S Comparison of model predictions of particulate nitrate with observed rural monitored nitrate levels indicates that 

REMSAD overpredicts nitrate in some parts of the Eastern US and underpredicts nitrate in parts of the Western

US.

3. Uncertainties Associated with PM Premature mortality Risk

S No scientific literature supporting a direct biological mechanism for observed epidemiological evidence.

S Direct causal agents within the complex mixture of PM have not been identified.

S The extent to which adverse health effects are associated with low level exposures that occur many times in the

year versus peak exposures.

S The extent to which effects reported in the long-term exposure studies are associated with historically higher levels

of PM rather than the levels occurring during the period of study.

S Reliability of the limited ambient PM2.5 monitoring data in reflecting actual PM2.5 exposures.

4. Uncertainties Associated With Possible Lagged Effects

S The portion of the PM-related long-term exposure mortality effects associated with changes in annual PM levels

would occur in a single year is uncertain as well as the portion that might occur in subsequent years.

5. Uncertainties Associated With Baseline Incidence Rates

S Some baseline incidence rates are not location-specific (e.g., those taken from studies) and may therefore not

accurately represent the actual location-specific rates.

S Current baseline incidence rates may not approximate well baseline incidence rates in 2030.

S Projected population and demographics may not represent well future-year population and demographics.

6. Uncertainties Associated With Economic Valuation

S Unit dollar values associated with health and welfare endpoints are only estimates of mean WTP and therefore

have uncertainty surrounding them.

S Mean WTP (in constant dollars) for each type of risk reduction may differ from current estimates due to

differences in income or other factors.

S Future markets for agricultural products are uncertain.

7. Uncertainties Associated With Aggregation of Monetized Benefits

S Health and welfare benefits estimates are limited to the available effect estimates. Thus, unquantified or

unmonetized benefits are not included.
Final Regulatory Impact Analysis

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Table 9-9

Distribution of PM2.5 Air Quality Improvements Over Population 

Due to Nonroad Engine/Diesel Fuel Standards a

 in 2020 and 2030

Change in Annual Mean PM2.5

Concentrations (μg/m3) 

2020 Population 2030 Population

Number (millions) Percent (%) Number (millions) Percent (%)

0 < ) PM2.5 Conc # 0.25 65.11 19.75% 28.60 8.04%

0.25 < ) PM2.5 Conc # 0.5 184.52 55.97% 147.09 41.33%

0.5 < ) PM2.5 Conc # 0.75 56.66 17.19% 107.47 30.20%

0.75 < ) PM2.5 Conc # 1.0 14.60 4.43% 38.50 10.82%

1.0 < ) PM2.5 Conc # 1.25 5.29 1.60% 8.82 2.48%

1.25 < ) PM2.5 Conc # 1.5 3.51 1.06% 15.52 4.36%

1.5 < ) PM2.5 Conc # 1.75 0 0.00% 5.70 1.60%

) PM2.5 Conc > 1.75 0 0.00% 4.19 1.18%

a

 The change is defined as the control case value minus the base case value. The results reflect the modeling for the preliminary

control option, not the final rule.

9.3.8 Apportionment of Benefits to NOx, SO2, and Direct PM Emissions Reductions

As noted in the introduction to this chapter, the standards we are finalizing in this rule differ

from those that we used in modeling air quality and economic benefits. As such, it is necessary

for us to scale the modeled benefits to reflect the difference in emissions reductions between the

final and preliminary modeled standards. In order to do so, however, we must first apportion

total benefits to the NOx, SO2, and direct PM reductions for the modeled preliminary control

options. This apportionment is necessary due to the differential contribution of each emission

species to the total change in ambient PM and total benefits. We do not attempt to develop

scaling factors for ozone benefits because of the difficulty in separating the contribution of NOx

and NMHC/VOC reductions to the change in ozone concentrations.

As discussed in detail in Chapter 2, PM is a complex mixture of particles of varying species,

including nitrates, sulfates, and primary particles, including organic and elemental carbon. 

These particles are formed in complex chemical reactions from emissions of precursor

pollutants, including NOx, SO2, ammonia, hydrocarbons, and directly emitted particles. Different

emissions species contribute to the formation of PM in different amounts, so that a ton of

emissions of NOx contributes to total ambient PM mass differently than a ton of SO2 or directly

emitted PM. As such, it is inappropriate to scale benefits by simply scaling the sum of all

precursor emissions. A more appropriate scaling method is to first apportion total PM benefits to

the changes in underlying emission species and then scale the apportioned benefits.

PM formation relative to any particular reduction in an emission species is a highly nonlinear

process, depending on meteorological conditions and baseline conditions, including the amount
Cost-Benefit Analysis

9-39

of available ammonia to form ammonium nitrate and ammonium sulfate. Given the limited air

quality modeling conducted for this analysis, we make several simplifying assumptions about the

contributions of emissions reductions for specific species to changes in particulate species. For

this exercise, we assume that changes in sulfate particles are attributable to changes in SO2

emissions, changes in nitrate particles are attributable to changes in NOx emissions, and changes

in primary PM are attributable to changes in direct PM emissions. These assumptions essentially

assume independence between SO2, NOx, and direct PM in the formation of ambient PM. This

is a reasonable assumption for direct PM, as it is generally not reactive in the atmosphere. 

However, SO2 and NOx emissions interact with other compounds in the atmosphere to form

PM2.5. For example, ammonia reacts with SO2 first to form ammonium sulfate. If there is

remaining ammonia, it reacts with NOx to form ammonium nitrate. When SO2 alone is reduced,

ammonia is freed to react with any NOx that has not been used in forming ammonium nitrate. If

NOx is also reduced, then there will be less available NOx to form ammonium nitrate from the

newly available ammonia. Thus, reducing SO2 can potentially lead to decreased ammonium

sulfate and increased nitrate, so that overall ambient PM benefits are less than the reduction in

sulfate particles. If NOx alone is reduced, there will be a direct reduction in ammonium nitrate,

although the amount of reduction depends on whether an area is ammonia limited. If there is not

enough ammonia in an area to use up all of the available NOx, then NOx reductions will only

have an impact if they reduce emissions to the point where ammonium nitrate formation will be

affected. NOx reductions will not result in any offsetting increases in ambient PM under most

conditions. The implications of this for apportioning benefits between NOx, SO2, and direct PM

is that some of the sulfate-related benefits will be offset by reductions in nitrate benefits, so

benefits from SO2 reductions will be overstated, while NOx benefits will be understated. It is

not immediately apparent the size of this bias.

The measure of change in ambient particulate mass that is most related to health benefits is

the population-weighted change in PM2.5 :g/m3, because health benefits are driven both by the

size of the change in PM2.5 and the populations exposed to that change. We calculate the

proportional share of total change in mass accounted for by nitrate, sulfate, and primary

particles. Results of these calculations for the 2020 and 2030 REMSAD modeling analysis are

presented in Table 9-10. The sulfate percentage of total change is used to represent the SO2

contribution to health benefits, the nitrate percentage is used to represent the NOx contribution to

health benefits, and the primary PM percentage is used to represent the direct PM contribution to

health benefits. These percentages will be applied to the PM-related health benefits estimates in

Appendix A in Tables 9A-30 and 9A-31 and combined with the emission scaling factors

developed in section 9.2 to estimate benefits for the final set of standards.
Final Regulatory Impact Analysis

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Table 9-10. Apportionment of Modeled Preliminary Control Option Population-weighted

Change in Ambient PM2.5 to Nitrate, Sulfate, and Primary Particles

2020 2030

Populationweighted

Change (:g/m3)

Percent of Total

Change

Populationweighted

Change (:g/m3)

Percent of Total

Change

Total PM2.5 0.316 -- 0.438 --

Sulfate 0.071 22.5% 0.090 20.5%

Nitrate 0.041 13.1% 0.073 16.8%

Primary PM 0.203 64.4% 0.274 62.7%

Visibility benefits are highly specific to the parks at which visibility improvement occur,

rather than where populations live. As such, it is necessary to scale benefits at each individual

park and then aggregate to total scaled visibility benefits. We apportion benefits at each park

using the contribution of changes in sulfates, nitrates, and primary particles to changes in light

extinction. The change in light extinction at each park is determined by the following equation

(Sisler, 1996):

∆ ∆ ∆ ∆ ∆∆ ∆ β [ ] ( ) [ ] ( ) EXT = + + ++ + 3 1375 4 3 129 3 10 4 0 6 F rh TSO F rh PNO PEC TOA PMFINE PMCOARSE *. * *. * * * . *

where rh is relative humidity, )TSO4 is the change in particulate sulfate, )PNO3 is the change

in particulate nitrate, )PEC is the change in primary elemental carbon, )TOA is the change in

total organic aerosols, )PMFINE is the change in primary fine particles, and )PMCOARSE is

the change in primary coarse particles.

The proportion of the total change in light extinction associated with changes in sulfate particles

is . The proportion of the total change in light extinction [ ] 3 1375 4 F rh TSO EXT ( )* . * ∆ ∆β

associated with changes in nitrate particles is . Finally, the [ ] 3 129 3 F rh PNO EXT ( )* . * ∆ ∆β

proportion of the total change in light extinction associated with the change in directly emitted

particles is . [ ] 10 4 0 6 * * .* ∆ ∆∆ ∆ ∆ PEC TOA PMFINE PMCOARSE ++ + βEXT

We calculate these proportions for each park to apportion park specific benefits between SO2,

NOx, and PM. The apportioned benefits are then scaled using the emission ratios in Table 9-5. 

Park specific apportionment of benefits is detailed in Appendix 9D.
Cost-Benefit Analysis

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9.4 Estimated Benefits of Final Nonroad Diesel Engine Standards in 2020

and 2030

To estimate the benefits of the NOx, SO2, and direct PM emission reductions from the

nonroad diesel engine standards in 2020 and 2030, we apply the emissions scaling factors

derived in section 9.2 and the apportionment factors described in section 9.3 to the benefits

estimates for 2020 and 2030 listed in Tables 9A-30 and 9A-31. Note that we apply scaling and

apportionment factors only to PM and visibility related endpoints. Ozone related health and

welfare benefits are not estimated for the emissions reductions associated with the final

standards for reasons noted in the introduction to this chapter. 

The scaled avoided incidence estimate for any particular health endpoint is calculated using

the following equation:

Scaled Incidence Modeled Incidence R A , i i

i

= *∑

where Ri is the emissions ratio for emission species i from Table 9-4, and Ai is the health

benefits apportionment factor for emission species i, from Table 9-10. Essentially, benefits are

scaled using a weighted average of the species specific emissions ratios. For example, the

calculation of the avoided incidence of premature mortality for the base estimate in 2020 is:

Scaled Premature Mortality Incidence = 7,821 * (0.759*0.131 + 0.800*0.225 + 0.869*0.644) =

6,562 (rounded to 6,600)

The monetized value for each endpoint is then obtained simply by multiplying the scaled

incidence estimate by the appropriate unit value in Table 9-6. The estimated changes in

incidence of health effects in 2020 and 2030 for the final rule based on application of the

weighted scaling factors are presented in Table 9-11. The estimated monetized benefits for both

PM health and visibility benefits are presented in Table 9-12. The visibility benefits are based

on application of the weighted scaling factors for visibility at each Class I area in the Chestnut

and Rowe study regions, aggregated to a national total for each year.
Final Regulatory Impact Analysis

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Table 9-11. 

Reductions in Incidence of PM-related Adverse Health Effects Associated with 

the Final Full Program of Nonroad Diesel Engine and Fuel Standards

Endpoint

Avoided IncidenceA

(cases/year)

2020 2030

Premature mortalityB

: Long-term exposure (adults, 30 and over) 6,400 12,000

Infant mortality (infants under one year) 15 22

Chronic bronchitis (adults, 26 and over) 3,500 5,600

Non-fatal myocardial infarctions (adults, 18 and older) 8,700 15,000

Hospital admissions – Respiratory (adults, 20 and older)C 2,800 5,100

Hospital admissions – Cardiovascular (adults, 20 and older)D 2,300 3,800

Emergency Room Visits for Asthma (18 and younger) 3,800 6,000

Acute bronchitis (children, 8-12) 8,400 13,000

Asthma exacerbations (asthmatic children, 6-18) 120,000 200,000

Lower respiratory symptoms (children, 7-14) 99,000 160,000

Upper respiratory symptoms (asthmatic children, 9-11) 76,000 120,000

Work loss days (adults, 18-65) 670,000 1,000,000

Minor restricted activity days (adults, age 18-65) 3,900,000 5,900,000

A Incidences are rounded to two significant digits.

B

 Premature mortality associated with ozone is not separately included in this analysis C Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. 

D Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart

disease, dysrhythmias, and heart failure.
Cost-Benefit Analysis

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Table 9-12. Results of PM Human Health and Welfare Benefits 

Valuation for the Final Full Program of Nonroad Diesel Engine and Fuel Standards

Endpoint

Monetary BenefitsA,B

(millions 2000$, Adjusted for Income

Growth)

2020 2030

Premature mortalityC: (adults, 30 and over)

3% discount rate $40,000 $77,000

7% discount rate $38,000 $72,000

Infant mortality (infants under one year) $960 $150

Chronic bronchitis (adults, 26 and over) $1,500 $2,400

Non-fatal myocardial infarctionsD

3% discount rate $740 $1,200

7% discount rate $720 $1,200

Hospital Admissions from Respiratory CausesE $49 $92

Hospital Admissions from Cardiovascular CausesF $50 $83

Emergency Room Visits for Asthma $1.0 $1.7

Acute bronchitis (children, 8-12) $3.2 $5.1

Asthma exacerbations (asthmatic children, 6-18) $5.7 $9.2

Lower respiratory symptoms (children, 7-14) $1.7 $2.7

Upper respiratory symptoms (asthmatic children, 9-11) $2.0 $3.2

Work loss days (adults, 18-65) $91 $130

Minor restricted activity days (adults, age 18-65) $210 $320

Recreational visibility (86 Class I Areas) $1,000 $1,700

Monetized TotalG

3% discount rate

7% discount rate

$44,000+B

$42,000+B

$83,000+B

$78,000+B

A Monetary benefits are rounded to two significant digits.

B Monetary benefits are adjusted to account for growth in real GDP per capita between 1990 and the analysis year (2020 or 2030). C Valuation of base estimate assumes discounting over the distributed lag structure described earlier. Results reflect the use of 3% and 7%

discount rates consistent with EPA and OMB’s guidelines for preparing economic analyses (US EPA, 2000c, OMB Circular A-4). D Estimates assume costs of illness and lost earnings in later life years are discounted using either 3 or 7 percent E

 Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. F

 Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart disease, dysrhythmias, and heart

failure.

G B represents the monetary value of the unmonetized health and welfare benefits. A detailed listing of unquantified PM, ozone, CO, and NMHC

related health effects is provided in Table 9-1. These estimates do not include the benefits of reduced sulfur in home heating oil or benefits in Alaska or

Hawaii.
Final Regulatory Impact Analysis

9-44

We also evaluated the benefits of the NOx, SO2, and direct PM emission reductions from the

nonroad diesel engine standards in 2020 and 2030 of the fuel-only portions of the program.

Accordingly, we applied the benefits transfer methods to calculate similar results for the fuel

only portion of the program and the 500 ppm NRLM program. Because there would be no NOx

or NMHC reductions for the fuel-only components of the rule, the benefits transfer technique

may have more uncertainty in this application compared to the full program. As discussed

above, we apply scaling and apportionment factors only to PM health and visibility related

endpoints. Toxics and ozone-related health and welfare benefits are not estimated for the

emissions reductions associated with the final standards for reasons noted in the introduction to

this chapter. 

The estimated changes in incidence of health effects in 2020 and 2030 for the fuel-only

components of the final rule based on application of the weighted scaling factors are presented in 

Table 9-13. The estimated monetized benefits for both PM health and visibility benefits are

presented in Table 9-14. As described above, the visibility benefits are based on application of

the weighted scaling factors for visibility at each Class I area in the Chestnut and Rowe study

regions, aggregated to a national total for each year.
Table 9-13. 

Reductions in Incidence of PM-related Adverse 

Health Effects Associated with the Final Fuel-Related Components of Nonroad Diesel

Standards

Endpoint

Avoided IncidenceA

(cases/year)

Fuel Only Program 500 ppm NRLM Fuel

2020 2030 2020 2030

Premature mortalityB

: Long-term exposure (adults, 30

and over)

2,700 4,000 2,400 3,600

Infant mortality (infants under one year) <10 <10 <10 <10

Chronic bronchitis (adults, 26 and over) 1,500 1,900 1,300 1,700

Non-fatal myocardial infarctions (adults, 18 and older) 3,600 5,200 3,200 4,700

Hospital admissions – Respiratory (adults, 20 and older)C 1,200 1,700 1,000 1,600

Hospital admissions – Cardiovascular (adults, 20 and

older)D

900 1,300 900 1,100

Emergency Room Visits for Asthma (18 and younger) 1,600 2,000 1,400 1,800

Acute bronchitis (children, 8-12) 3,500 4,600 3,100 4,100

Asthma exacerbations (asthmatic children, 6-18) 51,000 68,000 46,000 61,000

Lower respiratory symptoms (children, 7-14) 41,000 54,000 37,000 49,000

Upper respiratory symptoms (asthmatic children, 9-11) 31,000 41,000 28,000 37,000

Work loss days (adults, 18-65) 280,000 340,000 250,000 300,000

Minor restricted activity days (adults, age 18-65) 1,600,000 2,000,000 1,500,000 1,800,000

A Incidences are rounded to two significant digits or nearest ten. The estimates do not include the benefits of

reduced sulfur in home heating oil or benefits in Alaska or Hawaii.

B

 Premature mortality associated with ozone is not separately included in this analysis C Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. 

D Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart

disease, dysrhythmias, and heart failure.
Final Regulatory Impact Analysis

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Table 9-14. Results of PM Human Health and Welfare Benefits Valuation 

for the Final Fuel-Related Components of the Nonroad Diesel Standards

Endpoint

Monetary BenefitsA,B

(millions 2000$, Adjusted for Income Growth)

Fuel Only Program 500 ppm NRLM Fuel

2020 2030 2020 2030

Premature mortalityC: (adults, 30 and over)

3% discount rate $17,000 $26,000 $15,000 $23,000

7% discount rate $16,000 $24,000 $14,000 $22,000

Infant mortality (infants under one year) $40 $52 $36 $47

Chronic bronchitis (adults, 26 and over) $610 $820 $550 $740

Non-fatal myocardial infarctionsD

3% discount rate $310 $420 $280 $380

7% discount rate $300 $410 $270 $370

Hospital Admissions from Respiratory CausesE $20 $31 $18 $28

Hospital Admissions from Cardiovascular CausesF $21 $28 $19 $25

Emergency Room Visits for Asthma $0.4 $0.6 $0.4 $0.5

Acute bronchitis (children, 8-12) $1.3 $1.7 $1.2 $1.6

Asthma exacerbations (asthmatic children, 6-18) $2.3 $3.1 $2.1 $2.8

Lower respiratory symptoms (children, 7-14) $0.7 $0.9 $0.6 $0.8

Upper respiratory symptoms (asthmatic children, 9-11) $0.8 $1.1 $0.7 $1.0

Work loss days (adults, 18-65) $38 $43 $34 $39

Minor restricted activity days (adults, age 18-65) $90 $110 $80 $100

Recreational visibility (86 Class I Areas) $400 $550 $360 $500

Monetized TotalG

3% discount rate

7% discount rate

$18,000+B

$17,000+B

$28,000+B

$26,000+B

$16,000+B

$15,000+B

$25,000+B

$24,000+B A Monetary benefits are rounded to two significant digits B Monetary benefits are adjusted to account for growth in real GDP per capita between 1990 and the analysis year (2020 or 2030). C Valuation of base estimate assumes discounting over the distributed lag structure described earlier. Results reflect the use of 3% and 7% discount rates consistent

with EPA and OMB’s guidelines for preparing economic analyses (US EPA, 2000c, OMB Circular A-4). D Estimates assume costs of illness and lost earnings in later life years are discounted using either 3 or 7 percent E

 Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. F

 Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart disease, dysrhythmias, and heart failure. G B represents the monetary value of the unmonetized health and welfare benefits. A detailed listing of unquantified PM, ozone, CO, and NMHC related health

effects is provided in Table 9-1. The estimates do not include the benefits of reduced sulfur in home heating oil or benefits in Alaska or Hawaii.
Cost-Benefit Analysis

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9.5 Development of Intertemporal Scaling Factors and Calculation of

Benefits Over Time

To estimate the health and visibility benefits of the NOx, SO2, and direct PM emission

reductions from the final standards occurring in years other than 2020 and 2030, it is necessary

to develop factors to scale the modeled benefits in 2020 and 2030. In addition to scaling based

on the relative reductions in NOx, SO2, and direct PM, intertemporal scaling requires additional

adjustments to reflect population growth, changes in the age composition of the population, and

per capita income levels.

Two separate sets of scaling factors are required, one for PM related health benefits, and one

for visibility benefits. For the first of these, PM health benefits, we need scaling factors based on

ambient PM2.5. Because of the nonproportional relationship between precursor emissions and

ambient concentrations of PM2.5, it is necessary to first develop estimates of the marginal

contribution of reductions in each emission species to reductions in PM2.5 in each year. Because

we have only two points (2020 and 2030), we assume a very simple linear function for each

species over time (assuming that the marginal contribution of each emission species to PM2.5 is

independent of the other emission species) again assuming that sulfate changes are primarily

associated with SO2 emission reductions, nitrate changes are primarily associated with NOx

emission reductions, and primary PM changes are associated with direct PM emission

reductions. 

Using the linear relationship, we estimate the marginal contribution of SO2 to sulfate, NOx to

nitrate, and direct PM to primary PM in each year. These marginal contribution estimates are

presented in Table 9-15. Note that these projections do not take into account differences in

overall baseline proportions of NOx, SO2, and PM. They assume that the change in the relative

effectiveness of each emission species in reducing ambient PM that is observed between 2020

and 2030 can be extrapolated to other years. Because baseline emissions of NOx, SO2, and PM,

as well as ammonia and VOCs are changing between years, the relative effectiveness of NOx

and SO2 emission reductions may change in a non-linear fashion. It is not clear what overall

biases these nonlinearities will introduce into the scaling exercise. However, without these

assumptions, it is not possible to develop year by year benefits estimates.

Multiplying the year-specific marginal contribution estimates by the appropriate emissions

reductions in each year yields estimates of the population-weighted changes in PM2.5 constituent

species, which are summed to obtain year specific population-weighted changes in total PM2.5.

Total benefits in each specific year are then developed by scaling total benefits in a base year

using the ratio of the change in PM2.5 in the target year to the base year, with additional scaling

factors to account for growth in total population, age composition of the population, and growth

in per capita income.
Final Regulatory Impact Analysis

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Table 9-15. 

Projected Marginal Contribution of Reductions 

in Emission Species to Reductions in Ambient PM2.5

Change in PM2.5 species (population-weighted :g/m3 per million tons reduced)

Year Sulfate/SO2 Nitrate/NOx Primary PM/direct PM

2007 0.153 0.049 2.130

2008 0.154 0.050 2.123

2009 0.156 0.051 2.117

2010 0.157 0.052 2.111

2011 0.159 0.053 2.105

2012 0.160 0.054 2.098

2013 0.161 0.055 2.092

2014 0.163 0.056 2.086

2015 0.164 0.057 2.080

2016 0.166 0.058 2.073

2017 0.167 0.059 2.067

2018 0.169 0.060 2.061

2019 0.170 0.061 2.054

2020 0.171 0.062 2.048

2021 0.173 0.063 2.042

2022 0.174 0.064 2.036

2023 0.176 0.065 2.029

2024 0.177 0.066 2.023

2025 0.179 0.067 2.017

2026 0.180 0.069 2.011

2027 0.181 0.070 2.004

2028 0.183 0.071 1.998

2029 0.184 0.072 1.992

2030 0.186 0.073 1.985

Growth in population and changes in age composition are accounted for by apportioning

total benefits into benefits accruing to three different age groups, 0 to 18, 19 to 64, and 65 and

older. Benefits for each age group are then adjusted by the ratio of the age group population in

the target year to the age group population in the base year. Age composition adjusted estimates

are then reaggregated to obtain total population and age composition adjusted benefits for each

year. Growth in per capita income is accounted for by multiplying the target year estimate by

the ratio of the income adjustment factors in the target year to those in the base year.

For example, for the target year of 2015, there are 193,431 tons of NOx reductions, 297,513

tons of SO2 reductions, and 53,072 tons of direct PM2.5 reductions. These are associated with a
Cost-Benefit Analysis

9-49

populated weighted change in total PM2.5 of 0.17, calculated from Table 9-15. The ratio of this

change to the change in the 2030 base year is 0.392. The age group apportionment factors

(based on using a 3% discount rate for 2030) are 0.2% for 0 to 18, 19.2% for 19 to 64, and

80.6% for 65 and older. The age group population growth ratios for 2015 relative to 2030 are

0.891 for 0 to 18, 0.986 for 19 to 64, and 0.639 for 65 and older. The income growth adjustment

ratios for 2015 are 0.936 for premature mortality endpoints and 0.928 for morbidity endpoints. 

Premature mortality accounts for 93 percent of total health benefits and morbidity accounts for 7

percent of health benefits. Combining these elements with the total estimate of PM health

benefits in 2030 of $94.2 billion , total PM health benefits in 2015 for the final standards are

calculated as:

Total PM health benefits (2015) = 

[$94.2 billion * 0.392*(0.002*0.891+0.192*0.986+0.806*0.639)*(0.93*0.936+0.07*0.928)] 

= $24.2 billion

In order to develop the time stream of visibility benefits, we need to develop scaling factors

based on the contribution of each emission species to light extinction. Similar to ambient PM2.5,

because we have only two estimates of the change in light extinction (2020 and 2030), we

assume a very simple linear function for each species over time (assuming that the marginal

contribution of each emission species to light extinction is independent of the other emission

species) assuming that changes in the sulfate component of light extinction are associated with

SO2 emission reductions, changes in the nitrate component of light extinction are primarily

associated with NOx emission reductions, and changes in the primary PM components of light

extinction are associated with direct PM emission reductions. Linear relationships (slope and

intercept) are calculated for each Class I area.

Using the linear relationships, we estimate the marginal contribution of SO2, NOx, and direct

PM to the change in light extinction at each Class I area in each year. Again, note that these

estimates assume that the change in the relative effectiveness of each emission species in

reducing light extinction that is observed between 2020 and 2030 can be extrapolated to other

years.

Multiplying the year specific marginal contribution estimates by the appropriate emissions

reductions in each year yields estimates of the changes in light extinction components, which are

summed to obtain year specific changes in total light extinction. Benefits for each park in each

specific year are then developed by scaling total benefits in a base year using the ratio of the

change in light extinction in the target year to the base year, with additional scaling factors to

account for growth in total population, and growth in per capita income. Total national visibility

benefits for each year are obtained by summing the scaled benefits across Class I areas.
Final Regulatory Impact Analysis

KWe refer to discounting that occurs during the calculation of benefits for individual years as concurrent

discounting. This is distinct from discounting that occurs over the time stream of benefits, which is referred to as

intertemporal discounting.

9-50

Table 9-16 provides undiscounted estimates of the time stream of benefits for the final

standards using 3 and 7 percent concurrent discount rates.K Figure 9-1 shows the undiscounted

time stream of benefits using a 3 percent concurrent discount rate. Because of the assumptions

we made about the linearity of benefits for each emission species, overall benefits are also linear,

reflecting the relatively linear emissions reductions over time for each emission type. The

exception is during the early years of the program, where there is little NOx emission reduction,

so that benefits are dominated by SO2 and direct PM2.5 reductions.

Using a 3 percent intertemporal discount rate, the present value in 2004 of the benefits of the

final standards is approximately $805 billion for the time period 2007 to 2036, using a matching

3 percent concurrent discount rate. Using a 7 percent intertemporal discount rate, the present

value in 2004 of the benefits of the final standards for the base estimate is approximately $352

billion using a matching 7 percent concurrent discount rate.

Annualized benefits using 3 percent intertemporal and concurrent discount rates are

approximately $39 billion. Annualized benefits using 7 percent intertemporal and concurrent

discount rates are approximately $28 billion.
Cost-Benefit Analysis

9-51

Table 9-16. Time Stream of Benefits for Final Nonroad Diesel Engine StandardsA,B

Year

Monetized PM-Health and Visbility Benefits

(Million 2000$)

3% Concurrent Discount Rate 7% Concurrent Discount Rate

2007 $5,000 $4,700

2008 $9,100 $8,600

2009 $9,700 $9,100

2010 $11,000 $10,000

2011 $12,000 $12,000

2012 $15,000 $14,000

2013 $18,000 $17,000

2014 $21,000 $20,000

2015 $25,000 $23,000

2016 $28,000 $27,000

2017 $32,000 $31,000

2018 $36,000 $34,000

2019 $40,000 $38,000

2020 $44,000 $42,000

2021 $48,000 $46,000

2022 $52,000 $49,000

2023 $56,000 $53,000

2024 $61,000 $57,000

2025 $64,000 $61,000

2026 $68,000 $64,000

2027 $72,000 $68,000

2028 $76,000 $71,000

2029 $79,000 $75,000

2030 $83,000 $78,000

2031 $87,000 $82,000

2032 $90,000 $85,000

2033 $94,000 $89,000

2034 $98,000 $92,000

2035 $100,000 $96,000

2036 $110,000 $100,000

Present Value in 2004

3% Intertemporal Discount Rate $805,000 --

7% Intertemporal Discount Rate -- $350,000

A All dollar estimates rounded to two significant digits.

B Results reflect the use of 3% and 7% discount rates consistent with EPA and OMB’s guidelines for preparing economic analyses (US EPA,

2000c, OMB Circular A-4).
Final Regulatory Impact Analysis

9-52

Figure 9-1. 

Base Estimate of the Stream of Annual Benefits for the Final Nonroad Diesel Engine 

Standards: 2007 to 2036

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

200720082009201020112012201320142015201620172018201920202021202220232024202520262027202820292030203120322033203420352036

Million 2000$

9.6 Comparison of Costs and Benefits

The estimated social cost (measured as changes in consumer and producer surplus) in 2030

to implement the final rule, as described in Chapter 8 is $2.0 billion (here, converted to 2000$). 

Thus, the net benefit (social benefits minus social costs) of the program at full implementation is

approximately $81 + B billion, where B represents the sum of all unquantified benefits and

disbenefits. In 2020, partial implementation of the program yields net benefits of $42 + B

billion. Therefore, implementation of the final rule is expected, based purely on economic

efficiency criteria, to provide society with a significant net gain in social welfare. Table 9-17

presents a summary of the benefits, costs, and net benefits of the final rule. Figure 9-2 displays

the stream of benefits, costs, and net benefits of the Nonroad Diesel Engine and Fuel Standards

from 2007 to 2036. In addition, Table 9-18 presents the present value of the stream of benefits,

costs, and net benefits associated with the rule for this 30 year period. The total present value of

the stream of monetized net benefits (benefits minus costs) is $750 billion (using a three percent

discount rate). 
Cost-Benefit Analysis

9-53

Table 9-17.

Summary of Monetized Benefits, Costs, and Net Benefits of the 

Final Full Program Nonroad Diesel Engine and Fuel StandardsA

Base EstimateB

2020

(Billions of 2000

dollars)

2030

(Billions of 2000

dollars)

 Social CostsC $1.8 $2.0

 Social BenefitsD, E:

 CO, VOC, Air Toxic-related benefits Not monetized Not monetized

 Ozone-related benefits Not monetized Not monetized

 PM-related Welfare benefits $1.0 $1.7

 PM-related Health benefits (3% discount rate) $43 $81

 PM-related Health benefits (7% discount rate) $41 $78

Net Benefits (Benefits-Costs)D,E (3% discount rate) $42 +B $81 +B

Net Benefits (Benefits-Costs)D,E (7% discount rate) $41 +B $78 +B

A All costs and benefits are rounded to two significant digits.

B Base Estimate reflects premature mortality based on application of concentration-response function derived from long-term

exposure to PM2.5, valuation using the value of statistical lives saved apporach, and a willingness-to-pay approach for valuing

chronic bronchitis incidence.

C Note that costs are the total costs of reducing all pollutants, including CO, VOCs and air toxics, as well as NOx and PM. 

Benefits in this table are associated only with PM, NOx and SO2 reductions. These estimates do not include the benefits of

reduced sulfur in home heating oil or benefits in Alaska or Hawaii. Costs are converted from 2002$ to 2000$ in this table using

the PPI for Total Manufacturing Industries.

D Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories that have not

been quantified and monetized are listed in Table 9-1. These estimates do not include the benefits of reduced sulfur in home

heating oil or benefits in Alaska or Hawaii. B is the sum of all unquantified benefits and disbenefits. E

 Monetized benefits are presented using two different discount rates. Results reflect the use of 3% and 7% discount rates

consistent with EPA and OMB’s guidelines for preparing economic analyses (US EPA, 2000c, OMB Circular A-4).
Final Regulatory Impact Analysis

9-54

$(20,000)

$-

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

2005 2010 2015 2020 2025 2030 2035

Millions dollars

Total Social Benefits Total Social Costs Net Benefits

Figure 9-2.

Stream of Benefits, Costs, and Net Benefits of the 

Final Nonroad Diesel Engine and Fuel Standards
Cost-Benefit Analysis

9-55

Table 9-18.

Present Value in 2004 of the Stream of 30 Years of

Benefits, Costs, and Net Benefits for the Final Full Program 

Nonroad Diesel Engine and Fuel Standards

(Billions of 2000$)a, b

Billions of 2000$

3% Discount Rate

Billions of 2000$

7% Discount Rate

Social Costs $ 27 $ 14

Social Benefits $805 $352

Net Benefits a $780 $340

 a Rounded to two significant digits

b Benefits represent 48-state benefits and exclude home heating oil sulfur reduction

benefits, whereas costs include 50-state estimates. Costs were converted from 2002$

to 2000$ using the PPI for Total Manufacturing Industries. 
Final Regulatory Impact Analysis

9-56

Table 9-19.

Summary of Monetized Benefits, Costs, and Net Benefits of the 

Final Fuel Only Components of the Nonroad Diesel Standards (Billions of 2000 dollars) A

Fuel Only 

Program

500 ppm 

NRLM Fuel

2020 2030 2020 2030

Costs B, C $0.62 $0.72 ($0.28) ($0.36)

Social BenefitsC, D, E:

 CO, VOC, Air

 Toxic-related benefits

Not monetized Not monetized Not monetized Not monetized

 Ozone-related 

 benefits

Not monetized Not monetized Not monetized Not monetized

 PM-related Welfare

 benefits $0.4 $0.6 $0.4 $0.5

 PM-related Health

 benefits 

 (3 % discount rate)

$18 $28 $16 $25

 PM-related Health

 benefits 

 (7% discount rate)

$17 $26 $15 $23

Net Benefits (3% discount

rate) = (Benefits-Costs)C, D, E $ 18 + B $ 28 + B $ 16 + B $ 25 + B

Net Benefits (7% discount

rate) = (Benefits-Costs)C, D, E $ 17 + B $ 26 + B $ 16 + B $ 24 + B

A All costs and benefits are rounded to two significant digits.

B Engineering costs are presented instead of social costs. As discussed in previous chapters, total engineering costs include fuel

costs (refining, distribution, lubricity) and other operating costs (oil change maintenance savings). All engine and equipment

fixed cost expenditures are amortized using a seven percent capital cost to reflect the time value of money. The annual costs

presented here are the costs in the indicated year and are not the net present values. C Note that costs are the total costs of reducing all pollutants, including CO, VOCs and air toxics, as well as NOx and PM. 

Benefits in this table are associated only with PM, NOx and SO2 reductions. The estimates do not include the benefits of reduced

sulfur in home heating oil or benefits in Alaska or Hawaii. Costs were converted from 2002$ to 2000$ using the PPI for

Total Manufacturing Industries.

D Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories that

have not been quantified and monetized are listed in Table 9-1. B is the sum of all unquantified benefits and

disbenefits.

E

 Monetized costs and benefits are presented using two different discount rates. Results reflect the use of 3% and 7%

discount rates consistent with EPA and OMB’s guidelines for preparing economic analyses (US EPA, 2000c, OMB Circular A4).
Cost-Benefit Analysis

9-57

Table 9-20.

Present Value in 2004 of the Stream of 30 Years of

Benefits, Costs, and Net Benefits for the 

Final Fuel Only Components of the Nonroad Diesel Standards

(Billions of 2000$)A, B, C, D

Fuel Only 

Program

500 ppm 

NRLM Fuel

3 % discount rate

Costs $9.2 ($0.54)

Social Benefits $340 $310

Net Benefits $330 $310

7 % discount rate

Costs $4.6 ($0.3)

Social Benefits $160 $140

Net Benefits $160 $140

A Results are rounded to two significant digits. Sums may differ because of rounding.

B Engineering costs are presented instead of social costs. As discussed in previous chapters, total engineering costs

include fuel costs (refining, distribution, lubricity) and other operating costs (oil change maintenance savings). C Note that costs are the total costs of reducing all pollutants, including CO, VOCs and air toxics, as well as NOx and PM. 

Benefits in this table are associated only with PM, NOx and SO2 reductions. The estimates do not include the benefits of

reduced sulfur in home heating oil or benefits in Alaska or Hawaii. D Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit

categories that have not been quantified and monetized are listed in Table 9-1. B is the sum of all

unquantified benefits and disbenefits.

E

 Monetized costs and benefits are presented using two different discount rates. Results reflect the use of 3% and

7% discount rates consistent with EPA and OMB’s guidelines for preparing economic analyses (US EPA, 2000c, OMB

Circular A-4).
Final Regulatory Impact Analysis

9-58

A key input to our benefit-cost analysis is the social costs and emission reductions associated

with the final program. Each of these elements also has associated uncertainty which contributes

to the overall uncertainty in our analysis of benefit-cost.

EPA engineering cost estimates are based upon considerable expertise and experience within

the Agency. At the same time, any estimate of the future cost of control technology for engines

or the cost of removing sulfur from diesel fuel is inherently uncertain to some degree. At the

start is the question of what technology will actually be used to meet future standards, and what

such technology will cost at the time of implementation. Our estimates of control costs are based

upon current technology plus newer technology already “in the pipeline.” New technology not

currently anticipated is by its nature not specifically included. Potential new production

techniques which might lower costs are also not included in these estimates (although they are

partially included among factors contributing to learning curve effects). On the other side of the

equation are unforseen technical hurdles that may act to increase control system costs.

There is also uncertainty in our social cost estimates. Our Economic Impact Assessment

presented in Chapter 10 includes sensitivity analyses examining the effect of varying

assumptions surrounding the following key factors (Chapter 10, Appendix 10-I):

- market supply and demand elasticity parameters

- alternative assumptions about the fuel market supply shifts and fuel maintenance savings

- alternative assumptions about the engine and equipment market supply shifts

For all of these factors, the change in social cost was estimated to be very small, with a

maximum impact of less than one percent. These results are not surprising given the small share

of total production costs of diesel engines, equipment, and fuel affected by the rule. See Chapter

10 for a more detailed discussion.

Overall, we have limited means available to develop quantitative estimates of total

uncertainty in costs. Some of the factors identified above can act to either increase or decrease

actual cost compared to our estimates. Some, such as new technology developments and new

production techniques, will act to lower costs compared to our estimates. 

One source of a useful information about the overall uncertainty we might expect to see in

cost is literature comparing historical rulemaking cost estimates with actual price increases when
Cost-Benefit Analysis

L

For this analysis, we based our cost estimates on information received from industry and technical reports

relevant to the US market. We are also aware of two studies done to support nonroad standards development in

Europe, namely the VTT report and the EMA/Euromot report (Euromot 2002, Docket A-2001-28 Document number

II-B-12). We are not utilizing the cost information in these reports because neither one has sufficient information to

allow us to understand or derive the relevant cost figures and therefore provide us insufficient information that could

be used in trying to estimate cost uncertainty for nonroad diesel engine technologies. 

9-59

new standards went into effect.L Perhaps the most relevant of such studies is the paper by

Anderson and Sherwood analyzing these effects for those mobile source rules adopted since the

Clean Air Act Amendments of 1990. That paper reviewed six fuel quality rules and ten lightduty vehicle control rules that had been required by those amendments. It found that EPA

estimates of the costs for future standards tended to be similar to or higher than actual price

changes observed in the market place. Table 9-21 presents the results for some of the fuel and

vehicle rules reviewed in the paper.

Table 9-21.

Comparison of Historical EPA Cost Estimates with Actual Price Changes

EPA Rule

EPA Mid-point

Estimate

Actual Price

Change

Percent Difference

for Price vs EPA

Phase 2 RVP control 1.1 c/gal 0.5 c/gal -54%

Reformulated

Gasoline Phase 1

4.1 c/gal 2.2 c/gal -46%

Reformulated

Gasoline Phase 2

5.7 c/gal 5.1 c/gal -10%

500ppm Sulfur

Highway Diesel Fuel

2.2 c/gal 2.2 c/gal 0%

1994-2001 LDV

Regulations

$446/vehicle $347 -22%

The data in Table 9-21 would lead us to believe that cost uncertainty is largely a risk of

overestimation by EPA. However, given the uncertainty in estimating costs, we believe it is

appropriate to consider the potential for both overestimation and underestimation. As a

sensitivity factor for social cost variability we have chosen to evaluate a range of possible errors

in social cost of from twenty percent higher to twenty percent lower than the EPA estimate. The

resulting social cost range is shown in Table 9 -22. This uncertainty has virtually no impact on
Final Regulatory Impact Analysis

9-60

our estimates of the net benefits of the final rule, given the large magnitude by which benefits

exceed costs.

Table 9-22.

Estimated Uncertainty for Cost of Final Full Program

Year Engineering Cost

Estimate

Uncertainty Range (-20 to +20 percent)

2010 $0.30 billion $0.24 - $0.36 billion

2020 $1.8 billion $1.5 - $2.2 billion

2030 $2.1 billion $1.7 - $2.6 billion

Turning to the question of emissions uncertainty, the Agency does not at this time have

useful quantitative information to bring to bear on this question. For our estimates, we rely on

the best information that is available to us. However, there is uncertainty involved in many

aspects of emissions estimations. Uncertainty exists in the estimates of emissions from the

nonroad sources affected by this final rule, as well as in the universe of other sources included in

the emission inventories used for our air quality modeling. To the extent that these other sources

are unchanged between our baseline and control case, the impact of uncertainty in those

estimates is lessened. Similarly, since the key driver of the benefits of our final rule is the

changes produced by the new standards, the effect of uncertainty in the overall estimates of

nonroad emissions on our benefits estimates may be lessened.

As discussed in Chapter 3 and our summary and analysis of comments, the main sources of

uncertainty in our estimates of nonroad emissions fall in the three areas of population size

estimates, equipment usage rates (activity) and engine emission factors. Since nonroad

equipment is not subject to state registration and licensing requirements like those applying to

highway vehicles, it is difficult to develop precise equipment counts for in-use nonroad

equipment. Our modeled equipment populations are derived from related data about sales and

scrappage rates. Similarly, annual amount of usage and related load factor information is

estimated with some degree of uncertainty. We have access to extensive bodies of data on these

areas, but are also aware of the need for improvement. Finally, the emission rates of engines in

actual field operation cannot readily be measured at the present time, but are estimated from

laboratory testing under a variety of typical operating cycles. While laboratory estimates are a

reliable source of emissions data, they cannot fully capture all of the impacts of real in-use

operation on emissions, leading to some uncertainty about the results. For further details on our
Cost-Benefit Analysis

9-61

modeling of nonroad emissions, please refer to the discussions in Chapters 3 and Appendix 8A

of this RIA.

We have ongoing efforts in all three of these areas designed to improve their accuracy. Since

the opportunity to gather better data exists, we have chosen to focus our main efforts on

developing improved estimates rather than on developing elaborate techniques to estimate the

uncertainty of current estimates. In the long run, better estimates are the most desired outcome. 

One of the most important new tools we are developing is the use of portable emission

measurement devices to gather detailed data on actual engines and equipment in daily use. 

These devices have recently become practical due to advances in computing and sensor

technology, and will allow us to generate intensive data defining both activity-related factors

(e.g., hours of use, load factors, patterns of use) and in-use emissions data specific to the

measured activity and including effects from such things as age and emissions related

deterioration. The Agency is pursuing this equipment for improving both its highway and

nonroad engine emissions models. Because of the multiplicity of factors involved, we cannot

make a quantitative estimate of the uncertainty in our emissions estimates. 
Final Regulatory Impact Analysis

9-62

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Zanobetti, A., J. Schwartz, E. Samoli, A. Gryparis, G. Touloumi, R. Atkinson, A. Le Tertre, J.

Bobros, M. Celko, A. Goren, B. Forsberg, P. Michelozzi, D. Rabczenko, E. Aranguez Ruiz

and K. Katsouyanni. 2002. The temporal pattern of mortality responses to air pollution: a

multicity assessment of mortality displacement. Epidemiology. Vol. 13(1): 87-93.
Cost-Benefit Analysis

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APPENDIX 9A: Benefits Analysis of Modeled Preliminary Control Option

9A.1 Summary of Emissions Inventories and Modeled Changes in Emissions from Nonroad Engines 9-89

9A.2 Air Quality Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-92

9A.2.1 PM Air Quality Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-93

9A.2.1.1 Modeling Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-95

9A.2.1.2 Simulation Periods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-95

9A.2.1.3 Model Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-98

9A.2.1.4 Converting REMSAD Outputs to Benefits Inputs . . . . . . . . . . . . . . . . . . . . . . . . 9-98

9A.2.1.5 PM Air Quality Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-99

9A.2.2 Ozone Air Quality Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-102

9A.2.2.1 Modeling Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-103

9A.2.2.2 Simulation Periods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-106

9A.2.2.3 Converting CAMx Outputs to Full-Season Profiles for Benefits Analysis . . . . 9-106

9A.2.2.4 Ozone Air Quality Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-107

9A.2.3 Visibility Degradation Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-111

9A.2.3.1 Residential Visibility Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-113

9A.2.3.2 Recreational Visibility Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-114

9A.3 Benefit Analysis- Data and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-116

9A.3.1 Valuation Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-118

9A.3.2 Growth in WTP Reflecting National Income Growth Over Time . . . . . . . . . . . . . . . 9-120

9A.3.3 Methods for Describing Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-123

9A.3.4 Demographic Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-128

9A.3.5 Health Benefits Assessment Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-129

9A.3.5.1 Selecting Health Endpoints and Epidemiological Effect Estimates . . . . . . . . . . . . . 9-131

9A.3.5.2 Uncertainties Associated with Health Impact Functions . . . . . . . . . . . . . . . . . . . . . 9-147

9A.3.5.3 Baseline Health Effect Incidence Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-151

9A.3.6 Human Welfare Impact Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-173

9A.3.6.1 Visibility Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-173

9A.3.6.2 Agricultural, Forestry and other Vegetation Related Benefits . . . . . . . . . . . . . 9-176

9A.3.6.2.1 Agricultural Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-177

9A.3.6.2.2 Forestry Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-178

9A.3.6.2.3 Other Vegetation Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-178

9A.3.6.3 Benefits from Reductions in Materials Damage and Odor . . . . . . . . . . . . . . . . 9-179

9A.3.6.4 Benefits from Reduced Ecosystem Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-180

9A.4 Benefits Analysis—Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-181
Final Regulatory Impact Analysis

AShort-term exposure to ambient ozone has also been linked to premature death. The EPA is currently

evaluating the epidemiological literature examining the relationship between ozone and premature mortality,

sponsoring three independent meta-analyses of the literature. Once this evaluation has been completed and peerreviewed, the EPA will consider including ozone-related premature mortality in the primary benefits analysis for

future rules.

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This appendix details the models and methods used to generate the benefits estimates from

which the benefits of the final standards presented in Chapter IX are derived. This analysis uses

a methodology generally consistent with benefits analyses performed for the recent analysis of

the Heavy Duty Engines/Diesel Fuel rulemaking (U.S. EPA, 2000a) and the proposed Interstate

Air Quality Rule (U.S. EPA, 2004). The benefits analysis relies on three major modeling

components:

1) Calculation of the impact that a set of preliminary fuel and engine standards would have

on the nationwide inventories for NOx, non-methane hydrocarbons (NMHC), SO2, and

PM emissions in 2020 and 2030;

2) Air quality modeling for 2020 and 2030 to determine changes in ambient concentrations

of ozone and particulate matter, reflecting baseline and post-control emissions

inventories.

3) A benefits analysis to determine the changes in human health and welfare, both in terms

of physical effects and monetary value, that result from the projected changes in ambient

concentrations of various pollutants for the modeled standards.

Potential human health effects linked to PM2.5 range from premature mortality linked to longterm exposure to PM, to a range of morbidity effects linked to long-term (chronic) and shorterterm (acute) exposures (e.g., respiratory and cardiovascular symptoms resulting in hospital

admissions, asthma exacerbations, and acute and chronic bronchitis). Exposure to ozone has

also been linked to a variety of respiratory effects including hospital admissions and illnesses

resulting in school absences.a

 Welfare effects potentially linked to PM include materials damage

and visibility impacts, while ozone can adversely affect the agricultural and forestry sectors by

decreasing yields of crops and forests. Although methods exist for quantifying the benefits

associated with many of these human health and welfare categories, not all can be evaluated at

this time due to limitations in methods and/or data. Table 4-1 lists the full complement of human

health and welfare effects associated with PM and ozone and identifies those effects that are

quantified for the primary estimate, are quantified as part of the sensitivity analysis (to be

completed for the supplemental analysis), and remain unquantified because of to current

limitations in methods or available data. 
Cost-Benefit Analysis

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Figure 9A.1 illustrates the major steps in the analysis. Given baseline and post-control

emissions inventories for the emission species expected to impact ambient air quality, we use

sophisticated photochemical air quality models to estimate baseline and post-control ambient

concentrations of ozone and PM, and deposition of nitrogen and sulfur for each year. The

estimated changes in ambient concentrations are then combined with monitoring data to estimate

population level exposures to changes in ambient concentrations for use in estimating health

effects. Modeled changes in ambient data are also used to estimate changes in visibility, and

changes in other air quality statistics that are necessary to estimate welfare effects. Changes in

population exposure to ambient air pollution are then input to concentration-response functions

to generate changes in incidence of health effects, or, changes in other exposure metrics are input

to dose-response functions to generate changes in welfare effects. The resulting effects changes

are then assigned monetary values, taking into account adjustments to values for growth in real

income out to the year of analysis (values for health and welfare effects are in general positively

related to real income levels). Finally, values for individual health and welfare effects are

summed to obtain an estimate of the total monetary value of the changes in emissions.

On September 26, 2002, the National Academy of Sciences (NAS) released a report on its

review of the Agency’s methodology for analyzing the health benefits of measures taken to

reduce air pollution. The report focused on the EPA’s approach for estimating the health

benefits of regulations designed to reduce concentrations of airborne PM.

In its report, the NAS said that the EPA has generally used a reasonable framework for

analyzing the health benefits of PM-control measures. It recommended, however, that the

Agency take a number of steps to improve its benefits analysis. In particular, the NAS stated

that the Agency should

C include benefits estimates for a range of regulatory options; 

C estimate benefits for intervals, such as every 5 years, rather than a single year;

C clearly state the projected baseline statistics used in estimating health benefits,

including those for air emissions, air quality, and health outcomes;

C examine whether implementation of regulations might cause unintended impacts on

human health or the environment;

C when appropriate, use data from non-U.S. studies to broaden age ranges to which

current estimates apply and to include more types of relevant health outcomes; and

C begin to move the assessment of uncertainties from its ancillary analyses into its base

analyses by conducting probabilistic, multiple-source uncertainty analyses. This

assessment should be based on available data and expert judgment.
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Although the NAS made a number of recommendations for improvement in the EPA’s

approach, it found that the studies selected by the Agency for use in its benefits analysis were

generally reasonable choices. In particular, the NAS agreed with the EPA’s decision to use

cohort studies to derive benefits estimates. It also concluded that the Agency’s selection of the

American Cancer Society (ACS) study for the evaluation of PM-related premature mortality was

reasonable, although it noted the publication of new cohort studies that the Agency should

evaluate. Since the publication of the NAS report, the EPA has reviewed new cohort studies,

including reanalyses of the ACS study data and has carefully considered these new study data in

developing the analytical approach for the final rule (see below).

In addition to the NAS report, the EPA has also received technical guidance and input

regarding its methodology for conducting PM- and ozone-related benefits analysis from two

additional sources, including the Health Effects Subgroup (HES) of the SAB Council reviewing

the 812 blueprint (SAB-HES, 2003) and the Office of Management and Budget (OMB) through

ongoing discussions regarding methods used in conducting regulatory impact analyses (RIAs)

(e.g., see OMB Circular A-4). The SAB HES recommendations include the following (SABHES, 2003):

C use of the updated ACS Pope et al. (2002) study rather than the ACS Krewski et al.

study to estimate premature mortality for the primary analysis;

C dropping the alternative estimate used in the proposal RIA and instead including a

primary estimate that incorporates consideration of uncertainly in key effects

categories such as premature mortality directly into the estimates (e.g., use of the

standard errors from the Pope et al. [2002] study in deriving confidence bounds for

the adult mortality estimates);

C addition of infant mortality (children under the age of one) into the primary estimate,

based on supporting evidence from the World Health Organization Global Burden of

Disease study and other published studies that strengthen the evidence for a

relationship between PM exposure and respiratory inflamation and infection in

children leading to death; 

C inclusion of asthma exacerbations for children in the primary estimate;

C expansion of the age groups evaluated for a range of morbidity effects beyond the

narrow band of the studies to the broader (total) age group (e.g., expanding a study

population for 7 to 11 year olds to cover the entire child age range of 6 to 18 years). 

C inclusion of new endpoints (school absences [ozone], nonfatal heart attacks in adults

[PM], hospital admissions for children under two [ozone]), and suggestion of a new
Cost-Benefit Analysis

B

Note that the SAB-HES comments were made in the context of a review of the methods for the Section 812

analysis of the costs and benefits of the Clean Air Act. This context is pertinent to our interpretation of the SABHES comments on the selection of effect estimates for hospital admissions associated with PM (SAB-HES, 2003). 

The Section 812 analysis is focused on a broad set of air quality changes, including both the coarse and fine fractions

of PM10. As such, impact functions that focus on the full impact of PM10 are appropriate. However, for the Nonroad

Diesel Engines rule, which is expected to affect primarily the fine fraction (PM2.5) of PM10, impact functions that

focus primarily on PM2.5 are more appropriate.

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meta-analysis of hospital admissions (PM10) rather than using a few PM2.5 studies;b

and

C updating of populations and baseline incidences.

Recommendations from OMB regarding RIA methods have focused on the approach used to

characterize uncertainty in the benefits estimates generated for RIAs, as well as the approach

used to value premature mortality estimates. The EPA is currently in the process of developing a

comprehensive integrated strategy for characterizing the impact of uncertainty in key elements of

the benefits modeling process (e.g., emissions modeling, air quality modeling, health effects

incidence estimation, valuation) on the results that are generated. 

We are also altering the value of a statistical life (VSL) used in the analysis to reflect new

information in the ongoing academic debate over the appropriate characterization of the value of

reducing the risk of premature mortality. In previous analyses, we used a distribution of VSL

based on 26 VSL estimates from the economics literature. For this analysis, we are

characterizing the VSL distribution in a more general fashion, based on two recent meta-analyses

of the wage-risk-based VSL literature. The new distribution is assumed to be normal, with a

mean of $5.5 million and a 95 percent confidence interval between $1 and $10 million. The

EPA welcomes public comment on the appropriate methodology for valuing reductions in the

risk of premature death.

The EPA has addressed the comments received from the public, the NAS, the SAB-HES, and

OMB in developing the analytical approach for the final rule. We have also reflected advances in

data and methods in air quality modeling, epidemiology, and economics that have occurred since

the proposal analysis. Updates to the assumptions and methods used in estimating PM2.5-related

and ozone-related benefits since completion of the Proposed Nonroad Diesel Rule include the

following:

Health Endpoints

C The primary analysis incorporates updated impact functions to reflect updated timeseries studies of hospital admissions to correct for errors in application of the
Final Regulatory Impact Analysis

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generalized additive model (GAM) functions in S-plus. More information on this

issue is available at http://www.healtheffects.org.

C The primary analysis uses an all cause mortality effect estimate based on the Pope et

al. (2002) reanalysis of the ACS study data. In addition, we provide a breakout for

two major cause of death categories—cardiopulmonary and lung cancer.

C Infant mortality is included in the primary analysis (infants age 0-1 years).

C Asthma exacerbations are incorporated into the primary analysis. Although the

analysis of the proposed rule included asthma exacerbations as a separate endpoint

outside of the base case analysis, for the final rule, we will include asthma

exacerbations in children 6 to 18 years of age as part of the primary analysis. 

Valuation

C In generating the monetized benefits for premature mortality in the primary analysis,

the VSL is entered as a mean (best estimate) of 5.5 million. Unlike the analysis of the

proposed rule, the analysis of the final rule does not include a value of statistical life

year (VSLY) estimate.

The analysis of the proposed rule included an alternative estimate in addition to the primary

estimate that was intended to evaluate the impact of several key assumptions on the estimated

reductions in premature premature mortality and chronic bronchitis. However, reflecting

comments from the public, the SAB-HES as well as the NAS panel, rather than including an

alternative estimate in the analysis, the EPA will investigate the impact of key assumptions on

mortality and morbidity estimates through a series of sensitivity analyses.

The benefits estimates generated for the final Nonroad Diesel Engine rule are subject to a

number of assumptions and uncertainties, which are discussed throughout the document. For

example, key assumptions underlying the primary estimate for the premature mortality category

include the following:

(1) Inhalation of fine particles is causally associated with premature death at concentrations

near those experienced by most Americans on a daily basis. Although biological

mechanisms for this effect have not yet been definitively established, the weight of the

available epidemiological evidence supports an assumption of causality. 

(2) All fine particles, regardless of their chemical composition, are equally potent in causing

premature mortality. This is an important assumption, because PM produced via

transported precursors emitted from EGUs may differ significantly from direct PM

released from diesel engines and other industrial sources, but no clear scientific grounds

exist for supporting differential effects estimates by particle type. 
Cost-Benefit Analysis

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(3) The impact function for fine particles is approximately linear within the range of ambient

concentrations under consideration. Thus, the estimates include health benefits from

reducing fine particles in areas with varied concentrations of PM, including both regions

that are in attainment with fine particle standard and those that do not meet the standard. 

(4) The forecasts for future emissions and associated air quality modeling are valid. 

Although recognizing the difficulties, assumptions, and inherent uncertainties in the

overall enterprise, these analyses are based on peer-reviewed scientific literature and

up-to-date assessment tools, and we believe the results are highly useful in assessing this

rule.

In addition to the quantified and monetized benefits summarized above, a number of

additional categories are not currently amenable to quantification or valuation. These include 

reduced acid and particulate deposition damage to cultural monuments and other materials,

reduced odor, reduced ozone effects on forested ecosystems, and environmental benefits due to

reductions of impacts of acidification in lakes and streams and eutrophication in coastal areas. 

Additionally, we have not quantified a number of known or suspected health effects linked with

PM and ozone for which appropriate health impact functions are not available or which do not

provide easily interpretable outcomes (i.e., changes in forced expiratory volume [FEV1]). As a

result, monetized benefits generated for the primary estimate may underestimate the total

benefits attributable to the final regulatory option. 

Benefits estimates for the final Nonroad Diesel Engines rule were generated using BenMAP,

which is a computer program developed by the EPA that integrates a number of the modeling

elements used in previous RIAs (e.g., interpolation functions, population projections, health

impact functions, valuation functions, analysis and pooling methods) to translate modeled air

concentration estimates into health effects incidence estimates and monetized benefits estimates. 

BenMAP provides estimates of both the mean impacts and the distribution of impacts.

In general, the chapter is organized around the steps illustrated in Figure 9A.1. In section A,

we describe and summarize the emissions inventories and modeled reductions in emissions of

NOx, VOC, SO2, and directly emitted diesel PM for the set of preliminary control options. In

section B, we describe and summarize the air quality models and results, including both baseline

and post-control conditions, and discuss the way modeled air quality changes are used in the

benefits analysis. In Section C, we provide and overview of the data and methods that are used

to quantify and value health and welfare endpoints, and provide a discussion of how we

incorporate uncertainty into our analysis. In Section D, we report the results of the analysis for

human health and welfare effects. Additional sensitivity analyses are provided in Appendix 9B

and 9C.
Final Regulatory Impact Analysis

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Table 9A.1. Summary of Results: Estimated Benefits 

of the Modeled Preliminary Control Option

Discount Rate Total BenefitsA, B

(Billions 2000$)

2020 2030

3% discount rate

7% discount rate

$52+B

$49+B

$92+B

$87+B

A Benefits of CO and HAP emission reductions are not quantified in this analysis and, therefore, are not presented in

this table. The quantifiable benefits are from emission reductions of NOX, NMHC, SO2 and PM only. For

notational purposes, unquantified benefits are indicated with a “B” to represent the sum of additional monetary

benefits and disbenefits. A detailed listing of unquantified health and welfare effects is provided in Table 9A-2. B

 Results reflect the use of 3% and 7% discount rates consistent with EPA and OMB’s guidelines for preparing economic

analyses (US EPA, 2000c, OMB Circular A-4). Results are rounded to two significant digits. 
Cost-Benefit Analysis

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Estimate Expected

Changes in Human

Health Outcomes

(BenMAP)

Model baseline and postcontrol ambient air quality

(REMSAD, CAM-X)

Air Quality

Monitor Data

(AIRS)

Model Population Exposure

to Changes in Ambient

Concentrations

(BenMAP)

ConcentrationResponse Functions

Estimate Expected

Changes inWelfare

Effects

Dose-response

Functions

Valuation Functions

GDP Projections

Adjust Monetary Values for Growth in Real

Income to Year of Analysis

Valuation Functions

Sector Models

(AGSIM)

Population and

Demographic Data

Incidence and

Prevalence Rates

Estimate Monetary

Value of Changes in

Welfare Effects

Estimate Monetary

Value of Changes

in Human Health

Outcomes

(BenMAP)

Income Elasticities

Sum Health and Welfare Monetary Values to

Obtain Total Monetary Benefits

Figure 9A.1. Key Steps in Air Quality Modeling Based Benefits Analysis

INPUTS PROCESSES INPUTS

Emission Inventories

(1996 NET, Mobile

5b, NONROAD)
Table 9A.2. 

Human Health and Welfare Effects of Pollutants Affected by the Final Nonroad Diesel Engin

Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or Monetized Effects

in Sensitivity Analyses

 Unquantified Ef

PM/Health Premature mortality in adults – long

term exposures 

Infant mortalityBronchitis - chronic and acuteHospital admissions - respiratory

and cardiovascular

Emergency room visits for asthmaNon-fatal heart attacks (myocardial

infarction)

Asthma exacerbationsLower and upper respiratory illnessMinor restricted activity daysWork loss days

Low birth weightChanges in pulmonary functionChronic respiratory diseases other than Morphological changesAltered host defense mechanismsCancerNon-asthma respiratory emergency rooChanges in cardiac function (e.g. heart Allergic responses (to diesel exhaust)

PM/Welfare Visibility in California,

Southwestern, and SoutheasternClass I areas

Visibility in Northeastern,

Northwestern, and MidwesternClass I areas

Visibility in residential and nonClass I areasHousehold soiling
Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or Monetized Effects

in Sensitivity Analyses

 Unquantified Ef

Ozone/Health Increased airway responsiveness to stim

Inflammation in the lungChronic respiratory damagePremature aging of the lungsAcute inflammation and respiratory ceIncreased susceptibility to respiratory iNon-asthma respiratory emergency rooHospital admissions - respiratory Emergency room visits for asthmaMinor restricted activity daysSchool loss daysChronic Asthmaa

Asthma attacksCardiovascular emergency room visitsPremature mortality – acute exposures

Acute respiratory symptoms

Ozone/Welfare Decreased commercial forest productiv

Decreased yields for fruits and vegetabDecreased yields for commercial and nDamage to urban ornamental plantsImpacts on recreational demand from dDamage to ecosystem functions Decreased outdoor worker productivity

Nitrogen andSulfateDeposition/Welfare

Costs of nitrogen controls to reduce

eutrophication in selectedeastern estuaries

Impacts of acidic sulfate and nitrate de

forests

Impacts of acidic deposition on commeImpacts of acidic deposition on recreat

ecosystems

Impacts of nitrogen deposition on com

agriculture, and forests

Impacts of nitrogen deposition on recre

ecosystems

Reduced existence values for currently 
Pollutant/Effect Quantified and Monetized Effects in

Primary Analysis

Quantified and/or Monetized Effects

in Sensitivity Analyses

 Unquantified Ef

SO2/Health Hospital admissions for respiratory and 

Respiratory symptoms in asthmatics

NOx/Health Lung irritation

Lowered resistance to respiratory infecHospital Admissions for respiratory an

CO/Health Premature mortality

Behavioral effectsHospital admissions - respiratory, cardOther cardiovascular effectsDevelopmental effectsDecreased time to onset of angina

NMHCs c

Health

Cancer (diesel PM, benzene, 1,3-butad

acetaldehyde)

Anemia (benzene)Disruption of production of blood comReduction in the number of blood plateExcessive bone marrow formation (benDepression of lymphocyte counts (benReproductive and developmental effecIrritation of eyes and mucous membranRespiratory and respiratory tractAsthma attacks in asthmatics (formaldAsthma-like symptoms in non-asthmatIrritation of the eyes, skin, and respiratUpper respiratory tract irritation & con

NMHCs cWelfare

Direct toxic effects to animalsBioaccumlation in the food chainReduced odors

a While no causal mechanism has been identified linking new incidences of chronic asthma to ozone exposure, two epidemiological studies sh

association between long-term exposure to ozone and incidences of chronic asthma in exercising children and some non-smoking men (McCet al., 1999).

b Premature mortality associated with ozone is not separately included in the calculation of total monetized benefits.c All non-methane hydrocarbons (NMHCs) listed in the table are also hazardous air pollutants listed in Section 112(b) of the Clean Air Act.
Cost-Benefit Analysis

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9A.1 Summary of Emissions Inventories and Modeled Changes in Emissions

from Nonroad Engines

For the preliminary control options we modeled, implementation will occur in two ways:

reduction in sulfur content of nonroad diesel fuel and adoption of controls on new engines. 

Because full turnover of the fleet of nonroad diesel engines will not occur for many years, the

emission reduction benefits of the final standards will not be fully realized until decades after the

initial reduction in fuel sulfur content. Based on the projected time paths for emissions

reductions, EPA chose to focus detailed emissions and air quality modeling on two future years,

2020 and 2030, which reflect partial and close to complete turnover of the fleet of nonroad diesel

engines to models meeting the preliminary control options. Tables 9A-3 and 9A-4 summarize

the baseline emissions of NOX, SO2, VOC, and direct diesel PM2.5 and the change in the

emissions from nonroad engines used in modeling air quality changes.

Emissions and air quality modeling decisions are made early in the analytical process. Since

the preliminary control scenario was developed, EPA has gathered more information and

received public comment regarding the technical feasibility of the standards, and EPA has

revised the control scenario accordingly. Section 3.6 of the RIA describes the changes in the

inputs and resulting emission inventories between the preliminary baseline and control scenarios

used for the air quality modeling and the baseline and control scenarios.

Chapter 3 discussed the development of the 1996, 2020 and 2030 baseline emissions

inventories for the nonroad sector and for the sectors not affected by this rule. The emission

sources and the basis for current and future-year inventories are listed in Table 9A-5. 
Final Regulatory Impact Analysis

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Table 9A-3 

Summary of Baseline Emissions for Preliminary Nonroad Engine Control Options

Pollutant Emissions (tons)

Source NOX SO2 VOC PM2.5

1996 Baseline

Nonroad Engines 1,583,641 172,175 221,398 178,500

All Other Sources 22,974,945 18,251,679 18,377,795 2,038,726

Total, All Sources 24,558,586 18,423,854 18,599,193 2,217,226

2020 Base Case

Nonroad Engines 1,144,686 308,075 97,113 127,755

All Other Sources 14,394,399 14,882,962 13,812,619 1,940,307

Total, All Sources 15,539,085 15,191,037 13,909,732 2,068,062

2030 Base Case

Nonroad Engines 1,231,981 360,933 97,345 143,185

All Other Sources 14,316,841 15,190,439 15,310,670 2,066,918

Total, All Sources 15,548,822 15,551,372 15,408,015 2,210,103
Cost-Benefit Analysis

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Table 9A-4 

Summary of Emissions Changes for the Preliminary Nonroad Control Options*

Pollutant

Item NOX SO2 VOC PM2.5

2020 Nationwide Emission Changes

Absolute Tons 663,618 304,735 23,172 91,278

Percent Reduction from Landbased

Nonroad Emissions

58.0% 98.9% 23.9% 71.4%

Percentage Reduction from All

Manmade Sources

4.5% 2.1% 0.2% 4.6%

2030 Emission Changes

Absolute Tons 1,009,744 359,774 34,060 129,073

Percent Reduction from Landbased

Nonroad Emissions

82.0% 99.7% 35.0% 90.0%

Percentage Reduction from All

Manmade Sources

6.3% 2.1% 0.2% 5.5%

* Does not include SO2 and PM2.5 reductions from recreational marine diesel engines, commercial marine diesel

engines, and locomotives due to control of diesel fuel sulfur levels.
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Table 9A-5 

Emissions Sources and Basis for Current and Future-Year Inventories

Emissions Source 1996 Base year Future-year Base Case Projections

Utilities 1996 NEI Version 3.12

(CEM data)

Integrated Planning Model (IPM)

Non-Utility Point and Area

sources

1996 NEI 

Version 3.12 (point)

Version 3.11 (area)

BEA growth projections

Highway vehicles MOBILE5b model with

MOBILE6 adjustment

factors for VOC and

NOX;

PART5 model for PM 

VMT projection data

Nonroad engines (except

locomotives, commercial

marine vessels, and

aircraft)

NONROAD2002 model BEA and Nonroad equipment

growth projections

Note: Full description of data, models, and methods applied for emissions inventory development and modeling are

provided in Emissions Inventory TSD (EPA, 2003a).

9A.2 Air Quality Impacts

This section summarizes the methods for and results of estimating air quality for the 2020

and 2030 base cases and control scenarios for the purposes of benefit-cost analyses. EPA has

focused on the health, welfare, and ecological effects that have been linked to air quality

changes. These air quality changes include the following:

S Ambient particulate matter (PM10 and PM2.5)–as estimated using a national-scale version

of the REgional Modeling System for Aerosols and Deposition (REMSAD); 

S Ambient ozone–as estimated using regional-scale applications of the Comprehensive Air

Quality Model with Extensions (CAMx); and

S Visibility degradation (i.e., regional haze), as developed using empirical estimates of

light extinction coefficients and efficiencies in combination with REMSAD modeled

reductions in pollutant concentrations.
Cost-Benefit Analysis

C Given the potential impact of the Nonroad Engine/Diesel Fuel rule on secondarily formed particles it is

important to employ a Eulerian model such as REMSAD. The impact of secondarily formed pollutants typically

involves primary precursor emissions from a multitude of widely dispersed sources, and chemical and physical

processes of pollutants that are best addressed using an air quality model that employs an Eulerian grid model

design.

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Although we expect reductions in airborne sulfur and nitrogen deposition, these air quality

impacts have not been quantified for this rule nor have the associated benefits been estimated. 

The air quality estimates in this section are based on the emission changes for the modeled

preliminary control program discussed in Chapter 3. These air quality results are in turn

associated with human populations and ecosystems to estimate changes in health and welfare

effects. In Section B-1, we describe the estimation of PM air quality using REMSAD, and in

Section B-2, we cover the estimation of ozone air quality using CAMx. Lastly, in Section B-3,

we discuss the estimation of visibility degradation.

9A.2.1 PM Air Quality Estimates

We use the emissions inputs summarized above with a national-scale version of the REgional

Model System for Aerosols and Deposition (REMSAD) to estimate PM air quality in the

contiguous U.S. REMSAD is a three-dimensional grid-based Eulerian air quality model

designed to estimate annual particulate concentrations and deposition over large spatial scales

(e.g., over the contiguous U.S.). Consideration of the different processes that affect primary

(directly emitted) and secondary (formed by atmospheric processes) PM at the regional scale in

different locations is fundamental to understanding and assessing the effects of pollution control

measures that affect ozone, PM and deposition of pollutants to the surface.c

 Because it accounts

for spatial and temporal variations as well as differences in the reactivity of emissions,

REMSAD is useful for evaluating the impacts of the rule on U.S. PM concentrations. 

REMSAD was peer-reviewed in 1999 for EPA as reported in “Scientific Peer-Review of the

Regulatory Modeling System for Aerosols and Deposition” (Seigneur et al., 1999). Earlier

versions of REMSAD have been employed for the EPA’s Prospective 812 Report to Congress,

EPA’s HD Engine/Diesel Fuel rule, and EPA’s air quality assessment of the Clear Skies

Initiative. Version 7 of REMSAD was employed for this analysis and is fully described in the

air quality modeling technical support document (US EPA, 2003b). This version reflects

updates in the following areas to improve performance and address comments from the 1999

peer-review:

S Gas phase chemistry updates to “micro-CB4" mechanism including new treatment for the

NO3 and N2O5 species and the addition of several reactions to better account for the
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wide ranges in temperature, pressure, and concentrations that are encountered for

regional and national applications.

S PM chemistry updates to calculate particulate nitrate concentrations through use of the

MARS-A equilibrium algorithm and internal calculation of secondary organic aerosols

from both biogenic (terpene) and anthropogenic (estimated aromatic) VOC emissions.

S Aqueous phase chemistry updates to incorporate the oxidation of SO2 by O3 and O2 and

to include the cloud and rain liquid water content from MM5 meteorological data directly

in sulfate production and deposition calculations.

As discussed earlier in Chapter 2, the model tends to underestimate observed PM2.5

concentrations nationwide, especially over the western U.S. 

Our analysis applies the modeling system to the entire U.S. for the five emissions scenarios:

a 1996 baseline projection, a 2020 baseline projection and a 2020 projection with nonroad

controls, a 2030 baseline projection and a 2030 projection with nonroad controls. As discussed

in the Benefits Analysis TSD, we use the relative predictions from the model by combining the

1996 base-year and each future-year scenario with ambient air quality observations to determine

the expected change in 2020 or 2030 ozone concentrations due to the rule (Abt Associates,

2003). These results are used solely in the benefits analysis.

REMSAD simulates every hour of every day of the year and, thus, requires a variety of input

files that contain information pertaining to the modeling domain and simulation period. These

include gridded, 1-hour average emissions estimates and meteorological fields, initial and

boundary conditions, and land-use information. As applied to the contiguous U.S., the model

segments the area within the region into square blocks called grids (roughly equal in size to

counties), each of which has several layers of air conditions. Using this data, REMSAD

generates predictions of 1-hour average PM concentrations for every grid. We then calibrate the

modeling results to develop 2020 and 2030 PM estimates at monitor sites by normalizing the

observations to the observed 1996 concentrations at each monitor site. For areas (grids) without

PM monitoring data, we interpolated concentration values using data from monitors surrounding

the area. After completing this process, we then calculated daily and seasonal PM air quality

metrics as inputs to the health and welfare C-R functions of the benefits analysis. The following

sections provide a more detailed discussion of each of the steps in this evaluation and a summary

of the results.
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9A.2.1.1 Modeling Domain

 The PM air quality analyses employed the modeling domain used previously in support of

Clear Skies air quality assessment. As shown in Figure 9A-2, the modeling domain

encompasses the lower 48 States and extends from 126 degrees to 66 degrees west longitude and

from 24 degrees north latitude to 52 degrees north latitude. The model contains horizontal gridcells across the model domain of roughly 36 km by 36 km. There are 12 vertical layers of

atmospheric conditions with the top of the modeling domain at 16,200 meters. The 36 by 36 km

horizontal grid results in a 120 by 84 grid (or 10,080 grid-cells) for each vertical layer. Figure

9A-3 illustrates the horizontal grid-cells for Maryland and surrounding areas. 

9A.2.1.2 Simulation Periods

For use in this benefits analysis, the simulation periods modeled by REMSAD included

separate full-year application for each of the five emissions scenarios as described in Chapter 3,

i.e., 1996 baseline and the 2020 and 2030 base cases and control scenarios. 
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Figure 9A-2

REMSAD Modeling Domain for Continental United States

Note: Gray markings define individual grid-cells in the REMSAD model.
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Figure 9A-3. Example of REMSAD 36 x 36km Grid-cells for Maryland Area
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9A.2.1.3 Model Inputs

REMSAD requires a variety of input files that contain information pertaining to the

modeling domain and simulation period. These include gridded, 1-hour average emissions

estimates and meteorological fields, initial and boundary conditions, and land-use information. 

Separate emissions inventories were prepared for the 1996 baseline and each of the future-year

base cases and control scenarios. All other inputs were specified for the 1996 baseline model

application and remained unchanged for each future-year modeling scenario.

Similar to CAMx, REMSAD requires detailed emissions inventories containing temporally

allocated emissions for each grid-cell in the modeling domain for each species being simulated. 

The previously described annual emission inventories were preprocessed into model-ready

inputs through the SMOKE emissions preprocessing system. Details of the preprocessing of

emissions through SMOKE as provided in the emissions modeling TSD. Meteorological inputs

reflecting 1996 conditions across the contiguous U.S. were derived from Version 5 of the

Mesoscale Model (MM5). These inputs included horizontal wind components (i.e., speed and

direction), temperature, moisture, vertical diffusion rates, and rainfall rates for each grid cell in

each vertical layer. Details of the annual 1996 MM5 modeling are provided in Olerud (2000).

Initial species concentrations and lateral boundary conditions were specified to approximate

background concentrations of the species; for the lateral boundaries the concentrations varied

(decreased parabolically) with height. These background concentrations are provided in the air

quality modeling TSD (U.S. EPA, 2003b). Land use information was obtained from the U.S.

Geological Survey database at 10 km resolution and aggregated to the ~36 KM horizontal

resolution used for this REMSAD application. 

9A.2.1.4 Converting REMSAD Outputs to Benefits Inputs

REMSAD generates predictions of hourly PM concentrations for every grid. The particulate

matter species modeled by REMSAD include a primary coarse fraction (corresponding to PM in

the 2.5 to 10 micron size range), a primary fine fraction (corresponding to PM less than 2.5

microns in diameter), and several secondary particles (e.g., sulfates, nitrates, and organics). 

PM2.5 is calculated as the sum of the primary fine fraction and all of the secondarily-formed

particles. These hourly predictions for each REMSAD grid-cell are aggregated to daily averages

and used in conjunction with observed PM concentrations from AIRS to generate the predicted

changes in the daily and annual PM air quality metrics (i.e., annual mean PM concentration)

from the future-year base case to future-year control scenario as inputs to the health and welfare
Cost-Benefit Analysis

DBased on AIRS, there were 1,071 FRM PM monitors with valid data as defined as more than 11 observations

per season.

E

This approach is a generalization of planar interpolation that is technically referred to as enhanced Voronoi

Neighbor Averaging (EVNA) spatial interpolation (See Abt Associates (2003) for a more detailed description).

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C-R functions of the benefits analysis.d

 In addition, the speciated predictions from REMSAD are

employed as inputs to a post-processing module that estimates atmospheric visibility, as

discussed later in Section 9A.3.

In order to estimate PM-related health and welfare effects for the contiguous U.S., daily and

annual average PM concentrations are required for every location. Given available PM

monitoring data, we generated an annual profile for each location in the contiguous 48 States in

two steps: (1) we combine monitored observations and modeled PM predictions to interpolate

forecasted daily PM concentrations for each REMSAD grid-cell, and (2) we compute the daily

and annual PM measures of interest based on the annual PM profiles. e

 These methods are

described in detail in the benefits analysis technical support document (Abt Associates, 2003). 

9A.2.1.5 PM Air Quality Results

Table 9A-5 provides a summary of the predicted ambient PM2.5 concentrations for the 2020

and 2030 base cases and changes associated with Nonroad Engine/Diesel Fuel control scenarios. 

The REMSAD results indicate that the predicted change in PM concentrations is composed

almost entirely of reductions in fine particulates (PM2.5) with little or no reduction in coarse

particles (PM10 less PM2.5). Therefore, the observed changes in PM10 are composed primarily of

changes in PM2.5. In addition to the standard frequency statistics (e.g., minimum, maximum,

average, median), Table 9A-5 provides the population-weighted average which better reflects the

baseline levels and predicted changes for more populated areas of the nation. This measure,

therefore, will better reflect the potential benefits of these predicted changes through exposure

changes to these populations. As shown, the average annual mean concentrations of PM2.5

across all U.S. grid-cells declines by roughly 2.5 percent (or 0.2 μg/m3) and 3.4 percent (or 0.28

μg/m3) in 2020 and 2030, respectively. The population-weighted average mean concentration

declined by 3.3 percent (or 0.42 μg/m3

) in 2020 and 4.5 percent (or 0.59 μg/m3) in 2030, which

is much larger in absolute terms than the spatial average for both years. This indicates the rule

may generate greater absolute air quality improvements in more populated, urban areas.
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Table 9A-6. 

Summary of Base Case PM Air Quality 

and Changes Due to Preliminary Control Option for Nonroad Diesel Standards: 2020 and 2030

2020 2030

Statistic Base Case Changea

Percent

Change Base Case Changea

Percent

Change

PM2.5 (μg/m3

)

Minimum Annual Mean b 2.18 -0.02 -0.78% 2.33 -0.02 -1.01%

Maximum Annual Mean b 29.85 -1.36 -4.56% 32.85 -2.03 -6.18%

Average Annual Mean 8.10 -0.20 -2.49% 8.37 -0.28 -3.38%

Median Annual Mean 7.50 -0.18 -2.68% 7.71 -0.22 -2.80%

Pop-Weighted Average Annual Mean c 12.42 -0.42 -3.34% 13.07 -0.59 -4.48%

a

 The change is defined as the control case value minus the base case value.

b

 The base case minimum (maximum) is the value for the populated grid-cell with the lowest (highest) annual average. The

change relative to the base case is the observed change for the populated grid-cell with the lowest (highest) annual average in the

base case.

c

 Calculated by summing the product of the projected REMSAD grid-cell population and the estimated PM concentration, for that

grid-cell and then dividing by the total population in the 48 contiguous States.

Table 9A-6 provides information on the populations in 2020 and 2030 that will experience

improved PM air quality. There are significant populations that live in areas with meaningful

potential reductions in annual mean PM2.5 concentrations resulting from the rule. As shown,

almost 10 percent of the 2030 U.S. population are predicted to experience reductions of greater

than 1 μg/m3. This is an increase from the 2.7 percent of the U.S. population that are expected to

experience such reductions in 2020. Furthermore, just over 20 percent of the 2030 U.S.

population will benefit from reductions in annual mean PM2.5 concentrations of greater than 0.75

μg/m3 and slightly over 50 percent will live in areas with reductions of greater than 0.5 μg/m3. 

This information indicates how widespread the improvements in PM air quality are expected to

be and the large populations that will benefit from these improvements. 
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Table 9A-7

Distribution of PM2.5 Air Quality Improvements Over Population Due to Preliminary Control

Option for Nonroad Engine/Diesel Fuel Standards: 2020 and 2030

Change in Annual Mean PM2.5

Concentrations (μg/m3) 

2020 Population 2030 Population

Number (millions) Percent (%) Number (millions) Percent (%)

0 < ) PM2.5 Conc # 0.25 65.11 19.75% 28.60 8.04%

0.25 < ) PM2.5 Conc # 0.5 184.52 55.97% 147.09 41.33%

0.5 < ) PM2.5 Conc # 0.75 56.66 17.19% 107.47 30.20%

0.75 < ) PM2.5 Conc # 1.0 14.60 4.43% 38.50 10.82%

1.0 < ) PM2.5 Conc # 1.25 5.29 1.60% 88.22 2.48%

1.25 < ) PM2.5 Conc # 1.5 3.51 1.06% 15.52 4.36%

1.5 < ) PM2.5 Conc # 1.75 0 0.00% 5.70 1.60%

) PM2.5 Conc > 1.75 0 0.00% 4.19 1.18%

a

 The change is defined as the control case value minus the base case value.

Table 9A-7 provides additional insights on the potential changes in PM air quality resulting

from the standards. The information presented previously in Table 9A-5 illustrated the absolute

and relative changes for different points along the distribution of baseline 2020 and 2030 PM2.5

concentration levels, e.g., the change reflects the lowering of the minimum predicted baseline

concentration rather than the minimum predicted change for 2020 and 2030. The latter is the

focus of Table 9A-7 as it presents the distribution of predicted changes in both absolute terms

(i.e., μg/m3

) and relative terms (i.e., percent) across individual REMSAD grid-cells. Therefore,

it provide more information on the range of predicted changes associated with the rule. As

shown for 2020, the absolute reduction in annual mean PM2.5 concentration ranged from a low of

0.02 μg/m3 to a high of 1.36 μg/m3, while the relative reduction ranged from a low of 0.3 percent

to a high of 12.2 percent. Alternatively, for 2030, the absolute reduction ranged from 0.02 to

2.03 μg/m3, while the relative reduction ranged from 0.4 to 15.5 percent. 
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Table 9A-8. 

Summary of Absolute and Relative Changes in PM Air Quality Due to Preliminary Control

Option for Nonroad Engine/Diesel Fuel Standards: 2020 and 2030

2020 2030

Statistic PM2.5 Annual Mean PM2.5 Annual Mean

Absolute Change from Base Case (μg/m3)

a

 Minimum -0.02 -0.02

 Maximum -1.36 -2.03 

 Average -0.20 -0.28

 Median -0.19 -0.26

 Population-Weighted Average c -0.42 -0.59

Relative Change from Base Case (%)b

 Minimum -0.33% -0.44%

 Maximum -12.24% -15.52% 

 Average -2.44% -3.32%

 Median -2.33% -3.13%

 Population-Weighted Average c -3.28% -4.38%

a

 The absolute change is defined as the control case value minus the base case value for each REMSAD grid-cell.

b

 The relative change is defined as the absolute change divided by the base case value, or the percentage change, for each gridcell. 

The information reported in this section does not necessarily reflect the same gridcell as is portrayed in the absolute change

section.

c

 Calculated by summing the product of the projected gridcell population and the estimated gridcell PM absolute/relative measure

of change, and then dividing by the total population in the 48 contiguous states.

9A.2.2 Ozone Air Quality Estimates

We use the emissions inputs summarized in Section 9A.1 with a regional-scale version of

CAMx to estimate ozone air quality in the Eastern and Western U.S. CAMx is an Eulerian

three-dimensional photochemical grid air quality model designed to calculate the concentrations

of both inert and chemically reactive pollutants by simulating the physical and chemical

processes in the atmosphere that affect ozone formation. Because it accounts for spatial and

temporal variations as well as differences in the reactivity of emissions, the CAMx is useful for

evaluating the impacts of the rule on U.S. ozone concentrations. As discussed earlier in Chapter

2, although the model tends to underestimate observed ozone, especially over the western U.S., it

exhibits less bias and error than any past regional ozone modeling application conducted by EPA

(i.e., Ozone Transport Assessment Group (OTAG), On-highway Tier-2, and HD Engine/Diesel

Fuel).
Cost-Benefit Analysis

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Our analysis applies the modeling system separately to the Eastern and Western U.S. for five

emissions scenarios: a 1996 baseline projection, a 2020 baseline projection and a 2020 projection

with preliminary nonroad controls, a 2030 baseline projection and a 2030 projection with

preliminary nonroad controls. As discussed in the Benefits Analysis TSD, we use the relative

predictions from the model by combining the 1996 base-year and each future-year scenario with

ambient air quality observations to determine the expected change in 2020 or 2030 ozone

concentrations due to the rule (Abt Associates, 2003). These results are used solely in the

benefits analysis.

The CAMx modeling system requires a variety of input files that contain information

pertaining to the modeling domain and simulation period. These include gridded, day-specific

emissions estimates and meteorological fields, initial and boundary conditions, and land-use

information. The model divides the continental United States into two regions: East and West.

As applied to each region, the model segments the area within the subject region into square

blocks called grids (roughly equal in size to counties), each of which has several layers of air

conditions that are considered in the analysis. Using this data, the CAMx model generates

predictions of hourly ozone concentrations for every grid. We then calibrate the results of this

process to develop 2020 and 2030 ozone profiles at monitor sites by normalizing the

observations to the observed ozone concentrations at each monitor site. For areas (grids) without

ozone monitoring data, we interpolated ozone values using data from monitors surrounding the

area. After completing this process, we calculated daily and seasonal ozone metrics to be used

as inputs to the health and welfare C-R functions of the benefits analysis. The following sections

provide a more detailed discussion of each of the steps in this evaluation and a summary of the

results.

9A.2.2.1 Modeling Domain 

The modeling domain representing the Eastern U.S. is the same as that used previously for

OTAG and the On-highway Tier-2 rulemaking. As shown in Figure 9A-4, this domain

encompasses most of the Eastern U.S. from the East coast to mid-Texas and consists of two grids

with differing resolutions. The modeling domain extends from 99 degrees to 67 degrees west

longitude and from 26 degrees to 47 degrees north latitude. The inner portion of the modeling

domain shown in Figure 9A-4 uses a relatively fine grid of 12 km consisting of nine vertical

layers. The outer area has less horizontal resolution, as it uses a 36 km grid with the same nine

vertical layers. The vertical height of the modeling domain is 4,000 meters above ground level

for both areas. 

The modeling domain representing the Western U.S. is the same as that used previously for

the On-highway Tier-2 rulemaking. As shown in Figure 9A-5, this domain encompasses the

area west of the 99th degree longitude (which runs through North and South Dakota, Nebraska,
Final Regulatory Impact Analysis

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Kansas, Oklahoma, and Texas) and consists of two grids with differing resolutions. The domain

extends from 127 degrees to 99 degrees west longitude and from 26 degrees to 52 degrees north

latitude. The inner portion of the modeling domain shown in Figure 9A-5 uses a relatively fine

grid of 12 km consisting of eleven vertical layers. The outer area has less horizontal resolution,

as it uses a 36 km grid with the same eleven vertical layers. The vertical height of the modeling

domain is 4,800 meters above ground level.
Cost-Benefit Analysis

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Figure 9A-4 CAMx Eastern U.S. Modeling Domain

Figure 9A-5 CAMx Western U.S. Modeling Domain

Note: The inner area represents fine grid modeling at 12 km resolution, while the outer area represents the coarse grid

modeling at 36 km resolution.

Note: The inner area represents fine grid modeling at 12 km resolution, while the outer area represents the coarse grid

modeling at 36 km resolution.
Final Regulatory Impact Analysis

F

 The ozone season for this analysis is defined as the 5-month period from May to September; however, to

estimate certain crop yield benefits, the modeling results were extended to include months outside the 5-month

ozone season.

GBased on AIRS, there were 961 ozone monitors with sufficient data, i.e., 50 percent or more days reporting at

least 9 hourly observations per day (8 am to 8 pm) during the ozone season.

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9A.2.2.2 Simulation Periods

For use in this benefits analysis, the simulation periods modeled by CAMx included several

multi-day periods when ambient measurements recorded high ozone concentrations. A

simulation period, or episode, consists of meteorological data characterized over a block of days

that are used as inputs to the air quality model. A simulation period is selected to characterize a

variety of ozone conditions including some days with high ozone concentrations in one or more

portions of the U.S. and observed exceedances of the 1-hour NAAQS for ozone being recorded

at monitors. We focused on the summer of 1995 for selecting the episodes to model in the East

and the summer of 1996 for selecting the episodes to model in the West because each is a recent

time period for which we had model-ready meteorological inputs and this timeframe contained

several periods of elevated ozone over the Eastern and Western U.S., respectively. As detailed

in the air quality modeling TSD, this analysis used three multi-day meteorological scenarios

during the summer of 1995 for the model simulations over the eastern U.S.: June 12-24, July 5-

15, and August 7-21. Two multi-day meteorological scenarios during the summer of 1996 were

used in the model simulations over the western U.S.: July 5-15 and July 18-31. Each of the five

emissions scenarios (1996 base year, 2020 base, 2020 control, 2030 baseline, 2030 control) were

simulated for the selected episodes. These episodes include a three day “ramp-up” period to

initialize the model, but the results for these days are not used in this analysis.

9A.2.2.3 Converting CAMx Outputs to Full-Season Profiles for Benefits Analysis

This study extracted hourly, surface-layer ozone concentrations for each grid-cell from the

standard CAMx output file containing hourly average ozone values. These model predictions

are used in conjunction with the observed concentrations obtained from the Aerometric

Information Retrieval System (AIRS) to generate ozone concentrations for the entire ozone

season.f,g The predicted changes in ozone concentrations from the future-year base case to

future-year control scenario serve as inputs to the health and welfare C-R functions of the

benefits analysis, i.e., BENMAP. 

In order to estimate ozone-related health and welfare effects for the contiguous U.S., fullseason ozone data are required for every CAPMS grid-cell. Given available ozone monitoring

data, we generated full-season ozone profiles for each location in the contiguous 48 States in two

steps: (1) we combine monitored observations and modeled ozone predictions to interpolate
Cost-Benefit Analysis

HThe 8 km grid squares contain the population data used in the health benefits analysis model, CAPMS. See

Section C of this appendix for a discussion of this model.

I

This approach is a generalization of planar interpolation that is technically referred to as enhanced Voronoi

Neighbor Averaging (EVNA) spatial interpolation (See Abt Associates (2003) for a more detailed description).

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hourly ozone concentrations to a grid of 8 km by 8 km population grid-cells, and (2) we

converted these full-season hourly ozone profiles to an ozone measure of interest, such as the

daily average. h,i For the analysis of ozone impacts on agriculture and commercial forestry, we

use a similar approach except air quality is interpolated to county centroids as opposed to

population grid-cells. We report ozone concentrations as a cumulative index called the SUM06. 

The SUM06 is the sum of the ozone concentrations for every hour that exceeds 0.06 parts per

million (ppm) within a 12-hour period from 8 am to 8 pm in the months of May to September. 

These methods are described in detail in the benefits analysis technical support document (Abt

Associates, 2003). 

9A.2.2.4 Ozone Air Quality Results

This section provides a summary the predicted ambient ozone concentrations from the

CAMx model for the 2020 and 2030 base cases and changes associated with the Nonroad

Engine/Diesel Fuel control scenario. In Tables 9A-8 and 9A-9, we provide those ozone metrics

for grid-cells in the Eastern and Western U.S. respectively, that enter the concentration response

functions for health benefits endpoints. In addition to the standard frequency statistics (e.g.,

minimum, maximum, average, median), we provide the population-weighted average which

better reflects the baseline levels and predicted changes for more populated areas of the nation. 

This measure, therefore, will better reflect the potential benefits of these predicted changes

through exposure changes to these populations.

 As shown in Table 9A-8, for the 2020 ozone season, the rule results in average reductions of

roughly 2 percent, or between 0.57 to 0.85 ppb, in the daily average ozone concentration metrics

across the Eastern U.S. population grid-cells. For the 2030 ozone season, the average reductions

in the daily average ozone concentration are between 3 and 3.5 percent, or between 0.91 to 1.35

ppb. A slightly lower relative decline is predicted for the population-weighted average, which

reflects the observed increases in ozone concentrations for certain hours during the year in

highly populated urban areas associated with NOx emissions reductions (see more detailed

discussion in Chapter 2). Additionally, the daily 1-hour maximum ozone concentrations are

predicted to decline between 2.3 and 3.6 percent in 2020 and 2030 respectively, i.e., between

1.05 and 1.66 ppb. 

As shown in Table 9A-9, for the 2020 ozone season, the rule results in average reductions of

roughly 1.5 percent, or between 0.57 to 0.52 ppb, in the daily average ozone concentration
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metrics across the Western U.S. population grid-cells. For the 2030 ozone season, the average

reductions in the daily average ozone concentration are roughly 2 percent, or between 0.61 to

0.82 ppb. Additionally, the daily 1-hour maximum ozone concentrations are predicted to decline

between 1.3 and 2.1 percent in 2020 and 2030 respectively, i.e., between 0.62 and 0.97 ppb. 

As discussed in more detail in Chapter 2, our ozone air quality modeling showed that the

NOx emissions reductions from the preliminary modeled standards are projected to result in

increases in ozone concentrations for certain hours during the year, especially in urban, NOx

limited areas. These increases are often observed within the highly populated urban areas in

California. As a result, the population-weighted metrics for ozone shown in Table 9A-9 indicate

increases in concentrations. Most of these increases are expected to occur during hours where

ozone levels are low (and often below the one-hour ozone standard). These increase are

accounted for in the benefits analysis because it relies on the changes in ozone concentrations

across the entire distribution of baseline levels. However, as detailed in Chapter 2 and illustrated

by the results from Tables 9A-8 and 9A-9, most of the country experiences decreases in ozone

concentrations for most hours in the year.

In Table 9A-10, we provide the seasonal SUM06 ozone metric for counties in the Eastern

and Western U.S. that enters the concentration response function for agriculture benefit endpoints. This metric is a cumulative threshold measure so that the increase in baseline NOx

emissions from Tier 2 post-control to this rulemaking have resulted in a larger number of rural

counties exceeding the hourly 0.06 ppm threshold. As a result, changes in ozone concentrations

for these counties are contributing to greater impacts of the Nonroad Diesel Engine rule on the

seasonal SUM06 ozone metric. As shown, the average across all Eastern U.S. counties declined

by 78 percent, or almost 17 ppb. Similarly high percentage reductions are observed across the

other points on the distribution with the maximum declining by almost 30 ppb, or 55 percent,

and the median declining by almost 20 ppb, or 83 percent.
Table 9A-9. 

Summary of CAMx Derived Ozone Air Quality Metrics Due to Preliminary Control Option for Nonroad

Engine/Diesel Fuel Standards for Health Benefits EndPoints: Eastern U.S.

2020 2030

Statistic a Base Case Change b Percent Change b Base Case Change b Percent Change b

Daily 1-Hour Maximum Concentration (ppb)

Minimum c 28.85 -0.81 -2.80% 28.81 -1.24 -4.31%

Maximum c 93.94 -0.85 -0.90% 94.70 -1.61 -1.70%

Average 45.54 -1.05 -2.30% 45.65 -1.66 -3.64%

Median 45.45 -1.23 -2.71% 45.52 -1.73 -3.80%

Population-Weighted Average d 51.34 -0.67 -1.31% 51.47 -1.16 -2.25%

Daily 5-Hour Average Concentration (ppb)

Minimum c 24.90 -0.67 -2.68% 24.87 -1.03 -4.13%

Maximum c 68.69 -0.20 -0.29% 69.11 -0.44 -0.64%

Average 38.99 -0.85 -2.17% 39.08 -1.35 -3.45%

Median 38.94 -0.92 -2.39% 39.00 -1.40 -3.58%

Population-Weighted Average d 42.77 -0.47 -1.10% 42.90 -0.84 -1.96%

Daily 8-Hour Average Concentration (ppb)

Minimum c 24.15 -0.64 -2.64% 24.12 -0.98 -4.07%

Maximum c 68.30 -0.21 -0.31% 68.72 -0.46 -0.67%

Average 38.46 -0.83 -2.16% 38.55 -1.33 -3.44%

Median 38.44 -0.89 -2.33% 38.50 -1.45 -3.76%

Population-Weighted Average d 42.07 -0.46 -1.08% 42.19 -0.82 -1.93%

Daily 12-Hour Average Concentration (ppb)

Minimum c 22.42 -0.58 -2.57% 22.40 -0.89 -3.96%

Maximum c 66.06 -0.17 -0.25% 66.46 -0.38 -0.58%

Average 36.59 -0.78 -2.13% 36.66 -1.25 -3.40%

Median 36.61 -0.84 -2.30% 36.66 -1.43 -3.89%

Population-Weighted Average d 39.65 -0.40 -1.00 39.75 -0.72 -1.80%

Daily 24-Hour Average Concentration (ppb)

Minimum c 15.20 -0.35 -2.28% 15.19 -0.54 -3.52%

Maximum c 55.95 0.10 0.18% 56.23 0.04 0.07%

Average 28.93 -0.57 -1.96% 28.98 -0.91 -3.14%

Median 28.92 -0.63 -2.15% 28.98 -1.01 -3.48%

Population-Weighted Average d 30.24 -0.18 -0.60% 30.29 -0.37 -1.23%

a

 These ozone metrics are calculated at the CAMX grid-cell level for use in health effects estimates based on the results of spatial and temporal Voronoi Neighbor Averaging. 

Except for the daily 24-hour average, these ozone metrics are calculated over relevant time periods during the daylight hours of the “ozone season,” i.e., May through

September. For the 5-hour average, the relevant time period is 10 am to 3 pm; for the 8-hr average, it is 9 am to 5 pm; and, for the 12-hr average it is 8 am to 8 pm.

b

 The change is defined as the control case value minus the base case value. The percent change is the “Change” divided by the “Base Case,” and then multiplied by 100 to

convert the value to a percentage. 

c

 The base case minimum (maximum) is the value for the CAMX grid cell with the lowest (highest) value.

d

 Calculated by summing the product of the projected CAMX grid-cell population and the estimated CAMX grid-cell seasonal ozone concentration, and then dividing by the

total population.
Table 9A-10.

Summary of CAMx Derived Ozone Air Quality Metrics Due to Preliminary Control Option for Nonroad

Engine/Diesel Fuel Standards for Health Benefits EndPoints: Western U.S.

2020 2030

Statistic a Base Case Change b Percent Change b Base Case Change b Percent Change b

Daily 1-Hour Maximum Concentration (ppb)

Minimum c 27.48 -0.01 -0.03% 27.48 -0.01 -0.05%

Maximum c 201.28 4.87 2.42% 208.02 6.26 3.01%

Average 47.02 -0.62 -1.31% 47.04 -0.97 -2.07%

Median 46.10 -0.56 -1.19% 46.06 -0.66 -1.43%

Population-Weighted Average d 63.80 0.34 0.54% 64.23 0.38 0.58%

Daily 5-Hour Average Concentration (ppb)

Minimum c 24.20 -0.01 -0.04% 24.21 -0.01 -0.05%

Maximum c 163.41 2.55 1.56% 168.89 6.04 3.57%

Average 41.11 -0.52 -1.26% 41.13 -0.82 -2.00%

Median 40.48 -0.40 -1.04% 40.46 -0.69 -1.70%

Population-Weighted Average d 53.56 0.45 0.84% 53.89 0.55 1.03%

Daily 8-Hour Average Concentration (ppb)

Minimum c 23.77 -0.01 -0.04% 23.77 -0.01 -0.05%

Maximum c 157.49 1.33 0.84% 161.92 5.94 3.67%

Average 40.68 -0.51 -1.25% 40.69 -0.81 -1.99%

Median 40.11 -0.36 -1.03% 40.09 -0.72 -1.79%

Population-Weighted Average d 51.96 0.46 0.88% 52.29 0.57 1.10%

Daily 12-Hour Average Concentration (ppb)

Minimum c 22.13 0.31 1.39% 22.09 0.44 2.01%

Maximum c 140.48 1.65 1.18% 143.59 1.78 1.24%

Average 39.30 -0.48 -1.23% 39.31 -0.77 -1.95%

Median 38.85 -0.38 -0.97% 38.82 -0.58 -1.50%

Population-Weighted Average d 47.68 0.49 1.02% 47.99 0.63 1.32%

Daily 24-Hour Average Concentration (ppb)

Minimum c 14.08 0.22 1.60% 14.03 0.32 2.30%

Maximum c 95.27 0.41 0.43% 96.59 0.29 0.30%

Average 33.42 -0.38 -1.14% 33.42 -0.61 -1.82%

Median 32.97 -0.30 -0.89% 32.95 -0.61 -1.85%

Population-Weighted Average d 35.53 0.47 1.31% 35.74 0.63 1.77%

a

 These ozone metrics are calculated at the CAMX grid-cell level for use in health effects estimates based on the results of spatial and temporal Voronoi Neighbor Averaging. 

Except for the daily 24-hour average, these ozone metrics are calculated over relevant time periods during the daylight hours of the “ozone season,” i.e., May through

September. For the 5-hour average, the relevant time period is 10 am to 3 pm; for the 8-hr average, it is 9 am to 5 pm; and, for the 12-hr average it is 8 am to 8 pm.

b

 The change is defined as the control case value minus the base case value. The percent change is the “Change” divided by the “Base Case,” and then multiplied by 100 to

convert the value to a percentage. 

c

 The base case minimum (maximum) is the value for the CAMX grid cell with the lowest (highest) value.

d

 Calculated by summing the product of the projected CAMX grid-cell population and the estimated CAMX grid-cell seasonal ozone concentration, and then dividing by the

total population.
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Table 9A-11. 

Summary of CAMx Derived Ozone Air Quality Metrics Due to Preliminary Control Option for Nonroad

Engine/Diesel Fuel Standards for Welfare Benefits Endpoints: 2020 and 2030

2020 2030

Statistic a Base Case Change b

Percent

Change b Base Case Change b

Percent

Change b

Eastern U.S.

Sum06 (ppm)

Minimum c 0.00 0.00 - 0.00 0.00 -

Maximum c 67.24 -3.30 -4.91 68.63 -5.54 -8.07%

Average 4.74 -0.72 -15.10 4.88 -1.09 -22.43%

Median 2.18 -0.76 -35.02 2.21 -0.77 -34.84%

Western U.S.

Sum06 (ppm)

Minimum c 0.00 0.00 - 0.00 0.00 -

Maximum c 132.73 6.09 4.59 137.71 8.45 6.14%

Average 2.78 -0.22 -7.85 2.83 -0.33 -11.72%

Median 0.00 0.00 - 0.00 0.00 -

a

 SUM06 is defined as the cumulative sum of hourly ozone concentrations over 0.06 ppm (or 60 ppb) that occur during daylight

hours (from 8am to 8pm) in the months of May through September. It is calculated at the county level for use in agricultural

benefits based on the results of temporal and spatial Voronoi Neighbor Averaging. 

b

 The change is defined as the control case value minus the base case value. The percent change is the “Change” divided by the

“Base Case,” which is then multiplied by 100 to convert the value to a percentage.

c

 The base case minimum (maximum) is the value for the county level observation with the lowest (highest) concentration.

9A.2.3 Visibility Degradation Estimates

Visibility degradation is often directly proportional to decreases in light transmittal in the

atmosphere. Scattering and absorption by both gases and particles decrease light transmittance. 

To quantify changes in visibility, our analysis computes a light-extinction coefficient, based on

the work of Sisler (1996), which shows the total fraction of light that is decreased per unit

distance. This coefficient accounts for the scattering and absorption of light by both particles

and gases, and accounts for the higher extinction efficiency of fine particles compared to coarse

particles. Fine particles with significant light-extinction efficiencies include sulfates, nitrates,

organic carbon, elemental carbon (soot), and soil (Sisler, 1996).

Based upon the light-extinction coefficient, we also calculated a unitless visibility index,

called a “deciview,” which is used in the valuation of visibility. The deciview metric provides a
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linear scale for perceived visual changes over the entire range of conditions, from clear to hazy. 

Under many scenic conditions, the average person can generally perceive a change of one

deciview. The higher the deciview value, the worse the visibility. Thus, an improvement in

visibility is a decrease in deciview value. 

Table 9A-11 provides the distribution of visibility improvements across 2020 and 2030

populations resulting from the Nonroad Engine/Diesel Fuel rule. The majority of the 2030 U.S.

population live in areas with predicted improvement in annual average visibility of between 0.4

to 0.6 deciviews resulting from the rule. As shown, almost 20 percent of the 2030 U.S.

population are predicted to experience improved annual average visibility of greater than 0.6

deciviews. Furthermore, roughly 70 percent of the 2030 U.S. population will benefit from

reductions in annual average visibility of greater than 0.4 deciviews. The information provided

in Table 9A-11 indicates how widespread the improvements in visibility are expected to be and

the share of populations that will benefit from these improvements.

Because the visibility benefits analysis distinguishes between general regional visibility

degradation and that particular to Federally-designated Class I areas (i.e., national parks, forests,

recreation areas, wilderness areas, etc.), we separated estimates of visibility degradation into

“residential” and “recreational” categories. The estimates of visibility degradation for the

“recreational” category apply to Federally-designated Class I areas, while estimates for the

“residential” category apply to non-Class I areas. Deciview estimates are estimated using

outputs from REMSAD for the 2020 and 2030 base cases and control scenarios. 

Table 9A-12. 

Distribution of Populations Experiencing Visibility Improvements Due to Preliminary Control

Option for Nonroad Diesel Engine Standards: 2020 and 2030

2020 Population 2030 Population

Improvements in Visibility a

(annual average deciviews) Number (millions) Percent (%) Number (millions) Percent (%)

0 < ) Deciview # 0.2 52.0 15.8% 11.6 3.3%

0.2 < ) Deciview # 0.4 115.5 35.0% 179.7 50.5%

0.4 < ) Deciview # 0.6 81.3 24.7% 90.5 25.4%

0.6 < ) Deciview # 0.8 62.0 18.8% 49.1 13.8%

0.8 < ) Deciview # 1.0 13.2 4.0% 16.4 4.6%

) Deciview > 1.0 5.6 1.7% 8.5 2.4%

a

 The change is defined as the control case deciview level minus the base case deciview level.
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9A.2.3.1 Residential Visibility Improvements

Air quality modeling results predict that the Nonroad Engine/Diesel Fuel rule will create

improvements in visibility through the country. In Table 9A-12, we summarize residential

visibility improvements across the Eastern and Western U.S. in 2020 and 2030. The baseline

annual average visibility for all U.S. counties is 14.8 deciviews. The mean improvement across

all U.S. counties is 0.28 deciviews, or almost 2 percent. In urban areas with a population of

250,000 or more (i.e., 1,209 out of 5,147 counties), the mean improvement in annual visibility

was 0.39 deciviews and ranged from 0.05 to 1.08 deciviews. In rural areas (i.e., 3,938 counties),

the mean improvement in visibility was 0.25 deciviews in 2030 and ranged from 0.02 to 0.94

deciviews.

On average, the Eastern U.S. experienced slightly larger absolute but smaller relative

improvements in visibility than the Western U.S. from the Nonroad Engine/Diesel Fuel

reductions. In Eastern U.S., the mean improvement was 0.34 deciviews from an average

baseline of 19.32 deciviews. Western counties experienced a mean improvement of 0.21

deciviews from an average baseline of 9.75 deciviews projected in 2030. Overall, the data

suggest that the Nonroad Engine/Diesel Fuel rule has the potential to provide widespread

improvements in visibility for 2020 and 2030.

Table 9A-13. 

Summary of Baseline Residential Visibility and Changes by Region: 2020 and 2030

(Annual Average Deciviews)

2020 2030

Regionsa Base Case Changeb Percent

Change Base Case Changeb PercentChange

Eastern U.S. 20.27 0.24 1.3% 20.54 0.33 1.7%

 Urban 21.61 0.24 1.2% 21.94 0.33 1.6%

 Rural 19.73 0.24 1.3% 19.98 0.33 1.8%

Western U.S. 8.69 0.18 2.1% 8.83 0.25 2.8%

 Urban 9.55 0.25 2.7% 9.78 0.35 3.6%

 Rural 8.50 0.17 2.0% 8.61 0.23 2.7%

National, all counties 14.77 0.21 1.7% 14.98 0.29 2.3%

 Urban 17.21 0.24 1.7% 17.51 0.34 2.3%

 Rural 14.02 0.20 1.6% 14.20 0.28 2.2%

a

 Eastern and Western regions are separated by 100 degrees north longitude. Background visibility conditions differ by

region. 

b

 An improvement in visibility is a decrease in deciview value. The change is defined as the Nonroad Engine/Diesel

Fuel control case deciview level minus the basecase deciview level.
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9A.2.3.2 Recreational Visibility Improvements

In Table 9A-13, we summarize recreational visibility improvements by region in 2020 and

2030 in Federal Class I areas. These recreational visibility regions are shown in Figure 9A-6. 

As shown, the national improvement in visibility for these areas increases from 1.5 percent, or

0.18 deciviews, in 2020 to 2.1 percent, or 0.24 deciviews, in 2030. Predicted relative visibility

improvements are the largest in the Western U.S. as shown for California (3.2% in 2030), and

the Southwest (2.9%) and the Rocky Mountain (2.5%). Federal Class I areas in the Eastern U.S.

are predicted to have an absolute improvement of 0.24 deciviews in 2030, which reflects a 1.1 to

1.3 percent change from 2030 baseline visibility of 20.01 deciviews.
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 Northwest 

 Roc ky M ountain



 Northeast/Midwes t



 Southeast



  Southwest

 California

Study Region

Transfer Region

Figure 9A-6. Recreational Visibility Regions for Continental U.S.

Note: Study regions were represented in the Chestnut and Rowe (1990a, 1990b) studies used

in evaluating the benefits of visibility improvements, while transfer regions used extrapolated

study results.
Table 9A-14. 

Summary of Baseline Recreational Visibility and Changes by Region: 2020 and 2030

(Annual Average Deciviews)

2020 2030

Class I Visibility Regionsa Base Case Changeb Percent

Change Base Case Changeb PercentChange

Eastern U.S. 19.72 0.18 0.9% 20.01 0.24 1.2%

 Southeast 21.31 0.18 0.9% 21.62 0.24 1.1%

 Northeast/Midwest 18.30 0.18 1.0% 18.56 0.24 1.3%

Western U.S. 8.80 0.17 2.0% 8.96 0.24 2.7%

 California 9.33 0.21 2.3% 9.56 0.30 3.2%

 Southwest 6.87 0.16 2.3% 7.03 0.21 2.9%

 Rocky Mountain 8.46 0.15 1.8% 8.55 0.21 2.5%

 Northwest 12.05 0.18 1.5% 12.18 0.24 2.0%

National Average (unweighted) 11.61 0.18 1.5% 11.80 0.24 2.1%

a

 Regions are pictured in Figure VI-5 and are defined in the technical support document (see Abt Associates, 2003). b

 An improvement in visibility is a decrease in deciview value. The change is defined as the Nonroad Engine/Diesel

Fuel control case deciview level minus the basecase deciview level.

9A.3 Benefit Analysis- Data and Methods

Environmental and health economists have a number of methods for estimating the economic

value of improvements in (or deterioration of) environmental quality. The method used in any

given situation depends on the nature of the effect and the kinds of data, time, and resources that

are available for investigation and analysis. This section provides an overview of the methods

we selected to quantify and monetize the benefits included in this RIA. 

Given changes in environmental quality (ambient air quality, visibility, nitrogen and sulfate

deposition, odor), the next step is to determine the economic value of those changes. We follow

a “damage-function” approach in calculating total benefits of the modeled changes in

environmental quality. This approach estimates changes in individual health and welfare

endpoints (specific effects that can be associated with changes in air quality) and assigns values

to those changes assuming independence of the individual values. Total benefits are calculated

simply as the sum of the values for all non-overlapping health and welfare endpoints. This

imposes no overall preference structure, and does not account for potential income or

substitution effects, i.e. adding a new endpoint will not reduce the value of changes in other

endpoints. The “damage-function” approach is the standard approach for most cost-benefit

analyses of environmental quality programs, and has been used in several recent published

analyses (Banzhaf et al., 2002; Levy et al., 2001; Levy et al., 1999; Ostro and Chestnut, 1998). 
Cost-Benefit Analysis

J

 Several commentators from the public and from public interest groups noted that occupational studies have

shown diesel exhaust, as a mixture, to be carcinogenic. In addition, several of these commentors also noted that

diesel exhaust contains carcinogenic hazardous air pollutants (HAPs). For these reasons, it was suggested that EPA

should include modeling of cancer incidence associated with exposure to the carcinogenic components of diesel

exhaust. Diesel particles producing lung cancer mortality may be included in the lung cancer mortality estimates for

PM2.5. We also acknowledge both that diesel exhaust as a mixture is likely to be carcinogenic and that it contains

specific carcinogenic HAPs which represent a cancer risk. However, at this time, as discussed in Chapter 2, we do

not believe that the data support the determination of a unit risk for diesel exhaust as a mixture and therefore,

lifetime mortality attributable to diesel exhaust exposure cannot be quantified for purposes of benefits analysis. 

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In order to assess economic value in a damage-function framework, the changes in

environmental quality must be translated into effects on people or on the things that people

value. In some cases, the changes in environmental quality can be directly valued, as is the case

for changes in visibility. In other cases, such as for changes in ozone and PM, a health and

welfare impact analysis must first be conducted to convert air quality changes into effects that

can be assigned dollar values.

For the purposes of this RIA, the health impacts analysis is limited to those health effects that

are directly linked to ambient levels of air pollution, and specifically to those linked to ozone and

particulate matter. There are known health effects associated with other emissions expected to

be reduced by these standards, however, due to limitations in air quality models, we are unable

to quantify the changes in the ambient levels of CO, SO2, and air toxics such as benzene.j

 There

may be other, indirect health impacts associated with implementation of controls to meet the

preliminary control options, such as occupational health impacts for equipment operators. These

impacts may be positive or negative, but in general, for this set of preliminary control options,

are expected to be small relative to the direct air pollution related impacts.

The welfare impacts analysis is limited to changes in the environment that have a direct

impact on human welfare. For this analysis, we are limited by the available data to examining

impacts of changes in visibility and agricultural yields. We also provide qualitative discussions

of the impact of changes in other environmental and ecological effects, for example, changes in

deposition of nitrogen and sulfur to terrestrial and aquatic ecosystems and odor, but we are

unable to place an economic value on these changes.

We note at the outset that EPA rarely has the time or resources to perform extensive new

research to measure either the health outcomes or their values for this analysis. Thus, similar to

Kunzli et al. (2000) and other recent health impact analyses, our estimates are based on the best

available methods of benefits transfer. Benefits transfer is the science and art of adapting

primary research from similar contexts to obtain the most accurate measure of benefits for the

environmental quality change under analysis. Where appropriate, adjustments are made for the

level of environmental quality change, the sociodemographic and economic characteristics of the
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affected population, and other factors in order to improve the accuracy and robustness of benefits

estimates.

9A.3.1 Valuation Concepts

In valuing health impacts, we note that reductions in ambient concentrations of air pollution

generally lower the risk of future adverse health affects by a fairly small amount for a large

population. The appropriate economic measure is therefore willingness-to-pay for changes in

risk prior to the regulation (Freeman, 1993). In general, economists tend to view an individual’s

willingness-to-pay (WTP) for a improvement in environmental quality as the appropriate

measure of the value of a risk reduction. An individual’s willingness-to-accept (WTA)

compensation for not receiving the improvement is also a valid measure. However, WTP is

generally considered to be a more readily available and conservative measure of benefits. 

Adoption of WTP as the measure of value implies that the value of environmental quality

improvements is dependent on the individual preferences of the affected population and that the

existing distribution of income (ability to pay) is appropriate. For some health effects, such as

hospital admissions, WTP estimates are generally not available. In these cases, we use the cost

of treating or mitigating the effect as a primary estimate. These costs of illness (COI) estimates

generally understate the true value of reductions in risk of a health effect, reflecting the direct

expenditures related to treatment but not the value of avoided pain and suffering from the health

effect (Harrrington and Portnoy, 1987; Berger, 1987).

For many goods, WTP can be observed by examining actual market transactions. For

example, if a gallon of bottled drinking water sells for one dollar, it can be observed that at least

some persons are willing to pay one dollar for such water. For goods not exchanged in the

market, such as most environmental “goods,” valuation is not as straightforward. Nevertheless,

a value may be inferred from observed behavior, such as sales and prices of products that result

in similar effects or risk reductions, (e.g., non-toxic cleaners or bike helmets). Alternatively,

surveys may be used in an attempt to directly elicit WTP for an environmental improvement.

One distinction in environmental benefits estimation is between use values and non-use

values. Although no general agreement exists among economists on a precise distinction

between the two (see Freeman, 1993), the general nature of the difference is clear. Use values

are those aspects of environmental quality that affect an individual’s welfare more or less

directly. These effects include changes in product prices, quality, and availability, changes in

the quality of outdoor recreation and outdoor aesthetics, changes in health or life expectancy, and

the costs of actions taken to avoid negative effects of environmental quality changes. 

Non-use values are those for which an individual is willing to pay for reasons that do not

relate to the direct use or enjoyment of any environmental benefit, but might relate to existence
Cost-Benefit Analysis

KConcerns about the reliability of value estimates from CV studies arose because research has shown that bias

can be introduced easily into these studies if they are not carefully conducted. Accurately measuring WTP for

avoided health and welfare losses depends on the reliability and validity of the data collected. There are several

issues to consider when evaluating study quality, including but not limited to 1) whether the sample estimates of

WTP are representative of the population WTP; 2) whether the good to be valued is comprehended and accepted by

the respondent; 3) whether the WTP elicitation format is designed to minimize strategic responses; 4) whether WTP

is sensitive to respondent familiarity with the good, to the size of the change in the good, and to income; 5) whether

the estimates of WTP are broadly consistent with other estimates of WTP for similar goods; and 6) the extent to

which WTP responses are consistent with established economic principles. 

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values and bequest values. Non-use values are not traded, directly or indirectly, in markets. For

this reason, the measurement of non-use values has proved to be significantly more difficult than

the measurement of use values. The air quality changes produced by the Nonroad Diesel Engine

rule cause changes in both use and non-use values, but the monetary benefit estimates are almost

exclusively for use values. 

More frequently than not, the economic benefits from environmental quality changes are not

traded in markets, so direct measurement techniques can not be used. There are three main nonmarket valuation methods used to develop values for endpoints considered in this analysis. 

These include stated preference (or contingent valuation), indirect market (e.g. hedonic wage),

and avoided cost methods. 

The stated preference or CV method values endpoints by using carefully structured surveys

to ask a sample of people what amount of compensation is equivalent to a given change in

environmental quality. There is an extensive scientific literature and body of practice on both

the theory and technique of stated preference based valuation. EPA believes that well-designed

and well-executed stated preference studies are valid for estimating the benefits of air quality

regulation.k

 Stated preference valuation studies form the basis for valuing a number of health

and welfare endpoints, including the value of premature mortality risk reductions, chronic

bronchitis risk reductions, minor illness risk reductions, and visibility improvements.

Indirect market methods can also be used to infer the benefits of pollution reduction. The

most important application of this technique for our analysis is the calculation of the value of a

statistical life for use in the estimate of benefits from premature mortality risk reductions. There

exists no market where changes in the probability of death are directly exchanged. However,

people make decisions about occupation, precautionary behavior, and other activities associated

with changes in the risk of death. By examining these risk changes and the other characteristics

of people’s choices, it is possible to infer information about the monetary values associated with

changes in premature mortality risk (see Section 9A.3.5.5.1).

Avoided cost methods are ways to estimate the costs of pollution by using the expenditures

made necessary by pollution damage. For example, if buildings must be cleaned or painted more
Final Regulatory Impact Analysis

L

Income elasticity is a common economic measure equal to the percentage change in WTP for a one percent

change in income.

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frequently as levels of PM increase, then the appropriately calculated increment of these costs is

a reasonable lower bound estimate (under most conditions) of true economic benefits when PM

levels are reduced. Avoided costs methods are also used to estimate some of the health-related

benefits related to morbidity, such as hospital admissions (see section 9A.3.5).

The most direct way to measure the economic value of air quality changes is in cases where

the endpoints have market prices. For the final rule, this can only be done for effects on

commercial agriculture. Well-established economic modeling approaches are used to predict

price changes that result from predicted changes in agricultural outputs. Consumer and producer

surplus measures can then be developed to give reliable indications of the benefits of changes in

ambient air quality for this category (see Section 9A.3.6.2).

9A.3.2 Growth in WTP Reflecting National Income Growth Over Time

Our analysis accounts for expected growth in real income over time. Economic theory

argues that WTP for most goods (such as environmental protection) will increase if real incomes

increase. There is substantial empirical evidence that the income elasticityl

 of WTP for health

risk reductions is positive, although there is uncertainty about its exact value. Thus, as real

income increases the WTP for environmental improvements also increases. While many

analyses assume that the income elasticity of WTP is unit elastic (i.e., ten percent higher real

income level implies a ten percent higher WTP to reduce risk changes), empirical evidence

suggests that income elasticity is substantially less than one and thus relatively inelastic. As real

income rises, the WTP value also rises but at a slower rate than real income.

The effects of real income changes on WTP estimates can influence benefit estimates in two

different ways: (1) through real income growth between the year a WTP study was conducted

and the year for which benefits are estimated, and (2) through differences in income between

study populations and the affected populations at a particular time. Empirical evidence of the

effect of real income on WTP gathered to date is based on studies examining the former. The

Environmental Economics Advisory Committee (EEAC) of the SAB advised EPA to adjust

WTP for increases in real income over time, but not to adjust WTP to account for cross-sectional

income differences “because of the sensitivity of making such distinctions, and because of

insufficient evidence available at present” (EPA-SAB-EEAC-00-013). 

Based on a review of the available income elasticity literature, we adjust the valuation of

human health benefits upward to account for projected growth in real U.S. income. Faced with a

dearth of estimates of income elasticities derived from time-series studies, we applied estimates
Cost-Benefit Analysis

M Industry commentors suggest that the income elasticity values used to adjust willingness to pay (WTP) values

for avoidance of adverse health effects are based on incorrect methodology. Specifically, they assert that EPA

values are based on cross-sectional data when they should be based on time series data. The method we used to

derive income adjustment factors, which is detailed here, is consistent with advice from the SAB-EEAC and reflect

modest increases in WTP over time. Some recent evidence from published meta-analyses (see Viscusi and Aldy,

2003) suggest that we should be using a larger income adjustment factor for premature mortality.

NU.S. Bureau of Census. Annual Projections of the Total Resident Population, Middle Series, 1999-2100.

(Available on the internet at http://www.census.gov/population/www/projections/natsum-T1.html)

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derived from cross-sectional studies in our analysis. Details of the procedure can be found in

Kleckner and Neumann (1999). An abbreviated description of the procedure we used to account

for WTP for real income growth between 1990 and 2030 is presented below.m 

Reported income elasticities suggest that the severity of a health effect is a primary

determinant of the strength of the relationship between changes in real income and WTP. As

such, we use different elasticity estimates to adjust the WTP for minor health effects, severe and

chronic health effects, and premature mortality. We also expect that the WTP for improved

visibility in Class I areas would increase with growth in real income. The elasticity values used

to adjust estimates of benefits in 2020 and 2030 are presented in Table 9A-11.

Table 9A-15. Elasticity Values Used to Account for Projected Real Income GrowthA

Benefit Category Central Elasticity Estimate

Minor Health Effect 0.14

Severe and Chronic Health Effects 0.45

Premature Mortality 0.40

VisibilityB 0.90

A Derivation of estimates can be found in Kleckner and Neumann (1999) and Chestnut (1997). Cost of Illness (COI) estimates

are assigned an adjustment factor of 1.0. 

B No range was applied for visibility because no ranges were available in the current published literature.

In addition to elasticity estimates, projections of real GDP and populations from 1990 to

2020 and 2030 are needed to adjust benefits to reflect real per capita income growth. For

consistency with the emissions and benefits modeling, we use national population estimates for

the years 1990 to 1999 based on U.S. Census Bureau estimates (Hollman, Mulder and Kallan,

2000). These population estimates are based on application of a cohort-component model

applied to 1990 U.S. Census data projectionsn

. For the years between 2000 and 2030, we applied

growth rates based on the U.S. Census Bureau projections to the U.S. Census estimate of

national population in 2000. We use projections of real GDP provided in Kleckner and
Final Regulatory Impact Analysis

OU.S. Bureau of Economic Analysis, Table 2A (1992$). (Available on the internet at

http://www.bea.doc.gov/bea/dn/0897nip2/tab2a.htm) and U.S. Bureau of Economic Analysis, Economics and

Budget Outlook. Note that projections for 2007 to 2010 are based on average GDP growth rates between 1999 and

2007.

P

Standard and Poor’s. 2000. “The U.S. Economy: The 25 Year Focus.” Winter.

QIn previous analyses, we used the Standard and Poor’s projections of GDP directly. This led to an apparent

discontinuity in the adjustment factors between 2010 and 2011. We refined the method by applying the relative

growth rates for GDP derived from the Standard and Poor’s projections to the 2010 projected GDP based on the

Bureau of Economic Analysis projections.

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Neumann (1999) for the years 1990 to 2010o

. We use projections of real GDP (in chained 1996

dollars) provided by Standard and Poor’sp

 for the years 2010 to 2024q. The Standard and Poor’s

database only provides estimates of real GDP between 1990 and 2024. We were unable to find

reliable projections of GDP past 2024. As such, we assume that per capita GDP remains

constant between 2024 and 2030.

Using the method outlined in Kleckner and Neumann (1999), and the population and income

data described above, we calculate WTP adjustment factors for each of the elasticity estimates

listed in Table 1. Benefits for each of the categories (minor health effects, severe and chronic

health effects, premature mortality, and visibility) will be adjusted by multiplying the unadjusted

benefits by the appropriate adjustment factor. Table 2 lists the estimated adjustment factors. 

Note that for premature mortality, we apply the income adjustment factor ex post to the present

discounted value of the stream of avoided mortalities occurring over the lag period. Also note

that no adjustments will be made to benefits based on the cost-of-illness approach or to work loss

days and worker productivity. This assumption will also lead us to under predict benefits in

future years since it is likely that increases in real U.S. income would also result in increased

cost-of-illness (due, for example, to increases in wages paid to medical workers) and increased

cost of work loss days and lost worker productivity (reflecting that if worker incomes are higher,

the losses resulting from reduced worker production would also be higher). No adjustments are

needed for agricultural benefits, as the model is based on projections of supply and demand in

future years and should already incorporate future changes in real income. 
Cost-Benefit Analysis

R It should be recognized that in addition to uncertainty, the annual benefit estimates for the Nonroad Diesel

Engines rulemaking presented in this analysis are also inherently variable, due to the truly random processes that

govern pollutant emissions and ambient air quality in a given year. Factors such as engine hours and weather

display constant variability regardless of our ability to accurately measure them. As such, the estimates of annual

benefits should be viewed as representative of the types of benefits that will be realized, rather than the actual

benefits that would occur every year.

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Table 9A-16. Adjustment Factors Used to Account for Projected Real Income GrowthA,B

Benefit Category 2020 2030C

Minor Health Effect 1.066 1.076

Severe and Chronic Health Effects 1.229 1.266

Premature Mortality 1.201 1.233

Visibility 1.516 1.613

A Based on elasticity values reported in Table 9A-11, US Census population projections, and projections of real

gross domestic product per capita.

B

 Note that these factors have been modified from the proposal analysis to refelect relative growth rates for GDP

derived from the Standard and Poor’s projections rather than absolute growth rates.

C Income growth adjustment factor for 2030 is based on an assumption that there is no growth in per capita income

between 2024 and 2030, based on a lack of available GDP projections beyond 2024.

9A.3.3 Methods for Describing Uncertainty

In any complex analysis using estimated parameters and inputs from numerous models, there

are likely to be many sources of uncertainty.r This analysis is no exception. As outlined both in

this and preceding chapters, many inputs are used to derive the final estimate of benefits,

including emission inventories, air quality models (with their associated parameters and inputs),

epidemiological health effect estimates, estimates of values (both from WTP and cost-of-illness

studies), population estimates, income estimates, and estimates of the future state of the world

(i.e., regulations, technology, and human behavior). Each of these inputs may be uncertain, and

depending on their location in the benefits analysis, may have a disproportionately large impact

on final estimates of total benefits. For example, emissions estimates are used in the first stage

of the analysis. As such, any uncertainty in emissions estimates will be propagated through the

entire analysis. When compounded with uncertainty in later stages, small uncertainties in

emission levels can lead to much larger impacts on total benefits. A more thorough discussion of

uncertainty can be found in the benefits technical support document (TSD) (Abt Associates,

2003).

Some key sources of uncertainty in each stage of the benefits analysis are:

- Gaps in scientific data and inquiry;
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- Variability in estimated relationships, such as epidemiological effect estimates,

introduced through differences in study design and statistical modeling;

- Errors in measurement and projection for variables such as population growth rates;

- Errors due to misspecification of model structures, including the use of surrogate

variables, such as using PM10 when PM2.5 is not available, excluded variables, and

simplification of complex functions; and

- Biases due to omissions or other research limitations.

Some of the key uncertainties in the benefits analysis are presented in Table 9A-13. Given

the wide variety of sources for uncertainty and the potentially large degree of uncertainty about

any primary estimate, it is necessary for us to address this issue in several ways, based on the

following types of uncertainty:

a. Quantifiable uncertainty in benefits estimates. For some parameters or inputs it may be

possible to provide a statistical representation of the underlying uncertainty distribution.

Quantitative uncertainty may include measurement uncertainty or variation in estimates

across or within studies. For example, the variation in VSL results across available metaanalyses provides a quantifiable basis for representing some uncertainty that can be

calculated for monetized benefits. Methods typically used to evaluate the impact of these

quantifiable sources of uncertainty on benefits and incidence estimates center on Monte

Carlo-based probabilistic simulation. This technique allows uncertainty in key inputs to be

propagated through the model to generate a single distribution of results reflecting the

combined impact of multiple sources of uncertainty. Variability can also be considered

along with uncertainty using nested two-stage Monte Carlo simulation.

b. Uncertainty in the basis for quantified estimates. Often it is possible to identify a source of

uncertainty (for example, an ongoing debate over the proper method to estimate premature

mortality) that is not readily addressed through traditional uncertainty analysis. In these

cases, it is possible to characterize the potential impact of this uncertainty on the overall

benefits estimates through sensitivity analyses.

c. Nonquantifiable uncertainty. Uncertainties may also result from omissions of known effects

from the benefits calculation, perhaps owing to a lack of data or modeling capability. For

example, in this analysis we were unable to quantify the benefits of avoided airborne

nitrogen deposition on aquatic and terrestrial ecosystems, diesel odor, or avoided health and

environmental effects associated with reductions in CO emissions.

It should be noted that, even for individual endpoints, there is usually more than one source of

uncertainty. This makes it difficult to provide an overall quantified uncertainty estimate for

individual endpoints or for total benefits, without conducting a comprehensive uncertainty
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analysis that considers the aggregate impact of multiple sources of uncertainty on benefits

estimates.

The NAS report on the EPA’s benefits analysis methodology highlighted the need for the

EPA to conduct rigorous quantitative analysis of uncertainty in its benefits estimates. In

response to these comments, the EPA has initiated the development of a comprehensive

methodology for characterizing the aggregate impact of uncertainty in key modeling elements on

both health incidence and benefits estimates. This methodology will begin by identifying those

modeling elements that have a significant impact on benefits due to either the magnitude of their

uncertainty or other factors such as nonlinearity within the modeling framework. A combination

of influence analysis and sensitivity analysis methods may be used to focus the analysis of

uncertainty on these key sources of uncertainty. A probabilistic simulation approach based on

Monte Carlo methods will be developed for propagating the impact of these sources of

uncertainty through the modeling framework. Issues such as correlation between input

parameters and the identification of reasonable upper and lower bounds for input distributions

characterizing uncertainty will be addressed in developing the approach. 

For this analysis of the final rule, EPA has addressed key sources of uncertainty through a

series of sensitivity analyses examining the impact of alternate assumptions on the benefits

estimates that are generated. Sensitivity estimates are presented in Appendix 9C. We also

present information related to an expert elicitation pilot in Appendix 9B.

Our estimate of total benefits should be viewed as an approximate result because of the

sources of uncertainty discussed above (see Table 9A-13). Uncertainty about specific aspects of

the health and welfare estimation models are discussed in greater detail in the following sections

and in the benefits TSD (Abt Associates, 2003). The total benefits estimate may understate or

overstate actual benefits of the rule.

In considering the monetized benefits estimates, the reader should remain aware of the many

limitations of conducting these analyses mentioned throughout this RIA. One significant

limitation of both the health and welfare benefits analyses is the inability to quantify many of the

serious effects listed in Table 9A-1. For many health and welfare effects, such as changes in

ecosystem functions and PM-related materials damage, reliable C-R functions and/or valuation

functions are not currently available. In general, if it were possible to monetize these benefits

categories, the benefits estimates presented in this analysis would increase. Unquantified

benefits are qualitatively discussed in the health and welfare effects sections. In addition to

unquantified benefits, there may also be environmental costs that we are unable to quantify. 

Several of these environmental cost categories are related to nitrogen deposition, while one

category is related to the issue of ultraviolet light. These endpoints are qualitatively discussed in
the health and welfare effects sections as well. The net effect of excluding benefit and disbenefit

categories from the estimate of total benefits depends on the relative magnitude of the effects. 
Cost-Benefit Analysis

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Table 9A-17. Primary Sources of Uncertainty in the Benefit Analysis

1. Uncertainties Associated With Health Impact Functions

S The value of the ozone or PM effect estimate in each health impact function.

S Application of a single effect estimate to pollutant changes and populations in all locations.

S Similarity of future year effect estimates to current effect estimates. 

S Correct functional form of each impact function. 

S Extrapolation of effect estimates beyond the range of ozone or PM concentrations observed in the study. 

S Application of effect estimates only to those subpopulations matching the original study population.

2. Uncertainties Associated With Ozone and PM Concentrations 

S Responsiveness of the models to changes in precursor emissions resulting from the control policy.

S Projections of future levels of precursor emissions, especially ammonia and crustal materials.

S Model chemistry for the formation of ambient nitrate concentrations.

S Lack of ozone monitors in rural areas requires extrapolation of observed ozone data from urban to rural areas.

S Use of separate air quality models for ozone and PM does not allow for a fully integrated analysis of pollutants and

their interactions.

S Full ozone season air quality distributions are extrapolated from a limited number of simulation days.

S Comparison of model predictions of particulate nitrate with observed rural monitored nitrate levels indicates that 

REMSAD overpredicts nitrate in some parts of the Eastern US and underpredicts nitrate in parts of the Western

US.

3. Uncertainties Associated with PM Premature mortality Risk

S No scientific literature supporting a direct biological mechanism for observed epidemiological evidence.

S Direct causal agents within the complex mixture of PM have not been identified.

S The extent to which adverse health effects are associated with low level exposures that occur many times in the

year versus peak exposures.

S The extent to which effects reported in the long-term exposure studies are associated with historically higher levels

of PM rather than the levels occurring during the period of study.

S Reliability of the limited ambient PM2.5 monitoring data in reflecting actual PM2.5 exposures.

4. Uncertainties Associated With Possible Lagged Effects

S The portion of the PM-related long-term exposure mortality effects associated with changes in annual PM levels

would occur in a single year is uncertain as well as the portion that might occur in subsequent years.

5. Uncertainties Associated With Baseline Incidence Rates

S Some baseline incidence rates are not location-specific (e.g., those taken from studies) and may therefore not

accurately represent the actual location-specific rates.

S Current baseline incidence rates may not approximate well baseline incidence rates in 2030.

S Projected population and demographics may not represent well future-year population and demographics.

6. Uncertainties Associated With Economic Valuation

S Unit dollar values associated with health and welfare endpoints are only estimates of mean WTP and therefore

have uncertainty surrounding them.

S Mean WTP (in constant dollars) for each type of risk reduction may differ from current estimates due to

differences in income or other factors.

S Future markets for agricultural products are uncertain.

7. Uncertainties Associated With Aggregation of Monetized Benefits

S Health and welfare benefits estimates are limited to the available effect estimates. Thus, unquantified or

unmonetized benefits are not included.
Final Regulatory Impact Analysis

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9A.3.4 Demographic Projections

Quantified and monetized human health impacts depend critically on the demographic

characteristics of the population, including age, location, and income. In previous analyses, we

have used simple projections of total population that did not take into account changes in

demographic composition over time. In the current analysis, we use more sophisticated

projections based on economic forecasting models developed by Woods and Poole, Inc. The

Woods and Poole (WP) database contains county level projections of population by age, sex, and

race out to 2025. Projections in each county are determined simultaneously with every other

county in the U.S. to take into account patterns of economic growth and migration. The sum of

growth in county level populations is constrained to equal a previously determined national

population growth, based on Bureau of Census estimates (Hollman, Mulder and Kallan, 2000). 

According to WP, linking county level growth projections together and constraining to a national

level total growth avoids potential errors introduced by forecasting each county independently. 

County projections are developed in a four stage process. First, national level variables such as

income, employment, populations, etc. are forecasted. Second, employment projections are

made for 172 economic areas defined by the Bureau of Economic Analysis, using an “exportbase” approach, which relies on linking industrial sector production of non-locally consumed

production items, such as outputs from mining, agriculture, and manufacturing with the national

economy. The export-base approach requires estimation of demand equations or calculation of

historical growth rates for output and employment by sector. Third, population is projected for

each economic area based on net migration rates derived from employment opportunities, and

following a cohort-component method based on fertility and mortality in each area. Fourth,

employment and population projections are repeated for counties, using the economic region

totals as bounds. The age, sex, and race distributions for each region or county are determined

by aging the population by single year of age by sex and race for each year through 2025 based

on historical rates of mortality, fertility, and migration.

The WP projections of county level population are based on historical population data from

1969-1999, and do not include the 2000 Census results. Given the availability of detailed 2000

Census data, we constructed adjusted county level population projections for each future year

using a two stage process. First, we constructed ratios of the projected WP populations in a

future year to the projected WP population in 2000 for each future year by age, sex, and race. 

Second, we multiplied the block level 2000 Census population data by the appropriate age, sex,

and race specific WP ratio for the county containing the census block, for each future year. This

results in a set of future population projections that is consistent with the most recent detailed

census data. The WP projections extend only through 2025. To calculate populations for 2030,

we applied the growth rate from 2024 to 2025 to each year between 2025 and 2030.
Cost-Benefit Analysis

S

 US Bureau of Economic Analysis, Table 2A (1992$). (Available on the internet at

http://www.bea.doc.gov/bea/dn/0897nip2/tab2a.htm) and US Bureau of Economic Analysis, Economics and Budget

Outlook. Note that projections for 2007 to 2010 are based on average GDP growth rates between 1999 and 2007.

T

 Standard and Poor’s. 2000. “The U.S. Economy: The 25 Year Focus.” Winter 2000.

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Figure 9A-7 shows the projected trends in total U.S. population and the percentage of total

population aged zero to eighteen and over 65. This figure illustrates that total populations are

projected increase from 281 million in 2000 to 345 million in 2025. The percent of the

population 18 and under is expected to decrease slightly, from 27 to 25 percent, and the percent

of the population over 65 is expected to increase from 12 percent to 18 percent. 

populations. For consistency with the emissions and benefits modeling, we use national

population estimates based on the U.S. Census Bureau projections. We use projections of real

GDP provided in Kleckner and Neumann (1999) for the years 1990 to 2010.s We use projections

of real GDP (in chained 1996 dollars) provided by Standard and Poor’s for the years 2010 to

2024.t The Standard and Poor’s database only provides estimates of real GDP between 1990 and

2024. We were unable to find reliable projections of GDP beyond 2024. As such, we assume

that per capita GDP remains constant between 2024 and 2030. This assumption will lead us to

under-predict benefits because at least some level of income growth would be projected to occur

between the years 2024 and 2030.

9A.3.5 Health Benefits Assessment Methods

The most significant monetized benefits of reducing ambient concentrations of PM and

ozone are attributable to reductions in health risks associated with air pollution. The EPA’s

Criteria Documents for ozone and PM list numerous health effects known to be linked to

ambient concentrations of these pollutants (EPA, 1996a and 1996b). As illustrated in Figure 9A1, quantification of health impacts requires several inputs, including epidemiological effect

estimates, baseline incidence and prevalence rates, potentially affected populations, and

estimates of changes in ambient concentrations of air pollution. Previous sections have

described the population and air quality inputs. This section describes the effect estimates and

baseline incidence and prevalence inputs and the methods used to quantify and monetize changes

in the expected number of incidences of various health effects.
Figure 9A-7. 

Projections of U.S. Population, 2000-2025

0.0

50.0

100.0150.0200.0250.0300.0350.0400.0

2000 2002 2004 2005 2006 2008 2010 2012 2014 2015 2016 2018 2020 2022 2024 2025

Total Population (millions)

0.0%5.0%10.0%15.0%20.0%25.0%30.0%

Percent of Total Population

As noted above, values for environmental quality improvements are expected to increase with growth in real 

Accounting for real income growth over time requires projections of both real gross domestic product (GDP) and 
Cost-Benefit Analysis

UEvidence has been found linking ozone exposures with premature mortality independent of PM exposures. A

recent analysis by Thurston and Ito (2001) reviewed previously published time-series studies of the effect of daily

ozone levels on daily mortality and found that previous EPA estimates of the short-term exposure mortality benefits

of the ozone NAAQS (EPA, 1997) may have been underestimated by up to a factor of two, even when PM is

controlled for in the models. In its September 2001 advisory on the draft analytical blueprint for the second Section

812 prospective analysis, the SAB cited the Thurston and Ito study as a significant advance in understanding the

effects of ozone on daily mortality and recommended re-evaluation of the ozone mortality endpoint for inclusion in

the next prospective study (EPA-SAB-COUNCIL-ADV-01-004, 2001). In addition, a recent World Health

Organization (WHO) report found that “recent epidemiological studies have strengthened the evidence that there are

short-term O3 effects on premature mortality and respiratory morbidity and provided further information on

exposure-response relationships and effect modification.” (WHO, 2003). Based on these new analyses and

recommendations, the EPA is currently reevaluating ozone-related mortality for inclusion in the primary benefits

analysis. The EPA is sponsoring three independent meta-analyses of the ozone-mortality epidemiology literature to

inform a determination on inclusion of this important health endpoint. Upon completion and peer review of the

meta-analyses, the EPA will make its determination on whether benefits of reductions in ozone-related mortality will

be included in the future benefits analyses.

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9A.3.5.1 Selecting Health Endpoints and Epidemiological Effect Estimates

Quantifiable health benefits of the rule may be related to ozone only, PM only, or both

pollutants. Decreased worker productivity, respiratory hospital admissions for children under

two, and school absences are related to ozone but not PM. PM-only health effects include

premature mortality, nonfatal heart attacks, chronic bronchitis, acute bronchitis, upper and lower

respiratory symptoms, asthma exacerbations, and work loss days.u Health effects related to both

PM and ozone include hospital admissions, emergency room visits for asthma, and minor

restricted activity days.

We relied on the available published scientific literature to ascertain the relationship between

PM and ozone exposure and adverse human health effects. We evaluated studies using the

selection criteria summarized in Table 9A-18. These criteria include consideration of whether

the study was peer reviewed, the match between the pollutant studied and the pollutant of

interest, the study design and location, and characteristics of the study population, among other

considerations. The selection of C-R functions for the benefits analysis is guided by the goal of

achieving a balance between comprehensiveness and scientific defensibility. 

The Health Effects Institute (HEI) reported findings by health researchers at Johns Hopkins

University and others that have raised concerns about aspects of the statistical methods used in a

number of recent time-series studies of short-term exposures to air pollution and health effects

(Greenbaum, 2002). The estimates derived from the long-term exposure studies, which account

for a major share of the economic benefits described in this chapter, are not affected. Similarly,

the time-series studies employing generalized linear models (GLMs) or other parametric

methods, as well as case-crossover studies, are not affected. As discussed in HEI materials

provided to the EPA and to CASAC (Greenbaum, 2002), researchers working on the National

Morbidity, Mortality, and Air Pollution Study (NMMAPS) found problems in the default
Final Regulatory Impact Analysis

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“convergence criteria” used in Generalized Additive Models (GAM) and a separate issue first

identified by Canadian investigators about the potential to underestimate standard errors in the

same statistical package. Following identification of the GAM issue, a number of time-series

studies were reanalyzed using alternative methods, typically GAM with more stringent

convergence criteria and an alternative model such as generalized linear models (GLM) with

natural smoothing splines, and the results of the reanalyses have been compiled and reviewed in

a recent HEI publication (HEI, 2003a). In most, but not all, of the reanalyzed studies, it was

found that risk estimates were reduced and confidence intervals increased with the use of GAM

with more stringent convergence criteria or GLM analyses; however, the reanalyses generally

did not substantially change the findings of the original studies, and the changes in risk estimates

with alternative analysis methods were much smaller than the variation in effects across studies. 

The HEI review committee concluded the following:

S Although the number of studies showing an association of PM with premature mortality

was slightly smaller, the PM association persisted in the majority of studies.

S In some of the large number of studies in which the PM association persisted, the

estimates of PM effect were substantially smaller.

S In the few studies in which investigators performed further sensitivity analyses, some

showed marked sensitivity of the PM effect estimate to the degree of smoothing and/or

the specification of weather (HEI, 2003b, p. 269)

Examination of the original studies used in our benefits analysis found that the health

endpoints that are potentially affected by the GAM issues include reduced hospital admissions

and reduced lower respiratory symptoms. For the analysis of the final rule, we have

incorporated a number of studies that have been updated to correct for the GAM issue, including 

Ito et al. (2003) for respiratory-related hospital admissions (COPD and pneumonia), Shepard et

al. (2003) for respiratory-related hospital admissions (asthma), Moolgavkar (2003) for

cardiovascular-related hospital admissions (ICD codes 390-429), and Ito et al. (2003) for

cardiovascular-related hospital admissions (ischemic heart disease, dysrhythmia, and heart

failure). Several additional hospital admissions-related studies have not yet been formally

updated to correct for the GAM issue. These include the lower respiratory symptoms study and

hospital admissions for respiratory and cardiovascular causes in populations aged 20 to 64. 

However, as discussed above, available evidence suggests that the errors introduced into effect

estimates due to the GAM issue should not significantly affect incidence results.
Cost-Benefit Analysis

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Table 9A-18. Summary of Considerations Used in Selecting C-R Functions

Consideration Comments

Peer reviewed

research

Peer reviewed research is preferred to research that has not undergone the peer review process.

Study type Among studies that consider chronic exposure (e.g., over a year or longer) prospective cohort studies

are preferred over cross-sectional studies because they control for important individual-level

confounding variables that cannot be controlled for in cross-sectional studies. 

Study period Studies examining a relatively longer period of time (and therefore having more data) are preferred,

because they have greater statistical power to detect effects. More recent studies are also preferred

because of possible changes in pollution mixes, medical care, and life style over time. However, when

there are only a few studies available, studies from all years will be included.

Population

attributes

The most technically appropriate measures of benefits would be based on impact functions that cover

the entire sensitive population, but allow for heterogeneity across age or other relevant demographic

factors. In the absence of effect estimates specific to age, sex, preexisting condition status, or other

relevant factors, it may be appropriate to select effect estimates that cover the broadest population, to

match with the desired outcome of the analysis, which is total national-level health impacts.

Study size Studies examining a relatively large sample are preferred because they generally have more power to

detect small magnitude effects. A large sample can be obtained in several ways, either through a large

population, or through repeated observations on a smaller population, i.e. through a symptom diary

recorded for a panel of asthmatic children.

Study location U.S. studies are more desirable than non-U.S. studies because of potential differences in pollution

characteristics, exposure patterns, medical care system, population behavior and life style.

Pollutants included

in model

When modeling the effects of ozone and PM (or other pollutant combinations) jointly, it is important

to use properly specified impact functions that include both pollutants. Use of single pollutant models

in cases where both pollutants are expected to affect a health outcome can lead to double-counting

when pollutants are correlated.

Measure of

pollutant

For this analysis for PM-related effects, impact functions based on PM2.5 are preferred to PM10 because

the Nonroad Diesel Engine rule will regulate emissions of PM2.5 precursors and air quality modeling

was conducted for this size fraction of PM. Where PM2.5 functions are not available, PM10 functions

are used as surrogates, recognizing that there will be potential downward (upward) biases if the fine

fraction of PM10 is more (less) toxic than the coarse fraction. Adequacy of ozone exposure metrics in

studies was also considered.

Economically

valuable health

effects

Some health effects, such as forced expiratory volume and other technical measurements of lung

function, are difficult to value in monetary terms. These health effects are not quantified in this

analysis.

Non-overlapping

endpoints

Although the benefits associated with each individual health endpoint may be analyzed separately,

care must be exercised in selecting health endpoints to include in the overall benefits analysis because

of the possibility of double counting of benefits. 
Final Regulatory Impact Analysis

VThe fixed effects model assumes that there is only one pollutant coefficient for the entire modeled area. The

random effects model assumes that different studies are estimating different parameters; therefore, there may be a

number of different underlying pollutant coefficients. 

9-132

It is important to reiterate that the estimates derived from the long-term exposure studies,

which account for a major share of the economic benefits described in this chapter, are not

affected by the GAM issue. Similarly, the time-series studies employing GLMs or other

parametric methods, as well as case-crossover studies, are not affected. 

Although a broad range of serious health effects has been associated with exposure to

elevated ozone and PM levels (as noted for example in Table 9A-1 and described more fully in

the ozone and PM Criteria Documents (EPA, 1996a, 1996b)), we include only a subset of health

effects in this quantified benefit analysis. Health effects are excluded from this analysis for three

reasons: the possibility of double counting (such as hospital admissions for specific respiratory

diseases); uncertainties in applying effect relationships based on clinical studies to the affected

population; or a lack of an established relationship between the health effect and pollutant in the

published epidemiological literature.

In general, the use of results from more than a single study can provide a more robust

estimate of the relationship between a pollutant and a given health effect. However, there are

often differences between studies examining the same endpoint, making it difficult to pool the

results in a consistent manner. For example, studies may examine different pollutants or

different age groups. For this reason, we consider very carefully the set of studies available

examining each endpoint and select a consistent subset that provides a good balance of

population coverage and match with the pollutant of interest. In many cases, either because of a

lack of multiple studies, consistency problems, or clear superiority in the quality or

comprehensiveness of one study over others, a single published study is selected as the basis of

the effect estimate.

When several effect estimates for a pollutant and a given health endpoint have been selected,

they are quantitatively combined or pooled to derive a more robust estimate of the relationship. 

The benefits Technical Support Document (TSD) completed for the nonroad diesel rulemaking

provides details of the procedures used to combine multiple impact functions (Abt Associates,

2003). In general, we use fixed or random effects models to pool estimates from different

studies of the same endpoint. Fixed effects pooling simply weights each study’s estimate by the

inverse variance, giving more weight to studies with greater statistical power (lower variance). 

Random effects pooling accounts for both within-study variance and between-study variability,

due, for example, to differences in population susceptibility. We use the fixed effects model as

our null hypothesis and then determine whether the data suggest that we should reject this null

hypothesis, in which case we would use the random effects model.v

 Pooled impact functions are
Cost-Benefit Analysis

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used to estimate hospital admissions (PM), school absence days (ozone), lower respiratory

symptoms (PM), asthma exacerbations (PM), and asthma-related emergency room visits (ozone). 

For more details on methods used to pool incidence estimates, see the benefits TSD for the

nonroad diesel rulemaking (Abt Associates, 2003). 

Effect estimates for a pollutant and a given health endpoint are applied consistently across all

locations nationwide. This applies to both impact functions defined by a single effect estimate

and those defined by a pooling of multiple effect estimates. Although the effect estimate may, in

fact, vary from one location to another (e.g., due to differences in population susceptibilities or

differences in the composition of PM), location-specific effect estimates are generally not

available. 

The specific studies from which effect estimates for the primary analysis are drawn are

included in Table 9A-19. 

Premature Mortality. Both long- and short-term exposures to ambient levels of air pollution

have been associated with increased risk of premature mortality. The size of the premature

mortality risk estimates from these epidemiological studies, the serious nature of the effect itself,

and the high monetary value ascribed to prolonging life make premature mortality risk reduction

the most important health endpoint quantified in this analysis. 

Epidemiological analyses have consistently linked air pollution, especially PM, with excess

mortality. Although a number of uncertainties remain to be addressed by continued research

(NRC, 1998), a substantial body of published scientific literature documents the correlation

between elevated PM concentrations and increased mortality rates. Community epidemiological

studies that have used both short-term and long-term exposures and response have been used to

estimate PM/ mortality relationships. Short-term studies use a time-series approach to relate

short-term (often day-to-day) changes in PM concentrations and changes in daily mortality rates

up to several days after a period of elevated PM concentrations. Long-term studies examine the

potential relationship between community-level PM exposures over multiple years and

community-level annual mortality rates. 

Researchers have found statistically significant associations between PM and premature

mortality using both types of studies. In general, the risk estimates based on the long-term

exposure studies are larger than those derived from short-term studies. Cohort analyses are

better able to capture the full public health impact of exposure to air pollution over time (Kunzli,

2001; NRC, 2002). This section discusses some of the issues surrounding the estimation of

premature mortality.
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Over a dozen studies have found significant associations between various measures of

long-term exposure to PM and elevated rates of annual mortality, beginning with Lave and

Seskin (1977). Most of the published studies found positive (but not always statistically

significant) associations with available PM indices such as total suspended particles (TSP).

Particles of different fine particles components (i.e., sulfates), and fine particles, as well as

exploration of alternative model specifications sometimes found inconsistencies (e.g., Lipfert,

[1989]). These early “cross-sectional” studies (e.g., Lave and Seskin [1977]; Ozkaynak and

Thurston [1987]) were criticized for a number of methodological limitations, particularly for

inadequate control at the individual level for variables that are potentially important in causing

mortality, such as wealth, smoking, and diet. 

More recently, several long-term studies have been published that use improved approaches

and appear to be consistent with the earlier body of literature. These new “prospective cohort”

studies reflect a significant improvement over the earlier work because they include individuallevel information with respect to health status and residence. The most extensive study and

analyses has been based on data from two prospective cohort groups, often referred to as the

Harvard “Six-City Study” (Dockery et al., 1993) and the “American Cancer Society or ACS

study” ( Pope et al., 1995 and Pope et al., 2002); these studies have found consistent

relationships between fine particle indicators and premature mortality across multiple locations

in the United States. A third major data set comes from the California based 7th Day Adventist

Study (e.g., Abbey et al., 1999), which reported associations between long-term PM exposure

and premature mortality in men. Results from this cohort, however, have been inconsistent and

the air quality results are not geographically representative of most of the United States. The

Veterans Study was originally designed as a means of assessing the efficacy of anti-hypertensive

drugs in reducing morbidity and mortality in a population with pre-existing high blood pressure

(in this case, male veterans) (Lipfert et al., 2000). Unlike previous long-term analyses, this study

found some associations between premature mortality and ozone but found inconsistent results

for PM indicators. A variety of issues associated with the study design, including sample

representativeness and loss to follow up, make this cohort a poor choice for extrapolating to the

general public. Furthermore, because of the selective nature of the population in the veteran’s

cohort and methodological weaknesses, which may have resulted in estimates of relative risk that

are biased relative to a relative risk for the general population, we have chosen not to include any

effect estimates from the Lipfert et al. (2000) study in our benefits assessment. We note that,

while the PM analyses considering segmented (shorter) time periods such as Lipfert et al. gave

differing results (including significantly negative mortality coefficients for some PM metrics),

when methods consistent with the past studies were used (i.e., many- year average PM

concentrations), similar results were reported: the authors found that “(t)he single-mortalityperiod responses without ecological variables are qualitatively similar to what has been reported

before (SO4 > PM2.5 > PM15).” 
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Table 9A-19. Endpoints and Studies Used to Calculate Total Monetized Health Benefits

Endpoint Pollutant Study Study Population

Premature Mortality

Premature Mortality— Longterm exposure, all-causePM2.5 Pope et al. (2002) >29 years

Premature Mortality— Longterm exposure, all-causePM2.5 Woodruff et al., 1997 Infant (<1 yr)

Chronic Illness

Chronic Bronchitis PM2.5 Abbey, et al. (1995) > 26 years

Non-fatal Heart Attacks PM2.5 Peters et al. (2001) Adults

Hospital Admissions 

Respiratory Ozone Pooled estimate:

Schwartz (1995) - ICD 460-519 (all resp)

Schwartz (1994a, 1994b) - ICD 480-486 (pneumonia)

Moolgavkar et al. (1997) - ICD 480-487 (pneumonia)

Schwartz (1994b) - ICD 491-492, 494-496 (COPD)

Moolgavkar et al. (1997) - ICD 490-496 (COPD) 

> 64 years

Ozone Burnett et al. (2001) < 2 years

PM2.5 Pooled estimate:

Moolgavkar (2003) - ICD 490-496 (COPD)

Ito (2003) - ICD 490-496 (COPD)

> 64 years

PM2.5 Moolgavkar (2000) - ICD 490-496 (COPD) 20-64 years

PM2.5 Ito (2003) - ICD 480-486 (pneumonia) > 64 years

PM2.5 Sheppard, et al. (2003) - ICD 493 (asthma) < 65 years

Cardiovascular PM2.5 Pooled estimate:

Moolgavkar (2003) - ICD 390-429 (all cardiovascular)

Ito (2003) - ICD 410-414, 427-428 (ischemic heart disease,

dysrhythmia, heart failure)

> 64 years

PM2.5 Moolgavkar (2000) - ICD 390-429 (all cardiovascular) 20-64 years

Asthma-Related ER Visits Ozone Pooled estimate: Weisel et al. (1995), Cody et al. (1992),

Stieb et al. (1996)

All ages

PM2.5 Norris et al. (1999) 0-18 years

(continued)
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Given their consistent results and broad geographic coverage, the Six-City and ACS data

have been particularly important in benefits analyses. The credibility of these two studies is

further enhanced by the fact that they were subject to extensive reexamination and reanalysis by

an independent team of scientific experts commissioned by HEI (Krewski et al., 2000). The

final results of the reanalysis were then independently peer reviewed by a Special Panel of the

HEI Health Review Committee. The results of these reanalyses confirmed and expanded those

of the original investigators. This intensive independent reanalysis effort was occasioned both

by the importance of the original findings as well as concerns that the underlying individual

health effects information has never been made publicly available. 

The HEI re-examination lends credibility to the original studies and highlights sensitivities

concerning the relative impact of various pollutants, the potential role of education in mediating

the association between pollution and premature mortality, and the influence of spatial

Table 9A-19. Endpoints and Studies Used to Calculate Total Monetized Health Benefits

(continued)

Endpoint Pollutant Study Study Population

Other Health Endpoints

Acute Bronchitis PM2.5 Dockery et al. (1996) 8-12 years

Upper Respiratory Symptoms PM10 Pope et al. (1991) Asthmatics, 9-11

years

Lower Respiratory

Symptoms

PM2.5 Schwartz and Neas (2000) 7-14 years

Asthma Exacerbations PM2.5 Pooled estimate:

Ostro et al. (2001) (cough, wheeze and shortness of breath)

Vedal et al. (1998) Cough

6-18 yearsa

Work Loss Days PM2.5 Ostro (1987) 18-65 years

School Absence Days Ozone Pooled estimate:

Gilliland et al. (2001)

Chen et al. (2000)

9-10 years

6-11 years

Worker Productivity Ozone Crocker and Horst (1981) Outdoor workers,

18-65

Minor Restricted Activity

Days

PM2.5,

Ozone

Ostro and Rothschild (1989) 18-65 years

a The original study populations were 8 to 13 for the Ostro et al. (2001) study and 6 to 13 for the Vedal et al.

(1998) study. Based on advice from the SAB-HES, we have extended the applied population to 6 to 18,

reflecting the common biological basis for the effect in children in the broader age group.
Cost-Benefit Analysis

W Regarding potential confounding by copollutants, commentors noted that the HEI reanalysis of the ACS study

data for long-term exposure mortality found an association between SO2 and premature mortality and did not find a

strong association between PM2.5 and premature mortality. These commentors suggest that these findings regarding

potential confounding compromise the accuracy of the ACS study. While recognizing the need for research into the

issue of copollutants, including SO2, we disagree with the commentor’s interpretation of the HEI reanalysis. While

this study did find an association between premature mortality and SO2, such an association was also reported for

fine particles and sulfate. In addition, the HEI reanalysis, as well as other studies examining the copollutant issue

(Samet et al., 2000, 2001) have suggested that SO2 might represent a surrogate for ambient PM2.5 concentrations and

is likely associated with sulfate concentrations since it is a precursor. This could partially explain the association

between SO2 and premature mortality found in the HEI reanalysis. Finally, we have updated our methods for

characterizing premature mortality and are now using the Pope et al. 2002 reanalysis of the ACS study data. While

this study continues to find and association between SO2 and cardiovascular mortality, it also finds the strongest

association yet between long term PM2.5 exposure and premature mortality. 

Commentors have also suggested that both the ACS and Six Cities studies provide evidence for confounding by

socio-economic factors in the chronic exposure mortality endpoint. Following recommendations by the SAB-HES,

we have updated our analytical framework to use the Pope et al. 2002 reanalysis of the ACS study data in estimating

long-term exposure mortality. This study incorporates consideration for a variety of potential risk factors including

smoking, educational status and age. With the exception of smoking status, none of the socio-economic factors

examined in the Pope et al. 2002 reanalysis had a significant effect on the association between premature mortality

and PM2.5 exposure. Rather than representing confounders, several of these socio-economic factors, including

educational status, were identified as potential effects modifiers.

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correlation modeling.w Further confirmation and extension of the overall findings using more

recent air quality and a longer follow-up period for the ACS cohort was recently published in the

Journal of the American Medical Association (Pope et al., 2002).

In developing and improving the methods for estimating and valuing the potential reductions

in premature mortality risk over the years, the EPA has consulted with the SAB-HES. That

panel recommended use of long-term prospective cohort studies in estimating premature

mortality risk reduction (EPA-SAB-COUNCIL-ADV-99-005, 1999). This recommendation has

been confirmed by a recent report from the National Research Council, which stated that “it is

essential to use the cohort studies in benefits analysis to capture all important effects from air

pollution exposure” (NAS, 2002, p. 108). In the NRC’s view, compared with the time-series

studies, cohort studies give a more complete assessment of the long-term, cumulative effects of

air pollution. The overall effect estimates may be a combination of effects from long-term

exposure plus some fraction from short-term exposure, but the amount of overlap is unknown. 

Additionally, the SAB recommended emphasis on the ACS study because it includes a much

larger sample size and longer exposure interval and covers more locations (e.g., 50 cities

compared to the Six Cities Study) than other studies of its kind. As explained in the regulatory

impact analysis for the Heavy-Duty Engine/Diesel Fuel rule (EPA, 2000a), more recent EPA

benefits analyses have relied on an improved specification of the ACS cohort data that was

developed in the HEI reanalysis (Krewski et al., 2000). The latest reanalysis of the ACS cohort

data (Pope et al., 2002), provides additional refinements to the analysis of PM-related mortality

by (a) extending the follow-up period for the ACS study subjects to 16 years, which triples the

size of the mortality data set; (b) substantially increasing exposure data, including consideration
Final Regulatory Impact Analysis

X Commentors pointed out that both cardiovascular disease and cancer have latency periods of from 15 to 20

years. Therefore, given that PM concentrations were four times higher in the 1960's compared with the 1980's, we

may be overestimating mortality incidence by using effects estimates, based on the original ACS study data, that do

not sufficiently correct for these higher PM concentrations during earlier segments of the exposure period for target

populations. We recognize that uncertainty is introduced into benefits estimates as a result of both latency and lag

issues. As the SAB-HES pointed out, the lack of detailed temporal exposure data for long term prospective cohort

studies makes it difficult to characterize latency and lag periods and evaluate the importance of temporal variation in

exposure levels. The Pope et al. 2002 reanalysis of the ACS study data, which includes additional years of follow-up

data for the original study population, does suggest that lung cancer may have a longer latency period. However,

inclusion of additional years of exposure data, in the case of lung cancer has served to strengthen, rather than

weaken the association between PM2.5 and premature mortality. By contrast, inclusion of additional follow-on data

for cardiovascular effects has suggested that this endpoint may have a shorter latency/lag period in that the effects

estimate has been reduced and not strengthened with the inclusion of the additional data. 

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for cohort exposure to PM2.5 following implementation of PM2.5 standard in 1999; (c) controlling

for a variety of personal risk factors including occupational exposure and diet; and (d) using

advanced statistical methods to evaluate specific issues that can adversely affect risk estimates

including the possibility of spatial autocorrelation of survival times in communities located near

each other. Because of these refinements, the SAB- HES recommends using the Pope et al.

(2002) study as the basis for the primary mortality estimate for adults and suggests that alternate

estimates of premature mortality generated using other cohort and time series studies could be

included as part of the sensitivity analysis (SAB-HES, 2003).

The SAB-HES also recommended using the estimated relative risks from the Pope et al. 

(2002) study based on the average exposure to PM2.5, measured by the average of two PM2.5

measurements, over the periods 1979-1983, and 1999-2000. In addition to relative risks for allcause mortality, the Pope et al. (2002) study provides relative risks for cardiopulmonary, lung

cancer, and all other cause mortality.x

 Because of concerns regarding the statistical reliability of

the all-other cause mortality relative risk estimates, we calculate premature mortality impacts for

the primary analysis based on the all-cause relative risk. However, we provide separate

estimates of cardiopulmonary and lung cancer deaths to show how these important causes of

death are affected by reductions in PM2.5.

In previous RIAs, infant mortality has not been evaluated as part of the primary analysis

because of uncertainty in the strength of the association between exposure to PM and

postneonatal mortality. Instead, benefits estimates related to reduced infant mortality have been

included as part of the sensitivity analysis for RIAs. However, recently published studies have

strengthened the case for an association between PM exposure and respiratory inflamation and

infection leading to premature mortality in children under 5 years of age. Specifically, the SABHES noted the release of the World Health Organization Global Burden of Disease Study

focusing on ambient air, which cites several recently published time-series studies relating daily

PM exposure to mortality in children (SAB-HES, 2003). The SAB-HES also cites the study by

Belanger et al. (2003) as corroborating findings linking PM exposure to increased respiratory
Cost-Benefit Analysis

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inflamation and infections in children. Recently, a study by Chay and Greenstone (2003) found

that reductions in TSP caused by the recession of 1981-1982 were related to reductions in infant

mortality at the county level. With regard to the cohort study conducted by Woodruff et al.

(1997), the SAB- HES notes several strengths of the study, including the use of a larger cohort

drawn from a large number of metropolitan areas and efforts to control for a variety of individual

risk factors in infants (e.g., maternal educational level, maternal ethnicity, parental marital status,

and maternal smoking status). Based on these findings, the SAB-HES recommends that the EPA

incorporate infant mortality into the primary benefits estimate and that infant mortality be

evaluated using a impact function developed from the Woodruff et al. (1997) study (SAB-HES,

2003).

Chronic Bronchitis. Chronic bronchitis is characterized by mucus in the lungs and a

persistent wet cough for at least 3 months a year for several years in a row. Chronic bronchitis

affects an estimated 5 percent of the U.S. population (American Lung Association, 1999). A

limited number of studies have estimated the impact of air pollution on new incidences of

chronic bronchitis. Schwartz (1993) and Abbey et al.(1995) provide evidence that long-term PM

exposure gives rise to the development of chronic bronchitis in the United States. Because the

Nonroad Diesel regulations are expected to reduce primarily PM2.5, this analysis uses only the

Abbey et al. (1995) study, because it is the only study focusing on the relationship between PM2.5

and new incidences of chronic bronchitis. 

Nonfatal Myocardial Infarctions (heart attacks). Nonfatal heart attacks have been linked 

with short-term exposures to PM2.5 in the United States (Peters et al., 2001) and other countries

(Poloniecki et al. ,1997). We use a recent study by Peters et al. (2001) as the basis for the impact

function estimating the relationship between PM2.5 and nonfatal heart attacks. Peters et al. is the

only available U.S. study to provide a specific estimate for heart attacks. Other studies, such as

Samet et al. (2000) and Moolgavkar et al. (2000), show a consistent relationship between all

cardiovascular hospital admissions, including for nonfatal heart attacks, and PM. Given the

lasting impact of a heart attack on longer-term health costs and earnings, we choose to provide a

separate estimate for nonfatal heart attacks based on the single available U.S. effect estimate. 

The finding of a specific impact on heart attacks is consistent with hospital admission and other

studies showing relationships between fine particles and cardiovascular effects both within and

outside the United States. These studies provide a weight of evidence for this type of effect, as

discussed in the Criteria Document. Several epidemiologic studies (Liao et al., 1999; Gold et al.,

2000; Magari et al., 2001) have shown that heart rate variability (an indicator of how much the

heart is able to speed up or slow down in response to momentary stresses) is negatively related to

PM levels. Heart rate variability is a risk factor for heart attacks and other coronary heart

diseases (Carthenon et a.l, 2002; Dekker et al., 2000; Liao et al., 1997, Tsuji et al., 1996). As

such, significant impacts of PM on heart rate variability are consistent with an increased risk of

heart attacks.
Final Regulatory Impact Analysis

YNote that the Moolgavkar (2000) study has not been updated to reflect the more stringent GAM convergence

criteria. However, given that no other estimates are available for this age group, we have chosen to use the existing

study. Given the very small (<5 percent) difference in the effect estimates for 65 and older cardiovascular hospital

admissions between the original and reanalyzed results, we do not expect there to be much bias introduced by this

choice.

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Hospital and Emergency Room Admissions. Because of the availability of detailed hospital

admission and discharge records, there is an extensive body of literature examining the

relationship between hospital admissions and air pollution. Because of this, many of the hospital

admission endpoints use pooled impact functions based on the results of a number of studies. In

addition, some studies have examined the relationship between air pollution and emergency

room (ER) visits. Because most ER visits do not result in an admission to the hospital (the

majority of people going to the ER are treated and return home), we treat hospital admissions

and ER visits separately, taking account of the fraction of ER visits that are admitted to the

hospital.

Hospital admissions require the patient to be examined by a physician and, on average, may

represent more serious incidents than ER visits. The two main groups of hospital admissions

estimated in this analysis are respiratory admissions and cardiovascular admissions. There is not

much evidence linking ozone or PM with other types of hospital admissions. The only type of

ER visits that have been consistently linked to ozone and PM in the United States are asthmarelated visits. 

To estimate avoided incidences of cardiovascular hospital admissions associated with PM2.5,

we use studies by Moolgavkar (2003) and Ito et al. (2003). There are additional published

studies showing a statistically significant relationship between PM10 and cardiovascular hospital

admissions. However, given that the preliminary control options we are analyzing are expected

to reduce primarily PM2.5, we have chosen to focus on the two studies focusing on PM2.5. Both

of these studies provide an effect estimate for populations over 65, allowing us to pool the

impact functions for this age group. Only Moolgavkar (2000) provided a separate effect estimate

for populations 20 to 64.y Total cardiovascular hospital admissions are thus the sum of the

pooled estimate for populations over 65 and the single study estimate for populations 20 to 64. 

Cardiovascular hospital admissions include admissions for myocardial infarctions. To avoid

double counting benefits from reductions in myocardial infarctions when applying the impact

function for cardiovascular hospital admissions, we first adjusted the baseline cardiovascular

hospital admissions to remove admissions for myocardial infarctions. 

To estimate total avoided incidences of respiratory hospital admissions, we use impact

functions for several respiratory causes, including chronic obstructive pulmonary disease

(COPD), pneumonia, and asthma. As with cardiovascular admissions, there are additional

published studies showing a statistically significant relationship between PM10 and respiratory
Cost-Benefit Analysis

Z

Again, given the very small (<10 percent) difference in the effect estimates for 65 and older COPD hospital

admissions between the original and reanalyzed results, we do not expect there to be much bias introduced by this

choice.

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hospital admissions. We use only those focusing on PM2.5. Both Moolgavkar (2000) and Ito et

al. (2003) provide effect estimates for COPD in populations over 65, allowing us to pool the

impact functions for this group. Only Moolgavkar (2000) provided a separate effect estimate for

populations 20 to 64.z Total COPD hospital admissions are thus the sum of the pooled estimate

for populations over 65 and the single study estimate for populations 20 to 64. Only Ito et al.

(2003) estimated pneumonia, and only for the population 65 and older. In addition, Sheppard et

al. (2003) provided an effect estimate for asthma hospital admissions for populations under age

65. Total avoided incidences of PM-related respiratory-related hospital admissions is the sum of

COPD, pneumonia, and asthma admissions.

To estimate the effects of PM air pollution reductions on asthma-related ER visits, we use the

effect estimate from a study of children 18 and under by Norris et al. (1999). As noted earlier,

there is another study by Schwartz examining a broader age group (less than 65), but the

Schwartz study focused on PM10 rather than PM2.5. We selected the Norris et al. (1999) effect

estimate because it better matched the pollutant of interest. Because children tend to have higher

rates of hospitalization for asthma relative to adults under 65, we will likely capture the majority

of the impact of PM2.5 on asthma ER visits in populations under 65, although there may still be

significant impacts in the adult population under 65. 

To estimate avoided incidences of respiratory hospital admissions associated with ozone, we

use a number of studies examining hospital admissions for a range of respiratory illnesses,

including pneumonia and COPD. Two age groups, adults over 65 and children under 2, are

examined. For adults over 65, Schwartz (1995) provides effect estimates for two different cities

relating ozone and hospital admissions for all respiratory causes (defined as ICD codes 460-519). 

Impact functions based on these studies are pooled first before being pooled with other studies. 

Two studies (Moolgavkar et al., 1997; Schwartz, 1994a) examined ozone and pneumonia

hospital admissions in Minneapolis. One additional study (Schwartz, 1994b) examined ozone

and pneumonia hospital admissions in Detroit. The impact functions for Minneapolis are pooled

together first, and the resulting impact function is then pooled with the impact function for

Detroit. This avoids assigning too much weight to the information coming from one city. For

COPD hospital admissions, there are two available studies, Moolgavkar et al. (1997), conducted

in Minneapolis, and Schwartz (1994b), conducted in Detroit. These two studies are pooled

together. To estimate total respiratory hospital admissions for adults over 65, COPD admissions

are added to pneumonia admissions, and the result is pooled with the Schwartz (1995) estimate

of total respiratory admissions. Burnett et al. (2001) is the only study providing an effect

estimate for respiratory hospital admissions in children under 2.
Final Regulatory Impact Analysis

AASee http://www.nlm.nih.gov/medlineplus/ency/article/000124.htm, accessed January 2002. 

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Acute Health Events and School/Work Loss Days. As indicated in Table 9A-1, in addition to

mortality, chronic illness, and hospital admissions, a number of acute health effects not requiring

hospitalization are associated with exposure to ambient levels of ozone and PM. The sources for

the effect estimates used to quantify these effects are described below. 

Around 4 percent of U.S. children between ages 5 and 17 experience episodes of acute

bronchitis annually (American Lung Association, 2002). Acute bronchitis is characterized by

coughing, chest discomfort, slight fever, and extreme tiredness, lasting for a number of days. 

According to the MedlinePlus medical encyclopedia,aa with the exception of cough, most acute

bronchitis symptoms abate within 7 to 10 days. Incidence of episodes of acute bronchitis in

children between the ages of 5 and 17 are estimated using an effect estimate developed from

Dockery et al. (1996). 

Incidences of lower respiratory symptoms (e.g., wheezing, deep cough) in children aged 7 to

14 are estimated using an effect estimate from Schwartz and Neas (2000). 

Because asthmatics have greater sensitivity to stimuli (including air pollution), children with

asthma can be more susceptible to a variety of upper respiratory symptoms (e.g., runny or stuffy

nose; wet cough; and burning, aching, or red eyes). Research on the effects of air pollution on

upper respiratory symptoms has thus focused on effects in asthmatics. Incidences of upper

respiratory symptoms in asthmatic children aged 9 to 11 are estimated using an effect estimate

developed from Pope et al. (1991). 

Health effects from air pollution can also result in missed days of work (either from personal

symptoms or from caring for a sick family member). Work loss days due to PM2.5 are estimated

using an effect estimate developed from Ostro (1987). Children may also be absent from school

due to respiratory or other diseases caused by exposure to air pollution. Most studies examining

school absence rates have found little or no association with PM2.5, but several studies have

found a significant association between ozone levels and school absence rates. We use two

recent studies, Gilliland et al. (2001) and Chen et al. (2000), to estimate changes in absences

(school loss days) due to changes in ozone levels. The Gilliland et al. study estimated the

incidence of new periods of absence, while the Chen et al. study examined absence on a given

day. We convert the Gilliland estimate to days of absence by multiplying the absence periods by

the average duration of an absence. We estimate an average duration of school absence of 1.6

days by dividing the average daily school absence rate from Chen et al. (2000) and Ransom and

Pope (1992) by the episodic absence rate from Gilliland et al. (2001). This provides estimates

from Chen et al. (2000) and Gilliland et al. (2000), which can be pooled to provide an overall

estimate.
Cost-Benefit Analysis

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Minor restricted activity days (MRAD) result when individuals reduce most usual daily

activities and replace them with less strenuous activities or rest, yet not to the point of missing

work or school. For example, a mechanic who would usually be doing physical work most of

the day will instead spend the day at a desk doing paper and phone work due to difficulty

breathing or chest pain. The effect of PM2.5 and ozone on MRAD is estimated using an effect

estimate derived from Ostro and Rothschild (1989).

In previous RIAs, we have not included estimates of asthma exacerbations in the asthmatic

population in the primary analysis because of concerns over double counting of benefits and

difficulties in differentiating asthma symptoms for purposes of first developing impact functions

that cover distinct endpoints and then establishing the baseline incidence estimates required for

predicting incidence reductions. Concerns over double counting stem from the fact that studies

of the general population also include asthmatics, so estimates based solely on the asthmatic

population cannot be directly added to the general population numbers without double counting. 

In one specific case (upper respiratory symptoms in children), the only study available was

limited to asthmatic children, so this endpoint can be readily included in the calculation of total

benefits. However, other endpoints, such as lower respiratory symptoms and MRADs, are

estimated for the total population that includes asthmatics. Therefore, to simply add predictions

of asthma-related symptoms generated for the population of asthmatics to these total populationbased estimates could result in double counting, especially if they evaluate similar endpoints. 

The SAB-HES, in commenting on the analytical blueprint for 812 acknowledged these

challenges in evaluating asthmatic symptoms and appropriately adding them into the primary

analysis (SAB-HES, 2003). However, despite these challenges, the SAB-HES recommends the

addition of asthma-related symptoms (i.e., asthma exacerbations) to the primary analysis,

provided that the studies use the panel study approach and that they have comparable design and

baseline frequencies in both asthma prevalence and exacerbation rates. Note also, that the SABHES, while supporting the incorporation of asthma exacerbation estimates, does not believe that

the association between ambient air pollution, including ozone and PM, and the new onset of

asthma is sufficiently strong to support inclusion of this asthma-related endpoint in the primary

estimate. For this analysis, we have followed the SAB-HES recommendations regarding asthma

exacerbations in developing the primary estimate. To prevent double counting, we are focusing

the estimation on asthma exacerbations occurring in children and are excluding adults from the

calculation. Asthma exacerbations occurring in adults are assumed to be captured in the general

population endpoints such as work loss days and MRADs. Consequently, if we had included an

adult-specific asthma exacerbation estimate, we would likely double count incidence for this

endpoint. However, because the general population endpoints do not cover children (with regard

to asthmatic effects), an analysis focused specifically on asthma exacerbations for children (6 to

18 years of age) could be conducted without concern for double counting. 
Final Regulatory Impact Analysis

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To characterize asthma exacerbations in children, we selected two studies (Ostro et al., 2001

and Vedal et al., 1998) that followed panels of asthmatic children. Ostro et al. (2001) followed a

group of 138 African-American children in Los Angeles for 13 weeks, recording daily

occurrences of respiratory symptoms associated with asthma exacerbations (e.g., shortness of

breath, wheeze, and cough). This study found a statistically significant association between

PM2.5, measured as a 12-hour average, and the daily prevalence of shortness of breath and

wheeze endpoints. Although the association was not statistically significant for cough, the

results were still positive and close to significance; consequently, we decided to include this

endpoint, along with shortness of breath and wheeze, in generating incidence estimates (see

below). Vedal et al. (1998) followed a group of elementary school children, including 74

asthmatics, located on the west coast of Vancouver Island for 18 months including

measurements of daily peak expiratory flow (PEF) and the tracking of respiratory symptoms

(e.g., cough, phlegm, wheeze, chest tightness) through the use of daily diaries. Association

between PM10 and respiratory symptoms for the asthmatic population was only reported for two

endpoints: cough and PEF. Because it is difficult to translate PEF measures into clearly defined

health endpoints that can be monetized, we only included the cough-related effect estimate from

this study in quantifying asthma exacerbations. We employed the following pooling approach in

combining estimates generated using effect estimates from the two studies to produce a single

asthma exacerbation incidence estimate. First, we pooled the separate incidence estimates for

shortness of breath, wheeze, and cough generated using effect estimates from the Ostro et al.

study, because each of these endpoints is aimed at capturing the same overall endpoint (asthma

exacerbations) and there could be overlap in their predictions. The pooled estimate from the

Ostro et al. study is then pooled with the cough-related estimate generated using the Vedal study. 

The rationale for this second pooling step is similar to the first; both studies are attempting to

quantify the same overall endpoint (asthma exacerbations). 

Additional epidemiological studies are available for characterizing asthma-related health

endpoints (the full list of epidemiological studies considered for modeling asthma-related

incidence are presented in Table 9A-20). However, based on recommendations from the SABHES, we decided not to use these additional studies in generating the primary estimate. In

particular, the Yu et al. (2000) estimates show a much higher baseline incidence rate than other

studies, which may lead to an overstatement of the expected impacts in the overall asthmatic

population. The Whittemore and Korn (1980) study did not use a well-defined endpoint, instead

focusing on a respondent-defined “asthma attack.” Other studies looked at respiratory symptoms

in asthmatics but did not focus on specific exacerbations of asthma. 

9A.3.5.2 Uncertainties Associated with Health Impact Functions

Within-Study Variation. Within-study variation refers to the precision with which a given

study estimates the relationship between air quality changes and health effects. Health effects
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studies provide both a “best estimate” of this relationship plus a measure of the statistical

uncertainty of the relationship. This size of this uncertainty depends on factors such as the

number of subjects studied and the size of the effect being measured. The results of even the

most well-designed epidemiological studies are characterized by this type of uncertainty, though

well-designed studies typically report narrower uncertainty bounds around the best estimate than

do studies of lesser quality. In selecting health endpoints, we generally focus on endpoints

where a statistically significant relationship has been observed in at least some studies, although

we may pool together results from studies with both statistically significant and insignificant

estimates to avoid selection bias.

Across-Study Variation. Across-study variation refers to the fact that different published

studies of the same pollutant/health effect relationship typically do not report identical findings;

in some instances the differences are substantial. These differences can exist even between

equally reputable studies and may result in health effect estimates that vary considerably. 

Across-study variation can result from two possible causes. One possibility is that studies report

different estimates of the single true relationship between a given pollutant and a health effect

due to differences in study design, random chance, or other factors. For example, a hypothetical

study conducted in New York and one conducted in Seattle may report different C-R functions

for the relationship between PM and mortality, in part because of differences between these two

study populations (e.g., demographics, activity patterns). Alternatively, study results may differ

because these two studies are in fact estimating different relationships; that is, the same

reduction in PM in New York and Seattle may result in different reductions in premature

mortality. This may result from a number of factors, such as differences in the relative

sensitivity of these two populations to PM pollution and differences in the composition of PM in

these two locations. In either case, where we identified multiple studies that are appropriate for

estimating a given health effect, we generated a pooled estimate of results from each of those

studies.
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Table 9A-20. Studies Examining Health Impacts in the Asthmatic Population Evaluated

for Use in the Benefits Analysis

Endpoint Definition Pollutant Study Study Population

Asthma Attack Indicators1

Shortness of

breath

Prevalence of shortness of

breath; incidence of

shortness of breath

PM2.5 Ostro et al. (2001) African-American

asthmatics, 8-13

Cough Prevalence of cough;

incidence of cough

PM2.5 Ostro et al. (2001) African-American

asthmatics, 8-13

Wheeze Prevalence of wheeze;

incidence of wheeze

PM2.5 Ostro et al. (2001) African-American

asthmatics, 8-13

Asthma

exacerbation

$1 mild asthma symptom: 

wheeze, cough, chest

tightness, shortness of

breath)

PM10,

PM1.0

Yu et al. (2000) Asthmatics, 5-13

Cough Prevalence of cough PM10 Vedal et al. (1998) Asthmatics, 6-13

Other symptoms/illness endpoints

Upper respiratory

symptoms

$1 of the following: runny

or stuffy nose; wet cough;

burning, aching, or red

eyes 

PM10 Pope et al. (1991) Asthmatics 9-11

Moderate or worse

asthma

Probability of moderate (or

worse) rating of overall

asthma status

PM2.5 Ostro et al. (1991) Asthmatics, all ages

Acute bronchitis $1 episodes of bronchitis

in the past 12 months

PM2.5 McConnell et al.

(1999)

Asthmatics, 9-15*

Phlegm “Other than with colds,

does this child usually

seem congested in the

chest or bring up phlegm?”

PM2.5 McConnell et al.

(1999)

Asthmatics, 9-15*

Asthma attacks Respondent-defined

asthma attack

PM2.5,

ozone

Whittemore and

Korn (1980)

Asthmatics, all ages
Cost-Benefit Analysis

BBAlthough we are not able to use region-specific effect estimates, we use region-specific baseline incidence

rates where available. This allows us to take into account regional differences in health status, which can have a

significant impact on estimated health benefits.

9-147

Application of C-R Relationship Nationwide. Regardless of the use of impact functions

based on effect estimates from a single epidemiological study or multiple studies, each impact

function was applied uniformly throughout the United States to generate health benefit estimates. 

However, to the extent that pollutant/health effect relationships are region-specific, applying a

location-specific impact function at all locations in the United States may result in overestimates

of health effect changes in some locations and underestimates of health effect changes in other

locations. It is not possible, however, to know the extent or direction of the overall effect on

health benefit estimates introduced by application of a single impact function to the entire United

States. This may be a significant uncertainty in the analysis, but the current state of the scientific

literature does not allow for a region-specific estimation of health benefits.bb

Extrapolation of Impact Functions Across Populations. Epidemiological studies often focus

on specific age ranges, either due to data availability limitations (e.g., most hospital admission

data come from Medicare records, which are limited to populations 65 and older), or to simplify

data collection (e.g., some asthma symptom studies focus on children at summer camps, which

usually have a limited age range). We have assumed for the primary analysis that most impact

functions should be applied only to those populations with ages that strictly match the

populations in the underlying epidemiological studies. However, in many cases, there is no

biological reason why the observed health effect would not also occur in other populations

within a reasonable range of the studied population. For example, Dockery et al. (1996)

examined acute bronchitis in children aged 8 to 12. There is no biological reason to expect a

very different response in children aged 6 or 14. By excluding populations outside the range in

the studies, we may be underestimating the health impact in the overall population. In response

to recommendations from the SAB-HES, where there appears to be a reasonable physiological

basis for expanding the age group associated with a specific effect estimate beyond the study

population to cover the full age group (e.g., expanding from a study population of 7 to 11 year

olds to the full 6to 18 year child age group), we have done so and used those expanded incidence

estimates in the primary analysis.

Uncertainties in the PM Mortality Relationship. Health researchers have consistently linked

air pollution, especially PM, with excess mortality. A substantial body of published scientific

literature recognizes a correlation between elevated PM concentrations and increased premature

mortality rates. However, much about this relationship is still uncertain. These uncertainties

include the following:
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C Causality: A substantial number of published epidemiological studies recognize an

association between elevated PM concentrations and increased premature mortality

rates; however, these epidemiological studies are not designed to and cannot

definitively prove causation. For the analysis of the final Nonroad Diesel Engines

rulemaking, we assumed a causal relationship between exposure to elevated PM and

premature mortality, based on the consistent evidence of a correlation between PM

and premature mortality reported in the substantial body of published scientific

literature. 

C Other Pollutants: PM concentrations are correlated with the concentrations of other

criteria pollutants, such as ozone and CO, and it is unclear how much each of these

pollutants may influence mortality rates. Recent studies (see Thurston and Ito

[2001]) have explored whether ozone may have premature mortality effects

independent of PM, but we do not view the evidence as conclusive at this time. The

EPA is currently evaluating the epidemiological literature on the relationship between

ozone and premature mortality and in future regulatory analyses may include ozone

mortality as a separate impact in the primary analysis. To the extent that the effect

estimates we use to evaluate the preliminary control options in fact capture premature

mortality effects of other criteria pollutants besides PM, we may be overestimating

the benefits of reductions in PM. However, we are not providing separate estimates

of the premature mortality benefits from the ozone and CO reductions likely to occur

due to the preliminary control options.

C Shape of the C-R Function: The shape of the true PM premature mortality C-R

function is uncertain, but this analysis assumes the C-R function to have a log-linear

form (as derived from the literature) throughout the relevant range of exposures. If

this is not the correct form of the C-R function, or if certain scenarios predict

concentrations well above the range of values for which the C-R function was fitted,

avoided premature mortality may be mis-estimated.

C Regional Differences: As discussed above, significant variability exists in the results

of different PM/mortality studies. This variability may reflect regionally specific C-R

functions resulting from regional differences in factors such as the physical and

chemical composition of PM. If true regional differences exist, applying the

PM/mortality C-R function to regions outside the study location could result in

mis-estimation of effects in these regions.

C Exposure/Mortality Lags: There is a potential time lag between changes in PM

exposures and changes in premature mortality rates. For the chronic PM/mortality

relationship, the length of the lag is unknown and may be dependent on the kind of

exposure. The existence of such a lag is important for the valuation of premature

mortality incidence because economic theory suggests that benefits occurring in the

future should be discounted. There is no specific scientific evidence of the existence

or structure of a PM effects lag. However, current scientific literature on adverse

health effects similar to those associated with PM (e.g., smoking-related disease) and

the difference in the effect size between chronic exposure studies and daily mortality
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studies suggests that all incidences of premature mortality reduction associated with a

given incremental change in PM exposure probably would not occur in the same year

as the exposure reduction. The smoking-related literature also implies that lags of up

to a few years or longer are plausible. Adopting the lag structure used in the Tier

2/Gasoline Sulfur and Heavy-Duty Engine/Diesel Fuel RIAs and endorsed by the

SAB (EPA-SAB-COUNCIL-ADV-00-001, 1999), we assume a 5-year lag structure. 

This approach assumes that 25 percent of PM-related premature deaths occur in each

of the first 2 years after the exposure and the rest occur in equal parts (approximately

17 percent) in each of the ensuing 3 years.

C Cumulative Effects: As a general point, we attribute the PM/mortality relationship in

the underlying epidemiological studies to cumulative exposure to PM. However, the

relative roles of PM exposure duration and PM exposure level in inducing premature

mortality remain unknown at this time. 

9A.3.5.3 Baseline Health Effect Incidence Rates

The epidemiological studies of the association between pollution levels and adverse health

effects generally provide a direct estimate of the relationship of air quality changes to the relative

risk of a health effect, rather than an estimate of the absolute number of avoided cases. For

example, a typical result might be that a 10 :g/m3

 decrease in daily PM2.5 levels might decrease

hospital admissions by 3 percent. The baseline incidence of the health effect is necessary to

convert this relative change into a number of cases. The baseline incidence rate provides an

estimate of the incidence rate (number of cases of the health effect per year, usually per 10,000

or 100,000 general population) in the assessment location corresponding to baseline pollutant

levels in that location. To derive the total baseline incidence per year, this rate must be

multiplied by the corresponding population number (e.g., if the baseline incidence rate is number

of cases per year per 100,000 population, it must be multiplied by the number of 100,000s in the

population).

Some epidemiological studies examine the association between pollution levels and adverse

health effects in a specific subpopulation, such as asthmatics or diabetics. In these cases, it is

necessary to develop not only baseline incidence rates, but also prevalence rates for the defining

condition (e.g., asthma). For both baseline incidence and prevalence data, we use age-specific

rates where available. Impact functions are applied to individual age groups and then summed

over the relevant age range to provide an estimate of total population benefits.

In most cases, because of a lack of data or methods, we have not attempted to project

incidence rates to future years, instead assuming that the most recent data on incidence rates are

the best prediction of future incidence rates. In recent years, better data on trends in incidence

and prevalence rates for some endpoints, such as asthma, have become available. We are
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working to develop methods to use these data to project future incidence rates. However, for our

primary benefits analysis of the final rule, we will continue to use current incidence rates. 

Table 9A-21 summarizes the baseline incidence data and sources used in the benefits

analysis. In most cases, a single national incidence rate is used, due to a lack of more spatially

disaggregated data. We used national incidence rates whenever possible, because these data are

most applicable to a national assessment of benefits. However, for some studies, the only

available incidence information comes from the studies themselves; in these cases, incidence in

the study population is assumed to represent typical incidence at the national level. However,

for hospital admissions, regional rates are available, and for premature mortality, county-level

data are available. 

Age-, cause-, and county-specific mortality rates were obtained from the U.S. Centers for

Disease Control (CDC) for the years 1996 through 1998. CDC maintains an online data

repository of health statistics, CDC Wonder, accessible at http://wonder.cdc.gov/. The mortality

rates provided are derived from U.S. death records and U.S. Census Bureau postcensal

population estimates. Mortality rates were averaged across 3 years (1996 through 1998) to

provide more stable estimates. When estimating rates for age groups that differed from the CDC

Wonder groupings, we assumed that rates were uniform across all ages in the reported age group. 

For example, to estimate mortality rates for individuals ages 30 and up, we scaled the 25- to 34-

year old death count and population by one-half and then generated a population-weighted

mortality rate using data for the older age groups. Note that we have not projected any changes

in mortality rates over time. We are aware that the U.S. Census projections of total and agespecific mortality rates used in our population projections are based on projections of declines in

national level mortality rates for younger populations and increases in mortality rates for older

populations over time. We are evaluating the most appropriate way to incorporate these

projections of changes in overall national mortality rates into our database of county-level causespecific mortality rates. In the interim, we have not attempted to adjust future mortality rates. 

This will lead to an overestimate of premature mortality benefits in future years, with the

overestimation bias increasing the further benefits are projected into the future. We do not at

this time have a quantified estimate of the magnitude of the potential bias in the years analyzed

for this rule (2010 and 2015).
Table 9A-21. Baseline Incidence Rates and Population Prevalence Rates for Use in Impact

Functions, General Population

Endpoint Parameter

Rates

Value Sourcea

Premature

mortality

Daily or annual mortality

rate

Age, cause, and countyspecific rateCDC Wonder (1996-1998)

Hospitalizations Daily hospitalization rate Age, region, cause-specific

rate

1999 NHDS public use data

filesb

Asthma ER visits Daily asthma ER visit rate Age, Region specific visit

rate

2000 NHAMCS public use data

filesc

; 1999 NHDS public use

data filesb

Chronic

Bronchitis

Annual prevalence rate per

person

Age 18-44

Age 45-64

Age 65 and older

0.0367

0.0505

0.0587

1999 HIS (American Lung

Association, 2002b, Table 4) 

Annual incidence rate per

person

0.00378 Abbey et al. (1993, Table 3)

Nonfatal MI

(heart attacks)

Daily nonfatal myocardial

infarction incidence rate

per person, 18+

Northeast

Midwest

South

West

0.0000159

0.0000135

0.0000111

0.0000100

1999 NHDS public use data

filesb

; adjusted by 0.93 for

prob. of surviving after 28 days

(Rosamond et al., 1999)

Asthma

Exacerbations

Incidence (and prevalence)

among asthmatic African

American children

- daily wheeze

- daily cough

- daily dyspnea

0.076 (0.173)

0.067 (0.145)

0.037 (0.074)

Ostro et al. (2001)

Prevalence among

asthmatic children

- daily wheeze

- daily cough

- daily dyspnea

0.038

0.086

0.045

Vedal et al. (1998)

Acute Bronchitis Annual bronchitis

incidence rate, children

0.043 American Lung Association

(2002a, Table 11)

(continued)
Table 9A-21. Baseline Incidence Rates and Population Prevalence Rates for Use in Impact

Functions, General Population (continued)

Endpoint Parameter

Rates

Value Sourcea

Lower

Respiratory

Symptoms

Daily lower respiratory

symptom incidence among

childrend

0.0012 Schwartz (1994, Table 2)

Upper

Respiratory

Symptoms

Daily upper respiratory

symptom incidence among

asthmatic children

0.3419 Pope et al. (1991, Table 2)

Work Loss Days Daily WLD incidence rate

per person (18-65)

Age 18-24

Age 25-44

Age 45-64

0.00540

0.00678

0.00492

1996 HIS (Adams et al., 1999,

Table 41); U.S. Bureau of the

Census (2000)

Minor Restricted

Activity Days

Daily MRAD incidence

rate per person

0.02137 Ostro and Rothschild (1989, p.

243)

School Loss

Dayse

Daily school absence rate

per person

0.055 National Center for Education

Statistics (1996)

Daily illness-related school

absence rate per persone

Northeast

Midwest

South

Southwest

0.0136

0.0146

0.0142

0.0206

1996 HIS (Adams et al., 1999,

Table 47); estimate of 180

school days per year

Daily respiratory illnessrelated school absence rate

per person

Northeast

Midwest

South

West

0.0073

0.0092

0.0061

0.0124

1996 HIS (Adams et al., 1999,

Table 47); estimate of 180

school days per year

a The following abbreviations are used to describe the national surveys conducted by the National Center for

Health Statistics: HIS refers to the National Health Interview Survey; NHDS—National Hospital

Discharge Survey; NHAMCS—National Hospital Ambulatory Medical Care Survey. b See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHDS/ c See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHAMCS/ d Lower Respiratory Symptoms are defined as $2 of the following: cough, chest pain, phlegm, wheeze e The estimate of daily illness-related school absences excludes school loss days associated with injuries to

match the definition in the Gilliland et al. (2001) study.
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For the set of endpoints affecting the asthmatic population, in addition to baseline incidence

rates, prevalence rates of asthma in the population are needed to define the applicable

population. Table 9A-22 lists the prevalence rates used to determine the applicable population

for asthma symptom endpoints. Note that these reflect current asthma prevalence and assume no

change in prevalence rates in future years. As noted above, we are investigating methods for

projecting asthma prevalence rates in future years. 

9A.3.5.4 Accounting for Potential Health Effect Thresholds 

When conducting clinical (chamber) and epidemiological studies, functions may be

estimated with or without explicit thresholds. Air pollution levels below the threshold are

assumed to have no associated adverse health effects. When a threshold is not assumed, as is

often the case in epidemiological studies, any exposure level is assumed to pose a nonzero risk

of response to at least one segment of the population.

The possible existence of an effect threshold is a very important scientific question and issue

for policy analyses such as this one. The EPA SAB Advisory Council for Clean Air

Compliance, which provides advice and review of the EPA’s methods for assessing the benefits

and costs of the Clean Air Act under Section 812 of the Clean Air Act, has advised the EPA that

there is currently no scientific basis for selecting a threshold of 15 :g/m3

 or any other specific

threshold for the PM-related health effects considered in typical benefits analyses (EPA-SABCouncil-ADV-99-012, 1999). This is supported by the recent literature on health effects of PM

exposure (Daniels et al., 2000; Pope, 2000; Rossi et al., 1999; Schwartz, 2000) that finds in most

cases no evidence of a nonlinear relationship between PM and health effects and certainly does

not find a distinct threshold. The most recent draft of the EPA Air Quality Criteria for

Particulate Matter (EPA, 2004) reports only one study, analyzing data from Phoenix, AZ, that

reported even limited evidence suggestive of a possible threshold for PM2.5 (Smith et al., 2000).
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Recent cohort analyses by HEI (Krewski et al., 2000) and Pope et al. (2002) provide

additional evidence of a quasi-linear relationship between long-term exposures to PM2.5 and

premature mortality. According to the latest draft PM criteria document, Krewski et al. (2000)

found a “visually near-linear relationship between all-cause and cardiopulmonary mortality

residuals and mean sulfate concentrations, near-linear between cardiopulmonary mortality and

mean PM2.5, but a somewhat nonlinear relationship between all-cause mortality residuals and

mean PM2.5 concentrations that flattens above about 20 :g/m3. The confidence bands around the

fitted curves are very wide, however, neither requiring a linear relationship nor precluding a

nonlinear relationship if suggested by reanalyses.” 

The Pope et al. (2002) analysis, which represented an extension to the Krewski et al.

analysis, found that the functions relating PM2.5 and premature mortality “were not significantly

different from linear associations.” 

Daniels et al. (2000) examined the presence of thresholds in PM10 C-R relationships for daily

mortality using the largest 20 U.S. cities for 1987-1994. The results of their models suggest that

the linear model was preferred over spline and threshold models. Thus, these results suggest that

linear models without a threshold may well be appropriate for estimating the effects of PM10 on

the types of premature mortality of main interest. Schwartz and Zanobetti (2000) investigated

Table 9A-22. Asthma Prevalence Rates Used to Estimate Asthmatic Populations in Impact

Functions

Population Group

Asthma Prevalence Rates

Value Source

All Ages 0.0386 American Lung Association (2002c, Table 7)—based on 1999 HIS

<18 0.0527 American Lung Association (2002c, Table 7)—based on 1999 HIS

5-17 0.0567 American Lung Association (2002c, Table 7)—based on 1999 HIS

18-44 0.0371 American Lung Association (2002c, Table 7)—based on 1999 HIS

45-64 0.0333 American Lung Association (2002c, Table 7)—based on 1999 HIS

65+ 0.0221 American Lung Association (2002c, Table 7)—based on 1999 HIS

Male, 27+ 0.021 2000 HIS public use data filesa

African-American, 5 to 17 0.0726 American Lung Association (2002c, Table 9)—based on 1999 HIS

African-American, <18 0.0735 American Lung Association (2002c, Table 9)—based on 1999 HIS

a See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/HIS/2000/
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the presence of threshold by simulation and actual data analysis of 10 U.S. cities. In the analysis

of data from 10 cities, the combined C-R curve did not show evidence of a threshold in the PM10-

mortality associations. Schwartz, Laden, and Zanobetti (2002) investigated thresholds by

combining data on the PM2.5-mortality relationships for six cities and found an essentially linear

relationship down to 2 :g/m3, which is at or below anthropogenic background in most areas. 

They also examined just traffic-related particles and again found no evidence of a threshold. The

Smith et al. (2000) study of associations between daily total mortality and PM2.5 and PM10-2.5 in

Phoenix, AZ, (during 1995-1997) also investigated the possibility of a threshold using a

piecewise linear model and a cubic spline model. For both the piecewise linear and cubic spline

models, the analysis suggested a threshold of around 20 to 25 :g/m3

. However, the C-R curve

for PM2.5 presented in this publication suggests more of a U- or V-shaped relationship than the

usual “hockey stick” threshold relationship.

Based on the recent literature and advice from the SAB, we assume there are no thresholds

for modeling health effects. Although not included in the primary analysis, the potential impact

of a health effects threshold on avoided incidences of PM-related premature mortality is

explored as a key sensitivity analysis and is presented in Appendix 9-B.

Our assumptions regarding thresholds are supported by the National Research Council in its

recent review of methods for estimating the public health benefits of air pollution regulations. In

their review, the National Research Council concluded that there is no evidence for any

departure from linearity in the observed range of exposure to PM10 or PM2.5, nor any indication

of a threshold. They cite the weight of evidence available from both short- and long-term

exposure models and the similar effects found in cities with low and high ambient concentrations

of PM.

9A.3.5.5 Selecting Unit Values for Monetizing Health Endpoints

The appropriate economic value of a change in a health effect depends on whether the health

effect is viewed ex ante (before the effect has occurred) or ex post (after the effect has occurred). 

Reductions in ambient concentrations of air pollution generally lower the risk of future adverse

health affects by a fairly small amount for a large population. The appropriate economic

measure is therefore ex ante WTP for changes in risk. However, epidemiological studies

generally provide estimates of the relative risks of a particular health effect avoided due to a

reduction in air pollution. A convenient way to use this data in a consistent framework is to

convert probabilities to units of avoided statistical incidences. This measure is calculated by

dividing individual WTP for a risk reduction by the related observed change in risk. For

example, suppose a measure is able to reduce the risk of premature mortality from 2 in 10,000 to

1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk reduction is $100, then

the WTP for an avoided statistical premature mortality amounts to $1 million ($100/0.0001
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change in risk). Using this approach, the size of the affected population is automatically taken

into account by the number of incidences predicted by epidemiological studies applied to the

relevant population. The same type of calculation can produce values for statistical incidences

of other health endpoints.

For some health effects, such as hospital admissions, WTP estimates are generally not

available. In these cases, we use the cost of treating or mitigating the effect as a primary

estimate. For example, for the valuation of hospital admissions we use the avoided medical costs

as an estimate of the value of avoiding the health effects causing the admission. These COI

estimates generally understate the true value of reductions in risk of a health effect. They tend to

reflect the direct expenditures related to treatment but not the value of avoided pain and suffering

from the health effect. Table 9A-23 summarizes the value estimates per health effect that we

used in this analysis. Values are presented both for a 1990 base income level and adjusted for

income growth in the two future analysis years, 2010 and 2015. Note that the unit values for

hospital admissions are the weighted averages of the ICD-9 code-specific values for the group of

ICD-9 codes included in the hospital admission categories. A discussion of the valuation

methods for premature mortality and chronic bronchitis is provided here because of the relative

importance of these effects. Discussions of the methods used to value nonfatal myocardial

infarctions (heart attacks) and school absence days are provided because these endpoints have

only recently been added to the analysis and the valuation methods are still under development. 

In the following discussions, unit values are presented at 1990 levels of income for consistency

with previous analyses. Equivalent future year values can be obtained from Table 9A-23.
Table 9A-23. Unit Values Used for Economic Valuation of Health Endpoints (1999$)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Premature Mortality (Value of aStatistical Life)

$5,500,000 $6,600,000 $6,800,000 Point estimate is the mean of a normal distribution with a 95 percent confidence

interval between $1 and $10 million. Confidence interval is based on two metaanalyses of the wage-risk VSL literature. $1 million represents the lower end ofthe interquartile range from the Mrozek and Taylor (2000) meta-analysis. $10million represents the upper end of the interquartile range from the Viscusi andAldy (2003) meta-analysis. The VSL represents the value of a small change inmortality risk aggregated over the affected population.

Chronic Bronchitis (CB) $340,000 $420,000 $430,000 Point estimate is the mean of a generated distribution of WTP to avoid a case of

pollution-related CB. WTP to avoid a case of pollution-related CB is derivedby adjusting WTP (as described in Viscusi et al., 1991) to avoid a severe case ofCB for the difference in severity and taking into account the elasticity of WTPwith respect to severity of CB. 

Nonfatal Myocardial Infarction (heartattack)

3% discount rate

Age 0-24Age 25-44Age 45-54Age 55-65Age 66 and over7% discount rateAge 0-24Age 25-44Age 45-54Age 55-65Age 66 and over

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

$66,902$74,676$78,834

$140,649

$66,902$65,293$73,149$76,871

$132,214

$65,293

Age specific cost-of-illness values reflecting lost earnings and direct medicalcosts over a 5 year period following a non-fatal MI. Lost earnings estimatesbased on Cropper and Krupnick (1990). Direct medical costs based on simpleaverage of estimates from Russell et al. (1998) and Wittels et al. (1990).Lost earnings:

Cropper and Krupnick (1990). Present discounted value of 5 yrs of lostearnings:age of onset: at 3% at 7%

25-44 $8,774 $7,85545-54 $12,932 $11,57855-65 $74,746 $66,920Direct medical expenses: An average of: 

1. Wittels et al., 1990 ($102,658 – no discounting)2. Russell et al., 1998, 5-yr period. ($22,331 at 3% discount rate; $21,113 at 7%discount rate)

(continued)
Table 9A-23. Unit Values Used for Economic Valuation of Health Endpoints (1999$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Hospital AdmissionsChronic Obstructive Pulmonary Disease(COPD)(ICD codes 490-492, 494-496)

$12,378 $12,378 $12,378 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total COPD category illnesses) reported inAgency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Pneumonia(ICD codes 480-487)

$14,693 $14,693 $14,693 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total pneumonia category illnesses)reported in Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Asthma admissions $6,634 $6,634 $6,634 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total asthma category illnesses) reported inAgency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

All Cardiovascular(ICD codes 390-429)

$18,387 $18,387 $18,387 The COI estimates (lost earnings plus direct medical costs) are based on ICD-9

code level information (e.g., average hospital care costs, average length ofhospital stay, and weighted share of total cardiovascular category illnesses)reported in Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Emergency room visits for asthma $286 $286 $286 Simple average of two unit COI values: 

(1) $311.55, from Smith et al., 1997, and (2) $260.67, from Stanford et al., 1999.

(continued)
Table 9A-23. Unit Values Used for Economic Valuation of Health Endpoints (1999$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Respiratory Ailments Not Requiring HospitalizationUpper Respiratory Symptoms (URS) $25 $27 $27 Combinations of the 3 symptoms for which WTP estimates are available that

closely match those listed by Pope, et al. result in 7 different “symptom

clusters,” each describing a “type” of URS. A dollar value was derived for eachtype of URS, using mid-range estimates of WTP (IEc, 1994) to avoid eachsymptom in the cluster and assuming additivity of WTPs. The dollar value forURS is the average of the dollar values for the 7 different types of URS.

Lower Respiratory Symptoms (LRS) $16 $17 $17 Combinations of the 4 symptoms for which WTP estimates are available that

closely match those listed by Schwartz, et al. result in 11 different “symptom

clusters,” each describing a “type” of LRS. A dollar value was derived for eachtype of LRS, using mid-range estimates of WTP (IEc, 1994) to avoid eachsymptom in the cluster and assuming additivity of WTPs. The dollar value forLRS is the average of the dollar values for the 11 different types of LRS.

Asthma Exacerbations $42 $45 $45 Asthma exacerbations are valued at $42 per incidence, based on the mean of

average WTP estimates for the four severity definitions of a “bad asthma day,”described in Rowe and Chestnut (1986). This study surveyed asthmatics toestimate WTP for avoidance of a "bad asthma day,” as defined by the subjects. For purposes of valuation, an asthma attack is assumed to be equivalent to a dayin which asthma is moderate or worse as reported in the Rowe and Chestnut(1986) study.

Acute Bronchitis $360 $380 $390 Assumes a 6 day episode, with daily value equal to the average of low and high

values for related respiratory symptoms recommended in Neumann, et al. 1994.

(continued)
Table 9A-23. Unit Values Used for Economic Valuation of Health Endpoints (1999$) (continued)

Health

Endpoint

Central Estimate of Value Per Statistical Incidence 

Derivation of Estimates

1990 Income

Level

2020 Income

Level

2030 Income

Level

Restricted Activity and Work/School Loss DaysWork Loss Days (WLDs) Variable Variable Variable County-specific median annual wages divided by 50 (assuming 2 weeks of

vacation) and then by 5 – to get median daily wage. U.S. Year 2000 Census,compiled by Geolytics, Inc.

School Absence Days $75 $75 $75 Based on expected lost wages from parent staying home with child. Estimated

daily lost wage (if a mother must stay at home with a sick child) is based on themedian weekly wage among women age 25 and older in 2000 (U.S. CensusBureau, Statistical Abstract of the United States: 2001, Section 12: Labor

Force, Employment, and Earnings, Table No. 621). This median wage is $551. Dividing by 5 gives an estimated median daily wage of $103.The expected loss in wages due to a day of school absence in which the motherwould have to stay home with her child is estimated as the probability that themother is in the workforce times the daily wage she would lose if she missed aday = 72.85% of $103, or $75.

Worker Productivity $0.95 per

worker per 10%

change in ozone

per day

$0.95 per

worker per 10%

change in ozone

per day

$0.95 per

worker per 10%

change in ozone

per day

Based on $68 – median daily earnings of workers in farming, forestry andfishing – from Table 621, Statistical Abstract of the United States (“Full-TimeWage and Salary Workers – Number and Earnings: 1985 to 2000") (Source ofdata in table: U.S. Bureau of Labor Statistics, Bulletin 2307 and Employmentand Earnings, monthly).

Minor Restricted Activity Days(MRADs)

$51 $54 $55 Median WTP estimate to avoid one MRAD from Tolley, et al. (1986) .
Final Regulatory Impact Analysis

CC Commentors have suggested that the VSL used in the Draft RIA may not be appropriate for populations

impacted by the rule in that it may not reflect the risk preference of the of the target population. We recognize the

large amount of uncertainty in the VSL for application to environmental policy. Following SAB-EEAC guidance,

we used a wage-risk-based VSL in valuing premature mortality for the primary estimate in the final rule. In

response to concerns about the range of estimates included in the VSL distribution, we modified the value of life

distribution used for the final rule. As described above, the new mean value of avoiding one statistical death ($5.5

million in 1999 dollars) represents a central value consistent with the range of values suggested by recent metaanalyses of the wage-risk VSL literature. The distribution of VSL used in this RIA is characterized by a confidence

interval from $1 to $10 million, based on two meta-analyses of the wage-risk VSL literature. Following SAB-EEAC

guidance, we discount over the lag period between exposure and premature mortality in valuing reductions in

mortality incidence (see Section 9.A.3.5.2). 

DDThe choice of a discount rate, and its associated conceptual basis, is a topic of ongoing discussion within the

federal government. The EPA adopted a 3 percent discount rate for its base estimate in this case to reflect reliance

on a “social rate of time preference” discounting concept. We have also calculated benefits and costs using a 7

percent rate consistent with an “opportunity cost of capital” concept to reflect the time value of resources directed to

meet regulatory requirements. In this case, the benefit and cost estimates were not significantly affected by the

choice of discount rate. Further discussion of this topic appears in the EPA’s Guidelines for Preparing Economic

Analyses (EPA 2000c).

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9A.3.5.5.1 Valuing Reductions in Premature Mortality Risk. 

We estimate the monetary benefit of reducing premature mortality risk using the “value of

statistical lives saved” (VSL) approach, which is a summary measure for the value of small

changes in premature mortality risk experienced by a large number of people. The VSL

approach applies information from several published value-of-life studies to determine a

reasonable benefit of preventing premature mortality. The mean value of avoiding one statistical

death is assumed to be $5.5 million in 1999 dollars. This represents a central value consistent

with the range of values suggested by recent meta-analyses of the wage-risk VSL literature. The

distribution of VSL is characterized by a confidence interval from $1 to $10 million, based on

two meta-analyses of the wage-risk VSL literature. The $1 million lower confidence limit

represents the lower end of the interquartile range from the Mrozek and Taylor (2000)

meta-analysis. The $10 million upper confidence limit represents the upper end of the

interquartile range from the Viscusi and Aldy (2003) meta-analysis. 

In previous analyses, we used an estimate of mean VSL equal to $6.3 million, based on a

distribution fitted to the estimates from 26 value-of-life studies identified in the Section 812

reports as “applicable to policy analysis.” cc 

As indicated in the previous section on quantification of premature mortality benefits, we

assume for this analysis that some of the incidences of premature mortality related to PM

exposures occur in a distributed fashion over the 5 years following exposure. To take this into

account in the valuation of reductions in premature mortality, we apply 3 percent and 7 percent

discount rates to the value of premature mortality occurring in future years.dd
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The economics literature concerning the appropriate method for valuing reductions in

premature mortality risk is still developing. The adoption of a value for the projected reduction

in the risk of premature mortality is the subject of continuing discussion within the economics

and public policy analysis community. Regardless of the theoretical economic considerations,

the EPA prefers not to draw distinctions in the monetary value assigned to the lives saved even if

they differ in age, health status, socioeconomic status, gender, or other characteristic of the adult

population.

Following the advice of the EEAC of the SAB, the EPA currently uses the VSL approach in

calculating the primary estimate of premature mortality benefits, because we believe this

calculation provides the most reasonable single estimate of an individual’s willingness to trade

off money for reductions in premature mortality risk (EPA-SAB-EEAC-00-013). Although there

are several differences between the labor market studies the EPA uses to derive a VSL estimate

and the PM air pollution context addressed here, those differences in the affected populations

and the nature of the risks imply both upward and downward adjustments. Table 9A-24 lists

some of these differences and the expected effect on the VSL estimate for air pollution-related

premature mortality. In the absence of a comprehensive and balanced set of adjustment factors,

the EPA believes it is reasonable to continue to use the $5.5 million value while acknowledging

the significant limitations and uncertainties in the available literature.

Some economists emphasize that the VSL is not a single number relevant for all situations. 

Indeed, the VSL estimate of $5.5 million (1999 dollars) is itself the central tendency of a number

of estimates of the VSL for some rather narrowly defined populations. When there are

significant differences between the population affected by a particular health risk and the

Table 9A-24. Expected Impact on Estimated Benefits of Premature Mortality Reductions

of Differences Between Factors Used in Developing Applied VSL and Theoretically

Appropriate VSL

Attribute Expected Direction of Bias

Age Uncertain, perhaps overestimate

Life expectancy/health status Uncertain, perhaps overestimate

Attitudes toward risk Underestimate

Income Uncertain

Voluntary vs. Involuntary Uncertain, perhaps underestimate

Catastrophic vs. protracted death Uncertain, perhaps underestimate
Final Regulatory Impact Analysis

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populations used in the labor market studies, as is the case here, some economists prefer to adjust

the VSL estimate to reflect those differences. 

The SAB-EEAC has advised that the EPA “continue to use a wage-risk-based VSL as its

primary estimate, including appropriate sensitivity analyses to reflect the uncertainty of these

estimates,” and that “the only risk characteristic for which adjustments to the VSL can be made

is the timing of the risk” (EPA-SAB-EEAC-00-013, EPA, 2000b). In developing our primary

estimate of the benefits of premature mortality reductions, we have followed this advice and

discounted over the lag period between exposure and premature mortality. 

Uncertainties Specific to Premature Mortality Valuation. The economic benefits associated

with premature mortality are the largest category of monetized benefits of this rule. In addition,

in prior analyses, the EPA has identified valuation of premature mortality benefits as the largest

contributor to the range of uncertainty in monetized benefits (see EPA [1999]). Because of the

uncertainty in estimates of the value of premature mortality avoidance, it is important to

adequately characterize and understand the various types of economic approaches available for

premature mortality valuation. Such an assessment also requires an understanding of how

alternative valuation approaches reflect that some individuals may be more susceptible to air

pollution-induced premature mortality or reflect differences in the nature of the risk presented by

air pollution relative to the risks studied in the relevant economics literature.

The health science literature on air pollution indicates that several human characteristics

affect the degree to which mortality risk affects an individual. For example, some age groups

appear to be more susceptible to air pollution than others (e.g., the elderly and children). Health

status prior to exposure also affects susceptibility. An ideal benefits estimate of mortality risk

reduction would reflect these human characteristics, in addition to an individual’s WTP to

improve one’s own chances of survival plus WTP to improve other individuals’ survival rates. 

The ideal measure would also take into account the specific nature of the risk reduction

commodity that is provided to individuals, as well as the context in which risk is reduced. To

measure this value, it is important to assess how reductions in air pollution reduce the risk of

dying from the time that reductions take effect onward, and how individuals value these changes. 

Each individual’s survival curve, or the probability of surviving beyond a given age, should shift

as a result of an environmental quality improvement. For example, changing the current

probability of survival for an individual also shifts future probabilities of that individual’s

survival. This probability shift will differ across individuals because survival curves depend on

such characteristics as age, health state, and the current age to which the individual is likely to

survive.

Although a survival curve approach provides a theoretically preferred method for valuing the

benefits of reduced risk of premature mortality associated with reducing air pollution, the
Cost-Benefit Analysis

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approach requires a great deal of data to implement. The economic valuation literature does not

yet include good estimates of the value of this risk reduction commodity. As a result, in this

study we value avoided premature mortality risk using the VSL approach.

Other uncertainties specific to premature mortality valuation include the following:

C Across-study variation: There is considerable uncertainty as to whether the available

literature on VSL provides adequate estimates of the VSL saved by air pollution

reduction. Although there is considerable variation in the analytical designs and data

used in the existing literature, the majority of the studies involve the value of risks to

a middle-aged working population. Most of the studies examine differences in wages

of risky occupations, using a wage-hedonic approach. Certain characteristics of both

the population affected and the mortality risk facing that population are believed to

affect the average WTP to reduce the risk. The appropriateness of a distribution of

WTP based on the current VSL literature for valuing the premature mortality-related

benefits of reductions in air pollution concentrations therefore depends not only on

the quality of the studies (i.e., how well they measure what they are trying to

measure), but also on the extent to which the risks being valued are similar and the

extent to which the subjects in the studies are similar to the population affected by

changes in pollution concentrations. 

C Level of risk reduction: The transferability of estimates of the VSL from the wagerisk studies to the context of the this rulemaking analysis rests on the assumption that,

within a reasonable range, WTP for reductions in mortality risk is linear in risk

reduction. For example, suppose a study estimates that the average WTP for a

reduction in mortality risk of 1/100,000 is $50, but that the actual mortality risk

reduction resulting from a given pollutant reduction is 1/10,000. If WTP for

reductions in mortality risk is linear in risk reduction, then a WTP of $50 for a

reduction of 1/100,000 implies a WTP of $500 for a risk reduction of 1/10,000

(which is 10 times the risk reduction valued in the study). Under the assumption of

linearity, the estimate of the VSL does not depend on the particular amount of risk

reduction being valued. This assumption has been shown to be reasonable provided

the change in the risk being valued is within the range of risks evaluated in the

underlying studies (Rowlatt et al., 1998).

C Voluntariness of risks evaluated: Although job-related mortality risks may differ in

several ways from air pollution-related mortality risks, the most important difference

may be that job-related risks are incurred voluntarily, or generally assumed to be,

whereas air pollution-related risks are incurred involuntarily. Some evidence

suggests that people will pay more to reduce involuntarily incurred risks than risks

incurred voluntarily. If this is the case, WTP estimates based on wage-risk studies

may understate WTP to reduce involuntarily incurred air pollution-related mortality

risks.
Final Regulatory Impact Analysis

9-164

C Sudden versus protracted death: A final important difference related to the nature of

the risk may be that some workplace mortality risks tend to involve sudden,

catastrophic events, whereas air pollution-related risks tend to involve longer periods

of disease and suffering prior to death. Some evidence suggests that WTP to avoid a

risk of a protracted death involving prolonged suffering and loss of dignity and

personal control is greater than the WTP to avoid a risk (of identical magnitude) of

sudden death. To the extent that the mortality risks addressed in this assessment are

associated with longer periods of illness or greater pain and suffering than are the

risks addressed in the valuation literature, the WTP measurements employed in the

present analysis would reflect a downward bias.

C Self-selection and skill in avoiding risk. Recent research (Shogren et al., 2002)

suggests that VSL estimates based on hedonic wage studies may overstate the

average value of a risk reduction. This is based on the fact that the risk-wage tradeoff

revealed in hedonic studies reflects the preferences of the marginal worker (i.e., that

worker who demands the highest compensation for his risk reduction). This worker

must have either higher risk, lower risk tolerance, or both. However, the risk estimate

used in hedonic studies is generally based on average risk, so the VSL may be

upwardly biased because the wage differential and risk measures do not match.

For more discussion, see Appendix 9B.

9A.3.5.5.2 Valuing Reductions in the Risk of Chronic Bronchitis. 

The best available estimate of WTP to avoid a case of chronic bronchitis comes from Viscusi

et al. (1991). The Viscusi et al. study, however, describes a severe case of chronic bronchitis to

the survey respondents. We therefore employ an estimate of WTP to avoid a pollution-related

case of chronic bronchitis, based on adjusting the Viscusi et al. (1991) estimate of the WTP to

avoid a severe case. This is done to account for the likelihood that an average case of pollutionrelated chronic bronchitis is not as severe. The adjustment is made by applying the elasticity of

WTP with respect to severity reported in the Krupnick and Cropper (1992) study. Details of this

adjustment procedure are provided in the benefits TSD for the nonroad diesel rulemaking (Abt

Associates, 2003).

We use the mean of a distribution of WTP estimates as the central tendency estimate of WTP

to avoid a pollution-related case of chronic bronchitis in this analysis. The distribution

incorporates uncertainty from three sources: the WTP to avoid a case of severe chronic

bronchitis, as described by Viscusi et al.; the severity level of an average pollution-related case

of chronic bronchitis (relative to that of the case described by Viscusi et al.); and the elasticity

of WTP with respect to severity of the illness. Based on assumptions about the distributions of

each of these three uncertain components, we derive a distribution of WTP to avoid a pollutionrelated case of chronic bronchitis by statistical uncertainty analysis techniques. The expected
Cost-Benefit Analysis

9-165

value (i.e., mean) of this distribution, which is about $331,000 (2000$), is taken as the central

tendency estimate of WTP to avoid a PM-related case of chronic bronchitis.

9A.3.5.5.3 Valuing Reductions in Non-Fatal Myocardial Infarctions (Heart Attacks). 

The Agency has recently incorporated into its analyses the impact of air pollution on the

expected number of nonfatal heart attacks, although it has examined the impact of reductions in

other related cardiovascular endpoints. We were not able to identify a suitable WTP value for

reductions in the risk of nonfatal heart attacks. Instead, we propose a COI unit value with two

components: the direct medical costs and the opportunity cost (lost earnings) associated with the

illness event. Because the costs associated with an myocardial infarction extend beyond the

initial event itself, we consider costs incurred over several years. Using age-specific annual lost

earnings estimated by Cropper and Krupnick (1990) and a 3 percent discount rate, we estimated

a present discounted value in lost earnings (in 2000$) over 5 years due to an myocardial

infarction of $8,774 for someone between the ages of 25 and 44, $12,932 for someone between

the ages of 45 and 54, and $74,746 for someone between the ages of 55 and 65. The

corresponding age-specific estimates of lost earnings (in 2000$) using a 7 percent discount rate

are $7,855, $11,578, and $66,920, respectively. Cropper and Krupnick (1990) do not provide

lost earnings estimates for populations under 25 or over 65. As such, we do not include lost

earnings in the cost estimates for these age groups.

We found three possible sources in the literature of estimates of the direct medical costs of

myocardial infarction:

C Wittels et al. (1990) estimated expected total medical costs of myocardial infarction

over 5 years to be $51,211 (in 1986$) for people who were admitted to the hospital

and survived hospitalization. (There does not appear to be any discounting used.) 

Wittels et al. was used to value coronary heart disease in the 812 Retrospective

Analysis of the Clean Air Act. Using the CPI-U for medical care, the Wittels

estimate is $109,474 in year 2000$. This estimated cost is based on a medical cost

model, which incorporated therapeutic options, projected outcomes, and prices (using

“knowledgeable cardiologists” as consultants). The model used medical data and

medical decision algorithms to estimate the probabilities of certain events and/or

medical procedures being used. The authors note that the average length of

hospitalization for acute myocardial infarction has decreased over time (from an

average of 12.9 days in 1980 to an average of 11 days in 1983). Wittels et al. used 10

days as the average in their study. It is unclear how much further the length of stay 

for myocardial infarction may have decreased from 1983 to the present. The average

length of stay for ICD code 410 (myocardial infarction) in the year-2000 AHQR

HCUP database is 5.5 days. However, this may include patients who died in the

hospital (not included among our nonfatal myocardial infarction cases), whose length

of stay was therefore substantially shorter than it would be if they had not died.
Final Regulatory Impact Analysis

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C Eisenstein et al. (2001) estimated 10-year costs of $44,663 in 1997$, or $49,651 in

2000$ for myocardial infarction patients, using statistical prediction (regression)

models to estimate inpatient costs. Only inpatient costs (physician fees and hospital

costs) were included.

C Russell et al. (1998) estimated first-year direct medical costs of treating nonfatal

myocardial infarction of $15,540 (in 1995$) and $1,051 annually thereafter. 

Converting to year 2000$, that would be $23,353 for a 5-year period (without

discounting) or $29,568 for a 10-year period.

In summary, the three different studies provided significantly different values (see Table 9A25).

As noted above, the estimates from these three studies are substantially different, and we

have not adequately resolved the sources of differences in the estimates. Because the wagerelated opportunity cost estimates from Cropper and Krupnick (1990) cover a 5-year period, we

use estimates for medical costs that similarly cover a 5-year period (i.e., estimates from Wittels

et al. (1990) and Russell et al. (1998). We use a simple average of the two 5-year estimates, or

$65,902, and add it to the 5-year opportunity cost estimate. The resulting estimates are given in

Table 9A-26.
Cost-Benefit Analysis

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9A.3.5.5.4 Valuing Reductions in School Absence Days. 

School absences associated with exposure to ozone are likely to be due to respiratory-related

symptoms and illnesses. Because the respiratory symptom and illness endpoints we are

including are all PM-related rather than ozone-related, we do not have to be concerned about

double counting of benefits if we aggregate the benefits of avoiding ozone-related school

absences with the benefits of avoiding PM-related respiratory symptoms and illnesses. 

One possible approach to valuing a school absence is using a parental opportunity cost

approach. This method requires two steps: estimate the probability that, if a school child stays

home from school, a parent will have to stay home from work to care for the child, and value the

Table 9A-25. Alternative Direct Medical Cost of Illness Estimates for Nonfatal Heart

Attacks

Study Direct Medical Costs (2000$) Over an x-Year Period, for x =

Wittels et al. (1990) $109,474a 5

Russell et al. (1998) $22,331b 5

Eisenstein et al. (2001) $49,651b 10

Russell et al. (1998) $27,242b 10

a Wittels et al. did not appear to discount costs incurred in future years. b Using a 3 percent discount rate.

Table 9A-26. Estimated Costs Over a 5-Year Period (in 2000$) of a Nonfatal Myocardial

Infarction

Age Group Opportunity Cost Medical Costa Total Cost

0 - 24 $0 $65,902 $65,902

25-44 $8,774b $65,902 $74,676

45 - 54 $12,253b $65,902 $78,834

55 - 65 $70,619b $65,902 $140,649

> 65 $0 $65,902 $65,902

a An average of the 5-year costs estimated by Wittels et al., 1990, and Russell et al., 1998. b From Cropper and Krupnick, 1990, using a 3 percent discount rate.
Final Regulatory Impact Analysis

9-168

lost productivity at the person’s wage. Using this method, we would estimate the proportion of

families with school-age children in which both parents work, and value a school loss day as the

probability of a work loss day resulting from a school loss day (i.e., the proportion of households

with school-age children in which both parents work) times some measure of lost wages

(whatever measure we use to value work loss days). There are three significant problems with

this method, however. First, it omits WTP to avoid the symptoms/illness that resulted in the

school absence. Second, it effectively gives zero value to school absences which do not result in

a work loss day (unless we derive an alternative estimate of the value of the parent’s time for

those cases in which the parent is not in the labor force). Third, it makes an assumption about

the gender of the parent that would miss work. We are investigating approaches using WTP for

avoid the symptoms/illnesses causing the absence. In the interim, we will use the parental

opportunity cost approach.

For the parental opportunity cost approach, we make an explicit, lower assumption that in

married households with two working parents, the female parent will stay home with a sick

child. From the U.S. Census Bureau, Statistical Abstract of the United States: 2001, we

obtained (1) the numbers of single, married, and “other” (i.e., widowed, divorced, or separated)

women with children in the workforce, and (2) the rates of participation in the workforce of

single, married, and “other” women with children. From these two sets of statistics, we inferred

the numbers of single, married, and “other” women with children, and the corresponding

percentages. These percentages were used to calculate a weighted average participation rate, as

shown in Table 9A-27. We do not take into account that many single and “other” women with

children may lose their jobs if they are repeatedly absent due to their children’s illnesses.

Our estimated daily lost wage (if a mother must stay at home with a sick child) is based on

the median weekly wage among women age 25 and older in 2000 (U.S. Census Bureau,

Statistical Abstract of the United States: 2001, Section 12: Labor Force, Employment, and

Earnings, Table No. 621). This median wage is $551. Dividing by 5 gives an estimated median

daily wage of $103.
Cost-Benefit Analysis

EEIn a very recent article, Hall, Brajer, and Lurmann (2003) use a similar methodology to derive a mid-estimate

value per school absence day for California of between $70 and $81, depending on differences in incomes between

three counties in California. Our national average estimate of $75 per absence is consistent with these published

values.

9-169

The expected loss in wages due to a day of school absence in which the mother would have

to stay home with her child is estimated as the probability that the mother is in the workforce

times the daily wage she would lose if she missed a day = 72.85% of $103, or $75.ee

9A.3.5.6 Unquantified Health Effects

In addition to the health effects discussed above, there is emerging evidence that human

exposure to ozone may be associated with premature mortality (Ito and Thurston, 1996; Samet,

et al. 1997, Ito and Thurston, 2001), PM and ozone with increased emergency room visits for

non-asthma respiratory causes (US EPA, 1996a; 1996b), ozone with impaired airway

responsiveness (US EPA, 1996a), ozone with increased susceptibility to respiratory infection

(US EPA, 1996a), ozone with acute inflammation and respiratory cell damage (US EPA, 1996a),

ozone and PM with premature aging of the lungs and chronic respiratory damage (US EPA,

1996a; 1996b), ozone with onset of asthma in exercising children (McConnell et al. 2002), and

PM with reduced heart rate variability and other changes in cardiac function. An improvement

in ambient PM and ozone air quality may reduce the number of incidences within each effect

category that the U.S. population would experience. Although these health effects are believed

Table 9A-27. Women with Children: Number and Percent in the Labor Force, 2000, and

Weighted Average Participation Ratea

Number (in

millions) in

Labor Force

(1)

Participation

Rate

(2)

Implied Total

Number in

Population (in

millions)

(3) = (1)/(2)

Implied

Percent in

Population

(4)

Weighted

Average

Participation

Rate [=sum

(2)*(4) over

rows] 

Single 3.1 73.9% 4.19 11.84%

Married 18.2 70.6% 25.78 72.79%

Otherb 4.5 82.7% 5.44 15.36%

Total: 35.42

72.85%

a Data in columns (1) and (2) are from U.S. Census Bureau, Statistical Abstract of the United States: 2001,

Section 12: Labor Force, Employment, and Earnings, Table No. 577. b Widowed, divorced, or separated.
Final Regulatory Impact Analysis

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to be PM or ozone-induced, effect estimates are not available for quantifying the benefits

associated with reducing these effects. The inability to quantify these effects lends a downward

bias to the monetized benefits presented in this analysis.

9A.3.6 Human Welfare Impact Assessment

PM and ozone have numerous documented effects on environmental quality that affect

human welfare. These welfare effects include direct damages to property, either through impacts

on material structures or by soiling of surfaces, direct economic damages in the form of lost

productivity of crops and trees, indirect damages through alteration of ecosystem functions, and

indirect economic damages through the loss in value of recreational experiences or the existence

value of important resources. EPA’s Criteria Documents for PM and ozone list numerous

physical and ecological effects known to be linked to ambient concentrations of these pollutants

(US EPA, 1996a; 1996b). This section describes individual effects and how we quantify and

monetize them. These effects include changes in commercial crop and forest yields, visibility,

and nitrogen deposition to estuaries.

9A.3.6.1 Visibility Benefits

Changes in the level of ambient particulate matter caused by the reduction in emissions from

the preliminary control options will change the level of visibility in much of the U.S. Visibility

directly affects people’s enjoyment of a variety of daily activities. Individuals value visibility

both in the places they live and work, in the places they travel to for recreational purposes, and at

sites of unique public value, such as the Grand Canyon. This section discusses the measurement

of the economic benefits of visibility.

It is difficult to quantitatively define a visibility endpoint that can be used for valuation. 

Increases in PM concentrations cause increases in light extinction. Light extinction is a measure

of how much the components of the atmosphere absorb light. More light absorption means that

the clarity of visual images and visual range is reduced, ceteris paribus. Light absorption is a

variable that can be accurately measured. Sisler (1996) created a unitless measure of visibility

based directly on the degree of measured light absorption called the deciview. Deciviews are

standardized for a reference distance in such a way that one deciview corresponds to a change of

about 10 percent in available light. Sisler characterized a change in light extinction of one

deciview as “a small but perceptible scenic change under many circumstances.” Air quality
Cost-Benefit Analysis

FF A change of less than 10 percent in the light extinction budget represents a measurable improvement in

visibility, but may not be perceptible to the eye in many cases. Some of the average regional changes in visibility

are less than one deciview (i.e. less than 10 percent of the light extinction budget), and thus less than perceptible. 

However, this does not mean that these changes are not real or significant. Our assumption is then that individuals

can place values on changes in visibility that may not be perceptible. This is quite plausible if individuals are aware

that many regulations lead to small improvements in visibility which when considered together amount to

perceptible changes in visibility.

GG The Clean Air Act designates 156 national parks and wilderness areas as Class I areas for visibility

protection.

HH For details of the visibility estimates discussed in this chapter, please refer to the benefits technical support

document for this RIA (Abt Associates 2003).

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models were used to predict the change in visibility, measured in deciviews, of the areas affected

by the preliminary control options.ff

EPA considers benefits from two categories of visibility changes: residential visibility and

recreational visibility. In both cases economic benefits are believed to consist of both use values

and non-use values. Use values include the aesthetic benefits of better visibility, improved road

and air safety, and enhanced recreation in activities like hunting and birdwatching. Non-use

values are based on people’s beliefs that the environment ought to exist free of human-induced

haze. Non-use values may be a more important component of value for recreational areas,

particularly national parks and monuments.

Residential visibility benefits are those that occur from visibility changes in urban, suburban,

and rural areas, and also in recreational areas not listed as federal Class I areas.gg For the

purposes of this analysis, recreational visibility improvements are defined as those that occur

specifically in federal Class I areas. A key distinction between recreational and residential

benefits is that only those people living in residential areas are assumed to receive benefits from

residential visibility, while all households in the U.S. are assumed to derive some benefit from

improvements in Class I areas. Values are assumed to be higher if the Class I area is located

close to their home.hh

Only two existing studies provide defensible monetary estimates of the value of visibility

changes. One is a study on residential visibility conducted in 1990 (McClelland, et. al., 1993)

and the other is a 1988 survey on recreational visibility value (Chestnut and Rowe, 1990a;

1990b). Both utilize the contingent valuation method. There has been a great deal of

controversy and significant development of both theoretical and empirical knowledge about how

to conduct CV surveys in the past decade. In EPA’s judgment, the Chestnut and Rowe study

contains many of the elements of a valid CV study and is sufficiently reliable to serve as the
Final Regulatory Impact Analysis

II An SAB advisory letter indicates that“many members of the Council believe that the Chestnut and Rowe

study is the best available.” (EPA-SAB-COUNCIL-ADV-00-002, 1999) However, the committee did not formally

approve use of these estimates because of concerns about the peer-reviewed status of the study. EPA believes the

study has received adequate review and has been cited in numerous peer-reviewed publications (Chestnut and

Dennis, 1997).

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basis for monetary estimates of the benefits of visibility changes in recreational areas.ii This

study serves as an essential input to our estimates of the benefits of recreational visibility

improvements in the primary benefits estimates. Consistent with SAB advice, EPA has

designated the McClelland, et al. study as significantly less reliable for regulatory benefit-cost

analysis, although it does provide useful estimates on the order of magnitude of residential

visibility benefits (EPA-SAB-COUNCIL-ADV-00-002, 1999). Residential visibility benefits are

therefore only included as a sensitivity estimate in Appendix 9-B.

The Chestnut and Rowe study measured the demand for visibility in Class I areas managed

by the National Park Service (NPS) in three broad regions of the country: California, the

Southwest, and the Southeast. Respondents in five states were asked about their willingness to

pay to protect national parks or NPS-managed wilderness areas within a particular region. The

survey used photographs reflecting different visibility levels in the specified recreational areas. 

The visibility levels in these photographs were later converted to deciviews for the current

analysis. The survey data collected were used to estimate a WTP equation for improved

visibility. In addition to the visibility change variable, the estimating equation also included

household income as an explanatory variable.

The Chestnut and Rowe study did not measure values for visibility improvement in Class I

areas outside the three regions. Their study covered 86 of the 156 Class I areas in the U.S. We

can infer the value of visibility changes in the other Class I areas by transferring values of

visibility changes at Class I areas in the study regions. However, these values are not as

defensible and are thus presented only as an alternative calculation in Table 9A-25. A complete

description of the benefits transfer method used to infer values for visibility changes in Class I

areas outside the study regions is provided in the benefits TSD for this RIA (Abt Associates,

2003).

The estimated relationship from the Chestnut and Rowe study is only directly applicable to

the populations represented by survey respondents. EPA used benefits transfer methodology to

extrapolate these results to the population affected by the Nonroad Diesel Engines rule. A

general willingness to pay equation for improved visibility (measured in deciviews) was

developed as a function of the baseline level of visibility, the magnitude of the visibility

improvement, and household income. The behavioral parameters of this equation were taken

from analysis of the Chestnut and Rowe data. These parameters were used to calibrate WTP for

the visibility changes resulting from the Nonroad Diesel Engines rule. The method for
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developing calibrated WTP functions is based on the approach developed by Smith, et al. (2002).

Available evidence indicates that households are willing to pay more for a given visibility

improvement as their income increases (Chestnut, 1997). The benefits estimates here

incorporate Chestnut’s estimate that a 1 percent increase in income is associated with a 0.9

percent increase in WTP for a given change in visibility.

Using the methodology outlined above, EPA estimates that the total WTP for the visibility

improvements in California, Southwestern, and Southeastern Class I areas brought about by the

Nonroad Diesel Engines rule is $2.2 billion. This value includes the value to households living

in the same state as the Class I area as well as values for all households in the U.S. living outside

the state containing the Class I area, and the value accounts for growth in real income. We

examine the impact of expanding the visibility benefits analysis to other areas of the country in a

sensitivity analysis presented in Appendix 9-B.

One major source of uncertainty for the visibility benefit estimate is the benefits transfer

process used. Judgments used to choose the functional form and key parameters of the

estimating equation for willingness to pay for the affected population could have significant

effects on the size of the estimates. Assumptions about how individuals respond to changes in

visibility that are either very small, or outside the range covered in the Chestnut and Rowe study,

could also affect the results.

9A.3.6.2 Agricultural, Forestry and other Vegetation Related Benefits

The Ozone Criteria Document notes that “ozone affects vegetation throughout the United

States, impairing crops, native vegetation, and ecosystems more than any other air pollutant”

(US EPA, 1996). Changes in ground level ozone resulting from the preliminary control options

are expected to impact crop and forest yields throughout the affected area.

Well-developed techniques exist to provide monetary estimates of these benefits to

agricultural producers and to consumers. These techniques use models of planting decisions,

yield response functions, and agricultural products supply and demand. The resulting welfare

measures are based on predicted changes in market prices and production costs. Models also

exist to measure benefits to silvicultural producers and consumers. However, these models have

not been adapted for use in analyzing ozone related forest impacts. As such, our analysis

provides monetized estimates of agricultural benefits, and a discussion of the impact of ozone

changes on forest productivity, but does not monetize commercial forest related benefits.
Final Regulatory Impact Analysis

JJAGSIM© is designed to forecast agricultural supply and demand out to 2010. We were not able to adapt the

model to forecast out to 2030. Instead, we apply percentage increases in yields from decreased ambient ozone levels

in 2030 to 2010 yield levels, and input these into an agricultural sector model held at 2010 levels of demand and

supply. It is uncertain what impact this assumption will have on net changes in surplus.

KK Agricultural benefits differ from other health and welfare endpoints in the length of the assumed ozone

season. For agriculture, the ozone season is assumed to extend from April to September. This assumption is made

to ensure proper calculation of the ozone statistic used in the exposure-response functions. The only crop affected

by changes in ozone during April is winter wheat.

LL The total value for these crops in 1998 was $47 billion. 

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9A.3.6.2.1 Agricultural Benefits

Laboratory and field experiments have shown reductions in yields for agronomic crops

exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g., cotton and wheat). 

The most extensive field experiments, conducted under the National Crop Loss Assessment

Network (NCLAN) examined 15 species and numerous cultivars. The NCLAN results show that

“several economically important crop species are sensitive to ozone levels typical of those found

in the U.S.” (US EPA, 1996). In addition, economic studies have shown a relationship between

observed ozone levels and crop yields (Garcia, et al., 1986). The economic value associated with

varying levels of yield loss for ozone-sensitive commodity crops is analyzed using the AGSIM©

agricultural benefits model (Taylor, et al., 1993). AGSIM© is an econometric-simulation model

that is based on a large set of statistically estimated demand and supply equations for agricultural

commodities produced in the United States. The model is capable of analyzing the effects of

changes in policies (in this case, the implementation of the Nonroad Diesel Engines rule) that

affect commodity crop yields or production costs.jj

The measure of benefits calculated by the model is the net change in consumer and producer

surplus from baseline ozone concentrations to the ozone concentrations resulting from

attainment of particular standards. Using the baseline and post-control equilibria, the model

calculates the change in net consumer and producer surplus on a crop-by-crop basis.kk Dollar

values are aggregated across crops for each standard. The total dollar value represents a measure

of the change in social welfare associated with the Nonroad Diesel Engines rule.

The model employs biological exposure-response information derived from controlled

experiments conducted by the NCLAN (NCLAN, 1996). For the purpose of our analysis, we

analyze changes for the six most economically significant crops for which C-R functions are

available: corn, cotton, peanuts, sorghum, soybean, and winter wheat.ll For some crops there are

multiple C-R functions, some more sensitive to ozone and some less. Our base estimate assumes

that crops are evenly mixed between relatively sensitive and relatively insensitive varieties. 

Sensitivity to this assumption is tested in Appendix 9-B.
Cost-Benefit Analysis

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9A.3.6.2.2 Forestry Benefits

Ozone also has been shown conclusively to cause discernible injury to forest trees (US EPA,

1996; Fox and Mickler, 1996). In our previous analysis of the HD Engine/Diesel Fuel rule, we

were able to quantify the effects of changes in ozone concentrations on tree growth for a limited

set of species. Due to data limitations, we were not able to quantify such impacts for this

analysis. We plan to assess both physical impacts on tree growth and the economic value of

those phyisical impacts in our analysis of the final rule. We will use econometric models of

forest product supply and demand to estimate changes in prices, producer profits and consumer

surplus. 

9A.3.6.2.3 Other Vegetation Effects

An additional welfare benefit expected to accrue as a result of reductions in ambient ozone

concentrations in the U.S. is the economic value the public receives from reduced aesthetic

injury to forests. There is sufficient scientific information available to reliably establish that

ambient ozone levels cause visible injury to foliage and impair the growth of some sensitive

plant species (US EPA, 1996c, p. 5-521). However, present analytic tools and resources

preclude EPA from quantifying the benefits of improved forest aesthetics.

Urban ornamentals represent an additional vegetation category likely to experience some

degree of negative effects associated with exposure to ambient ozone levels and likely to impact

large economic sectors. In the absence of adequate exposure-response functions and economic

damage functions for the potential range of effects relevant to these types of vegetation, no direct

quantitative economic benefits analysis has been conducted. It is estimated that more than $20

billion (1990 dollars) are spent annually on landscaping using ornamentals (Abt Associates,

1995), both by private property owners/tenants and by governmental units responsible for public

areas. This is therefore a potentially important welfare effects category. However, information

and valuation methods are not available to allow for plausible estimates of the percentage of

these expenditures that may be related to impacts associated with ozone exposure.

The nonroad diesel standards, by reducing NOX emissions, will also reduce nitrogen

deposition on agricultural land and forests. There is some evidence that nitrogen deposition may

have positive effects on agricultural output through passive fertilization. Holding all other

factors constant, farmers’ use of purchased fertilizers or manure may increase as deposited

nitrogen is reduced. Estimates of the potential value of this possible increase in the use of

purchased fertilizers are not available, but it is likely that the overall value is very small relative

to other health and welfare effects. The share of nitrogen requirements provided by this

deposition is small, and the marginal cost of providing this nitrogen from alternative sources is

quite low. In some areas, agricultural lands suffer from nitrogen over-saturation due to an
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abundance of on-farm nitrogen production, primarily from animal manure. In these areas,

reductions in atmospheric deposition of nitrogen from PM represent additional agricultural

benefits.

Information on the effects of changes in passive nitrogen deposition on forests and other

terrestrial ecosystems is very limited. The multiplicity of factors affecting forests, including

other potential stressors such as ozone, and limiting factors such as moisture and other nutrients,

confound assessments of marginal changes in any one stressor or nutrient in forest ecosystems. 

However, reductions in deposition of nitrogen could have negative effects on forest and

vegetation growth in ecosystems where nitrogen is a limiting factor (US EPA, 1993).

On the other hand, there is evidence that forest ecosystems in some areas of the United States

are nitrogen saturated (US EPA, 1993). Once saturation is reached, adverse effects of additional

nitrogen begin to occur such as soil acidification which can lead to leaching of nutrients needed

for plant growth and mobilization of harmful elements such as aluminum. Increased soil

acidification is also linked to higher amounts of acidic runoff to streams and lakes and leaching

of harmful elements into aquatic ecosystems.

9A.3.6.3 Benefits from Reductions in Materials Damage and Odor

 The preliminary control options that we modeled are expected to produce economic benefits

in the form of reduced materials damage. There are two important categories of these benefits. 

Household soiling refers to the accumulation of dirt, dust, and ash on exposed surfaces. Criteria

pollutants also have corrosive effects on commercial/industrial buildings and structures of

cultural and historical significance. The effects on historic buildings and outdoor works of art

are of particular concern because of the uniqueness and irreplaceability of many of these objects.

Previous EPA benefit analyses have been able to provide quantitative estimates of household

soiling damage. Consistent with SAB advice, we determined that the existing data (based on

consumer expenditures from the early 1970's) are too out of date to provide a reliable enough

estimate of current household soiling damages (EPA-SAB-Council-ADV-003, 1998) to include

in our base estimate. We calculate household soiling damages in a sensitivity estimate provided

in Appendix 9C.

EPA is unable to estimate any benefits to commercial and industrial entities from reduced

materials damage. Nor is EPA able to estimate the benefits of reductions in PM-related damage

to historic buildings and outdoor works of art. Existing studies of damage to this latter category

in Sweden (Grosclaude and Soguel, 1994) indicate that these benefits could be an order of

magnitude larger than household soiling benefits.
Cost-Benefit Analysis

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Reductions in emissions of diesel hydrocarbons that result in unpleasant odors may also lead

to improvements in public welfare. The magnitude of this benefit is very uncertain, however,

Lareau and Rae (1989) found a significant and positive WTP to reduce the number of exposures

to diesel odors. They found that households were on average willing to pay around $20 to $27

(2000$) per year for a reduction of one exposure to intense diesel odors per week (translating

this to a national level, for the approximately 125 million households in 2020, the total WTP

would be between $2.5 and $3.4 billion annually). Their results are not in a form that can be

transferred to the context of this analysis, but the general magnitude of their results suggests this

could be a significant welfare benefit of the rule. 

9A.3.6.4 Benefits from Reduced Ecosystem Damage

The effects of air pollution on the health and stability of ecosystems are potentially very

important, but are at present poorly understood and difficult to measure. The reductions in NOX

caused by the final rule could produce significant benefits. Excess nutrient loads, especially of

nitrogen, cause a variety of adverse consequences to the health of estuarine and coastal waters. 

These effects include toxic and/or noxious algal blooms such as brown and red tides, low

(hypoxic) or zero (anoxic) concentrations of dissolved oxygen in bottom waters, the loss of

submerged aquatic vegetation due to the light-filtering effect of thick algal mats, and

fundamental shifts in phytoplankton community structure (Bricker et al., 1999). 

Direct C-R functions relating changes in nitrogen loadings to changes in estuarine benefits

are not available. The preferred WTP based measure of benefits depends on the availability of

these C-R functions and on estimates of the value of environmental responses. Because neither

appropriate C-R functions nor sufficient information to estimate the marginal value of changes in

water quality exist at present, calculation of a WTP measure is not possible. 

If better models of ecological effects can be defined, EPA believes that progress can be made

in estimating WTP measures for ecosystem functions. These estimates would be superior to

avoided cost estimates in placing economic values on the welfare changes associated with air

pollution damage to ecosystem health. For example, if nitrogen or sulfate loadings can be linked

to measurable and definable changes in fish populations or definable indexes of biodiversity,

then CV studies can be designed to elicit individuals’ WTP for changes in these effects. This is

an important area for further research and analysis, and will require close collaboration among

air quality modelers, natural scientists, and economists.

9A.4 Benefits Analysis—Results

Applying the C-R and valuation functions described in Section C to the estimated changes in

ozone and PM described in Section B yields estimates of the changes in physical damages (i.e.
Final Regulatory Impact Analysis

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premature mortalities, cases, admissions, change in deciviews, increased crop yields, etc.) and

the associated monetary values for those changes. Estimates of physical health impacts are

presented in Table 9A.9. Monetized values for both health and welfare endpoints are presented

in Table 9A.10, along with total aggregate monetized benefits. All of the monetary benefits are

in constant year 2000 dollars.

Not all known PM- and ozone-related health and welfare effects could be quantified or

monetized. The monetized value of these unquantified effects is represented by adding an

unknown “B” to the aggregate total. The estimate of total monetized health benefits is thus

equal to the subset of monetized PM- and ozone-related health and welfare benefits plus B, the

sum of the unmonetized health and welfare benefits.

The total monetized estimates are dominated by benefits of premature mortality risk

reductions. Our benefits analysis projects that the modeled preliminary control options will

result in 7,800 avoided premature deaths in 2020 and 14,000 avoided premature deaths in 2030. 

The increase in benefits from 2020 to 2030 reflects additional emission reductions from the

standards, as well as increases in total population and the average age (and thus baseline

mortality risk) of the population. 

Our primary estimate of total monetized benefits (including PM health, ozone health and

welfare, and visibility) in 2030 for the modeled nonroad preliminary control options is $96

billion using a 3 percent discount rate and $91 billion using a 7 percent discount rate. In 2020,

the monetized benefits are estimated at $54 billion using a 3 percent discount rate and $51 billion

using a 7 percent discount rate. Health benefits account for 97 percent of total benefits. The

monetized benefit associated with reductions in the risk of premature mortality, which accounts

for $89 billion in 2030 and $49 billion in 2020, is over 90 percent of total monetized health

benefits. The next largest benefit is for reductions in chronic illness (chronic bronchitis and nonfatal heart attacks), although this value is more than an order of magnitude lower than for

premature mortality. Visibility, minor restricted activity days, work loss days, school absence

days, and worker productivity account for the majority of the remaining benefits. The remaining

categories account for less than $10 million each, however, they represent a large number of

avoided incidences affecting many individuals.

A comparison of the incidence table to the monetary benefits table reveals that there is not

always a close correspondence between the number of incidences avoided for a given endpoint

and the monetary value associated with that endpoint. For example, there are 100 times more

work loss days than premature mortalities, yet work loss days account for only a very small

fraction of total monetized benefits. This reflects the fact that many of the less severe health

effects, while more common, are valued at a lower level than the more severe health effects. 

Also, some effects, such as hospital admissions, are valued using a proxy measure known to
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underestimate WTP. As such the true value of these effects may be higher than that reported in

Table 9A.9. 

Ozone benefits are in aggregate positive for the nation. However, due to ozone increases

occurring during certain hours of the day in some urban areas, in 2020 the net effect is an

increase in minor restricted activity days, which are related to changes in daily average ozone

(which includes hours during which ozone levels are low, but are increased relative to the

baseline). However, by 2030, there is a net decrease in MRAD consistent with widespread

reductions in ozone concentrations from the increased NOX emissions reductions. Overall,

ozone benefits are low relative to PM benefits for similar endpoint categories because of the

increases in ozone concentrations during some hours of some days in certain urban areas. For a

more complete discussion of this issue, see Chapter 3.
Final Regulatory Impact Analysis

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Table 9A.30. 

Reductions in Incidence of Adverse Health Effects Associated with Reductions in

Particulate Matter and Ozone Associated with the Modeled Preliminary Control Option

Endpoint

Avoided IncidenceA

(cases/year)

2020 2030

PM-related Endpoints

Premature mortality: Long-term exposure (adults, 30 and over)B 7,800 13,800

Infant mortality (infants under one year) 18 26

Chronic bronchitis (adults, 26 and over) 4,300 6,500

Non-fatal myocardial infarctions (adults, 18 and older) 10,600 17,700

Hospital admissions –– Respiratory (adults, 20 and older)C 3,400 6,000

Hospital admissions –– Cardiovascular (adults, 20 and older)D 2,800 4,400

Emergency Room Visits for Asthma (18 and younger) 4,600 6,900

Acute bronchitis (children, 8-12) 10,000 16,000

Asthma exacerbations (asthmatic children, 6-18) 150,000 230,000

Lower respiratory symptoms (children, 7-14) 120,000 190,000

Upper respiratory symptoms (asthmatic children, 9-11) 92,000 141,000

Work loss days (adults, 18-65) 810,000 1,160,000

Minor restricted activity days (adults, age 18-65) 4,800,000 6,800,000

Ozone-related Endpoints

Hospital Admissions – Respiratory Causes (adults, 65 and older)E 370 1,100

Hospital Admissions - Respiratory Causes (children, under 2 years) 150 280

Emergency Room Visits for Asthma (all ages) 93 200

Minor restricted activity days (adults, age 18-65) (2,400) 96,000

School absence days (children, age 6-11) 65,000 96,000

A Incidences are rounded to two significant digits.

B

 Premature mortality associated with ozone is not separately included in this analysis C Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. 

D Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart

disease, dysrhythmias, and heart failure.

E

 Respiratory hospital admissions for ozone includes admissions for all respiratory causes and subcategories for

COPD and pneumonia.
Table 9A.31 

Results of Human Health and Welfare Benefits Valuation for the Modeled Preliminary

Nonroad Diesel Engine Standards 

Endpoint Pollutant

Monetary BenefitsA,B

(millions 2000$, Adjusted for

Income Growth)

2020 2030

Premature mortalityC: (adults, 30 and over) PM

3% discount rate $49,000 $89,000

7% discount rate $46,000 $84,000

Infant mortality (infants under one year) PM $120 $180

Chronic bronchitis (adults, 26 and over) PM $1,800 $2,800

Non-fatal myocardial infarctions PM

3% discount rate $910 $1,440

7% discount rate $880 $1,400

Hospital Admissions from Respiratory CausesD,F O3 $7.4 $21

PM $60 $110

Hospital Admissions from Cardiovascular CausesE PM $61 $96

Emergency Room Visits for Asthma O3 $0.03 $0.06

PM $1.3 $2.0

Acute bronchitis (children, 8-12) PM $3.9 $6.0

Asthma exacerbations (asthmatic children, 6-18) PM $6.9 $10.7

Lower respiratory symptoms (children, 7-14) PM $2.0 $3.1

Upper respiratory symptoms (asthmatic children, 9-11) PM $2.4 $3.7

Work loss days (adults, 18-65) PM $110 $150

Minor restricted activity days (adults, age 18-65) O3 ($0.1) $4.9

PM $260 $370

School absence days (children, age 6-11) O3 $4.8 $10

Worker productivity (outdoor workers, age 18-65) O3 $4.2 $6.9

Recreational visibility (86 Class I Areas) PM $1,300 $2,100

Agricultural crop damage (6 crops) O3 $88 $137

Monetized TotalH

3% discount rate

7% discount rate

O3 and PM

$54,000+B

$51,000+B

$96,000+B

$91,000+B

A Monetary benefits are rounded to two significant digits.

B Monetary benefits are adjusted to account for growth in real GDP per capita between 1990 and the analysis year (2020 or 2030). C Premature mortality associated with ozone is not separately included in this analysis. It is assumed that the C-R function for premature mortality

captures both PM mortality benefits and any mortality benefits associated with other air pollutants. Also note that the valuation assumes the 5

year distributed lag structure described earlier. Results reflect the use 3% and 7% discount rates consistent with EPA and OMB’s guidelines for preparing

economic analyses (US EPA, 2000c, OMB Circular A-4).

D Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. E

 Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart disease, dysrhythmias, and heart

failure.

F

 Respiratory hospital admissions for ozone includes admissions for all respiratory causes and subcategories for COPD and pneumonia. G B represents the monetary value of the unmonetized health and welfare benefits. A detailed listing of unquantified PM, ozone, CO, and NMHC

related health effects is provided in Table XI-B.1. 
Final Regulatory Impact Analysis

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9A.5 Discussion

This analysis has estimated the health and welfare benefits of reductions in ambient

concentrations of particulate matter resulting from reduced emissions of NOx, SO2, VOC, and

diesel PM from nonroad diesel engines. The result suggests there will be significant health and

welfare benefits arising from the regulation of emissions from nonroad engines in the U.S. Our

estimate that 14,000 premature mortalities would be avoided in 2030, when emission reductions

from the regulation are fully realized, provides additional evidence of the important role that

pollution from the nonroad sector plays in the public health impacts of air pollution.

We provide sensitivity analyses in Appendix 9C to examine key modeling assumptions. In

addition, there are other uncertainties that we could not quantify, such as the importance of

unquantified effects and uncertainties in the modeling of ambient air quality. Inherent in any

analysis of future regulatory programs are uncertainties in projecting atmospheric conditions,

source-level emissions, and engine use hours, as well as population, health baselines, incomes,

technology, and other factors. The assumptions used to capture these elements are reasonable

based on the available evidence. However, data limitations prevent an overall quantitative

estimate of the uncertainty associated with estimates of total economic benefits. If one is

mindful of these limitations, the magnitude of the benefit estimates presented here can be useful

information in expanding the understanding of the public health impacts of reducing air pollution

from nonroad engines.

The U.S. EPA will continue to evaluate new methods and models and select those most

appropriate for the estimation the health benefits of reductions in air pollution. It is important to

continue improving benefits transfer methods in terms of transferring economic values and

transferring estimated C-R functions. The development of both better models of current health

outcomes and new models for additional health effects such as asthma and high blood pressure

will be essential to future improvements in the accuracy and reliability of benefits analyses (Guo

et al., 1999; Ibald-Mulli et al., 2001). Enhanced collaboration between air quality modelers,

epidemiologists, and economists should result in a more tightly integrated analytical framework

for measuring health benefits of air pollution policies. The Agency welcomes comments on how

we can improve the quantification and monetization of health and welfare effects and on

methods for characterizing uncertainty in our estimates.
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APPENDIX 9B: Supplemental Analyses Addressing Uncertainties in the

Concentration-Response and Valuation Functions for Particulate Matter Health Effects

9B.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-205

9B.2 Monte Carlo Based Uncertainty Analysis Using Classical Statistical Sources of

Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-206

9B.2.1 Monte Carlo Analysis Using Pope et al. (2002) to Characterize the Distribution

of Reductions in Premature Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-210

9B.3 Expert Elicitation of PM Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-215

9B.3.1 Elicitation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-216

9B.3.3 Experts’ Views of Sources of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . 9-223

9B.3.4 Advisory Council Comments on the Preliminary Design of the Elicitation . 9-223

9B.3.5 Limitations in Pilot Elicitation Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-224

9B.3.6 Combining the Expert Judgments for Application to Economic Benefit Analyses

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-227

9B.3.5 Limitations of Combining Expert Judgments . . . . . . . . . . . . . . . . . . . . . . . . 9-235

9B.4. Illustrative Application of Pilot Expert Elicitation Results . . . . . . . . . . . . . . . . . 9-235

9B.5.3 Limitations of the Application of the Pilot Elicitation Results to the Nonroad Scenario

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-246
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9B.1 Introduction

In this appendix, we describe our progress toward improving our approach to characterizing

the uncertainties in our economic benefits estimates, with particular emphasis on the

concentration-response (C-R) function. We present two types of probabilistic approaches

designed to illustrate how some aspects of the uncertainty in the C-R function might be handled

in a PM benefits analysis. The first approach generates a probabilistic estimate of statistical

uncertainty based on standard errors reported in the underlying studies used in the benefit

modeling framework. The second approach uses the results from a pilot expert elicitation

designed to characterize certain aspects of uncertainty in the ambient PM2.5/mortality

relationship. For the reasons discussed earlier in Chapter 9, neither the primary benefit estimate

nor these approaches have been used to inform any regulatory decisions in this rulemaking.

In any benefit analyses of air pollution regulations, estimation of pre-mature mortality

accounts for 85 to 95 percent of total benefits. Therefore, it is an endpoint that will be an

important focus for characterizing the uncertainty related to the estimates of total benefits. As

part of a collaboration with the EPA’s Office of Air and Radiation (OAR) and the Office of

Management and Budget (OMB) on the Non-Road Diesel Rule, EPA extended it’s collaboration

with OMB in 2003 to conduct a pilot expert elicitation intended to more fully characterize

uncertainty in the effect estimates used to estimate mortality resulting from exposure to PM. 

It should be recognized that in addition to uncertainty, the annual benefit estimates for the

Final Non-Road Diesel Rule also are inherently variable, due to the truly random processes that

govern pollutant emissions and ambient air quality in a given year. Factors such as hourly use of

engines and daily weather display constant variability regardless of our ability to accurately

measure them. As such, the primary estimates of annual benefits presented in this chapter and

the sensitivity analysis estimates presented in this and other appendices should be viewed as

representative of the types of benefits that will be realized, rather than the actual benefits that

would occur every year. As such, the distributions of the estimate of annual benefits should be

viewed as representative of the types of benefits that will be realized, rather than the actual

benefits that would occur every year.

9B.2 Monte Carlo Based Uncertainty Analysis Using Classical Statistical

Sources of Uncertainty

The recent NAS report on estimating public health benefits of air pollution regulations

recommended that EPA begin to move the assessment of uncertainties from its ancillary analyses

into its primary analyses by conducting probabilistic, multiple-source uncertainty analyses.
Final Regulatory Impact Analysis

MM Because this is a national analysis in which, for each endpoint, a single C-R function is applied everywhere,

there are two sources of uncertainty about incidence: (1) statistical uncertainty (due to sampling error) about the true

value of the pollutant coefficient in the location where the C-R function was estimated, and (2) uncertainty about

how well any given pollutant coefficient approximates $*.

NN Although such a “likelihood distribution” is not formally a Bayesian posterior distribution, it is very similar

in concept and function (see, for example, the discussion of the Bayesian approach in Kennedy 1990, pp. 168-172).

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However, for this proposal we did not attempt to assign probabilities to all of the uncertain

parameters in the model due to a lack of resources and reliable methods. At this time, we simply

generate estimates of the distributions of dollar benefits for PM health effects and for total dollar

benefits including visibility. We provide a likelihood distribution for the total benefits estimate,

based solely on the statistical uncertainty surrounding the estimated C-R functions and the

assumed distributions around the unit values. 

Our estimate of the likelihood distribution for total benefits should be viewed as an

approximate result because of the wide range of sources of uncertainty that we have not

incorporated. The 5th and 95th percentile points of our estimate are based on statistical error and

cross-study variability provides some insight into how uncertain our estimate is with regards to

those sources of uncertainty. However, it does not capture other sources of uncertainty regarding

other inputs to the model, including emissions, air quality, and aspects of the health science not

captured in the studies, such as the likelihood that PM is causally related to premature mortality

and other serious health effects..

Although there are several sources of uncertainty affecting estimates of endpoint-specific

benefits, the sources of uncertainty that are most readily quantifiable in this analysis are the C-R

relationships and uncertainty about unit dollar values. The total dollar benefit associated with a

given endpoint depends on how much reducing risk of the endpoint will change due to the final

standard (e.g., how many premature deaths will be avoided) and how much each unit of change

is worth (e.g., how much a premature death avoided is worth).mm However, as we have noted,

this omits important sources of uncertainty, such as the contribution of air quality changes,

baseline population incidences, projected populations exposed, transferability of the C-R

function to diverse locations, and uncertainty about the C-R relationship for premature mortality. 

Thus, a likelihood description based on the standard error would provide a misleading picture

about the overall uncertainty in the estimates. The empirical evidence about uncertainty is

presented where it is available.

Both the uncertainty about the incidence changes and uncertainty about unit dollar values can

be characterized by distributions. Each “ likelihood distribution” characterizes our beliefs about

what the true value of an unknown variable (e.g., the true change in incidence of a given health

effect in relation to PM exposure) is likely to be, based on the available information from

relevant studies.nn Unlike a sampling distribution (which describes the possible values that an
Cost-Benefit Analysis

OO This method assumes that the incidence change and the unit dollar value for an endpoint are stochastically

independent.

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estimator of an unknown variable might take on), this likelihood distribution describes our

beliefs about what values the unknown variable itself might be. Such likelihood distributions

can be constructed for each underlying unknown variable (such as a particular pollutant

coefficient for a particular location) or for a function of several underlying unknown variables

(such as the total dollar benefit of a regulation). In either case, a likelihood distribution is a

characterization of our beliefs about what the unknown variable (or the function of unknown

variables) is likely to be, based on all the available relevant information. A likelihood

description based on such distributions are typically expressed as the interval from the fifth

percentile point of the likelihood distribution to the ninety-fifth percentile point. If all

uncertainty had been included, this range would be the “credible range” within which we believe

the true value is likely to lie with 90 percent probability.

The uncertainty about the total dollar benefit associated with any single endpoint combines

the uncertainties from these two sources (the C-R relationship and the valuation), and is

estimated with a Monte Carlo method. In each iteration of the Monte Carlo procedure, a value is

randomly drawn from the incidence distribution and a value is randomly drawn from the unit

dollar value distribution, and the total dollar benefit for that iteration is the product of the two.oo

If this is repeated for many (e.g., thousands of) iterations, the distribution of total dollar benefits

associated with the endpoint is generated. 

Using this Monte Carlo procedure, a distribution of dollar benefits may be generated for each

endpoint. As the number of Monte Carlo draws gets larger and larger, the Monte Carlogenerated distribution becomes a better and better approximation of a joint likelihood

distribution for the considered likelihood distributions making up the overall model of total

monetary benefits for the endpoint. 

After endpoint-specific distributions are generated, the same Monte Carlo procedure can then

be used to combine the dollar benefits from different (non-overlapping) endpoints to generate a

distribution of total dollar benefits. 

The estimate of total benefits may be thought of as the end result of a sequential process in

which, at each step, the estimate of benefits from an additional source is added. Each time an

estimate of dollar benefits from a new source (e.g., a new health endpoint) is added to the

previous estimate of total dollar benefits, the estimated total dollar benefits increases. However,

our bounding or likelihood description of where the true total value lies also increases as we add

more sources. 
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(1)

(2)

(3)

As an example, consider the benefits from reductions in PM-related hospital admissions for

cardiovascular disease. Because the actual dollar value is unknown, it may be described using a 

variable, with a distribution describing the possible values it might have. If this variable is

denoted as X1 , then the mean of the distribution, E(X1) and the variance of X1, denoted Var(X1),

and the 5th and 95th percentile points of the distribution (related to Var(X1)), are ways to

describe the likelihood for the true but unknown value for the benefits reduction. 

Now suppose the benefits from reductions in PM-related hospital admissions for respiratory

diseases are added. Like the benefits from reductions in PM-related hospital admissions for

cardiovascular disease, the likelihood distribution for where we expect the true value to be may

be considered a variable, with a distribution. Denoting this variable as X2, the benefits from

reductions in the incidence of both types of hospital admissions is X1 + X2. This variable has a

distribution with mean E(X1 + X2) = E(X1) + E(X2), and a variance of Var(X1 + X2) = Var(X1) +

Var(X2) + 2Cov(X1,X2); if X1 and X2 are stochastically independent, then it has a variance of

Var(X1 + X2) = Var(X1) + Var(X2), and the covariance term is zero.

The benefits from reductions in all non-overlapping PM-related health and welfare endpoints

(Xm+1, ..., Xn) is X = X1 + ... + Xn. The mean of the distribution of total benefits, X, is: 

and the variance of the distribution of total benefits -- assuming that the components are

stochastically independent of each other (i.e., no covariance between variables) -- is:

If all the means are positive, then each additional source of benefits increases the point

estimate (mean) of total benefits. However, with the addition of each new source of benefits, the

variance of the estimate of total benefits also increases. That is,

but:

That is, the addition of each new source of benefits results in a larger mean estimate of total

benefits (as more and more sources of benefits are included in the total) about which there is less

certainty. This phenomenon occurs whenever estimates of benefits are added.
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Calculated with a Monte Carlo procedure, the distribution of X is composed of random draws

from the components of X. In the first draw, a value is drawn from each of the distributions, X1,

X2, through Xn, these values are summed, and the procedure is repeated again, with the number

of repetitions set at a high enough value (e.g., 5,000) to reasonably trace out the distribution of

X. The fifth percentile point of the distribution of X will be composed of points pulled from all

points along the distributions of the individual components, and not simply from the fifth

percentile. While the sum of the fifth percentiles of the components would be represented in the

distribution of X generated by the Monte Carlo, it is likely that this value would occur at a

significantly lower percentile. For a similar reason, the 95th percentile of X will be less than the

sum of the 95th percentiles of the components, and instead the 95th percentile of X will be

composed of component values that are significantly lower than the 95th percentiles.

The physical effects estimated in this analysis are assumed to occur independently. It is

possible that, for any given pollution level, there is some correlation between the occurrence of

physical effects, due to say avoidance behavior or common causal pathways and treatments (e.g.,

stroke, some kidney disease, and heart attack are related to treatable blood pressure). Estimating

accurately any such correlation, however, is beyond the scope of this analysis, and instead it is simply

assumed that the physical effects occur independently.

We conduct two different Monte Carlo analyses, one based on the distribution of reductions in

premature mortality characterized by the mean effect estimate and standard error from the epidemiology

study of PM-associated mortality associated with long-term exposure used in the primary estimate in

Chapter 9 (Pope et al., 2002), and one based on the results from a pilot expert elicitation project

(Industrial Economics, 2004). In both analyses, the distributions of all other health endpoints are

characterized by the reported mean and standard deviations from the epidemiology literature. 

Distributions for unit dollar values are based on reported ranges or distributions of values in the

economic literature and are summarized in Table 9B-1. We are unable at this time to

characterize the uncertainty in the estimate of benefits of improvements in visibility at Class I

areas. As such, we treat the visibility benefits as fixed and add them to all percentiles of the PM

health benefits distribution. Results of the Monte Carlo analysis based on the Pope et al. (2002)

distribution are presented in the next section. Results of the Monte Carlo analysis based on the

pilot expert elicitation are presented in section 9B.3.

9B.2.1 Monte Carlo Analysis Using Pope et al. (2002) to Characterize the Distribution of

Reductions in Premature Mortality

Based on the Monte Carlo techniques described earlier, we generated likelihood distributions 

for the dollar value of reductions in PM-related health endpoints and a similar distribution for 

total annual PM-related benefits including PM health and visibility benefits for the nonroad

diesel modeled preliminary control option. For this analysis, the likelihood descriptions for the
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true value for each of the PM health endpoint incidence measures, including premature

mortality, were based on classical statistical uncertainty measures, including the mean and

standard deviation for the C-R relationships in the epidemiological literature, and assumption of

particular likelihood distribution shapes for the valuation for each health endpoint values based

on reported values in the economic literature. Table 9B-1 summarizes the chosen parameters

for likelihood distributions for unit values for each of the PM health effects included in the

Monte Carlo simulation. The distributions for the value used to represent incidence of a health

effect in the total benefits valuation represent both the simple statistical uncertainty surrounding

individual effect estimates and, for those health endpoints with multiple effects from different

epidemiology studies, interstudy variability. Visibility benefits are also included in the

distribution of total benefits, however, we were unable to characterize a distribution for visibility

benefits. As such, they are simply added to each percentile of the distribution of PM health

benefits. 
Table 9B-1. Distributions for Unit Values of Health Endpoints

Health

Endpoint

Mean Value,

Adjusted for

Income

Growth to

2030

Derivation of Distribution

Premature Mortality (Value of

a Statistical Life)

$5,500,000

 Normal distribution anchored at 2.5th and 97.5th percentiles of $1

and $10 million, respectively. Confidence interval is based on two

meta-analyses of the wage-risk VSL literature. $1 million represents

the lower end of the interquartile range from the Mrozek and Taylor

(2000) meta-analysis. $10 million represents the upper end of the

interquartile range from the Viscusi and Aldy (2003) meta-analysis. 

The VSL represents the value of a small change in mortality risk

aggregated over the affected population. Normal distribution chosen

through best professional judgment.

Chronic Bronchitis (CB) $430,000

The distribution of WTP to avoid a case of pollution-related

CB was generated by Monte Carlo methods, drawing from each of

three distributions: (1) WTP to avoid a severe case of CB is assigned

a 1/9 probability of being each of the first nine deciles of the

distribution of WTP responses in Viscusi et al., 1991; (2) the severity

of a pollution related case of CB (relative to the case described in the

Viscusi study) is assumed to have a triangular distribution, centered

at severity level 6.5 with endpoints at 1.0 and 12.0 (see text for

further explanation); and (3) the constant in the elasticity of WTP

with respect to severity is normally distributed with mean = 0.18 and

standard deviation = 0.0669 (from Krupnick and Cropper, 1992). This

process and the rationale for choosing it is described in detail in the

Costs and Benefits of the Clean Air Act, 1990 to 2010 (U.S. EPA,

1999)

Nonfatal Myocardial Infarction

(heart attack)

3% discount rate

Age 0-24

Age 25-44

Age 45-54

Age 55-65

Age 66 and over

7% discount rate

Age 0-24

Age 25-44

Age 45-54

Age 55-65

Age 66 and over

$66,902

$74,676

$78,834

$140,649

$66,902

$65,293

$73,149

$76,871

$132,214

$65,293

No distribution available. Age specific cost-of-illness values

reflecting lost earnings and direct medical costs over a 5 year period

following a non-fatal MI. Lost earnings estimates based on Cropper

and Krupnick (1990). Direct medical costs based on simple average

of estimates from Russell et al. (1998) and Wittels et al. (1990).

Lost earnings:

Cropper and Krupnick (1990). Present discounted value of 5 yrs of

lost earnings:

age of onset: at 3% at 7%

25-44 $8,774 $7,855

45-54 $12,932 $11,578

55-65 $74,746 $66,920

Direct medical expenses: An average of: 

1. Wittels et al., 1990 ($102,658 – no discounting)

2. Russell et al., 1998, 5-yr period. ($22,331 at 3% discount rate;

$21,113 at 7% discount rate)

Hospital Admissions

Chronic Obstructive

Pulmonary Disease (COPD)

(ICD codes 490-492, 494-496)

$12,378

No distribution available. The COI point estimates (lost earnings plus

direct medical costs) are based on ICD-9 code level information (e.g.,

average hospital care costs, average length of hospital stay, and

weighted share of total COPD category illnesses) reported in Agency

for Healthcare Research and Quality, 2000 (www.ahrq.gov). 
Health

Endpoint

Mean Value,

Adjusted for

Income

Growth to

2030

Derivation of Distribution

Pneumonia

(ICD codes 480-487) $14,693

No distribution available. The COI point estimates (lost earnings plus

direct medical costs) are based on ICD-9 code level information (e.g.,

average hospital care costs, average length of hospital stay, and

weighted share of total pneumonia category illnesses) reported in

Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Asthma admissions $6,634

The COI estimates (lost earnings plus direct medical costs) are based

on ICD-9 code level information (e.g., average hospital care costs,

average length of hospital stay, and weighted share of total asthma

category illnesses) reported in Agency for Healthcare Research and

Quality, 2000 (www.ahrq.gov). 

All Cardiovascular

(ICD codes 390-429) $18,387

No distribution available. The COI point estimates (lost earnings plus

direct medical costs) are based on ICD-9 code level information (e.g.,

average hospital care costs, average length of hospital stay, and

weighted share of total cardiovascular category illnesses) reported in

Agency for Healthcare Research and Quality, 2000 (www.ahrq.gov). 

Emergency room visits for

asthma $286

No distribution available. The COI point estimate is the simple 

average of two unit COI values: 

(1) $311.55, from Smith et al., 1997, and 

(2) $260.67, from Stanford et al., 1999.

Respiratory Ailments Not Requiring Hospitalization

Upper Respiratory Symptoms 

(URS) $27

Combinations of the 3 symptoms for which WTP estimates are

available that closely match those listed by Pope, et al. result in 7

different “symptom clusters,” each describing a “type” of URS. A

dollar value was derived for each type of URS, using mid-range

estimates of WTP (IEc, 1994) to avoid each symptom in the cluster

and assuming additivity of WTPs. In the absence of information

surrounding the frequency with which each of the seven types of

URS occurs within the URS symptom complex, we assume a uniform

distribution between $10 and $45.

Lower Respiratory Symptoms 

(LRS) $17

Combinations of the 4 symptoms for which WTP estimates are

available that closely match those listed by Schwartz, et al. result in

11 different “symptom clusters,” each describing a “type” of LRS. A

dollar value was derived for each type of LRS, using mid-range

estimates of WTP (IEc, 1994) to avoid each symptom in the cluster

and assuming additivity of WTPs. The dollar value for LRS is the

average of the dollar values for the 11 different types of LRS. In the

absence of information surrounding the frequency with which each of

the eleven types of LRS occurs within the LRS symptom complex,

we assume a uniform distribution between $8 and $25.

Asthma Exacerbations $45

Asthma exacerbations are valued at $45 per incidence, based on the

mean of average WTP estimates for the four severity definitions of a

“bad asthma day,” described in Rowe and Chestnut (1986). This

study surveyed asthmatics to estimate WTP for avoidance of a "bad

asthma day,” as defined by the subjects. For purposes of valuation,

an asthma exacerbation is assumed to be equivalent to a day in which

asthma is moderate or worse as reported in the Rowe and Chestnut

(1986) study. The value is assumed have a uniform distribution

between $17 and $73.
Health

Endpoint

Mean Value,

Adjusted for

Income

Growth to

2030

Derivation of Distribution

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Acute Bronchitis $390

Assumes a 6 day episode, with the distribution of the daily value

specified as uniform with the low and high values based on those

recommended for related respiratory symptoms in Neumann, et al.

1994. The low estimate is the sum of the midrange values

recommended by IEc (1994) for two symptoms believed to be

associated with acute bronchitis: coughing and chest tightness. The

high estimate was taken to be twice the value of a minor respiratory

restricted activity day. 

Restricted Activity and Work Loss Days

Work Loss Days (WLDs) Variable 

No distribution available. Point estimate is based on county-specific

median annual wages divided by 50 (assuming 2 weeks of vacation)

and then by 5 – to get median daily wage. U.S. Year 2000 Census,

compiled by Geolytics, Inc.

Minor Restricted Activity

Days (MRADs) $55

Median WTP estimate to avoid one MRAD from Tolley, et al.

(1986) . Distribution is assumed to be triangular with a minimum of

$22 and a maximum of $83. Range is based on assumption that value

should exceed WTP for a single mild symptom (the highest estimate

for a single symptom--for eye irritation--is $16.00) and be less than

that for a WLD. The triangular distribution acknowledges that the

actual value is likely to be closer to the point estimate than either

extreme.

Results of the Monte Carlo simulations are presented in Table 9B-2. The table provides the

estimated means of the distributions and the estimated 5th and 95th percentiles of the distributions. 

The contribution of mortality to the mean benefits and to both the 5th and 95th percentiles of total

benefits is substantial, with mortality accounting for over 90 percent of the mean estimate, and

even the 5th percentile of mortality benefits dominating the 95th percentile of all other benefit

categories. Thus, the choice of value and the shape for likelihood distribution for VSL should be

examined closely and is key information to provide to decision makers for any decision

involving this variable. The 95th percentile of total benefits is approximately twice the mean,

while the 5th percentile is approximately one fourth of the mean. The overall range from 5th to

95th represents about one order of magnitude. 
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Table 9B-2. 

Distribution of Value of Annual Human Health and Welfare Benefits in 2030 for the

Modeled Preliminary Control Option of the Non-Road Diesel RuleA

Endpoint

Monetary BenefitsB, C

(Millions 2000$, Adjusted for Income Growth)

5th Percentile Mean 95th Percentile

Premature mortalityD

Long-term exposure, (adults, >30yrs) $20,000 $89,000 $180,000

Long-term exposure (child <1yr) $40 $180 $350

Chronic bronchitis (adults, 26 and over) $200 $2,800 $9,400

Non-fatal myocardial infarctions (adults, 18 and over) $300 $1,400 $3,300

Hospital Admissions from Respiratory CausesE $17 $36 $54

Hospital Admissions from Cardiovascular CausesF $59 $96 $130

Emergency Room Visits for Asthma (children, <18) $1.3 $2.2 $3.4

Acute bronchitis (children, 8-12) ($0.2) $5.9 $15

Lower respiratory symptoms (children, 7-14) $1.1 $2.9 $5.4

Upper respiratory symptoms (asthmatic children, 9-11) $0.9 $3.7 $7.7

Work loss days (adults, 18-65) $140 $160 $180

Asthma exacerbations (asthmatic children, 6-18) $0.2 $11 $29

Minor restricted activity days (adults, age 18-65) $200 $340 $500

Recreational visibility (86 Class I Areas) $1,700 $1,700 $1,700

Unquantified Benefits B B B

Monetized TotalG $23,000+B $96,000+B $200,000+B

A The benefit estimates provided in this table are based on the modeled air quality data for the preliminary control option used in the Non-Road

Diesel proposal analysis and do not reflect the predicted emission reductions of the final rule’s stringency levels. In the primary estimate in

Chapter 9, the modeled benefits were scaled to the level necessary to reflect the predicted emission reductions of the final rule. The estimates

provided in this table have not been scaled to the rule’s stringency level, as the scaling methodology adds a new element of uncertainty that

cannot be appropriately characterized here. These estimates should not be compared with the primary estimate provided in the chapter, but could

be compared to results presented in Apprendix 9A. 

B Monetary benefits are rounded to two significant digits.

C Monetary benefits are adjusted to account for growth in real GDP per capita between 1990 and 2030. D The valuation of mortality assumes the 5 year distributed lag structure described earlier. Impacts of alternative lag structures are provided in a

sensitivity analysis in Appendix 9C. Results reflect the use of 3% and 7% discount rates consistent with EPA and OMB’s guidelines for

preparing economic analyses (US EPA, 2000c, OMB Circular A-4).

E

 Respiratory hospital admissions for PM includes admissions for COPD, pneumonia, and asthma. F

 Cardiovascular hospital admissions for PM includes total cardiovascular and subcategories for ischemic heart disease, dysrhythmias, and heart

failure.

G B represents the monetary value of the unmonetized health and welfare benefits. A detailed listing of unquantified PM, ozone, CO, and NMHC

related health effects is provided in Table 9-1.
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9B.3 Expert Elicitation of PM Mortality

In its 2002 report, the NAS provides a number of recommendations on how EPA might

improve the characterization of uncertainty in its benefits analyses. One recommendation was

that “EPA should begin to move the assessment of uncertainties from its ancillary analyses into

its primary analyses by conducting probabilistic, multiple-source uncertainty analyses. This shift

will require specification of probability distributions for major sources of uncertainty. These

distributions should be based on available data and expert judgment.”(NAS, 2002: 14) The NAS

elaborated on this recommendation by saying “although the specific methods for selection and

elicitation of experts may need to be modified somewhat, the protocols that have been developed

and tested by OAQPS [in prior EPA projects -- see below] provide a solid foundation for future

work in the area. EPA may also consider having its approaches reviewed and critiqued by

decision analysts, biostatisticians, and psychologists from other fields where expert judgment is

applied.” (NAS, 2002: 140). They recommended the use of formally elicited expert judgments,

but noted that a number of issues must be addressed, and that sensitivity analyses would be

needed for distributions that are based on expert judgment. They also recommended that EPA

clearly distinguish between data-derived components of an uncertainty assessment and those

based on expert opinions. As a first step in addressing the NAS recommendations regarding

expert elicitation, EPA, in collaboration with OMB, conducted a pilot expert elicitation to

characterize uncertainties in the relationship between ambient PM2.5 and mortality. While it is

premature to include the results of the pilot in the primary analysis for this rulemaking, EPA and

OMB believe this pilot is an important step in moving toward the goal of incorporating

additional uncertainty analyses in its future primary benefits analyses.

This pilot was designed to provide EPA with an opportunity to improve its understanding of

the design and application of expert elicitation methods to economic benefits analysis and lay the

groundwork for a more comprehensive elicitation. For instance, the pilot was designed to

provide feedback on the efficacy of the protocol developed and the analytic challenges, as well

as to provide insight regarding potential implications of the results on the degree of uncertainty

surrounding the C-R function for PM2.5 mortality. The scope of the pilot was limited in that we

focused the elicitation on the C-R function of PM mass rather than on individual issues

surrounding an estimate of the change in mortality due to PM exposure. Also, to meet time

constraints placed on the pilot, we selected expert s for participation from two previously

established expert panels of the NAS, and chose not to conduct a workshop with the experts

prior to the elicitation. The limited scope of the pilot meant that a full expert elicitation process

was truncated and many aspects of the uncertainty surrounding the PM2.5-mortality relationship

could not be quantitatively characterized. Recognizing this, the results of the pilot are only used

in this benefits estimation for illustrative purposes. A full description of the pilot is contained in

a report titled, “An Expert Judgment Assessment of the Concentration-Response Relationship

between PM2.5 Exposure and Mortality,” (IEc, 2004) available in the public docket for this rule.
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The analytic plan for the pilot was developed based on established elicitation methods as

suggestedby the NAS and published in the peer-reviewed literature. The plan was internally

reviewed by EPA and OMB scientists with experience using expert elicitation methods. The

Health Effect Subcommittee (HES) of the Council on Clean Air Compliance Analysis (the

“Council”) then provided additional suggestions, which led to further changes in the elicitation

protocol. However, it should be noted that the Council did not provide a complete peer review

of the elicitation methods or interpretation of results. Finally, the protocol was tested on PM

scientists from within EPA and external to the Agency, who would not be part of the final

elicitation process. The project team that implemented the pilot consisted of individuals with

experience in expert elicitation and individuals with expertise in PM health effects and health

benefits. 

As a final step in this carefully designed pilot, the EPA and OMB will sponsor an external

peer review of the methods used in this pilot expert elicitation as well as the approaches to

presenting the results (particularly with respect to combining results across experts), in

accordance with EPA’s peer review guidelines. Until the peer review is complete andthe

comments of the reviewers addressed, we do not recommend use of these results for other

regulatory analysis. 

9B.3.1 Elicitation Method

Expert elicitation is a formal, highly structured and well documented process whereby expert

judgments, usually of multiple experts, are obtained (U.S. NRC, 1996). Formal expert elicitation

usually involves experts with training and expertise in statistics, decision analysis, and

probability encoding who work with subject matter experts to structure questions about uncertain

relationships or parameters and who design and implement the process used to obtain

probability and other judgments from subject matter experts. Several academic traditions –

judgment and decision-making, human factors, cognitive sciences, expert systems, management

science, to name a few – have sought to understand how to successfully elicit probabilistic

judgments from both lay people and experts (Morgan and Henrion 1990, Cooke 1991,; Wright

and Ayton 1994, Ayyub 2002). Over the past two decades, there has been an increasing number

of studies that have used expert judgment techniques to characterize uncertainty in quantities of

interest to environmental risk analysis and decision-making. North and Merkhofer (1976)

considered the use of expert judgment in evaluating emission control strategies. As referred to

by the NAS, the EPA’s Office of Air Quality Planning and Standards (OAQPS) successfully

used expert judgment to characterize uncertainty in the health effects of exposure to lead

(McCurdy and Richmond, 1983; Whitfield and Wallsten, 1989) and to ozone (Whitfield et al.

1991; Winkler et al., 1995). Amaral (1983) and Morgan et al. (1984) used expert judgment in

the evaluation of the transport and impacts of sulfur air pollution. Several studies have been

done in the area of climate change (Manne and Richels, 1994; Nordhaus, 1994; Morgan and
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Keith, 1995; Reilly et al, 2001). Hawkins and Evans (1989) used industrial hygienists to predict

toluene exposures to workers involved in a batch chemical process. In a more recent use of

expert judgment in exposure analysis, Walker et al. (2001, 2003) asked experts to estimate

ambient, indoor and personal air concentrations of benzene. A few studies have used expert

judgment to characterize uncertainty in chemical dose response: Hawkins and Graham (1988)

and Evans et al. (1994) for formaldehyde and Evans et al. (1994b) for risk of exposure to

chloroform in drinking water. Expert judgment has also been used in the characterization of

residential radon risks (Krewski et al., 1999). 

The literature (Granger and Morgan, 1990) suggest there are several steps involved in the

design and implementation of an expert elicitation, including: 

• developing a protocol that contains the specific content of the elicitation and the questions

that will be asked of the experts, 

• selection of experts, 

• compiling a briefing book of materials that can be used by the experts as background

information to respond to the elicitation,

• pilot testing the protocol,

• conducting the elicitation and summarizing the findings. 

The pilot expert elicitation consisted of a series of structured questions, both quantitative

and qualitative, about the nature of the PM2.5/mortality relationship. The objective was to obtain

experts’ quantitative, probabilistic judgments about the average expected decrease in mortality

rates associated with decreases in PM2.5 exposures in the United States. These judgments were

expressed in terms of median estimates and associated percentile values of an uncertainty

distribution. The quantitative questions in the protocol asked experts to provide judgments about

changes in mortality due exposure to PM2.5. Specifically, they were asked to estimate:1) the

percent change in annual non-accidental mortality associated with a 1 μg/m3 change in annual

average PM2.5 (long-term exposure); and 2) the percent change in daily non-accidental mortality

associated with a 10 μg/m3

 change in daily 24-hour average PM2.5 (short-term exposure). For

each type of exposure, each expert provided minimum, maximum, and median estimates, plus

5th, 25th, 75th, and 95th percentile values for the distribution describing his uncertainty in the

mortality effect of the specified change in PM2.5.

The pilot focused on eliciting judgments about the C-R function for PM2.5 mass (without

regard to source) and their solicited opinions about the key factors influencing the uncertainty in

estimating the PM2.5/mortality relationship. As a warm-up to answering the quantitative

question, experts were asked their views on several key issues including: cause of death,

mechanisms, thresholds, lag/cessation period, the relative effect of PM components and their

sources, confounding, and effect modification. This discussion allowed the experts to articulate
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the way they interpreted the underlying issues, thus what would form the conceptual framework

of their quantitative judgments. Their responses also provided EPA with information that would

be useful for designing a more comprehensive and disaggregated elicitation assessment in the

future.

The pilot elicitation consisted of personal interviews with five experts. The five experts were

selected from an initial pool defined by the membership on two PM-related NAS committees. The

rosters of both NRC committees included recognized experts in pertinent fields such as

epidemiology and toxicology who had already undergone extensive review of their qualifications

by the NRC, producing a reasonable initial list of experts likely to meet our expert selection criteria.

The five experts selected for participation in the elicitation include: Dr. Roger McClellan, Dr. Bart

Ostro, Dr. Jonathan Samet, Dr. Mark Utell, and Dr. Scott Zeger. The specific process used to select

experts is detailed in the technical report of the elicitation (IEc, 2004) along with additional

information about the experts’ affiliations and fields of expertise. The size of the final expert panel

was dictated by time and resource constraints, and the decision to restrict the initial expert pool to

the NRC committees was made to help expedite the expert selection process. The experts were

provided a briefing book of reference materials and a copy of the elicitation protocol prior to the

interviews. Each interview lasts 6-8 hours.

9.B.3.2 Elicitation Results

Figure 9B-1 displays the responses of the experts to the quantitative elicitation question for

the mortality effects of changes in long-term PM2.5 exposures. The distributions provided by each

expert, identified by the letters A through E, are depicted as box plots with the diamond symbol

showing the median (50th percentile), a circle symbol showing the mean estimate, the box defining

the interquartile range (bounded by the 25th and 75th percentiles), and the whiskers defining each

expert's 90 percent confidence interval (bounded by the 5th and 95th percentiles of the distribution).
0

0 .5

1

1 .5

2

A B * C --8 u g /m 3 C --1 0 u g /m 3 C --1 5 u g /m 3 C --2 0 u g /m 3 

E x p e rt

% Increase in Mortality per 1 ug/m3 PM2.5

Figure 9B-1. Summary of Experts’ Judgments About the Percent Increase in Annual Average 

Mortality Associated with a 1 :g/m3 Increase in Annual Average Exposures to PM2.5

*Expert B specified this distribution for the PM/mortality coefficient above an uncertain threshold which he characterized 

15 with a modal value of 12 :g/m3.As illustrated here, considerable variation exists in both the median values and the spread of uncerta

experts. The median value of the percent change in annual non-accidental mortality per unit change in annual PM2.5 concentration (with

concentrations from 8 to 20 :g/m3) ranged from values at or near zero to a value of 0.7 percent. The variation in the responses largely re

amount of uncertainty each expert considered inherent in the key epidemiological results from long-term cohort studies, the likelihood oand the shape of the C-R function. The technical report (IEc, 2004) provides detailed descriptions of the experts’ judgments about these few brief observations relative to their responses below.

** Expert C specified a non-linear model and provided distributions for the slope of the curve at four discrete concentrations w
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As illustrated by the figure, the experts exhibited considerable variation in both the

median values they reported and in the spread of uncertainty about the median. In response to the

question concerning the effects of changes in long-term exposures to PM2.5, the median value

ranged from values at or near zero to a 0.7 percent increase in annual non-accidental mortality

per 1 :g/m3 increase in annual mean PM2.5 concentration (within a range of PM2.5 concentrations

from 8 to 20 :g/m3

). The variation in the responses for the effects of long-term exposures

largely reflects differences of opinion among the experts on a number of factors such as key

epidemiological results from long-term cohort studies, the likelihood of a causal relationship,

and the shape of the C-R function. Some observations concerning the outcome of the individual

expert judgments are provided below:

Key Cohort Studies. The experts' non-zero responses for the percent change in annual

mortality were mostly influenced by the Krewski et al., (2000) reanalysis of the original American

Cancer Society (ACS) cohort study and by the later Pope et al. (2002) update of the ACS study that

included additional years of follow-up. None of the experts placed substantial weight on the

mortality estimates from the Six-Cities study (Dockery et al., 1993) in composing their quantitative

responses, despite citing numerous strengths of that analysis. Concern about sample size and

representativeness of the Six Cities study for the entire U.S. appeared to be a major reason for deemphasizing those results.

Causality for Long-Term Effects. Three of the five experts gave distributions more heavily

weighted towards zero. Those experts were also the ones who gave the lowest probability of a

causal effect of long-term exposure to PM2.5 in the preliminary questions. All of the experts placed

at least a 5 percent probability on the possibility that there is no causal relationship between fine PM

exposure and mortality; as a result, all experts gave a fifth percentile value for the C-R coefficient

of zero. For most of the experts, this was based primarily on residual concerns about the strength

of the mechanistic link between the exposures and mortality. 

Shape of the C-R Function for Long-Term Effects. The other key determinant of each

expert's responses for long-term effects was his assumption about the nature of the C-R function

across the range of baseline annual average PM2.5 concentrations assumed in the pilot (8 to 20

:g/m3

). Three experts (A, D, and E) assumed that the function relating mortality with PM

concentrations would be log-linear with constant slope over the specified range. They therefore

gave a single estimate of the distribution of the slope describing that log-linear function. The other

two experts provided more complex responses.

Expert B assumed a population threshold in his model, below which there would be no effect

of increased PM2.5 exposure and above which the relationship would be log-linear. He characterized

his estimate of a possible threshold as uncertain, ranging between 4 :g/m3 and 15 :g/m3, with a

modal value of 12 :g/m3. He then described a distribution for the slope for the log-linear function
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that might exist above the threshold; this distribution is depicted in Figure 9B-2. The effect of

incorporating the uncertain threshold is essentially to shift his entire distribution downward.

Expert C believed that the increased relative risks for mortality observed in the cohort studies

were likely to be the result of exposures at the higher end of the exposure range, and he expected

there to be a declining effect on mortality with decreasing levels of PM2.5. He also argued that some

practical concentration threshold was likely to exist below which we would not observe any increase

in mortality. He reflected these beliefs by developing a non-linear model within the range from 8

to 20 :g/m3

; he described the model by providing distributions for the slope of the curve at four

discrete concentrations within the range. 
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0

0.5

1

1.5

2

Above threshold Incorporating

threshold**

 Expert B

% Increase in Mortality per 1 ug/m3 PM 2.5

Figure 9B-2.

Expert B’s Distributions for the Percent Increase in Annual 

Non-Accidental Mortality Associated with a 1 μg/m3 Increase 

in Long-term Exposures to PM2.5: Comparison of His Distribution 

Above a Threshold to His Expected Distribution* for the Range 8-20 μg/m3

* Expert B specified the threshold as uncertain between 4 and

15 :g/m3

 with a modal value at 12 :g/m3. He assumed the percent

increase in mortality to increase linearly with concentration above the

threshold. His effective distribution was simulated using Monte Carlo

techniques assuming an underlying distribution of population-weighted

annual average PM2.5 concentrations for the U.S. generated from the

BenMAP model (see the technical report (IEc, 2004) for details).
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Final Regulatory Impact Analysis

PP The Council is an advisory committee with an independent statutory charter that is organized and supported

under the EPA’s Science Advisory Board.

QQ Council/HES report: ”...in view of the fact that the pilot project is well-underway, the experts have already

been selected, and many (if not all) of the interviews have been conducted, the HES sees little potential benefit in

providing detailed suggestions about the design or conduct of the pilot study.” (EPA-SAB-COUNCIL-ADV-04-002,

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9B.3.3 Experts’ Views of Sources of Uncertainty

The experts were asked at several points during the interview to discuss the key sources of

potential bias and uncertainty in current evidence on which they relied for their judgments. In the

context of the quantitative discussion they were asked to list the top five issues. They were

encouraged to think about how these issues would affect the uncertainty surrounding their best

estimate of the potential impact on total mortality of a small change in long-term exposure to PM2.5.

The tables summarizing the factors identified by each expert may be found in Appendix E of the

technical report (IEc, 2004).

Many of the same factors appeared in the list of the five experts. However, the experts often

differed on whether a particular factor was a source of potential bias or uncertainty. Some of the

common concerns raised as either sources of bias or uncertainty, include:

• Residual confounding by smoking, 

• Residual confounding by “life-style” or other personal factors or “stressors,”

• Exposure errors/misclassification,

• The role of co-pollutants as confounders or effect modifiers, 

• Impact of the relative toxicity of PM components, 

• Representativeness of the cohort populations with respect to the general U.S.

population, and

• Investigator/publication biases.

Despite the many qualitative discussions about sources of uncertainty, because the

pilot study did not elicit quantitative judgments about the size and nature of impacts of each

source of uncertainty and bias, we were unable to systematically evaluate the nature of the

influence of these factors on the quantitative results provided by each expert unless an expert

explicitly adjusted his estimates by a particular factor. 

9B.3.4 Advisory Council Comments on the Preliminary Design of the Elicitation

As part of a review of the analytical blueprint of the EPA’s Second Prospective Analysis

of the Costs and Benefits of the Clean Air Act under section 812 of the Act, a panel of outside

experts - the Health Effects Subcommittee (HES) of the Advisory Council on Clean Air

Compliance Analysis (Council)pp - provided a limitedqq and preliminary review of the
Cost-Benefit Analysis

March 2004, page 34).

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methodology and design of the expert elicitation. In an Advisory issued by the Council to the

EPA (EPA-SAB-COUNCIL-ADV-04-002, March 2004), the Council-HES provided the

following comments with regard to the elicitation: 

• "We applaud the Agency’s interest in exploring the use of formal expert judgment as

a tool for improving uncertainty analysis and believe that the proposed pilot study has

great potential to yield important insights. The pilot is well designed to inform

subsequent and more comprehensive expert elicitation projects, but relies on the

opinions of a relatively small group of experts. It may provide preliminary

information about the general magnitude of the mortality effects, and may yield a

sense of both the uncertainty inherent in these estimates and the factors largely

responsible for such uncertainty. However, until the pilot study methods and results

have been subjected to peer review, it may be unwise for the Agency to rely directly

on these preliminary results in key policy decisions." 

• In presenting results of the pilot elicitation, “the HES advises the EPA to present the

entire collection of individual judgments; to carefully examine the collection of

individual judgments noting the extent of agreement or disagreement; to thoughtfully

assess the reasons for any disagreement; and to consider formal combinations of

judgments only after such deliberation and with full awareness of the context ...” 

• "The HES recognizes that in order to make the pilot tractable it was necessary to limit

participation, and is aware of the many factors which must be balanced in the

selections of expert panels (Hawkins and Graham, 1988), but is concerned about

whether the judgments of such a limited group can reasonably be interpreted as

representing a fair and balanced view of the current state of knowledge." 

9B.3.5 Limitations in Pilot Elicitation Design

The pilot elicitation has afforded many opportunities for learning about expert

elicitation in the context of economic benefits analysis. However, because this was an initial

assessment that was limited in scope (as is discussed in section 9B.1), this section briefly

discusses some of the limitations in the design of the pilot. Additional detail on the strengths and

weaknesses of the pilot are provided in the technical report (IEc, 2004).

• Short time-period to design and conduct the elicitation - The scope of the pilot was

limited in order to complete the assessment and present our findings as part of the

Final Nonroad Diesel Rule. Thus, there was a one-year time period in which were
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designed the elicitation, conducted the interviews, and provided an interpretation of

the results in this RIA and the technical report (IEc, 2004). In addition to designing

the elicitation with specific limitations as are discussed below, the experts we given

short notice of the elicitation (some experts were interested but not available in our

time frame), and we were required to process the results rapidly to meet the

rulemaking schedule. 

• The design and implementation of the elicitation has not undergone a complete

external peer review. While EPA is planning to conduct a peer review of the

elicitation process, we were not able to complete the review prior to the promulgation

of the final rule. The results of the pilot should be viewed tentatively until the full

peer review is complete.

• Small panel of experts - Due to resource constraints we limited the pilot to a panel of

five experts. As noted above, the SAB-HES expressed their concern “about whether

the judgements of such a limited group can reasonably be interpreted as representing

a fair and balanced view of the current state of knowledge.” They point to the many

factors which must be balanced in the selection of expert panels (Hawkins and

Graham, 1988) and there are numerous opinions among a large set of experts. 

Little analytical research has been conducted on the more difficult question of how to

determine the ideal number of experts for a particular application. We have not found

any analyses of the effect of expert panel size based on comparisons of empirical

results of expert judgment studies. A theoretical analysis by Clemen and Winkler

(1985) suggests that where data sources are moderately positively dependent there are

diminishing marginal returns to the value of information associated with each

additional data source. In the context of expert judgment studies, such a result

implies that when dealing with experts of similar backgrounds who rely on the same

models and studies, a larger expert panel may not provide significantly higher quality

results than a smaller one. However, the addition of an expert expected to provide a

more independent assessment, such as an expert from a different, but pertinent field,

would be expected to exhibit a much greater value of information. Clemen and

Winkler (1999) note that “heterogeneity among experts is highly desirable.” These

findings would appear to support addressing complex issues using a panel comprised

of relatively small subgroups (perhaps three to five experts each) from multiple

disciplines. Although the decision analysis field tends to use relatively small sample

sizes (i.e., typically 5-10 experts), some are not comfortable with obtaining a

combined distribution from such small numbers in the absence of an apriori

assessment of the degree to which the expert panel is likely to be representative of the
Cost-Benefit Analysis

RR While the Project Team initially considered using a highly aggregated approach that would have asked

experts to characterize a single overall PM / mortality effect due to both short- and long-term exposures to PM2.5. 

However, based on advice from the SAB-HES, we opted to disaggregate effects due to long- and short-term exposures.

The Project Team felt that separate questions to address effects of long- and short-term exposures, though still at a high

level of aggregation, would prove to be easier for experts to address than a question that "rolled up" all the effects into

a single estimate. This level of disaggregation also enabled the elicitation team to explore with experts possible overlap

in reported mortality effects detected using long-term and short-term epidemiological studies.

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overall population of relevant experts on the question of interest. The panel we used

may not have captured the full range of reasonable opinions. 

• Use of an aggregate elicitation question - The expert judgment literature discusses

two broad approaches to elicitation of judgments; an aggregated and a disaggregated

approach. As the term implies, an aggregated approach asks the expert to estimate

the quantity of interest directly; for example, the numbers of newspapers sold in the

U.S. in a particular year. In a disaggregated approach, the expert (or group of

experts) would be asked to construct a model for estimating the quantity of interest

and would be asked directly about the inputs to that model (e.g. population in each

state, percentage of the population that reads newspapers, etc.) The intuition is that it

is easier for experts to answer questions about the intermediate quantities than about

the total quantity. 

The project team carefully considered the relative advantages and disadvantages of

the two approaches. A major advantage of the disaggregated approach is a more

structured and transparent characterization of the key inputs and sources of

uncertainty in the final quantity of interest. However, the method does require

additional time and resources to develop a model structure (or in some cases, multiple

models) and set of inputs on which the experts can agree prior to the individual

elicitations. 

The limited time frame available to complete this assessment drove the decision to

undertake an aggregate approach to elicit the C-R coefficient for the PM2.5/mortality

relationship.rr Nonetheless, a major goal of the preliminary and follow-up questions

in the protocol was to identify critical issues that could be addressed through the

development of a more disaggregated approach in a future assessment. 

Thus, the design of the pilot limits our ability to determine the influence of any one

key factor over others in a large list of issues that the experts were to consider prior to

answering the quantitative question. It also limited the ability of the experts to

express their views about the difference in the C-R function based on the location in

the U.S. (i.e., the demographics of the exposed population, the air concentration of

PM and/or PM mixture). 
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• No workshop was conducted - It is customary to conduct a workshop prior to the

elicitation interview with the experts. This allows the experts to become familiar

with the protocol, the background materials contained in the briefing book, and to

discuss methods to limit bias during the interview. Due to time constraints for the

pilot, we did not conduct a pre-elicitation workshop.

• No calibration of experts - We do not have calibration measures that could be used to

assess the results of this pilot. At this point, we can only assess the process – did the

pilot assessment employ a structure, supporting materials, and a process that enabled

experts to make judgments that would be likely to be well calibrated? The peer

review for this aspect is still underway. Nevertheless, without calibration measures,

we cannot weight experts based on their performance on calibration tasks.

• Full-day elicitation - The elicitation interview with each expert took a full-day to

complete. Again, experts were given short notice of the elicitation and found time in

their schedules to participate, yet not all of the experts were available for the full-day

interview. The length of the interview could lead to response fatigue that could affect

the outcome of the experts’ response. 

9B.3.6 Combining the Expert Judgments for Application to Economic Benefit

Analyses

Analysts must give careful thought to whether and how to combine the results individual

expert judgments into a single distribution. When dealing with a small sample number of

experts, the analyst must be particularly careful to identify the influence of each expert’s

response on the combined distribution. Therefore, we considered four alternative methods for

combining the pilot results. However, the Project Team identified significant issues associated

with each of the methods. In this section, we discuss the issues we considered in combining the

results of the pilot and how we came to the conclusion that for the illustrative benefits analysis

presented in Section 9B.5 below, we would present both the individual quantitative distributions

of the C-R coefficient elicited from the five experts interviewed as well as results based on a

probabilistic estimate that represents the combined results of the pilot based on an equal

weighting of the calculated change in mortality incidence based on the individual judgments. 

9B.3.6.1 Background

Combination of expert judgments is not strictly necessary; some investigators (e.g.,

Hawkins and Graham, 1990; Winkler and Wallsten, 1995; and Morgan et al., 1984) have

preferred to keep expert opinions separate in order to preserve the diversity of opinion on the
Cost-Benefit Analysis

A "Motivational bias" refers to the willful distortion of an expert's true judgments. The origins of this bias can

vary, but could include, for example, a reluctance to contradict views expressed by one's employer or a deliberate attempt

to skew the outcome of the study for political gain.

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issues of interest. In such situations, the range of values expressed by the experts can help

decision-makers to understand the sensitivity of their analyses to the analytical model chosen,

thereby bounding possible outcomes. Individual judgments can also illustrate varying opinions

arising from different disciplinary perspectives or from the rational selection of alternative

theoretical models or data sets (Morgan and Henrion, 1990). Nonetheless, analysts are often

interested in developing a single distribution of values that reflects a synthesis of the judgments

elicited from a group of experts. 

There are also some advantages to combining the results across experts. An extensive

literature exists concerning methods for combining expert judgments. These methods can be

broadly classified as either mathematical or behavioral (Clemen and Winkler, 1999). 

Mathematical approaches range from simple averaging of responses to much more complex

models incorporating information about the quality of expert responses, potential dependence

among expert judgments, or (in the case of Bayesian methods) prior probability distributions

about the variable of interest. Behavioral approaches require the interaction of experts in an

effort to encourage them to achieve consensus, either through face-to-face meetings or through

the exchange of information about judgments among experts. As noted in the technical report

(IEc, 2004) , there are both methodological and practical issues arguing against a behavioral

approach. Therefore, we used a mathematical combination process to derive a single

distribution.

One advantage of mathematical combination over behavioral approaches is the ability to be

completely transparent about how weights have been assigned to the judgments of specific experts

and about what assumptions have been made concerning the degree of correlation between experts.

Several approaches can be used to assign weights to individual experts. Weights can be assigned

based on the analyst's opinion of the relative expertise of each expert; on a quantitative assessment

of the calibration and informativeness (i.e., precision) of each expert based on their responses to a

set of calibration questions (as described in Cooke, 1991); or on weights assigned by each expert,

either to him or herself or to the other experts on the panel (see Evans et al., 1994 for an example

of this approach). Ideally, such a weighting system would address problems of uneven calibration

and informativeness across experts, as well as potential motivational biases (Cooke, 1991).a

 In

practice, appropriate weights can be difficult to determine, though Cooke and others have conducted

considerable research on this issue. 

At the design stages of the pilot, we decided that the resulting expert judgments would be

combined using equal weights, essentially calculating the arithmetic mean of the expert responses,

for simplicity and transparency. The reasons for choosing equal weights were both practical and
Final Regulatory Impact Analysis

B

 Expert B specified a distribution for the C-R coefficient for PM2.5 concentrations above a threshold and

assigned the coefficient a value of zero for all PM concentrations below the threshold. He then specified a

probability distribution to describe the uncertainty about the threshold value. Expert C specified separate

distributions for the C-R coefficient at four discrete points within the concentration ranges defined in the protocol, to

represent a continuous C-R function whose slope varied with the PM2.5 concentration. Expert C indicated that the

coefficient value between these points was best modeled as a continuous function, rather than a step function. Both

experts assumed the same functional forms in responding to elicitation question.

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methodological. Development of defensible differential weights was not possible given the

expedited schedule for this project. Although we did conduct a sample calibration exercise with

each expert, the purpose of the exercise was to train the experts in providing quantitative responses,

not to develop calibration scores that would be used to weight experts. Some empirical evidence

suggests that the simple combination rules, like equal weighting, perform equally well when

compared to more complex methods in terms of calibration scores for the combined results (Clemen

and Winkler, 1999). The methods to combine the expert judgments will be explicitly addressed

during the peer review of the pilot assessment.

9B.3.6.2 Alternative Combination Methods

While a combination method using equal weights for the results of each expert is

straightforward in principle, applying it in this context of the results of the pilot was complicated

by the fact that the elicitation protocol gave the experts freedom to specify different forms for the

C-R function. If all the experts had chosen the same form of the C-R function,(e.g., if each expert

had specified a log-linear C-R function with a constant, but uncertain, C-R coefficient (i.e., slope)

over the PM range specified in the protocol) the combination of their distributions for the C-R

coefficient would require a simple averaging across experts at each elicited percentile. However, in

this assessment, three experts specified log-linear functions with constant C-R coefficients over the

specified range of PM2.5 concentrations, and two of the experts specified the C-R coefficient as

likely to vary over the range of specified PM2.5 concentrations (as discussed in Section 9B.4.2

above). These more complex C-R functions necessitated some additional steps in the calculation

of the combined results.

As discussed in the technical report for the pilot (IEc, 2004), individual response either can

be combined before application of the benefits model or during the application of the model,

allowing each expert's C-R function to be estimated in the benefits model independently.

Specifically, we derive the total mortality incidence for each expert, and combine (or pool) the

estimates into an aggregate value before taking an average of the mortality incidence. This is

referred to as a "pooled" approach and is used in our modeling framework for other benefit

endpoints that have multiple C-R function (due to multiple studies). We prefer the pooled approach

because it seems to reduce the amount of alteration of the actual step-function responses provided

by Experts B and C (although some adjustments must still be made)b

. Details of the illustration are

provided in Section 9B.6.
Cost-Benefit Analysis

C To facilitate Monte Carlo sampling, we evaluated the fit of the BENMAP data to several distributional forms,

ultimately selecting a normal distribution, truncated at zero, with a mean of 11.04 μg/m3

 and a standard deviation of 2.32

μg/m3

.

D An example for mortality effects from long-term exposures helps illustrate this approach. Expert B estimated

that he was 75 percent sure (i.e., his 75th percentile) that the percent increase in mortality would be less than or equal to

0.5 percent per 1 μg/m3 change in PM2.5 concentration if the baseline concentration were above the threshold, but zero

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The alternative would be to combine the individual expert judgments into a single C-R

function before applying the results to the benefits model. Below, we present three approaches

we considered for combining the expert judgments before applying the benefits model. Among

the three approaches to combining expert judgments before the benefits analysis, the primary

difference is how they account for the underlying particulate air pollution levels. The first option

assumes a uniform distribution and equal weighting, which involves taking a simple average of

responses across experts for each percentile. In a second combination method, we combined the

results using a normal distribution describing population-weighted annual average PM2.5

concentration data generated from EPA's Environmental Benefits and Mapping Analysis

Program (BenMAP), the model EPA currently uses for economic benefit analyses of air quality

regulations affecting PM and other criteria pollutants.c 

As discussed above, for the two of the experts that specified a C-R function that varied

over the range of PM concentrations., their estimated C-R function necessitated some additional

steps in the calculation of the combined results. To derive a single distribution across all experts

for a particular range of exposures (e.g. 8-20 :g/m3

 annual average PM2.5), we first needed to

estimate an “effective” distribution of uncertainty about the C-R coefficient for both Experts B

and C across that range by using Monte Carlo simulation (Crystal Ball® software) to estimate the

expected value of each percentile elicited across the full PM2.5 range specified. Specifically, the

additional steps we took for this combination method are as follows: 

• Expert B specified a distribution for the C-R coefficient fo rPM2.5 concentrations

above a stated threshold and assigned the coefficient a value of zero for all PM

concentrations below the threshold. He then specified a probability distribution to

describe the uncertainty about the threshold value. Thus, we conducted Monte Carlo

sampling using two distributions: his uncertainty distribution for the threshold, and an

assumed distribution of baseline PM2.5 concentrations for the PM2.5 range specified in

the elicitation protocol. On each iteration, we selected a value from each of these two

distributions and compared them. If the selected baseline concentration was less than

or equal to the selected threshold value, each of the percentiles of Expert B’s

uncertainty distribution was assigned a zero value (no mortality effect); if the

concentration was greater than the threshold, we assigned each percentile the "abovethe-threshold" value specified by Expert B in his interview.d

 We repeated this
Final Regulatory Impact Analysis

percent if it were below the threshold. If on a given iteration, the program selects a baseline concentration of 12 μg/m3

and a threshold level of 10 μg/m3, we assign his 75th percentile the value of 0.5. If the threshold level selected were 15

μg/m3

, the 75th percentile would be assigned a value of zero.

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process for thousands of iterations and then took the average value for each of the

percentiles to obtain Expert B's "effective" distribution of uncertainty about the C-R

coefficient across each range of exposures.

• Expert C specified separate distributions for the C-R coefficient at four discrete

points within the concentration ranges defined in the protocol, to represent an

continuous function whose slope varied with the PM concentration. Thus, we first

randomly sampled from the assumed distribution of baseline PM concentrations. We

then linearly interpolated between Expert C's responses at the two points nearest to

the sampled PM concentration, to estimate his uncertainty distribution for the C-R

coefficient at the sampled concentration. For example, Expert C provided slope

values at PM2.5 concentrations of 8, 10, 15 and 20 for mortality effects of long-term

exposure. If, on a given iteration we selected a PM2.5 concentration of 12 μg/m3

, we

would generate a slope at each percentile of his uncertainty distribution by

interpolating between Expert C's responses at 10 and 15 μg/m3

. We repeated this

process for thousands of iterations and then took the average value for each of the

percentiles to obtain the "effective" distribution of the average slope of Expert C's CR function.

While the uniform distribution is the simplest method of combining the expert judgments,

it required us to alter the true responses of Experts B and C. It is also based on a uniform

distribution, which does not match the observed PM2.5 concentrations that tend to be skewed toward

the lower concentration values. The estimates of Expert B and C’s “effective” distributions, and

thus the combined expert distribution, are all sensitive to the probability density function chosen to

describe the U.S. baseline PM2.5 concentrations in the simulations. This sensitivity arises because

both Experts B and C assume that the effect of an increase in PM2.5 concentration on mortality

depends on the initial PM2.5 concentration. Table 9B-3 presents the resulting values of the

distribution for these two methods of combining the results of the pilot. 
Cost-Benefit Analysis

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Table 9B-3. Methods for Combining Expert Judgments: Combined C-R function

with Uniform Distribution and a Population-Weighted Distribution

Percentiles

Combined

Expert Judgments using

a Uniform Distribution

of Baseline Annual

Mean PM2.5

Concentrations

Combined Expert

Judgments Based on

Population-Weighted

Distribution of Baseline

Annual Mean PM2.5

Concentrations in U.S.

95th %ile 1.05 0.93

75th %ile 0.65 0.59

50th %ile 0.33 0.3

25th %ile 0.17 0.16

5th %ile 0.00 0

Minimum 0.00 0

Maximum 1.71 1.5

 Given the differences in the responses given by Experts B and C at various levels of PM

concentrations (i.e., a conditional C-R function), we considered a third combination method in

which we calculate combined expert distributions at four different PM2.5 baseline concentrations. 

Using the methods described above, we first calculated Expert B’s and C’s distributions at the

four concentration points and then averaged them with the distributions of the other three experts

(which remain constant over the concentration range) using equal weights. This method reduces

the level of adjustments that are made to Expert B's and C's response function in that we estimate

four C-R function for each individual, rather than one smoothed function. The functions for the

three other experts remain log-linear. Results of this combination method are provided in Table

9B-4.
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Table 9B-4. Combined Concentration-Response Function Conditional to PM

Concentrations

Percentiles 8 ug/m3 12 ug/m3 15 ug/m3 20 ug/m3

95th percentile 0.82 0.99 1.08 1.20

75th percentile 0.56 0.61 0.64 0.76

50th percentile 0.30 0.30 0.30 0.42

25th percentile 0.16 0.16 0.16 0.24

5th percentile 0 0 0 0

Overall, the combination methods considered result in fairly similar results at the

median and mean relative risk estimate. However, slight differences occur in the tails of the

distribution in their characterization of uncertainty. In figure 9B-2, the C-R function for the

population-weighted combination method was compared to the existing cohort epidemiological

studies of the long-term PM2.5/mortality relationship. We observe that the results of the pilot

elicitation are generally within the range of findings from these epidemiological studies. 

However, as expected, the elicitation results in a larger spread of uncertainty than is given by the

standard errors of the individual studies. 
Cost-Benefit Analysis

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0

0.5

1

1.5

2

Com bine d

Ex pe rt

D istrib u tio n *

P o p e e t a l., 1995 P o p e e t a l.,

R e a n a lysis, 63

citie s, K re w ski,

2000

P o p e e t a l., 200

% Increase in Mortality per 1 ug/m3 PM2.5

Figure 9B-2. Comparison of Combined Expert Judgment Distribution to Selected Published Studie
Final Regulatory Impact Analysis

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9B.3.5 Limitations of Combining Expert Judgments

Although we present several methods for combining the results of the pilot, there are

several limitations in interpreting the pilot results that should be considered. 

• The conditional functions of Experts B and C required us to estimate some values on

the C-R function between the points that were elicited, which requires an

extrapolation from the response provided in the pilot to create continuous

distributions.

• There are many methods available to combine the responses from the experts. Each

method has advantages and disadvantages from a statistical viewpoint. The project

team is not aware of any rule-of-thumb in statistics that would provide guidance for

combining linear and non-linear functions. Therefore, we present four alternative

methods for combining the results as an illustration of potential combinations of the

results, and have asked for a peer review of these methods. 

• In designing the pilot, there was a decision to combine the results of the individual

experts using an equal weighting. In some elicitation studies, the authors use a

calibration measure to weight the experts appropriately. Because we did not conduct

a calibration exercise, we present only an equal weighting of the responses. 

• We have used a normal distribution to characterize the pilot results, but the

distribution could potentially be skewed due to the bounding at zero. The C-R

functions are bounded by zero, and anchored to one data source. There is a concern

that the upper-end of the distribution resulting from the pilot may not fully reflect the

available data and knowledge on the PM/mortality relationship. There may have

been some anchoring to the study results from the ACS cohort, and less use of the

Six-Cities study in the characterization of uncertainty upper-bounds. However, the

experts were provided the Six Cities results in their briefing books as background

material. 

9B.4. Illustrative Application of Pilot Expert Elicitation Results

In this section, we apply the pilot expert elicitation results, using the pooled approach

discussed above for combining results across participants to the VSL distribution discussed in

Chapter 9 (section 9.3.4), thereby providing an illustrative example of how one might translate

the results from the pilot elicitation into quantified estimates of economic benefits. The analysis

is based on the modeled air quality changes conducted for the preliminary nonroad diesel control

option in 2030. As such, the results are comparable to the point estimates provided in Appendix
Cost-Benefit Analysis

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9A, but not to those in Chapter 9. The values generated below do not reflect the Agency's

estimates of the benefits of the emissions reductions expected from the Final Non-Road Diesel

rule and are included solely as an illustration of the impacts of using expert elicitation based

distributions for premature mortality associated with long-term exposure to PM2.5 rather than a

data-derived distribution. 

9B.5.1 Method 

9B.5.1.1 Concentration-Response Distribution Based on Combined Results Across

Experts

As discussed in Section 9B.4.5, we converted each expert’s percentile responses about

mortality associated with long-term exposure into a custom distribution such that each percentile

is correctly represented and percentiles in between are represented as continuous functions

(custom distributions were generated using Crystal Ball and are represented as 15,000 equally

probable points).

For experts A, D, and E, we used a standard log-linear functional form:

 (4) ∆ ∆

yy e x =⋅ − ⋅

0 ( ), 1 β

where we set $ equal to ln(1+B/100), where B is the percent change in all cause mortality

associated with a one :g reduction in PM2.5. BenMAP then represents the distribution of )y

based on the custom distribution of $.

Expert C provided a set of conditional C-R functions for different baseline levels of

PM2.5. Expert C provided four conditional responses, one for 8 :g/m3, one for 10 :g/m3, one for

15 :g/m3, and one for 20 :g/m3. In order to “fill-in” the C-R function for intermediate baseline

PM2.5 values, we linearly interpolated between the responses for each pair of points, e.g. 10 to 15

or 15 to 20. We calculated interpolated values for 13 points, ranging from 8 :g to 20 :g. For

baseline values less than 8 :g, we assigned a value of zero (essentially assuming a threshold at 8

:g). For baseline values greater than 20, we assigned the values provided by Expert C for 20 :g. 

This may result in an underestimate of the incidence of mortality for Expert C. For each of the

conditional functions, we used a log-linear specification, similar to A, D, and E. Total incidence

of mortality for Expert C is the sum of the conditional estimates over the range of baseline air

concentrations.

Expert B provided a log-linear C-R function, conditional on an unknown threshold

characterized by a triangular distribution bounded by 4 :g and 15 :g, with a mode at 12 :g. We

discretized the triangular distribution into 12 ranges of unit length (e.g. 4 to 5, 5 to 6, etc.) and
Final Regulatory Impact Analysis

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calculated the expected value of the response at each population gridcell based on the observed

baseline PM2.5 and the probability of that baseline value exceeding the potential threshold. We

assume that if a grid cell has a baseline value above the threshold, then the full value of the

reduction in PM2.5 at that grid cell is associated with a reduction in mortality. This may result in

an overestimate of the mortality impact for Expert B because for grid cells where the baseline

level is only marginally above the threshold, a benefit might only accrue to the change in PM2.5

down to the threshold. The rest of the change would not result in any mortality reduction. 

Because most of the changes in air quality are relatively small (population weighted change in

annual mean PM2.5 is -0.59 :g), this should not be a large issue. 

 To put these estimates in perspective, it is useful to summarize the projected baseline

(pre-nonroad diesel regulations) air quality in 2030. Table 9B-5 lists the population distribution

of baseline concentrations of PM2.5 in 2030:

Table 9B-5. Population Distribution of Baseline Ambient PM2.5

Baseline PM2.5 (:g/m3) 2030

Population

(millions)

Percent of

Total 2030

Population

PM2.5<5 3.5 1.0%

5#PM2.5<10 68.8 19.5%

10#PM2.5<15 198.1 56.2%

15#PM2.5<20 66.1 18.8%

20#PM2.5<25 12.1 3.4%

25#PM2.5<30 4 1.1%

9B.5.1.2 Estimated Reduction in Premature Morality and Valuation

Based on the air quality modeling conducted for the Nonroad Diesel preliminary

control option, we calculated the reduction in incidence of premature mortality associated with

PM2.5 and the value of that reduction. We used Monte Carlo simulations to derive the

distributions of the dollar values of estimated reductions in premature mortality. For each

expert, the Monte Carlo simulation generates a dollar value by randomly sampling from the

distribution of the reduction in mortality incidence and the distribution of VSL (normally

distributed with a mean of $5.5 and a 95 percent confidence interval between $1 and $10

million) and multiplying the values together. This yields an estimate of the dollar value of the

mortality reductions. This process is repeated 5,000 times to generate a distribution of dollar
Cost-Benefit Analysis

A As discussed above, the elicitation results were combined assuming equal weight for each expert’s distribution.

We assumed complete dependence of the expert’s distributions for this illustrative analysis, so that each percentile of

the pooled distribution is simply the average of the corresponding percentiles of the 5 experts.

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values. The Monte Carlo process was conducted using the estimated distribution for each expert

individually and for the combined (pooled) distribution, as well as for the distribution derived

from the Pope et al. (2002) study.

9B.5.2 Results

Figure 9B-4 presents box plots that display the distribution of the reduction in PM2.5

related premature mortality based on the concentration response distributions provided by each

expert, as well as that based on the pooled response.a

 For comparison, the figure also displays

the distribution derived from the statistical error associated with Pope et al (2002). The figure

shows that the average annual number of premature deaths avoided for the “modeled

preliminarily control option” ranges from approximately 4000 to 19,000, depending on the

concentration response function used. The medians span zero to 16,000, with the zero value due

to the low threshold associated with one of the expert’s distributions. Specifically, because less

than a quarter of the population is expected to live in areas with PM2.5 levels above the

threshold specified by expert C, and much of the decrease in PM2.5 predicted by the preliminary

control option occurs below that threshold, a much smaller decrease in premature morality is

predicted for expert C than those experts who provided continuos C-R functions down to zero

(PM2.5) as well as for expert B who provided an uncertain threshold. Furthermore, note that at

the 50th and 75th percentiles, the C-R functions provided by all of the experts predict positive

benefits from the modeled control option.

The boxplots displayed in Figure 9B-4 are derived by applying the C-R distributions

specified by each expert (as presented in Figure 9B-1) to the change in air quality predicted by

the preliminary non-road diesel control option. Although the figures 9B-3 and 9B-1 show

similar patterns, there are important differences. Specifically, the ratio of 75th percentiles of the

C-R functions specified by experts A and B (as denoted in Figure 9B-1) is 0.4, whereas the ratio

of the predicted change in incidence of premature mortality associated with the modeled

preliminary control option is 0.5. This 25% increase in the ratio suggests a larger effective

difference in the distributions between the experts than was evident before applying the expert's

C-R functions to a predicted change in air quality and highlights the impact of the air quality

change predicted on the choice of C-R function used in the benefits analysis.

The combined expert distribution depicted in Figure 9B-4 provides additional insights. 

The combined (average) distribution has a 90 percent credible interval between zero and 24,000. 

When compared with results derived from the Pope et al. (2002) study, it is clear that the

combined expert distribution reflects greater uncertainty about the estimated reduction in
Final Regulatory Impact Analysis

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premature mortality, as well as placing more weight on the lower end of the distribution. The

mean estimate from the combined expert distribution is almost 30 percent lower than the mean

derived from the Pope et al. (2002) distribution. However, the 90 percent confidence interval

based on the standard error from Pope et al. (2002) is completely contained within the 90 percent

credible interval of the combined expert distribution. 

Figure 9B-5 shows the same data using cumulative distribution functions (CDFs). This

figure is valuable for demonstrating differences in degree of certainty in achieving specific

reductions in premature mortality. For instance, the Pope et al. 2002 concentration response

distribution predicts a 20% chance that there will be at least 10,000 fewer premature deaths,

whereas the pooled distribution predicts a 60% chance of the same reduction in premature

deaths. The probabilities associated with the individual experts for avoiding 10,000 premature

deaths range from about 28% to 98%, demonstrating once again the sensitivity of the estimate to

assumptions regarding the concentration response function. The CDFs of the estimated

reductions in premature mortality shows that for several experts, there is a small probability of a

substantially higher estimate. For example, the 75th percentile of the distribution based on

Expert B’s responses is at 8,800, while the 99th percentile for that distribution is almost 4 times

higher, at 34,000. The CDF also shows that while most of the experts provided fairly wide

distributions, reflecting a lack of confidence in the precision of the empirical data, the CDF

based on Expert C’s responses is much narrower, reflecting the high degree of confidence he

placed on the existence of a threshold below 15 :g. 

Figures 9B-6 and 9B-7 use box plots and CDFs to display the estimated dollar value of these

annual reductions in premature mortality. Whereas the average based on the Pope et al 2002

distribution is $94 billion, the average based on the pooled estimate is $67 billion, a difference of

approximately one-third. Once the concentration response distributions are combined with the VSL

distributions, not only are the mean values closer to one another, but the distributions show

considerably more overlap.

Because these distributions are the result of a Monte Carlo simulation combining the

non-normal distributions for reductions in mortality with a normal distribution for VSL, the

resulting distributions will also be non-normal, but the shape depends on the skewness of the

input distribution of mortality reductions. For example, the ratio of the 95th to 75th percentile of

mortality reductions for Expert B is 3.1, while the same ratio for the value of mortality

reductions is 4.2, indicating the value distribution is more skewed than the reductions

distribution. In general, combining normal or left skewed distributions in a mulitplicative

fashion will result in left skewed distributions with greater skewness than the input distributions. 

So even for the normally distributed estimates based on Pope et al. (2002), the value distribution

is somewhat skewed, because it is the result of multiplying two normally distributed random

variables. 
Cost-Benefit Analysis

B

Note that visibility benefits are treated as fixed for this illustrative analysis. We are working on methods to

characterize the uncertainty in visibility and other non-health benefits.

9-239

The shapes of the two distributions are more similar in this case because both reflect

the same additional information in the VSL distribution. This demonstrates that as additional

sources of uncertainty are added to the analysis, the influence of any one source of uncertainty

will fall. Because VSL is a large source of uncertainty, the influence on overall uncertainty

relative to the distribution of the mortality reduction is also large. All of the distributions of the

value of mortality reductions have a small negative tail, this time due to propagation of the

normally distributed VSL, which has a small amount of the distribution below zero. Again, we

interpret this as a statistical artifact rather than a true probability that the value of a statistical life

is negative (implying that individuals would pay to increase the risk of death). 

We used additional Monte Carlo simulations to combine the expert-based

distributions for the dollar benefits of mortality with the distributions of dollar benefits for the

remaining health and welfare endpoints to derive estimates of the overall distribution of total

dollar benefitsb

. The box plots for these distributions of overall dollar benefits associated with

the modeled nonroad diesel preliminary control options are presented in Figure B-8. Because

mortality accounts for over 90 percent of the benefits, the addition of other endpoints has little

impact on the overall distributions. The overall mean annual total dollar benefits in 2030 for the

distribution incorporating the combined expert distribution for reductions in premature mortality

is $70 billion, compared to $96 billion for the results derived from the Pope et al. (2002) study

for the nonroad diesel modeled preliminary control option.

For clarity of presentation, in Figure 9B-9, we present CDFs for total dollar benefits

only for the combined expert distribution and results derived from the Pope et al. (2002) study. 

These again suggest that the use of the expert elicitation based representation of uncertainty in

the relationship between PM2.5 and premature mortality has a large impact on the shape and

range of the distribution of total benefits. The Pope et al. (2002) derived results have an

approximately Weibull shaped distribution with a range from 5th to 95th percentiles of $23 billion

to $190 billion, or about one order of magnitude. The distribution of total dollar benefits

incorporating the combined expert distribution for reductions in premature mortality has a much

more skewed shape with an elongated positive tail above the 75th percentile with a range from 5th

to 95th percentiles of $3 billion to $240 billion, or about two orders of magnitude. 
9,900

18,900

9,600

3,900

6,200

11,300

0

5,000

10,00015,00020,00025,00030,00035,00040,000

Expert A Expert B Expert C Expert D Expert E Combined

Experts

Pop

(2

Statist

Reduction in Premature Mortality in 2030 . 

Note: Distributions labeled Expert A - Expert E are based on individual expert responses. The distribution labeled Combined Experts is based on the averaged distributions of reduced incidence of premature mortality across the set of experts. The distribution labeled Pope et al. (2002) Statistical Error is based on the mean and standard error of the C-R function from the study.

Figure 9B-4 Results of Illustrative Application of Pilot Expert Elicitation: Annual Reduction

Premature Mortality in 2030 Associated with the Modeled Preliminary Control Option for the Nonro
0

0.10.20.30.40.50.60.70.80.9

1

0 10,000 20,000 30,000 40,000 50,000 6

Annual Reductions in Incidence of Premature Mortality in 2030

Probability

Expert A Expert B Expert C Expert D Expert E Combined Experts Pope et al (2002

Note: Distributions labeled Expert A - Expert E are baexpert responses. The distribution labeled Combined on the averaged distributions of reduced incidence of across the set of experts. The distribution labeled PoStatistical Error is based on the mean and standard efunction from the study.

Figure 9B-5. Cumulative Distribution Functions for Annual Reductions in Premature Mortality in 

with the Nonroad Diesel Modeled Preliminary Control Option
Final Regulatory Impact Analysis

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$67,00

$128,000

$65,000

$26,000

$42,000

$77,000

$0

$50,000

$100,000$150,000$200,000$250,000$300,000$350,000$400,000

Expert A Expert B Expert C Expert D Expert E Combined Experts 

Millions of $2000 .

Note: Mortality distributions labeled Expert A - Expert E are based on individual expert responses. The mortality distribution labeled Pooled Expert Estimate is based on the averaged distributions of reduced incidence of premature mortality across the set of experts. The mortality distribution labeled Pope et al. (2002) statistical error is based on the mean and standard error of the C-R function from the study. Mortality valuation is based on a normally distributed VSL with a mean of $5.5 million and a 95% CI between $1 and $10 million. The VSL distribution has then been adjusted for income growth out to 2030 using an adjustment factor of 1.23.

Figure 9B-6. Results of Illustrative Application of Pilot Expert Elicitation: Dollar Value of Annual R

Premature Mortality in 2030 Associated with the Modeled Preliminary Control Option for the Nonro
0

0.10.20.30.40.50.60.70.80.9

1

-$10,000 $90,000 $190,000 $290,000 $390,000 $490

Million ($2000)

Cumulative Probability

Expert A Expert B Expert CExpert D Expert E Combined ExpertsPope et al (2002) Statistical Error

Note: Mortality distributions labeled Expert A - Expert E are based on individual expert responses. The mortality distribution labeled Pooled Expert Estimate is based on the averaged distributions of reduced incidence of premature mortality across the set of experts. The mortality distribution labeled Pope et al. (2002) statistical error is based on the mean and standard error of the C-R function from the study. Mortality valuation is based on a normally distributed VSL with a mean of $5.5 million and a 95% CI between $1 and $10 million. The VSL distribution has then been adjusted for income growth out to 2030 using an adjustment factor of 1.23.

Figure 9B-7. Cumulative Distribution Functions for Dollar Value of Annual Reductions in 

Premature Mortality in 2030 Associated with the Nonroad Diesel Modeled Preliminary Control Option
$130,000

$69,000

$32,000 $47,000

$80,000

$0

$50,000

$100,000$150,000$200,000$250,000$300,000$350,000$400,000

Expert A Expert B Expert C Expert D Expert E Pooled Exp

Estimate

Million 2000$

Note: All non-mortality distributions are based on classical statistical error derived from the standard errors reported in epidemiology studies and distributions of unit values based on empirical data. Visibility benefits are included as a constant. Mortality distributions labeled Expert A - Expert E are based on individual expert responses. The mortality distribution labeled Pooled Expert Estimate is based on the averaged distributions of reduced incidence of premature mortality across the set of experts. The mortality distribution labeled Pope et al. (2002) statistical error is based on the mean and standard error of the C-R function from the study.

Figure 9B-8. Results of Illustrative Application of Pilot Expert Elicitation: Dollar Value of Tota

Health and Visibility Benefits in 2030 Associated with the Modeled Preliminary Control Option 
0

0.10.20.30.40.50.60.70.80.9

1

-$6,000 $44,000 $94,000 $144,000 $194,000 $244,000 $294,000 $344,000 $394,0

Annual Total Benefits in 2030 (Million $2000)

Cumulative Probability

Combined Experts Pope et al (2002) Statistical Error

Note: All non-mortality distributions are based on classical statisticaderived from the standard errors reported in epidemiology studies adistributions of unit values based on empirical data. Visibility benefincluded as a constant. Mortality distributions labeled Expert A - Exare based on individual expert responses. The mortality distribution Pooled Expert Estimate is based on the averaged distributions of reincidence of premature mortality across the set of experts. The modistribution labeled Pope et al. (2002) statistical error is based on thand standard error of the C-R function from the study.

Figure 9B-9. Cumulative Distribution Functions of Dollar Value of Total Annual PM-related Health a

Benefits in 2030 Associated with the Nonroad Diesel Modeled Preliminary Control Option
Final Regulatory Impact Analysis

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9B.5.3 Limitations of the Application of the Pilot Elicitation Results to

the Nonroad Scenario

The results presented in this section should be viewed cautiously given the limited

scope of the pilot, and the limitations of the elicitation design and methods used to combine the

expert judgments discussed above. Therefore, the results presented above should be considered

“illustrative” until both the peer review of the pilot is complete and the methods used to interpret

and apply the results of the pilot have been peer-reviewed and accepted. Until this occurs, we do

not recommend applying this method in other regulatory analyses.

Specific limitations of the illustrative application include:

• Extrapolation of percentile responses provided by individual experts. Each expert

provided minimum and maximum values, as well as the 5th, 25th, 50th, 75th, and 95th

percentiles. In order to generate the continuous distributions of mortality impacts, we

had to make assumptions about the continuity of the distributions between the

reported percentiles. This adds uncertainty to the results.

• Interpolation of C-R relationship across PM2.5 levels. Expert C provided a set of

conditional distributions of the C-R relationship conditioned on the baseline level of

PM2.5. Because he only provided functions for a limited number of baseline levels,

we had to interpolate the values between levels, introducing additional uncertainty. 

In addition, Expert C provided no information on the C-R function for baseline PM2.5

levels below 8 :g/m3 or above 20 :g/m3. We assumed no mortality impacts for

baseline levels lower than 8 and no increase in the C-R function above 20. This

likely biased our results downward.

• Interpretation of Expert B results. Expert B provided a conditional distribution for

the C-R function, conditioned on an uncertain threshold. Expert B provided

additional information about the shape of the distribution for the threshold. To

develop an applied function, we assumed that the uncertain threshold could be

incorporated into the C-R function through the construction of an expected value

function. The specific functions may lead to a slight overestimate of mortality

impacts.

• Use of simple averaging of expert results. To develop the combined expert

distribution, we used equal weights for each expert. Given the lack of calibration

questions in the pilot elicitation, this is the most defensible approach. However,

many expert elicitation applications have use more complex weighting schemes based

on how well experts are calibrated.
Cost-Benefit Analysis

9-247

• Ranges based on individual experts should be viewed with caution as they represent

only a single individual’s interpretation of the state of knowledge about PM and

mortality. Results for individual experts should not be extracted and presented

without reference to the full range of results across the five experts. 

• Any range of results presented based on this application should be presented along

with their relative likelihood (i.e., the percentile represented in the distribution).
Final Regulatory Impact Analysis

9-248

References for Appendix 9B

Amaral, D. 1983. Estimating Uncertainty in Policy Analysis: Health Effects from

inhaled Sulfur Oxides. Ph.D. Thesis, Department of Engineering and Public Policy, Carnegie

Mellon University, Pittsburgh, PA. 

Ayyub, B.M. Elicitation of Expert Opinions for Uncertainty and Risks. CRC Press,

Florida, 2002.. 

Cooke, R. Experts in Uncertainty. Oxford University Press, New York, 1991. 

Evans, J.S., J.D. Graham, G.M. Gray, R.L. Sielken 1994a. “A distributional approach to

characterizing low-dose cancer risk.” Risk Analysis 14(1): 25-34.

Evans, J.S., G.M Gray, R.L. Sielken, Jr., A.E. Smith, C. Valdez-Flores, and J.D. Graham.

1994b. "Use of Probabilistic Expert Judgment in Uncertainty Analysis of Carcinogenic Potency,"

Regulatory Toxicology and Pharmacology. 20:25-36.

Hawkins, N.C. and J.S. Evans 1989. “Subjective Estimation of Toluene Exposures: A

Calibration Study of Industrial Hygienists” Applied. Ind. Hygiene 4:61-68.

Hawkins, N.C. and J.D. Graham 1988 “Expert scientific judgment and cancer risk

assessment: a pilot study of pharmacokinetic data.”: Risk Analysis 8(4): 615-625.

Krewski et al., D., S.N. Ras, J.M. Zielmski, and P.K. Hopke 1999. “Characterization of

uncertainty and variability in residential radon cancer risks.” Ann. N.Y. Acad. Sci. 895:245-272.

Manne, A.S. and R.G. Richels, 1994. “The Costs of stabilizing global CO2 emissions: a

probabilistic analysis based on expert judgments.” The Energy Journal 15(1):31-56.

McCurdy, T and H. Richmond, 1983. Description of the OAQPS Risk Program and the

ongoing Lead NAAQS Risk Assessment Project. Paper 83-74.1. Presented at the 76th Annual

Meeting of the Air Pollution Control Association, June 19-24, Atlanta, Georgia. As cited in NAS.

Morgan, G. and M. Henrion, Uncertainty; A Guide to Dealing with Uncertainty in

Quantitative Risk and Policy Analysis, Cambridge University Press, Cambridge.

Morgan, M.G. and D.W Keith 1995. “Subjective judgments by climate experts.”

Environmental Science and Technology 29: 468A-476A.

Nordhaus, W.D. 1994. “ Expert Opinion on Climatic Change.” American Scientist. 82:45-51.

North, W. and M.W. Merkhofer 1976. “A methodology for analyzing emission control

strategies.” Comput. Oper. Res. 3:187-207.
Cost-Benefit Analysis

9-249

Reilly, J., P.H. Stone, C.E. Forest, M.D. Webster, H.E. Jacoby, and R.G. Prinn. 2001.

Climate Change. Uncertainty and climate change assessments. Science 293(5529):430-433.

U.S. Nuclear Regulatory Commission. 1996. “Branch Technical Position on the Use of

Expert Elicitation in the High-Level Radioactive Waste Program.” November, 1996.

Walker, K.D., P. Catalano, J.K. Hammitt, and J.S. Evans. 2003. “Use of expert judgment in

exposure assessment: Part 2. Calibration of expert judgments about personal exposures to benzene.”

J Expo Anal Environ Epidemiol. 13(1):1-16.

Walker, K.D., J.S. Evans, D. MacIntosh. 2001. “Use of expert judgment in exposure

assessment. Part 1. Characterization of personal exposure to benzene.”J Expo Anal Environ

Epidemiol. 11(4):308-22.

Whitfield and Wallsten 1989. “A risk assessment for selected lead-induced health effects:

an example of a general methodology.” Risk Analysis, 9(2):197-207.

Whitfield, R.G., T.S. Wallsten, R. L. Winkler, H.M. Richmond, and S.R. Hayes. 1991.

Assessing the Risks of Chronic Lung Injury Attributable to Long-Term Ozone Exposure. Argonne

National Laboratory Report ANL/EAIS-2. NTIS/DE91016814. Argonne, IL. July.

Winkler, R.L., T.S. Wallsten, R.G Whitfield, H.M. Richmond, S.R. Hayes, and A.S.

Rosenbaum. 1995. An assessment of the risk of chronic lung injury attributable to long-term ozone

exposure. Operations Research, Vol. 43 (1), pp. 19-28.

Wright, G. and P. Ayton (eds.) 1994. Subjective Probability. John Wiley, Chichester.
Final Regulatory Impact Analysis

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APPENDIX 9C: Sensitivity Analyses of Key Parameters in the Benefits Analysis

The primary analysis is based on our current interpretation of the scientific and

economic literature. That interpretation requires judgments regarding the best available data,

models, and modeling methodologies; and assumptions we consider most appropriate to adopt in

the face of important uncertainties. The majority of the analytical assumptions used to develop

the Base Estimate have been reviewed and approved by EPA's Science Advisory Board (SAB). 

However, we recognize that data and modeling limitations as well as simplifying assumptions

can introduce significant uncertainty into the benefit results and that alternative choices exist for

some inputs to the analysis, such as the mortality C-R functions. 

We supplement our primary estimates of benefits with a series of sensitivity

calculations that make use of other sources of health effect estimates and valuation data for key

benefits categories. These estimates examine sensitivity to both valuation issues (e.g. the

appropriate income elasticity) and for physical effects issues (e.g., possible recovery from chronic

illnesses). These estimates are not meant to be comprehensive. Rather, they reflect some of the

key issues identified by EPA or commentors as likely to have a significant impact on total

benefits. Individual adjustments in the tables should not be added together without addressing

potential issues of overlap and low joint probability among the endpoints. 

9C.1 Premature Mortality—Long term exposure

Given current evidence regarding their value, reduction in the risk of premature

mortality is the most important PM-related health outcome in terms of contribution to dollar

benefits. There are at least three important analytical assumptions that may significantly impact

the estimates of the number and valuation of avoided premature mortalities. These include

selection of the C-R function, structure of the lag between reduced exposure and reduced

mortality risk, and effect thresholds. Results of this set of sensitivity analyses are presented in

Table 9C.1.

9C.1.1 Alternative C-R Functions

Following the advice of the EPA Science Advisory Board Health Effects

Subcommittee (SAB-HES), we used the Pope, et al. (2002) all-cause mortality model exclusively

to derive our primary estimate of avoided premature mortality. While the SAB-HES

“recommends that the base case rely on the Pope et al. (2002) study and that EPA use total

mortality concentration-response functions (C-R), rather than separate cause-specific C-R

functions, to calculate total PM mortality cases,” they also suggested that “the cause-specific

estimates can be used to communicate the relative contribution of the main air pollution related

causes of death.” As such, we provide the estimates of cardiopulmonary and lung cancer deaths

based on the Pope et al. (2002).

In addition, the SAB-HES has noted that the American Cancer Society cohort used in

Pope et al. (2002) “has some inherent deficiencies, in particular the imprecise exposure data, and

the non-representative (albeit very large) population. Thus, ACS is not necessarily “the better
Cost-Benefit Analysis

9-251

study,” but, at this point in time, is a prudent choice for the base case estimates in the Second

Prospective Analysis. The Harvard Six-Cities C-R functions are valid estimates on a more

representative, although geographically selected, population, and its updated analysis has not yet

been published. The Six Cities estimates may be used in a sensitivity analysis to demonstrate that

with different but also plausible selection criteria for C-R functions, benefits may be considerably

larger than suggested by the ACS study.” (EPA-SAB-COUNCIL-ADV-04-002). In previous

advice, the SAB has noted that "the [Harvard Six Cities] study had better monitoring with less

measurement error than did most other studies" (EPA-SAB-COUNCIL-ADV-99-012, 1999). 

The demographics of the ACS study population, i.e., largely white and middle-class, may also

produce a downward bias in the estimated PM mortality coefficient, because short-term studies

indicate that the effects of PM tend to be significantly greater among groups of lower

socioeconomic status. The Harvard Six Cities study also covered a broader age category (25 and

older compared to 30 and older in the ACS study) and followed the cohort for a longer period (15

years compared to 8 years in the ACS study). We emphasize, that based on our understanding of

the relative merits of the two datasets, the Pope, et al. (2002) ACS model based on mean PM2.5

levels in 63 cities is the most appropriate model for analyzing the premature mortality impacts of

the nonroad standards. It is thus used for our base estimate of this important health effect. 

9C.1.2 Alternative Lag Structures

As noted by the SAB (EPA-SAB-COUNCIL-ADV-00-001, 1999), “some of the

mortality effects of cumulative exposures will occur over short periods of time in individuals

with compromised health status, but other effects are likely to occur among individuals who, at

baseline, have reasonably good health that will deteriorate because of continued exposure. No

animal models have yet been developed to quantify these cumulative effects, nor are there

epidemiologic studies bearing on this question.” However, they also note that “Although there is

substantial evidence that a portion of the mortality effect of PM is manifest within a short period

of time, i.e., less than one year, it can be argued that, if no lag assumption is made, the entire

mortality excess observed in the cohort studies will be analyzed as immediate effects, and this

will result in an overestimate of the health benefits of improved air quality. Thus some time lag is

appropriate for distributing the cumulative mortality effect of PM in the population.” In the

primary analysis, based on previous SAB advice, we assume that mortality occurs over a five

year period, with 25 percent of the deaths occurring in the first year, 25 percent in the second

year, and 16.7 percent in each of the third, fourth, and fifth years. Readers should note that the

selection of a 5 year lag is not supported by any scientific literature on PM-related mortality

(NRC 2002). Rather it is intended to be a reasonable guess at the appropriate distribution of

avoided incidences of PM-related mortality. The SAB-HES has recently noted that “empirical

evidence is lacking to inform the choice of the lag distribution directly and agrees with the NAS

report that there is little empirical justification for the 5-year cessation lag structure used in the

previous analyses.” The SAB-HES suggests that appropriate lag structures may be developed

based on the distribution of cause specific deaths within the overall all-cause estimate. Diseases

with longer progressions should be characterized by longer term lag structures, while air

pollution impacts occurring in populations with existing disease may be characterized by shorter

term lags. 
Final Regulatory Impact Analysis

CAlthough these studies were conducted for 8 and 15 years, respectively, the choice of the duration of the study

by the authors was not likely due to observations of a lag in effects, but is more likely due to the expense of

conducting long-term exposure studies or the amount of satisfactory data that could be collected during this time

period.

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A key question is the distribution of causes of death within the relatively broad

categories analyzed in the long-term cohort studies. While we may be more certain about the

appropriate length of cessation lag for lung cancer deaths, it is not at all clear what the

appropriate lag structure should be for cardiopulmonary deaths, which include both respiratory

and cardiovascular causes. Some respiratory diseases may have a long period of progression,

while others, such as pneumonia, have a very short duration. In the case of cardiovascular

disease, there is an important question of whether air pollution is causing the disease, which

would imply a relatively long cessation lag, or whether air pollution is causing premature death in

individuals with preexisting heart disease, which would imply very short cessation lags. The

SAB-HES provides several recommendations for future research that could support the

development of defensible lag structures, including the use of disease specific lag models, and the

construction of a segmented lag distribution to combine differential lags across causes of death. 

The SAB-HES indicated support for using “a Weibull distribution or a simpler distributional

form made up of several segments to cover the response mechanisms outlined above, given our

lack of knowledge on the specific form of the distributions.” However, they noted that “an

important question to be resolved is what the relative magnitudes of these segments should be,

and how many of the acute effects are assumed to be included in the cohort effect estimate.” 

They conclude their discussion of cessation lags by stating that “given the current lack of direct

data upon which to specify the lag function, the HES recommends that this question be

considered for inclusion in future expert elicitation efforts and/or sensitivity analyses.” (EPASAB-COUNCIL-ADV-04-002) EPA will continue to investigate this important issue for future

benefits analyses and in the upcoming 2nd Prospective Analysis of the Costs and Benefits of the

Clean Air Act. For this RIA, we investigate alternative cessation lag structures as senstivity

analyses, noting that these might be as likely as the previous 5-year distributed lag in the base

analysis. 

 Although the prior SAB recommended the five-year distributed lag be used for the

primary analysis, the SAB has also recommended that alternative lag structures be explored as a

sensitivity analysis (EPA-SAB-COUNCIL-ADV-00-001, 1999). Specifically, they recommended

an analysis of 0, 8, and 15 year lags. The 0 year lag is representative of EPA’s assumption in

previous RIAs. The 8 and 15 year lags are based on the study periods from the Pope, et al.

(1995) and Dockery, et al. (1993) studies, respectivelyc

. However, neither the Pope, et al. or

Dockery, et al. studies assumed any lag structure when estimating the relative risks from PM

exposure. In fact, the Pope, et al. and Dockery, et al. studies do not contain any data either

supporting or refuting the existence of a lag. Therefore, any lag structure applied to the avoided

incidences estimated from either of these studies will be an assumed structure. The 8 and 15 year

lags implicitly assume that all premature mortalities occur at the end of the study periods, i.e. at 8

and 15 years. 

In addition to the simple 8 and 15 year lags, we have added an additional senstivity

analysis examining the impact of assuming a segmented lag of the type suggested by the SAB-
Cost-Benefit Analysis

DThe most recent advice from the SAB-HES is characterized by the following: “For the studies of long-term

exposure, the HES notes that Krewski et al. (2000) have conducted the most careful work on this issue. They report

that the associations between PM2.5 and both all-cause and cardiopulmonary mortality were near linear within the

relevant ranges, with no apparent threshold. Graphical analyses of these studies (Dockery et al., 1993, Figure 3 and

Krewski et al., 2000, page 162) also suggest a continuum of effects down to lower levels. Therefore, it is reasonable

for EPA to assume a no threshold model down to, at least, the low end of the concentrations reported in the studies.”

E

The illustrative example in Appendix 9B presents the potential implications of assuming some probability of a

threshold on the benefits estimate.

9-253

HES. This illustrative lag structure is characterized by 20 percent of mortality reductions

occuring in the first year, 50 percent occuring evenly over years 2 to 5 after the reduction in

PM2.5, and 30 percent occurring evenly over the years 6 to 20 after the reduction in PM2.5. The

distribution of deaths over the latency period is intended to reflect the contribution of short term

exposures in the first year, cardiopulmonary deaths in the 2 to 5 year period, and longer term lung

disease and lung cancer in the 6 to 20 year period. For future analyses, the specific distribution

of deaths over time will need to be determined through research on causes of death and

progression of diseases associated with air pollution. It is important to keep in mind that changes

in the lag assumptions do not change the total number of estimated deaths, but rather the timing

of those deaths.

The estimated impacts of alternative lag structures on the monetary benefits associated

with reductions in PM-related premature mortality (estimated with the Pope et al. ACS impact

function) are presented in Table 9C.2. These estimates are based on the value of statistical lives

saved approach, i.e. $5.5 million per incidence, and are presented for both a 3 and 7 percent

discount rate over the lag period. 

9C.1.3 Thresholds

Although the consistent advice from EPA's Science Advisory Board has been to

model premature mortality associated with PM exposure as a non-threshold effect, that is, with

harmful effects to exposed populations regardless of the absolute level of ambient PM

concentrations, some analysts have hypothesized the presence of a threshold relationshipd

. The

nature of the hypothesized relationship is that there might exist a PM concentration level below

which further reductions no longer yield premature mortality reduction benefits.e

 EPA does not

necessarily endorse any particular threshold and, as discussed in Appendix 9A, virtually every

study to consider the issue indicates absence of a threshold. 

We construct a senstivity analysis by assigning different cutpoints below which

changes in PM2.5 are assumed to have no impact on premature mortality. The sensitivity analysis

illustrates how our estimates of the number of premature mortalities in the Base Estimate might

change under a range of alternative assumptions for a PM mortality threshold. If, for example,

there were no benefits of reducing PM concentrations below the PM2.5 standard of 15 :g/m3, our

estimate of the total number of avoided PM-related premature mortalities in 2030 from the

preliminary modeling would be reduced by approximately 70 percent, from approximately
Final Regulatory Impact Analysis

F

The pilot expert elicitation discussed in Appendix 9B provides some information on the impact of applying

nonlinear and threshold based C-R functions. 

9-254

14,000 annually to approximately 4,000 annually. However, this type of cutoff is unlikely, as

supported by the recent NRC report, which stated that “for pollutants such as PM10 and PM2.5,

there is no evidence for any departure of linearity in the observed range of exposure, nor any

indiciation of a threshold. (NRC, 2002)” Another possible senstivity analysis which we have not

conducted at this time might examine the potential for a nonlinear relationship at lower exposure

levels.f

One important assumption that we adopted for the threshold sensitivity analysis is that

no adjustments are made to the shape of the C-R function above the assumed threshold. Instead,

thresholds were applied by simply assuming that any changes in ambient concentrations below

the assumed threshold have no impacts on the incidence of premature mortality. If there were

actually a threshold, then the shape of the C-R function would likely change and there would be

no health benefits to reductions in PM below the threshold. However, as noted by the NRC, “the

assumption of a zero slope over a portion of the curve will force the slope in the remaining

segment of the positively sloped concentration-response function to be greater than was indicated

in the original study” and that “the generation of the steeper slope in the remaining portion of the

concentration-response function may fully offset the effect of assuming a threshold.” The NRC

suggested that the treatment of thresholds should be evaluated in a formal uncertainty analysis. 

The results of these sensitivity analyses demonstrate that choice of effect estimate can

have a large impact on benefits, potentially doubling benefits if the effect estimate is derived

from the HEI reanalysis of the Harvard Six-cities data (Krewski et al., 2000). Due to discounting

of delayed benefits, the lag structure may also have a large impact on monetized benefits,

reducing benefits by 30 percent if an extreme assumption that no effects occur until after 15 years

is applied. The overall impact of moving from the 5-year distributed lag to a segmented lag is

relatively modest, reducing benefits by approximately 8 percent when a three percent discount

rate is used and 22 percent when a seven percent discount rate is used. If no lag is assumed,

benefits are increased by around five percent. The threshold analysis indicates that

approximately 85 percent of the premature mortality related benefits are due to changes in PM2.5

concentrations occurring above 10 :g/m3, and around 30 percent are due to changes above 15

:g/m3

, the current PM2.5 standard.
Table 9C-1. 

Sensitivity of Benefits of Premature Mortality Reductions to Alternative

Assumptions (Relative to Base Case Benefits of Modeled Preliminary Control Option)

Description of Sensitivity

Analysis

Avoided

IncidencesA

Value (million

2000$)B

20

20

20

30

20

20

20

30

Alternative Concentration-Response Functions for PM-related Premature Mortality

Pope/ACS Study (2002)C

Lung Cancer 1,

200

 

2,100

$7

,700

$1

3,000

Cardiopulmonary 6,

000

11

,000

$3

7,000

$6

7,000

Krewski/Harvard Six-city Study 17

,000

30

,000

$1

10,000

$1

90,000

Alternative Lag Structures for PM-related Premature Mortality 

N

one

Incidences all occur in

the first year

7,

800

14

,000

$5

2,000

$9

4,000

8-

year

Incidences all occur in

the 8th year

 

3% Discount Rate 7,

800 

14

,000

$4

2,000

$7

6,000

7% Discount Rate 7,

800

14

,000

$3

2,000

$6

2,000

1

5-year

Incidences all occur in

the 15th year

 

3% Discount Rate 7,

800

14

,000

$3

4,000

$6

2,000

7% Discount Rate 7,

800

14

,000

$2

0,000

$3

6,000

S

egmented

20 percent of

incidences occur in 1st year,

50 percent in years 2 to 5, and

30 percent in years 6 to 20

3% Discount Rate 7,

800

14

,000

$4

5,000

$8

2,000

7% Discount Rate 7, 14 $3 $6
Final Regulatory Impact Analysis

9-256

Alternative Thresholds

No Threshold (base estimate) 7,

800

14

,000

$4

9,000

$8

9,000

5 7,

800

14

,000

$4

9,000

$8

9,000

10 6,

300

12

,000

$4

0,000

$7

7,000

15 1,

700

4,

000

$1

1,000

$2

6,000

20 63

0

1,

300

$4

,000

$8,

400

25 19

0

52

0

$1

,200

$3,

400 A Incidences rounded to two significant digits.

B

 Dollar values rounded to two significant digits.

C

 Note that the sum of lung cancer and cardiopulmonary deaths will not be equal to the total all cause death

estimate. There is some residual mortality associated with long term exposures to PM2.5 that is not captured by the

caridopulmonary and lung cancer categories. 

9C.2 Other Health Endpoint Sensitivity Analyses

9C.2.1 Overlapping Endpoints

In Appendix 9A, we estimated the benefits of the modeled preliminary control options

using the most comprehensive set of endpoints available. For some health endpoints, this meant

using a health impact function that linked a larger set of effects to a change in pollution, rather

than using health impact functions for individual effects. For example, for premature mortality,

we selected an impact function that captured reductions in incidences due to long-term exposures

to ambient concentrations of particulate matter, assuming that most incidences of mortality

associated with short-term exposures would be captured. In addition, the long-term exposure

premature mortality impact function for PM2.5 is expected to capture at least some of the

mortality effects associated with exposure to ozone.

In order to provide the reader with a fuller understanding of the health effects

associated with reductions in air pollution associated with the preliminary control options, this

set of sensitivity estimates examines those health effects which, if included in the primary

estimate, could result in double-counting of benefits. For some endpoints, such as ozone

mortality, additional research is needed to provide separate estimates of the effects for different

pollutants, i.e. PM and ozone. These supplemental estimates should not be considered as additive

to the total estimate of benefits, but illustrative of these issues and uncertainties. Sensitivity

estimates included in this appendix include premature mortality associated with short-term

exposures to ozone, and acute respiratory symptoms in adults. Results of this set of sensitivity
Cost-Benefit Analysis

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analyses are presented in Table 9.C-3.

There has been a great deal of research recently on the potential effect of ozone on

premature mortality. While the air pollutant most clearly associated with premature mortality is

particulate matter, with dozens of studies reporting such an association, repeated ozone exposure

is a likely contributing factor for premature mortality, causing an inflammatory response in the

lungs which may predispose elderly and other sensitive individuals to become more susceptible. 

The findings of three recent analyses provide consistent data suggesting that ozone exposure is

associated with increased mortality. Although the National Morbidity, Mortality, and Air

Pollution Study (NMMAPS) did not find an effect of ozone on total mortality across the full

year, Samet et al. (2000), who conducted the NMMAPS study, did observe an effect after

limiting the analysis to summer when ozone levels are highest. Similarly, Thurston and Ito

(1999) have shown associations between ozone and mortality. Toulomi et al. (1997) found that

1-hour maximum ozone levels were associated with daily numbers of deaths in 4 cities (London,

Athens, Barcelona, and Paris), and a quantitatively similar effect was found in a group of 4

additional cities (Amsterdam, Basel, Geneva, and Zurich). Fairly et al. (2003) also found a

relatively strong association between maximum 8-hour average ozone concentrations and

mortality in Santa Clara County, CA, even after controlling for PM2.5 exposure. 

While not as extensive as the data base for particulate matter, these recent studies

provide supporting evidence for inclusion of mortality in the ozone health benefits analysis. A

recent analysis by Thurston and Ito (2001) reviewed previously published time series studies of

the effect of daily ozone levels on daily mortality and found that previous EPA estimates of the

short-term mortality benefits of the ozone NAAQS (U.S. EPA, 1997) may have been

underestimated by up to a factor of two. Thurston and Ito hypothesized that much of the

variability in published estimates of the ozone/mortality effect could be explained by how well

each model controlled for the influence of weather, an important confounder of the

ozone/mortality effect, and that earlier studies using less sophisticated approaches to controlling

for weather consistently under-predicted the ozone/mortality effect. 

Thurston and Ito (2001) found that models incorporating a non-linear temperature

specification appropriate for the "U-shaped" nature of the temperature/mortality relationship

(i.e., increased deaths at both very low and very high temperatures) produced ozone/mortality

effect estimates that were both more strongly positive (a two percent increase in relative risk

over the pooled estimate for all studies evaluated) and consistently statistically significant. 

Further accounting for the interaction effects between temperature and relative humidity

produced even more strongly positive results. Inclusion of a PM index to control for

PM/mortality effects had little effect on these results, suggesting an ozone/mortality relationship

independent of that for PM. However, most of the studies examined by Thurston and Ito only

controlled for PM10 or broader measures of particles and did not directly control for PM2.5. As

such, there may still be potential for confounding of PM2.5 and ozone mortality effects, as ozone

and PM2.5 are highly correlated during summer months in some areas. 

A recent World Health Organization (WHO) report found that "recent

epidemiological studies have strengthened the evidence that there are short-term O3 effects on
Final Regulatory Impact Analysis

9-258

mortality and respiratory morbidity and provided further information on exposure-response

relationships and effect modification." (WHO, 2003). Based on a preliminary meta-analysis, the

WHO report suggests an effect estimate of between 0.2 and 0.4 percent increase in premature

death per 10 :g/m3 increase in 1 hour maximum ozone and between 0.4 and 0.6 percent increase

in premature death per 10 :g/m3

 increase in daily average. This is equivalent to a relative risk of

between 1.04 and 1.08 per 100 ppb increase in 1 hour maximum and between 1.08 and 1.12 per

100 ppb increase in daily average. The WHO report provides effect estimates for both all

seasons and summer seasons. Because our analysis is limited to the summer ozone season, the

most appropriate effect estimate is for the summer season. The WHO summer season relative

risk estimate is 1.08 per 100 ppb increase in 1 hour maximum ozone and 1.12 per 100 ppb

increase in daily average ozone.

Levy et al. (2001) assessed the epidemiological evidence examining the link between

short term exposures to ozone and premature mortality. Based on four U.S. studies (Kellsall et

al., 1997; Moolgavkar et al., 1995; Ito and Thurston, 1996; and Moolgavkar, 2000), they

conclude that an appropriate pooled effect estimate is a 0.5 percent increase in premature deaths

per 10 :g/m3

 increase in 24-hour average ozone concentrations, with a 95 percent confidence

interval between 0.3 percent and 0.7 percent. This is equivalent to a relative risk of 1.10 per 100

ppb increase in daily average, which falls in the middle of the range of relative risks from the

WHO report. Levy et al. also note that there are a number of studies which did not report a

quantitative effect estimate but did indicate that ozone was insignificant. They suggest that the

uncertainty surrounding the ozone-mortality effect estimate is greater than that reflected in the

confidence interval around their pooled estimate.

In its September 2001 advisory on the draft analytical blueprint for the second

Section 812 prospective analysis, the SAB Health Effects Subcommittee (HES) cited the

Thurston and Ito study as a significant advance in understanding the effects of ozone on daily

mortality and recommended re-evaluation of the ozone mortality endpoint for inclusion in the

next prospective study (EPA-SAB-COUNCIL-ADV-01-004, 2001). Based on these new

analyses and recommendations, EPA is sponsoring three independent meta-analyses of the

ozone-mortality epidemiology literature to inform a determination on inclusion of this important

health endpoint. Publication of these meta-analyses will significantly enhance the scientific

defensibility of benefits estimates for ozone which include the benefits of premature mortality

reductions. In its 2003 review of the analysis plans for the second Prospective Analysis, the

HES indicated support for EPAs new meta-analyses of the ozone mortality literature and EPA’s

plans to consider adding ozone mortality to the base case analysis, subsequent to review of the

results of the meta-analyses. Thus, recent evidence suggests that by not including an estimate of

reductions in short-term mortality due to changes in ambient ozone, the Base Estimate may

underestimate the benefits of implementation of the Nonroad Diesel Engine rule. 

The ozone mortality sensitivity estimate is calculated using results from four U.S.

studies (Ito and Thurston, 1996; Kinney et al., 1995; Moolgavkar et al., 1995; and Samet et al.,

1997), based on the assumption that demographic and environmental conditions on average

would be more similar between these studies and the conditions prevailing when the nonroad

standards are implemented. We include the Kinney et al., 1995 estimate for completeness, even
Cost-Benefit Analysis

9-259

though Levy et al. (2001) reject the results because the study only included a linear term for

temperature. Because the Kinney et al. (1995) study found no significant effect of ozone, this

has the effect of reducing the estimated mortality impacts and increasing the uncertainty

surrounding the estimated mortality reductions. We combined these studies using probabilistic

sampling methods to estimate the impact of ozone on mortality incidence. The technical support

document for this analysis provides additional details of this approach (Abt Associates, 2003). 

The estimated incidences of short-term premature mortality are valued using the value of

statistical lives saved method, as described in Appendix 9A.

Table 9C-2. 

Sensitivity Estimates for Potentially Overlapping EndpointsA

Description of Sensitivity

Analysis

Avoided

Incidences

Monetized

Value

(Million

2000$)

20

20

20

30

20

20

20

30

Mortality from Short-term Ozone ExposureB

Ito and Thurston (1996) 44

0

1,

000

$2

,900

$6,

800

Kinney et al. (1995) 0 0 $0 $0

Moolgavkar et al. (1995) 77 24

0

$5

10

$1,

600

Samet et al. (1997) 12

0

36

0

$7

90

$2,

400

Pooled estimate (random effects

weights)

94 28

0

$6

20

$1,

900

Any of 19 Acute Respiratory Symptoms, Adults 18-64 (Krupnick et al. 1990)

Ozone 1,

500,000

2,

800,000

$3

8

$7

1

PM 14

,000,000

19

,000,000

$3

40

$4

90

A All estimates rounded to two significant digits.

B

 Mortality valued using Base estimate of $5.5 million per premature statistical death,

adjusted for income growth.
Final Regulatory Impact Analysis

9-260

9C.2.2 Alternative and Supplementary Estimates

We also examine how the value for individual endpoints or total benefits would

change if we were to make a different assumption about specific elements of the benefits

analysis. Specifically, in Table 9C.3, we show the impact of alternative assumptions about other

parameters, including treatment of reversals in chronic bronchitis as lowest severity cases,

alternative impact functions for PM hospital and ER admissions, valuation of residential

visibility, valuation of recreational visibility at Class I areas outside of the study regions

examined in the Chestnut and Rowe (1990a, 1990b) study, and valuation of household soiling

damages.
Cost-Benefit Analysis

9-261

Table 9C-3. 

Additional Parameter Sensitivity Analyses

Alternative

Calculation

Description of Estimate

Impact on Base Benefit

Estimate (million 2000$)

2020 2030

1

Reversal

s in chronic

bronchitis

treated as

lowest severity

cases

Instead of omitting cases of

chronic bronchitis that reverse after

a period of time, they are treated as

being cases with the lowest severity

rating. The number of avoided

chronic bronchitis incidences in

2020 increases from 4,300 to 8,000

(87%). The increase in 2030 is

from 6,500 to 12,000 (87%).

+$730

(+1.4%)

+$1,10

0 (+1.2%)

2

Value of

visibility

changes in all

Class I areas

Values of visibility changes

at Class I areas in California, the

Southwest, and the Southeast are

transferred to visibility changes in

Class I areas in other regions of the

country.

+$640

(+1.2%)

+$970

(+1.1%)

3

Value of

visibility

changes in

Eastern U.S.

residential areas

Value of visibility changes

outside of Class I areas are

estimated for the Eastern U.S.

based on the reported values for

Chicago and Atlanta from

McClelland et al. (1990).

+$700

(+1.3%)

+$1,10

0 (+1.1%)

4

Value of

visibility

changes in

Western U.S.

residential areas

Value of visibility changes

outside of Class I areas are

estimated for the Western U.S.

based on the reported values for

Chicago and Atlanta from

McClelland et al. (1990).

+$530

(+1.0%)

+$830

(+0.9%)

5

Househ

old soiling

damage

Value of decreases in

expenditures on cleaning are

estimated using values derived

from Manuel, et al. (1983).

+$170

(+0.3%)

+$260

(+0.3%)
Final Regulatory Impact Analysis

9-262

An important issue related to chronic conditions is the possible reversal in chronic

bronchitis incidences (row 1 of Table 9C-3). Reversals are defined as those cases where an

individual reported having chronic bronchitis at the beginning of the study period but reported

not having chronic bronchitis in follow-up interviews at a later point in the study period. Since,

by definition, chronic diseases are long-lasting or permanent, if the disease goes away it is not

chronic. However, we have not captured the benefits of reducing incidences of bronchitis that

are somewhere in-between acute and chronic. One way to address this is to treat reversals as

cases of chronic bronchitis that are at the lowest severity level. These cases thus get the lowest

value for chronic bronchitis.

The alternative calculation for recreational visibility (row 2 of Table 9C-3) is an

estimate of the full value of visibility in the entire region affected by the nonroad emission

reductions. The Chestnut and Rowe study from which the primary valuation estimates are

derived only examined WTP for visibility changes in the southeastern portion of the affected

region. In order to obtain estimates of WTP for visibility changes in the northeastern and central

portion of the affected region, we have to transfer the southeastern WTP values. This introduces

additional uncertainty into the estimates. However, we have taken steps to adjust the WTP

values to account for the possibility that a visibility improvement in parks in one region, is not

necessarily the same environmental quality good as the same visibility improvement at parks in a

different region. This may be due to differences in the scenic vistas at different parks,

uniqueness of the parks, or other factors, such as public familiarity with the park resource. To

take this potential difference into account, we adjusted the WTP being transferred by the ratio of

visitor days in the two regions.

The alternative calculations for residential visibility (rows 3 and 4 of Table 9C-3) are

based on the McClelland, et al. study of WTP for visibility changes in Chicago and Atlanta. As

discussed in Appendix 9A, SAB advised EPA that the residential visibility estimates from the

available literature are inadequate for use in a primary estimate in a benefit-cost analysis. 

However, EPA recognizes that residential visibility is likely to have some value and the

McClelland, et al. estimates are the most useful in providing an estimate of the likely magnitude

of the benefits of residential visibility improvements.

The alternative calculation for household soiling (row 5 of Table 9C-3) is based on

the Manuel, et al. study of consumer expenditures on cleaning and household maintenance. This

study has been cited as being “the only study that measures welfare benefits in a manner

consistent with economic principals (Desvouges et al., 1998).” However, the data used to

estimate household soiling damages in the Manuel, et al. study are from a 1972 consumer

expenditure survey and as such may not accurately represent consumer preferences in 2030. 

EPA recognizes this limitation, but believes the Manuel, et al. estimates are still useful in

providing an estimate of the likely magnitude of the benefits of reduced PM household soiling.

9C.3 Income Elasticity of Willingness to Pay

As discussed in Appendix 9A, our estimate of monetized benefits accounts for growth

in real GDP per capita by adjusting the WTP for individual endpoints based on the central
Cost-Benefit Analysis

9-263

estimate of the adjustment factor for each of the categories (minor health effects, severe and

chronic health effects, premature mortality, and visibility). We examine how sensitive the

estimate of total benefits is to alternative estimates of the income elasticities. Table 9C-4 lists

the ranges elasticity values used to calculate the income adjustement factors, while Table 9C-5

lists the ranges of corresponding adjustement factors. The results of this sensitivity analysis,

giving the monetized benefit subtotals for the four benefit categories, are presented in Table 9C6.

Consistent with the impact of mortality on total benefits, the adjustment factor for

mortality has the largest impact on total benefits. The value of mortality ranges from 81 percent

to 150 percent of the primary estimate based on the lower and upper sensitivity bounds on the

income adjustment factor. The effect on the value of minor and chronic health effects is much

less pronounced, ranging from 93 percent to 111 percent of the primary estimate for minor

effects and from 88 percent to 110 percent for chronic effects.
Final Regulatory Impact Analysis

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Table 9C-4. 

Ranges of Elasticity Values Used to Account for Projected Real Income GrowthA

Benefit Category Lower Sensitivity

Bound

Upper Sensitivity

Bound

Minor Health Effect 0.04 0.30

Severe and Chronic

Health Effects 0.25 0.60

Premature Mortality 0.08 1.00

VisibilityB -- -- A Derivation of these ranges can be found in Kleckner and Neumann (1999) and Chestnut (1997). Cost of Illness

(COI) estimates are assigned an adjustment factor of 1.0. B No range was applied for visibility because no ranges were available in the current published literature.

Table 9C-5. 

Ranges of Adjustment Factors Used to Account for Projected Real Income GrowthA

Benefit

Category

Lower Sensitivity Bound Upper Sensitivity Bound

2020 2030 2020 2030

Minor Health

Effect 1.018 1.021 1.147 1.170

Severe and

Chronic Health

Effects

1.121 1.139 1.317 1.371

Premature

Mortality 1.037 1.043 1.591 1.705

VisibilityB -- -- -- -- A Based on elasticity values reported in Table 9A-11, US Census population projections, and projections of real gross

domestic product per capita. B No range was applied for visibility because no ranges were available in the current published literature.
Cost-Benefit Analysis

9-265

Table 9C-6. 

Sensitivity Analysis of Alternative Income ElasticitiesA

Benefit Category Lower Sensitivity

Bound

Upper Sensitivity

Bound

2020 2030 2020 2030

Minor Health Effect $510 $760 $540 $810

Severe and Chronic

Health Effects

$2,50

0

$3,90

0

$2,80

0

$4,40

0

Premature Mortality $42,0

00

$75,0

00

$65,0

00

$123,

000

Visibility and Other

Welfare EffectsA

$1,40

0

$2,20

0

$1,40

0

$2,20

0

Total Benefits $47,0

00

$82,0

00

$70,0

00

$131,

000

A All estimates rounded to two significant digits.

B No range was applied for visibility because no ranges were available in the current published literature.
Final Regulatory Impact Analysis

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Appendix 9C References

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Quality Estimation, Selected Healthand Welfare Benefits Methods, and Benefit

Analysis Results. Prepared for Office of Air Quality Planning and Standards, U.S.

EPA. April, 2003.

Alberini, A., M. Cropper, A. Krupnick, and N.B. Simon. 2002. Does the Value of a

Statistical Life Vary with Age and Health Status? Evidence from the United States

and Canada. Resources for the Future Discussion Paper 02-19. April.

Blumenschein, K. and M. Johannesson. 1998. “Relationship Between Quality of Life

Instruments, Health State Utilities, and Willingness to Pay in Patients with Asthma.”

Annals of Allergy, Asthma, and Immunology 80:189-194.

Chestnut, L.G. 1997. Draft Memorandum: Methodology for Estimating Values for

Changes in Visibility at National Parks. April 15.

Chestnut, L.G. and R.D. Rowe. 1990a. Preservation Values for Visibility Protection at

the National Parks: Draft Final Report. Prepared for Office of Air Quality Planning

and Standards, US Environmental Protection Agency, Research Triangle Park, NC

and Air Quality Management Division, National Park Service, Denver, CO.

Chestnut, L.G., and R.D. Rowe. 1990b. A New National Park Visibility Value Estimates.

In Visibility and Fine Particles, Transactions of an AWMA/EPA International

Specialty Conference, C.V. Mathai, ed. Air and Waste Management Association,

Pittsburgh.

Desvousges, W.H., F. R. Johnson, H.S. Banzhaf. 1998. Environmental Policy Analysis

With Limited Information: Principles and Applications of the Transfer Method (New

Horizons in Environmental Economics.) Edward Elgar Pub: London. 

Dockery, D.W., C.A. Pope, X.P. Xu, J.D. Spengler, J.H. Ware, M.E. Fay, B.G. Ferris and

F.E. Speizer. 1993. “An association between air pollution and mortality in six U.S.

cities.” New England Journal of Medicine. 329(24): 1753-1759.

EPA-SAB-COUNCIL-ADV-00-001, 1999. The Clean Air Act Amendments (CAAA)

Section 812 Prospective Study of Costs and Benefits (1999): Advisory by the Health

and Ecological Effects Subcommittee on Initial Assessments of Health and

Ecological Effects; Part 2. October.

EPA-SAB-COUNCIL-ADV-99-012, 1999. The Clean Air Act Amendments (CAAA)

Section 812 Prospective Study of Costs and Benefits (1999): Advisory by the Health

and Ecological Effects Subcommittee on Initial Assessments of Health and

Ecological Effects; Part 1. July.

EPA-SAB-COUNCIL-ADV-01-004. 2001. Review of the Draft Analytical Plan for

EPA's Second Prospective Analysis - Benefits and Costs of the Clean Air Act

1990-2020: An Advisory by a Special Panel of the Advisory Council on Clean Air

Compliance Analysis. September. 

Ito, K. and G.D. Thurston. 1996. “Daily PM10/mortality associations: an investigations

of at-risk subpopulations.” Journal of Exposure Analysis and Environmental

Epidemiology 6(1): 79-95.

Jones-Lee, M.W. 1989. The Economics of Safety and Physical Risk. Oxford: Basil

Blackwell.
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Jones-Lee, M.W., G. Loomes, D. O’Reilly, and P.R. Phillips. 1993. The Value of

Preventing Non-fatal Road Injuries: Findings of a Willingness-to-pay National

Sample Survey. TRY Working Paper, WP SRC2.

Kinney, P.L., K. Ito and G.D. Thurston. 1995. A Sensitivity Analysis of Mortality Pm10 Associations in Los Angeles. Inhalation Toxicology 7(1): 59-69.

Kleckner, N. and J. Neumann. 1999. Recommended Approach to Adjusting WTP

Estimates to Reflect Changes in Real Income. Memorandum to Jim Democker, US

EPA/OPAR, June 3.

Krewski D, Burnett RT, Goldbert MS, Hoover K, Siemiatycki J, Jerrett M,

Abrahamowicz M, White WH. 2000. Reanalysis of the Harvard Six Cities Study and

the American Cancer Society Study of Particulate Air Pollution and Mortality. 

Special Report to the Health Effects Institute, Cambrid.ge MA, July 2000.

Krupnick, A., M. Cropper., A. Alberini, N. Simon, B. O'Brien, R. Goeree, and M.

Heintzelman. 2002. Age, Health and the Willingness to Pay for Mortality Risk

Reductions: A Contingent Valuation Study of Ontario Residents, Journal of Risk and

Uncertainty, 24, 161-186.

Manuel, E.H., R.L. Horst, K.M. Brennan, W.N. Lanen, M.C. Duff and J.K. Tapiero. 

1982. Benefits Analysis of Alternative Secondary National Ambient Air Quality

Standards for Sulfur Dioxide and Total Suspended Particulates, Volumes I-IV. 

Prepared for U.S. Environmental Protection Agency, Office of Air Quality Planning

and Standards. Research Triangle Park, NC. 

McClelland, G., W. Schulze, D. Waldman, J. Irwin, D. Schenk, T. Stewart, L. Deck and

M. Thayer. 1991. Valuing Eastern Visibility: A Field Test of the Contingent

Valuation Method. Prepared for U.S. Environmental Protection Agency, Office of

Policy, Planning and Evaluation. June.

McDonnell, W.F., D.E. Abbey, N. Nishino and M.D. Lebowitz. 1999. Long-term

ambient ozone concentration and the incidence of asthma in nonsmoking adults: the

ahsmog study. Environmental Research. 80(2 Pt 1): 110-21.

Moolgavkar, S.H., E.G. Luebeck, T.A. Hall and E.L. Anderson. 1995. Air Pollution and

Daily Mortality in Philadelphia. Epidemiology 6(5): 476-484.

National Research Council (NRC). 2002. Estimating the Public Health Benefits of

Proposed Air Pollution Regulations. The National Academies Press: Washington,

D.C.

O'Connor, R.M. and G.C. Blomquist. 1997. Measurement of Consumer-Patient

Preferences Using a Hybrid Contingent Valuation Method. Journal of Health

Economics. Vol. 16: 667-683.

Ostro, B.D., M.J. Lipsett, M.B. Wiener and J.C. Selner. 1991. Asthmatic Responses to

Airborne Acid Aerosols. American Journal of Public Health 81(6): 694-702.

Pope, C.A., M.J. Thun, M.M. Namboodiri, D.W. Dockery, J.S. Evans, F.E. Speizer and

C.W. Heath. 1995. Particulate air pollution as a predictor of mortality in a

prospective study of U.S. adults. American Journal of Respiratory Critical Care

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Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, G.D. Thurston.

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Particulate Air Pollution. Journal of the American Medical Association. 287: 1132-
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1141. 

Samet, J.M., S.L. Zeger, J.E. Kelsall, J. Xu and L.S. Kalkstein. 1997. Air Pollution,

Weather, and Mortality in Philadelphia 1973-1988. Health Effects Institute. 

Cambridge, MA. March.

Scultze. W. 2003. Personal Communication. January.

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mortality. J Expo Anal Environ Epidemiol. Vol. 11(4): 286-94.

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July.

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White Paper for Review by the EPA Science Advisory Board.

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States. Environmental Health Perspectives. 105(6): 608-612.
APPENDIX 9D: Visibility Benefits Estimates for Individual Class I

Areas

Table 9D-1

Apportionment Factors for 2020 Park Specific Visibility Benefits

PARK COUNTY STAT

E

Percent of 2020 Visibility Benefit Due to

Changes in:

SO2 NOx direct PM

Shenandoah Lawrence AL 0.428 0.234 0.338

Anaconda-Pintlar W Cochise Co AZ 0.337 0.061 0.602

Boundary Waters Gila Co AZ 0.396 0.054 0.550

Breton W Gila Co AZ 0.396 0.054 0.550

Isle Royale Coconino AZ 0.336 0.053 0.612

Jarbidge W Apache Co AZ 0.469 0.049 0.481

Medicine Lake W Apache Co AZ 0.469 0.049 0.481

Red Rock Lakes W Graham Co AZ 0.302 0.038 0.660

Roosevelt Campobello Pima Co AZ 0.224 0.061 0.715

Selway-Bitterroot W Maricopa AZ 0.061 0.014 0.924

Seney W Coconino AZ 0.336 0.053 0.612

Wolf Island W Yavapai Co AZ 0.216 0.140 0.644

Agua Tibia W Tuolumne CA 0.090 0.580 0.330

Black Canyon of the San CA 0.074 0.158 0.768

Caribou W Calaveras CA 0.049 0.520 0.432

Chiricahua Trinity Co CA 0.367 0.239 0.394

Cucamonga W Fresno Co CA 0.051 0.101 0.848

Dome Land W Mono Co CA 0.195 0.302 0.504

Flat Tops W Inyo Co CA 0.145 0.098 0.757

Grand Canyon Marin Co CA 0.060 0.577 0.363

Hoover W Los CA 0.099 0.143 0.758

John Muir W Monterey CA 0.071 0.563 0.366

Kaiser W San Benito CA 0.057 0.633 0.310

La Garita W Riverside CA 0.040 0.314 0.646

Mazatzal W Siskiyou CA 0.469 0.220 0.311

Mesa Verde San CA 0.074 0.158 0.768

Petrified Forest Del Norte CA 0.518 0.097 0.385

Pine Mountain W Shasta Co CA 0.146 0.469 0.385

Pinnacles Fresno Co CA 0.051 0.101 0.848

Point Reyes Lassen Co CA 0.285 0.347 0.368

Rawah W Riverside CA 0.040 0.314 0.646

Rocky Mountain San Diego CA 0.068 0.497 0.435

Saguaro Shasta Co CA 0.146 0.469 0.385

San Gabriel W El Dorado CA 0.050 0.487 0.463

San Gorgino W Mariposa CA 0.085 0.374 0.541

San Jacinto W Fresno Co CA 0.051 0.101 0.848

San Rafael W Tuolumne CA 0.090 0.580 0.330

Sequoia-Kings Tulare Co CA 0.052 0.478 0.470

Sycamore Canyon W Siskiyou CA 0.469 0.220 0.311

Ventana W Santa CA 0.111 0.156 0.733

Yolla-Bolly-Middle- Tulare Co CA 0.052 0.478 0.470
PARK COUNTY STAT

E

Percent of 2020 Visibility Benefit Due to

Changes in:

SO2 NOx direct PM

Yosemite Modoc Co CA 0.277 0.407 0.316

Carlsbad Caverns San Juan CO 0.522 0.114 0.364

Gila W Garfield Co CO 0.335 0.246 0.420

Joyce Kilmer-Slickrock Routt Co CO 0.420 0.140 0.440

Kalmiopsis W Larimer Co CO 0.449 0.120 0.431

Linville Gorge W Pitkin Co CO 0.425 0.098 0.477

Lostwood W Alamosa CO 0.458 0.097 0.445

Pecos W Gunnison CO 0.437 0.152 0.411

Presidential Range-Dry Montezuma CO 0.353 0.077 0.570

Salt Creek W Montrose CO 0.355 0.175 0.470

Shining Rock W Summit Co CO 0.525 0.042 0.433

Wheeler Peak W Mineral Co CO 0.589 0.048 0.364

Wichita Mountains W Larimer Co CO 0.449 0.120 0.431

Fitzpatrick W Monroe Co FL 0.546 0.020 0.434

Glacier Peak W Wakulla Co FL 0.535 0.048 0.417

Mount Adams W Citrus Co FL 0.416 0.148 0.436

Dolly Sods W Charlton GA 0.543 0.058 0.399

North Absaroka W McIntosh GA 0.500 0.052 0.448

Olympic Edmonson KY 0.415 0.246 0.338

Lye Brook W Stone Co MS 0.539 0.112 0.349

Bridger W Hyde Co NC 0.344 0.327 0.329

Goat Rocks W Haywood NC 0.476 0.191 0.333

Otter Creek W Avery Co NC 0.516 0.184 0.300

Pasayten W Graham Co NC 0.564 0.138 0.298

Bandelier Sandoval NM 0.426 0.034 0.540

Bosque del Apache W Rio Arriba NM 0.512 0.047 0.441

Brigantine W Grant Co NM 0.414 0.017 0.569

Crater Lake Chaves Co NM 0.471 0.094 0.434

Mount Hood W Mora Co NM 0.568 0.081 0.352

Mount Washington W Eddy Co NM 0.417 0.052 0.531

San Pedro Parks W Socorro Co NM 0.409 0.025 0.565

Swanguarter W Taos Co NM 0.538 0.057 0.405

Theodore Roosevelt Lincoln Co NM 0.603 0.056 0.341

Maroon Bells- Elko Co NV 0.311 0.301 0.388

Mount Rainier Polk Co TN 0.405 0.237 0.358

North Cascades Blount Co TN 0.384 0.184 0.432

Bob Marshall W San Juan UT 0.373 0.048 0.579

Gates of the Mountain Grand Co UT 0.354 0.038 0.608

Glacier San Juan UT 0.373 0.048 0.579

St. Marks W Washington UT 0.219 0.096 0.685

Voyageurs Garfield Co UT 0.295 0.052 0.652

Teton W Botetourt VA 0.485 0.151 0.364

Yellowstone Madison VA 0.385 0.316 0.300

Grand Teton NP Grant Co WV 0.533 0.190 0.278

Washakie W Tucker Co WV 0.568 0.118 0.314
Table 9D-2

 Apportionment Factors for 2030 Park Specific Visibility Benefits

PARK COUNTY STATE

Percent of 2030 Visibility Benefit Due to

Changes in:

SO2 NOx direct PM

Shenandoah Lawrence AL 0.376 0.297 0.327

Anaconda-Pintlar W Cochise AZ 0.313 0.075 0.612

Boundary Waters Gila Co AZ 0.277 0.048 0.675

Breton W Gila Co AZ 0.293 0.089 0.619

Isle Royale Coconino AZ 0.342 0.107 0.551

Jarbidge W Apache AZ 0.429 0.069 0.503

Medicine Lake W Apache AZ 0.429 0.069 0.503

Red Rock Lakes W Graham AZ 0.188 0.173 0.639

Roosevelt Campobello Pima Co AZ 0.207 0.072 0.721

Selway-Bitterroot W Maricopa AZ 0.342 0.107 0.551

Seney W Coconino AZ 0.057 0.019 0.924

Wolf Island W Yavapai AZ 0.293 0.089 0.619

Agua Tibia W Tuolumne CA 0.055 0.571 0.375

Black Canyon of the San CA 0.226 0.407 0.368

Caribou W Calaveras CA 0.065 0.191 0.745

Chiricahua Trinity Co CA 0.129 0.111 0.759

Cucamonga W Fresno Co CA 0.039 0.520 0.441

Dome Land W Mono Co CA 0.046 0.493 0.461

Flat Tops W Inyo Co CA 0.070 0.616 0.314

Grand Canyon Marin Co CA 0.070 0.616 0.314

Hoover W Los CA 0.049 0.109 0.842

John Muir W Monterey CA 0.033 0.376 0.591

Kaiser W San Benito CA 0.049 0.109 0.842

La Garita W Riverside CA 0.049 0.109 0.842

Mazatzal W Siskiyou CA 0.116 0.518 0.366

Mesa Verde San CA 0.411 0.270 0.320

Petrified Forest Del Norte CA 0.411 0.270 0.320

Pine Mountain W Shasta Co CA 0.158 0.344 0.498

Pinnacles Fresno Co CA 0.043 0.535 0.422

Point Reyes Lassen Co CA 0.047 0.663 0.289

Rawah W Riverside CA 0.053 0.588 0.360

Rocky Mountain San Diego CA 0.468 0.133 0.399

Saguaro Shasta Co CA 0.090 0.175 0.735

San Gabriel W El Dorado CA 0.065 0.191 0.745

San Gorgino W Mariposa CA 0.033 0.376 0.591

San Jacinto W Fresno Co CA 0.099 0.179 0.722

San Rafael W Tuolumne CA 0.046 0.493 0.461

Sequoia-Kings Tulare Co CA 0.225 0.452 0.323

Sycamore Canyon W Siskiyou CA 0.116 0.518 0.366

Ventana W Santa CA 0.059 0.593 0.348

Yolla-Bolly-Middle- Tulare Co CA 0.321 0.292 0.386

Yosemite Modoc Co CA 0.073 0.400 0.527

Carlsbad Caverns San Juan CO 0.312 0.203 0.485

Gila W Garfield CO 0.464 0.087 0.449
PARK COUNTY STATE

Percent of 2030 Visibility Benefit Due to

Changes in:

SO2 NOx direct PM

Joyce Kilmer-Slickrock Routt Co CO 0.289 0.286 0.425

Kalmiopsis W Larimer CO 0.407 0.123 0.470

Linville Gorge W Pitkin Co CO 0.537 0.074 0.389

Lostwood W Alamosa CO 0.391 0.103 0.505

Pecos W Gunnison CO 0.320 0.091 0.589

Presidential Range-Dry Montezum CO 0.367 0.180 0.452

Salt Creek W Montrose CO 0.397 0.156 0.447

Shining Rock W Summit CO 0.397 0.156 0.447

Wheeler Peak W Mineral CO 0.471 0.140 0.389

Wichita Mountains W Larimer CO 0.385 0.188 0.428

Fitzpatrick W Monroe FL 0.365 0.204 0.431

Glacier Peak W Wakulla FL 0.503 0.033 0.464

Mount Adams W Citrus Co FL 0.497 0.070 0.433

Dolly Sods W Charlton GA 0.503 0.085 0.412

North Absaroka W McIntosh GA 0.463 0.082 0.456

Olympic Edmonson KY 0.365 0.304 0.332

Lye Brook W Stone Co MS 0.486 0.166 0.348

Bridger W Hyde Co NC 0.515 0.183 0.302

Goat Rocks W Haywood NC 0.455 0.252 0.293

Otter Creek W Avery Co NC 0.436 0.232 0.332

Pasayten W Graham NC 0.309 0.371 0.320

Bandelier Sandoval NM 0.389 0.051 0.560

Bosque del Apache W Rio Arriba NM 0.374 0.037 0.589

Brigantine W Grant Co NM 0.378 0.069 0.553

Crater Lake Chaves Co NM 0.387 0.021 0.592

Mount Hood W Mora Co NM 0.525 0.100 0.375

Mount Washington W Eddy Co NM 0.421 0.124 0.455

San Pedro Parks W Socorro NM 0.472 0.059 0.469

Swanguarter W Taos Co NM 0.481 0.092 0.427

Theodore Roosevelt Lincoln NM 0.553 0.078 0.369

Maroon Bells- Elko Co NV 0.261 0.345 0.394

Mount Rainier Polk Co TN 0.359 0.295 0.346

North Cascades Blount Co TN 0.345 0.232 0.423

Bob Marshall W San Juan UT 0.322 0.046 0.632

Gates of the Mountain Grand Co UT 0.265 0.065 0.671

Glacier San Juan UT 0.337 0.064 0.600

St. Marks W Washingto UT 0.337 0.064 0.600

Voyageurs Garfield UT 0.190 0.129 0.680

Teton W Botetourt VA 0.445 0.193 0.361

Yellowstone Madison VA 0.331 0.387 0.282

Grand Teton NP Grant Co WV 0.455 0.275 0.270

Washakie W Tucker Co WV 0.487 0.200 0.313
CHAPTER 10: Economic Impact Analysis

10.1 Overview and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-1

10.1.1 What is an Economic Impact Analysis? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-1

10.1.2 What Methodology Did EPA Use in this Economic Impact Assessment? . . . . . . . . . . . . . . . . . . . . . 10-2

10.1.3 What are the key features of the NDEIM? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-5

10.1.3.1 Brief Description of the NDEIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-5

10.1.3.2 Product Markets Included in the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-6

10.1.3.3 Supply and Demand Elasticities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-9

10.1.3.4 Fixed and Variable Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-11

10.1.3.5 Compliance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-11

10.1.3.6 Other NDEIM Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-12

10.1.4 Summary of Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-14

10.1.4.1 What are the Rule’s Expected Market Impacts? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-15

10.1.4.2 What are the Rule’s Expected Social Costs? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-19

10.2 Economic Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-28

10.2.1 Behavioral Economic Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-28

10.2.2 Conceptual Economic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-29

10.2.2.1 Types of Models: Partial vs. General Equilibrium Modeling Approaches . . . . . . . . . . . . . . 10-29

10.2.2.2 Market Equilibrium in a Single Commodity Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-31

10.2.2.3 Incorporating Multimarket Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-32

10.2.3 Key Modeling Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-37

10.2.3.1 Perfect vs. Imperfect Competition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-37

10.2.3.2 Short- vs. Long-Run Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-38

10.2.3.3 Variable vs. Fixed Regulatory Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-42

10.2.3.4 Substitution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-45

10.2.4 Estimation of Social Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-47

10.3 NDEIM Model Inputs and Solution Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-50

10.3.1 Description of Product Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-51

10.3.1.1 Engine Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-51

10.3.1.2 Equipment Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-51

10.3.1.3 Application Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-54

10.3.1.4 Diesel Fuel Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-55

10.3.1.5 Locomotive and Marine Transportation Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-57

10.3.2 Market Linkages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-58

10.3.3 Baseline Economic Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-58

10.3.3.1 Baseline Quantities: Engines, Equipment and Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-58

10.3.3.2 Baseline Prices: Engines, Equipment and Fuel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-64

10.3.3.3 Baseline Quantities and Prices for Transportation and Application Markets . . . . . . . . . . . . 10-65

10.3.4 Calibrating the Fuel Spillover Baseline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-67

10.3.5 Compliance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-67

10.3.5.1 Engine and Equipment Compliance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-68

10.3.5.2 Nonroad Diesel Fuel Compliance Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-76

10.3.5.3 Changes in Operating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-77

10.3.6 Growth Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-80

10.3.7 Market Supply and Demand Elasticities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-80

10.3.8 Model Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-84

10.3.8.1 Computing Baseline and With-Regulation Equilibrium Conditions . . . . . . . . . . . . . . . . . . . . 10-84

10.3.8.2 Solution Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-86

10.4 Estimating Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-87

APPENDIX 10A: Impacts on the Engine Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-93

APPENDIX 10B: Impacts on Equipment Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-102

APPENDIX 10C: Impacts on Application Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-153

APPENDIX 10D: Impacts on the Nonroad Fuel Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-159

APPENDIX 10E: Time Series of Social Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-164

APPENDIX 10F: Model Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-168

APPENDIX 10G: Elasticity Parameters for Economic Impact Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-173

APPENDIX 10H: Derivation of Supply Elasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-189

APPENDIX 10I: Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-190
Economic Impact Analysis

10-1

CHAPTER 10: Economic Impact Analysis

This chapter contains the Economic Impact Analysis (EIA) prepared to estimate the

economic impacts of this rule on producers and consumers of nonroad engines, equipment, fuel

and related industries. This EIA relies on the Nonroad Diesel Economic Impact Model

(NDEIM), developed for this analysis, to estimate market-level changes in prices and outputs for

affected engine, equipment, fuel, and application markets as well as the social costs and their

distribution across economic sectors affected by the program. The basis for this analysis is

provided in the Economic Impact Analysis technical support document prepared for the proposal

for this rule, as updated by a technical memoranda (RTI, 2003a, RTI 2004).

This analysis is based on an earlier version of the engineering costs developed for this rule. 

The final cost estimates for the engine program are slightly higher ($142 million) and the final

fuel costs are slightly lower ($246 million), resulting in a 30-year net present value of $27.1

billion (30 year net present values in the year 2004, using a 3% Discount Rate, $2002) or $104

million less than the engineering costs used in this analysis. We do not expect that the revised

engineering costs would change the overall results of this economic impact analysis given the

small portion of engine, equipment, and fuel costs to total production costs for goods and

services using these inputs and given the inelastic value of the estimated demand elasticities for

the application markets.

The first section of this chapter briefly describes the methodology we used to estimate the

economic impacts of this rule and presents an overview of the results. According to this analysis,

this rule would be highly beneficial to society, with a net present value of social costs of about

$27.2 billion, compared to net present value benefits through 2036 of $780 billion (30 year net

present values in the year 2004 using 3% discount rate, $2002). The impact of these costs on

society should be minimal, with the average price of goods and services produced using

equipment and fuel affected by the final rule expected to increase by about 0.1 percent. The

second section of this chapter presents a more detailed description of the economic methodology

behind the NDEIM and certain modeling assumptions. The third section describes the markets

included in the model and data inputs as well as the solution algorithm. Finally, the appendices

to this chapter contain detailed results, additional information on the model, and a sensitivity

analysis. 

10.1 Overview and Results 

10.1.1 What is an Economic Impact Analysis?

An Economic Impact Analysis is prepared to inform decision makers within the Agency

about the potential economic consequences of a regulatory action. The analysis contains

estimates of the social costs of a regulatory program and explores the distribution of these costs

across stakeholders. These estimated social costs can then be compared with estimated social

benefits (as presented in Chapter 9). As defined in EPA’s Guidelines for Preparing Economic
Final Regulatory Impact Analysis

10-2

Analyses (EPA 2000, p. 113), social costs are the value of the goods and services lost by society

resulting from a) the use of resources to comply with and implement a regulation and b)

reductions in output. In this analysis, social costs are explored in two steps. In the first step,

called the market analysis, we estimate how prices and quantities of good directly and indirectly

affected by the emission control program can be expected to change once the emission control

program goes into effect. The estimated price and quantity changes for engines, equipment, fuel,

and goods produced using these inputs are examined separately. In the second step, called the

economic welfare analysis, we look at the total social costs associated with the program and their

distribution across stakeholders.

10.1.2 What Methodology Did EPA Use in this Economic Impact Assessment?

The Nonroad Diesel Economic Impact Model (NDEIM) developed for this EIA estimates

how producers and consumers can be expected to respond to the regulatory compliance costs

associated with this rule. The NDEIM uses a multi-market analysis framework that considers

interactions between regulated markets and other markets to estimate how compliance costs can

be expected to ripple through these markets. The analysis provides an estimate of the average

increase in price and decrease in quantity of output produced for the markets examined. It also

allows us to estimate the social costs of the rule and identify how the various groups of affected

stakeholders will bear them. The economic theory on which the NDEIM is based is described in

Section 10.2. Market characteristics, compliance costs, and other data used in the NDEIM are

described in Section 10.3.

The NDEIM tracks average price and quantity changes for 62 integrated product markets. 

Figure 10.1-1 illustrates the connections between the industry segments included in the model

and the flow of regulatory compliance costs through the economic system. The rule will

increase the cost of producing nonroad diesel engines. Engine manufacturers are expected to

attempt to pass some or all of their direct compliance costs on to equipment manufacturers in the

form of higher diesel engine prices. Similarly, equipment manufacturers are expected to attempt

to pass some or all of their direct compliance costs (in the form of equipment redesign costs) and

indirect compliance costs (in the form of increased engine costs) to application market producers

through higher diesel equipment prices. Petroleum refiners are also expected to attempt to pass

some or all of their direct compliance costs on to application market producers and to the

locomotive and marine transportation service sectors through higher prices for diesel fuel. 

Finally, application market producers are expected to pass on some or all of their increased

equipment and diesel fuel costs to consumers of final application market products and services. 

It is the interaction of suppliers and purchasers in each of the markets that determines the extent

to which prices and quantities of goods produced change in response to the compliance costs

associated with the rule. The amount of the compliance costs that can be passed on is affected

by the price sensitivity of purchasers in the relevant market. The NDEIM explicitly models

market linkages and behavioral responses and estimates new equilibrium prices and output and

the resulting distribution of social costs across affected stakeholders.

Diesel engines, equipment, and fuel represent only a small portion of the total production

costs for each of the three application market sectors (the final users of the engines, equipment
Economic Impact Analysis

10-3

Application Consumers

Application Suppliers included in NDEIM

Diesel Equipment

Manufacturers

Petroleum Refineries

Diesel Fuel Markets

(by PADD Region)

Diesel Engine

Manufacturers

Diesel Equipment Markets (by hp size)

• Agriculture

• Construction

• Industrial

• Pumps and

Compressors • Generator Sets

• Refrigeration

• Lawn and Garden

Diesel Engine Markets

• ≤25 hp

• 26-50 hp

• 51-75 hp

• 76-100 hp

• 101-175 hp

• 176-600 hp

• ≥601 hp

Compliance

Costs

• 500 ppm sulfur content

• 15 ppm sulfur content

• Agriculture Construction • • Manufacturing

Application Markets included in NDEIM

Locomotive and

Marine Service

Providers

Locomotive and Marine

Fuel Consumption

Locomotive and

Marine Service

Markets

Application Suppliers not included in NDEIM

Application

Imports

Application

Exports

Nonlocomotive and Marine

Fuel Consumption

Figure 10.1-1. Market Linkages Included in the Economic Model

and fuel affected by this rule). Other more significant production costs include land, labor, other

capital, raw materials, insurance, profits, etc. These other production costs are not affected by

this emission control program. This is important because it means that this rule directly affects

only a small part of total inputs for the relevant markets. Therefore, rule is not expected to have

a large adverse impact on output and prices of goods produced in the three application sectors.
Final Regulatory Impact Analysis

10-4

10.1.3 What are the key features of the NDEIM?

10.1.3.1 Brief Description of the NDEIM

The NDEIM is a computer model comprised of a series of spreadsheet modules that define

the baseline characteristics of supply and demand for the relevant markets and the relationships

between them. The basis for this analysis is provided in the EIA technical support document, as

updated by a technical memo (RTI, 2003a, RTI 2004). The model methodology, as explained in

Section 10.2.2, is firmly rooted in applied microeconomic theory and was developed following

the OAQPS Economic Analysis Resource Document (EPA, 1999). The NDEIM uses a multimarket partial equilibrium approach to track changes in price and quantity for the modeled

product markets. As explained in the EPA Guidelines for Preparing Economic Analyses (EPA

2000, 125-6; see also Section 10.2.2, below), ‘partial’ equilibrium refers to the fact that the

supply and demand functions are modeled for just one or a few isolated markets and that

conditions in other markets are assumed either to be unaffected by a policy or unimportant for

social cost estimation. Multi-market models go beyond partial equilibrium analysis by extending

the inquiry to more than just a single market. Multi-market analysis attempts to capture at least

some of the interactions between markets.

The NDEIM uses an intermediate run time frame and assumes perfect competition in the

market sectors. These model features are explained in Sections 10.2.3.1 and 10.2.3.2. The use

of the intermediate run means that some factors of production are fixed and some are variable. 

This modeling period allows analysis of the economic effects of the rule’s compliance costs on

current producers. The short run, in contrast, imposes all compliance costs on the manufacturers

(no pass-through to consumers), while the long run imposes all costs on consumers (full cost

pass-through to consumers). The perfect competition assumption is appropriate given the

number of firms and other key characteristics for each market (no indications of barriers to entry;

the firms are not price setters; there is no evidence of high levels of strategic behavior in the

price and quantity decisions of the firms; the products produced within each market are

somewhat homogeneous in that engines from one firm can be purchased instead of engines from

another firm; see Section 10.2.3.1, below). The use of the intermediate run time frame and the

assumption of perfect competition are based on widely accepted economic practice for this type

of analysis (see for example EPA, 2000, p. 126).

The NDEIM is constructed based on the market characteristics and inter-connections

described in this chapter. The model is shocked by applying the engineering compliance cost

estimates to the appropriate market suppliers, and then numerically solved using an iterative

auctioneer approach by “calling out” new prices until a new equilibrium is reached in all markets

simultaneously. The output of the model is new equilibrium prices and quantities for all affected

markets. This information is used to estimate the social costs of the model and how those costs

are shared among affected markets.
Economic Impact Analysis

10-5

10.1.3.2 Product Markets Included in the Model

There are 62 integrated product markets included in the model, as follows:

C 7 diesel engine markets: less than 25 hp, 26 to 50 hp, 51 to 75 hp, 76 to 100 hp, 101 to

175 hp, 176 to 600 hp, and greater than 600 hp. The EIA includes more horsepower

categories than the standards to allow more efficient use of the engine compliance costs

estimates. The additional categories also allow estimating economic impacts for a more

diverse set of markets.

C 42 diesel equipment markets: 7 horsepower categories within 7 application categories:

agricultural, construction, general industrial, pumps and compressors, generator and

welder sets, refrigeration and air conditioning, and lawn and garden. There are 7

horsepower/application categories that did not have sales in 2000 and are not included in

the model, so the total number of diesel equipment markets is 42 rather than 49.

C 3 application markets: agricultural, construction, and manufacturing.

C 8 nonroad diesel fuel markets: 2 sulfur content levels (15 ppm and 500 ppm) for each of

4 PADDs. PADDs 1 and 3 are combined for the purpose of this analysis. It should be

noted that PADD 5 includes Alaska and Hawaii. Also, California fuel volumes that are

not affected by the program (because they are covered by separate California nonroad

diesel fuel standards) are not included in the analysis.

C 2 transportation service markets: locomotive and marine. 

Table 10.1-1 summarizes the characteristics of each of these five groups of markets. More

detailed information on NDEIM model inputs in provided in Section 10.3.
Table 10.1-1

Summary of Markets in Nonroad Diesel Economic Impact Model (NDEIM)

Model 

Dimension

Markets (number)

Diesel Engines (7) Diesel Equipment (42) Diesel Fuel (8) Application (3)

L

Tr

Geographicscope

National National Regional by PADDs National Nati

Productgroupings

7 horsepower categoriesconsistent with emissionstandardsa

7 horsepower categorieswithin seven applicationcategoriesb,c

2 diesel fuels by sulfurcontent (500, 15 ppm)for 4 regional marketsd

Three broadcommodity categoriese

2: ratrans

Marketstructure

Perfectly competitive Perfectly competitive Perfectly competitive Perfectly competitive Perf

Baselinepopulation

Power Systems Research(PSR) database for 2000as modified by EPA

Assume one-to-onerelationship with enginepopulationf

Based on EnergyInformationAdministration (EIA)2000 fuel consumptiondata

Value of shipmentsfor 2000 from U.S.Census Bureau

Serv1997 Suppand TablTabl

Growthprojections

Growth rates used incost analysis; seeSection 8.1

Growth rates used in costanalysis; see Section 8.1

Based on nonroadmodel and EIA

Average of equipmentgrowth ratesconsumed by thesemarkets

EPA

projeengidistiannu2003

Supplyelasticity

Econometric estimate(elastic)

Econometric estimate(elastic)

Published econometricestimate (inelastic)

Published econometricestimate (inelastic)

Publestim

Demandelasticity

Derived demand Derived demand Derived demand Econometric estimate

(inelastic)

Deri

Regulatoryshock

Direct compliance costscause shift in supplyfunction

Direct compliance costsand higher diesel engineprices cause shift insupply function

Direct compliancecosts cause shift insupply function

No direct compliancecosts but higher pricesfor diesel equipmentand fuel cause shift insupply function

No dbut hfuel func

a Horsepower categories are 0-25, 26-50, 51-75, 76-100, 101-175, 176-600, and 601 hp and greater; the EIA includes more horsepow

standards, allowing more efficient use of the engine compliance cost estimates.
b Engine categories are agricultural, construction, pumps and compressors, generator and welder sets, refrigeration and air conditioni

lawn and garden. c There are seven horsepower/application categories that do not have sales in 2000 and are not included in the model. These are: agr

hp; gensets & welders > 600 hp; refrigeration & A/C > 71 hp (4 hp categories); and lawn & garden >600 hp. Therefore, the total nmarkets is 42 rather than 49. d PADDs 1 and 3 are combined for the purpose of this analysis). Note that PADD 5 includes Alaska and Hawaii. Also, California fuaffected by the program (because they are covered by separate California nonroad diesel fuel standards) are not included in the ana

e Application market categories are construction, agriculture, and manufacturing. f See Section 10.3.1 for an explanation of how the engines were allocated to the seven categories.
Final Regulatory Impact Analysis

10-8

Analysis of the three application markets is limited to market output. The economic impacts

on particular groups of application market suppliers (e.g., the profitability of farm production

units or manufacturing or construction firms) or particular groups of consumers (e.g., households

and companies that consume agricultural goods, buildings, or durable or consumer goods) are

not estimated. In other words, while we estimate that the application markets will bear most of

the burden of the regulatory program and we apportion the decrease in application market

surplus between application market producers and application market consumers, we do not

estimate how those social costs will be shared among specific application market producers and

consumers (e.g., farmers and households). In some cases, application market producers may be

able to pass most if not all of their increased costs to the ultimate consumers of their products; in

other cases, they may be obliged to absorb a portion of these costs. The focus on market-level

impacts in this analysis is appropriate because the standards in this emission control program are

technical standards that apply to nonroad engines, equipment, and fuel regardless of how they

are used and the structure of the program does not suggest that different sectors will be affected

differently by the requirements.

10.1.3.3 Supply and Demand Elasticities

The estimated social costs of this emission control program are a function of the ways in

which producers and consumers of the engines, equipment, and fuels affected by the standards

change their behavior in response to the costs incurred in complying with the standards. As the

compliance costs ripple through the markets, producers and consumers change their production

and purchasing decisions in response to changes in prices. In the NDEIM, these behavioral

changes are modeled by the demand and supply elasticities (behavioral-response parameters),

which measure the price sensitivity of consumers and producers.

The supply elasticities for the equipment, engine, diesel fuel, and transportation service

markets and the demand and supply elasticities for the application markets used in the NDEIM

were obtained from peer-reviewed literature sources or were estimated using econometric

methods. These econometric methods are well-documented and are consistent with generally

accepted econometric practice. Details on sources and estimation method are provided in

Section 10.3 and Appendix 10H. 

The equipment and engine supply elasticities are elastic, meaning that quantities supplied are

expected to be fairly sensitive to price changes. This means that manufacturers are more likely

(better able) to change production levels in response to price changes. 

The supply elasticities for the fuel, transportation service, and the supply and demand

elasticities for the three application markets are inelastic or unit elastic, meaning that the quantity

supplied/demanded is expected to be fairly insensitive to price changes or will vary one-to-one

with price changes. For the agricultural application market, the inelastic supply and demand

elasticities reflect the relatively constant demand for food products and the high fixed cost nature

of food production. For the construction and manufacturing application markets, the estimated

demand and supply elasticities are less inelastic, because consumers have more flexibility to

substitute away from construction and manufactured products and producers have more
Economic Impact Analysis

AIf the elasticity of demand for a final product is less than the elasticity of substitution between

an input and other inputs to the final product, then the demand for the input is less elastic the

smaller its cost share. Hicks, J.R., 1961, 1963.

10-9

flexibility to adjust production levels. The estimated supply elasticity for the diesel fuel market

is inelastic, reflecting the fact that most refineries operate near capacity and are therefore less

responsive to fluctuations in market prices. Note that these elasticities reflect intermediate run

behavioral changes. In the long run, supply and demand are expected to be more elastic since

more substitutes may become available. 

The inelastic values for the demand elasticities for the application markets are consistent

with the Hicks-Allen derived demand relationship, according to which a low cost-share in

production combined with limited substitution yields inelastic demand.A As noted above, diesel

engines, equipment, and fuel represent only a small portion of the total production costs for each

of the three application sectors. The limited ability to substitute for these inputs is discussed in

Section 10.2.3.4.

Because the elasticity estimates are a key input to the model, a sensitivity analysis for supply

and demand elasticity parameters was performed as part of this EIA. The results are presented in

Appendix 10I. In general, varying the elasticity values across the range of values reported in the

literature or using the upper and lower bounds of a 90 percent confidence interval around

estimated elasticities has no impact on the magnitude of the total social costs and only a minimal

impact on the distribution of costs across stakeholders. This is not surprising because equipment

and diesel fuel costs are a relatively small share of total production costs in the construction,

agriculture, and manufacturing industries.

In contrast to the above, the demand elasticities for the engine, equipment, fuel, and

transportation markets are internally derived as part of the process of running the model. This is

an important feature of the NDEIM, which allows it to link the separate market components of

the model and simulate how compliance costs can be expected to ripple through the affected

economic sectors. In the real world, for example, the quantity of nonroad equipment units

produced in a particular period depends on the price of engines (the engine market) and the

demand for equipment (the application markets). Similarly, the number of engines produced

depends on the demand for engines (the equipment market) which depends on the demand for

equipment (the application markets). Changes in conditions in one of these markets will affect

the others. By designing the model to derive the engine, equipment, transportation market, and

fuel demand elasticities, the NDEIM simulates these connections between supply and demand

among all the product markets and replicates the economic interactions between producers and

consumers.

10.1.3.4 Fixed and Variable Costs

Engines and Equipment. The EIA treats the fixed costs expected to be incurred by engine

and equipment manufacturers differently in the market and social costs analyses. This feature of
Final Regulatory Impact Analysis

10-10

the model is described in greater detail in Section 10.2.3.3. In the market analysis, estimated

engine and equipment market impacts (changes in prices and quantities) are based solely on the

expected increase in variable costs associated with the standards. Fixed costs are not included in

the market analysis reported in Table 10.1-2 because in an analysis of competitive markets the

industry supply curve is based on its marginal cost curve and fixed costs are not reflected in

changes in the marginal cost curve. In addition, the fixed costs associated with the rule are

primarily R&D costs for design and engineering changes. Firms in the affected industries

currently allocate funds for R&D programs and this rule is not expected to lead firms to change

the size of their R&D budget. Therefore, changes in fixed costs for engine and equipment

redesign associated with this rule are not likely to affect the prices of engines or equipment. 

These fixed costs are reported in the social cost analysis reported in Table 10.1-4, however, as an

additional cost to producers. This is appropriate because even though firms currently allocated

funds to R&D those resources are intended for other purposes such as increasing engine power,

ease of use, or comfort. These improvements will therefore be postponed for the length of the

rule-related R&D program. This is a cost to society. 

It may be the case, however, that some firms will maintain their current R&D budget and

allocate additional funds to comply with the this rule. Therefore, a sensitivity analysis was

performed as part of this EIA in which fixed costs are included in intermediate-run decisionmaking. The results of this sensitivity analysis are presented in Appendix 10.I. In this scenario,

including fixed costs in the model results in a transfer of economic welfare losses from engine

and equipment markets to the application markets (engine and equipment producer surplus losses

decrease; consumer surplus losses increase), but does not change the overall social costs

associated with the rule.

Fuels. Unlike for engines and equipment, most of the petroleum refinery fixed costs are for

production hardware. Refiners are expected to have to make physical changes to their refineries

and purchase additional equipment to produce 500 ppm and then 15 ppm fuel. Therefore, fixed

costs are included in the market analysis for fuel price and quantity impacts.

10.1.3.5 Compliance Costs

Engine and Equipment Compliance Costs. The NDEIM uses the engine and equipment

compliance costs described in Chapter 6. Engine and equipment costs vary over time because

fixed costs are recovered over five to ten year periods while total variable costs, despite learning

effects that serve to reduce costs on a per unit basis, continue to increase at a rate consistent with

new sales increases. Similarly, engine operating costs also vary over time because oil change

maintenance savings, PM filter maintenance, and fuel economy effects, all of which are

calculated on the basis of gallons of fuel consumed, change over time consistent with the growth

in nationwide fuel consumption. 

The relative magnitude of engine and equipment compliance costs is expected to have a

predictable relationship on market prices and quantities. Generally, the estimated price increases

and quantity reductions for engines and equipment are expected to vary depending on the

magnitude of compliance costs relative to total engine or equipment costs. In general, higher
Economic Impact Analysis

10-11

(lower) price increases are expected as a result of a high (low) relative level of compliance costs

to market price. The change in price is also expected to be highest when compliance costs are

highest.

Fuel Compliance Costs. The NDEIM uses the fuel compliance costs described in Chapter 7. 

Fuel-related compliance costs (costs for refining and distributing regulated fuels) also change

over time. These changes are more subtle than the engine costs, however, as the fuel provisions

are largely implemented in discrete steps instead of phasing in over time. Compliance costs

were developed on a ¢/gallon basis; total compliance costs are determined by multiplying the

¢/gallon costs by the relevant fuel volumes. Therefore, total fuel costs increase as the demand

for fuel increases. The variable operating costs are based on the natural gas cost of producing

hydrogen and for heating diesel fuel for the new desulfurization equipment, and thus would

fluctuate along with the price of natural gas. 

10.1.3.6 Other NDEIM Features

Substitution. In modeling the market impacts and social costs of this rule, the NDEIM

considers only diesel equipment and fuel inputs to the production of goods in the applications

markets. It does not explicitly model alternate production inputs that would serve as substitutes

for new nonroad equipment or nonroad diesel fuel. In the model, market changes in the final

demand for application market goods and services directly correspond to changes in the demand

for nonroad equipment and fuel (i.e., in normalized terms there is a one-to-one correspondence

between the quantity of the final goods produced and the quantity of nonroad diesel equipment

and fuel used as inputs to that production). We believe modeling the market in this manner is

economically sound and reflects the general experience for the nonroad market. Section 10.2.3.4

describes several alternative means of production that could serve as substitutes for new nonroad

equipment and fuel and explains why they are not included in the NDEIM.

Operating Savings. Operating savings refers to changes in operating costs that are expected

to be realized by users of both existing and new nonroad diesel equipment as a result of the

reduced sulfur content of nonroad diesel fuel. These include operating savings (cost reductions)

due to fewer oil changes, which accrue to nonroad, marine and locomotive engines that are

already in use as well as new nonroad engines that will comply with the standards (see Section

6.2.3). These also include any extra operating costs associated with the new PM emission

control technology which may accrue to certain new engines that use this technology. Operating

savings are not included in the market analysis because some of the savings accrue to existing

engines and because, as explained in Chapter 6, these savings are not expected to affect

consumer decisions with respect to new engines. Operating savings are included in the social

cost analysis, however, because they accrue to society. They are added into the estimated social

costs as an additional savings to the application and transportation service markets, since it is the

users of these engines and fuels who will see these savings. A sensitivity analysis was

performed as part of this EIA that includes the operating savings in the market analysis. The

results of this sensitivity analysis are presented in Appendix 10.I.
Final Regulatory Impact Analysis

10-12

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

$2,200

$2,400

20042006200820102012201420162018202020222024202620282030203220342036

Figure 10.1-2

Heating Oil Marker Costs ($Million, $2002)

Fuel Marker Costs. Fuel marker costs refers to costs associated with marking high sulfur

heating oil to distinguish it from high sulfur diesel fuel produced after 2007 through the use of

early sulfur credits or small refiner provisions. Only heating oil sold outside of the Northeast is

affected. The higher sulfur NRLM fuel is not allowed to be sold in most of the Northeast, so the

marker need not be added in this large heating oil market. These costs are expected to be about

$810,000 in 2007, increasing to $1.38 million in 2008, but steadily decreasing thereafter to about

$940,000 in 2040 (see Chapter 10 of the RIA). Because these costs are relatively small, they are

incorporated into the estimated compliance costs for the fuel program (see discussion of fuel

costs, above). They are therefore not counted separately in this economic impact analysis. This

means that the costs of marking heating fuel are allocated to all users of the fuel affected by this

rule (nonroad, locomotive, and marine) instead of uniquely to heating oil users. This is a

reasonable approach since it is likely that refiners will pass the marker costs along their complete

nonroad diesel product line and not just to heating oil. 

Fuel Spillover. Spillover fuel is highway grade diesel fuel consumed by nonroad equipment,

stationary diesel engines, boilers, and furnaces. As described in 7.1, refiners are expected to

produce more 15 ppm fuel than is required for the highway diesel market. This excess 15 ppm

fuel will be sold into markets that allow fuel with a higher sulfur level (i.e., nonroad for a limited

period of time, locomotive, marine diesel and heating oil). This spillover fuel is affected by the
Economic Impact Analysis

10-13

diesel highway rule and is not affected by this regulation. Therefore, it is important to

differentiate between spillover and nonspillover fuel to ensure that the compliance costs for that

fuel pool are not counted twice. In the NDEIM, this is done by incorporating the impact of

increased fuel costs associated with the highway rule prior to analysis of the final nonroad rule

(see Section 10.3.8).

Compliance Flexibility Provisions. Consistent with the engine and equipment cost

discussion in Chapter 6, the EIA does not include any cost savings associated with the equipment

transition flexibility program or the nonroad engine ABT program. As a result, the results of this

EIA can be viewed as somewhat conservative.

Locomotive and Marine Fuel Costs. The locomotive and marine transportation sectors are

affected by this rule through the sulfur limits on the diesel fuel used by these engines. These

sectors provide transportation to the three application markets as well as to other markets not

considered in the NDEIM (e.g., public utilities, nonmanufacturing service industries,

government). As explained in Section 10.3.1.5, the NDEIM applies only a portion of the

locomotive and marine fuel costs to the three application markets. The rest of the locomotive

and marine fuel costs are added as a separate item to the total social cost estimates (as

Application Markets Not Included in NDEIM).

10.1.4 Summary of Economic Analysis

Economic impact results for 2013, 2020, 2030, and 2036 are presented in this section. The

first of these years, 2013, corresponds to the first year in which the standards affect all engines,

equipment, and fuels. It should be noted that, as illustrated in Table 10.1-3, aggregate program

costs peak in 2014; increases in costs after that year are due to increases in the population of

engines over time. The other years, 2020, 2030 and 2036, correspond to years analyzed in our

benefits analysis. Detailed results for all years are included in the appendices for this chapter.

In the following discussion, social costs are computed as the sum of market surplus offset by

operating savings. Market surplus is equal to the aggregate change in consumer and producer

surplus based on the estimated market impacts associated with the rule. As explained above,

operating savings are not included in the market analysis but instead are listed as a separate

category in the social cost results tables.

In considering the results of this analysis, it should be noted that the estimated output

quantities for diesel engines, equipment, and fuel are not identical to those estimated in the

engineering cost discussions in Chapters 6 and 7. The difference is due to the different

methodologies used to estimate these costs. As noted above, social costs are the value of goods

and services lost by society resulting from a) the use of resources to comply with and implement

a regulation (i.e., compliance costs) and b) reductions in output. Thus, the social cost analysis

considers both price and output (quantity) effects associated with consumer and producer

reaction to increased prices associated with the regulatory compliance costs. The engineering

cost analysis, on the other hand, is based on applying additional technology to comply with the

new regulations. The engine population in the engineering cost analysis does not adjust to
Final Regulatory Impact Analysis

BThe NDEIM distinguishes between “merchant” engines and “captive” engines. “Merchant”

engines are produced for sale to another company and are sold on the open market to anyone

who wants to buy them. “Captive” engines are produced by a manufacturer for use in its own

nonroad equipment line (this equipment is said to be produced by “integrated”

manufacturers). The market analysis for engines includes compliance costs for merchant

engines only. The market analysis for equipment includes equipment compliance costs plus a

portion of the engine compliance costs attributable to captive engines.

10-14

reflect consumer and producer reactions to the compliance costs. Consequently, the estimated

output quantities from the cost analysis are slightly larger than the estimated output quantities

from the social cost analysis. 

10.1.4.1 What are the Rule’s Expected Market Impacts?

The estimated market impacts for 2015, 2020, 2030, and 2036 are presented in Table 10.1-2. 

The market-level impacts presented in this table represent production-weighted averages of the

individual market-level impact estimates generated by the model: the average expected price

increase and quantity decrease across all of the units in each of the engine, equipment, fuel, and

final application markets. For example, the model includes seven individual engine markets that

reflect the seven different horsepower size categories. The 21.4 percent price change for engines

shown in Table 10.1-2 for 2013 is an average price change across all engine markets weighted

by the number of production units. Similarly, the equipment impacts presented in Table 10.1-2

are the weighted averages of 42 equipment-application markets, such as small (< 25hp)

agricultural equipment and large (>600hp) industrial equipment. Note that price increases and

quantity decreases for specific types of engines, equipment, application sectors, or diesel fuel

markets are likely to be different. The aggregated data presented in this table provide a broad

overview of the expected market impacts that is useful when considering the impacts of the rule

on the economy as a whole. Individual market-level impacts are presented in Appendix 10A

through Appendix 10D.B

The market impacts of this rule suggest that the overall economic impact on society is

expected be small, on average. With regard to the market analysis, the average price of goods

and services produced using affected equipment and fuel is expected to increase by less than 0.1

percent despite the high level of cost pass-through to those markets. 

Engine Market Results: This analysis suggests that most of the variable costs associated with

the rule will be passed along in the form of higher prices. The average price increase in 2013 for

engines is estimated to be about 21.4 percent. This percentage is expected to decrease to about

18.3 percent by 2020. In 2036, the last year considered, the average price increase is expected to

be about 18.2 percent. This expected price increase varies by engine size because compliance

costs are a larger share of total production costs for smaller engines. In 2013, the largest

expected percent price increase is for engines between 25 and 50 hp: 29 percent or $850; the

average price for an engine in this category is about $2,900. However, this price increase is

expected to drop to 22 percent, or about $645, for 2015 and later. The smallest expected percent
Economic Impact Analysis

10-15

price increase in 2013 is for engines in the greater than 600 hp category. These engines are

expected to see price increases of about 3 percent increase in 2013, increasing to about 7.6

percent in 2015 and then decreasing to about 6.6 percent in 2017 beyond. The expected price

increase for these engines is about $2,240 in 2013, increasing to about $6,150 in 2015 and then

decreasing to $5,340 in 2017 and later, for engines that cost on average about $80,500. 

The market impact analysis predicts that even with these increased in engine prices, total

demand is not expected to change very much. The expected average change in quantity is less

than 150 engines per year, out of total sales of more than 500,000 engines. The estimated

change in market quantity is small because as compliance costs are passed along the supply

chain they become a smaller share of total production costs. In other words, firms that use these

engines and equipment will continue to purchase them even at the higher cost because the

increase in costs will not have a large impact on their total production costs (diesel equipment is

only one factor of production for their output of construction, agricultural, or manufactured

goods).

Equipment Market Results: Estimated price changes for the equipment markets reflect both

the direct costs of the new standards on equipment production and the indirect cost through

increased engine prices. In general, the estimated percentage price changes for the equipment

are less than that for engines because the engine is only one input in the production of

equipment. In 2013, the average price increase for nonroad diesel equipment is estimated to be

about 2.9 percent. This percentage is expected to decrease to about 2.5 percent for 2020 and

beyond. The range of estimated price increases across equipment types parallels the share of

engine costs relative to total equipment price, so the estimated percentage price increase among

equipment types also varies. For example, the market price in 2013 for agricultural equipment

between 175 and 600 hp is estimated to increase about 1.2 percent, or $1,740 for equipment with

an average cost of $143,700. This compares with an estimated engine price increase of about

$1,700 for engines of that size. The largest expected price increase in 2013 for equipment is

$2,290, or 2.6 percent, for pumps and compressors over 600 hp. This compares with an

estimated engine price increase of about $2,240 for engines of that size. The smallest expected

price increase in 2013 for equipment is $120, or 0.7 percent, for construction equipment less than

25 hp. This compares with an estimated engine price increase of about $120 for engines of that

size. 

Again, the market analysis predicts that even with these increased equipment prices total

demand is not expected to change very much. The expected average change in quantity is less

than 250 pieces of equipment per year, out of a total sales of more than 500,000 units. The

average decrease in the quantity of nonroad diesel equipment produced as a result of the

regulation is estimated to be about 0.02 percent for all years. The largest expected decrease in

quantity in 2013 is 18 units of construction equipment per year for construction equipment

between 100 and 175 hp, out of about 63,000 units. The smallest expected decrease in quantity

in 2013 is less than one unit per year in all hp categories of pumps and compressors. 

It should be noted that the absolute change in the number of engines and equipment does not

match. This is because the absolute change in the quantity of engines represents only engines
Final Regulatory Impact Analysis

10-16

sold on the market. Reductions in engines consumed internally by integrated engine/equipment

manufacturers are not reflected in this number but are captured in the cost analysis.
Economic Impact Analysis

10-17

Table 10.1-2

Summary of Market Impacts ($2002)

Market

Engineering Cost Change in Price Change in Quantity

Per Unit Absolute

 ($million)

Percent Absolute Percent

2013

Engines $1,052 $821 21.4 –79a –0.014

Equipment $1,198 $975 2.9 –139 –0.017 

Loco/Marine Transpb 0.009 –0.007

Application Marketsb 0.097 –0.015 

No. 2 Distillate Nonroad $0.06 $0.07 6.0 –2.75c –0.019 

2020

Engines $950 $761 18.3 –98a –0.016

Equipment $1,107 $976 2.5 –172 –0.018

Loco/Marine Transpb 0.01 –0.008

Application Marketsb 0.105 –0.017

No. 2 Distillate Nonroad $0.07 $0.07 7.0 –3.00c –0.021

2030

Engines $937 $751 18.2 –114a –0.016

Equipment $968 $963 2.5 –200 –0.018

Loco/Marine Transpb 0.010 –0.008

Application Marketsb 0.102 –0.016

No. 2 Distillate Nonroad $0.07 $0.07 7.0 –3.53c –0.022

2036

Engines $931 $746 18.2 –124a –0.016

Equipment $962 $956 2.5 –216 –0.018

Loco/Marine Transpb 0.010 –0.008

Application Marketsb 0.101 –0.016

No. 2 Distillate Nonroad $0.07 $0.07 7.0 –3.85c –0.022
Final Regulatory Impact Analysis

10-18

a

 The absolute change in the quantity of engines represents only engines sold on the market. Reductions in engines

consumed internally by integrated engine/equipment manufacturers are not reflected in this number but are captured in

the cost analysis. For this reason, the absolute change in the number of engines and equipment does not match.

b

 The model uses normalized commodities in the application markets because of the great heterogeneity of products. 

Thus, only percentage changes are presented.

c

 Units are in million of gallons.

Transportation Market Results: The estimated price increase associated with the proposed

standards in the locomotive and marine transportation markets is negligible, at 0.01 percent for

all years. This means that these transportation service providers are expected to pass along

nearly all of their increased costs to the agriculture, construction, and manufacturing application

markets, as well as other application markets not explicitly modeled in the NDEIM. This price

increases represent a small share of total application market production costs, and therefore are

not expected to affect demand for these services.

Application Market Results: The estimated price increase associated with the new standards

in all three application markets is very small and averages about 0.1 percent for all years. In

other words, on average, the prices of goods and services produced using the affected engines,

equipment, and fuel are expected to increase negligibly. This results from the observation that

compliance costs passed on through price increases represent a very small share of total

production costs in all the application markets. For example, the construction industry realizes

an increase in production costs of approximately $580 million in 2013 because of the price

increases for diesel equipment and fuel. However, this represents less than 0.001 percent of the

$820 billion value of shipments in the construction industry in 2000. The estimated average

commodity price increase in 2013 ranges from 0.08 percent in the manufacturing application

market to about 0.5 percent in the construction application market. The percentage change in

output is also estimated to be very small and averages less than 0.02 percent for all years. Note

that these estimated price increases and quantity decreases are average for these sectors and may

vary for specific subsectors. Also, note that absolute changes in price and quantity are not

provided for the application markets in Table 10.1-2 because normalized commodity values are

used in the market model. Because of the great heterogeneity of manufactured or agriculture

products, a normalized commodity ($1 unit) is used in the application markets. This has no

impact on the estimated percentage change impacts but makes interpretation of the absolute

changes less informative.

Fuel Markets Results: The estimated average price increase across all nonroad diesel fuel is

about 7 percent for all years. For 15 ppm fuel, the estimated price increase for 2013 ranges from

5.6 percent in the East Coast region (PADD 1&3) to 9.1 percent in the mountain region (PADD

4). The average national output decrease for all fuel is estimated to be about 0.02 percent for all

years, and is relatively constant across all four regional fuel markets.

10.1.4.2 What are the Rule’s Expected Social Costs?

Social costs include the changes in market surplus estimated by the NDEIM and changes in

operating costs associated with the regulation. Table 10.1-3 shows the time series of engineering
Economic Impact Analysis

10-19

compliance costs and social cost estimates for 2004 through 2036. As shown, these estimates for

engineering and social costs are of similar magnitude for each year of the analysis. However, the

compliance costs are distributed differently than the social costs. As illustrated in Figure 10.1-

3a, engineering compliance costs are distributed evenly across engine, equipment, and fuel

producers. However, as illustrated in Figure 10.1-3b, the social costs that result from those

compliance costs are borne mostly by producers and consumers in the application markets (about

84 percent when the operating savings are not considered) due to the increased prices for diesel

engines, equipment, and fuel. This means that engine, equipment, and fuel producers are

expected to be able to pass on most of their compliance costs. Specifically, engine producers are

expected to be able to pass on about 91.3 percent their compliance costs through higher prices. 

The remaining 8.7 percent are primarily fixed R&D costs that are internalized by engine

manufacturers and not passed into the market. Equipment manufacturers are expected to retain a

slightly higher share of compliance costs (28.5 percent) because they have greater fixed costs. 

Diesel fuel refiners are expected to pass about 99 percent of their compliance costs on to the

application producers and consumers because, as discussed in Chapter 6, refiners pass both fixed

and variable costs into the market. 
Final Regulatory Impact Analysis

10-20

a) Engineering Cost Distributiona

Engine Producers

27%

Equipment Producers

28%

Fuel Refiners

45%

Application Producers and

Consumers

0%

Application Producers

and Consumers

84%

Fuel Refiners

<1%

Engine Producers

2%

Equipment Producers

8%

$1,796 million

b) Social Cost Distributiona

$1,795 million

Locomotive and Marine

Transportation Services

<0.1%

Locomotive

and Marine

Transportation

Services

0%

Application Markets Not

Included in NDEIM

0%

Application Markets Not

Included in NDEIM

6%

Figure 10.1-3. Comparing the Distribution of Engineering Compliance Costs with Social Cost

Estimates by Industry (2013)

a

 Costs do not include operating cost savings, which represent negative $285 million in costs (i.e., benefits). 
Economic Impact Analysis

10-21

Table 10.1-3

National Engineering Compliance Costs and 

Social Costs Estimates for the Rule (2004 - 2036)($2002; $Million)

Year Engineering Compliance Costs Total Social Costs

2004 $0 $0

2005 $0 $0

2006 $0 $0

2007 ($17) ($18)

2008 $54 $54

2009 $54 $54

2010 $328 $327

2011 $923 $922

2012 $1,305 $1,304

2013 $1,511 $1,510

2014 $1,691 $1,690

2015 $1,742 $1,741

2016 $1,743 $1,743

2017 $1,763 $1,762

2018 $1,778 $1,778

2019 $1,795 $1,795

2020 $1,829 $1,828

2021 $1,816 $1,815

2022 $1,819 $1,818

2023 $1,844 $1,843

2024 $1,858 $1,857

2025 $1,888 $1,887

2026 $1,921 $1,920

2027 $1,954 $1,952

2028 $1,985 $1,984

2029 $2,017 $2,016

2030 $2,047 $2,046

2031 $2,078 $2,077

2032 $2,108 $2,107

2033 $2,139 $2,137

2034 $2,169 $2,167

2035 $2,198 $2,197

2036 $2,228 $2,227

NPV at 3% $27,247 $27,232

NPV at 7% $13,876 $13,868
Final Regulatory Impact Analysis

10-22

Figure 10.1-4 shows the time series of total social costs from 2004 through 2036. Social

costs increase rapidly between 2007 and 2014 as engine, equipment and fuel costs are phased

into the regulation. Estimated net annual social costs (including operating savings) in 2014 are

about $1,690 million. After 2014, per unit compliance costs decrease as fixed costs are

depreciated. However, due to growth in engine and equipment sales and related fuel

consumption, net social costs are expected continue to increase, but at a slower rate, from 2015

to 2036. The estimated net present value of social costs over the time period 2004 through 2036

based on a social discount rate of 3 percent is reported in Table 10.1-3 and is about $27.2 billion. 

The present value over this same period based on a social discount rate of 7 percent is about

$13.9 billion. As shown in Table 10.1-3, these results suggest that total engineering costs exceed

compliance costs by a small amount. This is due primarily to the fact that the estimated output

quantities for diesel engines, equipment, and fuel are not identical to those estimated in the

engineering cost analysis, which is due to the different methodologies used to estimate these

costs (see previous discussion in this Section 10.1.4).

Estimated social costs are disaggregated by market in Table 10.1-4, for 2015, 2020, 2030,

and 2036. A more detailed time series from 2007 to 2030 provided is in Appendix 10E. The

data in Table 10.1-4 shows that in 2013, social costs are expected to be about $1,510 million

($2002). About 83 percent of the total social costs is expected to be borne by producers and

consumers in the application markets in 2013, indicating that the majority of the compliance

costs associated with the rule are expected to be passed on in the form of higher prices. When

these estimated impacts are broken down, about 58.5 percent of the social costs are expected to

be borne by consumers in the application markets and about 41.5 percent are expected to be

borne by producers in the application markets. Equipment manufacturers are expected to bear

about 9.5 percent of the total social costs. Engine manufacturers and diesel fuel refineries are

expected to bear 2.8 percent and 0.5 percent, respectively. The remaining 4.2 percent of the

social costs is expected to be borne by the locomotive and marine transportation service sector. 

In this last sector, about 97 percent of the gross decrease in market surplus is expected to be

borne by the application markets that are not included in the NDEIM but that use these services

(e.g., public utilities, nonmanufacturing service industries, government) while about 3 percent is

expected to be borne by locomotive and marine service providers. Because of the way the

NDEIM is structured, with the fuel savings added separately, the results imply that locomotive

and marine service provides would see net benefits from the rule due to the operating savings

associated with low sulfur fuel. In fact, they are likely to pass along some or all of those

operating savings to the users of their services, reducing the size of the welfare losses for those

users.

Total social costs continue to increase over time and are projected to be about $2,046 million

by 2030 and $2,227 million in 2036 ($2002). The increase is due to the projected annual growth

in the engine and equipment populations. Producers and consumers in the application markets

are expected to bear an even larger portion of the costs, approximately 96 percent. This is

consistent with economic theory, which states that, in the long run, all costs are passed on to the

consumers of goods and services. 

Table 10.1-4
Summary of Social Costs Estimates Associated with Primary Program

2015, 2020, 2030, and 2036 ($2002, $Million)a,b

2013

Market Surplus

($106

)

Operating

Savings

 ($106) Total Percent

Engine Producers Total $42.0 $42.0 2.8%

Equipment Producers Total $143.1 $143.1 9.5%

Construction Equipment $64.0 $64.0

Agricultural Equipment $51.8 $51.8

Industrial Equipment $27.2 $27.2

Application Producers & Consumers Total $1,496.7 ($243.2) $1,253.5 83.0%

Total Producer $620.9 41.5%

Total Consumer $875.7 58.5%

Construction $584.3 ($115.2) $469.2

Agriculture $430.0 ($78.2) $351.8 

Manufacturing $482.4 ($49.8) $432.5

Fuel Producers Total $8.0 $8.0 0.5%

PADD I&III $4.1 $4.1

PADD II $3.3 $3.3

PADD IV $0.0 $0.0

PADD V $0.6 $6.0

Transportation Services, Total $104.9 ($41.5) $63.4 4.2%

Locomotive $1.6 ($12.4) ($10.8)

Marine $0.9 ($9.9) ($9.0)

Application markets not included in NDEIM $102.4 ($19.2) $83.2

Total $1,794.7 ($284.7) $1,510.0 100.0%

2020

Market Surplus

($106

)

Operating

Savings

 ($106) Total Percent

Engine Producers Total $0.1 $0.1 0.0%

Equipment Producers Total $122.7 $122.7 6.7% 

Construction Equipment $57.8 $57.8

Agricultural Equipment $39.7 $39.7

Industrial Equipment $25.2 $25.2

Application Producers & Consumers Total $1,826.1 ($192.3) $1,633.8 89.4%

Total Producer $762.2 41.7%

Total Consumer $1,063.8 58.3%

Construction $744.0 ($91.1) $653.0

Agriculture $524.3 ($61.8) $462.5

Manufacturing $557.8 ($39.4) $518.3

Fuel Producers Total $11.2 $11.2 0.6%

PADD I&III $5.6 $5.6

PADD II $4.6 $4.6
Final Regulatory Impact Analysis

10-24

PADD IV $0.2 $0.2

PADD V $0.8 $0.8

Transportation Services, Total $95.7 ($35.1) $60.6 3.3% 

Locomotive $2.0 ($7.2) ($5.2)

Marine $1.1 ($11.6) ($10.5) 

Application markets not included in NDEIM $92.6 ($16.3) $76.3

Total $2,055.7 ($227.4) $1,828.3 100.0%

2030

Engine Producers Total $0.1 $0.1 0.0%

Equipment Producers Total $5.9 $5.9 0.3%

Construction Equipment $4.0 $4.0

Agricultural Equipment $1.9 $1.9 

Industrial Equipment $0.1 $0.1

Application Producers & Consumers Total $2,112.3 ($154.2) $1,958.1 95.7%

Total Producer $882.2 41.7%

Total Consumer $1,230.1 58.3%

Construction $863.8 ($73.0) $790.8

Agriculture $606.8 ($49.6) $557.2

Manufacturing $641.6 ($31.6) $610.0

Fuel Producers Total $13.2 $13.2 0.6%

PADD I&III $6.7 $6.7

PADD II $5.2 $5.2

PADD IV $0.3 $0.3

PADD V $1.0 $1.0

Transportation Services, Total $109.1 ($39.9) $69.2 3.4%

Locomotive $2.5 ($7.8) ($5.3)

Marine $1.4 ($13.6) ($12.2)

Application markets not included in NDEIM $105.2 ($18.5) $86.7

Total $2,240.6 ($194.1) $2,046.4 100.0%

2036

Market Surplus

($106

)

Operating

Savings

 ($106) Total Percent

Engine Producers Total $0.2 $0.2 0.0%

Equipment Producers Total $6.4 $6.4 0.3%

Construction Equipment $4.3 $4.3

Agricultural Equipment $2.0 $2.0

Industrial Equipment $0.1 $0.1

Application Producers & Consumers Total $2,287.4 ($155.7) $2,131.7 95.7%

Total Producer $955.5 41.7%
Total Consumer $1,331.9 58.3%

Construction $936.4 ($50.0) $862.7

Agriculture $657.8 ($73.7) $607.8

Manufacturing $693.2 ($31.9) $661.3

Fuel Producers Total $14.5 $14.5 0.7%

PADD I&III $7.3 $7.3

PADD II $5.8 $5.8

PADD IV $0.3 $0.3

PADD V $1.0 $1.0

Transportation Services, Total $116.9 ($42.6) $74.3 3.3%

Locomotive $2.8 ($8.2) ($5.4)

Marine $1.6 ($14.6) ($13.0)

Application markets not included in NDEIM $112.5 ($19.8) $92.7

Total $2,425.3 ($198.4) $2,227.0 100.0%

a Figures are in 2002 dollars.

b Operating savings are shown as negative costs. 
Final Regulatory Impact Analysis

10-26

Table 10.1-5

Summary of Social Costs Estimates Associated with Primary Program:

NPV, 3%, 2004-2036 ($million)a,b

Market Surplus

($106

)

Operating

Savings 

($106) Total Percent

Engine Producers Total $256.0 $256.0 0.9%

Equipment Producers Total $1,162.0 $1,162.0 4.3%

Construction Equipment $545.0 $545.0

Agricultural Equipment $397.0 $397.0

Industrial Equipment $220.0 $220.0

Application Producers & Consumers

Total

$28,429.0 ($3,757.0) $24,672.0 90.6%

Total Producer $11,838.0 41.6%

Total Consumer $16,591.0 58.4%

Construction $11,526.0 ($1,779.0) $9,746.0

Agriculture $8,181.0 ($1,208.0) $6,973.0

Manufacturing $8,723.0 ($770.0) $7,953.0

Fuel Producers Total $169.0 $169.0 0.6%

PADD I&III $85.0 $85.0

PADD II $69.0 $69.0

PADD IV $3.0 $3.0

PADD V $12.0 $12.0

Transportation Services Total $1,653.0 ($679.0) $973.0 3.6%

Locomotive $31.0 ($160.0) ($129.0)

Marine $18.0 ($204.0) ($187.0)

Application markets not included in

NDEIM

$1,604.0 ($315.0) $1,228.0

Total $31,669.0 ($4,437.0) $27,232.0 100.0%

a Figures are in 2002 dollars. b Operating savings are shown as negative costs. 
Economic Impact Analysis

10-27

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

$2,200

$2,400

20042006200820102012201420162018202020222024202620282030203220342036

Figure 10.1-4

Total Social Costs (2004-2036; $2002; $Million)

10.2 Economic Methodology

Economic impact analysis uses a combination of theory and econometric modeling to

evaluate potential behavior changes associated with a new regulatory program. As noted above,

the goal is to estimate the impact of the regulatory program on producers and consumers. This is

done by creating a mathematical model based on economic theory and populating the model

using publically available price and quantity data. A key factor in this type of analysis is

estimating the responsiveness of the quantity of engines, equipment, and fuels demanded by

consumers or supplied by producers to a change in the price of that product. This relationship is

called the elasticity of demand or supply. This section discusses the economic theory underlying

the modeling for this EIA and several key issues that affect the way the model was developed.
Final Regulatory Impact Analysis

10-28

10.2.1 Behavioral Economic Models

Models incorporating different levels of economic decision making can generally be

categorized as with-behavior responses or without-behavior responses (engineering cost

analysis). Engineering cost analysis is an example of the latter and provides detailed estimates

of the cost of a regulation based on the projected number of affected units and engineering

estimates of the annualized costs. 

The behavioral approach builds on the engineering cost analysis and incorporates economic

theory related to producer and consumer behavior to estimate changes in market conditions. 

Owners of affected plants are economic agents that can make adjustments, such as changing

production rates or altering input mixes, that will generally affect the market environment in

which they operate. As producers change their production levels in response to a regulation,

consumers are typically faced with changes in prices that cause them to alter the quantity that

they are willing to purchase. These changes in price and output from the market-level impacts

are used to estimate the distribution of social costs between consumers and producers. 

Generally, the behavioral approach and engineering cost approach yield approximately the

same total cost impact. However, the advantage of the behavioral approach is that it illustrates

how the costs flow through the economic system and identifies which stakeholders, producers,

and consumers are most affected.

10.2.2 Conceptual Economic Approach 

This EIA models basic economic relationships between supply and demand to estimate

behavioral changes expected to occur as a result of the rule. An overview of the basic economic

theory used to develop the model to estimate the potential effect of the rule on market outcomes

is presented in this section. Following the OAQPS Economic Analysis Resource Document

(EPA, 1999), standard concepts in microeconomics are used to model the supply of affected

products and the impacts of the regulations on production costs and the operating decisions. 

10.2.2.1 Types of Models: Partial vs. General Equilibrium Modeling Approaches

In the broadest sense, all markets are directly or indirectly linked in the economy; thus, the

rule will affect all commodities and markets to some extent. The appropriate level of market

interactions to be included in an EIA is determined by the number of industries directly affected

by the requirements and the ability of affected firms to pass along the regulatory costs in the

form of higher prices. Alternative approaches for modeling interactions between economic

sectors can generally be divided into three groups:

C Partial equilibrium model—Individual markets are modeled in isolation. The only factor

affecting the market is the cost of the regulation on facilities in the industry being

modeled; there are no interaction effects with other markets. 

C General equilibrium model—All sectors of the economy are modeled together,

incorporating interaction effects between all sectors included in the model. General
Economic Impact Analysis

10-29

equilibrium models operationalize neoclassical microeconomic theory by modeling not

only the direct effects of control costs but also potential input substitution effects,

changes in production levels associated with changes in market prices across all sectors,

and the associated changes in welfare economy-wide. A disadvantage of general

equilibrium modeling is that substantial time and resources are required to develop a new

model or tailor an existing model for analyzing regulatory alternatives.

C Multimarket model—A subset of related markets is modeled together, with sector

linkages, and hence selected interaction effects, explicitly specified. This approach

represents an intermediate step between a simple, single-market partial equilibrium

approach and a full general equilibrium approach. This technique has most recently been

referred to in the literature as “partial equilibrium analysis of multiple markets” (Berck

and Hoffmann, 2002).

This analysis uses a behavioral multimarket framework because the benefits of increasing the

dimensions of the model outweigh the cost associated with additional model detail. As Bingham

and Fox (1999) note, this increased scope provides “a richer story” of the expected distribution

of economic welfare changes across producers and consumers. Therefore, the NDEIM

developed for this analysis consists of a spreadsheet model that links a series of standard partial

equilibrium models by specifying the interactions between the supply and demand for products. 

Changes in prices and quantities are then solved across all markets simultaneously. The

following markets were included in the model; their linkages are illustrated in Figure 10.2-1 and

they are described in detail in Section 10.3.3 below:

C seven diesel engine markets categorized by engine size;

C 42 equipment markets, including construction, agriculture, refrigeration, lawn and

garden, pumps and compressors, generators and welder sets, and general industrial

equipment types—with five to seven horsepower size categories for each equipment type;

C eight fuel markets, four regions (PADDs) each with two nonroad diesel fuel markets

(500 ppm and 15 ppm); and

C three application markets (construction, agriculture, and manufacturing). 
Final Regulatory Impact Analysis

10-30

p

Sd

qd qf Q

Domestic Supply

Sf SM

DM

+ = p p

Foreign Supply Market

a) Baseline Equilibrium

p

q′

d qf Q′

Domestic Supply

Sf

SM′

DM

+ = p p

Foreign Supply Market

b) With-Regulation Equilibrium

p′

Sd

qd q′

f Q

SM

p′ p′

S′

d

S′

f

Figure 10.2-1

Market Equilibrium without and with Regulation

10.2.2.2 Market Equilibrium in a Single Commodity Market

A graphical representation of a general economic competitive model of price formation, as

shown in Figure 10.2-1(a), posits that market prices and quantities are determined by the

intersection of the market supply and market demand curves. Under the baseline scenario, a

market price and quantity (p,Q) are determined by the intersection of the downward-sloping

market demand curve (DM) and the upward-sloping market supply curve (SM). The market

supply curve reflects the sum of the domestic (Sd) and import (Sf

) supply curves.

With the regulation, the costs of production increase for suppliers. The imposition of these

regulatory control costs is represented as an upward shift in the supply curve for domestic and
Economic Impact Analysis

CThis one-to-one relationship holds for engines sold on the market and for engines consumed

internally by integrated engine/equipment manufacturers. 

10-31

import supply, by the estimated compliance costs. As a result of the upward shift in the supply

curve, the market supply curve will also shift upward as shown in Figure 10.2-1(b) to reflect the

increased costs of production.

At baseline without regulation, the industry produces total output, Q, at price, p, with

domestic producers supplying the amount qd and imports accounting for Q minus qd, or qf

. With

the regulation, the market price increases from p to pN, and market output (as determined from

the market demand curve) declines from Q to QN. This reduction in market output is the net

result of reductions in domestic and import supply.

10.2.2.3 Incorporating Multimarket Interactions

The above description is typical of the expected market effects for a single product market

(e.g., diesel engine manufacturers) considered in isolation. However, the modeling problem for

this EIA is more complicated because of the need to investigate affected equipment

manufacturers and fuel producers as well as engine manufacturers. 

For example, the Tier 4 standards will affect equipment producers in two ways. First, these

producers are affected by higher input costs (increases in the price of diesel engines) associated

with the rule. Second, the standards will also impose additional production costs on equipment

producers associated with equipment changes necessary to accommodate changes in engine

design.

The demand for diesel engines is directly linked to the production of diesel equipment. A

single engine is typically used in each piece of equipment, and there are no substitutes (i.e., to

make diesel equipment one needs a diesel engine). For this reason, it is reasonable to assume

that the input-output relationship between the diesel engines and the equipment is strictly fixed

and that the demand for engines varies directly with the demand for equipment.C

The demand for diesel equipment is directly linked to the production of final goods and

services that use diesel equipment. For example, the demand for agricultural equipment depends

on the final demand for agricultural products and the total price of supplying these products. 

Thus, any change in the price of agricultural equipment will shift the agriculture supply curve,

leading to a decrease in agricultural production and hence decreased consumption of agricultural

equipment. Assuming a fixed input-output relationship, the percentage change in agricultural

production will equal the percentage change in agricultural equipment production. 

These relationships link the demand for engines and equipment directly to the level of

production of goods and services in the application markets. A demand curve specified in terms

of its downstream consumption is referred to as a derived demand curve. Figure 10.2-2

graphically illustrates how a derived demand curve is identified. Consider an event in the
Final Regulatory Impact Analysis

10-32

construction equipment market that causes the price of equipment to increase by )P (such as an

increase in the price of engines). This increase in the price of equipment will cause the supply

curve in the construction market to shift up, leading to a decreased quantity of construction

activity ()QC). The change in construction activity leads to a decrease in the demand for

construction equipment ()QE). The new point (QE – )QE, P – )P) traces out the derived demand

curve. Note that the supply and demand curves in the construction applications market are

needed to identify the derived demand in the construction equipment market. The construction

application market supply and demand curves are functional form and elasticity parameters

described in Appendix10F.
Economic Impact Analysis

10-33

Unit Price of

Construction

Construction

∆QC Output

∆P

S′

C

DC

SC

Price Equipment

Equipment

∆QE Output

Derived

Demand

SE

∆QE ∆QC

∆Price

Equipment

Upward Shift

Construction

Supply Curve

Figure 10.2-2

Derived Demand for Construction Equipment
Final Regulatory Impact Analysis

10-34

Each point on the derived demand curve equals the construction industry’s willingness to pay

for the corresponding marginal input. This is typically referred to as the input’s net value of

marginal product (VMP), which is equal to the price of the output (Px) times the input’s marginal

physical product (MPP). MPP is the incremental construction output attributable to a change in

equipment inputs: 

Value Marginal Product (VMP) = Px * MPP.

An increase in regulatory costs ©) associated with equipment will lower the VMP of all

inputs, leading to a decrease in the net marginal product:

Net Value Marginal Product = (Px – c) * MPP.

This decrease in the VMP of equipment, as price increases, is what leads the downward-sloping

derived demand curve in the equipment market.

Similarly, derived demand curves are developed for the engine markets that supply the

equipment markets. As shown in Figure 10.2-3, the increased price of engines resulting from

regulatory costs shifts the supply curve for engines and leads to a shift in the supply curve for

equipment. The resulting increased price of equipment leads to a shift in the supply curve for the

construction industry, decreasing construction output. The decrease in construction output flows

back through the equipment market, resulting in decreased demand for engines ()Qeng).
Economic Impact Analysis

10-35

Unit Price of

Construction

Q – Construction ∆QC

∆PE

S′

C

DC

SC

Price

Equipment

Q – Equipment ∆QE

Derived

Demand

S eng

∆QE = ∆Qeng

∆Peng

Price

Engines

Q – Engines ∆Q eng

Derived

Demand

Figure 10.2-3

Derived Demand for Engines
Final Regulatory Impact Analysis

10-36

10.2.3 Key Modeling Elements

In addition to specifying the type of model used and the relationships between the markets, it

is also necessary to specify several other key model characteristics. These characteristics

include the degree of competition in each market, the time horizon of the analysis, and how fixed

costs affect firms’ production decisions. The specification of the industry/market characteristics

and how regulatory costs are introduced into the model has an impact on the size and

interpretation of the estimated economic impacts. These modeling issues are discussed below.

10.2.3.1 Perfect vs. Imperfect Competition

For all markets that are modeled, the analyst must characterize the degree of competition

within each market. The discussion generally focuses on perfect competition (price-taking

behavior) versus imperfect competition (the lack of price-taking behavior). The central issue is

whether individual firms have sufficient market power to influence the market price. 

Under imperfect (such as monopolistic) competition, firms produce products that have

unique attributes that differentiate them from competitors’ products. This allows them to limit

supply, which in turn increases the market price, given the traditional downward-sloping demand

curve. Decreasing the quantity produced increases the monopolist’s profits but decreases total

social surplus because a less than optimal amount of the product is being consumed. In the

monopolistic equilibrium, the value society (consumers) places on the marginal product, the

market price, exceeds the marginal cost to society (producers) of producing the last unit. Thus,

social welfare is increased by inducing the monopolist to increase production.

Social cost estimates associated with a regulation are larger with monopolistic market

structures because the regulation exacerbates an already existing social inefficiency of too little

output from a social perspective. The Office of Management and Budget (OMB) explicitly

mentions the need to consider these market power-related welfare costs in evaluating regulations

under Executive Order 12866 (OMB, 1996).

However, as discussed in the industry profiles in Chapter 1, most of the diesel engine and

equipment markets have significant levels of domestic and international competition. Even in

markets where a few firms dominate the market, there is significant excess capacity enabling

competitors to quickly respond to changes in price. In addition, there are no indications of

barriers to entry, the firms in these markets are not price setters, and there is no evidence of high

levels of strategic behavior in the price and quantity decisions of the firms. Also, the products

produced within each market are somewhat homogeneous in that engines from one firm can be

purchased instead of engines from another firm. Finally, according to contestable market theory,

oligopolies and even monopolies will behave very much like firms in a competitive market if it

is possible to enter particular markets costlessly (i.e., there are no sunk costs associated with
Economic Impact Analysis

DA monopoly or firms in oligopoly may not behave as neo-classical economic theories of the

firm predict because they may be fearful of new entrants to the market. If super-normal profits

are earned potential competitors may enter the market, so it is argued that the existing firm(s)

will keep prices and output at a level where only normal profits are made, setting price and

output at or close to the competitive price and output. Baumol W J, Panzer J and Willig R D,

(1982); Baumol, 1982.

10-37

market entry or exit).D With regard to the nonroad engine market, production capacity is not

fully utilized. This means that manufacturers could potentially switch their product line to

compete in another segment of the market without a significant investment. For these reasons,

for the nonroad diesel rule analysis, it is assumed that within each modeled engine and

equipment market the commodities of interest are similar enough to be considered homogeneous

(e.g., perfectly substitutable) and that the number of buyers and sellers is large enough so that no

individual buyer or seller has market power or influence on market prices (i.e., perfect

competition). As a result of these conditions, producers and consumers take the market price as

given when making their production and consumption choices. The assumption of perfect

competition in this case is consistent with widely accepted economic practice for this type of

analysis (see for example EPA 2000, p. 126).

With regard to the fuel market, the Federal Trade Commission (FTC) has developed an

approach to ensure competitiveness in this sector. The FTC reviews oil company mergers and

frequently requires divestiture of refineries, terminals, and gas stations to maintain a minimum

level of competition. Therefore, it is reasonable to assume a competitive structure for this

market. At the same time, however, there are several ways in which refiners may pass along

their fuel compliance costs. This analysis explores three approaches. The primary modeling

scenario is the average cost scenario, according to which the change in market price is driven by

the average total (variable + fixed) regional cost of the regulation. The two other approaches are

modeled in a sensitivity analysis and reflect the case in which the highest-cost producer sets the

market price in a region. The first of these is the maximum variable cost scenario, according to

which the market price is drive by the maximum variable regional cost of the regulation. The

second is the maximum total (fixed + variable) regional cost of the regulation. The results of the

sensitivity analyses for these two fuel scenarios are contained in Appendix 10I.

10.2.3.2 Short- vs. Long-Run Models

In developing the multimarket partial equilibrium model, the choices available to producers

must be considered. For example, are producers able to increase their factors of production (e.g.,

increase production capacity) or alter their production mix (e.g., substitution between materials,

labor, and capital)? These modeling issues are largely dependent on the time horizon for which

the analysis is performed. Three benchmark time horizons are discussed below: the very short

run, the long run, and the intermediate run. This discussion relies in large part on the material

contained in the OAQPS Economic Analysis Resource Guide (U.S. EPA, 1999).
Final Regulatory Impact Analysis

E

The constancy of marginal costs reflects an underlying assumption of constant returns to scale

of production, which may or may not apply in all cases.

10-38

In the very short run, all factors of production are assumed to be fixed, leaving the directly

affected entity with no means to respond to increased costs associated with the regulation. 

Within a very short time horizon, regulated producers are constrained in their ability to adjust

inputs or outputs due to contractual, institutional, or other factors and can be represented by a

vertical supply curve as shown in Figure 10.2-4. In essence, this is equivalent to the

nonbehavioral model described earlier. Neither the price nor quantity change and the

manufacturer’s compliance costs become fixed or sunk costs. Under this time horizon, the

impacts of the regulation fall entirely on the regulated entity. Producers incur the entire

regulatory burden as a one-to-one reduction in their profit. This is referred to as the “full-cost

absorption” scenario and is equivalent to the engineering cost estimates. While there is no hard

and fast rule for determining what length of time constitutes the very short run, it is inappropriate

to use this time horizon for this analysis because it assumes economic entities have no flexibility

to adjust factors of production.

In the long run, all factors of production are variable, and producers can be expected to adjust

production plans in response to cost changes imposed by a regulation. Figure 10.2-5 illustrates a

typical, if somewhat simplified, long-run industry supply function. The function is horizontal,

indicating that the marginal and average costs of production are constant with respect to output.E

This horizontal slope reflects the fact that, under long-run constant returns to scale, technology

and input prices ultimately determine the market price, not the level of output in the market.
Economic Impact Analysis

10-39

Q

S

P

D

Price

Output

Figure 10.2-4

Full-Cost Absorption of Regulatory Costs

Unit Cost Increase } Price

Increase }

Q1 Q0

S1

: With Regulation

S0

: Without Regulation

P1

P0

D

c b

a

$

Output

d

Figure 10.2-5

Full-Cost Pass-Through of Regulatory Costs

Q1 Q0

P1

P0

c

b

a

$

Output

g

e

d

f

S1

: With Regulation

S0

: Without Regulation Price

Increase }

Unit Cost Increase }

Figure 10.2-6

Partial Cost Pass-Through of Regulatory Costs

Market demand is represented by the standard downward-sloping curve. The market is

assumed here to be perfectly competitive; equilibrium is determined by the intersection of the
Final Regulatory Impact Analysis

F

As a semantical matter, the situation where some factors are variable and some are fixed is often

referred to as the “short run” in economics, but the term “intermediate run” is used here to

avoid any confusion with the term “very short run.”

10-40

supply and demand curves. In this case, the upward parallel shift in the market supply curve

represents the regulation’s effect on production costs. The shift causes the market price to

increase by the full amount of the per-unit control cost (i.e., from P0 to P1). With the quantity

demanded sensitive to price, the increase in market price leads to a reduction in output in the

new with-regulation equilibrium (i.e., Q0 to Q1). As a result, consumers incur the entire

regulatory burden as represented by the loss in consumer surplus (i.e., the area P0 ac P1). In the

nomenclature of EIAs, this long-run scenario is typically referred to as “full-cost pass-through,”

and is illustrated in Figure 10.2-5.

Taken together, impacts modeled under the long-run/full-cost-pass-through scenario reveal

an important point: under fairly general economic conditions, a regulation’s impact on producers

is transitory. Ultimately, the costs are passed on to consumers in the form of higher prices. 

However, this does not mean that the impacts of a regulation will have no impact on producers

of goods and services affected by a regulation. For example, the long run may cover the time

taken to retire all of today’s capital vintage, which could take decades. Therefore, transitory

impacts could be protracted and could dominate long-run impacts in terms of present value. In

addition, to evaluate impacts on current producers, the long-run is approach is not appropriate. 

Consequently an time horizon that falls between the very short-run/full-cost-absorption case and

the long-run/full-cost-pass-through case is most appropriate for this EIA.

The intermediate run can best be defined by what it is not. It is not the very short run and it

is not the long run. In the intermediate run, some factors are fixed; some are variable.F The

existence of fixed production factors generally leads to diminishing returns to those fixed factors. 

This typically manifests itself in the form of a marginal cost (supply) function that rises with the

output rate, as shown in Figure 10.2-6.

Again, the regulation causes an upward shift in the supply function. The lack of resource

mobility may cause producers to suffer profit (producer surplus) losses in the face of regulation;

however, producers are able to pass through some of the associated costs to consumers, to the

extent the market will allow. As shown, in this case, the market-clearing process generates an

increase in price (from P0 to P1) that is less than the per-unit increase in costs (fb), so that the

regulatory burden is shared by producers (net reduction in profits) and consumers (rise in price). 

In other words there is a loss of both producer and consumer surplus.

10.2.3.3 Variable vs. Fixed Regulatory Costs 

Related to short-run versus long-run modeling issues is the question of how fixed and

variable cost increases affect market prices and quantities. The engineering estimates of fixed

R&D and capital costs and variable material and operating and maintenance (O&M) costs

provide an initial measure of total annual compliance costs without accounting for behavioral
Economic Impact Analysis

10-41

MC′

ATAC

ATAC ′

$/q

qm qm qM q/t ′

Pm

Pm′

MC

TVCC

q

TCC

q

c2 =

c1 =

(a) Upward-sloping supply function

Figure 10.2-7

Modeling Fixed Costs

responses. The starting point for assessing the market impacts of a regulatory action is to

incorporate the regulatory compliance costs into the production decision of the firm. 

In general, shifting the supply curve by the total cost per unit implies that both capital and

operating costs vary with output levels. At least in the case of capital, this raises some questions. 

In the long run, all inputs (and their costs) can be expected to vary with output. But a

short(er)-run analysis typically holds some capital factors fixed. For instance, to the extent that a

market supply function is tied to existing facilities, there is an element of fixed capital (or onetime R&D). As indicated above, the current market supply function might reflect these fixed

factors with an upward slope. As shown in Figure 10.2-7, the MC curve will only be affected, or

shift upwards, by the per-unit variable compliance costs, while the ATAC curve will shift up by

the per-unit total compliance costs (c2). Thus, the variable costs will directly affect the

production decision (optimal output rate), and the fixed costs will affect the closure decision by

establishing a new higher reservation price for the firm (i.e., Pm'). In other words, the fixed costs

are important in determining whether the firm will stay in this line of business (i.e., produce

anything at all), and the variable costs determine the level (quantity) of production.

In the EIA for this rule, it is assumed that only the variable cost influences the firm’s

production decision level and that the fixed costs are absorbed by the firm. Fixed costs

associated with the engine emission standards are not included in the market analysis, because in
Final Regulatory Impact Analysis

GThe fixed R&D costs capture the lost opportunity of forgone investments to the firm. 

10-42

an analysis of competitive markets the industry supply curve is based on its marginal cost curve,

and fixed costs are not reflected in changes in the marginal cost curve. In addition, fixed costs

are primarily R&D costs associated with design and engineering changes, and firms in the

affected industries currently allocate funds for these costs (see below). These costs are still a

cost to society because they displace other R&D activities that may improve the quality or

performance of engines and equipment. However, in this example, the fixed costs do not

influence the market price or quantity in the intermediate run. Therefore, fixed costs are not

likely to affect the prices of engines or equipment. 

R&D costs are a long-run concern, and decisions to invest or not invest in R&D are made in

the long run. If funds have to be diverted from some other activity into R&D needed to meet the

environmental regulations, then these costs represent a component of the social costs of the rule. 

Therefore, fixed R&D costs are included in the welfare impact estimates reported in Table 10.1-

4 as unavoidable costs that reduce producer surplus. In other words, engine manufacturers

budget for research and development programs and include these charges in their long-run

strategies. In the absence of new standards, these resources would be focused on design changes

to increase customer satisfaction. Engine manufacturers are expected to redirect these resources

toward compliance with the standards, instead of adding additional resources to research and

development programs. 

Operationally, the model used in this EIA shifts the diesel engines’ and equipment markets’

supply curves by the variable cost per unit only. The rule’s estimated fixed costs are calculated

to reflect their opportunity costs and then added to the producer surplus decrease after the new

market (with-regulation) equilibrium has been established.G The primary fixed costs in these

markets are associated with one-time expenditures to redesign products and retool production

lines to comply with the regulation. These fixed costs can be recovered as part of the industry’s

routine R&D budget and hence are not likely to lead to additional price increases. This

assumption is supported by information received from a number of nonroad engine and

equipment manufacturers, with whom EPA met to discuss redesign and equipment costs. The

manufacturers indicated that their redesign budgets (for emissions or other product changes) are

constrained by R&D budgets that are set annually as a percentage of annual revenues. While the

decision to redesign may be driven by anticipated future revenues for an individual piece of

equipment, the resources from with the redesign budget is allocated are determined from the

current year’s R&D budget. Thus, redesigns to meet emission standards represent a reallocation

of resources that would have been spent for other kinds of R&D (i.e., a lost opportunity cost). 

To account for the value to the company of this loss, the engineering cost analysis includes a 7

percent rate of return for all fixed costs“recovered” over a defined period for the emission

compliant products.

An alternative approach for R&D expenditures can be used, in which these costs are included

in intermediate-run decision-making. This alternative assumes that manufacturers will change
Economic Impact Analysis

10-43

their behavior based on the R&D required for compliance with the standards. A sensitivity

analysis in Appendix 10I reflects this approach.

Fixed costs on the refiner side are treated differently in the NDEIM. Unlike for engines and

equipment where the fixed costs are primarily for up-front R&D, most of the petroleum refinery

fixed costs are for production hardware. The decision to invest to increase, maintain, or decrease

production capacity may be made in response to anticipated or actual changes in price. To

reflect the different ways in which refiners can pass costs through to refiners, three scenarios

were run for the following supply shifts in the diesel fuel markets:

C shift by average total (variable + fixed cost)

C shift by max total (variable + fixed cost)

C shift by max variable cost. 

The first, shift by average total cost (variable + fixed), is the primary scenario and is included in

the NDEIM. The other two are investigated using sensitivity analyses. These supply shifts are

discussed further in sensitivity analysis presented in Appendix10I.

10.2.3.4 Substitution

In modeling the market impacts and social costs of this rule, the NDEIM considers only

diesel equipment and fuel inputs to the production of goods in the applications markets. It does

not explicitly model alternate production inputs that could serve as substitutes for new nonroad

equipment or nonroad diesel fuel. In the model, market changes in the final demand for

application goods and services directly correspond to changes in the demand for nonroad

equipment and fuel (i.e., in normalized terms there is a one-to-one correspondence between the

quantity of the final goods produced and the quantity of nonroad diesel equipment and fuel used

as inputs to that production). We believe modeling the market in this manner is economically

sound and reflects the general experience for the nonroad market.

Alternate means of production include pre-buying, delayed buying, extending the life of a

current machine, and substituting with different (e.g., gasoline-powered) equipment. For the

reasons described below, we conclude that revising the NDEIM to include these effects would be

inappropriate.

The term “pre-buying” refers to the possibility that the suppliers in the application market

could choose to buy additional unneeded quantities of nonroad equipment prior to the beginning

of the Tier 4 program and then use that equipment as an alternate means of production during the

time period of the Tier 4 program, thus avoiding the higher cost for the Tier 4 equipment. 

Although such pre-buying may be economically rational in some very limited situations, its use

as a substitute is severely limited. First, it should be clear that this form of pre-buying only

applies to equipment and not to nonroad diesel fuel. The high cost to storing any significant

quantity of nonroad diesel fuel prior to Tier 4 makes such pre-buying unlikely. For nonroad

equipment, the logic behind pre-buying is relatively straightforward and analogous to the

average consumer deciding to buy a new car at the end of the model year in the anticipation that

next year’s model will be more expensive. The critical difference is that the nonroad equipment
Final Regulatory Impact Analysis

10-44

is bought early and then held idle until it is needed as an input to production. The economic

viability of such strategic purchases are limited by the cost of idle capital and the cost for

maintaining unused equipment. In simple terms, if one assumed that the value of capital tied up

in an idle piece of equipment would have returned 7 percent in some other investment and the

cost of equipment were to go up by 7 percent, it would be economically rational to pre-buy

equipment up to one-year earlier than needed. If the equipment will not be needed as an input to

production in the next year, it would be more rational to invest the money elsewhere and then

purchase the equipment when it is actually needed. In real terms, the window for which prebuying can be a rational choice is even more limited due to the cost of maintaining, storing and

insuring equipment that is not being used. In practice then, such strategic purchases are limited

to a time period of a few months around the start of a new regulation. The NDEIM is intended to

model market reactions in the intermediate run time frame and thus models a period of time well

beyond the scope of the short time period during which any potential pre-buy might be rational. 

We therefore have not tried to include pre-buying as a means of substitution in NDEIM.

“Delayed-buying” refers to the possibility that producers in the application market would

defer purchasing new equipment initially but would eventually (after a delay period?) buy new

equipment. The economic rationality of such a delay is not clear (i.e., what cheaper substitute

might be used). However, since in the end it is assumed that the new more expensive equipment

is purchased, such a substitution method would appear to be inappropriate for an economic

model designed to model the intermediate run time frame.

In addition, there are many other factors besides a new regulatory program that may affect a

consumer’s decision to pre-buy or delay a purchase. Specifically, manufacturer short-term

pricing promotions or marketing strategies such as rebates, dealer incentives, and advertising can

change consumer behavior. These effects are not well captured in a general equilibrium model

such as the one used in the NDEIM, the goal of which is to estimate the rule’s impact on

equilibrium prices and quantities. Distinguishing these effects would require the use of a sales

function, which is beyond the scope of the NDEIM.

Extending the life of a current machine is suggested as another alternative to purchasing new

equipment. We believe this would also be a short term phenomenon that is not relevant for the

intermediate time frame of the NDEIM. Based on our meetings with equipment users and

suppliers, we do not believe that extending the life of nonroad equipment will prove to be an

economically rational substitute to the purchase of new equipment. Based on our understanding

of the nonroad equipment market, we believe that most users of nonroad equipment already do

this to the maximum extent possible. That is, we believe it is already economically rational to

extend the life of nonroad equipment as long as possible. It is our understanding that new

nonroad equipment is only bought when: 1) the existing equipment can no longer perform its

function; or 2) when new demand for production requires additional means for production; or 3)

when new equipment offers a cheaper means of production than existing equipment. The

changes in equipment due to the Tier 4 program will not substantially change these three primary

reasons for purchasing new equipment. Further, were we to discover that extending equipment

life is economically rational (i.e., if it were cheaper to extend equipment life rather than to buy

new equipment), this would lower the cost of nonroad equipment as an input to production and
Economic Impact Analysis

H “To date, there is no substitute for diesel power.” Associated General Contractors of America,

OAR-2003-0012-0791.

I

 Preamble Table VI.C-1 documents the lifetime operating costs (for fuel and oil only) for a 500

hp bulldozer as $77,850. If simplistically, we assumed that a gasoline engine would have a

30 percent higher operating cost (in practice it would likely be higher), the extra operating

cost for a gasoline engine would be in excess of $23,000 dwarfing any additional control cost

from the Tier 4 program.

10-45

thus would reduce the economic impact of the Tier 4 program compared to our estimate. For all

of the reasons stated here, we have decided not to attempt to model an extended equipment life

in the NDEIM.

Finally, stakeholders suggested that equipment users may choose to substitute with different

equipment or perhaps more generally different inputs to production. These could include the use

of gasoline powered equipment, or the use of additional labor (i.e., the use of a laborer and

shovel instead of a backhoe), or some other unknown substitute. We have specifically

considered the possibility of substitution to gasoline technology. Gasoline engines are an

alternative power source for equipment in the lowest power categories (i.e., below 75

horsepower). Above this size range there are very limited viable gasoline engine substitutes

today, and we do not believe that such substitutes will arise in the future. We should also note

that there are a number of benefits to diesel engines and some stakeholders have argued that

there are no acceptable substitutes for diesel powered equipment.H The fuel economy advantage

of diesel engines compared to gasoline engines dominates the overall operating costs for larger

equipment and makes the application of large gasoline engines to large nonroad equipment

economically infeasible.I

 For smaller nonroad equipment, where the fuel portion of operating

costs are not as important, gasoline and diesel engines are both provided today. The dominant

reasons for choosing diesel engines over the substantially cheaper gasoline engines include

better performance from diesel engines, lower fuel consumption from diesel engines, and the

ability to use diesel fuel. This latter reason is a significant advantage for two reasons: diesel fuel

is safer to store and dispense due to its lower volatility and, hence, greater resistance to

accidental ignition, and it is compatible with the fuel needed for larger equipment at the same

worksite. Thus, the costs for addressing safety issues with gasoline fuel storage and the costs for

storing two fuels onsite (gasoline for small engines and diesel for large) acts as a barrier to entry

to the market for gasoline powered equipment. Where such a barrier doesn’t exist, gasoline

engines already enjoy a substantial economic advantage over diesel. In cases where the more

expensive diesel powered equipment is currently used, an incremental increase in new

equipment cost is unlikely to provide the necessary economic incentives for switching to

gasoline based power systems. In short, we believe that users who can economically dispense

gasoline fuel already choose the substantially cheaper gasoline technology, while diesel users are

already choosing a more expensive technology due to reasons that will persist independent of

this rulemaking. The incremental equipment costs are not expected to be large enough to change

these market characteristics. Therefore, we have not attempted to model the possibility of

substitution to gasoline equipment in NDEIM. 
Final Regulatory Impact Analysis

10-46

10.2.4 Estimation of Social Costs

The economic welfare implications of the market price and output changes with the

regulation can be examined by calculating consumer and producer net “surplus” changes

associated with these adjustments. This is a measure of the negative impact of an environmental

policy change and is commonly referred to as the “social cost” of a regulation. It is important to

emphasize that this measure does not include the benefits that occur outside of the market, that

is, the value of the reduced levels of air pollution with the regulations. Including this benefit will

reduce the net cost of the regulation and even make it positive. 

The demand and supply curves that are used to project market price and quantity impacts can

be used to estimate the change in consumer, producer, and total surplus or social cost of the

regulation (see Figure 10.2-8).

The difference between the maximum price consumers are willing to pay for a good and the

price they actually pay is referred to as “consumer surplus.” Consumer surplus is measured as

the area under the demand curve and above the price of the product. Similarly, the difference

between the minimum price producers are willing to accept for a good and the price they actually

receive is referred to as “producer surplus.” Producer surplus is measured as the area above the

supply curve below the price of the product. These areas can be thought of as consumers’ net

benefits of consumption and producers’ net benefits of production, respectively.

In Figure 10.2-8, baseline equilibrium occurs at the intersection of the demand curve, D, and

supply curve, S. Price is Pl

 with quantity Ql. The increased cost of production with the

regulation will cause the market supply curve to shift upward to SN. The new equilibrium price

of the product is P2. With a higher price for the product there is less consumer welfare, all else

being unchanged. In Figure 10.2-8(a), area A represents the dollar value of the annual net loss

in consumers’ welfare associated with the increased price. The rectangular portion represents

the loss in consumer surplus on the quantity still consumed due to the price increase, Q2, while

the triangular area represents the foregone surplus resulting from the reduced quantity consumed,

Ql

 – Q2. 

In addition to the changes in consumers’ welfare, there are also changes in producers’

welfare with the regulatory action. With the increase in market price, producers receive higher

revenues on the quantity still purchased, Q2. In Figure 10.2-8(b), area B represents the increase

in revenues due to this increase in price. The difference in the area under the supply curve up to

the original market price, area C, measures the loss in producer surplus, which includes the loss

associated with the quantity no longer produced. The net change in producers’ welfare is

represented by area B – C.
Economic Impact Analysis

J

However, it is important to emphasize that this measure does not include the benefits that occur

outside the market, that is, the value of the reduced levels of air pollution with the regulations. 

Including this benefit may reduce the net cost of the regulation or even make it positive.

10-47

The change in economic welfare attributable to the compliance costs of the regulations is the

sum of consumer and producer surplus changes, that is, – (A) + (B–C). Figure 10.2-8©) shows

the net (negative) change in economic welfare associated with the regulation as area D.J

 
Final Regulatory Impact Analysis

10-48

P1

P2

Q2 Q1

S

S′

D

Q/t

$/Q

(a) Change in Consumer Surplus with

Regulation

P1

P2

Q2 Q1

S

S′

D

Q/t

$/Q

(b) Change in Producer Surplus with

Regulation

P1

P2

Q2 Q1

S

S′

D

Q/t

$/Q

(c) Net Change in Economic Welfare with

Regulation

A

B

C

D

Figure 10.2-8

Market Surplus Changes with Regulation: Consumer and Producer Surplus
Economic Impact Analysis

10-49

If not all the costs of the regulation are reflected in the supply shift, then the producer and

consumer surplus changes reflected in Figure 10.2-5 will not capture the total social costs of the

regulation. As discussed earlier, fixed R&D and capital costs are not included in the supply

curve shift for the engine and equipment markets. The fixed costs in these instances are assumed

to be borne totally by the producers in that none of these costs are passed on to consumers in the

form of higher prices. The costs are added to the producer surplus estimates generated from the

market analysis so that the accounting accurately reflects the total social cost of the regulation. 

Operating savings are included in the total social cost estimates but not integrated into the

market analysis. Operating savings are changes in operating costs are expected to be realized by

diesel equipment users, for both existing and new equipment, as a result of the reduced sulfur

content of nonroad diesel fuel. These include operating savings (cost reductions) due to fewer

oil changes, which accrue to nonroad engines that are already in use as well as those that will

comply with new emission standards. These savings (costs) also include any extra operating

costs associated with the new PM emission control technology that may accrue to new engines

that use this new technology. Operating savings are not included in the market analysis because

some of the savings accrue to existing engines and because these savings are not expected to

affect consumer decisions with respect to new engines (see Chapter 6). Operating savings are

included in the social cost analysis, however, because they accrue to society. They are added

into the estimated social costs as an additional savings to the application and transportation

service markets, since it is the users of these engines and fuels that will see these savings. A

sensitivity analysis was performed in which operating savings are included as inputs to the

NDEIM market. The results of this analysis are presented in Appendix 10I.

10.3 NDEIM Model Inputs and Solution Algorithm

The NDEIM is a computer model comprising a series of spreadsheet modules. The model

equations, presented in Appendix F to this chapter, are based on the economic relationships

described in Section 10.2. The NDEIM analysis consists of four steps:

C Define the baseline characteristics of the supply and demand of affected commodities and

specify the intermarket relationships.

C Introduce a policy “shock” into the model based on estimated compliance costs that shift

the supply functions.

C Use a solution algorithm to estimate a new, with-regulation equilibrium price and

quantity for all markets.

C Estimate the change in producer and consumer surplus in all markets included in the

model.

This section describes the data inputs used to construct the model, the compliance costs used

to shock it, and the algorithm used to solve it. The model results are presented in Appendices A

through E.
Final Regulatory Impact Analysis

10-50

10.3.1 Description of Product Markets

There are 60 integrated engine, equipment, fuel, transportation service, and application

product markets included in the NDEIM.

10.3.1.1 Engine Markets

The engine markets are the markets associated with the production and consumption of

engines. The producers in these markets are the engine manufacturers; the consumers are

companies that make the nonroad equipment that use these engines. Seven engine markets are

modeled, segmented by engine size (in horsepower). 

 

C less than 25 hp

C 26 to 50 hp

C 51 to 75 hp

C 76 to 100 hp

C 101 to 175 hp

C 176 to 600 hp

C greater than 601 hp 

The number of horsepower categories included in the NDEIM is larger than the number of

nonroad engine standard horsepower categories. This allows more efficient use of the engine

compliance cost estimates developed for this proposal. It also allows a more refined examination

of economic impacts on equipment types.

The NDEIM distinguishes between “merchant” engines and “captive” engines. “Merchant”

engines are produced for sale to another company and are sold on the open market to anyone

who wants to buy them. “Captive” engines are produced by a manufacturer for use in its own

nonroad equipment line (this equipment is said to be produced by “integrated” manufacturers). 

It is important to differentiate between merchant and captive engines because compliance costs

affect them differently. All compliance costs for captive engines are absorbed into the

equipment costs of integrated suppliers. In contrast, nonintegrated equipment suppliers who buy

merchant engines pay only a portion of the engine compliance costs. As long as engine demand

is not perfectly inelastic, the increased market price for merchant engines will reflect only a

partial pass through of engine compliance costs. The rest of the compliance costs will be borne

by the engine manufacturer.

10.3.1.2 Equipment Markets 

The equipment markets are the markets associated with the production and consumption of

equipment that use nonroad diesel engines. The producers in these markets are the equipment

manufacturers; the consumers are companies that use this equipment to make goods sold in the

application markets. Seven equipment markets are modeled:

C Construction
Economic Impact Analysis

KThere are seven horsepower/application categories that do not have sales in 2000 and are not

included in the model. These are: agricultural equipment >600 hp; gensets & welders > 600

hp; refrigeration & A/C > 71 hp (4 hp categories); and lawn & garden >600 hp. Therefore,

the total number of diesel equipment markets is 42 rather than 49.

10-51

C Agricultural

C Pumps and compressors

C Generators and welder sets

C Refrigeration and air conditioning 

C General industrial, and

C Lawn and garden.

Each of the 60 applications listed in the Power Systems Research OELink Sales Version

2002 (PSR) database were allocated to one of these categories to obtain a manageable number of

equipment markets to be included in the NDEIM (Gallaher, 2003). The mapping is contained in

Table 10.3-1. For each of these equipment types, up to seven horsepower size category markets

are included in the model, for a total of 42 individual equipment markets.K
Final Regulatory Impact Analysis

10-52

Table 10.3-1

Mapping from PSR Equipment Categories to Equipment Markets

Application Markets Equip Markets Equipment Types

AGRICULTURE AGRICULTURAL EQUIP 2-WHEEL TRACTORS

AG TRACTORS

BALERS

COMBINES

IRRIGATION SETS

OTHER AG EQUIPMENT

SPRAYERS

WINDROWERS

CONSTRUCTION CONSTRUCTION AERIAL LIFTS

BORE/DRILL RIGS

CRANES

CRAWLERS

EXCAVATORS

FINISHING EQUIPMENT

FOREST EQUIPMENT

GRADERS

LT PLANTS/SIGNAL BDS

MIXERS

OFF-HWY TRACTORS

OFF-HWY TRUCKS

OTHER CONSTRUCTION

PAVERS

PLATE COMPACTORS

ROLLERS

S/S LOADERS

SCRAPERS

TAMPERS/RAMMERS

TRACTR/LOADR/BCKHOES

TRENCHERS

WHEEL LOADERS/DOZERS

MANUFACTURING GENERAL INDUSTRIAL AIRCRFT SUPPRT EQUIP

CHIPPERS/GRINDERS

CONCRETE/IND SAWS

CRUSH/PROC EQUIP

DUMPERS/TENDERS

FORKLIFTS

OIL FIELD EQUIPMENT

OTH MATERIAL HANDLNG

OTHER GEN INDUSTRIAL

RAILWAY MAINTENANCE

ROUGH TRN FORKLFTS

SCRUBBERS/SWEEPERS

SPEC VEHICLES/CARTS

SURFACING EQUIP

TERMINAL TRACTORS

UTILITY VEHICLES

GENERATOR SETS & WELDERS GENERATOR SETS
Economic Impact Analysis

Application Markets Equip Markets Equipment Types

10-53

WELDERS

LAWN & GARDEN COMMERCIAL MOWERS

COMMERCIAL TURF

LEAF BLOWERS/VACS

LN/GDN TRACTORS

OTHER LAWN&GARDEN

TRIMMER/EDGER/CTTERS

PUMPS & COMPRESSORS AIR COMPRESSORS

GAS COMPRESSORS

HYD POWER UNITS

PRESSURE WASHERS

PUMPS

REFRIGERATION/AC REFRIGERATION/AC

Source: Gallaher (2003).

For the purpose of this analysis, nonroad diesel equipment is assumed to be a fixed factor of

production in the application markets. Applying this assumption, a 1 percent decrease in

agricultural output will lead to a 1 percent decrease in the demand for agricultural equipment

(and fuel). The relationship between the percentage increase in equipment price and the

percentage change in equipment demand (the elasticity of demand) is determined by the input

share of diesel equipment relative to other inputs in the application markets and the supply and

demand elasticities in the application markets.

10.3.1.3 Application Markets 

The application markets are the markets associated with the production and consumption of

goods that use the affected diesel engines, equipment, and fuel. The producers in these markets

include farmers, ranchers, construction firms, industrial firms, and mines; consumers include

other companies and households. Three application markets are modeled:

C Construction

C Agricultural

C Manufacturing

These three application markets created after considering various economic activity

classification schemes, including the NAICS and SIC (Revelt, 2004; Gallaher, 2003). These

three markets are included as separate groupings in each of those economic activity classification

schemes. They are also the most significant categories of activities for which diesel engines,

equipment, and fuel are most likely to be used, as suggested in the PSR data on which the

equipment markets were chosen. Finally, they are a manageable number of markets to use in the

NDEIM. Each of the 7 equipment markets listed above were allocated to one of these

categories. The mapping is contained in Table 10.3-2.
Final Regulatory Impact Analysis

10-54

Table 10.3-2

Mapping from Equipment Markets to Application Markets

Application Market Equipment Market

Agricultural Agricultural equipment

Construction Construction equipment

Manufacturing Pumps and compressors

Gen sets and welding equipment

Refrigeration

Lawn and garden

General industrial

One of the consequences of reducing economic activities that use diesel engines, equipment,

and fuel into such a small number of application market categories is that seemingly unrelated

activities are linked to aggregate trends and market responses. So, for example, if 

manufacturing application market production decreases by one percent, the demand for lawn and

garden equipment, gen sets and welders, and forklifts will all decrease by the same one percent

because they are all linked to the same application market. Similarly, forest equipment and

signal boards are grouped with cranes and bulldozers in the construction application market. In

addition, gen sets used in agricultural activities are considered to be used in the manufacturing

application market. Unfortunately, this is a problem whenever a large number of different kinds

of products or activities are reduced to a small number of categories. At the same time, most of

the activity covered by each of the three categories, and thus most of the engines and equipment

that are included in them, is directly related to the application category.

Analysis of the impacts on the three application markets is limited to market level changes. 

The results are reported in terms of average percent change for prices and quantities of goods

sold in each of the three application markets. Changes in producer and consumer surplus at the

market level are also reported. The economic impacts on suppliers or consumers in particular

markets (e.g., farm production units or manufacturing or construction firms, or households and

companies that consume agricultural goods, buildings, or durable or consumer goods) are not

estimated.

10.3.1.4 Diesel Fuel Markets

The diesel fuel markets are the markets associated with the production and consumption of

nonroad diesel fuel. Eight nonroad diesel fuel markets were modeled: two distinct nonroad

diesel fuel commodities in four regional markets. The two fuels are:

C 500 ppm nonroad diesel fuel

C 15 ppm nonroad diesel fuel
Economic Impact Analysis

10-55

The Department of Energy defines five Petroleum Administrative Districts for Defense

(PADDs). For the purpose of this EIA, two of these PADDs are combined, giving four regional

district fuel markets. These are:

C PADD 1 and 3

C PADD 2 

C PADD 4 

C PADD 5 (includes Alaska and Hawaii; California fuel volumes that are not affected by

the program because they are covered by separate California nonroad diesel fuel

standards are not included in the analysis)

PADD 1 and PADD 3 are combined because of the high level of interregional trade. 

Regional imports and exports across the remaining four regions included in the model are not

included in the analysis. 

Separate compliance costs are estimated for each 500 ppm and 15 ppm regional fuel market. 

As a result, the price and quantify impacts, as well as the changes in producer surplus, vary

across the eight fuel markets. 

As discussed in Section 10.2, the NDEIM is based on the assumption of perfect competition. 

Using this assumption, estimated social costs are obtained by using average per-unit variable

compliance costs to shift the market supply curve (see Section 10.2.3.3). In the fuel market case,

however, each regional supply curve is shifted by the average total (variable + fixed) regional

cost of the regulation. This approach is used for the fuel market because, unlike for engines and

equipment where the fixed costs are primarily for up-front R&D, most of the petroleum refinery

fixed costs are for production hardware. This fuel market scenario (referred to as average total

cost) is used when presenting disaggregated market results in Appendices 10.A through 10.D

and sensitivity analysis results in Appendix 10I. 

However, in some fuel regions, it may be more appropriate to let the “high cost” refinery’s

compliance cost drive the new market price. If refiners' investment in desulfurization capacity is

very close to that needed to satisfy demand for 15 ppm NRLM fuel, then refiners may have to

often operate their equipment at a capacity beyond that which minimizes cost. For example, the

temperature in the reactor can be increased, allowing greater fuel throughput. However, this

speeds up catalyst deactiviation and shortens catalyst life. This effectively increases the

operating cost per gallon of producing 15 ppm fuel. The long-term solution is for refiners not

producing 15 ppm fuel to invest in desulfurization capacity. However, according to EPA's cost

methodology, this incremental fuel would have a higher desulfurization cost than that

experienced by those who have already invested. In order to justify this new 15 ppm fuel

capacity, refiners have to anticipate not only covering their operating costs, but their capital costs

as well. For this to occur, they would have to anticipates prices being at or above those of the

"high cost" refineries as estimated here. Under this assumption it is the high cost producer’s

dollars per gallon compliance cost increase that determines the new price. This is referred to as

the max cost scenario and no longer reflects perfect competition because now individual firms

have direct influence on market price. Two max cost scenarios are explored in the sensitivity
Final Regulatory Impact Analysis

10-56

analysis presented in Appendix 10I: one in which the high-cost refinery’s total (variable + fixed)

compliance costs determine price, and a second in which only the high-cost refinery’s variable

compliance costs determine price.

10.3.1.5 Locomotive and Marine Transportation Markets

The locomotive and marine sectors are affected by this rule through the limits on the sulfur

content of fuel. These sectors provide inputs to a variety of end-use sectors in the form of

transportation services. In this sense, their role is similar to other markets for intermediate goods

already included in the NDEIM. For example, the equipment markets in the NDEIM are markets

for intermediate goods that provide diesel-powered equipment to agriculture, construction, and

manufacturing application markets. Using this analogy, locomotive and marine sectors are

included in the NDEIM as two intermediate markets (see Figure 10.1-1). The intermediate

goods/services in this context are the rail and water transportation services provided to end-use

markets.

The U.S. Bureau of Economic Analysis (BEA) Industry Economic Program produces the

input-output tables, which show how industries interact to provide input to, and take output

from, each other. The data set can provide an appropriate measure transportation services

purchased by the application markets included in NDEIM. The BEA data show that

approximately 54 percent of rail and water transportation expenditures are made by the three

application markets in the NDEIM (see Table 10.3-3). The remaining expenditures for these

services are associated with explicitly modeled sectors not included in the model (e.g. electric

utilities (transporting coal to electric power plants), nonmanufacturing service industries (public

transportation), and governments). Costs flowing into these “other” sectors are included as a line

item in the economic impact estimates but do not lead to changes in market prices or quantities.

Table 10.3-3

Distribution of Rail and Water Costs to Deliver Commodities by Industry: 1997

Application Market

Share of Rail Transportation

Expenditures

Share of Water Transportation

Expenditures

Agriculture 3.5% 2.5%

Construction 4.3% 8.3%

Manufacturing 45.9% 42.7%

Other 46.2% 45.5%

Source: U.S. Bureau of Economic Analysis (BEA). 1997 Benchmark I-O Supplementary Make, Use, and Direct

Requirements Tables at the Detailed Level. Table 4. http://www.bea.gov/bea/dn2/i-o_benchmark.htm. Last

updated November 24, 2003.

Locomotive and fuel costs were added only to the three application markets, even though

equipment and engine manufacturers also use these services. This is a simplifying assumption
Economic Impact Analysis

10-57

and, is not expected to have an impact on the results of the market or social cost analysis because

the share of these costs in total engine and equipment production is very small.

10.3.2 Market Linkages

In the national economy, the markets described above are connected in that changes in

demand in one market will affect the supply of goods in a related market. For example, nonroad

equipment manufacturers consume engines in their production processes in the sense that each

piece of nonroad equipment has a nonroad engine. This equipment is then supplied to

application market producers through the application markets. A decrease in the demand for

equipment in the application market will lead to a decrease in the quantity of equipment

produced, which will in turn lead to a decrease in the quantity of engines produced. Similarly,

the fuel markets are also linked to the application markets, with the demand for No. 2 distillate

being specified as a function of the production and consumption decisions made in the

construction, agricultural, and manufacturer application markets. In the NDEIM, increased

equipment costs decrease the demand for fuel, and increased fuel costs decrease the demand for

equipment because both increase the costs of production in the application markets. This in turn

leads to a decrease in production in the application markets and hence a decrease in the demand

for inputs (fuel and equipment).

The linkages between the markets are illustrated in Figure 10.1-1. These interaction effects

are accounted for by designing the model to derive the engine, equipment, transportation, and

fuel market demand elasticities. The derived demand aspect of the model simulates connections

between supply and demand among all the product markets and replicates the economic

interactions between producers and consumers. Detailed specifications of the market model

equations (supply and demand functions, equilibrium conditions) are provided in Appendix 10F. 

10.3.3 Baseline Economic Data

This section describes the data used to define the baseline conditions in the model. These

include baseline quantities and prices for the engines, equipment and fuel affected by the rule

and for the transportation service sectors and application markets that use these engines,

equipment, and fuel. 

10.3.3.1 Baseline Quantities: Engines, Equipment and Fuel

Engines and Equipment: The NDEIM uses the same engine sales that are used in the engine

and equipment cost analysis presented in Chapter 6. The engine sales are based on the Power

Systems Research OELink Sales Version 2002 database, adjusted to eliminate stationary

equipment and to maintain consistency with the 1998 Nonroad inventory model (see Chapter 8,

Table 8.1-1 and related text). Sales data are used as a proxy for production data in the NDEIM

because detailed production data by horsepower and equipment application are not available

(modeling inventory decisions of engine and equipment manufacturers is beyond the scope of the

NDEIM). The sales distribution by size and application is the same for equipment as for engines

due to the assumption of a one-to-one relationship between engines and equipment. Engines and
Final Regulatory Impact Analysis

10-58

equipment are allocated to equipment type categories according to the PSR database

categorization scheme (see Section 10.3.1.2 and Table 10.3-1, above). Table 10.3-4 lists sales

data for affected diesel nonroad engines and equipment sold in the United States in 2000 by

engine horsepower and equipment category.
10-59

Table 10.3-4

Engine/Equipment Sales in 2000

Engine Market

Agricultural

Equipment Construction 

General

Industrial

Generator

Sets and

Welders

Lawn and

Garden

Pumps and

Compressors

Refrigera

Air Cond

0<hp<25 13,195 17,043 3,173 54,971 17,118 4,980 8,677 

25#hp<50 38,303 30,233 6,933 32,540 10,323 4,254 10,39

50#hp<75 19,156 30,919 7,074 13,234 1,456 3,930 18,14

75#hp<100 11,788 30,146 14,204 5,567 2,722 4,238 

100#hp<175 35,226 49,503 17,757 7,313 1,556 985 

175#hp<600 41,678 42,126 8,327 1,813 509 1,494 — 

hp > 600 hp — 4,945 576 — — 16 — 

Grand Total 159,347 204,915 58,044 115,440 33,684 19,898 37,21

Source: Power Systems Research, OELink Sales Version, 2002.; see also Chapter 8, Table 8.1-1 and related text.
Final Regulatory Impact Analysis

L

 Petroleum Administrative Districts for Defense.

10-60

Fuel: Baseline nonroad, locomotive, and marine diesel fuel consumption is provided in

Table 10.3-5. Fuel consumption is broken out by region (PADD) and application market

(construction, agriculture, and manufacturing).

The fuel volumes used in NDEIM were developed from the information contained in Section

7.1 of Chapter 7 of the RIA. Only a brief summary of the methodology used to develop these

volumes is contained here so the reader is directed to Chapter 7 of the RIA for a complete

discussion. Demand volumes are first estimated for nonroad, locomotive and marine diesel fuel

for 2001 for each PADDL

 and then grown to 2014. The analysis of varying regulatory scenarios

always occurs using the 2014 estimated volumes. The three regulatory scenarios associated with

the final rule are: 

• NRLM meeting a 500 ppm sulfur standard in 2007 to 2010 exempting small refiners

• NR meeting a 15 ppm sulfur standard and LM meeting a 50 ppm sulfur standard in 2010

to 2012 exempting small refiners

• NRLM meeting a 15 ppm sulfur standard in 2010 to 2014 exempting some small refiners

and allowing downgrade to meet demand except in PADD 1

• NRLM meeting a 15 ppm sulfur standard in 2014 which is fully phased in. The

downgrade can be used in locomotive and marine diesel fuel except in PADD 1 

The volume of pipeline downgrade and highway diesel fuel spillover are estimated and

apportioned to nonroad, locomotive and marine diesel fuel depending on the distribution system

constraints identified for each PADD and consistent with each regulatory scenario. After the

downgrade and spillover are accounted for, the residual demands in each PADD are met by onpurpose production of low sulfur fuel. 

The summary tables of 2014 volumes for each regulatory scenario are contained in Chapter

7. The volumes are summarized in Table 7.1.4-10 for the period from 2007 to 2010, Table 7.1.4-

11 for the period from 2010 to 2012, Table 7.1.4-12 for the period from 2012 to 2014, and Table

7.1.4-13 for the period 2014 and thereafter.

The 2014 volumes are adjusted to estimated the volumes in each year from 2007 to 2040

using growth ratios compared to 2014 based on the growth rate factors in Tables 7.1.5-1 and

7.1.5-2. Each substream (i.e., spillover, downgrade, low sulfur fuel) within each fuel category is

adjusted using the same growth factor. 

The results of the volumes analysis are shown in Table 10.3-5. In the first column, the

nonroad, locomotive and marine diesel fuel volume which must be desulfurized are summarized. 
Economic Impact Analysis

10-61

The downgrade and spillover are aggregated together and shown in another column. Then a total

is presented which represents the total of the two columns. The volumes are shown for PADDs

1 and 3 together, PADD 2, PADD 4 and PADD 5 without California, as well as a national total

without California.
Year

Nonroad, 

Locomotiv

e, Marine

Highway 

Sulfur, 

Downgrad

e and 

Spillover Total

Nonroad, 

Locomotiv

e, Marine

Highway 

Sulfur, 

Downgrad

e and 

Spillover Total

Nonroad, 

Locomotiv

e, Marine

Highway 

Sulfur, 

Downgrad

e and 

Spillover Total

Nonroad, 

Locomotiv

e, Marine

Highway 

Sulfur, 

Downgrad

e and 

Spillover Total

Nonro

Locom

e, Ma

2007 3,771 4,169 7,940 2,573 3,617 6,189 217 695 912 223 785 1,007 6,7

 

2008 6,592 1,503 8,095 4,503 1,817 6,319 380 551 931 390 639 1,029 11,8

 

2009 6,720 1,532 8,252 4,597 1,855 6,452 387 563 950 398 652 1,050 12,

 

2010 7,008 1,405 8,412 4,392 2,195 6,587 337 633 970 420 652 1,072 12,

 

2011 7,282 1,300 8,582 4,277 2,450 6,727 303 687 991 439 655 1,095 12,3

 

2012 7,414 1,323 8,737 4,359 2,498 6,857 309 700 1,010 448 669 1,116 12,5

 

2013 7,540 1,343 8,883 4,440 2,544 6,984 315 713 1,028 455 682 1,137 12,7

 

2014 7,669 1,365 9,034 4,521 2,591 7,111 321 725 1,046 553 605 1,158 13,0

 

2015 7,801 1,384 9,185 4,609 2,631 7,240 327 737 1,065 629 550 1,179 13,3

 

2016 7,932 1,403 9,336 4,696 2,673 7,369 334 749 1,083 641 560 1,200 13,6

 

2017 8,064 1,423 9,487 4,783 2,714 7,497 340 762 1,102 652 569 1,222 13,8

 

2018 8,200 1,442 9,643 4,871 2,753 7,625 347 773 1,120 664 579 1,243 14,0

 

2019 8,342 1,464 9,806 4,960 2,796 7,756 353 785 1,139 677 588 1,265 14,3

 

2020 8,545 1,411 9,956 4,934 2,948 7,882 353 804 1,157 688 598 1,286 14,5

 

2021 8,729 1,375 10,104 4,937 3,069 8,006 354 821 1,174 700 607 1,307 14,7

 

2022 8,872 1,395 10,266 5,022 3,114 8,137 360 833 1,193 712 616 1,329 14,9

 

2023 9,007 1,413 10,420 5,107 3,159 8,265 366 845 1,211 724 626 1,350 15,2

 

2024 9,145 1,432 10,577 5,191 3,204 8,395 372 857 1,230 736 636 1,371 15,4

 

2025 9,282 1,451 10,733 5,276 3,249 8,525 379 870 1,249 748 645 1,393 15,6

 

2026 9,420 1,469 10,889 5,360 3,294 8,653 385 882 1,267 759 655 1,414 15,9

 

2027 9,558 1,488 11,046 5,444 3,338 8,782 391 894 1,285 771 664 1,436 16,

 

2028 9,696 1,506 11,203 5,528 3,382 8,910 397 907 1,304 783 674 1,457 16,4

 

2029 9,835 1,525 11,360 5,612 3,427 9,039 403 919 1,322 795 684 1,478 16,6

 

2030 9,974 1,544 11,518 5,697 3,472 9,168 410 931 1,341 807 693 1,500 16,8

 

2031 10,113 1,563 11,676 5,781 3,516 9,297 416 943 1,359 819 703 1,521 17,

 

2032 10,253 1,582 11,835 5,865 3,561 9,427 422 956 1,377 831 712 1,543 17,3

 

2033 10,393 1,601 11,994 5,950 3,606 9,556 428 968 1,396 843 722 1,565 17,6

 

2034 10,534 1,620 12,154 6,034 3,651 9,686 434 980 1,414 855 732 1,586 17,8

 

2035 10,675 1,639 12,314 6,119 3,696 9,815 441 992 1,433 867 741 1,608 18,

 

2036 10,816 1,659 12,475 6,204 3,742 9,945 447 1,005 1,452 879 751 1,630 18,3

 

PADD I&III PADD II PADD IV PADD V 

Table 10.3-5

Nonroad, Locomotive and Marine Diesel Fuel Consumption, 2007-2036 (million gallons)
Economic Impact Analysis

MIt should be noted that the equipment prices used in this analysis reflect current conditions and

do not reflect any future price increases associated with EPA’s nonroad Tier 3 standards.

10-63

10.3.3.2 Baseline Prices: Engines, Equipment and Fuel

Engines and Equipment: The baseline engine prices used in the NDEIM are the same as

those contained in Table 6.2-5 in Chapter 6, above, sales weighting those values where

appropriate. Table 10.3-6 provides the prices for the seven engine categories used in the model. 

The baseline equipment prices used in the NDEIM are contained in Table 10.3-7.M These were

estimated by EPA using price data for the seven categories of equipment were complied from a

variety of sources, including the U.S. General Services Administration and various websites. A

relationship between price and horsepower was obtained using a linear interpolation method. 

The price estimates for the equipment were obtained using the sales weighted horsepower value

for each power category and the corresponding linear equation (Guerra, 2004).

Table 10.3-6

Baseline Engine Prices

Power Range Estimated Price

0<hp<25 $1,500

25#hp<50 $2,900

50#hp<75 $3,000

75#hp<100 $4,000

100#hp<175 $5,500

175#hp<600 $20,000

hp > 600 hp $80,500

Source: See also Chapter 6, Table 6.2-5.
Final Regulatory Impact Analysis

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Table 10.3-7

Baseline Prices of Nonroad Diesel Equipmenta

Application <25 hp 26-50 hp 51-75 hp 76-100 hp 101-175 hp 176-600 hp >600 hp

 Agricultural Equip $6,900 $14,400 $22,600 $33,400 $69,100 $143,700 N/A

 Construction Equip $18,000 $29,700 $31,600 $57,900 $122,700 $312,900 $847,400 

 Pumps & Compressors $6,000 $12,200 $10,600 $12,500 $23,800 $53,000 $88,000

 GenSets & Welders $6,800 $8,700 $8,300 $18,000 $21,400 $35,700 N/A

 Refrigeration & A/C $12,500 $27,000 $42,100 N/A N/A N/A N/A

 General Industrial $17,300 $42,300 $56,400 $74,300 $116,900 $154,200 $345,700

 Lawn & Garden $9,300 $21,500 $33,100 $38,500 $29,900 $64,300 N/A

Source: Guerra, 2004.

a

 These equipment prices reflect current conditions and do not reflect any future price increases associated with

EPA’s nonroad Tier 3 standards.

Fuel Prices: The baseline fuel prices used in the NDEIM are the 2002 market prices for each

PADD obtained from the U.S. Energy Information Administration’s Petroleum Market Monthly. 

These prices are reported in Table 10.3-8 and are based on the average sales to end-users for

high-sulfur diesel fuel.

Table 10.3-8

Average Market Prices for Diesel Fuela: 2002

Market Price ($/gallon)

PADD I&III $0.91

PADD II $0.94

PADD IV $0.91

PADD V $0.87

a

High-Sulfur Diesel Fuel observation for December 2002.

Source: U.S. Energy Information Administration. 2004. Petroleum Marketing Monthly March 2004. Table 41. 

10.3.3.3 Baseline Quantities and Prices for Transportation and Application Markets

For the three application markets, the NDEIM uses the values of production data reported by

the U.S. Bureau of the Census and the U.S. Department of Agriculture. The Economic Census

provides official measures of output for industries and geographic areas. It is the best publicly

available data that measures market supply for the broadly defined application markets in the

NDEIM, because its industrial classification system provides aggregate statistics for agriculture,

constructing, and manufacturing. Trade data for agriculture and manufacturing is reported by
Economic Impact Analysis

NInternational trade in construction is not significant.

10-65

the USDA and U.S. International Trade Commission (USITC)N. The NDEIM uses normalized

commodities (e.g. price is one and value equals quantity) because of the great heterogeneity of

products within each application market. To estimate production for future years, we applied

average equipment growth rates to the value of output reported in Table 10.3-9 (see discussion of

growth rates in Section 10.3.6).

Table 10.3-9

Baseline Data for NDEIM’s Application Markets: 2000

Application Market Value ($109

)

Agriculture Domestic Production: $ 219

Imports: $ 39 

Construction Domestic Production: $ 820

Manufacturing Domestic Production: $ 4,209

Imports: $ 1,074 

Sources: U.S. Department of Agriculture, National Agricultural Statistics Service (USDA-NASS). 2002. 

Agricultural Statistics 2002. Washington, DC: U.S. Department of Agriculture. Table 9-39 and Table 15-1. U.S.

Census Bureau. 2003b. Value of Construction Put In Place: December 2002. C30/02-12. Washington, DC: U.S.

Census Bureau. Table 1. U.S. Census Bureau. 2003a. Annual Survey of Manufactures. 2001 Statistics for

Industry Groups and Industries. M01(AS)-1. Washington, DC: U.S. Census Bureau. Table 1. U.S. International

Trade Commission. 2004. ITC Trade DataWeb. http://dataweb.usitc.gov/ As obtained March, 2004.

For the transportation service sectors, the NDEIM uses the latest service expenditure data

reported by the U.S. Bureau of Economic Analysis. These values come from the 1997

Benchmark I-O Supplementary Make, Use, and Direct Requirements Tables at the Detailed

Level." BEA's Industry Economic Program produces the input-output tables, which show how

industries interact to provide input to, and take output from, each other. The data set can provide

an appropriate measure transportation services purchased by the application markets included in

NDEIM. Similar to the application markets, the model uses normalized commodities (e.g. price

is one and value equals quantity). To estimate production for future years, we applied SO2

growth rates for these sectors to the service expenditures reported in Table 10.3-10 (see

discussion of growth rates in Section 10.3.6).
Final Regulatory Impact Analysis

10-66

Table 10.3-10

Baseline Data for NDEIM’s Transportation Service Markets: 1997

Transportation Service Market Value of Services Used by Application

Markets Included in NDEIM ($109)

Locomotive $19

Marine $4

Source: U.S. Bureau of Economic Analysis (BEA). 1997 Benchmark I-O Supplementary Make, Use, and Direct

Requirements Tables at the Detailed Level. Table 4. http://www.bea.gov/bea/dn2/i-o_benchmark.htm. Last

updated November 24, 2003.

10.3.4 Calibrating the Fuel Spillover Baseline

The economic impact of the nonroad diesel rule is measured relative to the highway diesel

rule. The highway rule is scheduled to be phased in prior to the nonroad rule. Thus, the effect of

the highway rule must be incorporated into the baseline prior to modeling the impact of the

nonroad rule. The main factor to be addressed is “spillover” fuel from the highway market. The

Agency estimates that approximately one-third of nonroad equipment currently uses highway

grade fuel because of access and distribution factors. Nonroad equipment currently using

highway diesel will experience increased fuel costs as a result of the highway rule, but not as a

result of the nonroad rule. These costs have already been captured in the highway rule analysis;

thus, it is important to discount “spillover” fuel in the nonroad market to avoid double counting

of cost impacts.

In this analysis, the baseline model is shocked by applying the compliance costs for the

highway fuel requirements to the spillover fuel volumes included in Table 10.3-5. This provides

an adjusted baseline for the nonroad economic impact analysis from which the incremental

impact of the nonroad rule is estimated. When this adjustment is performed, increasing the cost

of producing spillover fuel leads to a slight increase in the cost of producing goods and services

in the application markets, and a decrease in application quantity ripples through the deriveddemand curves of the equipment and engine markets, slightly reducing the baseline equipment

and engine population. We assume that there are no substitutions between spillover diesel fuel

consumption and nonroad diesel fuel consumption as prices change because demand is primarily

driven by availability constraints.

10.3.5 Compliance Costs

The NDEIM uses the compliance cost estimates described in Chapters 6 and 7. These cost

are summarized in Tables 10.3-13 through 10.3-15. The compliance cost per unit vary over time

and by industry sector (engine, equipment, or fuel producer). All costs are presented in 2002

dollars.
Economic Impact Analysis

OFixed engine costs are not included in the supply shift; see Section 10.2.3.3.

10-67

For the reasons described in Section 10.1 and 10.2, the NDEIM does not handle all

compliance costs in the same way. While all compliance costs are included in the economic

welfare analysis to estimate the total social costs associated with the program, only some

compliance costs are included in the market analysis to estimate changes in price and quantities

of goods produced using the engines, equipment, and fuel affected by the rule. Table 10.3-11

identifies which compliance costs are used as shocks in the market analysis and which are added

to the social cost estimates after changes in market prices and quantifies have been determined.

Table 10.3-11

How Compliance Costs are Accounted for in the Economic Analysis

Compliance Costs used to 

Shock the Market Model

Compliance Costs added after 

Market Analysis

C Variable costs for diesel engines

C Variable costs for diesel equipment

C Fixed and variable costs for nonroad

diesel fuel

C Fixed costs for diesel engines

C Fixed costs for diesel equipment

C Changes in operating costs of diesel equipment

As noted above, marker costs for home heating fuel are included in the estimate of fixed and

variable costs for nonroad diesel fuel (see Section 10.3.3.2, above).

10.3.5.1 Engine and Equipment Compliance Costs

For diesel engines, the projected compliance costs are largely due to using new technologies,

such as advanced emissions control technologies and low-sulfur diesel fuel, to meet the proposed

Tier 4 emissions standards. Compliance costs for engines are broken out by horsepower

category and impact year. The method used to estimate these compliance costs is described in

Section 6.4.3; the per unit compliance costs for the 175 to 600 hp range were estimated by sales

weighting the 175 to 300 hp and the 300 to 600 hp per unit costs. The costs per unit change from

year to year because engine standards are implemented differently in each power category. As

shown in Table 10.3-13, the fixed cost per engine typically decreases after 5 years as these

annualized costs are depreciated. The regulation’s market impacts are driven primarily by the

per-engine variable costs that remain relatively constant over time.

Because the estimated compliance costs for the rule are not directly proportional to engine

price, the relative supply shift in each of the engine size markets is expected to vary.O As

illustrated in Table 10.3-12, the ratio of variable engine compliance costs to market price ranges

from 29 percent for engines 25 to 50 hp to 3 percent for engines above 600 hp. These different

ratios lead to different relative shifts in the supply curves, and different impacts on the changes

in market price and quantity for each market.

Table 10.3-12
Final Regulatory Impact Analysis

10-68

Ratio of Variable Engine Compliance Costs to Engine Price

Power Range Variable Engine Compliance

Cost / Engine Price

0<hp<25 8.2%

25#hp<50 29.3%

50#hp<75 27.9%

75#hp<100 28.3%

100#hp<175 25.0%

175#hp<600 8.5%

hp > 600 hp 2.8%

For nonroad equipment, the majority of the projected compliance costs are due to the need to

redesign the equipment. The method used to estimate these compliance costs is described in

Section 6.4.3. The fixed cost consists of the redesign cost to accommodate new emissions

control devices. The variable cost consists of the cost of new or modified equipment hardware

and of labor to install the new emissions control devices. The per unit compliance costs are

weighted average costs within the appropriate horsepower range. The equipment sector

compliance costs are broken out by horsepower category and impact year in Table 10.3-14. The

majority of costs per piece of equipment are the fixed costs. The overall compliance costs per

piece of equipment are less than half the overall costs associated with the same horsepower

category engine. 
10-69

Table 10.3-13

Compliance Costs per Enginea

HP Category Cost Types 2008 2009 2010 2011 2012 2013 2014 2015 

0<hp<25 Variable $129 $129 $123 $123 $123 $123 $123 $123 

Fixed $33 $32 $31 $30 $30 $0 $0 $0 

Total $162 $161 $154 $153 $152 $123 $123 $123 

25#hp<50 Variable $147 $147 $139 $139 $139 $849 $849 $645 

Fixed $49 $48 $47 $46 $45 $74 $73 $71 

Total $196 $195 $187 $186 $185 $924 $922 $716 

50#hp<75 Variable $167 $167 $158 $158 $158 $837 $837 $636 

Fixed $50 $49 $49 $48 $47 $76 $75 $73 

Total $217 $216 $206 $205 $205 $913 $912 $710 

75#hp<100 Variable $0 $0 $0 $0 $1,133 $1,133 $1,122 $1,122 

Fixed $0 $0 $0 $0 $80 $78 $108 $106 

Total $0 $0 $0 $0 $1,213 $1,212 $1,229 $1,227 

100#hp<175 Variable $0 $0 $0 $0 $1,375 $1,375 $1,351 $1,351 

Fixed $0 $0 $0 $0 $78 $77 $106 $105 

Total $0 $0 $0 $0 $1,453 $1,452 $1,457 $1,455 

175#hp<600 Variable $0 $0 $0 $2,191 $2,190 $1,697 $2,137 $2,136 

Fixed $0 $0 $0 $326 $321 $316 $437 $430 

Total $0 $0 $0 $2,517 $2,511 $2,012 $2,574 $2,567 

hp$600hp Variable $0 $0 $0 $2,911 $2,910 $2,246 $2,733 $6,153 

Fixed $0 $0 $0 $861 $848 $835 $1,083 $1,526 

Total $0 $0 $0 $3,771 $3,758 $3,081 $3,817 $7,679 

a 2002 dollars 
10-70

Table 10.3-13 (continued)

Compliance Costs per Enginea

HP Category Cost Types 2018 2019 2020 2021 2022 2023 2024 2025 

0<hp<25 Variable $123 $123 $123 $123 $123 $123 $123 $123 

Fixed $0 $0 $0 $0 $0 $0 $0 $0 

Total $123 $123 $123 $123 $123 $123 $123 $123 

25#hp<50 Variable $645 $645 $645 $645 $645 $645 $645 $645 

Fixed $0 $0 $0 $0 $0 $0 $0 $0 

Total $645 $645 $645 $645 $645 $645 $645 $645 

50#hp<75 Variable $636 $636 $636 $636 $636 $636 $636 $636 

Fixed $0 $0 $0 $0 $0 $0 $0 $0 

Total $636 $636 $636 $636 $636 $636 $636 $636 

75#hp<100 Variable $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 

Fixed $28 $0 $0 $0 $0 $0 $0 $0 

Total $1,150 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 

100#hp<175 Variable $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 

Fixed $29 $0 $0 $0 $0 $0 $0 $0 

Total $1,380 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 

175#hp<600 Variable $2,134 $2,133 $2,132 $2,132 $2,131 $2,130 $2,130 $2,129 

Fixed $119 $0 $0 $0 $0 $0 $0 $0 

Total $2,253 $2,133 $2,132 $2,132 $2,131 $2,130 $2,130 $2,129 

hp$600hp Variable $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 

Fixed $685 $433 $0 $0 $0 $0 $0 $0 

Total $6,032 $5,780 $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 

a 2002 dollars 
Table 10.3-13 (continued)

Compliance Costs per Enginea

HP Category Cost Types 2028 2029 2030 2031 2032 2033 2034 

0<hp<25 Variable $123 $123 $123 $123 $123 $123 $123 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $123 $123 $123 $123 $123 $123 $123 

25#hp<50 Variable $645 $645 $645 $645 $645 $645 $645 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $645 $645 $645 $645 $645 $645 $645 

50#hp<75 Variable $636 $636 $636 $636 $636 $636 $636 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $636 $636 $636 $636 $636 $636 $636 

75#hp<100 Variable $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 $1,122 

100#hp<175 Variable $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 $1,351 

175#hp<600 Variable $2,127 $2,127 $2,126 $2,126 $2,125 $2,124 $2,124 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $2,127 $2,127 $2,126 $2,126 $2,125 $2,124 $2,124 

hp$600hp Variable $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 $5,347 

a 2002 dollars
10-72

Table 10.3-14

Costs per Piece of Equipmenta

HP Category Cost Types 2008 2009 2010 2011 2012 2013 2014 2015 

0<hp<25 Variable $0 $0 $0 $0 $0 $0 $0 $0 

Fixed $15 $15 $14 $14 $14 $13 $13 $13 

Total $15 $15 $14 $14 $14 $13 $13 $13 

25#hp<50 Variable $0 $0 $0 $0 $0 $20 $20 $16 

Fixed $8 $8 $8 $7 $7 $42 $41 $40 

Total $8 $8 $8 $7 $7 $62 $62 $57 

50#hp<75 Variable $0 $0 $0 $0 $0 $21 $21 $17 

Fixed $8 $8 $8 $8 $8 $44 $43 $42 

Total $8 $8 $8 $8 $8 $65 $64 $59 

75#hp<100 Variable $0 $0 $0 $0 $45 $45 $48 $48 

Fixed $0 $0 $0 $0 $109 $107 $132 $130 

Total $0 $0 $0 $0 $154 $152 $180 $178 

100#hp<175 Variable $0 $0 $0 $0 $46 $46 $49 $49 

Fixed $0 $0 $0 $0 $170 $168 $207 $204 

Total $0 $0 $0 $0 $216 $213 $256 $253 

175#hp<600 Variable $0 $0 $0 $75 $75 $60 $80 $80 

Fixed $0 $0 $0 $378 $372 $366 $453 $446 

Total $0 $0 $0 $453 $447 $426 $533 $526 

hp$600hp Variable $0 $0 $0 $57 $57 $46 $61 $123 

Fixed $0 $0 $0 $690 $680 $670 $806 $1,404 

Total $0 $0 $0 $748 $737 $716 $867 $1,527 

a 2002 dollars 
10-73

Table 10.3-14 (continued)

Costs per Piece of Equipmenta

HP Category Cost Types 2018 2019 2020 2021 2022 2023 2024 2025 

0<hp<25 Variable $0 $0 $0 $0 $0 $0 $0 $0 

Fixed $0 $0 $0 $0 $0 $0 $0 $0 

Total $0 $0 $0 $0 $0 $0 $0 $0 

25#hp<50 Variable $16 $16 $16 $16 $16 $16 $16 $16 

Fixed $32 $31 $31 $30 $30 $0 $0 $0 

Total $48 $47 $47 $46 $46 $16 $16 $16 

50#hp<75 Variable $17 $17 $17 $17 $17 $17 $17 $17 

Fixed $33 $33 $32 $32 $31 $0 $0 $0 

Total $50 $50 $49 $49 $48 $17 $17 $17 

75#hp<100 Variable $48 $48 $48 $48 $48 $48 $48 $48 

Fixed $124 $122 $120 $118 $24 $24 $0 $0 

Total $172 $170 $168 $167 $72 $72 $48 $48 

100#hp<175 Variable $49 $49 $49 $49 $49 $49 $49 $49 

Fixed $194 $192 $189 $186 $37 $37 $0 $0 

Total $243 $241 $238 $235 $86 $86 $49 $49 

175#hp<600 Variable $80 $80 $79 $79 $79 $79 $79 $79 

Fixed $427 $421 $415 $83 $82 $81 $0 $0 

Total $506 $500 $494 $162 $161 $160 $79 $79 

hp$600hp Variable $111 $111 $111 $111 $111 $111 $111 $11

Fixed $1,346 $1,328 $1,310 $693 $684 $675 $540 $0 

Total $1,457 $1,438 $1,421 $804 $795 $786 $650 $11

a 2002 dollars 
Table 10.3-14 (continued)

Costs per Piece of Equipmenta

HP Category Cost Types 2028 2029 2030 2031 2032 2033 2034 

0<hp<25 Variable $0 $0 $0 $0 $0 $0 $0 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $0 $0 $0 $0 $0 $0 $0 

25#hp<50 Variable $16 $16 $16 $16 $16 $16 $16 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $16 $16 $16 $16 $16 $16 $16 

50#hp<75 Variable $17 $17 $17 $17 $17 $17 $17 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $17 $17 $17 $17 $17 $17 $17 

75#hp<100 Variable $48 $48 $48 $48 $48 $48 $48 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $48 $48 $48 $48 $48 $48 $48 

100#hp<175 Variable $49 $49 $49 $49 $49 $49 $49 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $49 $49 $49 $49 $49 $49 $49 

175#hp<600 Variable $79 $79 $79 $79 $79 $79 $79 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $79 $79 $79 $79 $79 $79 $79 

hp$600hp Variable $111 $111 $111 $111 $111 $111 $111 

Fixed $0 $0 $0 $0 $0 $0 $0 

Total $111 $111 $111 $111 $111 $111 $111 

a 2002 dollars
Economic Impact Analysis

10-75

10.3.5.2 Nonroad Diesel Fuel Compliance Costs

The fuel compliance costs used in the NDEIM are the same as those described in Chapter 7. 

The NDEIM uses different compliance costs for each PADD, and for different fuel sulfur levels

(15 and 500 ppm fuel). Thus, the compliance costs change when the fuel standards change,

reflecting the phase-in of the fuel requirements. From 2007 to 2010, nonroad, locomotive, and

marine diesel fuels are required to meet a 500 ppm sulfur cap. During this period small refiners

can continue producing high sulfur distillate fuel (~3000 ppm) and sell it into the nonroad,

locomotive and marine diesel fuel pool. In 2010, the sulfur standard for nonroad, locomotive

and marine diesel fuel changes to a 15 ppm sulfur cap. From 2010 to 2014, small refiners can

provide fuel complying with a 500 ppm sulfur cap to the nonroad, locomotive and marine diesel

fuel pool, except in most of PADD 1 where 500 ppm small refiner fuel cannot be sold. After

2014, the program is fully phased-in when the small refinery provisions cease. Table 10.3-15

presents a summary of the compliance costs used in the model. It should be noted that these

compliance costs are weighted averages of the separate compliance costs for each grade of fuel

sold in that period.

In contrast to the engine and equipment compliance costs, the fuel compliance costs include

fixed costs. They also include the marker costs described in Section 10.1.3.6. See Chapter 7 for

a more detailed description of the components of the fuel compliance costs and how they are

estimated. See Section 10.2..2.3 for a discussion of how fixed and variable costs are handled in

the model.

Table 10.3-15

Fuel Compliance Costs, Locomotive, and Marine Diesel Fuel by PADD

Selected Years

Yeara Average Cost Maximum Total Cost

500 ppm 15 ppm 500 ppm 15 ppm

PADD I and III

2007-9 1.8 — 4.5 —

2010 1.86 5.7 4.57 9.4

2011 2.7 5.7 6.1 9.4

2014-13 2.7 6.0 6.1 9.6

2015 2.7 6.3 6.1 9.8

PADD II

2007-9 2.5 — 3.8 —

2010 2.55 7.4 3.94 10.8

2011-13 3.5 7.4 5.9 10.8
Final Regulatory Impact Analysis

Yeara Average Cost Maximum Total Cost

500 ppm 15 ppm 500 ppm 15 ppm

10-76

2014 3.5 7.7 5.9 11.1

2015 3.5 7.9 5.9 11.2

PADD IV

2007-9 3.5 — 6.1 —

2010 3.83 12.6 6.26 13.6

2011-13 9.2 12.6 9.2 13.6

2014 9.2 12.8 9.2 13.8

2015 9.2 13 9.2 13.9

PADD Vb

2007-9 1.5 — 1.5 —

2010 1.58 5.1 1.62 5.2

2011 3.7 5.1 4.4 5.2

2014-13 3.7 6.1 4.4 6.4

2015 3.7 6.9 4.4 7.3

a

Note that the 500 ppm standard begins in 6/06 and the 15 ppm standard begins in 6/10

b Excludes diesel fuel sold for use in California which is regulated by California’s regulations.

10.3.5.3 Changes in Operating Costs

As described in Section 6.2.3 of Chapter 6, changes in operating costs are expected to be

realized by all diesel equipment users as a result of the reduced sulfur content of nonroad diesel

fuel. These changes in operating costs include the change in maintenance costs associated with

applying new emission controls to the engines; the change in maintenance costs associated with

low-sulfur fuel such as extended oil-change intervals (extended oil change intervals results in

maintenance savings); the change in fuel costs associated with the incrementally higher costs for

low-sulfur fuel (see Chapter 7), and the change in fuel costs due to any fuel consumption impacts

associated with applying new emission controls to the engines (e.g., cost is attributed to the

CDPF and its need for periodic regeneration). Some of these changes in operating costs will

accrue to users of existing as well as new equipment.

The expected changes in operating costs are not included in the market analysis. This is

because, as explained in Chapter 6, these savings are not expected to affect consumer decisions

with respect to new engines. Changes in operating costs are included in the social cost analysis,

however, because they accrue to society. They are added into the estimated social costs as an
Economic Impact Analysis

10-77

additional savings to the application markets, since it is the users of these engines and fuels who

will see these savings. Appendix 10I contains a sensitivity analysis in which operating cost

savings are introduced into the market analysis as a downward shift in the application supply

functions. 

The operating savings in the social cost analysis were estimated by EPA using the estimated

¢/gallon operating savings estimates and the fuel volumes described in Chapter 6 and 7. Total

annual operating savings were estimated for nonroad, locomotive, and marine fuel. The annual

operating savings associated with nonroad fuel were allocated to the three application markets

(i.e., the users of nonroad equipment) based on the number of gallons of nonroad diesel

consumed in each of the agriculture (32.1 percent), construction (47.4 percent), and

manufacturing sectors (20.5 percent). A different approach was followed for locomotive and

marine fuel. This is necessary because not all locomotive and marine transportation services are

provided to the three application markets included in the NDEIM (see Section 10.1.5). In this

case, 54 percent of the locomotive and marine operating savings were allocated to the marine

and locomotive transportation services included in the NDEIM and 46 percent were allocated to

marine and locomotive transportation services provided for application markets not included in

the NDEIM.
Final Regulatory Impact Analysis

10-78

Table 10.3-16

Operating Cost Savings ($Millions)

Year Nonroad Locomotive Marine Total

2007 140 12 9 161

2008 246 21 15 282

2009 251 21 16 288

2010 266 22 17 305

2011 271 23 18 311

2012 261 23 18 302

2013 243 23 18 285

2014 257 17 19 293

2015 256 13 20 288

2016 241 13 20 274

2017 228 13 20 261

2018 216 13 20 249

2019 205 13 21 239

2020 192 13 22 227

2021 182 13 23 218

2022 176 14 23 213

2023 171 14 23 208

2024 167 14 23 204

2025 163 14 24 201

2026 160 14 24 198

2027 157 14 24 196

2028 156 14 25 195

2029 155 14 25 194

2030 154 15 25 194

2031 154 15 26 194

2032 154 15 26 195

2033 154 15 26 195

2034 154 15 27 196

2035 155 15 27 197

2036 156 15 27 198

Source: See Chapter 6 for an explanation of operating savings; the above values are based on the values reported in

Table 6.4-3, applied to the relevant fuel volumes.
Economic Impact Analysis

P

A supply function was estimated as part of the simultaneous equations approach used for the

construction and manufacturing application markets. However, the supply elasticity estimates

were not statistically significant and were negative, which is inconsistent with generally

10-79

10.3.6 Growth Rates

The growth rates used in this analysis for engines and equipment are the same as those

provided in Section 8.1. The growth rate for nonroad diesel fuel is from the Nonroad Model. 

The growth rates for locomotive, marine, heating oil, and highway diesel fuel are all from EIA’s

Annual Energy Outlook 2003. 

Growth rates for the application markets are the average of the growth rates for equipment

used in the relevant markets. They range from 1.8 percent (>600 HP) to 3.5 percent (<25 HP).

This method was used over a method applying sales weighted averages because it does not

overestimate the application growth rate by giving more weight to higher growth rates of small

HP equipment. If a weighted average were used, the small engine growth rate would dominate

because there are so many more small engines. Using such a weighted average would then

overstate the growth rate for the larger engines. The difference between the two approach is

about 0.2 percent (about 2.3 percent for unweighted and about 2.5 percent for weighted).

Finally, for the locomotive and marine sectors, growth is based on EPA’s SO2 inventory

growth projections for marine diesel engines that use distillate fuel (typically engines with

displacement less than 30 liters per cylinder), 50-state annual inventories, 1999-2003.

10.3.7 Market Supply and Demand Elasticities

To operationalize the market model, supply and demand elasticities are needed to represent

the behavior adjustments that are likely to be made by market participants. The following

parameters are needed:

C supply and demand price elasticities for application markets (construction, agriculture,

and manufacturing),

C supply elasticities for equipment markets,

C supply elasticities for engine markets, and

C supply elasticities for diesel fuel markets.

Note that, for the equipment, engine, and diesel fuel markets, demand-specific elasticity

estimates are not needed because they are derived internally as a function of changes in output

levels in the applications markets.

Tables 10.3-17 and 10.3-18 provides a summary of the demand and supply elasticities used

to estimate the economic impact of the proposed rule. Most elasticities were derived

econometrically using publicly available data, with the exception of the supply elasticities for the

construction and agricultural application markets and the diesel fuel supply elasticity, which

were obtained from previous studies.P

 The general methodologies for estimating the supply and
Final Regulatory Impact Analysis

accepted economic theory. For this reason, literature estimates were used for the supply

elasticities in the construction and manufacturing application markets.

10-80

demand elasticities are discussed below. The specific regression results are presented in

Appendix 10G. It should be noted that these elasticities reflect intermediate run behavioral

changes. In the long run, supply and demand are expected to be more elastic since more

substitutes may become available.
Economic Impact Analysis

10-81

Table 10.3-17

Summary of Market Demand Elasticities Used in the NDEIM

Market Estimate Source Method Input Data Summary

Applications

Agriculture –0.20 EPA econometric

estimate

Productivity shift

approach (Morgenstern,

Pizer, and Shih, 2002) 

Annual time series from

1958 ! 1995 developed by 

Jorgenson et al.

(Jorgenson, 1990; Jorgenson,

Gollop, and Fraumeni, 1987)

Construction –0.96 EPA econometric

estimate

Simultaneous equation

(log-log) approach

Annual time series from

1958 ! 1995 developed by

Jorgenson et al. (Jorgenson,

1990; Jorgenson, Gollop, and

Fraumeni, 1987)

Manufacturing –0.58 EPA econometric

estimate

Simultaneous equation

(log-log) approach. 

Annual time series from

1958 ! 1995 developed by

Jorgenson et al. (Jorgenson,

1990; Jorgenson, Gollop, and

Fraumeni, 1987)

Transportation

Services

Locomotive Derived demand In the derived demand approach, 

C compliance costs increase prices and decrease demand

for products and services in the application markets;

C this in turn leads to reduced demand for diesel

equipment, engines and fuel, which are inputs into the

production of products and services in the application

markets 

 

Marine Derived demand

Equipment

Agriculture Derived demand

Construction Derived demand

Pumps/

compressors

Derived demand

Generators and

Welders

Derived demand

Refrigeration Derived demand

Industrial Derived demand

Lawn and

Garden

Derived demand

Engines Derived demand

Diesel fuel Derived demand
Final Regulatory Impact Analysis

10-82

Table 10.3-18

Summary of Market Supply Elasticities Used in the NDEIM

Markets Estimate Source Method Input Data Summary

Applications

Agriculture 0.32 Literature-based

estimate

Production-weighted

average of individual

crop estimates ranging

from 0.27 to 0.55.

(Lin et al., 2000) 

Agricultural Census data

1991 ! 1995

Construction 1.0 Literature-based

estimate

Based on Topel and

Rosen, (1988).a

Census data, 1963 ! 1983

Manufacturing 1.0 Literature-based

estimate

Literature estimates are

not available so assumed

same value as for

Construction market

Not applicable

Transportation Services

Locomotive 0.6 Literature-based

estimate

Method based on Ivaldi

and McCollough (2001)

Association of American

Railroads 1978-1997

Marine 0.6 Literature-based

estimate

Literature estimates not

available so assumed

same value as for

locomotive market

Not applicable

Equipment

Agriculture 2.14 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3523

Construction 3.31 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3531

Pumps/

compressors

2.83 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3561 and 3563

Generators/

Welder Sets

2.91 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3548

Refrigeration 2.83 EPA econometric

estimate

Assumed same as

pumps/compressors

Industrial 5.37 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3537

Lawn and

Garden

3.37 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3524

Engines 3.81 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3519

Diesel fuel 0.24 Literature based

estimate

Based on Considine

(2002).b

 

From Energy Intelligence

Group (EIG); 1987-2000c

a Most other studies estimate ranges that encompass 1.0, including DiPasquale (1997) and DiPasquale and Wheaton

(1994). b Other estimates range from 0.02 to 1.0 (Greene and Tishchishyna, 2000). However, Considine (2002) is one of the few

studies that estimates a supply elasticity for refinery operations. Most petroleum supply elasticities also include

extraction. c This source refers to the data used by Considine in his 2002 study.
Economic Impact Analysis

QWe discuss the calculation of the appropriate per-unit compliance cost measure used in each

market in Section 10.2.3.3 of the RIA.

10-83

10.3.8 Model Solution

10.3.8.1 Computing Baseline and With-Regulation Equilibrium Conditions

To perform the economic impact analysis, the model compares the baseline equilibrium

conditions and the counterfactual with-regulation equilibrium conditions produced under a

changed policy regime. The assumption of an “observable” baseline equilibrium leads directly to

the need for and construction of a data set that fulfills the equilibrium conditions for markets

included in NDEIM. For this analysis, we examine the impacts of the rule for 29 years (2007 to

2036). As a result, we need to develop an observable baseline for each of these future years. 

This section describes the data and approach used to establish these baselines.

Developing a Baseline Equilibrium: In order to construct a baseline for each year,

equilibrium market conditions without the rule were computed using the following three steps:

• Collect baseline prices and production data for the most recently available year (2000).

• Apply appropriate growth rates to estimate future production for markets included in

NDEIM, and

• Incorporate the impact of increased fuel costs associated with the highway rule prior to

analysis of the final nonroad rule. We incorporate the impact of the highway rule costs in

the baseline because they have already been captured in the highway rule analysis; thus,

we avoid double counting of cost impacts of the highway rule. In effect, our baseline

market projections are "shocked" by the highway rule and a new set of baseline prices

and quantities is estimated for all linked markets. This new baseline is the appropriate

point of departure for analysis of the final nonroad rule.

It is important to note that the baseline analysis of each year does not incorporate the

cumulative regulatory effects from the highway and nonroad rule in previous years. For

example, the regulatory effects impacts from year 2007 do not affect the baseline conditions for

the years 2008 through 2036. These dynamic interactions would reduce the estimated impact of

the regulation but are beyond the scope of the modeling effort. As a result, the impact estimates

may be viewed as conservative in that they likely over estimate impacts.

Shifting the Supply Function: The starting point for assessing the market impacts of a

regulatory action is to incorporate the regulatory compliance costs into the production decision

of the firm. In order to quantify this upward shift, the model the per-unit compliance cost

estimates as the measure of additional cost per unit of producing outputQ. Treatment of

compliance costs in this manner is the conceptual equivalent of a unit tax on output. 
Final Regulatory Impact Analysis

10-84

P

D

$/Q

Q/t

S

P*

A B

P

P

Excess Supply

Excess Demand

P′

Figure 10.3-1. 

For Prices Higher (Lower) than P*, Price Will Fall (Rise)

Computing With-Regulation Equilibrium Conditions: The French economist Léon Walras

proposed one early model of market price adjustment by using the following thought experiment. 

Suppose there is a hypothetical agent that facilitates market adjustment by playing the role of an

"auctioneer." He announces prices, collects information about supply and demand responses

(without transactions actually taking place), and continues this process until market equilibrium

is achieved. 

For example, suppose the auctioneer calls out a price (P) that is lower than the equilibrium

price (P*) (see Figure 10.3-1). He then determines that the quantity demanded (A) exceeds the

quantity supplied (B) and calls out a new (higher) price (P'). This process continues until P=P*. 

A similar analysis takes place when excess supply exists. The auctioneer calls out lower prices

when the price is higher than the equilibrium price. 

10.3.8.2 Solution Algorithm

Supply responses and market adjustments can be conceptualized as an interactive process. 

Producers facing increased production costs due to compliance are willing to supply smaller

quantities at the baseline price. This reduction in market supply leads to an increase in the

market price that all producers and consumers face, which leads to further responses by

producers and consumers and thus new market prices, and so on. The new with-regulation

equilibrium is the result of a series of iterations in which price is adjusted and producers and

consumers respond, until a set of stable market prices arises where total market supply equals

market demand. Market price adjustment takes place based on a price revision rule, described
Economic Impact Analysis

10-85

below, that adjusts price upward (downward) by a given percentage in response to excess

demand (excess supply).

The NDEIM model uses a similar type of algorithm for determining with-regulation

equilibria and the process can be summarized by six recursive steps:

1. Impose the control costs on affected supply segments, thereby affecting their supply

decisions.

2. Recalculate the market supply in each market. Excess demand currently exists.

3. Determine the new prices via a price revision rule. We use a rule similar to the factor

price revision rule described by Kimbell and Harrison (1986). Pi

 is the market price at

iteration I, qd is the quantity demanded, and qs is the quantity supplied. The parameter z

influences the magnitude of the price revision and speed of convergence. The revision

rule increases the price when excess demand exists, lowers the price when excess supply

exists, and leaves the price unchanged when market demand equals market supply. The

price adjustment is expressed as follows:

Pi+1 = P1 • (10.1) q

q

d

s

z





 





4. Recalculate market supply with new prices,

5. Compute market demand in each market.

6. Compare supply and demand in each market. If equilibrium conditions are not satisfied,

go to Step 3, resulting in a new set of market prices. Repeat until equilibrium conditions

are satisfied (i.e., the ratio of supply and demand is arbitrarily close to one). When the

ratio is appropriately close to one, the market- clearing condition of supply equals

demand is satisfied.

10.4 Estimating Impacts

Using the static partial equilibrium analysis, the NDEIM model loops through each year

calculating new market equilibriums based on the projected baseline economic conditions and

compliance cost estimates that shift the supply curves in the model. The model calculates price

and quantity changes and uses these measures to estimate the social costs of the rule and 

partition the impact between producers and consumers. This approach follows the classical

treatment of tax burden distribution in the public finance literature (e.g., Harberger, 1974).
Final Regulatory Impact Analysis

10-86

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Final Regulatory Impact Analysis

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Final Regulatory Impact Analysis

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Economic Impact Analysis

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APPENDIX 10A: Impacts on the Engine Markets

This appendix provides the time series of impacts from 2007 through 2036 for the engine

markets. Seven separate engine markets were modeled segmented by engine size in horsepower

(the EIA includes more horsepower categories than the standards, allowing more efficient use of

the engine compliance cost estimates developed for this rule): 

C less than 25 hp

C 26 to 50 hp

C 51 to 75 hp

C 76 to 100 hp

C 101 to 175 hp

C 176 to 600 hp

C greater than 601 hp

Tables 10A-1 through 10A-7 provide the time series of impacts for the seven horsepower

markets included in the analysis. Each table includes the following:

C average engine price

C average engineering costs (variable and fixed) per engine

! Note that in the engineering cost analysis, fixed costs for engine manufacturers are

recovered in the first five years (see Chapter 6)

C absolute change in the market price ($)

! Note that the estimated absolute change in market price is based on variable costs

only; see Appendix 10I for a sensitivity analysis including fixed costs as well

C relative change in market price (%)

C relative change in market quantity (%)

C total engineering (regulatory) costs for merchant engines ($)

C change in producer surplus from merchant engine manufacturers

As described in Section 10.3.3.1, approximately 65 percent of engines are sold on the

market and these are referred to as “merchant” engines. The remaining 35 percent are consumed

internally by integrated equipment manufacturers and are referred to as “captive” engines. The

total engineering costs and changes in producer surplus presented in this appendix include only

merchant engines because captive engines never pass through the engines markets. Fixed and

variable engineering costs and changes in producer surplus associated with captive engines are

included in equipment manufacture impact estimates presented in Appendix 10B.

All prices and costs are presented in $2002, and real engine prices are assumed to be

constant. The engineering cost per engine typically decreases after 5 years as the annualized

fixed costs are recovered. The price increase after that time is driven by the per-engine variable

costs and remains relatively constant over time.
Final Regulatory Impact Analysis

10-92

For all the engine size categories, the majority of the cost of the regulation is passed

along through increased engine prices. Price increases in 2036 are estimated to be $123 (8.2

percent) for engines <25 hp, $645 (22.2 percent) for engines 26 to 50 hp, $636 (21.2 percent) for

engines 51 to 75 hp, $1,121 (28 percent) for engines 76 to 100 hp, $1,350 (24.6 percent) for

engines 101 to 175 hp, $2,122 (10.6 percent) for engines 176 to 600 hp, and $5,343 (6.6 percent)

for engines above 601 hp.

While the cost per engine and market impacts (in terms of percentage change in price and

quantity) stabilize in the later years of the regulation, the engineering costs and producer surplus

changes continue to gradually increase because the projected baseline population of engines

increases over time.
Economic Impact Analysis

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Table 10A-1. Impacts on the Engine Market and Engine Manufacturers: #25hp

(Average Price per Engine = $1,500)a

Engine (#25Hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.001% — —

2008 $162 $129 8.6% –0.002% $20,017 –$4,043

2009 $161 $129 8.6% –0.002% $20,449 –$4,043

2010 $154 $123 8.2% –0.004% $20,007 –$4,044

2011 $153 $123 8.2% –0.007% $20,417 –$4,045

2012 $152 $123 8.2% –0.009% $20,827 –$4,047

2013 $123 $123 8.2% –0.010% $17,195 –$5

2014 $123 $123 8.2% –0.011% $17,605 –$6

2015 $123 $123 8.2% –0.011% $18,015 –$6

2016 $123 $123 8.2% –0.011% $18,425 –$6

2017 $123 $123 8.2% –0.011% $18,835 –$6

2018 $123 $123 8.2% –0.011% $19,245 –$6

2019 $123 $123 8.2% –0.011% $19,654 –$6

2020 $123 $123 8.2% –0.011% $20,064 –$7

2021 $123 $123 8.2% –0.011% $20,474 –$7

2022 $123 $123 8.2% –0.011% $20,884 –$7

2023 $123 $123 8.2% –0.011% $21,294 –$7

2024 $123 $123 8.2% –0.011% $21,704 –$7

2025 $123 $123 8.2% –0.011% $22,114 –$7

2026 $123 $123 8.2% –0.011% $22,524 –$7

2027 $123 $123 8.2% –0.011% $22,934 –$7

2028 $123 $123 8.2% –0.011% $23,344 –$8

2029 $123 $123 8.2% –0.011% $23,753 –$8

2030 $123 $123 8.2% –0.011% $24,163 –$8

2031 $123 $123 8.2% –0.011% $24,573 –$8

2032 $123 $123 8.2% –0.011% $24,983 –$8

2033 $123 $123 8.2% –0.011% $25,393 –$8

2034 $123 $123 8.2% –0.011% $25,803 –$8

2035 $123 $123 8.2% –0.011% $26,213 –$9

2036 $123 $123 8.2% –0.011% $26,623 –$9

NPVb $370,428 –$17,043

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

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Table 10A-2. Impacts on the Engine Market and Engine Manufacturers: 26–50hp

(Average Price per Engine = $2,900)a

Engine (26hp to 50hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.002% — –$1

2008 $196 $147 5.1% –0.003% $26,163 –$6,592

2009 $195 $147 5.1% –0.003% $26,589 –$6,592

2010 $187 $139 4.8% –0.006% $25,943 –$6,595

2011 $186 $139 4.8% –0.011% $26,347 –$6,600

2012 $185 $139 4.8% –0.014% $26,750 –$6,604

2013 $924 $849 29.3% –0.015% $136,464 –$10,981

2014 $922 $849 29.3% –0.016% $138,927 –$10,983

2015 $716 $645 22.2% –0.016% $110,004 –$10,983

2016 $715 $645 22.2% –0.016% $111,875 –$10,984

2017 $714 $645 22.2% –0.016% $113,746 –$10,984

2018 $645 $645 22.2% –0.016% $104,651 –$19

2019 $645 $645 22.2% –0.016% $106,522 –$19

2020 $645 $645 22.2% –0.016% $108,392 –$19

2021 $645 $645 22.2% –0.016% $110,263 –$20

2022 $645 $645 22.2% –0.016% $112,134 –$20

2023 $645 $645 22.2% –0.016% $114,005 –$20

2024 $645 $645 22.2% –0.016% $115,875 –$21

2025 $645 $645 22.2% –0.016% $117,746 –$21

2026 $645 $645 22.2% –0.016% $119,617 –$21

2027 $645 $645 22.2% –0.016% $121,488 –$22

2028 $645 $645 22.2% –0.016% $123,359 –$22

2029 $645 $645 22.2% –0.016% $125,229 –$22

2030 $645 $645 22.2% –0.016% $127,100 –$23

2031 $645 $645 22.2% –0.016% $128,971 –$23

2032 $645 $645 22.2% –0.016% $130,842 –$23

2033 $645 $645 22.2% –0.016% $132,712 –$24

2034 $645 $645 22.2% –0.016% $134,583 –$24

2035 $645 $645 22.2% –0.016% $136,454 –$24

2036 $645 $645 22.2% –0.016% $138,325 –$25

NPVb $1,722,675 –$67,561

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Economic Impact Analysis

10-95

Table10.A-3. Impacts on the Engine Market and Engine Manufacturers: 51–75hp

(Average Price per Engine = $3,000)a

Engine (51hp to 75hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.002% — –$1

2008 $217 $167 5.6% –0.004% $18,388 –$4,259

2009 $216 $167 5.6% –0.004% $18,650 –$4,259

2010 $206 $158 5.3% –0.006% $18,102 –$4,261

2011 $205 $158 5.3% –0.011% $18,350 –$4,264

2012 $205 $158 5.3% –0.014% $18,597 –$4,267

2013 $913 $837 27.9% –0.015% $84,465 –$7,033

2014 $912 $837 27.9% –0.017% $85,780 –$7,035

2015 $710 $636 21.2% –0.017% $67,870 –$7,035

2016 $709 $636 21.2% –0.017% $68,869 –$7,035

2017 $708 $636 21.2% –0.017% $69,868 –$7,035

2018 $636 $636 21.2% –0.017% $63,844 –$13

2019 $636 $636 21.2% –0.017% $64,843 –$13

2020 $636 $636 21.2% –0.017% $65,842 –$13

2021 $636 $636 21.2% –0.017% $66,841 –$13

2022 $636 $636 21.2% –0.017% $67,840 –$13

2023 $636 $636 21.2% –0.017% $68,840 –$13

2024 $636 $636 21.2% –0.017% $69,839 –$14

2025 $636 $636 21.2% –0.017% $70,838 –$14

2026 $636 $636 21.2% –0.017% $71,837 –$14

2027 $636 $636 21.2% –0.017% $72,836 –$14

2028 $636 $636 21.2% –0.017% $73,835 –$14

2029 $636 $636 21.2% –0.017% $74,834 –$15

2030 $636 $636 21.2% –0.017% $75,833 –$15

2031 $636 $636 21.2% –0.017% $76,832 –$15

2032 $636 $636 21.2% –0.017% $77,832 –$15

2033 $636 $636 21.2% –0.017% $78,831 –$15

2034 $636 $636 21.2% –0.017% $79,830 –$16

2035 $636 $636 21.2% –0.017% $80,829 –$16

2036 $636 $636 21.2% –0.017% $81,828 –$16

NPVb $1,052,492 –$43,432

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Final Regulatory Impact Analysis

10-96

Table10A-4. Impacts on the Engine Market and Engine Manufacturers: 76–100hp 

(Average Price per Engine = $4,000)a

Engine (76hp to 100hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.002% — –$1

2008 — — 0.0% –0.004% — –$1

2009 — — 0.0% –0.004% — –$2

2010 — — 0.0% –0.006% — –$3

2011 — — 0.0% –0.011% — –$6

2012 $1,213 $1,133 28.3% –0.015% $69,454 –$4,576

2013 $1,212 $1,133 28.3% –0.016% $70,577 –$4,577

2014 $1,229 $1,121 28.0% –0.017% $72,815 –$6,379

2015 $1,227 $1,121 28.0% –0.017% $73,926 –$6,379

2016 $1,226 $1,121 28.0% –0.017% $75,037 –$6,379

2017 $1,151 $1,121 28.0% –0.017% $71,580 –$1,812

2018 $1,150 $1,121 28.0% –0.017% $72,691 –$1,812

2019 $1,122 $1,121 28.0% –0.017% $72,001 –$11

2020 $1,122 $1,121 28.0% –0.017% $73,112 –$11

2021 $1,122 $1,121 28.0% –0.017% $74,223 –$11

2022 $1,122 $1,121 28.0% –0.017% $75,334 –$11

2023 $1,122 $1,121 28.0% –0.017% $76,445 –$12

2024 $1,122 $1,121 28.0% –0.017% $77,556 –$12

2025 $1,122 $1,121 28.0% –0.017% $78,667 –$12

2026 $1,122 $1,121 28.0% –0.017% $79,778 –$12

2027 $1,122 $1,121 28.0% –0.017% $80,889 –$12

2028 $1,122 $1,121 28.0% –0.017% $82,000 –$12

2029 $1,122 $1,121 28.0% –0.017% $83,111 –$13

2030 $1,122 $1,121 28.0% –0.017% $84,222 –$13

2031 $1,122 $1,121 28.0% –0.017% $85,333 –$13

2032 $1,122 $1,121 28.0% –0.017% $86,444 –$13

2033 $1,122 $1,121 28.0% –0.017% $87,555 –$13

2034 $1,122 $1,121 28.0% –0.017% $88,666 –$13

2035 $1,122 $1,121 28.0% –0.017% $89,777 –$14

2036 $1,122 $1,121 28.0% –0.017% $90,889 –$14

NPVb $1,098,490 –$23,502

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Economic Impact Analysis

10-97

Table 10A-5. Impacts on the Engine Market and Engine Manufacturers: 101–175hp 

(Average Price per Engine = $5,500)a

Engine (101hp to 175hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.003% — –$1

2008 — — 0.0% –0.004% — –$3

2009 — — 0.0% –0.004% — –$3

2010 — — 0.0% –0.007% — –$5

2011 — — 0.0% –0.013% — –$11

2012 $1,453 $1,375 25.0% –0.017% $90,913 –$4,892

2013 $1,452 $1,375 25.0% –0.018% $92,337 –$4,894

2014 $1,457 $1,350 24.6% –0.019% $94,162 –$6,885

2015 $1,455 $1,350 24.6% –0.020% $95,561 –$6,886

2016 $1,454 $1,350 24.6% –0.020% $96,960 –$6,886

2017 $1,380 $1,350 24.6% –0.020% $93,480 –$2,008

2018 $1,380 $1,350 24.6% –0.020% $94,879 –$2,009

2019 $1,351 $1,350 24.6% –0.020% $94,288 –$19

2020 $1,351 $1,350 24.6% –0.020% $95,687 –$19

2021 $1,351 $1,350 24.6% –0.020% $97,086 –$19

2022 $1,351 $1,350 24.6% –0.020% $98,485 –$19

2023 $1,351 $1,350 24.6% –0.020% $99,884 –$20

2024 $1,351 $1,350 24.6% –0.020% $101,283 –$20

2025 $1,351 $1,350 24.6% –0.020% $102,682 –$20

2026 $1,351 $1,350 24.6% –0.020% $104,081 –$21

2027 $1,351 $1,350 24.6% –0.020% $105,480 –$21

2028 $1,351 $1,350 24.6% –0.020% $106,879 –$21

2029 $1,351 $1,350 24.6% –0.020% $108,278 –$21

2030 $1,351 $1,350 24.6% –0.020% $109,677 –$22

2031 $1,351 $1,350 24.6% –0.020% $111,075 –$22

2032 $1,351 $1,350 24.6% –0.020% $112,474 –$22

2033 $1,351 $1,350 24.6% –0.020% $113,873 –$23

2034 $1,351 $1,350 24.6% –0.020% $115,272 –$23

2035 $1,351 $1,350 24.6% –0.020% $116,671 –$23

2036 $1,351 $1,350 24.6% –0.020% $118,070 –$23

NPVb $1,431,405 –$25,444

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Final Regulatory Impact Analysis

10-98

Table 10A-6. Impacts on the Engine Market and Engine Manufacturers: 176–600hp 

(Average Price per Engine = $20,000)a

Engine (176hp to 600hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.003% — –$3

2008 — — 0.0% –0.004% — –$7

2009 — — 0.0% –0.004% — –$7

2010 — — 0.0% –0.008% — –$13

2011 $2,517 $2,191 11.0% –0.014% $101,112 –$13,109

2012 $2,511 $2,189 10.9% –0.018% $102,473 –$13,118

2013 $2,012 $1,696 8.5% –0.019% $83,408 –$13,121

2014 $2,574 $2,136 10.7% –0.021% $108,339 –$18,421

2015 $2,567 $2,135 10.7% –0.021% $109,668 –$18,423

2016 $2,258 $2,135 10.7% –0.021% $97,915 –$5,342

2017 $2,255 $2,134 10.7% –0.021% $99,244 –$5,342

2018 $2,253 $2,133 10.7% –0.021% $100,573 –$5,343

2019 $2,133 $2,132 10.7% –0.021% $96,607 –$48

2020 $2,132 $2,131 10.7% –0.021% $97,936 –$48

2021 $2,132 $2,131 10.7% –0.021% $99,265 –$49

2022 $2,131 $2,130 10.7% –0.021% $100,594 –$49

2023 $2,130 $2,129 10.6% –0.021% $101,923 –$50

2024 $2,130 $2,129 10.6% –0.021% $103,253 –$51

2025 $2,129 $2,128 10.6% –0.021% $104,582 –$51

2026 $2,128 $2,127 10.6% –0.021% $105,911 –$52

2027 $2,128 $2,127 10.6% –0.021% $107,240 –$53

2028 $2,127 $2,126 10.6% –0.021% $108,570 –$54

2029 $2,127 $2,126 10.6% –0.021% $109,899 –$54

2030 $2,126 $2,125 10.6% –0.021% $111,228 –$55

2031 $2,126 $2,124 10.6% –0.021% $112,557 –$56

2032 $2,125 $2,124 10.6% –0.021% $113,887 –$56

2033 $2,124 $2,123 10.6% –0.021% $115,216 –$57

2034 $2,124 $2,123 10.6% –0.021% $116,545 –$58

2035 $2,123 $2,122 10.6% –0.021% $117,874 –$58

2036 $2,123 $2,122 10.6% –0.021% $119,203 –$59

NPVb $1,561,195 –$69,509

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-99

Table 10A-7. Impacts on the Engine Market and Engine Manufacturers: $601hp 

(Average Price per Engine = $80,500)a

Engine ($601hp)

Change in Producer

Surplus for Engine

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.002% — —

2008 — –$1 0.0% –0.004% — –$1

2009 — –$1 0.0% –0.004% — –$1

2010 — –$1 0.0% –0.007% — –$2

2011 $3,771 $2,908 3.6% –0.013% $6,156 –$1,409

2012 $3,758 $2,907 3.6% –0.017% $6,228 –$1,410

2013 $3,081 $2,242 2.8% –0.017% $5,182 –$1,411

2014 $3,817 $2,730 3.4% –0.019% $6,514 –$1,856

2015 $7,679 $6,149 7.6% –0.020% $13,296 –$2,649

2016 $6,857 $6,149 7.6% –0.020% $12,044 –$1,244

2017 $6,042 $5,343 6.6% –0.020% $10,761 –$1,244

2018 $6,032 $5,343 6.6% –0.020% $10,893 –$1,244

2019 $5,780 $5,343 6.6% –0.020% $10,582 –$800

2020 $5,347 $5,343 6.6% –0.020% $9,921 –$7

2021 $5,347 $5,343 6.6% –0.020% $10,054 –$7

2022 $5,347 $5,343 6.6% –0.020% $10,187 –$7

2023 $5,347 $5,343 6.6% –0.020% $10,319 –$8

2024 $5,347 $5,343 6.6% –0.020% $10,452 –$8

2025 $5,347 $5,343 6.6% –0.020% $10,584 –$8

2026 $5,347 $5,343 6.6% –0.020% $10,717 –$8

2027 $5,347 $5,343 6.6% –0.020% $10,850 –$8

2028 $5,347 $5,343 6.6% –0.020% $10,982 –$8

2029 $5,347 $5,343 6.6% –0.020% $11,115 –$8

2030 $5,347 $5,343 6.6% –0.020% $11,248 –$8

2031 $5,347 $5,343 6.6% –0.020% $11,380 –$8

2032 $5,347 $5,343 6.6% –0.020% $11,513 –$8

2033 $5,347 $5,343 6.6% –0.020% $11,646 –$9

2034 $5,347 $5,343 6.6% –0.020% $11,778 –$9

2035 $5,347 $5,343 6.6% –0.020% $11,911 –$9

2036 $5,347 $5,343 6.6% –0.020% $12,044 –$9

NPVb $150,134 –$9,762

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Final Regulatory Impact Analysis

R

These seven equipment categories that did not have sales in 2000 are: agricultural equipment >600 hp; gensets &

welders > 600 hp; refrigeration & A/C > 71 hp (4 hp categories); and lawn & garden >600 hp. 

10-100

APPENDIX 10B: Impacts on Equipment Markets

This appendix provides the time series of impacts from 2007 through 2036 for the equipment

markets. The equipment markets are the markets associated with the production and

consumption of equipment that use nonroad diesel engines. Seven equipment types were

modeled:

C agricultural

C construction

C pumps and compressors

C generators and welder sets

C refrigeration and air conditioning 

C general industrial

C lawn and garden

Forty-two equipment markets were modeled, representing 7 horsepower categories within 7

application categories. There are 7 horsepower/application categories that did not have sales in

2000 and are not included in the model, so the total number of diesel equipment markets is 42

rather than 49.R

There are two sets of tables in this appendix. Tables 10B-1 through 10B-7 provide a

summary of the time series of impacts for the seven equipment markets included in the analysis. 

Tables 10B-8 through 10B-49 provide the time series impacts for each equipment market by

horsepower grouping. Each table includes the following:

C average equipment price

C average engineering costs (variable and fixed) per piece of equipment

! Note that in the engineering cost analysis, fixed costs for equipment manufacturers

are recovered in the first ten years (see Chapter 6)

C absolute change in the market price ($)

! Note that the estimated absolute change in market price is based on variable costs

only; see Appendix 10I for a sensitivity analysis including fixed costs as well

C relative change in the market price (%)

C relative change in the market quantity (%)

C total engineering (regulatory) costs associated with each market ($)

C change in producer surplus for all manufacturers in the market

As described in Section 10.3.3.1, approximately 65 percent of engines are sold on the market

and these are referred to as “merchant” engines. The remaining 35 percent are consumed
Economic Impact Analysis

10-101

internally by integrated equipment manufacturers and are referred to as “captive” engines. The

engineering costs and changes in producer surplus presented in this appendix include total

equipment costs as well as captive engine costs. Because captive engines never pass through the

engines markets, they therefore present an additional cost for integrated equipment producers. 

All prices and costs are presented in $2002, and real equipment prices are assumed to be

constant. The engineering cost per piece of equipment peak around 2014 as the fixed cost per

equipment are phased in and then are depreciated over the next several years. 

A greater percentage of the cost of the regulation is borne by the various equipment markets

than is borne by the engine market. However, a substantial percentage of the cost is still passed

along through increased equipment prices. For each equipment market as a whole, price

increases range from an average increase of 1.31 percent in the general industrial equipment

market to 5.4 percent in the pumps and compressors market. For specific types of equipment,

the price increases range from 0.7 percent for construction <25, 176-600 and >600 hp, and

general industrial equipment (<25 hp), to 9.4 percent for pumps and compressors 76-100 hp.

Even though the cost per piece of equipment and market impacts (in terms of percentage

change in price and quantity) stabilize after the initial years of the regulation, the engineering

costs and produce surplus changes continue to gradually increase because the projected baseline

population of equipment increases over time.
Final Regulatory Impact Analysis

10-102

Table 10B-1. Impacts on Agricultural Equipment Market and Manufacturers 

(Average Price per Equipment = $24,200)a,b

Agricultural Equipment Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$1 0.0% –0.004% — –$114

2008 $94 $67 0.5% –0.006% $6,217 –$2,359

2009 $93 $67 0.5% –0.006% $6,304 –$2,364

2010 $89 $62 0.5% –0.010% $6,163 –$2,578

2011 $836 $630 0.9% –0.019% $136,011 –$36,021

2012 $1,278 $1,021 1.6% –0.024% $201,592 –$48,332

2013 $1,432 $1,158 3.1% –0.025% $205,681 –$51,844

2014 $1,611 $1,268 3.2% –0.027% $242,214 –$65,974

2015 $1,529 $1,191 2.7% –0.027% $238,948 –$65,991

2016 $1,448 $1,191 2.7% –0.027% $227,805 –$52,188

2017 $1,423 $1,191 2.7% –0.027% $227,549 –$49,273

2018 $1,390 $1,191 2.7% –0.027% $227,388 –$46,453

2019 $1,349 $1,190 2.7% –0.027% $223,284 –$39,690

2020 $1,347 $1,190 2.7% –0.027% $225,968 –$39,703

2021 $1,263 $1,190 2.7% –0.027% $209,555 –$20,621

2022 $1,230 $1,190 2.7% –0.027% $203,133 –$11,540

2023 $1,218 $1,190 2.7% –0.027% $203,137 –$8,884

2024 $1,190 $1,190 2.7% –0.027% $198,628 –$1,716

2025 $1,189 $1,189 2.7% –0.027% $201,312 –$1,740

2026 $1,189 $1,189 2.7% –0.027% $203,996 –$1,764

2027 $1,189 $1,189 2.7% –0.027% $206,680 –$1,788

2028 $1,189 $1,189 2.7% –0.027% $209,364 –$1,813

2029 $1,189 $1,189 2.7% –0.027% $212,048 –$1,837

2030 $1,189 $1,189 2.7% –0.027% $214,731 –$1,861

2031 $1,188 $1,188 2.7% –0.027% $217,415 –$1,885

2032 $1,188 $1,188 2.7% –0.027% $220,099 –$1,909

2033 $1,188 $1,188 2.7% –0.027% $222,783 –$1,933

2034 $1,188 $1,188 2.7% –0.027% $225,467 –$1,957

2035 $1,188 $1,188 2.7% –0.027% $228,151 –$1,982

2036 $1,188 $1,188 2.7% –0.027% $230,834 –$2,006

NPVc $3,203,099 –$396,969 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-103

Table 10.B-2. Impacts on Construction Equipment Market and Manufacturers

(Average Price per Equipment = $128,100)a,b

Construction Equipment Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$1 0.0% –0.004% — –$227

2008 $82 $58 0.2% –0.006% $2,791 –$1,822

2009 $81 $58 0.2% –0.006% $2,819 –$1,831

2010 $77 $53 0.2% –0.011% $2,764 –$2,307

2011 $771 $567 0.4% –0.021% $129,258 –$41,345

2012 $1,342 $1,073 0.9% –0.027% $222,497 –$60,765

2013 $1,455 $1,172 1.6% –0.028% $215,758 –$64,049

2014 $1,621 $1,268 1.6% –0.031% $252,584 –$81,136

2015 $1,658 $1,285 1.4% –0.032% $277,706 –$87,572

2016 $1,574 $1,285 1.4% –0.032% $265,984 –$72,975

2017 $1,523 $1,266 1.4% –0.032% $260,346 –$68,895

2018 $1,495 $1,266 1.4% –0.032% $261,583 –$67,318

2019 $1,452 $1,266 1.4% –0.032% $257,237 –$60,158

2020 $1,440 $1,266 1.4% –0.032% $257,684 –$57,783

2021 $1,359 $1,265 1.4% –0.032% $237,148 –$34,427

2022 $1,323 $1,265 1.4% –0.032% $225,352 –$19,817

2023 $1,313 $1,265 1.4% –0.032% $225,367 –$17,019

2024 $1,285 $1,265 1.4% –0.032% $218,660 –$7,497

2025 $1,272 $1,265 1.4% –0.032% $217,689 –$3,712

2026 $1,272 $1,265 1.4% –0.032% $220,554 –$3,763

2027 $1,272 $1,265 1.4% –0.032% $223,419 –$3,814

2028 $1,272 $1,264 1.4% –0.032% $226,284 –$3,865

2029 $1,272 $1,264 1.4% –0.032% $229,149 –$3,915

2030 $1,272 $1,264 1.4% –0.032% $232,014 –$3,966

2031 $1,271 $1,264 1.4% –0.032% $234,880 –$4,017

2032 $1,271 $1,264 1.4% –0.032% $237,745 –$4,068

2033 $1,271 $1,264 1.4% –0.032% $240,610 –$4,119

2034 $1,271 $1,264 1.4% –0.032% $243,475 –$4,170

2035 $1,271 $1,264 1.4% –0.032% $246,340 –$4,221

2036 $1,271 $1,263 1.4% –0.032% $249,206 –$4,272

NPVc $3,510,842 –$545,099 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-104

Table 10B-3. Impacts on Pumps and Compressor Equipment Market and Manufacturers

(Average Price per Equipment = $13,700)a,b

Pumps and Compressors Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $135 $98 1.1% –0.001% $176 –$177

2009 $134 $98 1.1% –0.001% $176 –$177

2010 $128 $93 1.1% –0.001% $176 –$177

2011 $340 $255 1.4% –0.002% $1,011 –$876

2012 $682 $563 3.6% –0.003% $2,102 –$1,668

2013 $952 $817 6.1% –0.003% $2,685 –$2,051

2014 $1,006 $847 6.1% –0.003% $3,136 –$2,432

2015 $923 $766 5.4% –0.003% $3,115 –$2,444

2016 $899 $766 5.4% –0.003% $3,126 –$2,444

2017 $878 $765 5.4% –0.003% $3,137 –$2,444

2018 $842 $765 5.4% –0.003% $2,971 –$2,268

2019 $826 $765 5.4% –0.003% $2,982 –$2,268

2020 $824 $765 5.4% –0.003% $2,993 –$2,268

2021 $800 $765 5.4% –0.003% $2,306 –$1,571

2022 $793 $765 5.4% –0.003% $1,526 –$779

2023 $780 $765 5.4% –0.003% $1,155 –$398

2024 $773 $765 5.4% –0.003% $785 –$17

2025 $772 $764 5.4% –0.003% $784 –$5

2026 $772 $764 5.4% –0.003% $795 –$5

2027 $772 $764 5.4% –0.003% $805 –$5

2028 $772 $764 5.4% –0.003% $816 –$5

2029 $772 $764 5.4% –0.003% $827 –$5

2030 $772 $764 5.4% –0.003% $838 –$5

2031 $772 $764 5.4% –0.003% $849 –$5

2032 $772 $764 5.4% –0.003% $860 –$5

2033 $772 $764 5.4% –0.003% $871 –$5

2034 $772 $764 5.4% –0.003% $882 –$5

2035 $772 $764 5.4% –0.003% $893 –$5

2036 $772 $764 5.4% –0.003% $904 –$6

NPVc $27,665 –$17,056 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-105

Table 10.B-4. Impacts on Generator Sets and Welding Equipment Market and Manufacturers

(Average Price per Equipment = $9,200)a,b

Generator Sets and Welders Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $169 $123 1.6% –0.001% $7,721 –$2,899

2009 $168 $123 1.6% –0.001% $7,832 –$2,899

2010 $161 $117 1.5% –0.001% $7,677 –$2,902

2011 $202 $149 1.6% –0.002% $11,511 –$4,090

2012 $354 $285 2.3% –0.003% $25,652 –$7,014

2013 $631 $553 5.5% –0.003% $41,613 –$9,151

2014 $644 $558 5.5% –0.003% $43,801 –$10,345

2015 $563 $479 4.6% –0.003% $40,244 –$10,345

2016 $557 $479 4.6% –0.003% $40,403 –$9,992

2017 $548 $479 4.6% –0.003% $40,314 –$9,391

2018 $512 $479 4.6% –0.003% $37,930 –$6,496

2019 $507 $479 4.6% –0.003% $38,054 –$6,109

2020 $507 $479 4.6% –0.003% $38,566 –$6,109

2021 $502 $479 4.6% –0.003% $38,247 –$5,278

2022 $493 $479 4.6% –0.003% $36,440 –$2,959

2023 $481 $479 4.6% –0.003% $34,816 –$824

2024 $478 $479 4.6% –0.003% $34,523 –$19

2025 $478 $479 4.6% –0.003% $35,035 –$19

2026 $478 $479 4.6% –0.003% $35,547 –$19

2027 $478 $479 4.6% –0.003% $36,058 –$20

2028 $478 $478 4.6% –0.003% $36,570 –$20

2029 $478 $478 4.6% –0.003% $37,082 –$20

2030 $478 $478 4.6% –0.003% $37,594 –$21

2031 $478 $478 4.6% –0.003% $38,106 –$21

2032 $478 $478 4.6% –0.003% $38,618 –$21

2033 $478 $478 4.6% –0.003% $39,130 –$22

2034 $478 $478 4.6% –0.003% $39,642 –$22

2035 $478 $478 4.6% –0.003% $40,154 –$22

2036 $478 $478 4.6% –0.003% $40,666 –$23

NPVc $563,662 –$69,507 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-106

Table 10B-5. Impacts on Refrigeration and Air-Conditioning Equipment Market and

Manufacturers (Average Price per Equipment = $6,314)a,b

Refrigeration and Air Conditioning Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $208 $152 0.6% –0.001% $447 –$449

2009 $206 $152 0.6% –0.001% $447 –$449

2010 $197 $144 0.6% –0.001% $447 –$452

2011 $196 $143 0.6% –0.002% $447 –$456

2012 $195 $143 0.6% –0.003% $447 –$459

2013 $768 $676 2.1% –0.003% $2,551 –$1,792

2014 $766 $676 2.1% –0.003% $2,565 –$1,793

2015 $610 $521 1.7% –0.003% $2,418 –$1,793

2016 $609 $521 1.7% –0.003% $2,429 –$1,793

2017 $607 $521 1.7% –0.003% $2,440 –$1,793

2018 $546 $521 1.7% –0.003% $2,005 –$1,347

2019 $546 $521 1.7% –0.003% $2,016 –$1,347

2020 $545 $521 1.7% –0.003% $2,027 –$1,347

2021 $545 $521 1.7% –0.003% $2,038 –$1,348

2022 $545 $521 1.7% –0.003% $2,049 –$1,348

2023 $522 $521 1.7% –0.003% $732 –$19

2024 $522 $521 1.7% –0.003% $743 –$20

2025 $522 $521 1.7% –0.003% $754 –$20

2026 $522 $521 1.7% –0.003% $765 –$20

2027 $522 $521 1.7% –0.003% $776 –$21

2028 $522 $521 1.7% –0.003% $787 –$21

2029 $522 $521 1.7% –0.003% $798 –$21

2030 $522 $521 1.7% –0.003% $810 –$21

2031 $522 $521 1.7% –0.003% $821 –$22

2032 $522 $521 1.7% –0.003% $832 –$22

2033 $522 $521 1.7% –0.003% $843 –$22

2034 $522 $521 1.7% –0.003% $854 –$23

2035 $522 $521 1.7% –0.003% $865 –$23

2036 $522 $521 1.7% –0.003% $876 –$23

NPVc $22,468 –$12,722 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-107

Table 10.B-6. Impacts on General Industrial Equipment Market and Manufacturers

 (Average Price per Equipment = $91,200)a,b

General Industrial Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — $1

2008 $64 $46 0.1% –0.001% $557 –$287

2009 $63 $46 0.1% –0.001% $563 –$287

2010 $60 $44 0.1% –0.001% $552 –$294

2011 $516 $387 0.3% –0.002% $7,656 –$4,870

2012 $1,320 $1,101 1.1% –0.003% $27,925 –$11,353

2013 $1,429 $1,200 1.4% –0.003% $29,960 –$12,069

2014 $1,549 $1,260 1.4% –0.003% $33,740 –$15,024

2015 $1,537 $1,242 1.3% –0.003% $34,239 –$15,489

2016 $1,483 $1,242 1.3% –0.003% $34,263 –$15,216

2017 $1,431 $1,234 1.3% –0.003% $33,767 –$14,467

2018 $1,409 $1,234 1.3% –0.003% $33,729 –$14,131

2019 $1,372 $1,234 1.3% –0.003% $33,618 –$13,723

2020 $1,366 $1,234 1.3% –0.003% $33,896 –$13,705

2021 $1,313 $1,234 1.3% –0.003% $29,901 –$9,412

2022 $1,268 $1,234 1.3% –0.003% $24,474 –$3,688

2023 $1,260 $1,233 1.3% –0.003% $24,119 –$3,036

2024 $1,236 $1,233 1.3% –0.003% $21,873 –$493

2025 $1,231 $1,233 1.3% –0.003% $21,724 –$47

2026 $1,231 $1,233 1.3% –0.003% $22,021 –$47

2027 $1,231 $1,233 1.3% –0.003% $22,319 –$48

2028 $1,231 $1,233 1.3% –0.003% $22,616 –$48

2029 $1,231 $1,233 1.3% –0.003% $22,914 –$49

2030 $1,231 $1,233 1.3% –0.003% $23,212 –$50

2031 $1,230 $1,233 1.3% –0.003% $23,509 –$50

2032 $1,230 $1,233 1.3% –0.003% $23,807 –$51

2033 $1,230 $1,233 1.3% –0.003% $24,104 –$52

2034 $1,230 $1,232 1.3% –0.003% $24,402 –$52

2035 $1,230 $1,232 1.3% –0.003% $24,700 –$53

2036 $1,230 $1,232 1.3% –0.003% $24,997 –$54

NPVc $401,039 –$102,642 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-108

Table 10.B-7. Impacts on Lawn and Garden Equipment Market and Manufacturers

(Average Price per Equipment = $17,700)a,b

Lawn and Garden Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $164 $119 1.0% –0.001% $2,293 –$838

2009 $163 $119 1.0% –0.001% $2,331 –$838

2010 $156 $113 0.9% –0.001% $2,289 –$839

2011 $195 $144 1.0% –0.002% $2,604 –$1,074

2012 $361 $292 1.4% –0.003% $3,590 –$1,780

2013 $604 $530 2.5% –0.003% $5,759 –$2,097

2014 $616 $535 2.5% –0.003% $6,106 –$2,338

2015 $544 $465 2.2% –0.003% $5,667 –$2,338

2016 $539 $465 2.2% –0.003% $5,734 –$2,338

2017 $529 $465 2.2% –0.003% $5,801 –$2,338

2018 $496 $465 2.2% –0.003% $5,266 –$1,736

2019 $491 $465 2.2% –0.003% $5,333 –$1,736

2020 $491 $465 2.2% –0.003% $5,400 –$1,736

2021 $486 $465 2.2% –0.003% $5,234 –$1,503

2022 $479 $465 2.2% –0.003% $4,596 –$799

2023 $469 $465 2.2% –0.003% $4,113 –$249

2024 $467 $465 2.2% –0.003% $3,940 –$9

2025 $467 $465 2.2% –0.003% $4,007 –$9

2026 $467 $465 2.2% –0.003% $4,075 –$9

2027 $467 $465 2.2% –0.003% $4,142 –$10

2028 $467 $465 2.2% –0.003% $4,209 –$10

2029 $467 $465 2.2% –0.003% $4,276 –$10

2030 $467 $465 2.2% –0.003% $4,343 –$10

2031 $466 $465 2.2% –0.003% $4,410 –$10

2032 $466 $465 2.2% –0.003% $4,477 –$10

2033 $466 $465 2.2% –0.003% $4,544 –$10

2034 $466 $465 2.2% –0.003% $4,611 –$11

2035 $466 $465 2.2% –0.003% $4,678 –$11

2036 $466 $465 2.2% –0.003% $4,745 –$11

NPVb $76,592 –$17,642 a Figures are in 2002 dollars. b Average price per equipment for the market is a weighted average of the price of equipment by hp. c Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-109

Table 10B-8. Impacts on Agricultural Equipment Market and Manufacturers (<25 hp)

(Average Price per Equipment = $6,900)a

Agricultural Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$1

2008 $177 $129 1.9% –0.006% $666 –$341

2009 $176 $129 1.9% –0.006% $675 –$341

2010 $168 $122 1.8% –0.010% $666 –$343

2011 $167 $122 1.8% –0.019% $674 –$348

2012 $166 $122 1.8% –0.024% $683 –$351

2013 $136 $122 1.8% –0.025% $608 –$269

2014 $136 $122 1.8% –0.027% $617 –$271

2015 $135 $122 1.8% –0.027% $625 –$271

2016 $135 $122 1.8% –0.027% $634 –$272

2017 $135 $122 1.8% –0.027% $642 –$272

2018 $123 $122 1.8% –0.027% $395 –$17

2019 $123 $122 1.8% –0.027% $404 –$18

2020 $123 $122 1.8% –0.027% $412 –$18

2021 $123 $122 1.8% –0.027% $421 –$18

2022 $123 $122 1.8% –0.027% $429 –$19

2023 $123 $122 1.8% –0.027% $437 –$19

2024 $123 $122 1.8% –0.027% $446 –$19

2025 $123 $122 1.8% –0.027% $454 –$20

2026 $123 $122 1.8% –0.027% $463 –$20

2027 $123 $122 1.8% –0.027% $471 –$21

2028 $123 $122 1.8% –0.027% $479 –$21

2029 $123 $122 1.8% –0.027% $488 –$21

2030 $123 $122 1.8% –0.027% $496 –$22

2031 $123 $122 1.8% –0.027% $505 –$22

2032 $123 $122 1.8% –0.027% $513 –$22

2033 $123 $122 1.8% –0.027% $522 –$23

2034 $123 $122 1.8% –0.027% $530 –$23

2035 $123 $122 1.8% –0.027% $538 –$24

2036 $123 $122 1.8% –0.027% $547 –$24

NPVb $9,600 –$2,622 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-110

Table 10B-9. Impacts on Agricultural Equipment Market and Manufacturers (26-50 hp)

(Average Price per Equipment = $14,400)a

Agricultural Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$7

2008 $204 $147 1.0% –0.006% $3,707 –$1,225

2009 $203 $147 1.0% –0.006% $3,762 –$1,225

2010 $194 $139 1.0% –0.010% $3,679 –$1,238

2011 $193 $138 1.0% –0.019% $3,731 –$1,268

2012 $192 $138 1.0% –0.024% $3,782 –$1,284

2013 $986 $868 6.0% –0.025% $20,616 –$3,639

2014 $984 $868 6.0% –0.027% $20,951 –$3,648

2015 $773 $660 4.6% –0.027% $17,064 –$3,649

2016 $771 $660 4.6% –0.027% $17,319 –$3,651

2017 $769 $660 4.6% –0.027% $17,575 –$3,653

2018 $693 $660 4.6% –0.027% $16,061 –$1,886

2019 $692 $660 4.6% –0.027% $16,316 –$1,887

2020 $692 $660 4.6% –0.027% $16,571 –$1,888

2021 $691 $660 4.6% –0.027% $16,826 –$1,890

2022 $691 $660 4.6% –0.027% $17,081 –$1,891

2023 $661 $660 4.6% –0.027% $15,546 –$103

2024 $661 $660 4.6% –0.027% $15,801 –$105

2025 $661 $660 4.6% –0.027% $16,057 –$107

2026 $661 $660 4.6% –0.027% $16,312 –$108

2027 $661 $660 4.6% –0.027% $16,567 –$110

2028 $661 $660 4.6% –0.027% $16,822 –$112

2029 $661 $660 4.6% –0.027% $17,077 –$114

2030 $661 $660 4.6% –0.027% $17,332 –$115

2031 $661 $660 4.6% –0.027% $17,587 –$117

2032 $661 $660 4.6% –0.027% $17,842 –$119

2033 $661 $660 4.6% –0.027% $18,097 –$121

2034 $661 $660 4.6% –0.027% $18,353 –$122

2035 $661 $660 4.6% –0.027% $18,608 –$124

2036 $661 $660 4.6% –0.027% $18,863 –$126

NPVb $248,449 –$25,062 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-111

Table 10B-10. Impacts on Agricultural Equipment Market and Manufacturers (51-75 hp)

(Average Price per Equipment = $22,600)a

Agricultural Equipment (50#hp<75) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$5

2008 $226 $167 0.7% –0.006% $1,844 –$582

2009 $225 $167 0.7% –0.006% $1,867 –$583

2010 $214 $157 0.7% –0.010% $1,818 –$592

2011 $213 $156 0.7% –0.019% $1,840 –$615

2012 $212 $155 0.7% –0.024% $1,863 –$627

2013 $978 $856 3.8% –0.025% $9,199 –$1,771

2014 $976 $856 3.8% –0.027% $9,326 –$1,778

2015 $769 $651 2.9% –0.027% $7,616 –$1,778

2016 $767 $651 2.9% –0.027% $7,713 –$1,780

2017 $765 $651 2.9% –0.027% $7,810 –$1,781

2018 $687 $651 2.9% –0.027% $7,086 –$961

2019 $686 $651 2.9% –0.027% $7,183 –$962

2020 $686 $651 2.9% –0.027% $7,280 –$963

2021 $685 $651 2.9% –0.027% $7,377 –$964

2022 $685 $651 2.9% –0.027% $7,474 –$965

2023 $653 $651 2.9% –0.027% $6,681 –$76

2024 $653 $651 2.9% –0.027% $6,777 –$77

2025 $653 $651 2.9% –0.027% $6,874 –$78

2026 $653 $651 2.9% –0.027% $6,971 –$79

2027 $653 $651 2.9% –0.027% $7,068 –$80

2028 $653 $651 2.9% –0.027% $7,165 –$81

2029 $653 $651 2.9% –0.027% $7,262 –$82

2030 $653 $651 2.9% –0.027% $7,359 –$84

2031 $653 $651 2.9% –0.027% $7,456 –$85

2032 $653 $651 2.9% –0.027% $7,553 –$86

2033 $653 $651 2.9% –0.027% $7,650 –$87

2034 $653 $651 2.9% –0.027% $7,747 –$88

2035 $653 $651 2.9% –0.027% $7,844 –$89

2036 $653 $651 2.9% –0.027% $7,941 –$90

NPVb $108,842 –$12,491 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-112

Table 10B-11. Impacts on Agricultural Equipment Market and Manufacturers (76-100 hp)

(Average Price per Equipment = $22,400)a

Agricultural Equipment (70#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$5

2008 — –$1 0.0% –0.006% — –$10

2009 — –$1 0.0% –0.006% — –$10

2010 — –$1 0.0% –0.010% — –$18

2011 — –$3 0.0% –0.019% — –$39

2012 $1,303 $1,175 3.5% –0.024% $13,727 –$2,422

2013 $1,302 $1,175 3.5% –0.025% $13,923 –$2,426

2014 $1,325 $1,166 3.5% –0.027% $14,767 –$3,146

2015 $1,324 $1,166 3.5% –0.027% $14,962 –$3,146

2016 $1,322 $1,166 3.5% –0.027% $15,157 –$3,147

2017 $1,247 $1,166 3.5% –0.027% $14,600 –$2,396

2018 $1,246 $1,166 3.5% –0.027% $14,796 –$2,397

2019 $1,218 $1,166 3.5% –0.027% $14,695 –$2,102

2020 $1,218 $1,166 3.5% –0.027% $14,890 –$2,102

2021 $1,218 $1,166 3.5% –0.027% $15,085 –$2,103

2022 $1,218 $1,166 3.5% –0.027% $13,661 –$485

2023 $1,218 $1,166 3.5% –0.027% $13,857 –$486

2024 $1,218 $1,166 3.5% –0.027% $13,635 –$70

2025 $1,218 $1,166 3.5% –0.027% $13,830 –$71

2026 $1,218 $1,166 3.5% –0.027% $14,026 –$72

2027 $1,218 $1,166 3.5% –0.027% $14,221 –$73

2028 $1,218 $1,166 3.5% –0.027% $14,416 –$74

2029 $1,218 $1,166 3.5% –0.027% $14,612 –$75

2030 $1,218 $1,166 3.5% –0.027% $14,807 –$76

2031 $1,218 $1,166 3.5% –0.027% $15,002 –$77

2032 $1,218 $1,166 3.5% –0.027% $15,198 –$78

2033 $1,218 $1,166 3.5% –0.027% $15,393 –$79

2034 $1,218 $1,166 3.5% –0.027% $15,588 –$80

2035 $1,218 $1,166 3.5% –0.027% $15,784 –$81

2036 $1,218 $1,166 3.5% –0.027% $15,979 –$82

NPVb $206,738 –$18,829 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-113

Table 10B-12. Impacts on Agricultural Equipment Market and Manufacturers (101-175 hp)

(Average Price per Equipment = $69,100)a

Agricultural Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$1 0.0% –0.004% — –$28

2008 — –$1 0.0% –0.006% — –$59

2009 — –$1 0.0% –0.006% — –$60

2010 — –$3 0.0% –0.010% — –$113

2011 — –$6 0.0% –0.019% — –$241

2012 $1,623 $1,414 2.0% –0.024% $50,277 –$9,980

2013 $1,619 $1,414 2.0% –0.025% $50,949 –$10,007

2014 $1,664 $1,391 2.0% –0.027% $53,852 –$12,849

2015 $1,659 $1,391 2.0% –0.027% $54,515 –$12,853

2016 $1,654 $1,391 2.0% –0.027% $55,178 –$12,859

2017 $1,577 $1,391 2.0% –0.027% $53,654 –$10,677

2018 $1,574 $1,391 2.0% –0.027% $54,317 –$10,684

2019 $1,542 $1,391 2.0% –0.027% $54,087 –$9,797

2020 $1,539 $1,391 2.0% –0.027% $54,750 –$9,800

2021 $1,537 $1,391 2.0% –0.027% $55,413 –$9,804

2022 $1,388 $1,391 2.0% –0.027% $48,590 –$2,324

2023 $1,387 $1,391 2.0% –0.027% $49,253 –$2,330

2024 $1,351 $1,391 2.0% –0.027% $48,004 –$424

2025 $1,351 $1,391 2.0% –0.027% $48,667 –$430

2026 $1,351 $1,391 2.0% –0.027% $49,330 –$436

2027 $1,351 $1,391 2.0% –0.027% $49,993 –$442

2028 $1,351 $1,391 2.0% –0.027% $50,656 –$448

2029 $1,351 $1,391 2.0% –0.027% $51,319 –$454

2030 $1,351 $1,391 2.0% –0.027% $51,982 –$460

2031 $1,351 $1,391 2.0% –0.027% $52,645 –$466

2032 $1,351 $1,391 2.0% –0.027% $53,308 –$472

2033 $1,351 $1,391 2.0% –0.027% $53,971 –$478

2034 $1,351 $1,391 2.0% –0.027% $54,634 –$484

2035 $1,351 $1,391 2.0% –0.027% $55,298 –$491

2036 $1,351 $1,391 2.0% –0.027% $55,961 –$497

NPVb $741,939 –$81,965 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-114

Table 10B-13. Impacts on Agricultural Equipment Market and Manufacturers (176-600 hp)

(Average Price per Equipment = $143,700)a

Agricultural Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$1 0.0% –0.004% — –$68

2008 — –$3 0.0% –0.006% — –$143

2009 — –$3 0.0% –0.006% — –$146

2010 — –$6 0.0% –0.010% — –$274

2011 $2,970 $2,255 1.6% –0.019% $129,766 –$33,510

2012 $2,958 $2,251 1.6% –0.024% $131,260 –$33,668

2013 $2,439 $1,741 1.2% –0.025% $110,384 –$33,733

2014 $3,107 $2,200 1.5% –0.027% $142,701 –$44,283

2015 $3,092 $2,199 1.5% –0.027% $144,166 –$44,293

2016 $2,777 $2,198 1.5% –0.027% $131,803 –$30,479

2017 $2,768 $2,197 1.5% –0.027% $133,268 –$30,494

2018 $2,759 $2,197 1.5% –0.027% $134,733 –$30,508

2019 $2,634 $2,196 1.5% –0.027% $130,600 –$24,924

2020 $2,627 $2,195 1.5% –0.027% $132,065 –$24,931

2021 $2,294 $2,194 1.5% –0.027% $114,433 –$5,842

2022 $2,292 $2,194 1.5% –0.027% $115,898 –$5,856

2023 $2,291 $2,193 1.5% –0.027% $117,363 –$5,870

2024 $2,209 $2,192 1.5% –0.027% $113,965 –$1,021

2025 $2,208 $2,191 1.5% –0.027% $115,430 –$1,035

2026 $2,208 $2,191 1.5% –0.027% $116,895 –$1,048

2027 $2,207 $2,190 1.5% –0.027% $118,360 –$1,062

2028 $2,206 $2,189 1.5% –0.027% $119,824 –$1,076

2029 $2,206 $2,189 1.5% –0.027% $121,289 –$1,090

2030 $2,205 $2,188 1.5% –0.027% $122,754 –$1,104

2031 $2,204 $2,187 1.5% –0.027% $124,219 –$1,118

2032 $2,204 $2,187 1.5% –0.027% $125,684 –$1,132

2033 $2,203 $2,186 1.5% –0.027% $127,149 –$1,145

2034 $2,203 $2,186 1.5% –0.027% $128,614 –$1,159

2035 $2,202 $2,185 1.5% –0.027% $130,079 –$1,173

2036 $2,202 $2,185 1.5% –0.027% $131,544 –$1,187

NPVb $1,887,531 –$256,000 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-115

Table 10.B-14. Impacts on Construction Equipment Market and Manufacturers (<25 hp)

(Average Price per Equipment = $18,000)a

Construction Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$3

2008 $177 $129 0.7% –0.006% $370 –$343

2009 $176 $129 0.7% –0.006% $371 –$344

2010 $168 $122 0.7% –0.011% $370 –$350

2011 $167 $122 0.7% –0.021% $371 –$363

2012 $166 $121 0.7% –0.027% $372 –$371

2013 $136 $121 0.7% –0.028% $364 –$365

2014 $136 $121 0.7% –0.031% $365 –$370

2015 $135 $121 0.7% –0.032% $366 –$372

2016 $135 $121 0.7% –0.032% $367 –$373

2017 $135 $121 0.7% –0.032% $368 –$374

2018 $123 $121 0.7% –0.032% $39 –$46

2019 $123 $121 0.7% –0.032% $40 –$47

2020 $123 $121 0.7% –0.032% $41 –$48

2021 $123 $121 0.7% –0.032% $42 –$48

2022 $123 $121 0.7% –0.032% $42 –$49

2023 $123 $121 0.7% –0.032% $43 –$50

2024 $123 $121 0.7% –0.032% $44 –$51

2025 $123 $121 0.7% –0.032% $45 –$52

2026 $123 $121 0.7% –0.032% $46 –$53

2027 $123 $121 0.7% –0.032% $47 –$54

2028 $123 $121 0.7% –0.032% $47 –$55

2029 $123 $121 0.7% –0.032% $48 –$56

2030 $123 $121 0.7% –0.032% $49 –$57

2031 $123 $121 0.7% –0.032% $50 –$58

2032 $123 $121 0.7% –0.032% $51 –$59

2033 $123 $121 0.7% –0.032% $52 –$60

2034 $123 $121 0.7% –0.032% $52 –$61

2035 $123 $121 0.7% –0.032% $53 –$62

2036 $123 $121 0.7% –0.032% $54 –$63

NPVb $3,325 –$3,348 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-116

Table 10.B-15. Impacts on Construction Equipment Market and Manufacturers (26-50 hp)

(Average Price per Equipment = $29,700)a

Construction Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$8

2008 $204 $146 0.5% –0.006% $438 –$345

2009 $203 $146 0.5% –0.006% $440 –$345

2010 $194 $138 0.5% –0.011% $437 –$362

2011 $193 $137 0.5% –0.021% $439 –$397

2012 $192 $137 0.5% –0.027% $441 –$420

2013 $986 $867 2.9% –0.028% $3,293 –$1,864

2014 $984 $867 2.9% –0.031% $3,323 –$1,875

2015 $773 $659 2.2% –0.032% $3,006 –$1,882

2016 $771 $659 2.2% –0.032% $3,030 –$1,884

2017 $769 $659 2.2% –0.032% $3,053 –$1,885

2018 $693 $659 2.2% –0.032% $2,723 –$1,534

2019 $692 $659 2.2% –0.032% $2,747 –$1,536

2020 $692 $659 2.2% –0.032% $2,770 –$1,538

2021 $691 $659 2.2% –0.032% $2,794 –$1,540

2022 $691 $659 2.2% –0.032% $2,817 –$1,543

2023 $661 $659 2.2% –0.032% $1,428 –$132

2024 $661 $659 2.2% –0.032% $1,451 –$134

2025 $661 $659 2.2% –0.032% $1,475 –$137

2026 $661 $659 2.2% –0.032% $1,498 –$139

2027 $661 $659 2.2% –0.032% $1,521 –$141

2028 $661 $659 2.2% –0.032% $1,545 –$143

2029 $661 $659 2.2% –0.032% $1,568 –$145

2030 $661 $659 2.2% –0.032% $1,592 –$148

2031 $661 $659 2.2% –0.032% $1,615 –$150

2032 $661 $659 2.2% –0.032% $1,639 –$152

2033 $661 $659 2.2% –0.032% $1,662 –$154

2034 $661 $659 2.2% –0.032% $1,685 –$156

2035 $661 $659 2.2% –0.032% $1,709 –$159

2036 $661 $659 2.2% –0.032% $1,732 –$161

NPVb $32,256 –$14,120 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-117

Table 10.B-16. Impacts on Construction Equipment Market and Manufacturers (51-75 hp)

(Average Price per Equipment = $31,600)a

Construction Equipment (50#hp<70) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$8

2008 $226 $167 0.5% –0.006% $1,983 –$710

2009 $225 $167 0.5% –0.006% $2,007 –$711

2010 $214 $157 0.5% –0.011% $1,957 –$728

2011 $213 $156 0.5% –0.021% $1,980 –$764

2012 $212 $155 0.5% –0.027% $2,002 –$788

2013 $978 $856 2.7% –0.028% $10,288 –$2,484

2014 $976 $856 2.7% –0.031% $10,422 –$2,495

2015 $769 $650 2.1% –0.032% $8,629 –$2,502

2016 $767 $650 2.1% –0.032% $8,731 –$2,504

2017 $765 $650 2.1% –0.032% $8,834 –$2,505

2018 $687 $650 2.1% –0.032% $7,991 –$1,561

2019 $686 $650 2.1% –0.032% $8,093 –$1,563

2020 $686 $650 2.1% –0.032% $8,196 –$1,565

2021 $685 $650 2.1% –0.032% $8,298 –$1,567

2022 $685 $650 2.1% –0.032% $8,401 –$1,569

2023 $653 $650 2.1% –0.032% $7,067 –$134

2024 $653 $650 2.1% –0.032% $7,169 –$136

2025 $653 $650 2.1% –0.032% $7,272 –$138

2026 $653 $650 2.1% –0.032% $7,374 –$140

2027 $653 $650 2.1% –0.032% $7,477 –$142

2028 $653 $650 2.1% –0.032% $7,580 –$144

2029 $653 $650 2.1% –0.032% $7,682 –$146

2030 $653 $650 2.1% –0.032% $7,785 –$148

2031 $653 $650 2.1% –0.032% $7,887 –$150

2032 $653 $650 2.1% –0.032% $7,990 –$152

2033 $653 $650 2.1% –0.032% $8,092 –$154

2034 $653 $650 2.1% –0.032% $8,195 –$156

2035 $653 $650 2.1% –0.032% $8,297 –$158

2036 $653 $650 2.1% –0.032% $8,400 –$160

NPVb $118,863 –$17,987 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-118

Table 10.B-17 Impacts on Construction Equipment Market and Manufacturers (76-100 hp)

(Average Price per Equipment = $57,900)a

Construction Equipment (70#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% –0.004% — –$15

2008 — –$1 0.0% –0.006% — –$30

2009 — –$1 0.0% –0.006% — –$31

2010 — –$2 0.0% –0.011% — –$62

2011 — –$3 0.0% –0.021% — –$127

2012 $1,303 $1,174 2.0% –0.027% $23,156 –$5,449

2013 $1,302 $1,174 2.0% –0.028% $23,465 –$5,460

2014 $1,325 $1,165 2.0% –0.031% $25,237 –$6,995

2015 $1,324 $1,164 2.0% –0.032% $25,545 –$7,007

2016 $1,322 $1,164 2.0% –0.032% $25,854 –$7,011

2017 $1,247 $1,164 2.0% –0.032% $25,024 –$5,875

2018 $1,246 $1,164 2.0% –0.032% $25,333 –$5,879

2019 $1,218 $1,164 2.0% –0.032% $25,192 –$5,434

2020 $1,218 $1,164 2.0% –0.032% $25,501 –$5,437

2021 $1,218 $1,164 2.0% –0.032% $25,809 –$5,440

2022 $1,218 $1,164 2.0% –0.032% $21,977 –$1,303

2023 $1,218 $1,164 2.0% –0.032% $22,285 –$1,306

2024 $1,218 $1,164 2.0% –0.032% $21,527 –$244

2025 $1,218 $1,164 2.0% –0.032% $21,836 –$247

2026 $1,218 $1,164 2.0% –0.032% $22,144 –$251

2027 $1,218 $1,164 2.0% –0.032% $22,452 –$254

2028 $1,218 $1,164 2.0% –0.032% $22,761 –$258

2029 $1,218 $1,164 2.0% –0.032% $23,069 –$262

2030 $1,218 $1,164 2.0% –0.032% $23,377 –$265

2031 $1,218 $1,164 2.0% –0.032% $23,686 –$269

2032 $1,218 $1,164 2.0% –0.032% $23,994 –$272

2033 $1,218 $1,164 2.0% –0.032% $24,303 –$276

2034 $1,218 $1,164 2.0% –0.032% $24,611 –$279

2035 $1,218 $1,164 2.0% –0.032% $24,919 –$283

2036 $1,218 $1,164 2.0% –0.032% $25,228 –$287

NPVb $339,723 –$45,057 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-119

Table 10.B-18. Impacts on Construction Equipment Market and Manufacturers (101-175 hp)

(Average Price per Equipment = $122,700)a

Construction Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$1 0.0% –0.004% — –$51

2008 — –$2 0.0% –0.006% — –$105

2009 — –$2 0.0% –0.006% — –$107

2010 — –$4 0.0% –0.011% — –$215

2011 — –$7 0.0% –0.021% — –$438

2012 $1,623 $1,412 1.2% –0.027% $68,698 –$14,076

2013 $1,619 $1,411 1.2% –0.028% $69,612 –$14,114

2014 $1,664 $1,389 1.1% –0.031% $73,652 –$18,081

2015 $1,659 $1,388 1.1% –0.032% $74,553 –$18,122

2016 $1,654 $1,388 1.1% –0.032% $75,455 –$18,134

2017 $1,577 $1,388 1.1% –0.032% $73,387 –$15,171

2018 $1,574 $1,388 1.1% –0.032% $74,289 –$15,183

2019 $1,542 $1,388 1.1% –0.032% $73,979 –$13,984

2020 $1,539 $1,388 1.1% –0.032% $74,881 –$13,994

2021 $1,537 $1,388 1.1% –0.032% $75,783 –$14,004

2022 $1,388 $1,388 1.1% –0.032% $66,164 –$3,496

2023 $1,387 $1,388 1.1% –0.032% $67,065 –$3,508

2024 $1,351 $1,388 1.1% –0.032% $65,280 –$833

2025 $1,351 $1,388 1.1% –0.032% $66,182 –$844

2026 $1,351 $1,388 1.1% –0.032% $67,083 –$856

2027 $1,351 $1,388 1.1% –0.032% $67,985 –$868

2028 $1,351 $1,388 1.1% –0.032% $68,887 –$880

2029 $1,351 $1,388 1.1% –0.032% $69,788 –$891

2030 $1,351 $1,388 1.1% –0.032% $70,690 –$903

2031 $1,351 $1,388 1.1% –0.032% $71,592 –$915

2032 $1,351 $1,388 1.1% –0.032% $72,493 –$927

2033 $1,351 $1,388 1.1% –0.032% $73,395 –$939

2034 $1,351 $1,388 1.1% –0.032% $74,297 –$950

2035 $1,351 $1,388 1.1% –0.032% $75,198 –$962

2036 $1,351 $1,388 1.1% –0.032% $76,100 –$974

NPVb $1,011,838 –$118,002 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-120

Table 10.B-19. Impacts on Construction Equipment Market and Manufacturers (176-600 hp)

(Average Price per Equipment = $312,900)a

Construction Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$2 0.0% –0.004% — –$110

2008 — –$5 0.0% –0.006% — –$225

2009 — –$5 0.0% –0.006% — –$229

2010 — –$9 0.0% –0.011% — –$461

2011 $2,970 $2,248 0.7% –0.021% $103,262 –$30,609

2012 $2,958 $2,241 0.7% –0.027% $104,397 –$30,925

2013 $2,439 $1,731 0.6% –0.028% $88,557 –$31,005

2014 $3,107 $2,189 0.7% –0.031% $114,342 –$40,265

2015 $3,092 $2,187 0.7% –0.032% $115,456 –$40,352

2016 $2,777 $2,186 0.7% –0.032% $106,203 –$30,010

2017 $2,768 $2,185 0.7% –0.032% $107,317 –$30,022

2018 $2,759 $2,184 0.7% –0.032% $108,431 –$30,046

2019 $2,634 $2,184 0.7% –0.032% $105,349 –$25,874

2020 $2,627 $2,183 0.7% –0.032% $106,462 –$25,894

2021 $2,294 $2,182 0.7% –0.032% $88,274 –$6,612

2022 $2,292 $2,181 0.7% –0.032% $89,388 –$6,637

2023 $2,291 $2,181 0.7% –0.032% $90,502 –$6,661

2024 $2,209 $2,180 0.7% –0.032% $86,700 –$1,769

2025 $2,208 $2,179 0.7% –0.032% $87,814 –$1,793

2026 $2,208 $2,178 0.7% –0.032% $88,928 –$1,817

2027 $2,207 $2,178 0.7% –0.032% $90,042 –$1,841

2028 $2,206 $2,177 0.7% –0.032% $91,156 –$1,865

2029 $2,206 $2,176 0.7% –0.032% $92,270 –$1,889

2030 $2,205 $2,176 0.7% –0.032% $93,384 –$1,913

2031 $2,204 $2,175 0.7% –0.032% $94,498 –$1,936

2032 $2,204 $2,175 0.7% –0.032% $95,612 –$1,960

2033 $2,203 $2,174 0.7% –0.032% $96,726 –$1,984

2034 $2,203 $2,173 0.7% –0.032% $97,839 –$2,008

2035 $2,202 $2,173 0.7% –0.032% $98,953 –$2,032

2036 $2,202 $2,172 0.7% –0.032% $100,067 –$2,056

NPVb $1,477,053 –$250,397 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-121

Table 10.B-20. Impacts on Construction Equipment Market and Manufacturers (>600 hp)

(Average Price per Equipment = $847,400)a

Construction Equipment ($600hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — –$6 0.0% –0.004% — –$31

2008 — –$11 0.0% –0.006% — –$63

2009 — –$11 0.0% –0.006% — –$65

2010 — –$22 0.0% –0.011% — –$130

2011 $4,519 $2,923 0.4% –0.021% $23,207 –$8,646

2012 $4,496 $2,909 0.4% –0.027% $23,431 –$8,735

2013 $3,797 $2,230 0.3% –0.028% $20,179 –$8,757

2014 $4,684 $2,727 0.4% –0.031% $25,243 –$11,056

2015 $9,206 $6,205 0.8% –0.032% $50,150 –$17,335

2016 $8,364 $6,205 0.8% –0.032% $46,344 –$13,058

2017 $7,517 $5,387 0.7% –0.032% $42,363 –$13,061

2018 $7,489 $5,387 0.7% –0.032% $42,777 –$13,068

2019 $7,218 $5,387 0.7% –0.032% $41,837 –$11,720

2020 $6,767 $5,388 0.7% –0.032% $39,833 –$9,307

2021 $6,151 $5,388 0.7% –0.032% $36,149 –$5,214

2022 $6,142 $5,388 0.7% –0.032% $36,563 –$5,221

2023 $6,133 $5,388 0.7% –0.032% $36,978 –$5,227

2024 $5,997 $5,388 0.7% –0.032% $36,488 –$4,330

2025 $5,458 $5,388 0.7% –0.032% $33,066 –$500

2026 $5,458 $5,388 0.7% –0.032% $33,480 –$506

2027 $5,458 $5,388 0.7% –0.032% $33,895 –$513

2028 $5,458 $5,388 0.7% –0.032% $34,309 –$519

2029 $5,458 $5,388 0.7% –0.032% $34,724 –$526

2030 $5,458 $5,388 0.7% –0.032% $35,138 –$532

2031 $5,458 $5,388 0.7% –0.032% $35,552 –$539

2032 $5,458 $5,388 0.7% –0.032% $35,967 –$545

2033 $5,458 $5,388 0.7% –0.032% $36,381 –$551

2034 $5,458 $5,388 0.7% –0.032% $36,795 –$558

2035 $5,458 $5,388 0.7% –0.032% $37,210 –$564

2036 $5,458 $5,388 0.7% –0.032% $37,624 –$571

NPVb $527,785 –$96,188 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-122

Table 10B-21. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (<25 hp)

(Average Price per Equipment = $6,000)a

Pumps and Compressor Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $177 $129 2.2% –0.001% $96 –$96

2009 $176 $129 2.2% –0.001% $96 –$96

2010 $168 $123 2.0% –0.001% $96 –$96

2011 $167 $123 2.0% –0.002% $96 –$97

2012 $166 $123 2.0% –0.003% $96 –$97

2013 $136 $123 2.0% –0.003% $96 –$97

2014 $136 $123 2.0% –0.003% $96 –$97

2015 $135 $123 2.0% –0.003% $96 –$97

2016 $135 $123 2.0% –0.003% $96 –$97

2017 $135 $123 2.0% –0.003% $96 –$97

2018 $123 $123 2.0% –0.003% — –$1

2019 $123 $123 2.0% –0.003% — –$1

2020 $123 $123 2.0% –0.003% — –$1

2021 $123 $123 2.0% –0.003% — –$1

2022 $123 $123 2.0% –0.003% — –$1

2023 $123 $123 2.0% –0.003% — –$1

2024 $123 $123 2.0% –0.003% — –$1

2025 $123 $123 2.0% –0.003% — –$1

2026 $123 $123 2.0% –0.003% — –$1

2027 $123 $123 2.0% –0.003% — –$1

2028 $123 $123 2.0% –0.003% — –$1

2029 $123 $123 2.0% –0.003% — –$1

2030 $123 $123 2.0% –0.003% — –$1

2031 $123 $123 2.0% –0.003% — –$1

2032 $123 $123 2.0% –0.003% — –$1

2033 $123 $123 2.0% –0.003% — –$1

2034 $123 $123 2.0% –0.003% — –$1

2035 $123 $123 2.0% –0.003% — –$1

2036 $123 $123 2.0% –0.003% — –$1

NPVb $752 –$760 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-123

Table 10B-22. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (26-50 hp)

(Average Price per Equipment = $12,200)a

Pumps and Compressor Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $204 $147 1.2% –0.001% $41 –$41

2009 $203 $147 1.2% –0.001% $41 –$41

2010 $194 $139 1.1% –0.001% $41 –$41

2011 $193 $139 1.1% –0.002% $41 –$42

2012 $192 $139 1.1% –0.003% $41 –$42

2013 $986 $870 7.1% –0.003% $356 –$241

2014 $984 $870 7.1% –0.003% $359 –$241

2015 $773 $661 5.4% –0.003% $337 –$241

2016 $771 $661 5.4% –0.003% $339 –$241

2017 $769 $661 5.4% –0.003% $340 –$241

2018 $693 $661 5.4% –0.003% $301 –$200

2019 $692 $661 5.4% –0.003% $303 –$200

2020 $692 $661 5.4% –0.003% $305 –$200

2021 $691 $661 5.4% –0.003% $307 –$200

2022 $691 $661 5.4% –0.003% $309 –$200

2023 $661 $661 5.4% –0.003% $112 –$1

2024 $661 $661 5.4% –0.003% $113 –$1

2025 $661 $661 5.4% –0.003% $115 –$1

2026 $661 $661 5.4% –0.003% $117 –$1

2027 $661 $661 5.4% –0.003% $119 –$1

2028 $661 $661 5.4% –0.003% $121 –$1

2029 $661 $661 5.4% –0.003% $123 –$1

2030 $661 $661 5.4% –0.003% $124 –$1

2031 $661 $661 5.4% –0.003% $126 –$1

2032 $661 $661 5.4% –0.003% $128 –$1

2033 $661 $661 5.4% –0.003% $130 –$1

2034 $661 $661 5.4% –0.003% $132 –$1

2035 $661 $661 5.4% –0.003% $134 –$1

2036 $661 $661 5.4% –0.003% $135 –$1

NPVb $3,189 –$1,673 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-124

Table 10B-23. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (51-75 hp)

(Average Price per Equipment = $10,600)a

Pumps and Compressor Equipment (50#hp<70) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $226 $167 1.6% –0.001% $39 –$39

2009 $225 $167 1.6% –0.001% $39 –$39

2010 $214 $158 1.5% –0.001% $39 –$39

2011 $213 $158 1.5% –0.002% $39 –$39

2012 $212 $158 1.5% –0.003% $39 –$39

2013 $978 $858 8.1% –0.003% $328 –$222

2014 $976 $858 8.1% –0.003% $329 –$222

2015 $769 $653 6.2% –0.003% $309 –$222

2016 $767 $653 6.2% –0.003% $311 –$222

2017 $765 $653 6.2% –0.003% $312 –$222

2018 $687 $653 6.2% –0.003% $275 –$183

2019 $686 $653 6.2% –0.003% $276 –$183

2020 $686 $653 6.2% –0.003% $278 –$183

2021 $685 $653 6.2% –0.003% $279 –$183

2022 $685 $653 6.2% –0.003% $281 –$183

2023 $653 $653 6.2% –0.003% $99 –$1

2024 $653 $653 6.2% –0.003% $101 –$1

2025 $653 $653 6.2% –0.003% $102 –$1

2026 $653 $653 6.2% –0.003% $104 –$1

2027 $653 $653 6.2% –0.003% $105 –$1

2028 $653 $653 6.2% –0.003% $107 –$1

2029 $653 $653 6.2% –0.003% $108 –$1

2030 $653 $653 6.2% –0.003% $110 –$1

2031 $653 $653 6.2% –0.003% $111 –$1

2032 $653 $653 6.2% –0.003% $112 –$1

2033 $653 $653 6.2% –0.003% $114 –$1

2034 $653 $653 6.2% –0.003% $115 –$1

2035 $653 $653 6.2% –0.003% $117 –$1

2036 $653 $653 6.2% –0.003% $118 –$1

NPVb $2,896 –$1,542 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-125

Table 10B-24. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (76-100 hp)

(Average Price per Equipment = $12,500)a

Pumps and Compressor Equipment (70#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 — — 0.0% –0.002% — —

2012 $1,303 $1,178 9.4% –0.003% $823 –$583

2013 $1,302 $1,178 9.4% –0.003% $827 –$583

2014 $1,325 $1,169 9.4% –0.003% $998 –$733

2015 $1,324 $1,169 9.4% –0.003% $1,003 –$733

2016 $1,322 $1,169 9.4% –0.003% $1,007 –$733

2017 $1,247 $1,169 9.4% –0.003% $1,011 –$733

2018 $1,246 $1,169 9.4% –0.003% $1,016 –$733

2019 $1,218 $1,169 9.4% –0.003% $1,020 –$733

2020 $1,218 $1,169 9.4% –0.003% $1,025 –$733

2021 $1,218 $1,169 9.4% –0.003% $1,029 –$733

2022 $1,218 $1,169 9.4% –0.003% $452 –$151

2023 $1,218 $1,169 9.4% –0.003% $456 –$151

2024 $1,218 $1,169 9.4% –0.003% $311 –$1

2025 $1,218 $1,169 9.4% –0.003% $315 –$1

2026 $1,218 $1,169 9.4% –0.003% $320 –$1

2027 $1,218 $1,169 9.4% –0.003% $324 –$1

2028 $1,218 $1,169 9.4% –0.003% $328 –$1

2029 $1,218 $1,169 9.4% –0.003% $333 –$1

2030 $1,218 $1,169 9.4% –0.003% $337 –$1

2031 $1,218 $1,169 9.4% –0.003% $342 –$1

2032 $1,218 $1,169 9.4% –0.003% $346 –$1

2033 $1,218 $1,169 9.4% –0.003% $351 –$1

2034 $1,218 $1,169 9.4% –0.003% $355 –$1

2035 $1,218 $1,169 9.4% –0.003% $360 –$1

2036 $1,218 $1,169 9.4% –0.003% $364 –$1

NPVb $9,294 –$5,030 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-126

Table 10B-25. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (101-175 hp)

(Average Price per Equipment = $23,800)a

Pumps and Compressor Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 — — 0.0% –0.002% — —

2012 $1,623 $1,421 6.0% –0.003% $266 –$210

2013 $1,619 $1,421 6.0% –0.003% $267 –$210

2014 $1,664 $1,399 5.9% –0.003% $325 –$263

2015 $1,659 $1,399 5.9% –0.003% $326 –$263

2016 $1,654 $1,399 5.9% –0.003% $327 –$263

2017 $1,577 $1,399 5.9% –0.003% $328 –$263

2018 $1,574 $1,399 5.9% –0.003% $329 –$263

2019 $1,542 $1,399 5.9% –0.003% $330 –$263

2020 $1,539 $1,399 5.9% –0.003% $331 –$263

2021 $1,537 $1,399 5.9% –0.003% $332 –$263

2022 $1,388 $1,399 5.9% –0.003% $124 –$54

2023 $1,387 $1,399 5.9% –0.003% $125 –$54

2024 $1,351 $1,399 5.9% –0.003% $72 —

2025 $1,351 $1,399 5.9% –0.003% $73 —

2026 $1,351 $1,399 5.9% –0.003% $74 —

2027 $1,351 $1,399 5.9% –0.003% $75 —

2028 $1,351 $1,399 5.9% –0.003% $76 —

2029 $1,351 $1,399 5.9% –0.003% $77 —

2030 $1,351 $1,399 5.9% –0.003% $78 —

2031 $1,351 $1,399 5.9% –0.003% $79 —

2032 $1,351 $1,399 5.9% –0.003% $80 —

2033 $1,351 $1,399 5.9% –0.003% $81 —

2034 $1,351 $1,399 5.9% –0.003% $82 —

2035 $1,351 $1,399 5.9% –0.003% $83 —

2036 $1,351 $1,399 5.9% –0.003% $84 —

NPVb $2,796 –$1,807 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-127

Table 10B-26. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (176-600 hp)

(Average Price per Equipment = $53,000)a

Pumps and Compressor Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — –$1 0.0% –0.001% — —

2011 $2,970 $2,265 4.3% –0.002% $821 –$685

2012 $2,958 $2,264 4.3% –0.003% $823 –$685

2013 $2,439 $1,755 3.3% –0.003% $797 –$686

2014 $3,107 $2,216 4.2% –0.003% $1,010 –$860

2015 $3,092 $2,215 4.2% –0.003% $1,012 –$860

2016 $2,777 $2,214 4.2% –0.003% $1,015 –$860

2017 $2,768 $2,213 4.2% –0.003% $1,017 –$860

2018 $2,759 $2,212 4.2% –0.003% $1,019 –$860

2019 $2,634 $2,211 4.2% –0.003% $1,021 –$860

2020 $2,627 $2,210 4.2% –0.003% $1,023 –$860

2021 $2,294 $2,210 4.2% –0.003% $341 –$176

2022 $2,292 $2,209 4.2% –0.003% $343 –$176

2023 $2,291 $2,208 4.2% –0.003% $345 –$176

2024 $2,209 $2,207 4.2% –0.003% $173 –$1

2025 $2,208 $2,207 4.2% –0.003% $175 –$1

2026 $2,208 $2,206 4.2% –0.003% $177 –$1

2027 $2,207 $2,205 4.2% –0.003% $180 –$1

2028 $2,206 $2,205 4.2% –0.003% $182 –$1

2029 $2,206 $2,204 4.2% –0.003% $184 –$1

2030 $2,205 $2,203 4.2% –0.003% $186 –$1

2031 $2,204 $2,203 4.2% –0.003% $188 –$1

2032 $2,204 $2,202 4.2% –0.003% $190 –$1

2033 $2,203 $2,202 4.2% –0.003% $192 –$1

2034 $2,203 $2,201 4.2% –0.003% $195 –$1

2035 $2,202 $2,200 4.2% –0.003% $197 –$1

2036 $2,202 $2,200 4.2% –0.003% $199 –$1

NPVb $8,508 –$6,048 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-128

Table 10B-27. Impacts on Pumps and Compressor Equipment Market and 

Manufacturers (>600 hp)

(Average Price per Equipment = $88,000)a

Pumps and Compressor Equipment ($600hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — –$1 0.0% –0.001% — —

2009 — –$1 0.0% –0.001% — —

2010 — –$2 0.0% –0.001% — —

2011 $4,519 $2,965 3.4% –0.002% $15 –$14

2012 $4,496 $2,964 3.4% –0.003% $15 –$14

2013 $3,797 $2,287 2.6% –0.003% $14 –$14

2014 $4,684 $2,790 3.2% –0.003% $18 –$16

2015 $9,206 $6,271 7.1% –0.003% $32 –$29

2016 $8,364 $6,271 7.1% –0.003% $32 –$29

2017 $7,517 $5,453 6.2% –0.003% $31 –$29

2018 $7,489 $5,453 6.2% –0.003% $31 –$29

2019 $7,218 $5,453 6.2% –0.003% $32 –$29

2020 $6,767 $5,453 6.2% –0.003% $32 –$29

2021 $6,151 $5,453 6.2% –0.003% $18 –$16

2022 $6,142 $5,453 6.2% –0.003% $18 –$16

2023 $6,133 $5,453 6.2% –0.003% $18 –$16

2024 $5,997 $5,453 6.2% –0.003% $15 –$13

2025 $5,458 $5,453 6.2% –0.003% $3 —

2026 $5,458 $5,453 6.2% –0.003% $3 —

2027 $5,458 $5,453 6.2% –0.003% $3 —

2028 $5,458 $5,453 6.2% –0.003% $3 —

2029 $5,458 $5,453 6.2% –0.003% $3 —

2030 $5,458 $5,453 6.2% –0.003% $3 —

2031 $5,458 $5,453 6.2% –0.003% $3 —

2032 $5,458 $5,453 6.2% –0.003% $3 —

2033 $5,458 $5,453 6.2% –0.003% $3 —

2034 $5,458 $5,453 6.2% –0.003% $3 —

2035 $5,458 $5,453 6.2% –0.003% $3 —

2036 $5,458 $5,453 6.2% –0.003% $3 —

NPVb $231 –$196 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-129

Table 10.B-28. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (<25 hp)

(Average Price per Equipment = $6,800)a

Generator Sets and Welding Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $177 $129 1.9% –0.001% $3,795 –$1,615

2009 $176 $129 1.9% –0.001% $3,854 –$1,615

2010 $168 $123 1.8% –0.001% $3,794 –$1,616

2011 $167 $123 1.8% –0.002% $3,850 –$1,618

2012 $166 $123 1.8% –0.003% $3,906 –$1,619

2013 $136 $123 1.8% –0.003% $3,410 –$1,068

2014 $136 $123 1.8% –0.003% $3,466 –$1,069

2015 $135 $123 1.8% –0.003% $3,522 –$1,069

2016 $135 $123 1.8% –0.003% $3,578 –$1,069

2017 $135 $123 1.8% –0.003% $3,634 –$1,069

2018 $123 $123 1.8% –0.003% $2,627 –$6

2019 $123 $123 1.8% –0.003% $2,683 –$7

2020 $123 $123 1.8% –0.003% $2,739 –$7

2021 $123 $123 1.8% –0.003% $2,795 –$7

2022 $123 $123 1.8% –0.003% $2,851 –$7

2023 $123 $123 1.8% –0.003% $2,907 –$7

2024 $123 $123 1.8% –0.003% $2,963 –$7

2025 $123 $123 1.8% –0.003% $3,019 –$7

2026 $123 $123 1.8% –0.003% $3,075 –$7

2027 $123 $123 1.8% –0.003% $3,131 –$8

2028 $123 $123 1.8% –0.003% $3,187 –$8

2029 $123 $123 1.8% –0.003% $3,243 –$8

2030 $123 $123 1.8% –0.003% $3,299 –$8

2031 $123 $123 1.8% –0.003% $3,355 –$8

2032 $123 $123 1.8% –0.003% $3,411 –$8

2033 $123 $123 1.8% –0.003% $3,467 –$8

2034 $123 $123 1.8% –0.003% $3,523 –$9

2035 $123 $123 1.8% –0.003% $3,579 –$9

2036 $123 $123 1.8% –0.003% $3,634 –$9

NPVb $58,866 –$10,712 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-130

Table 10.B-29. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (26-50 hp)

(Average Price per Equipment = $8,700)a

Generator Sets and Welding Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $204 $147 1.7% –0.001% $1,896 –$713

2009 $203 $147 1.7% –0.001% $1,922 –$713

2010 $194 $139 1.6% –0.001% $1,883 –$714

2011 $193 $139 1.6% –0.002% $1,907 –$715

2012 $192 $139 1.6% –0.003% $1,932 –$716

2013 $986 $870 10.0% –0.003% $10,977 –$2,502

2014 $984 $870 10.0% –0.003% $11,143 –$2,502

2015 $773 $661 7.6% –0.003% $9,227 –$2,502

2016 $771 $661 7.6% –0.003% $9,354 –$2,502

2017 $769 $661 7.6% –0.003% $9,481 –$2,502

2018 $693 $661 7.6% –0.003% $8,631 –$1,525

2019 $692 $661 7.6% –0.003% $8,758 –$1,525

2020 $692 $661 7.6% –0.003% $8,885 –$1,525

2021 $691 $661 7.6% –0.003% $9,012 –$1,525

2022 $691 $661 7.6% –0.003% $9,139 –$1,525

2023 $661 $661 7.6% –0.003% $7,746 –$5

2024 $661 $661 7.6% –0.003% $7,873 –$5

2025 $661 $661 7.6% –0.003% $8,000 –$5

2026 $661 $661 7.6% –0.003% $8,127 –$5

2027 $661 $661 7.6% –0.003% $8,254 –$5

2028 $661 $661 7.6% –0.003% $8,381 –$5

2029 $661 $661 7.6% –0.003% $8,508 –$5

2030 $661 $661 7.6% –0.003% $8,635 –$5

2031 $661 $661 7.6% –0.003% $8,762 –$5

2032 $661 $661 7.6% –0.003% $8,889 –$5

2033 $661 $661 7.6% –0.003% $9,017 –$6

2034 $661 $661 7.6% –0.003% $9,144 –$6

2035 $661 $661 7.6% –0.003% $9,271 –$6

2036 $661 $661 7.6% –0.003% $9,398 –$6

NPVb $128,538 –$16,831 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-131

Table 10.B-30. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (51-75 hp)

(Average Price per Equipment = $8,300)a

Generator Sets and Welding Equipment (50#hp<70) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $226 $167 2.0% –0.001% $2,029 –$570

2009 $225 $167 2.0% –0.001% $2,056 –$570

2010 $214 $158 1.9% –0.001% $2,000 –$570

2011 $213 $158 1.9% –0.002% $2,025 –$571

2012 $212 $158 1.9% –0.003% $2,051 –$571

2013 $978 $858 10.3% –0.003% $9,825 –$1,472

2014 $976 $858 10.3% –0.003% $9,966 –$1,472

2015 $769 $653 7.9% –0.003% $8,049 –$1,472

2016 $767 $653 7.9% –0.003% $8,157 –$1,472

2017 $765 $653 7.9% –0.003% $8,265 –$1,472

2018 $687 $653 7.9% –0.003% $7,518 –$617

2019 $686 $653 7.9% –0.003% $7,626 –$617

2020 $686 $653 7.9% –0.003% $7,734 –$617

2021 $685 $653 7.9% –0.003% $7,842 –$617

2022 $685 $653 7.9% –0.003% $7,950 –$617

2023 $653 $653 7.9% –0.003% $7,443 –$2

2024 $653 $653 7.9% –0.003% $7,551 –$2

2025 $653 $653 7.9% –0.003% $7,659 –$2

2026 $653 $653 7.9% –0.003% $7,767 –$2

2027 $653 $653 7.9% –0.003% $7,875 –$2

2028 $653 $653 7.9% –0.003% $7,983 –$2

2029 $653 $653 7.9% –0.003% $8,091 –$2

2030 $653 $653 7.9% –0.003% $8,199 –$2

2031 $653 $653 7.9% –0.003% $8,307 –$2

2032 $653 $653 7.9% –0.003% $8,415 –$2

2033 $653 $653 7.9% –0.003% $8,523 –$2

2034 $653 $653 7.9% –0.003% $8,631 –$2

2035 $653 $653 7.9% –0.003% $8,739 –$2

2036 $653 $653 7.9% –0.003% $8,847 –$2

NPVb $118,426 –$9,648 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-132

Table 10.B-31. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (76-100 hp)

(Average Price per Equipment = $18,000)a

Generator Sets and Welding Equipment (70#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 — — 0.0% –0.002% — –$1

2012 $1,303 $1,178 6.5% –0.003% $2,241 –$842

2013 $1,302 $1,178 6.5% –0.003% $2,265 –$842

2014 $1,325 $1,169 6.5% –0.003% $2,527 –$1,069

2015 $1,324 $1,169 6.5% –0.003% $2,552 –$1,069

2016 $1,322 $1,169 6.5% –0.003% $2,576 –$1,069

2017 $1,247 $1,169 6.5% –0.003% $2,524 –$993

2018 $1,246 $1,169 6.5% –0.003% $2,548 –$993

2019 $1,218 $1,169 6.5% –0.003% $2,543 –$963

2020 $1,218 $1,169 6.5% –0.003% $2,567 –$963

2021 $1,218 $1,169 6.5% –0.003% $2,592 –$963

2022 $1,218 $1,169 6.5% –0.003% $1,851 –$198

2023 $1,218 $1,169 6.5% –0.003% $1,876 –$199

2024 $1,218 $1,169 6.5% –0.003% $1,703 –$2

2025 $1,218 $1,169 6.5% –0.003% $1,727 –$2

2026 $1,218 $1,169 6.5% –0.003% $1,752 –$2

2027 $1,218 $1,169 6.5% –0.003% $1,776 –$2

2028 $1,218 $1,169 6.5% –0.003% $1,801 –$2

2029 $1,218 $1,169 6.5% –0.003% $1,825 –$2

2030 $1,218 $1,169 6.5% –0.003% $1,849 –$2

2031 $1,218 $1,169 6.5% –0.003% $1,874 –$2

2032 $1,218 $1,169 6.5% –0.003% $1,898 –$2

2033 $1,218 $1,169 6.5% –0.003% $1,923 –$2

2034 $1,218 $1,169 6.5% –0.003% $1,947 –$2

2035 $1,218 $1,169 6.5% –0.003% $1,971 –$2

2036 $1,218 $1,169 6.5% –0.003% $1,996 –$2

NPVb $30,552 –$7,004 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-133

Table 10.B-32. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (101-175 hp)

(Average Price per Equipment = $21,400)a

Generator Sets and Welding Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — –$1

2011 — — 0.0% –0.002% — –$1

2012 $1,623 $1,421 6.6% –0.003% $11,755 –$2,081

2013 $1,619 $1,421 6.6% –0.003% $11,915 –$2,081

2014 $1,664 $1,399 6.5% –0.003% $12,544 –$2,692

2015 $1,659 $1,399 6.5% –0.003% $12,702 –$2,692

2016 $1,654 $1,399 6.5% –0.003% $12,860 –$2,692

2017 $1,577 $1,399 6.5% –0.003% $12,493 –$2,167

2018 $1,574 $1,399 6.5% –0.003% $12,651 –$2,168

2019 $1,542 $1,399 6.5% –0.003% $12,595 –$1,953

2020 $1,539 $1,399 6.5% –0.003% $12,753 –$1,953

2021 $1,537 $1,399 6.5% –0.003% $12,911 –$1,953

2022 $1,388 $1,399 6.5% –0.003% $11,515 –$399

2023 $1,387 $1,399 6.5% –0.003% $11,673 –$399

2024 $1,351 $1,399 6.5% –0.003% $11,434 –$2

2025 $1,351 $1,399 6.5% –0.003% $11,591 –$2

2026 $1,351 $1,399 6.5% –0.003% $11,749 –$3

2027 $1,351 $1,399 6.5% –0.003% $11,907 –$3

2028 $1,351 $1,399 6.5% –0.003% $12,065 –$3

2029 $1,351 $1,399 6.5% –0.003% $12,223 –$3

2030 $1,351 $1,399 6.5% –0.003% $12,381 –$3

2031 $1,351 $1,399 6.5% –0.003% $12,539 –$3

2032 $1,351 $1,399 6.5% –0.003% $12,697 –$3

2033 $1,351 $1,399 6.5% –0.003% $12,855 –$3

2034 $1,351 $1,399 6.5% –0.003% $13,013 –$3

2035 $1,351 $1,399 6.5% –0.003% $13,171 –$3

2036 $1,351 $1,399 6.5% –0.003% $13,329 –$3

NPVb $174,772 –$16,116 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-134

Table 10.B-33. Impacts on Generator Sets and Welding Equipment Market and 

Manufacturers (176-600 hp)

(Average Price per Equipment = $21,400)a

Generator Sets and Welding Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 $2,970 $2,266 6.3% –0.002% $3,728 –$1,185

2012 $2,958 $2,265 6.3% –0.003% $3,767 –$1,185

2013 $2,439 $1,756 4.9% –0.003% $3,221 –$1,186

2014 $3,107 $2,216 6.2% –0.003% $4,154 –$1,540

2015 $3,092 $2,215 6.2% –0.003% $4,192 –$1,540

2016 $2,777 $2,214 6.2% –0.003% $3,877 –$1,187

2017 $2,768 $2,214 6.2% –0.003% $3,916 –$1,187

2018 $2,759 $2,213 6.2% –0.003% $3,954 –$1,187

2019 $2,634 $2,212 6.2% –0.003% $3,850 –$1,044

2020 $2,627 $2,211 6.2% –0.003% $3,888 –$1,044

2021 $2,294 $2,210 6.2% –0.003% $3,096 –$213

2022 $2,292 $2,210 6.2% –0.003% $3,134 –$213

2023 $2,291 $2,209 6.2% –0.003% $3,173 –$213

2024 $2,209 $2,208 6.2% –0.003% $3,000 –$1

2025 $2,208 $2,207 6.2% –0.003% $3,038 –$1

2026 $2,208 $2,207 6.2% –0.003% $3,077 –$1

2027 $2,207 $2,206 6.2% –0.003% $3,115 –$1

2028 $2,206 $2,205 6.2% –0.003% $3,154 –$1

2029 $2,206 $2,205 6.2% –0.003% $3,192 –$1

2030 $2,205 $2,204 6.2% –0.003% $3,231 –$1

2031 $2,204 $2,203 6.2% –0.003% $3,269 –$1

2032 $2,204 $2,203 6.2% –0.003% $3,308 –$1

2033 $2,203 $2,202 6.2% –0.003% $3,346 –$1

2034 $2,203 $2,202 6.2% –0.003% $3,385 –$1

2035 $2,202 $2,201 6.2% –0.003% $3,423 –$1

2036 $2,202 $2,201 6.2% –0.003% $3,462 –$1

NPVb $52,508 –$9,195 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-135

Table 10B-34. Impacts on Refrigeration and Air-Conditioning Equipment Market and

Manufacturers (<25 hp)

(Average Price per Equipment = $12,500)a

Refrigeration and Air-Conditioning Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $177 $129 1.0% –0.001% $168 –$168

2009 $176 $129 1.0% –0.001% $168 –$168

2010 $168 $123 1.0% –0.001% $168 –$168

2011 $167 $123 1.0% –0.002% $168 –$169

2012 $166 $123 1.0% –0.003% $168 –$169

2013 $136 $123 1.0% –0.003% $168 –$169

2014 $136 $123 1.0% –0.003% $168 –$170

2015 $135 $123 1.0% –0.003% $168 –$170

2016 $135 $123 1.0% –0.003% $168 –$170

2017 $135 $123 1.0% –0.003% $168 –$170

2018 $123 $123 1.0% –0.003% — –$2

2019 $123 $123 1.0% –0.003% — –$2

2020 $123 $123 1.0% –0.003% — –$2

2021 $123 $123 1.0% –0.003% — –$2

2022 $123 $123 1.0% –0.003% — –$2

2023 $123 $123 1.0% –0.003% — –$2

2024 $123 $123 1.0% –0.003% — –$2

2025 $123 $123 1.0% –0.003% — –$2

2026 $123 $123 1.0% –0.003% — –$2

2027 $123 $123 1.0% –0.003% — –$2

2028 $123 $123 1.0% –0.003% — –$2

2029 $123 $123 1.0% –0.003% — –$2

2030 $123 $123 1.0% –0.003% — –$2

2031 $123 $123 1.0% –0.003% — –$2

2032 $123 $123 1.0% –0.003% — –$2

2033 $123 $123 1.0% –0.003% — –$3

2034 $123 $123 1.0% –0.003% — –$3

2035 $123 $123 1.0% –0.003% — –$3

2036 $123 $123 1.0% –0.003% — –$3

NPVb $1,310 –$1,340 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-136

Table 10B-35. Impacts on Refrigeration and Air-Conditioning Equipment Market and

Manufacturers (26-50 hp)

(Average Price per Equipment = $27,000)a

Refrigeration and Air-Conditioning Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $204 $147 0.5% –0.001% $100 –$101

2009 $203 $147 0.5% –0.001% $100 –$101

2010 $194 $139 0.5% –0.001% $100 –$102

2011 $193 $139 0.5% –0.002% $100 –$103

2012 $192 $139 0.5% –0.003% $100 –$104

2013 $986 $869 3.2% –0.003% $871 –$590

2014 $984 $869 3.2% –0.003% $876 –$590

2015 $773 $661 2.4% –0.003% $823 –$590

2016 $771 $661 2.4% –0.003% $827 –$591

2017 $769 $661 2.4% –0.003% $832 –$591

2018 $693 $661 2.4% –0.003% $736 –$490

2019 $692 $661 2.4% –0.003% $740 –$490

2020 $692 $661 2.4% –0.003% $745 –$490

2021 $691 $661 2.4% –0.003% $749 –$490

2022 $691 $661 2.4% –0.003% $754 –$490

2023 $661 $661 2.4% –0.003% $273 –$5

2024 $661 $661 2.4% –0.003% $277 –$5

2025 $661 $661 2.4% –0.003% $281 –$5

2026 $661 $661 2.4% –0.003% $286 –$5

2027 $661 $661 2.4% –0.003% $290 –$5

2028 $661 $661 2.4% –0.003% $295 –$5

2029 $661 $661 2.4% –0.003% $299 –$5

2030 $661 $661 2.4% –0.003% $304 –$5

2031 $661 $661 2.4% –0.003% $308 –$6

2032 $661 $661 2.4% –0.003% $313 –$6

2033 $661 $661 2.4% –0.003% $317 –$6

2034 $661 $661 2.4% –0.003% $322 –$6

2035 $661 $661 2.4% –0.003% $326 –$6

2036 $661 $661 2.4% –0.003% $331 –$6

NPVb $7,790 –$4,126 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-137

Table 10B-36. Impacts on Refrigeration and Air-Conditioning Equipment Market and

Manufacturers (51-75 hp)

(Average Price per Equipment = $42,100)a

 

Refrigeration and Air-Conditioning Equipment (50#hp<70) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $226 $167 0.4% –0.001% $179 –$180

2009 $225 $167 0.4% –0.001% $179 –$180

2010 $214 $158 0.4% –0.001% $179 –$182

2011 $213 $157 0.4% –0.002% $179 –$184

2012 $212 $157 0.4% –0.003% $179 –$187

2013 $978 $858 2.0% –0.003% $1,512 –$1,032

2014 $976 $858 2.0% –0.003% $1,521 –$1,033

2015 $769 $653 1.6% –0.003% $1,428 –$1,033

2016 $767 $653 1.6% –0.003% $1,434 –$1,033

2017 $765 $653 1.6% –0.003% $1,441 –$1,033

2018 $687 $653 1.6% –0.003% $1,269 –$855

2019 $686 $653 1.6% –0.003% $1,276 –$855

2020 $686 $653 1.6% –0.003% $1,282 –$855

2021 $685 $653 1.6% –0.003% $1,289 –$855

2022 $685 $653 1.6% –0.003% $1,295 –$855

2023 $653 $653 1.6% –0.003% $459 –$12

2024 $653 $653 1.6% –0.003% $466 –$13

2025 $653 $653 1.6% –0.003% $472 –$13

2026 $653 $653 1.6% –0.003% $479 –$13

2027 $653 $653 1.6% –0.003% $486 –$13

2028 $653 $653 1.6% –0.003% $492 –$13

2029 $653 $653 1.6% –0.003% $499 –$13

2030 $653 $653 1.6% –0.003% $506 –$14

2031 $653 $653 1.6% –0.003% $512 –$14

2032 $653 $653 1.6% –0.003% $519 –$14

2033 $653 $653 1.6% –0.003% $526 –$14

2034 $653 $653 1.6% –0.003% $532 –$14

2035 $653 $653 1.6% –0.003% $539 –$15

2036 $653 $653 1.6% –0.003% $546 –$15

NPVb $13,368 –$7,255 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-138

Table 10.B-37. Impacts on General Industrial Equipment Market and Manufacturers (<25 hp)

(Average Price per Equipment = $17,300)a

General Industrial Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $177 $129 0.7% –0.001% $61 –$61

2009 $176 $129 0.7% –0.001% $61 –$61

2010 $168 $123 0.7% –0.001% $61 –$61

2011 $167 $123 0.7% –0.002% $61 –$62

2012 $166 $123 0.7% –0.003% $61 –$62

2013 $136 $123 0.7% –0.003% $61 –$62

2014 $136 $123 0.7% –0.003% $61 –$62

2015 $135 $123 0.7% –0.003% $61 –$62

2016 $135 $123 0.7% –0.003% $61 –$62

2017 $135 $123 0.7% –0.003% $61 –$62

2018 $123 $123 0.7% –0.003% — –$1

2019 $123 $123 0.7% –0.003% — –$1

2020 $123 $123 0.7% –0.003% — –$1

2021 $123 $123 0.7% –0.003% — –$1

2022 $123 $123 0.7% –0.003% — –$1

2023 $123 $123 0.7% –0.003% — –$1

2024 $123 $123 0.7% –0.003% — –$1

2025 $123 $123 0.7% –0.003% — –$1

2026 $123 $123 0.7% –0.003% — –$1

2027 $123 $123 0.7% –0.003% — –$1

2028 $123 $123 0.7% –0.003% — –$1

2029 $123 $123 0.7% –0.003% — –$1

2030 $123 $123 0.7% –0.003% — –$1

2031 $123 $123 0.7% –0.003% — –$1

2032 $123 $123 0.7% –0.003% — –$1

2033 $123 $123 0.7% –0.003% — –$1

2034 $123 $123 0.7% –0.003% — –$1

2035 $123 $123 0.7% –0.003% — –$1

2036 $123 $123 0.7% –0.003% — –$1

NPVb $479 –$487 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-139

Table 10.B-38. Impacts on General Industrial Equipment Market and Manufacturers (26-50 hp)

(Average Price per Equipment = $42,300)a

General Industrial Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $204 $147 0.3% –0.001% $83 –$71

2009 $203 $147 0.3% –0.001% $83 –$71

2010 $194 $139 0.3% –0.001% $83 –$72

2011 $193 $139 0.3% –0.002% $83 –$72

2012 $192 $139 0.3% –0.003% $83 –$73

2013 $986 $870 2.1% –0.003% $664 –$400

2014 $984 $869 2.1% –0.003% $670 –$400

2015 $773 $661 1.6% –0.003% $616 –$400

2016 $771 $661 1.6% –0.003% $620 –$400

2017 $769 $661 1.6% –0.003% $624 –$400

2018 $693 $661 1.6% –0.003% $555 –$326

2019 $692 $661 1.6% –0.003% $559 –$327

2020 $692 $661 1.6% –0.003% $563 –$327

2021 $691 $661 1.6% –0.003% $567 –$327

2022 $691 $661 1.6% –0.003% $571 –$327

2023 $661 $661 1.6% –0.003% $251 –$3

2024 $661 $661 1.6% –0.003% $256 –$3

2025 $661 $661 1.6% –0.003% $260 –$3

2026 $661 $661 1.6% –0.003% $264 –$3

2027 $661 $661 1.6% –0.003% $268 –$3

2028 $661 $661 1.6% –0.003% $272 –$3

2029 $661 $661 1.6% –0.003% $276 –$3

2030 $661 $661 1.6% –0.003% $280 –$3

2031 $661 $661 1.6% –0.003% $284 –$3

2032 $661 $661 1.6% –0.003% $289 –$3

2033 $661 $661 1.6% –0.003% $293 –$3

2034 $661 $661 1.6% –0.003% $297 –$3

2035 $661 $661 1.6% –0.003% $301 –$3

2036 $661 $661 1.6% –0.003% $305 –$3

NPVb $6,249 –$2,785 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-140

Table 10.B-39. Impacts on General Industrial Equipment Market and Manufacturers (51-75 hp)

(Average Price per Equipment = $56,400)a

General Industrial Equipment (50#hp<70) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $226 $167 0.3% –0.001% $413 –$150

2009 $225 $167 0.3% –0.001% $418 –$150

2010 $214 $158 0.3% –0.001% $408 –$150

2011 $213 $158 0.3% –0.002% $412 –$151

2012 $212 $157 0.3% –0.003% $417 –$151

2013 $978 $858 1.5% –0.003% $2,167 –$532

2014 $976 $858 1.5% –0.003% $2,195 –$533

2015 $769 $653 1.2% –0.003% $1,824 –$533

2016 $767 $653 1.2% –0.003% $1,845 –$533

2017 $765 $653 1.2% –0.003% $1,867 –$533

2018 $687 $653 1.2% –0.003% $1,687 –$332

2019 $686 $653 1.2% –0.003% $1,708 –$332

2020 $686 $653 1.2% –0.003% $1,730 –$332

2021 $685 $653 1.2% –0.003% $1,751 –$332

2022 $685 $653 1.2% –0.003% $1,772 –$332

2023 $653 $653 1.2% –0.003% $1,465 –$3

2024 $653 $653 1.2% –0.003% $1,486 –$3

2025 $653 $653 1.2% –0.003% $1,507 –$4

2026 $653 $653 1.2% –0.003% $1,529 –$4

2027 $653 $653 1.2% –0.003% $1,550 –$4

2028 $653 $653 1.2% –0.003% $1,571 –$4

2029 $653 $653 1.2% –0.003% $1,592 –$4

2030 $653 $653 1.2% –0.003% $1,614 –$4

2031 $653 $653 1.2% –0.003% $1,635 –$4

2032 $653 $653 1.2% –0.003% $1,656 –$4

2033 $653 $653 1.2% –0.003% $1,677 –$4

2034 $653 $653 1.2% –0.003% $1,699 –$4

2035 $653 $653 1.2% –0.003% $1,720 –$4

2036 $653 $653 1.2% –0.003% $1,741 –$4

NPVb $24,870 –$3,615 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-141

Table 10.B-40. Impacts on General Industrial Equipment Market and Manufacturers (76-100

hp)

(Average Price per Equipment = $74,300)a

General Industrial Equipment (75#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — –$1

2009 — — 0.0% –0.001% — –$1

2010 — — 0.0% –0.001% — –$2

2011 — — 0.0% –0.002% — –$4

2012 $1,303 $1,178 1.6% –0.003% $8,518 –$2,336

2013 $1,302 $1,178 1.6% –0.003% $8,625 –$2,337

2014 $1,325 $1,169 1.6% –0.003% $9,382 –$2,990

2015 $1,324 $1,169 1.6% –0.003% $9,489 –$2,990

2016 $1,322 $1,169 1.6% –0.003% $9,596 –$2,990

2017 $1,247 $1,169 1.6% –0.003% $9,325 –$2,611

2018 $1,246 $1,169 1.6% –0.003% $9,432 –$2,611

2019 $1,218 $1,169 1.6% –0.003% $9,390 –$2,462

2020 $1,218 $1,169 1.6% –0.003% $9,497 –$2,462

2021 $1,218 $1,169 1.6% –0.003% $9,604 –$2,462

2022 $1,218 $1,169 1.6% –0.003% $7,760 –$511

2023 $1,218 $1,169 1.6% –0.003% $7,867 –$511

2024 $1,218 $1,169 1.6% –0.003% $7,471 –$9

2025 $1,218 $1,169 1.6% –0.003% $7,578 –$9

2026 $1,218 $1,169 1.6% –0.003% $7,685 –$9

2027 $1,218 $1,169 1.6% –0.003% $7,792 –$10

2028 $1,218 $1,169 1.6% –0.003% $7,899 –$10

2029 $1,218 $1,169 1.6% –0.003% $8,006 –$10

2030 $1,218 $1,169 1.6% –0.003% $8,113 –$10

2031 $1,218 $1,169 1.6% –0.003% $8,220 –$10

2032 $1,218 $1,169 1.6% –0.003% $8,327 –$10

2033 $1,218 $1,169 1.6% –0.003% $8,434 –$10

2034 $1,218 $1,169 1.6% –0.003% $8,541 –$10

2035 $1,218 $1,169 1.6% –0.003% $8,648 –$11

2036 $1,218 $1,169 1.6% –0.003% $8,756 –$11

NPVb $122,225 –$18,884 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-142

Table 10.B-41. Impacts on General Industrial Equipment Market and 

Manufacturers (101-175 hp)

(Average Price per Equipment = $116,900)a

General Industrial Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — –$2

2009 — — 0.0% –0.001% — –$2

2010 — — 0.0% –0.001% — –$5

2011 — –$1 0.0% –0.002% — –$8

2012 $1,623 $1,420 1.2% –0.003% $11,708 –$4,156

2013 $1,619 $1,420 1.2% –0.003% $11,833 –$4,160

2014 $1,664 $1,399 1.2% –0.003% $13,023 –$5,276

2015 $1,659 $1,399 1.2% –0.003% $13,147 –$5,276

2016 $1,654 $1,399 1.2% –0.003% $13,272 –$5,276

2017 $1,577 $1,399 1.2% –0.003% $13,025 –$4,905

2018 $1,574 $1,399 1.2% –0.003% $13,150 –$4,905

2019 $1,542 $1,399 1.2% –0.003% $13,123 –$4,754

2020 $1,539 $1,399 1.2% –0.003% $13,247 –$4,754

2021 $1,537 $1,399 1.2% –0.003% $13,371 –$4,755

2022 $1,388 $1,399 1.2% –0.003% $9,722 –$981

2023 $1,387 $1,399 1.2% –0.003% $9,846 –$981

2024 $1,351 $1,399 1.2% –0.003% $9,007 –$18

2025 $1,351 $1,399 1.2% –0.003% $9,131 –$18

2026 $1,351 $1,399 1.2% –0.003% $9,256 –$18

2027 $1,351 $1,399 1.2% –0.003% $9,380 –$18

2028 $1,351 $1,399 1.2% –0.003% $9,504 –$19

2029 $1,351 $1,399 1.2% –0.003% $9,629 –$19

2030 $1,351 $1,399 1.2% –0.003% $9,753 –$19

2031 $1,351 $1,399 1.2% –0.003% $9,878 –$19

2032 $1,351 $1,399 1.2% –0.003% $10,002 –$20

2033 $1,351 $1,399 1.2% –0.003% $10,127 –$20

2034 $1,351 $1,399 1.2% –0.003% $10,251 –$20

2035 $1,351 $1,399 1.2% –0.003% $10,375 –$20

2036 $1,351 $1,399 1.2% –0.003% $10,500 –$21

NPVb $159,307 –$34,647 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-143

Table 10.B-42. Impacts on General Industrial Equipment Market and 

Manufacturers (176-600 hp)

(Average Price per Equipment = $154,200)a

General Industrial Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — –$1

2009 — — 0.0% –0.001% — –$1

2010 — –$1 0.0% –0.001% — –$3

2011 $2,970 $2,265 1.5% –0.002% $6,434 –$4,061

2012 $2,958 $2,264 1.5% –0.003% $6,470 –$4,063

2013 $2,439 $1,755 1.1% –0.003% $5,975 –$4,065

2014 $3,107 $2,215 1.4% –0.003% $7,625 –$5,135

2015 $3,092 $2,214 1.4% –0.003% $7,662 –$5,135

2016 $2,777 $2,213 1.4% –0.003% $7,457 –$4,894

2017 $2,768 $2,213 1.4% –0.003% $7,494 –$4,895

2018 $2,759 $2,212 1.4% –0.003% $7,530 –$4,895

2019 $2,634 $2,211 1.4% –0.003% $7,469 –$4,797

2020 $2,627 $2,210 1.4% –0.003% $7,506 –$4,798

2021 $2,294 $2,209 1.4% –0.003% $3,727 –$982

2022 $2,292 $2,209 1.4% –0.003% $3,763 –$982

2023 $2,291 $2,208 1.4% –0.003% $3,799 –$982

2024 $2,209 $2,207 1.4% –0.003% $2,864 –$11

2025 $2,208 $2,206 1.4% –0.003% $2,901 –$11

2026 $2,208 $2,206 1.4% –0.003% $2,937 –$11

2027 $2,207 $2,205 1.4% –0.003% $2,974 –$11

2028 $2,206 $2,204 1.4% –0.003% $3,010 –$11

2029 $2,206 $2,204 1.4% –0.003% $3,046 –$11

2030 $2,205 $2,203 1.4% –0.003% $3,083 –$12

2031 $2,204 $2,203 1.4% –0.003% $3,119 –$12

2032 $2,204 $2,202 1.4% –0.003% $3,156 –$12

2033 $2,203 $2,201 1.4% –0.003% $3,192 –$12

2034 $2,203 $2,201 1.4% –0.003% $3,229 –$12

2035 $2,202 $2,200 1.4% –0.003% $3,265 –$12

2036 $2,202 $2,200 1.4% –0.003% $3,302 –$12

NPVb $76,149 –$35,032 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-144

Table 10.B-43. Impacts on General Industrial Equipment Market and Manufacturers (>600 hp)

(Average Price per Equipment = $345,700)a

General Industrial Equipment ($600hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — –$1 0.0% –0.001% — —

2009 — –$1 0.0% –0.001% — —

2010 — –$2 0.0% –0.001% — —

2011 $4,519 $2,964 0.9% –0.002% $665 –$512

2012 $4,496 $2,963 0.9% –0.003% $667 –$512

2013 $3,797 $2,287 0.7% –0.003% $634 –$513

2014 $4,684 $2,789 0.8% –0.003% $783 –$629

2015 $9,206 $6,270 1.8% –0.003% $1,439 –$1,095

2016 $8,364 $6,270 1.8% –0.003% $1,410 –$1,061

2017 $7,517 $5,452 1.6% –0.003% $1,371 –$1,061

2018 $7,489 $5,452 1.6% –0.003% $1,375 –$1,061

2019 $7,218 $5,452 1.6% –0.003% $1,369 –$1,050

2020 $6,767 $5,452 1.6% –0.003% $1,355 –$1,031

2021 $6,151 $5,452 1.6% –0.003% $881 –$554

2022 $6,142 $5,452 1.6% –0.003% $886 –$554

2023 $6,133 $5,452 1.6% –0.003% $890 –$554

2024 $5,997 $5,452 1.6% –0.003% $789 –$449

2025 $5,458 $5,452 1.6% –0.003% $346 –$2

2026 $5,458 $5,452 1.6% –0.003% $351 –$2

2027 $5,458 $5,452 1.6% –0.003% $355 –$2

2028 $5,458 $5,452 1.6% –0.003% $359 –$2

2029 $5,458 $5,452 1.6% –0.003% $364 –$2

2030 $5,458 $5,452 1.6% –0.003% $368 –$2

2031 $5,458 $5,452 1.6% –0.003% $372 –$2

2032 $5,458 $5,452 1.6% –0.003% $377 –$2

2033 $5,458 $5,452 1.6% –0.003% $381 –$2

2034 $5,458 $5,452 1.6% –0.003% $385 –$2

2035 $5,458 $5,452 1.6% –0.003% $390 –$2

2036 $5,458 $5,452 1.6% –0.003% $394 –$2

NPVb $11,760 –$7,192 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-145

Table 10.B-44. Impacts on Lawn and Garden Equipment Market and Manufacturers (<25 hp)

(Average Price per Equipment = $9,300)a

Lawn and Garden Equipment (<25hp) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $177 $129 1.4% –0.001% $1,805 –$629

2009 $176 $129 1.4% –0.001% $1,836 –$629

2010 $168 $123 1.3% –0.001% $1,804 –$629

2011 $167 $123 1.3% –0.002% $1,834 –$630

2012 $166 $123 1.3% –0.003% $1,864 –$630

2013 $136 $123 1.3% –0.003% $1,597 –$333

2014 $136 $123 1.3% –0.003% $1,627 –$333

2015 $135 $123 1.3% –0.003% $1,657 –$333

2016 $135 $123 1.3% –0.003% $1,687 –$333

2017 $135 $123 1.3% –0.003% $1,717 –$333

2018 $123 $123 1.3% –0.003% $1,417 –$2

2019 $123 $123 1.3% –0.003% $1,447 –$2

2020 $123 $123 1.3% –0.003% $1,477 –$2

2021 $123 $123 1.3% –0.003% $1,507 –$3

2022 $123 $123 1.3% –0.003% $1,537 –$3

2023 $123 $123 1.3% –0.003% $1,568 –$3

2024 $123 $123 1.3% –0.003% $1,598 –$3

2025 $123 $123 1.3% –0.003% $1,628 –$3

2026 $123 $123 1.3% –0.003% $1,658 –$3

2027 $123 $123 1.3% –0.003% $1,688 –$3

2028 $123 $123 1.3% –0.003% $1,718 –$3

2029 $123 $123 1.3% –0.003% $1,749 –$3

2030 $123 $123 1.3% –0.003% $1,779 –$3

2031 $123 $123 1.3% –0.003% $1,809 –$3

2032 $123 $123 1.3% –0.003% $1,839 –$3

2033 $123 $123 1.3% –0.003% $1,869 –$3

2034 $123 $123 1.3% –0.003% $1,900 –$3

2035 $123 $123 1.3% –0.003% $1,930 –$3

2036 $123 $123 1.3% –0.003% $1,960 –$3

NPVb $29,853 –$3,868 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-146

Table 10.B-45. Impacts on Lawn and Garden Equipment Market and Manufacturers (26-50 hp)

(Average Price per Equipment = $21,500)a

Lawn and Garden Equipment (25#hp<50) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $204 $147 0.7% –0.001% $474 –$194

2009 $203 $147 0.7% –0.001% $480 –$194

2010 $194 $139 0.6% –0.001% $471 –$195

2011 $193 $139 0.6% –0.002% $477 –$196

2012 $192 $139 0.6% –0.003% $482 –$196

2013 $986 $870 4.0% –0.003% $2,817 –$742

2014 $984 $870 4.0% –0.003% $2,858 –$742

2015 $773 $661 3.1% –0.003% $2,391 –$742

2016 $771 $661 3.1% –0.003% $2,422 –$742

2017 $769 $661 3.1% –0.003% $2,453 –$742

2018 $693 $661 3.1% –0.003% $2,228 –$485

2019 $692 $661 3.1% –0.003% $2,259 –$485

2020 $692 $661 3.1% –0.003% $2,290 –$485

2021 $691 $661 3.1% –0.003% $2,321 –$486

2022 $691 $661 3.1% –0.003% $2,353 –$486

2023 $661 $661 3.1% –0.003% $1,901 –$3

2024 $661 $661 3.1% –0.003% $1,933 –$3

2025 $661 $661 3.1% –0.003% $1,964 –$3

2026 $661 $661 3.1% –0.003% $1,995 –$3

2027 $661 $661 3.1% –0.003% $2,026 –$3

2028 $661 $661 3.1% –0.003% $2,057 –$4

2029 $661 $661 3.1% –0.003% $2,089 –$4

2030 $661 $661 3.1% –0.003% $2,120 –$4

2031 $661 $661 3.1% –0.003% $2,151 –$4

2032 $661 $661 3.1% –0.003% $2,182 –$4

2033 $661 $661 3.1% –0.003% $2,213 –$4

2034 $661 $661 3.1% –0.003% $2,245 –$4

2035 $661 $661 3.1% –0.003% $2,276 –$4

2036 $661 $661 3.1% –0.003% $2,307 –$4

NPVb $32,380 –$5,037 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-147

Table 10.B-46. Impacts on Lawn and Garden Equipment Market and Manufacturers (51-75 hp)

(Average Price per Equipment = $33,100)a

Lawn and Garden Equipment (50#hp<75) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 $226 $167 0.5% –0.001% $14 –$14

2009 $225 $167 0.5% –0.001% $14 –$14

2010 $214 $158 0.5% –0.001% $14 –$15

2011 $213 $158 0.5% –0.002% $14 –$15

2012 $212 $157 0.5% –0.003% $14 –$15

2013 $978 $858 2.6% –0.003% $121 –$83

2014 $976 $858 2.6% –0.003% $122 –$83

2015 $769 $653 2.0% –0.003% $115 –$83

2016 $767 $653 2.0% –0.003% $115 –$83

2017 $765 $653 2.0% –0.003% $116 –$83

2018 $687 $653 2.0% –0.003% $102 –$68

2019 $686 $653 2.0% –0.003% $102 –$68

2020 $686 $653 2.0% –0.003% $103 –$68

2021 $685 $653 2.0% –0.003% $103 –$68

2022 $685 $653 2.0% –0.003% $104 –$68

2023 $653 $653 2.0% –0.003% $37 –$1

2024 $653 $653 2.0% –0.003% $37 –$1

2025 $653 $653 2.0% –0.003% $38 –$1

2026 $653 $653 2.0% –0.003% $38 –$1

2027 $653 $653 2.0% –0.003% $39 –$1

2028 $653 $653 2.0% –0.003% $40 –$1

2029 $653 $653 2.0% –0.003% $40 –$1

2030 $653 $653 2.0% –0.003% $41 –$1

2031 $653 $653 2.0% –0.003% $41 –$1

2032 $653 $653 2.0% –0.003% $42 –$1

2033 $653 $653 2.0% –0.003% $42 –$1

2034 $653 $653 2.0% –0.003% $43 –$1

2035 $653 $653 2.0% –0.003% $43 –$1

2036 $653 $653 2.0% –0.003% $44 –$1

NPVb $1,072 –$577 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-148

Table 10.B-47. Impacts on Lawn and Garden Equipment Market and Manufacturers (76-100 hp)

(Average Price per Equipment = $38,500)a

Lawn and Garden Equipment (70#hp<100) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 — — 0.0% –0.002% — –$1

2012 $1,303 $1,178 3.1% –0.003% $529 –$375

2013 $1,302 $1,178 3.1% –0.003% $531 –$375

2014 $1,325 $1,169 3.0% –0.003% $641 –$471

2015 $1,324 $1,169 3.0% –0.003% $644 –$471

2016 $1,322 $1,169 3.0% –0.003% $647 –$471

2017 $1,247 $1,169 3.0% –0.003% $650 –$471

2018 $1,246 $1,169 3.0% –0.003% $653 –$471

2019 $1,218 $1,169 3.0% –0.003% $655 –$472

2020 $1,218 $1,169 3.0% –0.003% $658 –$472

2021 $1,218 $1,169 3.0% –0.003% $661 –$472

2022 $1,218 $1,169 3.0% –0.003% $290 –$98

2023 $1,218 $1,169 3.0% –0.003% $293 –$98

2024 $1,218 $1,169 3.0% –0.003% $200 –$1

2025 $1,218 $1,169 3.0% –0.003% $202 –$1

2026 $1,218 $1,169 3.0% –0.003% $205 –$1

2027 $1,218 $1,169 3.0% –0.003% $208 –$2

2028 $1,218 $1,169 3.0% –0.003% $211 –$2

2029 $1,218 $1,169 3.0% –0.003% $214 –$2

2030 $1,218 $1,169 3.0% –0.003% $217 –$2

2031 $1,218 $1,169 3.0% –0.003% $220 –$2

2032 $1,218 $1,169 3.0% –0.003% $222 –$2

2033 $1,218 $1,169 3.0% –0.003% $225 –$2

2034 $1,218 $1,169 3.0% –0.003% $228 –$2

2035 $1,218 $1,169 3.0% –0.003% $231 –$2

2036 $1,218 $1,169 3.0% –0.003% $234 –$2

NPVb $5,970 –$3,244 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

10-149

Table 10.B-48. Impacts on Lawn and Garden Equipment Market and 

Manufacturers (101-175 hp)

(Average Price per Equipment = $29,200)a

Lawn and Garden Equipment (100#hp<175) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — — 0.0% –0.001% — —

2011 — — 0.0% –0.002% — —

2012 $1,623 $1,421 4.8% –0.003% $420 –$331

2013 $1,619 $1,421 4.8% –0.003% $421 –$331

2014 $1,664 $1,399 4.7% –0.003% $514 –$416

2015 $1,659 $1,399 4.7% –0.003% $515 –$416

2016 $1,654 $1,399 4.7% –0.003% $517 –$416

2017 $1,577 $1,399 4.7% –0.003% $518 –$416

2018 $1,574 $1,399 4.7% –0.003% $520 –$416

2019 $1,542 $1,399 4.7% –0.003% $521 –$416

2020 $1,539 $1,399 4.7% –0.003% $523 –$416

2021 $1,537 $1,399 4.7% –0.003% $525 –$416

2022 $1,388 $1,399 4.7% –0.003% $195 –$85

2023 $1,387 $1,399 4.7% –0.003% $197 –$85

2024 $1,351 $1,399 4.7% –0.003% $114 –$1

2025 $1,351 $1,399 4.7% –0.003% $116 –$1

2026 $1,351 $1,399 4.7% –0.003% $117 –$1

2027 $1,351 $1,399 4.7% –0.003% $119 –$1

2028 $1,351 $1,399 4.7% –0.003% $120 –$1

2029 $1,351 $1,399 4.7% –0.003% $122 –$1

2030 $1,351 $1,399 4.7% –0.003% $124 –$1

2031 $1,351 $1,399 4.7% –0.003% $125 –$1

2032 $1,351 $1,399 4.7% –0.003% $127 –$1

2033 $1,351 $1,399 4.7% –0.003% $128 –$1

2034 $1,351 $1,399 4.7% –0.003% $130 –$1

2035 $1,351 $1,399 4.7% –0.003% $131 –$1

2036 $1,351 $1,399 4.7% –0.003% $133 –$1

NPVb $4,418 –$2,856 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

10-150

Table 10.B-49. Impacts on Lawn and Garden Equipment Market and 

Manufacturers (176-600 hp)

(Average Price per Equipment = $64,300)a

Lawn and Garden Equipment (175#hp<600) Change in Producer

Surplus for

Equipment

Manufacturers (103 Year )

Engineering

Cost/Unit

Absolute

Change in

Price

Change in

Price (%)

Change in

Quantity

(%)

Total

Engineering

Costs (103)

2007 — — 0.0% 0.000% — —

2008 — — 0.0% –0.001% — —

2009 — — 0.0% –0.001% — —

2010 — –$1 0.0% –0.001% — —

2011 $2,970 $2,265 3.5% –0.002% $279 –$233

2012 $2,958 $2,264 3.5% –0.003% $280 –$233

2013 $2,439 $1,755 2.7% –0.003% $271 –$233

2014 $3,107 $2,216 3.4% –0.003% $344 –$293

2015 $3,092 $2,215 3.4% –0.003% $345 –$293

2016 $2,777 $2,214 3.4% –0.003% $346 –$293

2017 $2,768 $2,213 3.4% –0.003% $346 –$293

2018 $2,759 $2,212 3.4% –0.003% $347 –$293

2019 $2,634 $2,211 3.4% –0.003% $348 –$293

2020 $2,627 $2,210 3.4% –0.003% $349 –$293

2021 $2,294 $2,210 3.4% –0.003% $116 –$60

2022 $2,292 $2,209 3.4% –0.003% $117 –$60

2023 $2,291 $2,208 3.4% –0.003% $118 –$60

2024 $2,209 $2,207 3.4% –0.003% $59 —

2025 $2,208 $2,207 3.4% –0.003% $60 —

2026 $2,208 $2,206 3.4% –0.003% $60 —

2027 $2,207 $2,205 3.4% –0.003% $61 —

2028 $2,206 $2,205 3.4% –0.003% $62 —

2029 $2,206 $2,204 3.4% –0.003% $63 —

2030 $2,205 $2,203 3.4% –0.003% $63 —

2031 $2,204 $2,203 3.4% –0.003% $64 —

2032 $2,204 $2,202 3.4% –0.003% $65 —

2033 $2,203 $2,202 3.4% –0.003% $66 —

2034 $2,203 $2,201 3.4% –0.003% $66 —

2035 $2,202 $2,200 3.4% –0.003% $67 —

2036 $2,202 $2,200 3.4% –0.003% $68 –$1

NPVb $2,898 –$2,060 a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

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APPENDIX 10C: Impacts on Application Markets

This appendix provides the time series of impacts from 2007 through 2036 for the application markets and the

transportation service markets included in the model. 

There are 3 application markets: construction, agriculture, and manufacturing. 

There are 2 transportation service markets: locomotive and marine. 

Tables 10C-1 through 10C-5 provide the time series of impacts for these markets. Each table includes the

following:

C relative change in market price (%)

C relative change in market quantity (%)

C change in producer and consumer surplus for each application market

For the three application markets, prices are expected to increase 0.02 percent in the manufacturing sector, 0.1

percent in the agricultural sector, and 0.5 percent in the construction sector. Price increase are highest in about 2015,

and decrease thereafter. Quantity decreases stabilize in about 2015 as well.

For the transportation service markets, prices are expected to increase 0.03 percent in the locomotive sector and

0.006 percent in the marine sector. Price increases and quantity decreases stabilize in about 2015.
Final Regulatory Impact Analysis

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Table 10C-1. Impacts on Agricultural Application Marketa

Agriculture Change in Producer and

Consumer Surplus ($103 Year Change in Price (%) Change in Quantity (%) )

2007 0.030% 0.000% –$35,860

2008 0.050% –0.001% –$75,265

2009 0.050% –0.001% –$76,967

2010 0.104% –0.002% –$144,827

2011 0.142% –0.003% –$309,684

2012 0.139% –0.004% –$394,695

2013 0.136% –0.005% –$429,981

2014 0.147% –0.005% –$478,692

2015 0.154% –0.005% –$484,874

2016 0.152% –0.005% –$493,522

2017 0.150% –0.005% –$502,205

2018 0.148% –0.005% –$510,901

2019 0.146% –0.005% –$519,570

2020 0.143% –0.005% –$524,291

2021 0.140% –0.005% –$530,035

2022 0.138% –0.005% –$538,585

2023 0.136% –0.005% –$547,123

2024 0.134% –0.005% –$555,669

2025 0.132% –0.005% –$564,198

2026 0.130% –0.005% –$572,713

2027 0.128% –0.005% –$581,228

2028 0.127% –0.005% –$589,742

2029 0.125% –0.005% –$598,257

2030 0.123% –0.005% –$606,770

2031 0.121% –0.005% –$615,284

2032 0.119% –0.005% –$623,797

2033 0.118% –0.005% –$632,309

2034 0.116% –0.005% –$640,821

2035 0.114% –0.005% –$649,333

2036 0.113% –0.005% –$657,844

NPVb –$8,180,632

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

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Table 10C-2. Impacts on Construction Application Marketa

Construction Change in Producer and

Consumer Surplus ($103 Year Change in Price (%) Change in Quantity (%) )

2007 0.105% –0.001% –$47,524

2008 0.176% –0.001% –$97,113

2009 0.174% –0.001% –$99,303

2010 0.382% –0.002% –$199,991

2011 0.526% –0.004% –$409,111

2012 0.517% –0.005% –$548,053

2013 0.508% –0.006% –$584,333

2014 0.553% –0.006% –$650,082

2015 0.587% –0.006% –$689,966

2016 0.579% –0.006% –$702,193

2017 0.573% –0.006% –$709,196

2018 0.568% –0.006% –$721,412

2019 0.565% –0.006% –$733,610

2020 0.559% –0.006% –$744,027

2021 0.554% –0.006% –$754,910

2022 0.550% –0.006% –$767,057

2023 0.544% –0.006% –$779,171

2024 0.539% –0.006% –$791,302

2025 0.533% –0.006% –$803,409

2026 0.527% –0.006% –$815,495

2027 0.522% –0.006% –$827,581

2028 0.517% –0.006% –$839,668

2029 0.512% –0.006% –$851,754

2030 0.507% –0.006% –$863,841

2031 0.502% –0.006% –$875,929

2032 0.497% –0.006% –$888,016

2033 0.492% –0.006% –$900,104

2034 0.487% –0.006% –$912,193

2035 0.482% –0.006% –$924,281

2036 0.478% –0.006% –$936,370

NPVb –$11,525,673

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Final Regulatory Impact Analysis

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Table 10C-3. Impacts on Manufacturing Application Marketa

Manufacturing Change in Producer and

Consumer Surplus ($103 Year Change in Price (%) Change in Quantity (%) )

2007 0.007% –0.003% –$40,523

2008 0.015% –0.004% –$104,885

2009 0.015% –0.004% –$106,956

2010 0.028% –0.007% –$190,735

2011 0.059% –0.013% –$289,933

2012 0.074% –0.016% –$382,352

2013 0.079% –0.017% –$482,357

2014 0.086% –0.019% –$519,105

2015 0.086% –0.019% –$517,361

2016 0.086% –0.019% –$525,764

2017 0.086% –0.019% –$533,562

2018 0.086% –0.019% –$542,061

2019 0.086% –0.019% –$550,840

2020 0.086% –0.019% –$557,759

2021 0.085% –0.018% –$564,953

2022 0.085% –0.019% –$573,644

2023 0.085% –0.019% –$582,045

2024 0.085% –0.019% –$590,571

2025 0.085% –0.019% –$599,072

2026 0.085% –0.019% –$607,560

2027 0.085% –0.019% –$616,061

2028 0.085% –0.019% –$624,576

2029 0.085% –0.019% –$633,104

2030 0.085% –0.019% –$641,646

2031 0.086% –0.019% –$650,201

2032 0.086% –0.019% –$658,771

2033 0.086% –0.019% –$667,355

2034 0.086% –0.019% –$675,953

2035 0.086% –0.019% –$684,566

2036 0.086% –0.019% –$693,194

NPVb –$8,722,570

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

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Table 10C-4. Impacts on the Locomotive Transportation Marketa

Manufacturing Change in Producer and

Consumer Surplus ($103 Year Change in Price (%) Change in Quantity (%) )

2007 0.003% –0.004% –$44

2008 0.005% –0.006% –$234

2009 0.005% –0.006% –$240

2010 0.010% –0.011% –$519

2011 0.020% –0.021% –$970

2012 0.027% –0.027% –$1,314

2013 0.028% –0.028% –$1,579

2014 0.031% –0.031% –$1,739

2015 0.032% –0.032% –$1,773

2016 0.032% –0.032% –$1,813

2017 0.032% –0.032% –$1,850

2018 0.032% –0.032% –$1,892

2019 0.032% –0.032% –$1,936

2020 0.032% –0.032% –$1,973

2021 0.032% –0.032% –$2,013

2022 0.032% –0.032% –$2,059

2023 0.032% –0.032% –$2,106

2024 0.032% –0.032% –$2,155

2025 0.032% –0.032% –$2,204

2026 0.032% –0.032% –$2,255

2027 0.032% –0.032% –$2,306

2028 0.032% –0.032% –$2,359

2029 0.032% –0.032% –$2,413

2030 0.032% –0.032% –$2,469

2031 0.032% –0.032% –$2,525

2032 0.032% –0.032% –$2,583

2033 0.032% –0.032% –$2,643

2034 0.032% –0.032% –$2,704

2035 0.032% –0.032% –$2,766

2036 0.032% –0.032% –$2,829

NPVb –$31,271

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Final Regulatory Impact Analysis

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Table 10C-3. Impacts on the Marine Transportation Marketa

Manufacturing Change in Producer and

Consumer Surplus ($103 Year Change in Price (%) Change in Quantity (%) )

2007 0.001% 0.000% –$32

2008 0.001% –0.001% –$132

2009 0.001% –0.001% –$135

2010 0.002% –0.001% –$289

2011 0.004% –0.002% –$549

2012 0.005% –0.003% –$744

2013 0.006% –0.003% –$876

2014 0.006% –0.003% –$967

2015 0.006% –0.003% –$996

2016 0.006% –0.003% –$1,019

2017 0.006% –0.003% –$1,038

2018 0.006% –0.003% –$1,062

2019 0.006% –0.003% –$1,087

2020 0.006% –0.003% –$1,108

2021 0.006% –0.003% –$1,131

2022 0.006% –0.003% –$1,157

2023 0.006% –0.003% –$1,184

2024 0.006% –0.003% –$1,211

2025 0.006% –0.003% –$1,239

2026 0.006% –0.003% –$1,267

2027 0.006% –0.003% –$1,296

2028 0.006% –0.003% –$1,326

2029 0.006% –0.003% –$1,357

2030 0.006% –0.003% –$1,388

2031 0.006% –0.003% –$1,420

2032 0.006% –0.003% –$1,452

2033 0.006% –0.003% –$1,486

2034 0.006% –0.003% –$1,520

2035 0.006% –0.003% –$1,555

2036 0.006% –0.003% –$1,591

NPVb –$17,569

a Figures are in 2002 dollars. 

b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period.
Economic Impact Analysis

S

These percentages exclude heating oil; if high-sulfur heating oil is included, then about 35

percent of high-sulfur fuel was consumed in nonroad diesel equipment and about 17 percent

was consumed in marine equipment and locomotive engines.

10-157

APPENDIX 10D: Impacts on the Nonroad Fuel Market

This appendix provides the time series of impacts from 2007 through 2036 for the nonroad

diesel fuel market. Eight nonroad diesel fuel markets were modeled: 2 sulfur content levels (15

ppm and 500 ppm) for each of 4 PADDs (PADDs 1&3, PADD 2, PADD 4, and PADD 5). Note

that PADD 5 includes Alaska and Hawaii but excludes California fuel volumes that are not

affected by the program because they are covered by separate California nonroad diesel fuel

standards.

Tables 10D-1 through 10D-4 provide the time series of impacts for the diesel fuel market for

the four regional fuel markets. Each table includes the following:

C average price per gallon 

C average engineering costs (variable and fixed) per gallon

C absolute change in the PADDs’ nonroad diesel price ($) 

! Note that the estimated absolute change in market price is based on average variable

and fixed costs; see Appendix 10I for sensitivity analyses reflecting maximum total

costs and maximum variable costs

C relative change in the PADDs’ nonroad diesel price (%)

C relative change in the PADDs’ nonroad diesel quantity (%)

C total engineering (regulatory) costs associated with each PADD’s fuel market ($)

C change in producer surplus for all fuel producers

In 2001, about 68 percent of high-sulfur diesel fuel was consumed in nonroad diesel

equipment and about 32 percent was consumed in marine equipment and locomotive engines.S

The engineering costs and changes in producer surplus presented in this appendix include both of

these diesel fuel segments. 

All prices and costs are presented in $2002, and the real per-gallon prices are assumed to be

constant within each regional fuel market. For each regional fuel market, the majority of the cost

of the regulation is passed along through increased fuel prices. 
Final Regulatory Impact Analysis

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Table 10D-1. Impacts on the Nonroad Fuel Market in PADD 1&3

(Average Price per Gallon = $0.91)a

Year

Engineering

Cost/Unit

15ppm

Engineering

Cost/Unit

500ppm

Absolute

Change

in Price

Change

in Price

(%)

Change in

Quantity

(%)

Total

Engineering

Costs ($103)

Change in

Producer

Surplus for Fuel

Producers ($103)

2007 — $0.02 $0.01 1.0% –0.002% $56,985 –$54

2008 — $0.02 $0.02 1.8% –0.004% $99,743 –$613

2009 — $0.02 $0.02 1.8% –0.004% $101,806 –$629

2010 $0.06 $0.02 $0.04 4.1% –0.007% $236,629 $65

2011 $0.06 $0.03 $0.05 5.7% –0.013% $339,851 –$2,313

2012 $0.06 $0.03 $0.05 5.7% –0.017% $346,465 –$3,292

2013 $0.06 $0.03 $0.05 5.6% –0.018% $352,867 –$3,624

2014 $0.06 $0.03 $0.06 6.1% –0.019% $390,537 –$4,187

2015 $0.06 $0.03 $0.06 6.5% –0.020% $421,492 –$4,532

2016 $0.06 $0.03 $0.06 6.5% –0.020% $429,036 –$4,625

2017 $0.06 $0.03 $0.06 6.5% –0.020% $436,616 –$4,689

2018 $0.06 $0.03 $0.06 6.5% –0.020% $444,324 –$4,783

2019 $0.06 $0.03 $0.06 6.5% –0.020% $452,220 –$4,877

2020 $0.06 $0.03 $0.06 6.5% –0.020% $462,196 –$5,027

2021 $0.06 $0.03 $0.06 6.6% –0.020% $471,507 –$5,164

2022 $0.06 $0.03 $0.06 6.6% –0.020% $479,447 –$5,259

2023 $0.06 $0.03 $0.06 6.6% –0.020% $487,125 –$5,353

2024 $0.06 $0.03 $0.06 6.6% –0.020% $494,924 –$5,448

2025 $0.06 $0.03 $0.06 6.6% –0.020% $502,671 –$5,542

2026 $0.06 $0.03 $0.06 6.6% –0.020% $510,413 –$5,636

2027 $0.06 $0.03 $0.06 6.6% –0.020% $518,166 –$5,730

2028 $0.06 $0.03 $0.06 6.6% –0.020% $525,932 –$5,824

2029 $0.06 $0.03 $0.06 6.6% –0.020% $533,710 –$5,918

2030 $0.06 $0.03 $0.06 6.6% –0.020% $541,500 –$6,012

2031 $0.06 $0.03 $0.06 6.6% –0.020% $549,303 –$6,106

2032 $0.06 $0.03 $0.06 6.6% –0.020% $557,119 –$6,200

2033 $0.06 $0.03 $0.06 6.6% –0.020% $564,948 –$6,294

2034 $0.06 $0.03 $0.06 6.6% –0.020% $572,789 –$6,388

2035 $0.06 $0.03 $0.06 6.6% –0.020% $580,644 –$6,482

2036 $0.06 $0.03 $0.06 6.6% –0.020% $588,512 –$6,576

NPVb $7,422,281 –$76,083

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Economic Impact Analysis

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Table 10D-2. Impacts on the Nonroad Fuel Market in PADD 2

(Average Price per Gallon = $0.94)a

Year

Engineering

Cost/Unit

15ppm

Engineering

Cost/Unit

500ppm

Absolute

Change

in Price

Change

in Price

(%)

Change in

Quantity

(%)

Total

Engineering

Costs ($103)

Change in

Producer

Surplus for Fuel

Producers ($103)

2007 — $0.02 $0.01 1.5% –0.003% $57,852 $64

2008 — $0.02 $0.02 2.6% –0.005% $101,359 –$544

2009 — $0.02 $0.02 2.6% –0.005% $103,564 –$558

2010 $0.07 $0.03 $0.05 5.0% –0.008% $204,945 $578

2011 $0.07 $0.03 $0.06 6.7% –0.015% $281,683 –$932

2012 $0.07 $0.03 $0.06 6.7% –0.019% $287,389 –$1,649

2013 $0.07 $0.03 $0.06 6.7% –0.021% $293,011 –$1,903

2014 $0.08 $0.03 $0.07 7.3% –0.022% $323,985 –$2,523

2015 $0.08 $0.03 $0.07 7.7% –0.023% $349,620 –$2,889

2016 $0.08 $0.03 $0.07 7.7% –0.023% $356,353 –$2,957

2017 $0.08 $0.03 $0.07 7.7% –0.023% $363,096 –$3,012

2018 $0.08 $0.03 $0.07 7.7% –0.023% $369,869 –$3,083

2019 $0.08 $0.03 $0.07 7.7% –0.023% $376,682 –$3,151

2020 $0.08 $0.03 $0.07 7.5% –0.023% $374,491 –$2,895

2021 $0.08 $0.03 $0.07 7.4% –0.023% $374,573 –$2,733

2022 $0.08 $0.03 $0.07 7.4% –0.023% $381,107 –$2,791

2023 $0.08 $0.03 $0.07 7.4% –0.023% $387,586 –$2,849

2024 $0.08 $0.03 $0.07 7.4% –0.023% $394,090 –$2,907

2025 $0.08 $0.03 $0.07 7.4% –0.023% $400,582 –$2,964

2026 $0.08 $0.03 $0.07 7.4% –0.023% $407,040 –$3,021

2027 $0.08 $0.03 $0.07 7.4% –0.023% $413,500 –$3,079

2028 $0.08 $0.03 $0.07 7.4% –0.023% $419,963 –$3,136

2029 $0.08 $0.03 $0.07 7.4% –0.023% $426,429 –$3,194

2030 $0.08 $0.03 $0.07 7.4% –0.023% $432,896 –$3,251

2031 $0.08 $0.03 $0.07 7.4% –0.023% $439,367 –$3,308

2032 $0.08 $0.03 $0.07 7.5% –0.023% $445,840 –$3,366

2033 $0.08 $0.03 $0.07 7.5% –0.023% $452,315 –$3,423

2034 $0.08 $0.03 $0.07 7.5% –0.023% $458,794 –$3,480

2035 $0.08 $0.03 $0.07 7.5% –0.023% $465,275 –$3,537

2036 $0.08 $0.03 $0.07 7.5% –0.023% $471,758 –$3,594

NPVb $6,075,867 –$42,383

a Figures are in 2001 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2030 time period. 
Final Regulatory Impact Analysis

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Table 10D-3. Impacts on the Nonroad Fuel Market in PADD 4

(Average Price per Gallon = $0.91)a

Year

Engineering

Cost/Unit

15ppm

Engineering

Cost/Unit

500ppm

Absolute

Change

in Price

Change

in Price

(%)

Change in

Quantity

(%)

Total

Engineering

Costs ($103)

Change in

Producer

Surplus for Fuel

Producers ($103)

2007 — $0.04 $0.02 2.0% –0.003% $6,826 $34

2008 — $0.04 $0.03 3.4% –0.005% $11,955 –$34

2009 — $0.04 $0.03 3.4% –0.005% $12,214 –$35

2010 $0.13 $0.04 $0.07 6.8% –0.009% $24,781 $432

2011 $0.13 $0.09 $0.09 9.1% –0.016% $33,824 $459

2012 $0.13 $0.09 $0.09 9.1% –0.020% $34,500 $401

2013 $0.13 $0.09 $0.09 9.1% –0.021% $35,166 $390

2014 $0.13 $0.09 $0.09 9.9% –0.023% $39,254 $324

2015 $0.13 $0.09 $0.10 10.6% –0.024% $42,621 $273

2016 $0.13 $0.09 $0.10 10.6% –0.024% $43,461 $276

2017 $0.13 $0.09 $0.10 10.6% –0.024% $44,301 $280

2018 $0.13 $0.09 $0.10 10.6% –0.024% $45,142 $281

2019 $0.13 $0.09 $0.10 10.6% –0.024% $45,982 $284

2020 $0.13 $0.09 $0.10 10.4% –0.024% $45,886 $322

2021 $0.13 $0.09 $0.10 10.3% –0.024% $46,029 $349

2022 $0.13 $0.09 $0.10 10.3% –0.024% $46,840 $352

2023 $0.13 $0.09 $0.10 10.3% –0.024% $47,652 $356

2024 $0.13 $0.09 $0.10 10.3% –0.024% $48,463 $359

2025 $0.13 $0.09 $0.10 10.4% –0.024% $49,275 $363

2026 $0.13 $0.09 $0.10 10.4% –0.024% $50,081 $366

2027 $0.13 $0.09 $0.10 10.4% –0.024% $50,886 $369

2028 $0.13 $0.09 $0.10 10.4% –0.024% $51,692 $373

2029 $0.13 $0.09 $0.10 10.4% –0.024% $52,498 $376

2030 $0.13 $0.09 $0.10 10.4% –0.024% $53,304 $379

2031 $0.13 $0.09 $0.10 10.4% –0.024% $54,109 $383

2032 $0.13 $0.09 $0.10 10.4% –0.024% $54,915 $386

2033 $0.13 $0.09 $0.10 10.4% –0.024% $55,721 $390

2034 $0.13 $0.09 $0.10 10.4% –0.024% $56,527 $393

2035 $0.13 $0.09 $0.10 10.4% –0.024% $57,333 $397

2036 $0.13 $0.09 $0.10 10.4% –0.024% $58,138 $400

NPVb $742,250 $5,626

a Figures are in 2001 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2030 time period. 
Economic Impact Analysis

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Table 10D-4. Impacts on the Nonroad Fuel Market in PADD 5

(Average Price per Gallon = $0.87)a

Year

Engineering

Cost/Unit

15ppm

Engineering

Cost/Unit

500ppm

Absolute

Change

in Price

Change

in Price

(%)

Change in

Quantity

(%)

Total

Engineering

Costs ($103)

Change in

Producer

Surplus for Fuel

Producers ($103)

2007 — $0.01 $0.01 0.5% –0.003% $3,004 –$24

2008 — $0.01 $0.01 0.9% –0.005% $5,266 –$68

2009 — $0.01 $0.01 0.9% –0.005% $5,382 –$70

2010 $0.05 $0.02 $0.02 1.8% –0.008% $11,146 –$44

2011 $0.05 $0.04 $0.03 2.8% –0.015% $17,727 –$171

2012 $0.05 $0.04 $0.03 2.8% –0.019% $18,083 –$287

2013 $0.05 $0.04 $0.03 2.8% –0.020% $18,428 –$322

2014 $0.06 $0.04 $0.04 4.4% –0.022% $29,541 –$321

2015 $0.07 $0.04 $0.06 5.9% –0.023% $40,159 –$377

2016 $0.07 $0.04 $0.06 5.9% –0.023% $40,915 –$385

2017 $0.07 $0.04 $0.06 5.9% –0.023% $41,678 –$390

2018 $0.07 $0.04 $0.06 5.9% –0.023% $42,453 –$398

2019 $0.07 $0.04 $0.06 5.9% –0.023% $43,236 –$406

2020 $0.07 $0.04 $0.06 5.9% –0.023% $44,001 –$413

2021 $0.07 $0.04 $0.06 5.9% –0.023% $44,768 –$420

2022 $0.07 $0.04 $0.06 5.9% –0.023% $45,551 –$428

2023 $0.07 $0.04 $0.06 5.9% –0.023% $46,317 –$436

2024 $0.07 $0.04 $0.06 5.9% –0.023% $47,090 –$444

2025 $0.07 $0.04 $0.06 5.9% –0.023% $47,859 –$452

2026 $0.07 $0.04 $0.06 5.9% –0.023% $48,627 –$460

2027 $0.07 $0.04 $0.06 5.9% –0.023% $49,396 –$468

2028 $0.07 $0.04 $0.06 5.9% –0.023% $50,166 –$476

2029 $0.07 $0.04 $0.06 5.9% –0.023% $50,936 –$485

2030 $0.07 $0.04 $0.06 5.9% –0.023% $51,707 –$493

2031 $0.07 $0.04 $0.06 5.9% –0.023% $52,478 –$501

2032 $0.07 $0.04 $0.06 5.9% –0.023% $53,251 –$509

2033 $0.07 $0.04 $0.06 5.9% –0.023% $54,024 –$517

2034 $0.07 $0.04 $0.06 6.0% –0.023% $54,797 –$525

2035 $0.07 $0.04 $0.06 6.0% –0.023% $55,572 –$533

2036 $0.07 $0.04 $0.06 6.0% –0.023% $56,347 –$541

NPVb $647,478 –$6,343

a Figures are in 2001 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2030 time period. 
Final Regulatory Impact Analysis

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APPENDIX 10E: Time Series of Social Cost

This appendix provides a time series of the rule’s estimated social costs from 2007 through 2036. Costs are

presented in 2002 dollars.
10-163

Table 10E-1. Time Series of Market Impacts

2007 2008 2009 2010 2011 2012 2013 2014 

Engine Producers Total $0.0 $14.9 $14.9 $14.9 $29.4 $38.9 $42.0 $5Equipment Producers Total $0.3 $8.8 $8.8 $9.6 $88.7 $131.4 $143.1 $17

Construction Equipment $0.2 $1.8 $1.8 $2.3 $41.3 $60.8 $64.0 $8Agricultural Equipment $0.1 $2.4 $2.4 $2.6 $36.0 $48.3 $51.8 $6Industrial Equipment $0.0 $4.6 $4.7 $4.7 $11.4 $22.3 $27.2 $3

Application Producers & Consumers Total $123.9 $277.3 $283.2 $535.6 $1,008.7 $1,325.1 $1,496.7 $1,64

Total Producer $45.5 $108.4 $110.8 $216.5 $418.5 $553.0 $620.9 $68Total Consumer $78.4 $168.8 $172.4 $319.1 $590.2 $772.1 $875.7 $96Construction $47.5 $97.1 $99.3 $200.0 $409.1 $548.1 $584.3 $65Agriculture $35.9 $75.3 $77.0 $144.8 $309.7 $394.7 $430.0 $47Manufacturing $40.5 $104.9 $107.0 $190.7 $289.9 $382.4 $482.4 $51

Fuel Producers Total $0.2 $1.7 $1.7 –$0.2 $4.7 $7.2 $8.0 $

PADD 1 & 3 $0.1 $0.7 $0.7 $0.1 $2.6 $3.7 $4.1 $PADD 2 $0.0 $0.8 $0.8 –$0.1 $1.9 $2.9 $3.3 $PADD 4 $0.0 $0.1 $0.1 –$0.3 –$0.2 $0.0 $0.0 $PADD 5 $0.0 $0.1 $0.1 $0.1 $0.4 $0.6 $0.6 $

Transportation Services, Total $18.9 $33.1 $33.5 $71.5 $102.0 $103.6 $104.9 $9

Locomotive $0.0 $0.2 $0.2 $0.5 $1.0 $1.3 $1.6 $Marine $0.0 $0.1 $0.1 $0.3 $0.5 $0.7 $0.9 $Application Markets Not Included in $18.9 $32.7 $33.1 $70.7 $100.5 $101.6 $102.4 $9

Operating Savings –$160.9 –$281.9 –$288.0 –$304.6 –$311.4 –$302.2 –$284.7 –$29Total –$17.6 $53.9 $54.2 $326.7 $922.3 $1,304.0 $1,510.0 $1,69

(continued)
Table 10E-1. Time Series of Market Impacts (continued)

2017 2018 2019 2020 2021 2022 2023 2024 

Engine Producers Total $28.4 $10.4 $0.9 $0.1 $0.1 $0.1 $0.1 $Equipment Producers Total $148.6 $139.7 $125.0 $122.7 $74.2 $40.9 $30.4 $

Construction Equipment $68.9 $67.3 $60.2 $57.8 $34.4 $19.8 $17.0 $Agricultural Equipment $49.3 $46.5 $39.7 $39.7 $20.6 $11.5 $8.9 $Industrial Equipment $30.4 $26.0 $25.2 $25.2 $19.1 $9.6 $4.5 $

Application Producers & Consumers Total $1,745.0 $1,774.4 $1,804.0 $1,826.1 $1,849.9 $1,879.3 $1,908.3 $1,93

Total Producer $728.2 $740.5 $752.9 $762.2 $772.3 $784.6 $796.8 $80Total Consumer $1,016.8 $1,033.9 $1,051.1 $1,063.8 $1,077.6 $1,094.7 $1,111.6 $1,12

Construction $709.2 $721.4 $733.6 $744.0 $754.9 $767.1 $779.2 $79Agriculture $502.2 $510.9 $519.6 $524.3 $530.0 $538.6 $547.1 $55Manufacturing $533.6 $542.1 $550.8 $557.8 $565.0 $573.6 $582.0 $59

Fuel Producers Total $10.9 $11.1 $11.3 $11.2 $11.2 $11.5 $11.7 $1

PADD 1 & 3 $5.3 $5.4 $5.5 $5.6 $5.8 $5.9 $6.0 $PADD 2 $4.6 $4.7 $4.8 $4.6 $4.5 $4.5 $4.6 $PADD 4 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $PADD 5 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $

Transportation Services, Total $90.2 $91.3 $92.6 $95.6 $98.1 $99.5 $100.5 $10

Locomotive $1.8 $1.9 $1.9 $2.0 $2.0 $2.1 $2.1 $Marine $1.0 $1.1 $1.1 $1.1 $1.1 $1.2 $1.2 $Application Markets Not Included in $87.3 $88.3 $89.6 $92.6 $95.0 $96.2 $97.2 $9

Operating Savings –$260.8 –$249.4 –$239.3 –$227.4 –$218.2 –$212.8 –$208.1 –$20Total $1,762.2 $1,777.6 $1,794.6 $1,828.3 $1,815.3 $1,818.5 $1,843.0 $1,85

(continued)
Table 10E-1. Time Series of Market Impacts (continued)

2027 2028 2029 2030 2031 2032 2033 2034 

Engine Producers Total $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 $Equipment Producers Total $5.7 $5.8 $5.9 $5.9 $6.0 $6.1 $6.2 $

Construction Equipment $3.8 $3.9 $3.9 $4.0 $4.0 $4.1 $4.1 $Agricultural Equipment $1.8 $1.8 $1.8 $1.9 $1.9 $1.9 $1.9 $Industrial Equipment $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 $

Application Producers & Consumers Total $2,024.9 $2,054.0 $2,083.1 $2,112.3 $2,141.4 $2,170.6 $2,199.8 $2,22

Total Producer $845.6 $857.8 $870.0 $882.2 $894.4 $906.6 $918.8 $93Total Consumer $1,179.3 $1,196.2 $1,213.1 $1,230.1 $1,247.0 $1,264.0 $1,280.9 $1,29

Construction $827.6 $839.7 $851.8 $863.8 $875.9 $888.0 $900.1 $91Agriculture $581.2 $589.7 $598.3 $606.8 $615.3 $623.8 $632.3 $64Manufacturing $616.1 $624.6 $633.1 $641.6 $650.2 $658.8 $667.4 $67

Fuel Producers Total $12.5 $12.7 $13.0 $13.2 $13.4 $13.6 $13.8 $1

PADD 1 & 3 $6.4 $6.5 $6.6 $6.7 $6.8 $6.9 $7.0 $PADD 2 $5.0 $5.1 $5.2 $5.2 $5.3 $5.4 $5.5 $PADD 4 $0.2 $0.2 $0.2 $0.3 $0.3 $0.3 $0.3 $PADD 5 $0.9 $0.9 $0.9 $1.0 $1.0 $1.0 $1.0 $

Transportation Services, Total $105.3 $106.5 $107.8 $109.0 $110.3 $111.6 $112.9 $11

Locomotive $2.3 $2.4 $2.4 $2.5 $2.5 $2.6 $2.6 $Marine $1.3 $1.3 $1.4 $1.4 $1.4 $1.5 $1.5 $Application Markets Not Included in $101.7 $102.8 $104.0 $105.2 $106.3 $107.5 $108.8 $11

Operating Savings –$196.0 –$194.9 –$194.3 –$194.1 –$194.3 –$194.8 –$195.4 –$19Total $1,952.5 $1,984.2 $2,015.5 $2,046.4 $2,076.9 $2,107.2 $2,137.4 $2,16

a Figures are in 2002 dollars. b Net present values are calculated using a social discount rate of 3 percent over the 2004 to 2036 time period. 
Final Regulatory Impact Analysis

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APPENDIX 10F: Model Equations

To enhance understanding of the economic model EPA used in this report, additional details about the model’s

structure are provided in this appendix. The equations describing supply, final demand, and intermediate (i.e.,

derived) demand relationships are presented below along with a brief description of the solution algorithm.

10F.1 Model Equations

A constant-elasticity functional form was selected for all supply and final demand functions. The general form

and description of these equations are presented below:

Supply Equation: Qx = a(Px – )c – )cy)

g (10F.1)

Final Demand Equation: Qx = aPx

0 (10F.2)

where 

x = production output, 

y = production input, 

Qx = quantity of output (x) supplied or demanded,

Px = market price for output (x),

a = constant,

)c = direct supply shift ($/Qx), 

)cy = indirect supply shift resulting from change in the price of input y, and

g,0 = these parameters can be interpreted as the own-price elasticity of supply/demand for the

economic agent (see Tables 10.3-12 and 10.3-13 for values of these parameters). 

With this choice of functional form, the supply and demand elasticities are assumed to remain constant over the

range of output affected by the regulation. This can be demonstrated by applying the definition of own-price

elasticity of demand:

. (10F.3) dq

dp pq

 Eap p

a (1 )

(1 )

•= • = − − ε εε

The intermediate input (Qy) demands is specified within the supply chain as a function of output (Qx). The

subscript “0" denotes baseline and the subscript “1" denotes with regulation. 

Derived Demand Equation: Qy = f(Qx) (10F.4a)

Qy1 = Qy0(1+)Qx/Qx) (10F.4b)

Computing Supply/Demand Function Constants. Using the baseline price, quantity, and elasticity parameter,

the value of the constants can be computed. For example, supply function constants can be calculated as follows:

Constant Calibration: a = (10F.5) Q

P

x

x

0

0 ( )ε

Direct Supply Shift (Dc). The direct upward shift in the supply function is calculated by using the annualized

compliance cost estimates provided by the engineering cost analysis. Computing the supply shift in this manner

treats the compliance costs as the conceptual equivalent of a unit tax on output. 

Indirect Supply Shift (Dcy). The indirect upward shift in the supply function is calculated by using the change in

input (y) prices (i.e., engines, equipment, and/or fuel) that result from the direct compliance costs introduced into the

model. Only two types of suppliers are affected by these changes: equipment producers that use diesel engines and

application markets that use equipment with diesel engines and diesel fuel. The term Dcy is computed as follows:
Economic Impact Analysis

T

Note that engines sold to foreign equipment manufacturers are not included in the domestic

engine market because they are subject to different (foreign) environmental regulations and

hence are considered different products.

U These are: agricultural equipment >600 hp; gensets & welders > 600 hp; refrigeration & A/C >

71 hp (4 hp categories); and lawn & garden >600 hp.

10-167

∆

∆

c

P Q

Q y

y y0

x0

= • . (10F.6)

10F.2 Engine Markets

As described in Section 10.3.3.1, seven separate engine markets were modeled segmented by engine size in

horsepower (the EIA includes more horsepower categories than the standards, allowing more efficient use of the

engine compliance cost estimates developed for this rule): 

C less than 25 hp

C 26 to 50 hp

C 51 to 75 hp

C 76 to 100 hp

C 101 to 175 hp

C 176 to 600 hp

C greater than 601 hp

In each of these engine markets, there are three types of suppliers: captive suppliers (engines are consumed

internally by integrated equipment manufacturers), merchant suppliers (engines are sold on the open market), and

foreign suppliers. These supply segments are represented by upward-sloping supply functions. On the demand side,

consumers of engines include integrated and nonintegrated equipment manufacturersT

 and are represented by derived

demand functions (Eqs. [10F-4a] and [10F.4b]). 

Captive Domestic Supply Equation: S a (p c) engcap 1 = − ε (10F.7)

Merchant Domestic Supply Equation: S a (p c) engmer 2 = − ε (10F.8)

Import Supply Equation: M a(p c) eng = − ε (10F.9)

Integrated Demand Equation: DI = S (Sequip) (10F.10)

Nonintegrated Demand Equation: DNI = S(Sequip) (10F.11)

Market Clearing Condition: Sengcap + Sengmer + Meng = DI

 + DNI (10F.12)

10F.3 Equipment Markets

As described in Section 10.3.3.2, integrated and nonintegrated equipment manufacturers supply their products

into a series of 42 equipment markets (7 horsepower categories within 7 application categories; there are 7

horsepower/application categories that did not have sales in 2000 and are not included in the model, so the total

number of diesel equipment markets is 42, not 49).U The equipment types are: 
Final Regulatory Impact Analysis

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C agricultural 

C construction

C refrigeration 

C generators and welder sets

C lawn and garden 

C pumps and compressors

C general industrial

Each individual equipment market is comprised of two aggregate suppliers groups: (1) domestic integrated

suppliers that produce and consume their own engines (captive engines) and (2) domestic nonintegrated suppliers

that purchase engines from the open market to be used in their equipment (merchant engines).

On the demand side, each of the 42 equipment markets is linked to one of three application markets

(agricultural, construction, and manufacturers) is represented by derived demand functions (Eq. [10F.4a and

10F.4b])

Domestic Integrated Supply Equation: S a(p c) eqI = − ε (10F.13)

Domestic Nonintegrated Supply Equation: (10F.14) S a(p c c ) eqNI y = −− ε

Domestic Demand Equation: D Q Q

Q eq eq

qpp

qpp0

= +













 ∑  1

∆

(10F.15)

Market Clearing Condition: SeqI + SeqNI = Deq (10F.16)

10F.4 Application Markets

As described in Section 10.3.3.3, there are three application markets that supply products and services to

consumers:

C agricultural

C construction

C manufacturing

The supply in each of these three application markets is the sum of a domestic supply and an foreign (import)

supply. The consumers in the application markets are represented by a domestic demand and a foreign (export)

demand function. 

Supply Equation: S a(papp c p) app

EkS = −− β∆ (10F.17)

Foreign (Import) Supply Equation: S ap app app

E = (10F.18)

Domestic Demand Equation: D ap app = η (10F.19)

Foreign (Export) Demand Equation: X ap app = η (10F.20)

Market Clearing Condition: Sapp + Mapp = Dapp+ Xapp (10F.21)

$0, $1, and $2 are the baseline input shares of equipment, fuel, and transportation services.

10F.5 Fuel Markets

As described in Section 10.3.3.4, eight nonroad diesel fuel markets were modeled: two distinct nonroad diesel

fuel commodities in four regional markets. The two fuels are:
Economic Impact Analysis

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C 500 ppm nonroad diesel fuel, and

C 15 ppm nonroad diesel fuel.

The four regional nonroad diesel fuel markets are 

C PADD 1 and 3

C PADD 2 

C PADD 4 

C PADD 5 (includes Alaska and Hawaii; California fuel volumes that are not affected by the program because

they are covered by separate California nonroad diesel fuel standards are not included in the analysis)

The supply and demand for nonroad diesel fuel is specified for the model for four regional diesel fuel markets. 

Derived demand of diesel fuel comes from three application markets. The equations for PADD district j are

specified below: 

Supply Equation: Sj

 = a(Pj – )c)g (10F.22)

Derived Demand Equation: Dj

 = G Q 1 (10F.23)

Q

Q j0

app

app0

+

















∆

Market Clearing Condition: Sj = Dj (10F.24)

10F.6 Locomotive and Marine Transportation Markets 

There are two transportation service markets that supply services to the application markets:

C locomotive

C marine

The supply in each of these three application markets is the sum of a domestic supply

Supply Equation: S a(ptrans c p ) fuel

EkS

trans = −− β∆ (10F.25)

Market Clearing Condition: Strans = Dtrans (10F.26)

$ is the baseline input share of fuel . Q

Q

fuel0

app0

















10F.7 Market-Clearing Process and Equations 

Supply responses and market adjustments can be conceptualized as an interactive process. Producers facing

increased production costs due to compliance with the control program are willing to supply smaller quantities at the

baseline price. This reduction in market supply leads to an increase in the market price that all producers and

consumers face, which leads to further responses by producers and consumers and thus new market prices, and so

on. The new with-regulation equilibrium is the result of a series of iterations in which price is adjusted and

producers and consumers respond, until a set of stable market prices arises where total market supply equals market

demand. 

Market-Clearing Equation: Total Supply = Total Demand. (10F.27)

The algorithm for determining with-regulation equilibria can be summarized by six recursive steps:

1. Impose the control costs on affected supply segments, thereby affecting their supply decisions.
Final Regulatory Impact Analysis

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2. Recalculate the market supply in each market. Excess demand currently exists.

3. Determine the new prices via a price revision rule. A rule similar to the factor price revision rule described

by Kimbell and Harrison (1986) is used. Pi

 is the market price at iteration i, qd is the quantity demanded,

and qs is the quantity supplied. The parameter z influences the magnitude of the price revision and speed of

convergence. The revision rule increases the price when excess demand exists, lowers the price when

excess supply exists, and leaves the price unchanged when market demand equals market supply. The price

adjustment is expressed as follows:

Pi+1 = P1 • (10F.26) q

q

d

s

z 



 





4. Recalculate market supply with new prices.

5. Compute market demand in each market.

6. Compare supply and demand in each market. If equilibrium conditions are not satisfied, go to Step 3,

resulting in a new set of market prices. Repeat until equilibrium conditions are satisfied (i.e., the ratio of

supply and demand is arbitrarily close to one).
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APPENDIX 10G: Elasticity Parameters for Economic Impact Modeling

The Nonroad Diesel Economic Impact Model (NDEIM) relies on elasticity parameters to estimate the

behavioral response of consumers and producers to the regulation and its associated costs. To operationalize the

market model, supply and demand elasticities are needed to represent the behavioral adjustments that are likely to be

made by market participants. The following parameters are needed:

C supply and demand elasticities for application markets (agriculture, construction, and manufacturing)

C supply elasticities for equipment markets

C supply elasticities for engine markets

C supply elasticities for diesel fuel markets

C supply elasticities for locomotive and marine transportation markets

Note that demand elasticities for the equipment, engine, diesel fuel, and transportation markets are not estimated

because they are derived internally in the model. They are a function of changes in output levels in the applications

markets.

Tables 10G-1 and 10G-2 contain the demand and supply elasticities used to estimate the economic impact of the

rule. Two methods were used to obtain the supply and demand elasticities used in the NDEIM. First, the

professional literature was surveyed to identify elasticity estimates used in published studies. Second, when

literature estimates were not available for specific markets, established econometric techniques were used to estimate

supply and demand elasticity parameters directly. Specifically, the supply elasticities for the agricultural and

construction application markets and the supply elasticity for the diesel fuel market were obtained from the

literature. The supply elasticity for the manufacturing market is assumed to be the same as for the construction

market. The supply elasticities for all of the application markets and for equipment and engine markets were

estimated econometrically. 

This appendix discusses the literature for elasticities based on existing studies and presents the data sources and

estimation methodology and regression results for the econometric estimation.

Finally, it should be noted that these elasticities reflect intermediate run behavioral changes. In the long run,

supply and demand are expected to be more elastic since more substitutes may become available.
Final Regulatory Impact Analysis

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Table 10G-1

Summary of Market Demand Elasticities Used in the NDEIM

Market Estimate Source Method Input Data Summary

Applications

Agriculture –0.20 EPA econometric

estimate

Productivity shift

approach (Morgenstern,

Pizer, and Shih, 2002) 

Annual time series from

1958 ! 1995 developed by 

Jorgenson et al.

(Jorgenson, 1990; Jorgenson,

Gollop, and Fraumeni, 1987)

Construction –0.96 EPA econometric

estimate

Simultaneous equation

(log-log) approach

Annual time series from

1958 ! 1995 developed by

Jorgenson et al. (Jorgenson,

1990; Jorgenson, Gollop, and

Fraumeni, 1987)

Manufacturing –0.58 EPA econometric

estimate

Simultaneous equation

(log-log) approach. 

Annual time series from

1958 ! 1995 developed by

Jorgenson et al. (Jorgenson,

1990; Jorgenson, Gollop, and

Fraumeni, 1987)

Transportation

Services

Locomotive Derived demand In the derived demand approach, 

C compliance costs increase prices and decrease demand

for products and services in the application markets;

C this in turn leads to reduced demand for diesel

equipment, engines and fuel, which are inputs into the

production of products and services in the application

markets 

 

Marine Derived demand

Equipment

Agriculture Derived demand

Construction Derived demand

Pumps/

compressors

Derived demand

Generators and

Welders

Derived demand

Refrigeration Derived demand

Industrial Derived demand

Lawn and

Garden

Derived demand

Engines Derived demand

Diesel fuel Derived demand
Economic Impact Analysis

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Table 10G-2

Summary of Market Supply Elasticities Used in the NDEIM

Markets Estimate Source Method Input Data Summary

Applications

Agriculture 0.32 Literature-based

estimate

Production-weighted

average of individual

crop estimates ranging

from 0.27 to 0.55.

(Lin et al., 2000) 

Agricultural Census data

1991 ! 1995

Construction 1 Literature-based

estimate

Based on Topel and

Rosen, (1988).a

Census data, 1963 ! 1983

Manufacturing 1 Literature-based

estimate

Literature estimates are

not available so assumed

same value as for

Construction market

Not applicable

Transportation

Services

Locomotive 0.6 Literature-based

estimate

Method based on Ivaldi

and McCollough (2001)

Association of American

Railroads 1978-1997

Marine 0.6 Literature-based

estimate

Literature estimates not

available so assumed

same value as for

locomotive market

Not applicable

Equipment

Agriculture 2.14 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3523

Construction 3.31 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3531

Pumps/

compressors

2.83 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3561 and 3563

Generators/

Welder Sets

2.91 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3548

Refrigeration 2.83 EPA econometric

estimate

Assumed same as

pumps/compressors

Industrial 5.37 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3537

Lawn and

Garden

3.37 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3524

Engines 3.81 EPA econometric

estimate

Cobb-Douglas

production function

Census data 1958-1996; SIC

3519

Diesel fuel 0.24 Literature based

estimate

Based on Considine

(2002).b

 

From Energy Intelligence

Group (EIG); 1987-2000c

a Most other studies estimate ranges that encompass 1.0, including DiPasquale (1997) and DiPasquale and Wheaton (1994). b Other estimates range from 0.02 to 1.0 (Greene and Tishchishyna, 2000). However, Considine (2002) is one of the few studies that estimates a

supply elasticity for refinery operations. Most petroleum supply elasticities also include extraction. c This source refers to the data used by Considine in his 2002 study.
Final Regulatory Impact Analysis

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10G.1 Application Markets - Demand Elasticities

There are three application markets in the NDEIM: agricultural, construction, and

manufacturing. Demand elasticities for the construction and manufacturing application markets

were estimated using a simultaneous equation (two-stage least squares) method. This approach

was also investigated for the agricultural application market; however, the estimated demand

elasticity parameter for that market was not statistically significant. For this reason, a production

function approach (Morgenstern, Pizer and Shih, 2002) was employed for the agricultural

application market. Publicly available data developed by Dale Jorgenson and his associates

(Jorgenson, 1990; Jorgenson, Gollop, and Fraumeni, 1987) were used in the regression analysis. 

A time series of 38 observations, from 1958 to 1995, was used to estimate the demand

elasticities in both the two-stage least squares and production function approach. Both of these

techniques are described below.

10G.1.1 Construction and Manufacturing Demand Elasticities

10G.1.1.1 Description of Simultaneous Equation Method

The demand elasticities for the construction and manufacturing application markets were

estimated using a simultaneous equation (two-stage least squares) approach. The methodology

is described below and the individual regression results are presented in Appendix 10F. 

In a partial equilibrium model, supply and demand are represented by a series of

simultaneous interdependent equations, in which the price and quantity produced of a product

are simultaneously determined by the interaction of producers and consumers in the market. In

simultaneous equations models, where one variable feeds back in to the other equations, the error

terms are correlated with the endogenous variable. As a result, estimating parameter values

using the ordinary least squares (OLS) regression method for each individual equation yields

biased and inconsistent parameter estimates. Therefore, OLS is not an appropriate estimation

technique. 

Instead, a simultaneous equations approach is used. In the simultaneous equations approach

both the supply and demand equations for the market are specified and parameters for the twoequation system are estimated simultaneously. 

The log-log version of the model is specified as follows:

Supply: Qts = a0 + a1Pt

 + a2PLt + a3PKt + a4PMt + et (10G.1a)

Demand: Qtd= b0 + b1Pt

 + b2HHt + b3It + vt (10G.1b)

where

Qt = log of quantity of the market product in year t

Pt = log of price of the market product in year t 

PLt = log of cost of labor inputs in year t 
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PKt = log of cost of capital inputs in production in year t

PMt = log of cost of material inputs in production in year t 

HHt = log of number of households in year t 

It = average income per household in year t 

et, vt = error terms in year t 

The parameter estimates â1 and are the estimated price elasticity of supply and price elasticity $

b1

of demand, respectively. 

The first equation defines quantity supplied in each year as a function of the product price

and the cost of inputs: labor, capital and materials. The second equation defines the quantity

demanded in each year as a function of the production price, the number of households, and the

average income per household. The equilibrium condition is that supply equals demand

equilibrium: Qts = Qtd

Application of this two-stage least square regression approach was successful for estimating

the demand elasticity parameters for use here but was unsuccessful for estimating the supply

elasticities. The supply elasticity estimates were negative and not statistically significant. 

Therefore, as noted above, literature estimates were used for the supply elasticities for the three

application markets in the NDEIM.

To estimate the demand elasticities using this two-stage least squares approach, it is

necessary to first estimate the reduced-form equation for price using OLS. The reduced-form

equation expresses price as a function of all exogenous variables in the system:

Pt

 = fn(PLt , PKt , PMt , HHt , It)

The results of this regression are used to develop fitted values of the dependent price variable Pt

(this is a new instrumental variable for price). The fitted values by construction will be

independent of error terms in the demand equation. In the second stage regression, the fitted

price variable Pt (the instrumental variable) is used as a replacement for Pt, in the demand

equation. An OLS is performed on this equation, which produces a consistent, unbiased estimate

of the demand elasticity b1.

10G.1.1.2 Construction Application Market Demand Elasticity

The results of the simultaneous equation method for the construction demand elasticity are

presented in Table 10G-3. The estimated demand elasticity is !0.96 and is statistically

significant with a t-statistic of –3.83. This inelastic estimate implies that a 1 percent increase in

price will lead to a 0.96 percent decrease in demand for construction, and means that the quantity

of goods and services demanded is expected to be fairly insensitive to price changes.

Table 10G-3. Construction Demand Elasticity
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Number of Observations = 29

R squared = 0.78

Adjusted R squared = 0.75

Variable Estimated Coefficients t-statistic

intercept 18.83 5.19

In price –0.96 –3.83

In number of households –1.73 –3.37

In average income per

household

–1.67 5.34

10G.1.1.3 Manufacturing Application Market Demand Elasticity

The results of the simultaneous equation method for the manufacturing market are presented

in Table 10G-4. The estimated demand elasticity is !0.58 and is statistically significant with a tstatistic of –2.24. This inelastic estimate implies that a 1 percent increase in price will lead to a

0.58 percent decrease in the demand for manufactured products, and means that the quantity of

goods and services demanded is expected to be fairly insensitive to price changes.

Table 10G-4. Manufacturing Demand Elasticity

Number of Observations = 29

R squared = 0.83

Adjusted R squared = 0.81

Variable Estimated Coefficients t-statistic

intercept 6.16 0.84

In price –0.58 –2.24

In number of households 0.19 0.23

In average income per

household

0.62 1.49

10G.1.2 Agricultural Application Market Demand Elasticity

10G.1.2.1: Description of Productivity Shift Approach

When the simultaneous equation method was attempted for the agricultural application

market, the resulting demand elasticity parameter estimate was not statistically significant. 

Thus, the demand elasticity for the agricultural market was estimated using the productivity shift

approach. This is a technique that regresses historical data for aggregate output on industry

productivity (Morgenstern, Pizer, and Shih, 2002). 
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P

Q

S3

S2

S1

D

Figure 10G-1

Productivity Shifts Trace-Out Demand Curve

Îln prodt

 = 3sh (Lsh,t+Lsh,t-1) (lnPsh,t-lnPsh,t-1) - (lnPOt-lnPOt-1) (10.G-2)

 M

As shown in Figure 10G-1, changes in industry productivity represent shifts in the supply

curve. The supply curve shifts in conjunction with the known output values trace-out the

demand curve and enables the estimation of the demand elasticity. Because the agricultural

sector is relatively small compared to the entire economy, it is reasonable to assume that the

productivity changes do not shift the demand curve through income effects.

The demand elasticity (>d) is estimated through a simple regression of the annual change in

the natural log of outputs on change in the natural log of productivity: 

a ln outputt

 = >d a ln prodt + gt

where

outputt

 = output t is the industry output in year t

prodt = industry productivity in year t

gt

 = random error term

The change in the natural log of productivity is computed as the log difference between the

annual change in input price and the annual change in output price:

where

P = input prices

PO = output prices

L = input shares
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Eq. (10G.2) is a similar to a standard quantity-based definition of productivity (output divided by

input), but expressed in terms of input and output prices. Under a competitive market with zeroprofit assumptions, revenue equals cost, and the price of output must equal the price of input

divided by the standard definition of productivity: 

PO = PI ( QI / QO )

Thus, 

PI / PO = QO / QI

where

QO = quantity of output

QI = quantity of input 

Since QO / QI is a quantity based productivity, PI / PO is an equivalent measure of productivity

according to the above equation. The difference in logged changes in PI and PO is a valid

measure of productivity growth (Pizer, 2002). 

10G.1.2.2 Agricultural Application Market Demand Elasticity

The results of the estimated agricultural model are presented in Table 10G-5. The demand

elasticity estimate is !0.20 and is statistically significant with a t-statistic of 2.31. This implies

that a 1 percent increase in price will lead to a 0.2 percent decrease in demand, and means that

the quantity of goods and services demanded is expected to be fairly insensitive to price changes.

Table 10G-5. Agricultural Demand Elasticity

Number of Observations = 38

R squared = 0.13

Adjusted R squared = 0.11

Variable Estimated Coefficients t-statistic

intercept 0.02 3.49

ln productivity t –0.20 2.31

10G.2 Application Market - Supply Elasticities

Professional literature sources were used to obtain supply elasticity estimates for the

applications markets. These literature sources used are described below.

It should be noted that both of the econometric estimation methods described above, the

simultaneous equation approach and the production function approach, were also attempted for

the supply elasticities. However, because of the great variety of the production processes in
Economic Impact Analysis

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these aggregate industry sectors (heterogeneity), parameter estimates were either not statistically

significant or did not conform with standard microeconomic theory (i.e., estimates were not

upward sloping). 

10G.2.1 Agricultural Application Market Supply Elasticity

Obtaining reasonable estimates of supply response in agriculture has been a persistent

problem since the inception of farm price support programs in the 1930s. The nonrecourse

marketing loans, deficiency payments, and conservation set-asides that make up the current farm

price support system distort equilibrium prices to the point that any econometric estimates are

difficult to formulate or support. 

A recent study by economists at the USDA’s Economic Research Service provides an

approach to estimating agricultural demand elasticities (Lin et al., 2000). Taking into account

recent changes in the 1996 Farm Bill, the authors measure nationwide acreage price elasticity

values for the seven major agricultural crops, obtaining values ranging from 0.269 for soybeans

to 0.550 for sorghum. Although a composite number for all farm output is not reported, an

average value of 0.32 can be obtained by weighting the reported values by the acreage planted

for each crop. This value was used for the supply elasticity in the agriculture application market. 

This estimated elasticity is inelastic, which means that the quantity of goods and services

supplied is expected to be fairly insensitive to price changes.

Although the literature estimates vary, this estimate conforms closely to historical evidence

and economic theory of small but positive supply elasticities. This determination of price having

little impact on supply (referred to as inelastic supply) is consistent with a historical observation

that total acreage cultivated varies little from year to year. Between 1986 and 2001, for instance,

U.S. cropland harvested has ranged from 289 to 318 million acres, with an average of 305

million acres over that 15-year period. A low supply elasticity is also supported by the fact that

there are few alternative uses (except in the very long run) for cropland, capital, and labor

employed in farming. Abandonment or redeployment of farm assets is an often irreversible

decision, and one not greatly affected by annual price swings.

10G.2.2 Construction Application Market Supply Elasticity

Although the construction market does not suffer from government-induced distortions to

prices and quantities, the evidence on supply elasticity is even more varied than that for

agriculture. Estimates of supply elasticity ranging from near zero to infinity have been reported

in credible papers on housing construction published during the past 20 to 30 years. A literature

survey paper by DiPasquale (1997) describes the methodological issues that have led to this

variety of responses. A key issue is the conceptual problem of distinguishing between increases

in the stock the of housing (or other structures) through new construction and changes in the

flow of housing services, which can also include renovation, apartment or condominium

conversion, and abandonment.

DiPasquale cites a number of published studies that suggest that a value of 1.0 for supply

elasticity is appropriate. In the study that most closely matches the analysis for this regulation,
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Poterba (1984) estimated elasticity of new construction with respect to real house prices ranging

from 0.5 to 2.3, depending on the specification. A study by Topel and Rosen investigating

asset-markets and also found a short-run elasticity value of 1.0 (Topel and Rosen, 1988). 

Finally, DiPasquale cites one of her own papers that estimated values of 1.0 to 1.2 for the price

elasticity of construction (DiPasquale and Wheaton, 1994). Based on these studies, a value of

1.0 was used for the supply elasticity in the construction application market. This unit elastic

elasticity means that the quantity supplied is expected to vary directly with changes in prices.

Estimates of supply response for other portions of the construction market, namely

nonresidential buildings and nonbuilding (roads and bridges, water and sewer systems, etc.), are

not available in the literature. However, the similarity between technologies employed in

construction of residential and other nonindustrial buildings suggests that supply elasticities

should be comparable. In addition, residential construction accounts for a significant portion of

construction activity. According to the Census Bureau’s most recent Annual Value of

Construction Put in Place report, residential and nonindustrial buildings accounted for about 77

percent of the $842 billion in construction spending in 2001, with new residential housing

making up about 33 percent (U.S. Census Bureau, 2002). 

10G.2.3 Manufacturing Application Market Supply Elasticity

No supply elasticity estimates were available in the professional literature for the aggregate

manufacturing sector. For this reason, a unitary supply elasticity of 1.0 was used in the model. 

This unit elastic elasticity means that the quantity supplied is expected to vary directly with

changes in prices. A sensitivity analysis for this assumed elasticity is presented in Appendix 10I.

10G.3 Engine and Equipment Markets Supply Elasticity

Published sources for the price elasticity of supply for diesel engine and diesel equipment

markets were not available. Therefore, the supply elasticities used in the model were estimated

econometrically using a production function cost minimization approach. 

10G.3.1 Production Function Cost Minimization Approach

The production function cost minimization approach for econometrically estimating the

supply elasticities is based on the cost-minimizing behavior of the firm subject to production

function constraints. The production function describes the relationship between output and

inputs. For this analysis, a Cobb-Douglas, or multiplicative form, was used as the functional

form of the production function:

Qt = A kt

"k

 Lt

"L

 Mt

"k

 t8 (10G-3)

where

Qt = output in year t
Economic Impact Analysis

VCapital consumed is defined as the value added minus labor expenditures, divided by the price

index for capital.

10-181

Kt = real capital consumed in production in year tV 

Lt = quantify of labor used in year t 

Mt = material inputs in year t

t = a time trend variable to reflect technology changes

This equation can be written in linear form by taking the natural logarithms of each side of the

equation. The parameters of this model, "K, "L, "M, can then be estimated using linear regression

techniques:

ln Qt = ln A + "k ln kt + " ln Lt + "m ln Mt + 8 ln t.

Under the assumptions of a competitive market and perfect competition, the elasticity of supply

with respect to the price of the final product can be expressed in terms of the parameters of the

production function:

Supply Elasticity = ("l

 + "m) / (1– "l – "m) (10G-4)

This underlying relationship is derived from the technical production function and the

behavioral profit maximization conditions. The derivation for equation (10G-4) is provided in

Appendix 10H. 

In a competitive market, a firm will supply output as long as the marginal cost (MC) of

producing the next unit does not exceed the marginal revenue (MR, i.e., the price). In a shortrun analysis, where capital stock is assumed to be fixed (or a sunk cost of production), the firm

will adjust its variable inputs of labor and material to minimize the total cost of producing a

given level of output. 

The supply function is estimated by minimization, subject to the technical constraints of the

production function, and then setting the MC = P to determine the quantity produced as a

function of market price. To maintain the desired properties of the Cobb-Douglas production

function, it is necessary to place restrictions on the estimated coefficients. For example, if "L +

"M = 1, then the supply elasticity will be undefined. Alternatively, if "L + "M > 1, this yields a

negative supply elasticity. Thus, a common assumption is that "K + "L + "M = 1. This implies

constant returns to scale, which is consistent with most empirical studies.

10G.3.2 Data for Estimating Engine and Equipment Supply Elasticities

The data for the supply elasticity estimation were obtained from the National Bureau of

Economic Research-Center for Economic Studies (NBER-CES). All nominal values were

deflated into $1987, using the appropriate price index. The following variables were used:

C value of shipments
Final Regulatory Impact Analysis

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C price index of value shipments

C production worker wages

C implicit GDP deflators

C cost of materials

C price index for materials

C real capital stock

C investment

C price index for investment

C value added 

C price index for capital

The capital (k) variable used in the Cobb-Douglas regression analysis is calculated as:

K = (Value Added – Labor Costs) / Price Index for Capital

This provides a measure of capital consumed as opposed to using a measure of total capital stock

in place at the firm. 

10G.3.3 Engine Supply Elasticity Regression Results

The results of the estimated production function is presented in Table 10G-6. All parameter

estimates are statistically significant at the 95 percent confidence level and the supply elasticity

is calculated to be 3.81. This elastic elasticity estimate means that the quantities supplied in this

market are expected to be very responsive to price changes.

Table 10G-6. Engine Supply Elasticity

Supply Elasticity = 3.81

Number of Observations = 33

R-squared = 0.9978

Goldfeld-Quandt F = 1.88

Note: F(14,14) = 2.46. 

Variable Estimated Coefficients t-statistic

Intercept 0.954 24.76

ln K 0.2081 4.77

ln T 0.0215 2.37

ln M 0.5909 13.4

ln L 0.201 5.55

10G.3.4 Equipment Supply Elasticity Regression Results

The results of the estimated production functions are presented in Tables 10G-7 through

10G-12. The supply elasticities are calculated from the estimated coefficients for lnM and lnL as
Economic Impact Analysis

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described in Equation G10-4. The supply elasticities range from approximately 1.0 for

refrigeration to 5.4 for general industrial equipment. The average supply elasticity is 3.6. These

elastic elasticity estimates means that the quantities supplied in this market are expected to be

responsive to price changes.

Table 10G-7. Agricultural Supply Elasticity

Supply Elasticity = 2.14

Number of Observations = 33

R-squared = 0.9969

Goldfeld-Quandt F = 2.01

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 1.1289 20.81

ln K 0.3189 11.12

ln T –0.0241 –3.10

ln M 0.4952 10.29

ln L 0.1858 4.64

Table 10G-8. Construction Supply Elasticity

Supply Elasticity = 3.31

Number of Observations = 33

R-squared = 0.9926

Goldfeld-Quandt F = 1.76

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 1.172 28.54

ln K 0.2318 5.83

ln T –0.0617 –7.08

ln M 0.1511 4.54

ln L 0.6172 13.97
Final Regulatory Impact Analysis

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Table 10G-9. Industrial Supply Elasticity

Supply Elasticity = 5.37

Number of Observations = 33

R-squared = 0.9949

Goldfeld-Quandt F = 1.23

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 0.6927 18.29

ln K 0.157 3.47

ln T –0.00739 –0.76

ln M 0.0412 0.96

ln L 0.8018 21.9

Table 10G-10. Garden

Supply Elasticity = 3.37

Number of Observations = 33

R-squared = 0.9963

Goldfeld-Quandt F = 1.18

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 0.6574 13.34

ln K 0.2287 3.75

ln T 0.0413 2.78

ln M 0.0644 1.72

ln L 0.7069 11.23
Economic Impact Analysis

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Table 10G-11. Gensets

Supply Elasticity = 2.91

Number of Observations = 33

R-squared = 0.9909

Goldfeld-Quandt F = 1.16

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 1.1304 11.09

ln K 0.2557 3.6

ln T 0.0325 2.73

ln M 0.3797 4.67

ln L 0.3646 4.51

Table 10G-12. Pumps 

Supply Elasticity = 2.83

Number of Observations = 33

R-squared = 0.9979

Goldfeld-Quandt F = 1.40

Note: F(14,14) = 2.46

Variable Estimated Coefficients t-statistic

Intercept 0.9367 19.01

ln K 0.2608 4.45

ln T –0.207 –1.74

ln M 0.0891 1.57

ln L 0.6501 14.48

10G.4 Diesel Fuel Supply Elasticity: Literature Estimate

Very few studies have attempted to quantify supply responsiveness for individual refined

products, such as diesel fuel. For example, a study for the California Energy Commission stated

“There do not seem to be credible estimates of gasoline supply elasticity” (Finizza, 2002). 

However, sources agree that refineries have little or no ability to change output in response to

price: high fixed costs compel them to operate as close to their capacity limit as possible. The

Federal Trade Commission (FTC) analysis made this point explicitly (FTC, 2001). 

Greene and Tishchishyna (2000) reviewed supply elasticity estimates available in the

literature. The supply elasticity values cited in most of these studies were for “petroleum” or

“oil” production in the United States, which includes exploration, distribution and refining
Final Regulatory Impact Analysis

WUnder the assumption of perfect competition, supply elasticities can be derived by taking the

inverse of the reported cost elasticities. Therefore, Invalid and McCullough's cost elasticity of

0.6 is used to compute a supply elasticity of 1/0.6 = 1.6.

10-186

activities. The lowest short-term numbers cited were 0.02 to 0.05, with long-run values ranging

from 0.4 to 1.0. It seems likely that these extremely low numbers are influenced by the limited

domestic supply of crude petroleum and the difficulty of extraction. 

A recent paper by Considine (2002) provides one of the few supply elasticity estimates for

refining production (excluding extraction and distribution) based on historical price and quantity

data. In this study, Considine estimates a refining production supply elasticity of 0.24. This

estimate is for aggregate refinery production and includes distillate and nondistillate fuels. 

Because petroleum products are made in strict proportion and refineries have limited ability to

adjust output mix in the short to medium run, it is reasonable to assume that supply is relatively

inelastic and similar across refinery products. This value of 0.24 was used for the supply

elasticity for this market. This estimated elasticity is inelastic, which means that the quantity of

goods and services supplied is expected to be fairly insensitive to price changes.

10G.4 Locomotive and Marine Supply Elasticities: Literature Estimate

Over the past three decades, several studies have empirically estimated railroad cost

functions (see for example Braeutigam, 1999). One of the most recent studies by Ivald and

McCullough (2001) estimated a multi-product cost function for railroad services using data from

the Association of American Railroads (1978 to 1997). They report cost elasticities for which

we can derive a supply elasticity parameter for rail transportation servicesW. The supply

parameters are slightly elastic (1.6), suggesting a one percent change in the market price of the

services would induce producers increase service supply more than one percent.

Similar studies for marine transportation services are generally restricted to the study of the

liner shipping industry (see for example Klein and Kyle, 1997). However, these ocean carrier

services are not directly comparable to commercial marine services in the Great Lakes and

Inland River Ports in the United States. Instead, they are more likely to be consistent with onland transportation services provided by the railroad sector. As a result, we have assumed the

supply elasticity parameter for best characterizes the supply responses of the marine

transportation market included in NDEIM.
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APPENDIX 10H: Derivation of Supply Elasticity

This appendix derives the underlying relationship for the supply elasticity used in the

production function approach described in Appendix 10G.

Cobb-Douglas:

Q = L" k1–" where Q = output

L = labor input

k = capital input

Cost Minimization:

Marginal Revenue Product of Labor = Wage Rate

MRPL = P • MPL = w

MPL = ∂

∂

α Q

L = L k α α − − 1 1

P • MPL = P" L"-1 k1-" = w

L"-1 = 

w

P k1 α −α

L1-" = 

P k

w

1 α −α

L = P k

w

P

w k

1

1

1

1

α α 1 α α α − −  −



 



 = 



 





Substitute Back into Cobb-Douglas:

y = P

w

k k

1

1 α 1 α

α

 α



 

























− −

y = P

w k p w k 1 1 α α 1

α

α α

α

α

 α



 



 = 



 



 − − −

ln y = α

α

α

α

α

1

lnP

1

ln

w

lnk − + −





 



 +

∂

∂

α

α

lny

lnP 1 = Supply Elasticity − =
Final Regulatory Impact Analysis

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APPENDIX 10I: Sensitivity Analysis

The Economic Impact Analysis presented in this Chapter 10 is based on the Nonroad Diesel

Economic Impact Model (NDEIM) developed for this analysis. The NDEIM reflects certain

assumptions about behavioral responses (modeled by supply and demand elasticities) and how

costs are treated by producers. This appendix presents a sensitivity analysis for several model

components by varying how they are treated. Five model components are examined:

C Scenario 1: alternative market supply and demand elasticity parameters

C Scenario 2: alternative ways to treat fuel market costs

C Scenario 3: alternative way to treat operating costs

C Scenario 4: alternatives way to treat engine and equipment fixed costs

C Scenario 5: alternative discount rates

The results of these sensitivity analyses are presented below. All of the results are presented

for 2013 only. The results for the application and transportation service markets do not include

the operating savings. Instead, operating savings are added into the total social costs as a

separate item.

In general, varying the model parameters does not significantly change the results of the

economic impact assessment analysis presented above. Total social costs are about the same

across all sensitivity analysis scenarios, $1,510 million. In addition, varying these model

parameters does not significantly affect the way the social costs are borne. In all cases, the

application markets bear the majority of the burden (about 83 percent), although there are small

differences in the way the costs are borne among the scenarios. The exception is Scenario 2, the

fuel cost scenario. In the maximum total cost scenario, the share of the social costs borne by the

application market exceeds the social costs of the rule ($2,029 million versus $1,510.9 million

for the rule), indicating that refiners will gain from the rule (about $526 million). In the

maximum variable cost scenario, the share of the social costs borne by the application market

also exceeds the social costs of the rule ($1,584 million versus $1,510.9 million for the rule),

indicating that refiners would gain from the rule in this scenario as well (about $79 million). 

There are also differences in the way the application market costs are shared among producers

and consumers in that market, especially for Scenario 1. 

With regard to the market analysis, expected percentage changes for price and price and

quantity for each market are about the same as in the base case. Prices are expected to increase

about 2.14. 2.9, and 6 percent for the engine, equipment, and fuel markets respectively, while

quantities. These engine and equipment percentage price increases are stable across scenarios

except in Scenario 4, in which engine and equipment fixed costs and included in the model. In

this case, the expected engine price increase goes up from about 21.4 percent to 23.0 percent and

the expected equipment price increase goes up from about 2.9 percent to 3.4 percent. The fuel

percentage price increases are also stable across scenarios, with the exception of Scenario 2, in

which a price increase of 11 percent is expected in the maximum total cost scenario and a 7
Economic Impact Analysis

10-189

percent increase is expected in the maximum variable cost scenario.

Percentage decreases in the quantities produced in the markets are also relatively stable

across the scenarios with decreases of 0.01, 0.02, and 0.02 percent expected for the engine,

equipment, and fuel markets respectively. There is some variation in absolute quantities across

the scenarios, but these are negligible when compared to the total output of each market. The

largest change in absolute quantity of output is associated with Scenario 1, when supply

elasticities are varied. The largest decline is 107 engines, 189 equipment units, and 3.25 million

gallons of fuel; the smallest is 44 engines, 74 equipment units, and 1.29 million gallons of fuel. 

This is in comparison to 79 engines, 139 equipment units, and 2.38 million gallons of fuel in the

base case.

For the application market, the expected price increase remains stable across the scenarios at

about 0.1 percent, and the expected quantity decrease at about 0.02. Prices in the transportation

service markets are expected to increase about 0.0.01 percent and quantity to decrease about 0.01

percent. 

10I.1 Model Elasticity Parameters

Key model parameters include supply and demand elasticity estimates used by the model to

characterize behavioral responses of producers and consumers in each market. 

Consumer demand and producer supply responsiveness to changes in the commodity prices

are referred to by economists as “elasticity.” The measure is typically expressed as the

percentage change in quantity (demanded or supplied) brought about by a percent change in own

price. A detailed discussion regarding the estimation and selection of the elasticities used in the

NDEIM are discussed in Appendix 10G. This component of the sensitivity analysis examines

the impact of changes in selected elasticity values, holding other parameters constant. The goal

is to determine whether alternative elasticity values significantly alter conclusions in this report.

10I.1.1 Application Markets (Supply and Demand Elasticity Parameters)

The choice of supply and demand elasticities for the application market is important because

changes in quantities in the application markets are the key drivers in the derived demand

functions used to link impacts in the engine, equipment, and fuel markets. In addition, the

distribution of regulatory costs depends on the relative supply and demand elasticities used in

the analysis. For example, consumers will bear less of the regulatory burden if they are more

responsive to price changes than producers. 

Table 10I-1 reports the upper- and lower-bound values of the application market elasticity

parameters (supply and demand) used in the sensitivity analysis. The variation in estimates

reported in the literature were used for supply elasticity ranges. For the manufacturing market,

an assumed elasticity of 1.0 was used. For the purpose of this sensitivity analysis, the same

upper and lower bounds were used as for the construction market. For demand elasticity values,

a 90 percent confidence interval was computed using the coefficient and standard error values
Final Regulatory Impact Analysis

10-190

reported in the econometric analysis (see Appendix 10G).

Table 10I-1. Sensitivity Analysis of the Supply and Demand Elasticities

for the Application Markets

Parameter/Market

Elasticity

Source Upper Bound Base Case Lower Bound

Supply elasticity

Agriculture Literature

estimate

0.55 0.32 0.027

Construction Literature

estimate

2.3 1 0.5

Manufacturing Assumed value 2.3 1 0.5

Demand elasticity

Agriculture EPA estimate –0.35 –0.20 –0.054

Construction EPA estimate –1.39 –0.96 –0.534

Manufacturing EPA estimate –1.02 –0.58 –0.140

Note: For literature estimates, the variations in estimates reported were used to develop

elasticity ranges. In contrast, EPA computed upper- and lower-bound estimates using

the coefficient and standard error values associated with its econometric analysis and

reflect a 90 percent confidence interval.

The results of the NDEIM using these alternative elasticity values for the application markets

are reported in Tables 10I-2 and 10I-3. As can be seen in those tables, market prices are stable 

across the upper- and lower-bound sensitivity scenarios. Absolute quantities vary but the

percentage changes in output are negligible for the two scenarios.

The change in total social surplus for 2013 also remains nearly unchanged across all

scenarios and is approximately the same as for the rule ($1,510 million). However, consumers in

the application market bear a smaller share of the social costs when they are more responsive to

price changes relative to producers (supply lower bound and demand upper bound scenarios). 

As shown, consumers bear approximately 34.5 and 46.5 percent, respectively, in these scenarios

compared to 58.5 percent in the base case. In contrast, they bear a higher share (up to 78.5

percent) when they are less responsive to price changes relative to producers (supply upper

bound and demand lower bound scenarios). While the burden of the fuel market changes

slightly, it always remain below 1 percent of the social costs.
Economic Impact Analysis

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Table 10I-2. Application Market Sensitivity Analysis for Supply Elasticitiesa,b

Base Case Supply Upper Bound Supply Lower Bound

Scenario Absolute Relative Absolute Relative Absolute Relative

Application Markets

Price ($/q) NA 0.10% NA 0.11% NA 0.05%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.01%

Change in Consumer Surplus

($106

/yr)

$876 NA $1,113 NA $520 NA

Change in Producer Surplus

($106

/yr)

$621 NA $377 NA $985 NA

Change in Total Surplus

($106

/yr)

$1,497 NA $1,490 NA $1,505 NA

Equipment Markets

Price ($/q) $975 2.9% $973 2.9% $977 2.9%

Quantity (gal/yr) –139 –0.02% –189 –0.02% –74 –0.01%

Change in Producer Surplus

($106

/yr)

$143 NA $145 NA $141 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4% $821 21.4%

Quantity (gal/yr) –79 –0.01% –107 –0.02% –44 –0.01%

Change in Producer Surplus

($106

/yr)

$42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –3.25 –0.03% –1.29 –0.01%

Change in Producer Surplus

($106

/yr)

$8 NA $12 NA $3 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA –0.01%

Change in Producer Surplus

($106

/yr)

$2 NA $3 NA $2 NA

Applications Not Included in

NDEIM ($106

/yr)

$102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,509.9 NA $1,510.1 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
10-192

Table 10I-3. Application Market Sensitivity Analysis for Demand Elasticitiesa,b

Base Case Demand Upper Bound Demand Lower Bound

Scenario Absolute Relative Absolute Relative Absolute Relative

Application Markets

Price ($/q) NA 0.10% NA 0.08% NA 0.12%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.01%

Change in Consumer Surplus

($106

/yr)

$876 NA $695 NA $1,181 NA

Change in Producer Surplus

($106

/yr)

$621 NA $798 NA $323 NA

Change in Total Surplus

($106

/yr)

$1,497 NA $1,493 NA $1,503 NA

Equipment Markets

Price ($/q) $975 2.9% $974 2.9% $977 2.9%

Quantity (gal/yr) –139 –0.02% –170 –0.02% –88 –0.01%

Change in Producer Surplus

($106

/yr)

$143 NA $144 NA $142 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4% $821 21.4%

Quantity (gal/yr) –79 –0.01% –96 –0.02% –50 –0.01%

Change in Producer Surplus

($106

/yr)

$42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –2.89 –0.02% –1.54 –0.01%

Change in Producer Surplus

($106

/yr)

$8 NA $10 NA $4 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA 0.00%

Change in Producer Surplus

($106

/yr)

$2 NA $3 NA $1 NA

Applications Not Included in

NDEIM ($106

/yr)

$102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,509.9 NA $1,510.0 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
Economic Impact Analysis

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10I.1.2 Equipment, Engine and Diesel Fuel Markets (Supply Elasticity Parameters)

Sensitivity analysis was also conducted for the engine, equipment, and diesel fuel market

supply elasticities. The range of supply elasticity values evaluated for each market are provided

in Table 10I-4. The engine and equipment market supply elasticities are derived

econometrically. Therefore, the upper and lower bound values were computed using the

coefficient and standard error values associated with the econometric analysis and reflect a 90

percent confidence interval (see Appendix 10G). 

The fuel market supply elasticity was obtained from the literature. The value for the lower

bound for the sensitivity analysis is based on the range of available estimates. The value for the

upper bound was derived from a set of regulatory studies of the petroleum refining industry that

were conducted using a techno-economic method to estimate supply costs at the individual

refinery level (EPA, 2000; CRA/BOB, 2000; MathPro, 2002). Synthetic industry supply curves

(i.e., marginal cost curves) were developed from these studies and yielded supply elasticities

ranging from 0.2 to 2.0. Therefore, the sensitivity analysis uses 2.0 as an upper bound for the

supply elasticity of nonroad diesel fuel.

Three sets of sensitivity results are presented in Tables 10I-5, 10I-6, and 10I-7, where supply

elasticities are changed in the equipment, engines, and fuel markets, respectively.

Table 10I-4

Engine, Equipment, and Diesel Fuel Market Sensitivity Analysis for Supply Elasticity

Parameters

Market

Elasticity Source Upper

Bound

Base Case Lower

Bound

Supply

Engines EPA Estimate 7.64 3.81 2.33

Equipment

Agriculture EPA Estimate 3.72 2.14 1.31

Construction EPA Estimate 6.06 3.31 2.09

Refrigeration EPA Estimate 5.62 2.83 1.62

Industrial EPA Estimate 12.93 5.37 2.9

Garden EPA Estimate 7.96 3.37 1.82

Generator EPA Estimate 12.14 2.91 1.12

Pumps EPA Estimate 5.62 2.83 1.62

Diesel fuel Literature Estimate 2 0.2 0.04

Note: For literature estimates, the variations in estimates reported were used to develop

elasticity ranges. In contrast, EPA computed upper- and lower-bound estimates using the

coefficient and standard error values associated with its econometric analysis and reflect

a 90 percent confidence interval.
Final Regulatory Impact Analysis

XFor a discussion of the concept of derived demand, see Section 10.2.2.3 Incorporating

Multimarket Interactions.

10-194

Tables 10I-5 and 10I-6 contain the results of varying the engine and equipment supply

elasticities. When these elasticities are allowed to vary, all quantitative estimates for both

market impacts (price and quantity changes) and social impacts (how the burden is shared across

markets) remain nearly unchanged when compared with the rule, across both the upper and

lower bound supply elasticity scenarios for equipment and engines. These results imply that the

results presented in Section 10.1 are not sensitive to the supply elasticity values used in the

engine and equipment markets, because the derived demand for engines and equipment is highly

inelastic (it is a function of the inelastic demand and supply in the application markets), and so

almost all of the compliance costs are passed on to the application markets through price

increases. 

Table 10I-7 contains the results of varying the fuel supply elasticity. The results for the

upper bound is nearly identical to the base case. However, in the case of the lower bound

(producers are less sensitive to price changes), the expected percentage change in the price of

fuel decreases from 6 percent in the base case to 5.6 percent. There is a reallocation of surplus

loss from the application markets to the fuel markets. In the base case, the application markets

are expected to bear about 83 percent of the social costs ($1,497 million), while the fuel market

is expected to bear about 0.5 percent ($8 million). When the lower bound of the supply elasticity

for the fuel market is used, the share of the application markets decreases to 80 percent ($1,436

million) while the share of the fuel markets increases to about 4 percent ($70 million). The total

welfare losses are stable, however, at $1,510.

The demand elasticities for the equipment and engine diesel fuel markets are derived as part

of the model, and therefore sensitivity analysis was not conducted on those parameters.X In other

words, the change in the application market quantities determines the demand responsiveness in

the engine, equipment, and diesel fuel markets. As a result, the demand sensitivity analysis for

these markets is indirectly shown in Table 10I-2. Nonroad diesel equipment and fuel

expenditures are relatively small shares of total production costs for the application markets. 

Therefore changes in these input prices do not significantly alter input demand (i.e., demand in

these markets is highly inelastic).
Economic Impact Analysis

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Table 10I-5. Equipment Market Supply Elasticity Sensitivity Analysisa,b

Base Case Supply Upper Bound Supply Lower Bound

Scenario Absolute Relative Absolute Relative Absolute Relative

Application Markets

Price ($/q) NA 0.10% NA 0.10% NA 0.10%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.02%

Change in Consumer Surplus

($106

/yr)

$876 NA $877 NA $874 NA

Change in Producer Surplus

($106

/yr)

$621 NA $622 NA $620 NA

Change in Total Surplus

($106

/yr)

$1,497 NA $1,499 NA $1,494 NA

Equipment Markets

Price ($/q) $975 2.9% $977 2.9% $972 2.9%

Quantity (q/yr) –139 –0.02% –139 –0.02% –139 –0.02%

Change in Producer Surplus

($106

/yr)

$143 NA $141 NA $146 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4% $821 21.4%

Quantity (q/yr) –79 –0.01% –76 –0.01% –79 –0.01%

Change in Producer Surplus

($106

/yr)

$42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –2.39 –0.02% –2.38 –0.02%

Change in Producer Surplus

($106

/yr)

$8 NA $8 NA $8 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA –0.01%

Change in Producer Surplus

($106

/yr)

$2 NA $2 NA $2 NA

Applications Not Included in

NDEIM ($106

/yr)

$102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,510.0 NA $1,510.0 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
Final Regulatory Impact Analysis

10-196

Table 10I-6. Engine Market Supply Elasticity Sensitivity Analysisa,b

Base Case Supply Upper Bound Supply Lower Bound

Scenario Absolute Relative Absolute Relative Absolute Relative

Application Markets

Price ($/q) NA 0.10% NA 0.10% NA 0.10%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.02%

Change in Consumer Surplus

($106

/yr)

$876 NA $876 NA $876 NA

Change in Producer Surplus

($106

/yr)

$621 NA $621 NA $621 NA

Change in Total Surplus

($106

/yr)

$1,497 NA $1,497 NA $1,497 NA

Equipment Markets

Price ($/q) $975 2.9% $975 2.9% $975 2.9%

Quantity (q/yr) –139 –0.02% –139 –0.02% –139 –0.02%

Change in Producer Surplus

($106

/yr)

$143 NA $143 NA $143 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4% $821 21.4%

Quantity (q/yr) –79 –0.01% –79 –0.01% –77 –0.01%

Change in Producer Surplus

($106

/yr)

$42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –2.38 –0.02% –2.38 –0.02%

Change in Producer Surplus

($106

/yr)

$8 NA $8 NA $8 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA –0.01%

Change in Producer Surplus

($106

/yr)

$2 NA $2 NA $2 NA

Applications Not Included in

NDEIM ($106

/yr)

$102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,510.0 NA $1,510.0 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
Economic Impact Analysis

10-197

Table 10I-7. Fuel Market Supply Elasticity Sensitivity Analysisa,b

Base Case Supply Upper Bound Supply Lower Bound

Scenario Absolute Relative Absolute Relative Absolute Relative

Application Markets

Price ($/q) NA 0.10% NA 0.10% NA 0.09%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.01%

Change in Consumer Surplus

($106

/yr)

$876 NA $878 NA $839 NA

Change in Producer Surplus

($106

/yr)

$621 NA $623 NA $597 NA

Change in Total Surplus

($106

/yr)

$1,497 NA $1,501 NA $1,436 NA

Equipment Markets

Price ($/q) $975 2.9% $975 2.9% $975 2.9%

Quantity (q/yr) –139 –0.02% –140 –0.02% –134 –0.02%

Change in Producer Surplus

($106

/yr)

$143 NA $143 NA $143 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4% $821 21.4%

Quantity (q/yr) –79 –0.01% –78 –0.01% –75 –0.01%

Change in Producer Surplus

($106

/yr)

$42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0% $0.05 5.6%

Quantity (q/yr) –2.38 –0.02% –2.39 –0.02% –2.31 –0.02%

Change in Producer Surplus

($106

/yr)

$8 NA –$2 NA $70 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA –0.01%

Change in Producer Surplus

($106

/yr)

$2 NA $2 NA $3 NA

Applications Not Included in

NDEIM ($106

/yr)

$102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,510.6 NA $1,510.6 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
Final Regulatory Impact Analysis

10-198

High Cost Supplier Aggregate Remaining

Suppliers

Fuel Market

Qmax

P P P

Qagg

Cagg

Cmax

Figure 10I-1

High Cost Producer Drives Price Increases

10.I.2 Fuel Market Supply Shift Alternatives

Section 10.2 discusses alternative approaches to shifting the supply curve in the market

model. Three alternatives for the fuel market supply shift are investigated in this sensitivity

analysis:

C Total average (variable + fixed) cost shift—the results presented in Section 10.1 and the

appendices are generated using this cost shift. 

C Total maximum (variable + fixed) cost shift

C Variable maximum cost shift

To model the total and variable maximum cost scenarios, the high-cost producer is

represented by a separate supply curve as shown in Figure 10I-1. The remainder of the market is

represented as a single aggregate supplier. The high-cost producer’s supply curve is then shifted

by Cmax (either total or variable), and the aggregate supply curve is shifted by Cagg. Using this

structure, the high-cost producer will determine price as long as 

C the decrease in market quantity does not shut down the high-cost producer, and 

C the supply from aggregate producers is highly inelastic (i.e., remaining producers are

operating close to capacity); thus, the aggregate producers cannot expand output in

response to the price increase.

Note that the aggregate supply curve is no longer shifted by the average compliance costs but

slightly less than the average because the high-cost producer has been removed. The adjusted

average aggregate cost shift (Cagg) is calculated from the following: 

Cave*Qtot = Cmax * Qmax + Cagg * Qagg (10I.2)

where Cave is the average control cost for the total population; Qmax, Cmax, and Qagg, Cagg are the
Economic Impact Analysis

10-199

baseline output and cost shift for the maximum cost producer; and the baseline output and cost

shift for the remaining aggregate producers, respectively.

The results of this sensitivity analysis are reported in Table 10I-8.

Table 10I-8

Sensitivity Analysis to Cost Shifts in the Diesel Fuel Market

Average Total Scenario Maximum Total Scenario Maximum Variable Scenario

Scenario

Absolute

Change

Relative

Change (%)

Absolute

Change

Relative

Change (%)

Absolute

Change

Relative

Change (%)

Application Markets

Price ($/q) NA 0.10% NA 0.14% NA 0.10%

Quantity (q/yr) NA –0.02% NA –0.02% NA –0.02%

Change in Consumer Surplus ($106

/yr) $876 NA $1,176 NA $919 NA

Change in Producer Surplus ($106

/yr) $621 NA 852 NA 665 NA

Change in Total Surplus ($106

/yr) $1,497 NA $2,029 NA $1,584 NA

Equipment Markets

Price ($/q) $975 2.9% $973 2.9% $975 2.9%

Quantity (q/yr) –139 –0.02% –177 –0.02% –138 –0.02%

Change in Producer Surplus ($106

/yr) $143 NA $145 NA $143 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.0% $821 21.0%

Quantity (q/yr) –79 –0.01% –100 –0.02% –78 –0.01%

Change in Producer Surplus ($106

/yr) $42 NA $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.10 11.0% $0.06 7.0%

Quantity (q/yr) –2.38 –0.02% –3.02 –0.02% –2.36 –0.02%

Change in Producer Surplus ($106

/yr) $8 NA –$526 NA –$79 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01% NA –0.01%

Change in Producer Surplus ($106

/yr) $2 NA $4 NA $3 NA

Applications Not Included in NDEIM $102.4 NA $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,510.9 NA $1,510.9 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 

The total and variable maximum cost shift scenarios lead to different conclusions for two

important variables: the estimated market price increase for diesel fuel and the estimated welfare

impact for affected refineries. Under the base case (total average cost scenario), refiners pass

most of the average compliance costs on to the application markets, and the net decrease in
Final Regulatory Impact Analysis

YAlso, see Table 7.6-1 and related text in Chapter 7 regarding the possible diesel fuel price

increases for the maximum operating cost scenario

10-200

producer surplus for refiners is relatively small ( about $7.8 million, or 0.6 percent of total social

costs), and prices are expected to increase about 6.0 percent. Note that these are industry

averages, and individual refiners will gain or lose because compliance costs vary across

individual refineries.

In the total maximum cost scenario, the highest operating cost refinery determines the new

market price through the impacts on both fixed and variable costs. This refinery has the highest

per-unit supply shift, which leads to a higher price increase relative to the average cost scenario. 

As a result, all refiners except the highest cost refiner are expected to benefit from the rule, by

about $526 million, because the change in market price exceeds the additional per-unit

compliance costs for most of the refineries (i.e., most refiners have costs less than the costs for

the highest operating cost refinery). Consequently, in this scenario the producers and consumers

in the application market are expected to bear a larger share of the total cost of the program: 

$2,029 million compared to $1,497 million, out of total social costs of about $1,510 million for

the welfare costs of the rule without considering the operating savings.

The variable maximum cost scenario is similar to the total maximum cost scenario because

the highest cost refinery determines the with-regulation market price. However, the variable

maximum cost scenario leads to an expected price increase that is smaller than the total

maximum cost scenario because the refiner supply shift includes only variable compliance costs. 

In other words, the refiners do not pass along any fixed costs; they absorb the fixed costs.

However, the refinery industry still experiences a small net surplus gain ($79 million) because

the change in market price (driven by the maximum variable cost) exceeds the additional

per-unit compliance costs for many of the refineries (i.e., many refiners still have total costs less

than the costs for the highest operating cost refinery in this scenario).Y The net surplus gain for

refiners is smaller than the total maximum scenario ($79 million compared to $596 million)

because refiners absorb fixed costs, and the projected market price increase is smaller. Again,

consumers and producers in the application markets are expected to bear a larger share of the

total cost of the program, about $1,584 million.

The results of this sensitivity analysis suggest that the expected impacts on producers and

consumers in the application markets and on refiners is affected by how refinery costs are

modeled. The NDEIM models these costs based on the average (variable + fixed) cost scenario,

reflecting a competitive market situation in all regional markets. However, if the highest cost

refinery drives the new market price, then prices are expected to increase more, with a larger

contraction in output. In this case, consumers and producers in the application market are

expected to bear more than the cost of the rule. When the highest cost refinery’s variable costs

drive the new market price, then prices will increase slightly more that the base case (from 6

percent to 7 percent), producers and consumer will again bear more of the burden of the rule, and

refiners bear less than in the base case.
Economic Impact Analysis

Z

 See Section 10.3.5.3 for a description of how the operating savings are estimated.

AAWe only consider cost savings for market included in NDEIM (the three application markets

and the transportation service markets). This amounts to $265 million, or 93 percent of the

operating savings. The remaining $19 million is added as a line item to the social costs for

application markets not included in NDEIM.

10-201

10I.3 Operating Cost Scenario

In the base case analysis presented in Chapter 10, operating savings are not included in the

market analysis. As explained in Section 10.3.5.3, this approach is used because these operating

savings are not expected to affect consumer decisions with respect to new engines and

equipment. However, these operating savings accrue to society and so they are added to social

costs after changes in price and quantity are estimated. In the analysis for 2013, $284.7 million

in operating savings are applied to the application markets; these savings are expected to accrue

to producers in these markets. Specifically, $265.5 million are applied to the social costs for the

three application markets and for the transportation services providers ($243.2 million and $22.3

million, respectively) and $19.2 million are applied to the social costs for those markets not

included in NDEIM.Z

 The results of this base case analysis are set out in Table 10.1-4. In the

summary presented in Table 10I-9, all of the operating savings are presented as a separate item.

In this sensitivity analysis, we modify the analysis to include operating savings in the market

analysis. This scenario considers the possibility that some portion of the operating savings

realized by users of nonroad engines, equipment, and fuel can be transmitted to consumers

through the market relationships specified in the model, thereby affecting prices and output. The

operating savings are modeled as a cost reduction (benefit) for producers in the application

markets and service providers in the locomotive and marine sectors.AA Specifically, they are

treated as negative supply shift for the supply curves in these markets. Treating operating

savings like this reduces the size of the supply shift and illustrates how operating savings may be

shared among producers and consumers in these markets. 

The results of this sensitivity analysis are included in Table I-9. In this scenario, the price

increase and quantity decrease in the application markets are expected to be smaller (0.08

percent compared to 0.10 percent for price, and -0.01 percent compared to -0.02 percent for

quantity). This is a direct result of the smaller supply shift. Although the estimated total social

costs associated with the rule are comparable for both scenarios, $1,510.1 million compared to

$1.510.0 million in the base case, there are two important distributional consequences associated

with including operating savings in the market analysis. First, almost all of the locomotive and

marine savings ($22 million) are now directly passed to the application markets in the form of

lower prices. As a result, the application markets benefit from operating savings in

transportation services and they bear 80.6 percent of the total social costs instead of 83.4 percent

(the change in total application market surplus decreases from $1,254 to $1,234 million). 

Second, a portion of the operating savings is now distributed to consumers in application

markets. In 2013, the change in consumer surplus in the application markets decreases from

$876 million to $709 million. The change in producer surplus is smaller, and decreases from
Final Regulatory Impact Analysis

10-202

$621 to $525 million.

Table 10I-9

Operating Savings Included in the Market Analysisa,b

Scenario

Base Case (2013) Adding Operating Savings To App

Absolute 

Change

Relative Change

(%)

Absolute 

Change

Relative Change

(%)

Application Markets

Price ($/q) NA 0.10% NA 0.08%

Quantity (q/yr) NA –0.02% NA –0.01%

Change in Consumer Surplus $876 NA $709 NA

Change in Producer Surplus $621 NA $525 NA

Change in Total Surplus ($106

/yr) $1,497 NA $1,234 NA

Equipment Markets

Price ($/q) $975 2.9% $976 2.9%

Quantity (q/yr) –139 –0.02% –93 –0.01%

Change in Producer Surplus $143 NA $142 NA

Engine Markets

Price ($/q) $821 21.4% $821 21.4%

Quantity (q/yr) –79 –0.01% –53 –0.01%

Change in Producer Surplus $42 NA $42 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –1.57 –0.01%

Change in Producer Surplus $8 NA $6 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01%

Change in Producer Surplus $2 NA $2 NA

Applications Not Included in $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$19.2 NA

Total Social Cost $1,510.0 NA $1,510.1 NA

a Sensitivity analysis is presented for 2013.

b Figures are in 2002 dollars. 
Economic Impact Analysis

10-203

10I.4 Engine and Equipment Fixed Cost Shift Scenario

As discussed in Section 10.3 only the variable costs are used to shift the supply curve in the

engines and equipment markets. Fixed costs are assumed to be R&D costs that are absorbed by

engine and equipment markets over a 5-year period and hence do not affect market prices or

quantities. As a result, producers are not able to pass any of these costs on and bear all fixed

costs as a decrease in producer surplus.

In this scenario, the supply shift for engine producers includes the fixed and variable

compliance costs. The results are presented in Table 10I-10. In this scenario, engine producers

are able to pass along the majority of the fixed compliance costs to the downstream markets

rather than absorb them as a one-to-one reduction in profits. As expected, this scenario leads to a

higher projected price increases for the engine and equipment markets (from 2.9 percent in the

baseline case to 3.4 percent for equipment markets and from 21.4 percent in the baseline case to

23.0 percent for engine markets), and the share of the social costs borne by these markets

decreases from 9.5 percent to 0.2 percent for the equipment markets, and from 2.8 percent to 0

percent for the engine markets. These costs are passed on to the application markets, and their

expected share of the compliance burden increases from 83 percent to 93 percent. However, the

total social costs of the regulation are not expected to change measurably as the higher prices

lead to almost no change in the demand for equipment and engines. 
Final Regulatory Impact Analysis

10-204

Table 10I-10 Fixed Costs Added to Supply Shift in Engine and Equipment Marketsa,b

Scenario

Base Case (2013)

Shocking Engine and Equipment

Markets by Total Costs

Absolute 

Change

Relative Change

(%)

Absolute 

Change

Relative Change

(%)

Application Markets

Price ($/q) NA 0.10% NA 0.11%

Quantity (q/yr) NA –0.02% NA –0.02%

Change in Consumer Surplus $876 NA $978 NA

Change in Producer Surplus $621 NA $697 NA

Change in Total Surplus $1,497 NA $1,675 NA

Equipment Markets

Price ($/q) $975 2.9% $1,192 3.4%

Quantity (q/yr) –139 –0.02% –156 –0.02%

Change in Producer Surplus $143 NA $5 NA

Engine Markets

Price ($/q) $821 21.4% $898 23.0%

Quantity (q/yr) –79 –0.01% –87 –0.02%

Change in Producer Surplus $42 NA $0 NA

Fuel Markets

Price ($/q) $0.06 6.0% $0.06 6.0%

Quantity (q/yr) –2.38 –0.02% –2.67 –0.02%

Change in Producer Surplus $8 NA $9 NA

Transportation Services

Price ($/q) NA 0.01% NA 0.01%

Quantity (q/yr) NA –0.01% NA –0.01%

Change in Producer Surplus $2 NA $3 NA

Applications Not Included in $102.4 NA $102.4 NA

Operating Savings ($106

/yr) –$284.7 NA –$284.7 NA

Social Costs ($106

/yr) $1,510.0 NA $1,509.9 NA

a Sensitivity analysis is presented for 2013. b Figures are in 2002 dollars. 

10I.5 Alternative Social Discount Rates

Future benefits and costs are commonly discounted to account for the time value of money. 
Economic Impact Analysis

10-205

The market and economic impact estimates presented in Section 10.1 calculate the present value

of economic impacts using a social discount rate of 3 percent, yielding a total social cost of

$27.2 billion. The 3 percent discount rate reflects the commonly used substitution rate of

consumption over time. An alternative is the OMB-recommended discount rate of 7 percent that

reflects the commonly used real private rate of investment. Table 10I-11 shows the present

value calculated over 2004 to 2030 using both the 3 and 7 percent social discount rates. With the

7 percent social discount rate, the present value of total social costs decreases to $13.9 billion.

Table 10I-11. Net Present Valuesa

NPV (3%) NPV (7%)

Market 

Surplus 

(106

)

Operating Cost

Savings

(106

) Total

Market

Surplus

(106

)

Operating

Cost Savings 

(106

) Total

Engine Producers Total $256 $256 $180 $180

Equipment Producers Total $1,162 $1,162 $740 $740

Construction Equipment $545 $545 $343 $343

Agricultural Equipment $397 $397 $255 $255

Industrial Equipment $220 $220 $141 $141

Application Producers &

Consumers Total

$28,429 –$3,757 $24,672 $14,663 –$2,309 $12,354

Total Producer $11,838 $6,096

Total Consumer $16,591 $8,567

Construction $11,526 –$1,779 $9,746 $5,922 –$1,093 $4,829

Agriculture $8,181 –$1,208 $6,973 $4,222 –$742 $3,480

Manufacturing $8,723 –$770 $7,953 $4,519 –$473 $4,046

Fuel Producers Total $169 $169 $86 $86

PADD 1 & 3 $85 $85 $43 $43

PADD 2 $69 $69 $35 $35

PADD 4 $3 $3 $1 $1

PADD 5 $12 $12 $6 $6

Transportation Services Total $1,653 $973 $900 $508

Locomotive $31 –$160 –$129 $16 –$97 –$82

Marine $18 –$204 –$187 $9 –$113 –$104

Application Markets Not

Included in NDEIM

$1,604 –$315 $1,288 $875 –$182 $693

Total $31,669 –$4,437 $27,232 $16,569 –$2,701 $13,868

a Figures are in 2001 dollars. b Figures are in 2002 dollars. 
CHAPTER 11: Small-Business Flexibility Analysis

11.1 Overview of the Regulatory Flexibility Act . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-1

11.2 Need for the Rulemaking and Rulemaking Objectives . . . . . . . . . . . . . . . . . . . . . . . 11-2

11.3 Issues Raised by Public Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-2

11.3.1 Comments Regarding Small Business Engine and Equipment Manufacturers 11-3

11.3.2 Comments Regarding Small Fuel Refiners, Distributors, and Marketers . . . . 11-3

11.3.2.1 General Comments on Small Refiner Flexibility . . . . . . . . . . . . . . . . . . . 11-3

11.3.2.2 Comments on the Small Refiner Definition . . . . . . . . . . . . . . . . . . . . . . . 11-4

11.3.2.3 Comments on the Baseline Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-4

11.3.2.4 Comments on Small Refiner ‘Option 4’ . . . . . . . . . . . . . . . . . . . . . . . . . 11-4

11.3.2.5 Comments on Emission Impacts of the Small Refiner Provisions . . . . . 11-5

11.3.2.6 Comments on Inclusion of a Crude Capacity Limit for Small Refiners . 11-5

11.3.2.7 Comments on Leadtime Afforded for Mergers and Acquisitions . . . . . . 11-6

11.3.2.8 Necessity of Small Refiner Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-6

11.3.2.9 Comments on Fuel Marker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-6

11.4 Description of Affected Entities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-6

11.4.1 Description of Nonroad Diesel Engine and Equipment Manufacturers . . . . . . 11-7

11.4.1.1 Nonroad Diesel Engine Manufacturers . . . . . . . . . . . . . . . . . . . . . . . . . . 11-8

11.4.1.2 Nonroad Diesel Equipment Manufacturers . . . . . . . . . . . . . . . . . . . . . . . 11-8

11.4.2 Description of the Nonroad Diesel Fuel Industry . . . . . . . . . . . . . . . . . . . . . . . 11-9

11.4.2.1 Nonroad Diesel Fuel Refiners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-9

11.4.2.2 Nonroad Diesel Fuel Distributors and Marketers . . . . . . . . . . . . . . . . . 11-10

11.5 Projected Reporting, Recordkeeping, and Other Compliance Requirements of the

Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-10

11.6 Steps to Minimize Significant Economic Impact on Small Entities . . . . . . . . . . . . 11-11

11.6.1 Transition and Hardship Provisions for Small Engine Manufacturers . . . . . . 11-12

11.6.1.1 Panel Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-12

11.6.1.2 What We Proposed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-13

11.6.1.3 Provisions Being Finalized in This Rule . . . . . . . . . . . . . . . . . . . . . . . . 11-14

11.6.2 Transition and Hardship Provisions for Nonroad Diesel Equipment Manufacturers

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-16

11.6.2.1 Panel Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-16

11.6.2.2 What We Proposed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-17

11.6.2.3 Provisions in the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-19

11.6.3 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Refiners 11-20

11.6.3.1 Panel Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-20

11.6.3.2 What We Proposed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-22

11.6.3.3 Provisions in the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-23

11.6.4 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Distributors

and Marketers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-26

11.6.4.1 Panel Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-26

11.6.4.2 What We Proposed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-26

11.6.4.3 Provisions in the Final Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-26

11.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-27
Small-Business Flexibility Analysis

11-1

CHAPTER 11: Small-Business Flexibility Analysis

This chapter discusses our Final Regulatory Flexibility Analysis, which evaluates the

potential impacts of new standards on small entities. Pursuant to the requirements of the

Regulatory Flexibility Act, as amended by the Small Business Regulatory Enforcement Fairness

Act of 1996 (SBREFA), which generally requires an agency to prepare a regulatory flexibility

analysis of any rule subject to notice-and-comment rulemaking requirements under the

Administrative Procedure Act or any other statute unless the agency certifies that the rule will

not have a significant economic impact on a substantial number of small entities. Prior to

issuing a proposal for this rulemaking, we analyzed the potential impacts of these regulations on

small entities. As a part of this analysis, we convened a Small Business Advocacy Review Panel

(SBAR Panel, or ‘the Panel’). During the Panel process, we gathered information and

recommendations from Small Entity Representatives (SERs) on how to reduce the impact of the

rule on small entities, and those comments are detailed in the Final Panel Report which is located

in the public record for this rulemaking (Docket A-2001-28, Document No. II-A-172).

11.1 Overview of the Regulatory Flexibility Act

In accordance with section 609(b) of the Regulatory Flexibility Act, we convened an SBAR

Panel before conducting the Regulatory Flexibility Analysis. A summary of the Panel’s

recommendations can be found in our proposal. Further, the Final Panel Report contains a

detailed discussion of the Panel’s advice and recommendations (as well as the SER

recommendations). The regulatory alternatives that are being adopted in this final rule are

described below.

Section 609(b) of the Regulatory Flexibility Act further directs the Panel to report on the

comments of small entity representatives and make findings on issues related to identified

elements of the Regulatory Flexibility Analysis under section 603 of the Regulatory Flexibility

Act. Key elements of a Regulatory Flexibility Analysis are:

- a description and, where feasible, an estimate of the number of small entities to which the

proposed rule applies;

- projected reporting, record keeping, and other compliance requirements of the proposed rule,

including an estimate of the classes of small entities that would be subject to the rule and the

type of professional skills necessary to prepare reports or other records;

- an identification, to the extent practicable, of all other relevant federal rules that may

duplicate, overlap, or conflict with the proposed rule;

- any significant alternatives to the proposed rule that accomplish the stated objectives of

applicable statutes and that minimize any significant economic impact of the proposed rule

on small entities.

The Regulatory Flexibility Act was amended by SBREFA to ensure that concerns regarding

small entities are adequately considered during the development of new regulations that affect
Final Regulatory Support Document

11-2

those entities. Although we are not required by the Clean Air Act to provide special treatment to

small businesses, the Regulatory Flexibility Act requires us to carefully consider the economic

impacts that our rules will have on small entities. The recommendations made by the Panel may

serve to help lessen these economic impacts on small entities when consistent with Clean Air

Act requirements.

11.2 Need for the Rulemaking and Rulemaking Objectives

A detailed discussion on the need for and objectives of this rule are in the preamble to the

final rule. Controlling emissions from nonroad engines and equipment, in conjunction with

diesel fuel controls, has important public health and welfare benefits. With the advent of more

stringent controls on highway vehicles and their fuels, emissions from nonroad sources, unless

controlled, will contribute significantly more harmful pollution than those from highway

sources.

Section 213(a)(3) of the Clean Air Act requires EPA to regulate NOx emissions from

nonroad engines and vehicles upon an EPA determination that nonroad engines contribute to

emissions in a nonattainment area. In part, section 213(a)(3) authorizes EPA to promulgate

standards for designated pollutants (including NOx) that require the greatest degree of emission

reduction achievable from application of technology to nonroad engines (or vehicles) while

giving “appropriate consideration to the cost of applying such technology within the period of

time available to manufacturers and to noise, energy, and safety factors associated with the

application of such technology.” Section 213(a)(4) applies to all pollutants not specifically

identified in section 213(a)(3), and authorizes EPA to promulgate “appropriate” standards for

such pollutants, taking into account “costs, noise, safety, and energy factors associated with the

application of technology which the Administrator determines will be available” for those

engines (or vehicles). Controls on PM implement this provision.

Similarly, section 211(c)(1) authorizes EPA to regulate fuels if any emission product of the

fuel causes or contributes to air pollution that may endanger public health or welfare, or that may

impair the performance of emission-control technology on engines and vehicles. We believe

there is an opportunity for cost-effective emission reductions on a large scale.

11.3 Issues Raised by Public Comments

During the public comment period we received numerous comments regarding various

aspects of the NPRM, including our proposed small business provisions. The following section

provides a summary of the comments that we received on our proposed provisions. More

information on these comments can be found in the Final Summary and Analysis of Comments,

which is a part of the rulemaking record.
Small-Business Flexibility Analysis

11-3

11.3.1 Comments Regarding Small Business Engine and Equipment Manufacturers

One small business engine manufacturer commented that the proposed provisions for small

manufacturers are appropriate and strongly supported their inclusion in the final rule. The

manufacturer raised many concerns of why it believes that it is necessary to include such

provisions, such as: larger/higher-volume manufacturers will have priority in supply of new

technologies and will thus have more R&D time to complete development of these systems

before they are available to smaller manufacturers; and, smaller manufacturers do not command

the same amount of attention from potential suppliers of critical technologies for T4 controls,

and are thus concerned that they may not be able to attract a manufacturer to work with them on

the development of compliant technologies. The small manufacturer believes that the additional

three-year time period proposed for small business engine manufacturers in the NPRM is

necessary for its company, and is the company’s estimate of the time that it will take for these

technologies to be available to small engine manufacturers.

The Small Business Administration’s Office of Advocacy (“Advocacy”) raised the concern

that the rule would impose significant burdens on a substantial number of small entities with

little corresponding environmental benefit. Advocacy commented that we should exclude

smaller engines (those under 75 hp) from further regulation in order to comply with the

Regulatory Flexibility Act and fulfill the requirement of reducing the burden on small engine

classes. Advocacy recommended that PM standards for engines in the 25-75 hp powerband

should not be based on performance of aftertreatment technologies. Advocacy believes that the

proposed flexibilities will not suffice on their own to appropriately minimize the regulatory

burdens on small entities; and Advocacy noted that during the SBREFA process, some small

equipment manufacturers stated that although EPA would allow some equipment to be sold

which would not require new emissions controls, engine manufacturers would not produce or

sell such equipment. Advocacy also commented that we have not shown that substantial

numbers of small businesses have taken advantage of previous small business flexibilities, or

that small businesses would be able to take advantage of the flexibilities under this rule. Lastly,

Advocacy commented that although full compliance with the more stringent emissions controls

requirements would be delayed for small manufacturers, small business manufacturers

eventually will be required to produce equipment meeting the new requirements.

11.3.2 Comments Regarding Small Fuel Refiners, Distributors, and Marketers

11.3.2.1 General Comments on Small Refiner Flexibility

One small refiner commented that it is not plausible at this time to evaluate the impact of the

three fuels regulations on the refining industry (and small refiners), however it stated that we

should continue to evaluate the impacts and act quickly to avoid shortages and price spikes and

we should be prepared, if necessary, to act quickly in considering changes in the regulations to

avoid these problems. We also received comment that some small refiners that produce

locomotive and marine fuels fear that future sulfur reductions to these markets could be very

damaging.
Final Regulatory Support Document

11-4

11.3.2.2 Comments on the Small Refiner Definition

A small refiner commented that the proposed redefinition of a small refiner (to not

grandfather as small refiners those that were small for highway diesel) would both negate the

benefits afforded under the small refiner provisions in the Highway Diesel Sulfur rule and

disqualify its status as a small refiner. The refiner suggested that we clarify the language and

include provisions for continuance of small refiner flexibility for refiners who qualified under

the Highway Diesel Sulfur rule (and have not been disqualified as the result of a merger or

acquisition).

11.3.2.3 Comments on the Baseline Approach

A coalition of small refiners provided comments on a few aspects of concern. The small

refiners believe that the fuel segregation, and ensuing marking and dying, provisions are quite

complex. One small refiner believes that mandating a minimum volume of NRLM production

would conflict with the purpose of maintaining adequate on-highway volumes of 15ppm sulfur

fuel and unnecessarily restricts small refiners, and offered suggestions in their comments on how

to improve the language.

11.3.2.4 Comments on Small Refiner ‘Option 4’

A coalition of small refiners commented that if the final rule is not issued before January 1,

2004, a provision should be made to accommodate those small refiners planning to take

advantage of the proposed small refiner “Option 4" (the NRLM/Gasoline Compliance option). A

small refiner echoed the concerns of the small refiner coalition, commenting that delayed

finalization of the final rule would undermine the benefits of small refiner flexibility Option 4. 

The small refiner is concerned that a delay in issuing the rule, and subsequent delay in the

opportunity to apply the interim gasoline flexibility, would negate its opportunity to take full

advantage of the credits the refiner now has, as it would not be able to comply with the 300 ppm

cap. The small refiner suggested that we allow small refiners to apply for temporary relief and

operate under the Option 4 provision.

A small refiner commented that, in the NPRM, it was unclear if a small refiner could elect to

use any or all of the first three of the small refiner provisions if it did not elect to use Option 4. 

Further, the refiner understood that if Option 4 was chosen, a small refiner could not use any of

the first three options. The refiner believes that it is important that a small refiner be able to use

Options 1, 2, and 3 in combination with each other, and stated that we need to clarify the intent

in the final rule. The small refiner also commented that the provisions in 40 CFR §§ 80.553 and

80.554 are not clear and should be revised to clarify their intent. Specifically, the refiner

questioned whether or not a small refiner who committed to producing ULSD by June 1, 2006 in

exchange for an extension of its interim gasoline sulfur standards (under 40 CFR 80.553) could

elect to exercise the options allowed under 40 CFR 80.554.

Another small refiner raised the concern that the small refiner Option 4 only provides an

adjustment to those small refiners whose small refiner gasoline sulfur standards were established
Small-Business Flexibility Analysis

11-5

through the hardship process of 40 CFR § 80.240. The small refiner suggested that we finalize a

compliance option that allows a 20% increase in small refiner gasoline sulfur standards be

extended to all small refiners, not just those with standards established pursuant 40 CFR §

80.240(a), and offers suggested language in its comments.

11.3.2.5 Comments on Emission Impacts of the Small Refiner Provisions

A state environmental group commented that the provisions for small refiners raise

substantial environmental concerns. The group is concerned that these provisions will allow

small refiners the ability to produce gasoline with an unknown sulfur content for an unknown

length of time; this fuel may then be sold at the refiner’s retail outlet, and may become the

primary fuel for some vehicles, which alters vehicle fleet emissions performance. This

environmental group also commented that the absence of any process of notification regarding

small business provisions to notify States of these provisions is troubling. The group’s concern

is that any deviations from fuel content regulations that affect fuels consumed, can significantly

alter their inventories and can undermine the State planning process. The group suggested that in

the future there should be greater communication from us regarding decisions that impact the

quality of fuels consumed in a state, and thus impact the quality of that state’s air.

Another state environmental group commented on the flexibility provisions for small

refiners; the group is concerned that the exemption will not have a minor effect on the nation’s

fuel supply, as the state is an intermountain western state. The group comments that the impact

of this exemption is concentrated in these states, namely Washington and Oregon- states which

are served primarily by refineries that will be allowed to delay compliance with the ULSD

standards until 2014. Therefore, the group commented, residents of these areas are denied air

quality benefits equivalent to those promised the rest of the country. The group is concerned that

those seeking to purchase and use equipment in the West will be subject to the ULSD standard

regardless of fuel supply and availability in their area. Further, they would be faced with

problems such as misfueling, the need to defer the purchase of new equipment, or paying a

premium for a ‘boutique’ fuel.

11.3.2.6 Comments on Inclusion of a Crude Capacity Limit for Small Refiners

Two non-small refiners supported the inclusion of the 155,000 bpcd limit; further, one refiner

commented that any refiner with the financial wherewithal to acquire additional refineries to

allow its crude capacity to exceed 155,000 bpcd should not be able to retain status as a small

refiner. Another commenter stated that if we were to finalize the 155,000 bpcd limit, we should

not apply it in cases of a merger between two small refiners. The commenter further stated that a

merger of two small companies in a hardship condition does not imply improved financial health

in the same way that an acquisition would. A small refiner is commented that it supports the

addition of the capacity limit in the small refiner definition as it would correct the problem of the

inadvertent loop-hole in the two previous fuel rules. Though the refiner did raise the concern

that the wording of the proposed language may result in small refiners such as itself, who grew

by normal business practice, being disqualified as small refiners.
Final Regulatory Support Document

11-6

11.3.2.7 Comments on Leadtime Afforded for Mergers and Acquisitions

A non-small refiner suggested that we limit the provision of affording a two-year leadtime to

small refiners who lose their small status due to merger or acquisition to the case where a small

refiner merges with another small refiner. Further, the refiner commented that it would be

inappropriate to allow such small refiners to be able to generate credits for “early” production of

lower sulfur diesels during this two-year leadtime. Lastly, the refiner commented that a small

refiner which acquires a non-small refiner, and thus loses its small refiner status, should not be

eligible for hardship provisions. Another non-small refiner commented that it supports the twoyear lead time for refineries that lose their status as a small refiner due to a merger or acquisition.

11.3.2.8 Necessity of Small Refiner Program

A non-small refiner provided comment on the NPRM stating the belief that the proposed

provisions for small refiners are not practical. The refiner is concerned that having provisions

for small refiners adds a level of complication, results in emissions losses, increases the potential

for ULSD contamination, and create an unfair situation in the marketplace. Similarly, another

non-small refiner and a trade group representing many refiners and others in the fuels industry

commented that they oppose the extension of compliance deadlines for small refiners, as this can

result in inequitable situations that may affect the refining industry for some time and can put the

distribution system at risk for contamination of lower sulfur fuels. They further stated that all

refiners will face challenges in complying with the upcoming standards and would not

significantly alter the business decisions that small refiners would make. They also stated that

non-small refiners face similar issues with their older and/or smaller refineries, but will not have

the benefit of being able to postpone making these decisions as small refiners will.

11.3.2.9 Comments on Fuel Marker

We received comments from terminal operators stating that the proposed heating oil marker

requirements would force small terminal operators to install expensive injection equipment and

that they would not be able to recoup the costs.

11.4 Description of Affected Entities

Small entities include small businesses, small organizations, and small governmental

jurisdictions. For assessing the impacts of the rule on small entities, a small entity is defined as:

(1) a small business that meets the definition for business based on the Small Business

Administration’s (SBA) size standards (see Table 11-1); (2) a small governmental jurisdiction

that is a government of a city, county, town, school district or special district with a population

of less than 50,000; and (3) a small organization that is any not-for-profit enterprise that is

independently owned and operated and is not dominant in its field. Table 11-1 provides an

overview of the primary SBA small business categories potentially affected by this regulation.
Small-Business Flexibility Analysis

11-7

The following sections discuss the small entities directly regulated by this final rule—namely

nonroad diesel engine manufacturers, nonroad diesel equipment manufacturers, and nonroad fuel

refiners and fuel marketers/distributors. Also, Table 11-2 lists our assessment of the number of

small entities that will be directly affected by this rulemaking.

Table 11-1

Small Business Definitions

Industry Defined as small 

entity by SBA if:

Major SIC Codesa

Engine manufacturers Less than 1,000 employees Major Group 35

Equipment manufacturers:

- construction equipment

- industrial truck manufacturers (i.e., forklifts)

- all other nonroad equipment manufacturers

Less than 750 employees

Less than 750 employees

Less than 500 employees

Major Group 35

Major Group 35

Major Group 35

Fuel refiners Less than 1500 employeesb 2911

Fuel distributors varies varies

a

 Standard Industrial Classification

b

 In previous rulemakings to set fuel requirements, we have included a provision that a refiner must also have a companywide crude refining capacity of no greater than 155,000 barrels per calendar day to qualify for the small-refiner

flexibilities,. We have included this criterion in the small-refiner definition for this final rule.

Table 11-2

Number of Small Entities To Which the Nonroad Diesel Rule Will Apply

Industry Defined as small entity by SBA if: Number of Affected Entities

Engine manufacturers Less than 1,000 employees 4a

Equipment manufacturers (see criteria in Table 11-1) 335a

Fuel refiners Less than 1500 employees 26

Fuel distributors varies (see discussion in 11.4.2.2)

a

 The numbers of affected entities for these categories are taken from the total number of companies that were used in our

screening analysis (i.e., companies with publicly available employee and sales data).

11.4.1 Description of Nonroad Diesel Engine and Equipment Manufacturers

To assess how many small engine and equipment manufacturers would be directly affected

by the rule, we first created a database consisting of firms listed in the Power Systems Research

(PSR) database and compared this with the list of companies from the analysis performed for the

1998 nonroad final rule and with membership lists from trade organizations. We then found

sales and employment data for the parent companies of these firms using databases such as the

Thomas Register and Dun and Bradstreet. Due to the wide variety in the types of equipment that
Final Regulatory Support Document

A All sales information used for this analysis was 2000 data.

11-8

use nonroad diesel engines, there are numerous SIC codes in which the equipment manufacturers

report their sales, though the majority of the firms are listed under the SIC major group 35xxIndustrial and Commercial Machinery and Computer Equipment.

We conducted a preliminary industry profile to identify the engine and equipment

manufacturers that are in the nonroad diesel sector. We identified more than 1,000 businesses

that fit this description; however, due to a lack of publicly available sales or employment data,

some of these entities could not be confirmed for consideration in the analysis.

11.4.1.1 Nonroad Diesel Engine Manufacturers

Using information from the preliminary industry profile, we identified a total of 61 engine

manufacturers. The top 10 engine manufacturers comprise over 80 percent of the total market,

while the other 51 companies make up the remaining percentage.A Of the 61 manufacturers, four

fit the SBA definition of a small entity. These four manufacturers were Anadolu Motors,

Farymann Diesel GmbH, Lister-Petter Group, and V & L Tools (parent company of Wisconsin

Motors LLC, formerly ‘Wis-Con Total Power’). These businesses comprise approximately 8

percent of the total engine sales for the year 2000. Lister Petter and V & L Tools were the only

two manufacturers which had certified engines for model year 2000.

Wisconsin Motors produces diesel engines for a small niche market and served as a Small

Entity Representative (SER) during the Small Business Advocacy Review Panel process,

speaking to the needs of small engine manufacturers.

11.4.1.2 Nonroad Diesel Equipment Manufacturers

This rule will result in equipment manufacturers incurring some increased costs as a result of

the need to make changes to their equipment to accommodate the addition of aftertreatment

technologies. The vast majority of equipment manufacturers are not integrated companies,

meaning that they do not make the engines they install. Thus, most equipment manufacturers are

largely dependent on engine manufacturers for the availability of pre-production information

about the new engines and for a sufficient supply of the engines once production begins. 

Equipment manufacturers that are small businesses may, in general, face a disproportionate

degree of hardship in adapting to these types of changes in design and increased costs of new,

cleaner engines.

To determine the number of equipment manufacturers, we also used the industry profile that

was conducted. From this, we identified more than 700 manufacturers with sales and/or

employment data that could be included in the screening analysis. These businesses included

manufacturers in the construction, agricultural, and outdoor power equipment (mainly, lawn and

garden equipment) sectors of the nonroad diesel market. The equipment produced by these

manufacturers ranged from small (sub-25 hp walk-behind equipment) to large (in excess of 750
Small-Business Flexibility Analysis

11-9

hp, such as mining and construction equipment). Of the manufacturers with available sales and

employment data (approximately 500 manufacturers), small equipment manufacturers represent

68 percent of total equipment manufacturers (and these manufacturers account for 11 percent of

nonroad diesel equipment industry sales). Thus, the majority of the small entities that could

potentially experience a significant impact as a result of this rulemaking are in the nonroad

equipment manufacturing sector.

While a few small equipment manufacturers did serve as SERs during the SBREFA Panel

process, a trade association representing many equipment manufacturers also served as a SER. 

We believe that due to the large number of small equipment manufacturers, this SER was better

able to contact and disseminate information to the large universe of small entities in this category

and serve as a voice for some of the extremely small equipment manufacturers.

11.4.2 Description of the Nonroad Diesel Fuel Industry

The analysis that we developed for the refining industry is built on analyses that were

performed for the gasoline and highway diesel sulfur programs in recent years. Information

about the characteristics of refiners came from sources including the Energy Information

Administration within the U.S. Department of Energy, and from oil industry literature. Our

assessment was that the refining industry is located primarily in SIC 2911. In both the gasoline

sulfur and highway diesel sulfur rules, we applied specific small-refiner flexibilities to refiners

that have no more than 1500 employees and no greater than 155,000 barrels per calendar day

crude capacity. For transporters, distributors, and marketers of nonroad diesel fuel, trade groups

were our key sources for information about this industry. We determined that this industry

sector includes several types of businesses that fall into several different SBA small entity

criteria; our assessment was that the vast majority of these entities are small.

11.4.2.1 Nonroad Diesel Fuel Refiners

Our assessment is that 26 high-sulfur (nonroad and locomotive and marine) refiners,

collectively owning 33 refineries, meet SBA’s definition of a small business for the refining

industry. The 33 refineries appear to meet both of the employee number and production volume

criteria mentioned above, out of a total of approximately 91 nonroad refineries. These small

refiners produce approximately 6 percent of the total high-sulfur diesel fuel. Note that because

of the dynamics in the refining industry (such as mergers and acquisitions), this figure could

likely change.

A few small refiners, as well as representatives of an ad-hoc coalition of some of the small

refiners participated in the SBREFA process. These small refiners, and those in which they

represented, provide high sulfur diesel fuel for various non-highway markets and applications,

and own and operate refineries throughout the country.
Final Regulatory Support Document

11-10

11.4.2.2 Nonroad Diesel Fuel Distributors and Marketers

The industry that transports, distributes, and markets nonroad diesel fuel encompasses a wide

range of businesses, including bulk terminals, bulk plants, fuel oil dealers, and diesel fuel

trucking operations, and totals thousands of entities that have some role in this activity. More

than 90 percent of these entities meet small-entity criteria. Common carrier pipeline companies

are also a part of the distribution system; 10 of them are small businesses.

Similar to the nonroad small business equipment sector, the universe of nonroad fuel

distributors and marketers is quite large, so representatives of fuel pipeline and fuel marketing

trade groups participated in the SBREFA process. We believe that these representatives were

very capable of speaking to the needs of their members that are small entities and were also

better able to disseminate SER outreach information to these markets.

11.5 Projected Reporting, Recordkeeping, and Other Compliance

Requirements of the Regulation

For engine and equipment manufacturers, EPA is continuing many of the reporting,

recordkeeping, and compliance requirements prescribed for these categories in 40 CFR part 89. 

These include, certification requirements and provisions related to reporting of production,

emissions information, use of transition provisions, etc. The types of professional skills required

to prepare reports and records is also similar to the types of skills set out in 40 CFR part 89. Key

differences in the requirements of this final rule, as compared to 40 CFR part 89, are the

reporting of emissions information and defect reporting -- we are finalizing an increase in the

number of data points (i.e. transient testing) that will be required for reporting emissions

information, as well as adopting an increased reporting burden for Tier 3 and earlier engines for

defect reporting. In addition, we are requiring that manufacturers report to us if they learn that a

substantial number of their engines have emission-related defects. This is generally not an

affirmative requirement to collect information. However, if manufacturers learn that there are,

or might be, a substantial number of emission-related defects, then they must send us

information describing the defects.

For any fuel control program, we must have the assurance that fuel produced by refiners

meets the applicable standard, and that the fuel continues to meet this standard as it passes

downstream through the distribution system to the ultimate end user. Which is of particular

importance in regards to diesel fuel, since the aftertreatment technologies expected to be used to

meet the engine standards are highly sensitive to sulfur. Many of the recordkeeping, reporting,

and compliance provisions we are finalizing are fairly consistent with those currently in place for

other fuel programs, including the current 15 ppm highway diesel regulation. For example,

recordkeeping involves the use of product transfer documents, which are already required under

the 15 ppm highway diesel sulfur rule (40 CFR 80.560). We are finalizing additional

recordkeeping and reporting requirements for refiners, importers, and fuel distributors to

implement the designate and track provisions. Discussions with parties from all segments of the

distribution system indicated that the records necessary were analogous to records already kept
Small-Business Flexibility Analysis

11-11

as a normal process of conducting business. Consequently, the only significant additional

burden would be associated with the reporting requirement.

General requirements for reporting for refiners and importers include: registration (if the

refiner or importer is not registered under a previous fuel program), pre-compliance reports (on a

refiner or importer’s progress towards meeting the nonroad diesel fuel requirements as specified

in this rule), quarterly designation reports, and annual reports. All parties, from the refiner to the

terminal, will be required to report volumes of designated fuels received and distributed, as well

as compliance with quarterly and annual limits. All parties in the distribution system will be

required to keep product transfer documents (PTDs), though refiners and importers are required

to initially generate and provide information on commercial PTDs that identify the diesel fuel

with meeting specific needs (i.e. 15 ppm highway diesel, 500 ppm highway diesel, etc.). Also,

small refiners in Alaska that choose to delay compliance must, at a minimum, report end users of

their fuel. These end users must at a minimum also keep records of these fuel purchases. As

with previous fuel regulations, small refiners will be required to apply for small refiner status

and small refiner baselines.

In general, we are requiring that all records be kept for at least five years. This

recordkeeping requirement should impose little additional burden, as five years is the applicable

statute of limitations for current fuel programs.

Section X.B of the preamble to the final rule includes a discussion of the estimated burden

hours and costs of the recordkeeping and reporting that will be required by this final rule. 

Detailed information on the reporting and recordkeeping measures associated with this

rulemaking are described in the Information Collection Requests (ICRs), also located in the

preamble to this rulemaking-- 1897.05 for nonroad diesel engines, and 1718.05 for fuel-related

items.

11.6 Steps to Minimize Significant Economic Impact on Small Entities

As a part of the SBREFA process, we conducted outreach to a number of small entities

representing the various sectors covered in this rulemaking and convened a Panel to gain

feedback and advice from these representatives. Prior to convening the Panel, we held outreach

meetings with the SERs to learn the needs of small businesses and potential challenges that these

entities may face. The outreach meetings also helped to provide the SERs an opportunity to gain

a better understanding of the upcoming standards. The feedback that we received from SERs as

a result of these meetings was used during the Panel convening for developing regulatory

alternatives to mitigate the impacts of the rulemaking on small businesses. General concerns

raised by SERs during the SBREFA process were potential difficulty and costs of compliance

with the upcoming standards.

The Panel consisted of members from EPA, the Office of Management and Budget (OMB),

and the Small Business Administration’s Office of Advocacy (‘Advocacy’). Following the Panel

convening, a Final Panel Report detailing all of the alternatives that were recommended by the
Final Regulatory Support Document

11-12

Panel (as well as individual Panel members) was issued. We either proposed or requested

comment on the various recommendations put forth by the Panel. Below we discuss those

flexibility options recommended in the Panel Report, our proposed regulatory alternatives, and

those provisions which are being finalized. We are finalizing many of the provisions

recommended by the Panel, with exceptions noted below. We believe that the provisions that we

are finalizing will help to mitigate the burden imposed upon small entities in complying with this

rule.

11.6.1 Transition and Hardship Provisions for Small Engine Manufacturers

11.6.1.1 Panel Recommendations

The following provisions were recommended by the Panel for nonroad diesel small business

engine manufacturers. During the SBREFA process and the development of the rule, we

considered both a one-step approach as well as the two-step approach in the final rule. To be

eligible for the recommended provisions set out below, a manufacturer would have to have

certified in model year 2002 or earlier and would be limited to 2500 units per year (to allow for

some market growth). The Panel recommended these qualifications to prevent misuse of the

transition and hardship provisions as a way to enter the nonroad diesel market or to gain unfair

market position relative to other manufacturers.

For an approach that entails only one phase of standards, the Panel recommended that a

manufacturer could opt to delay compliance for a period of up to three years. The Panel also

recommended that we take comment on whether this delay period should be two, three, or four

years. Each delay would be pollutant-specific (i.e., the delay would apply to each pollutant as it

is phased in).

For an approach with two phases of standards the Panel recommended the following

transition provisions:

• an engine manufacturer could skip the first phase and comply on time with the

second; or, 

• a manufacturer could delay compliance with each phase of standards for up to two

years.

The Panel recommended that there should not be any PM aftertreatment-based standards for

engines between 25 and 75 hp. It was also recommended by the Panel that an emission-credit

program of averaging, banking, and trading (ABT) be included as part of the overall rulemaking

program.

The Panel recommended that two types of hardship provisions be extended to small engine

manufacturers. These provisions are:

• for the case of a catastrophic event or other extreme unforseen circumstances beyond

the control of the manufacturer that could not have been avoided with reasonable discretion

(such as fire, tornado, or supplier not fulfilling contract); and
Small-Business Flexibility Analysis

B EPA did not propose a change in the NOx standard for engines under 25 hp and those between 50 and 75 hp. 

For these two power bands, EPA would retain the Tier 3 standards.

11-13

• for the case where a manufacturer has taken all reasonable business, technical, and

economic steps to comply but cannot do so.

The Panel recommended that either hardship relief provision could provide lead time for up

to 2 years- in addition to the transition provisions- and a manufacturer would have to

demonstrate to the Agency’s satisfaction that failure to sell the noncompliant engines would

jeopardize the company’s solvency. The Panel further recommended that the Agency may

require that the manufacturer make up the lost environmental benefit through the use of

programs such as supplemental environmental projects.

11.6.1.2 What We Proposed

Due to the structure of the standards and their timing, we proposed transition provisions, for

small engine manufacturers encompassing both approaches recommended by the Panel (with the

inclusion of the 2,500 unit limit for each manufacturer). Following the recommendations of the

Panel, we proposed the following transition provisions for small business engine manufacturers:

• for PM-

- small engine manufacturers could delay compliance with the standards for up to three

years for engines under 25 hp, and for engines between 75 and 175 hp (as these

engines only have one standard)

- small engine manufacturers could have the option to delay compliance for one year if

interim standards are met for engines between 50 and 75 hp (for this power category

we would be treating the PM standard as a two phase standard) with the stipulation

that small manufacturers could not use PM credits to meet the interim standard; also,

if a small manufacturer elects the optional approach to the standard (elects to skip the

interim standard), no further relief would be provided

• for NOxB-

- a three year delay in the program for engines in the 25-50 hp and the 75-175 hp

categories, consistent with the one-phase approach recommendation above;

- a small engine manufacturer could be afforded up to two years of hardship (in

addition to the transition flexibilities) upon demonstrating to EPA a significant

hardship situation;

- small engine manufacturers would be able to participate in an averaging, banking,

and trading (ABT) program (which we proposed as part of the overall rulemaking

program for all manufacturers); and,

- no NOx aftertreatment-based standards for engines 75 hp and under.

We did propose ABT provisions for all nonroad engine manufacturers to enhance the

flexibility offered to engine manufacturers as they make the transition to meet the more stringent
Final Regulatory Support Document

11-14

standards. We proposed to retain the basic structure of the current nonroad diesel ABT program,

with some changes to accommodate implementation of the emission standards. Though the

Panel recommended small engine manufacturer-specific ABT provisions, we did not believe it

would be appropriate to provide a different ABT program for small business engine

manufacturers. Discussions during the SBAR process indicated that small-volume

manufacturers would need extra time to comply due to cost and personnel constraints, and we

found little reason to believe that ABT provisions specific to small manufacturers would create

an incentive to accelerate compliance. Small manufacturers would, of course, always be able to

participate in the general ABT program.

We proposed the majority of the Panel’s recommendations for small business engine

manufacturers, with noted specific provision elements for PM and NOx. As we disagreed

strongly with the Panel’s recommendation that there not be any PM aftertreatment-based

standards for engines between 25 and 75 hp, we requested comment on this recommendation,

noting our strong reservations. In addition, we proposed the Panel recommended hardship

provisions for small business engine manufacturers to provide a useful safety valve in the event

of unforeseen extreme hardship.

11.6.1.3 Provisions Being Finalized in This Rule

For nonroad diesel small business engine manufacturers, we are finalizing many of the

transition and hardship provisions that we proposed; we are finalizing some revisions to the

transition provisions, as described below, and we are finalizing all of the hardship provisions that

were proposed. While we believe that emissions from nonroad engines have a significant effect

on emissions, we also believe that offering these transition provisions to small business engine

manufacturers will have a negligible effect on air quality and the emissions inventory, and

provide an appropriate measure of lead time for these small entities. Further, we continue to

believe that a complete exemption from the upcoming standards (even assuming that such an

exemption could be justified legally) would put small business engine manufacturers at a

competitive disadvantage as eventually the rest of the market will be producing engines that are

compliant with these new standards and the equipment produced will only be able to

accommodate these compliant engines. With the transition provisions, small business engine

manufacturers will be in compliance with the Tier 4 standards in the long run and the flexibility

options will give them appropriate lead time to comply. Further, we received comments from a

small business engine manufacturer stating that such provisions are necessary and adequate to

ease the burden of compliance with the upcoming standards. As such, we believe that the

transition provisions we are adopting will be of significant help for small business engine

manufacturers, and is part of our consideration of appropriate costs in assessing lead time

pursuant to section 213 (b) of the Act.

We are finalizing the following transition provisions for small business engine

manufacturers:

For engines under 25 hp-
Small-Business Flexibility Analysis

C As the cost issues raised in SBA’s comments relate to all manufacturers (not just small business

manufacturers), further information on the costs of this technology as well as the benefits analysis, can be found in

Section VI of this preamble (and also Chapters 6 and 9, respectively).

11-15

• PM- a manufacturer may elect to delay compliance with the standard for up to three

years.

• NOx- there is no change in the level of the existing NOx standard for engines in this

category, so no special provisions are being provided.

For engines in the 25-50 hp category-

• PM- manufacturers must comply with the interim standards (the Tier 4 requirements that

begin in model year 2008) on time, and may elect to delay compliance with the 2013 Tier

4 requirements (0.02 g/bhp-hr PM standard) for up to three years.

• NOx- a manufacturer may elect to delay compliance with the standard for up to three

years.

For engines in the 50-75 hp category-

• PM- A small business engine manufacturer may delay compliance with the 2013 Tier 4

requirement of 0.02 g/bhp-hr PM for up to three years provided that it complies with the

interim Tier 4 requirements that begin in model year 2008 on time, without the use of

credits. Alternatively, a manufacturer may elect to skip the interim standard completely. 

Manufacturers choosing this option will receive only one additional year for compliance

with the 0.02 g/bhp-hr standard (i.e. compliance in 2013, rather than 2012). See Section

III.C of the preamble to the final rule for a fuller explanation of these provisions.

• NOx- there is no change in the level of the NOx standard for engines in this category,

therefore no special provisions are being provided.

For engines in the 75 to 175 hp category-

• PM- a manufacturer may elect to delay compliance with the standard for up to three

years.

• NOx- a manufacturer may elect to delay compliance with the standard for up to three

years.

Regarding the Office of Advocacy’s comments on the technical feasibility of PM and NOx

aftertreatment devices. As we proposed in the NPRM, we are not adopting standards based on

performance of NOx aftertreatment technologies for engines under 75 hp. We believe the factual

record, as documented in the preamble, the Summary and Analysis of Comments (e.g., the

response to comment 3.1.4.3), and elsewhere in this RIA, does not support the claim that the PM

standards will not be technically feasible in 2013 for the 25-75 hp engines. As set out at length

in Section 4.1.3, among other places, performance of PM traps is not dependent on engine size. 

Furthermore, as we discussed in the preamble to this final rule and earlier in Chapter 6, we

believe that such standards are feasible for these engines at reasonable costC, and will help to

improve very significant air quality problems, especially by reducing exposure to diesel PM and

by aiding in attainment of the PM 2.5 and ozone National Ambient Air Quality Standards. 

Indeed, given these facts, we do not believe that an alternative of no aftertreatment-based PM

standards for these engines would be appropriate under section 213(a)(4). We believe the

transition and hardship provisions being finalized for small business engine manufacturers in this
Final Regulatory Support Document

11-16

rule are reasonable and are a factor in our ultimate finding that the PM standards for engines in

the 25-75 hp range are appropriate, and that the lead time provided for these standards is the

earliest possible after appropriate consideration of compliance costs.

11.6.2 Transition and Hardship Provisions for Nonroad Diesel Equipment Manufacturers

11.6.2.1 Panel Recommendations

For small business equipment manufacturers the Panel recommended that we propose to

continue the transition provisions offered for the Tier 1 and Tier 2 nonroad diesel emission

standards, as set out in 40 CFR 89.102, with some modifications. Those recommended transition

provisions were:

• Percent-of-Production Allowance: Over a period of seven model years, equipment

manufacturers may install engines not certified to the new emission standards in an

amount of equipment equivalent to 80 percent of one year’s production. This would be

implemented by power category with the average determined over the period in which

the flexibility is used.

• Small-Volume Allowance: A manufacturer could exceed the 80 percent allowance in

seven years as described above, provided that the previous Tier engine use does not

exceed 700 total over seven years, and 200 in any given year. This would be limited to

one family per power category. Alternatively, the Panel recommended, at the

manufacturer’s choice by power category, a program that eliminates the “single family

provision” restriction with revised total and annual sales limits as shown below:

- For power categories below 175 hp, a manufacturer could use 525 previous Tier

engines (over seven years) with an annual cap of 150 units (these engine numbers are

separate for each of the three power categories defined in the regulations).

- For power categories above 175 hp, a manufacturer could use 350 previous Tier

engines (over seven years) with an annual cap of 100 units (these engine numbers are

separate for each of the two power categories defined in the regulations).

The Panel recommended that we seek comment on the total number of engines and

annual cap values listed above. Advocacy believed the transition to the Tier 4

technology will be more costly and technically difficult, and therefore suggested that

small business equipment manufacturers may therefore need more liberal flexibility

allowances especially for equipment using the lower hp engines. SBA and OMB

recommended that we seek comment on implementing the small-volume allowance (700

engine provision) for small equipment manufacturers without a limit on the number of

engine families that could be covered in any power category, as these Panel members

were concerned that the Panel’s recommended flexibility might not adequately address

the approximately 50 percent of small business equipment models where the annual sales

per model is less than 300 and the fixed costs are higher.

• An allowance for small business equipment manufacturers to be able to borrow from the

Tier3/Tier 4 flexibilities for use in the Tier 2/Tier 3 time frame.
Small-Business Flexibility Analysis

11-17

 The Panel recommended that - similar to the application of flexibility options that are

currently in place - the three transition provisions listed above should be provided to all

equipment manufacturers to maximize the likelihood that the application of these flexibilities

would result in the availability of previous Tier engines for use by the small business equipment

manufacturers. (See discussion on transition provisions for all equipment manufacturers in

Section III.B of the preamble to this final rule.)

The Panel also recommended that we seek comment on the need for and value of special

“application-specific” alternative standards for small equipment manufacturers for equipment

configurations that present unusually challenging technical issues for compliance. Further,

Advocacy suggested that we include a technological review of the standards in the 2008

timeframe in the proposal, and the Panel recommended that we consider this.

The Panel recommended that the following two types of hardship provisions be extended to

small equipment manufacturers:

• for the case of a catastrophic event or other extreme unforseen circumstances beyond the

control of the manufacturer that could not have been avoided with reasonable discretion

(such as fire, tornado, or supplier not fulfilling contract); and

• for the case where a manufacturer has taken all reasonable business, technical, and

economic steps to comply but cannot. In this case relief would have to be sought before

there is imminent jeopardy that a manufacturer’s equipment could not be sold and a

manufacturer would have to demonstrate to the Agency’s satisfaction that failure to get

permission to sell equipment with a previous Tier engine would create a serious

economic hardship. Hardship relief of this nature could not be sought by a manufacturer

that also manufactures the engines for its own equipment.

11.6.2.2 What We Proposed

Following the Panel’s recommendation, we proposed both the Percent-of-Production and

Small-Volume Allowances for all equipment manufacturers. Within limits, small business

equipment manufacturers would be able to continue to use their current engine/equipment

configuration and avoid out-of-cycle equipment redesign until the allowances are exhausted or

the time limit passes. We did not propose the Panel’s suggested exemption and annual cap

values; however, we did request comment on these items. We also requested comment on

implementing the small-volume allowance provision without the single family limit provision

using caps slightly lower than 700 units, with the provision being applied separately to each

engine power category subject to the proposed standards.

We also proposed and requested comment on requirements associated with the use of

transition provisions by foreign importers. During the SBREFA Panel process, the Panel

discussed the possible misuse of the transition provisions by using them as a loophole to enter

the nonroad diesel equipment market or to gain unfair market position relative to other

manufacturers. The Panel recognized that this was a possible problem, and believed that the

requirement for small business equipment manufacturers and importers to have reported

equipment sales using certified engines in model year 2002 or earlier was a sufficient safeguard. 
Final Regulatory Support Document

11-18

Upon further analysis, we found that importers of equipment from a foreign equipment

manufacturer could as a group import more excepted equipment from that foreign manufacturer

than 80 percent of that manufacturer’s production for the U.S. market or more than the smallvolume allowances identified in the transition provisions. This would create a potentially

significant disparity between the treatment of foreign and domestic equipment manufacturers. 

We did not intend this situation, and we believe it is not needed to provide reasonable lead time

for foreign equipment manufacturers.

To ensure that the transition provisions meet the intended goal of alleviating the burden on

small business equipment manufacturers, we requested comment on the additional requirement

that only the small business nonroad diesel equipment manufacturer that is most responsible for

the installing engines, and the designing, manufacturing, and assembling processes, would

qualify for the allowances provided under the small equipment manufacturer transition

provisions. For importers, only a small importer that produced or manufactured nonroad diesel

equipment would be eligible for these transition provisions. A small importer that does not

manufacture or produce equipment does not face a burden in meeting the standards, and

therefore would not receive any allowances under the transition provisions directly, but could

import exempt equipment if it is covered by an allowance or by transition provisions associated

with a foreign small business equipment manufacturer. We proposed this requirement to transfer

the flexibility offered in the transition provisions to the party with the burden. We would also

allow transition provisions and allowances to be used by foreign small business equipment

manufacturers in the same way as domestic small business equipment manufacturers, while

avoiding the potential for misuse by importers of unnecessary allowances.

We also proposed the Panel’s recommendation that equipment manufacturers be allowed to

borrow from Tier 4 flexibilities in the Tier2/3 time frame. A more detailed discussion on this

issue, as well as the proposed recommendations for importers, can be found in Section VII.B of

the preamble to the proposed rule, and Section III.B of the preamble to the final rule.

With regard to the Panel recommendation of a provision allowing small business

manufacturers to request limited “application-specific” alternative standards for equipment

configurations that present unusually challenging technical issues for compliance, we requested

comment on this recommendation (in Section VII.C of the preamble to the proposed rule);

however, we did not receive any public comments on this matter. We believed (and continue to

believe) that the transition provisions that we proposed would provide latitude, at least in the

near term, and a properly structured emission credit program for the engine manufacturers. Even

if one were to assume that these flexibilities provide insufficient lead time (which may not be the

case), application-specific standards would still be cumbersome for both the small business

equipment manufacturers and for the Agency. Further, this provision could potentially have

provided more lead time than could be justified and undermine achievable emission reductions. 

Moreover, no participant in the SBAR process offered any empirical support that such a problem

existed, nor have such issues been demonstrated (or raised) by any equipment manufacturers in

implementing the current nonroad standards. We do note, however, that we are adopting a

Technical Hardship provision for all equipment manufacturers, which allows a case-by-case

showing of extreme and unpreventable technical difficulty which can justify additional lead time
Small-Business Flexibility Analysis

11-19

for specific applications. See Section III.B.2.b to the preamble to the final rule. We believe that

this provision meets some of the concerns voiced by the Panel.

We proposed that the Panel’s recommended hardship provisions be extended to small

business equipment manufacturers in addition to the transition provisions described above. To

be eligible for these hardship provisions (as well as for the proposed transition provisions),

equipment manufacturers and importers must have reported equipment sales using certified

engines in model year 2002 or earlier. As discussed earlier, we noted this requirement to thwart

misuse of the provisions as a loophole to enter the nonroad diesel equipment market or to gain

unfair market position relative to other manufacturers and we request comment on this

restriction. Either relief provision would provide additional lead time for small business

equipment manufacturers for up to two model years based on the circumstances, and hardship

relief would not be available until other allowances have been exhausted.

11.6.2.3 Provisions in the Final Rule

We are finalizing many of the transition and hardship provisions that we proposed for small

business nonroad equipment manufacturers, with some modifications as noted below. Adopting

an alternative on which we solicited comment, the final rule will allow all equipment

manufacturers the opportunity to choose between two options:

 • manufacturers would be allowed to exempt 700 pieces of equipment over seven years,

with one engine family; or,

• manufacturers using the small-volume allowance could exempt

- 525 machines over seven years (with a maximum of 150 in any given year) for each

of the three power categories below 175 horsepower, and

- 350 machines over seven years (with a maximum of 100 in any given year) for the

two power categories above 175 horsepower.

Concurrent with the revised caps, manufacturers could exempt engines from more than one

engine family under the small-volume allowance program. Based on sales information for small

businesses, we estimated that the alternative small-volume allowance program to include lower

caps and allow manufacturers to exempt more than one engine family would keep the total

number of engines eligible for the allowance at roughly the same overall level as the 700-unit

program.

We believe that these provisions will afford small manufacturers the type of transition

leeway recommended by the Panel. Further, these transition provisions could allow small

business equipment manufacturers to postpone any redesign needed on low sales volume or

difficult equipment packages, thus saving decreasing the strain on financial resources and- in

many cases, limited- engineering personnel. Within limits, small business equipment

manufacturers would be able to continue to use their current engine/equipment configuration and

avoid out-of-cycle equipment redesign until the allowances are exhausted or the time limit

passes.

We are not finalizing the requirement that small equipment manufacturers and importers

have reported equipment sales using certified engines in model year 2002 or earlier. Please see
Final Regulatory Support Document

11-20

Section III.C.2.a.ii of the preamble for a detailed discussion on our decision to eliminate this

requirement from ths rule.

We are also finalizing three additional provisions. Two of these provisions are being

finalized for all equipment manufacturers, and therefore small business equipment manufacturers

may also take advantage of them. These are the Technical Hardship Provision and the Early Tier

4 Engine Incentive Program, and are discussed in greater detail in Sections III.B.2.b and e of the

preamble. The third provision is being finalized for small business equipment manufacturers

only, for the 20-50 hp category. This provision is discussed in greater detail in Section

III.C.2.b.ii of the preamble.

11.6.3 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Refiners

11.6.3.1 Panel Recommendations

During the SBREFA process, the Panel considered a range of options and regulatory

alternatives for providing small refiners with flexibility in complying with new sulfur standards

for nonroad diesel fuel. Taking into consideration the comments received on these ideas during

the outreach meetings with SERs, as well as additional business and technical information

gathered about potentially affected small entities, the Panel recommended that whether we

propose a one-step or a two-step approach, we should provide for delayed compliance for small

refiners as shown in Table 11-3 below.

Table 11-3

SBREFA Panel Small-Refiner Options Under 

Potential 1-Step and 2-Step Nonroad Diesel Base Programs

Recommended Sulfur Standards (in parts per million, ppm) a

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015+

1-Step

Program

Non-small b -- -- 15 15 15 15 15 15 15 15

Small -- -- -- – – – 15 15 15 15

2-Step

Program

Non-small c -- 500 500 500 15 15 15 15 15 15

Small -- -- -- -- 500 500 500 500 15 15

a New standards are assumed to take effect June 1 of the applicable year.

b

 Assumes 500 ppm standard for marine + locomotive fuel for nonsmall refiners for 2008, and for small refiners for 2012

and later.

c

 Assumes 500 ppm standard for marine + locomotive fuel for nonsmall refiners for 2007, and for small refiners for 2010

and later.
Small-Business Flexibility Analysis

11-21

The Panel also recommended that we propose certain provisions to encourage early

compliance with lower sulfur standards. The Panel recommended that we propose that small

refiners be eligible to select one of the two following options (with the maximum per-gallon

sulfur cap for any small refiner remaining at 450 ppm):

• Credits for Early Desulfurization- The Panel recommended that we propose, as part of an

overall trading program, a credit trading system that allows small refiners to generate and

sell credits for nonroad diesel fuel that meets the small-refiner standards earlier than that

required in the above table. Such credits could be used to offset higher sulfur fuel

produced by that refiner or by another refiner that purchases the credits.

• Limited Relief on Small-Refiner Interim Gasoline Sulfur Standards- The Panel

recommended that a small refiner producing its entire nonroad diesel fuel pool at 15 ppm

sulfur by June 1, 2006, and that chooses not to generate nonroad credits for its early

compliance, receive a 20 percent relaxation in its assigned small-refiner interim gasoline

sulfur standards.

The Panel recommended that we propose small refiner hardship provisions modeled after

those established under the gasoline sulfur and highway diesel fuel sulfur programs (see 40 CFR

80.270 and 80.560). Specifically, it was recommended that we propose a process that, like the

hardship provisions of the gasoline and highway diesel rules, would allow small refiners to seek

case-by-case approval of applications for temporary waivers to the nonroad diesel sulfur

standards, based on a demonstration of extreme hardship circumstances. This provision was

recommended as it would allow domestic and foreign refiners, including small refiners, to

request additional flexibility based on a showing of unusual circumstances resulting in extreme

hardship and significantly affecting the ability of the small refiner to comply by the applicable

date, despite its best efforts.

11.6.3.2 What We Proposed

We proposed the small refiner transition provisions as recommended by the Panel for a twostep program (as we chose to propose a two-step fuel implementation program), which are

shown in Table 11-4 below.
Final Regulatory Support Document

11-22

Table 11-4

Small-Refiner Options 2-Step Nonroad Diesel Base Programs

Recommended Sulfur Standards (in parts per million (ppm))a

Under 2-Step

Program

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015+

Non-smallb — 500 500 500 15 15 15 15 15 15

Small — — — — 500 500 500 500 15 15

a

 New standards are assumed to take effect June 1 of the applicable year.

b

 Assumes 500 ppm standard for marine + locomotive fuel for nonsmall refiners for 2007 and later and for small refiners

for 2010 and later.

The proposed provisions were to address the concerns that small refiners raised during the

SBREFA process and during the development of the proposal, while still expeditiously

achieving air quality benefits and ensuring timely availability of 15 ppm nonroad diesel fuel for

the introduction of 2011 model year nonroad diesel engines and equipment.

In accordance with the Panel recommendation of encouraging early compliance with the

standards, we proposed that small refiners be able to choose between the two Panelrecommended options discussed above (‘Credits for Early Desulfurization’ and ‘Limited Relief

on Small-Refiner Interim Gasoline Sulfur Standards’) to provide incentives for such early

compliance. Following the Panel’s recommendation, we proposed that the per-gallon cap for

either option could not exceed 450 ppm under any circumstances (this is also consistent with the

gasoline sulfur program).

For the ‘Credits for Early Desulfurization’ option, we proposed that a small refiner would be

able to generate NRLM diesel sulfur credits for production of 500 ppm NRLM diesel fuel before

June 1, 2010, and for production of 15 ppm nonroad fuel from June 1, 2010 through May 31,

2012. During discussions with small refiners during the development of the proposal, some

small refiners indicated that they might find it necessary to produce fuel meeting the nonroad

diesel sulfur standards earlier than required under the small-refiner program. These small

refiners listed various reasons for this, including: a limited number of grades of diesel fuel that

their respective distribution systems would carry; economically advantageous to make 500 ppm

or 15 ppm fuel earlier so as not to lose market share; and one small refiner indicated that it may

decide to desulfurize its nonroad pool at the same time as its highway diesel fuel, in June of 2006

(due to limitations in its distribution system and to take advantage of economies of scale).

For the option of ‘Limited Relief on Small-Refiner Interim Gasoline Sulfur Standards’, we

proposed that a small refiner qualifying for this option would receive a 20 percent revision in its

interim small-refiner gasoline sulfur standards for the duration of the program (i.e., through

either 2007 or 2010, depending on whether the refiner had extended its participation in the

gasoline sulfur interim program by complying with the highway diesel standard at the beginning

of that program (June, 2006, as provided in 40 CFR 80.552(c))), beginning January 1, 2004. In
Small-Business Flexibility Analysis

D Since new engines with sulfur sensitive emission controls will begin to become widespread during this time,

small refiner fuel will need to be segregated and only supplied for use in pre-2011 nonroad equipment or in

locomotives or marine engines.

11-23

addition, we proposed that a small refiner wishing to use this option would be required to

produce a minimum of 85 percent of the volume represented by its non-highway distillate

baseline percentage at 15 ppm by June 1, 2006. Further, if the refiner began to produce gasoline

in 2004 at the higher interim standard of this provision but then either failed to meet the 15 ppm

standard for its nonroad fuel or failed to meet the 85 percent requirement, the small refiner’s

original interim gasoline sulfur standard would be reinstated. The refiner would then need to

compensate for the higher gasoline levels that it had enjoyed by either purchasing gasoline sulfur

credits or producing an equivalent volume of gasoline below the required sulfur levels.

We also requested comment on a slightly different compliance schedule which would have

required small refiners to produce 15 ppm nonroad diesel fuel beginning June 1, 2013, one year

earlier than proposed above. Such a schedule would align the end of the interim small-refiner

provisions with the end of the proposed phase-in for nonroad engines and equipment and

eliminate higher sulfur nonroad fuel from the distribution system by the time all new engines

required 15 ppm fuel.

We also proposed small refiner hardship provisions, as recommended by the Panel, which are

identical to those offered under the gasoline sulfur and highway diesel fuel sulfur programs. 

These provisions would be evaluated on a case-by-case basis to provide short-term relief to those

refiners needing additional lead time due to extreme hardship circumstances.

11.6.3.3 Provisions in the Final Rule

In addition to regulating nonroad diesel fuel to a 15 ppm sulfur limit, we are also finalizing a

15 ppm standard for locomotive and marine diesel fuel. As a result, we have modified the

proposed provisions to also incorporate flexibility for small refiners in meeting the 15 ppm

locomotive and marine standard. Given the regulatory transition provisions that we are

finalizing for small refiners and small terminal operators, we are confident about going forward

with the 500 ppm sulfur standard for NRLM diesel fuel in 2007, and the 15 ppm sulfur standard

for nonroad diesel fuel in 2010 and locomotive and marine diesel fuel in 2012, as part of our

general program.

We are finalizing the Panel’s recommendation of delayed compliance for small refiners

along with transition provisions to encourage early compliance with the new standards. The

transition provisions that we are finalizing for small refiners are as follows:

• NRLM Delay Option- Small refiners will be required to comply with the standards set out

in Table 11-5 below, meeting the 500 ppm sulfur standard in 2010 and the 15 ppm sulfur

standard in 2014.D This is identical to the relief proposed in the NPRM (which small

refiners considered sufficient and supported) with the exception that it applies not only to
Final Regulatory Support Document

E This is down from the 100% requirement proposed to allow for some contamination losses in the process of

delivering fuel from the refinery. Production volumes in the final rule are based upon actual delivered volumes. The

5% allowance for greater than 15 ppm fuel should provide adequate flexibility for any refiner’s contamination

issues, while not providing any opportunity to significantly alter their compliance plans.

11-24

nonroad fuel, but also to locomotive and marine fuel. However, this delay option is not

being finalized for the Northeast and Mid-Atlantic areas due to the removal of the heating

oil marker in these areas (see discussion in Section V of the preamble). Removal of the

marker provision for heating oil in these areas will help to alleviate the concern raised by

small terminal operators in their comments regarding the cost of adding a marker to

heating oil. At the same time, its removal is not expected to impact small refiners since

we do not anticipate that they would have marketed fuel in this area. Further, this

provision will be finalized in Alaska only if a refiner gets an approved compliance plan

for segregating their fuel to the end user.

• The NRLM Credit Option- Some small refiners have indicated that they might need to

produce fuel meeting the NRLM diesel fuel sulfur standards earlier than required under

the small refiner program described above (distribution systems might limit the number

of grades of diesel fuel that will be carried, it may be economically advantageous to make

compliant NRLM diesel fuel earlier to prevent losing market share, etc.) This option

allows small refiners to participate in the NRLM diesel fuel sulfur credit banking and

trading program discussed in Section IV of the preamble. Generating and selling credits

could provide small refiners with funds to help defray the costs of early NRLM

compliance.

• The NRLM/Gasoline Compliance Option- This option is available to small refiners that

produce greater than 95 percent of their NRLM diesel fuel at the 15 ppm sulfur standard

by June 1, 2006 and elect not to use the provision described above to earn NRLM diesel

fuel sulfur credits for this early compliance.E

 For small refiners choosing this option, the

applicable small refiner annual average and per-gallon cap gasoline sulfur standards will

be increased by 20 percent for the duration of the interim program; however, in no case

may the per-gallon gasoline sulfur cap exceed 450 ppm.
Small-Business Flexibility Analysis

11-25

Table 11-5

Sulfur Standards for the NRLM Diesel Fuel Small Refiner Program

 (in parts per million (ppm))a

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015+

Non-Small- NR -- 500 500 500 15 15 15 15 15 15

Non-Small- LM -- 500 500 500 500 500 15 15 15 15

Small- all

NRLM

-- -- -- -- 500 500 500 500 15 15

Notes:

a

 New standards are assumed to take effect June 1 of the applicable year.

A small refiner may choose to use the relaxed standards (the NRLM Delay option), the

NRLM Credit option, or both in combination. Thus any fuel that it produces from crude at or

below the sulfur standards earlier than required will qualify for generating credits. However, the

NRLM/Gasoline Compliance option may not be used in combination with either the NRLM

Delay option or the NRLM Credit option, since a small refiner must produce at least 85 percent

of its NRLM diesel fuel at the 15 ppm sulfur standard under the NRLM/Gasoline Compliance

option.

Combined with the transition provisions for small refiners, the compliance schedule that we

are adopting will achieve the air quality benefits of the nonroad diesel program as soon as

possible, while helping to ensure that small refiners will have adequate time to raise capital for

new or upgraded fuel desulfurization equipment. Most small refiners have limited additional

sources of income beyond refinery earnings for financing and typically do not have the financial

backing that larger and generally more integrated companies have. They can therefore benefit

from this additional time to accumulate capital internally or to secure capital financing from

lenders. This will help to offset the disproportionate financial burden facing small refiners.

We recognize that while the sulfur levels in the proposed program can be achieved using

conventional refining technologies, new technologies are also being developed that may reduce

the capital and/or operational costs of sulfur removal. We believe that allowing small refiners

some additional time for newer technologies to be proven out by other refiners may have the

added benefit of reducing the risks faced by small refiners. Further, this additional time may

also increase the availability of engineering and construction resources. Some refiners will need

to install additional processing equipment to meet the nonroad diesel sulfur requirements. 

Vendors will be more likely to contract their services with the larger refiners first, as their

projects will offer larger profits for the vendors. Therefore, we anticipate that there may be

significant competition for technology services, engineering resources, and construction

management and labor. Temporarily delaying compliance for small refiners will allow for lower

costs of improvements in desulfurization technology and would spread out the demand for

construction and engineering resources, and likely reduce any cost premiums caused by limited

supply.
Final Regulatory Support Document

11-26

11.6.4 Transition and Hardship Provisions for Nonroad Diesel Fuel Small Distributors and

Marketers

11.6.4.1 Panel Recommendations

During the SBREFA process, we were considering both a one-step fuel approach, and the

two-step approach that we are finalizing. The Panel recognized that a two-step fuel approach

would include the possibility of there being two grades of nonroad diesel fuel in the market place

for at least a transition period, the Panel recommended that we study the issue of multiple fuel

grades in the distribution system further during our development of the NPRM. In discussions

that took place during the SBREFA process, distributors supported a one-step approach as it

would have no significant impact on their operations. However, they did offer suggestions on

how they might deal with this issue, but indicated that there would be adverse impacts in some

circumstances. (A more complete discussion of costs and related issues relevant to fuel

distributors under the proposed program is located in Chapter 7 of the Draft Regulatory Impact

Analysis.)

11.6.4.2 What We Proposed

Our proposed fuel sulfur program was designed to minimize the need for additional product

segregation and the associated feasibility and cost issues for fuel distributors associated with it. 

Beyond the accommodation of fuel distributor concerns during the overall design of the

proposed program, we did not believe it possible for us to provide special provisions for

particular (i.e., small) fuel distributors to further limit the potential impact of the proposed rule. 

However, to allow for a smooth transition of diesel fuel in the distribution system to 15 ppm, we

proposed that parties downstream of the refineries be allowed a small amount of additional time

to turnover their tanks to 15 ppm. Specifically, we proposed that at the terminal level, nonroad

diesel fuel would be required to meet the 15 ppm standard beginning July 15, 2010. At bulk

plants, wholesale purchaser-consumers, and any retail stations carrying nonroad diesel, this fuel

would have to meet the 15 ppm standard by September 1, 2010. The proposed transition

schedule for compliance with the 15 ppm standard at refineries, terminals, and secondary

distributors would be the same as those allowed under the recently promulgated highway diesel

fuel program. Lastly, to avoid the costs associated with segregating 500 ppm NRLM diesel fuel

from 500 ppm highway fuel, we proposed that the existing requirement that NRLM diesel fuel

be dyed leaving the refinery would need to be made voluntary (this element of the proposed rule

is discussed in more detail in Section 11.7 of the proposed RIA).

11.6.4.3 Provisions in the Final Rule

We are finalizing provisions to alleviate the problems raised in the public comments on our

NPRM regarding small terminal operators (heating oil marker requirements would force small

terminal operators to install expensive injection equipment and they would not be able to recoup

these costs). To decrease the burden on these small operators, we are not requiring the addition

of a fuel marker to home heating oil for terminals in much of PADD 1 (Northeast/Mid-Atlantic

Area). This Northeast/Mid-Atlantic Area covers the vast majority of heating oil that will be
Small-Business Flexibility Analysis

F The cost-to-sales ratio test assumes that control costs are completely absorbed by each entity and does not

account for or consider interaction between manufacturers/producers and consumers in a market context.

G Including the refinery, pipeline, marine tanker, and barge segments of the distribution system.

11-27

marketed; however, we are not allowing small refiner or credit fuel to be sold in the

Northeast/Mid-Atlantic Area. Further, we expect that few terminals outside of

Northeast/Mid-Atlantic Area would need to put in injection equipment, since very little fuel

above 500 ppm will be marketed outside of this area except directly from the refinery gate.

11.7 Conclusion

Throughout the entire rulemaking process, we conducted substantial outreach- including

convening a Panel during the SBREFA process as well as meetings with other stakeholders- to

gather information about the effect of this final rule on small entities. We also took into account

comments received during the public comment period and information from contractor studies in

developing regulatory transition provisions to ease the burden on small entities. From this

information (and performing a cost-to-sales ratio test- a ratio of the estimated annualized

compliance costs to the value of sales per company)F, we found that approximately 4 percent (13

companies) of small entities in the engine and equipment manufacturing industry were affected

between 1 and 3 percent of sales (i.e., the estimated costs of compliance with the final rule will

be greater than 1 percent, but less than 3 percent, of their sales). One percent of small entities (4

companies) were affected at greater than 3 percent. In all, 17 of the 518 potentially affected

small engine and equipment manufacturers are estimated to have compliance costs that could

exceed 1 percent of their sales.

Similarly, small refiners in general would likely experience a significant and disproportionate

financial hardship in complying with the fuel-sulfur requirements in this rule. One indication of

this disproportionate hardship for small refiners is the relatively high projected cost per gallon

for producing compliant nonroad diesel fuel. Refinery modeling (of all refineries) indicates that

without special provisions, refining costs for small refiners on average would be about 2.3 cents

per gallon higher than the costs for non-small refiners. The majority of the cost for meeting the

fuel requirements in this final rule are related to refining, with only 15 to 25 percent of the

estimated costs being related to distribution. Allowing highway and off-highway diesel fuel

meeting the same sulfur specification to be shipped fungibly until it leaves the terminal obviates

the need for additional storage tankage in this segment of the distribution system.G The final rule

allows 500 ppm highway and 500 ppm NRLM fuel to be shipped fungibly as proposed. 

However, it also allows high sulfur NRLM and heating oil to be shipped fungibly. Furthermore,

the final rule allows 500 ppm off-highway diesel engine fuel to be mixed with high-sulfur diesel

fuel as long as its designation changes.
CHAPTER 12: Regulatory Alternatives

12.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-1

12.2 Description of Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-2

12.2.1 One-Step Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-3

12.2.2 Two-Step Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-7

12.2.2.1 Options Evaluated for Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-7

12.2.2.2 Option 5c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-18

12.2.2.2.1 Emission Inventory Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-19

12.2.2.2.2 Cost Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-20

12.2.2.2.3 Benefits Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-20

12.2.2.2.4 Costs Per Ton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12-21
Regulatory Alternatives

12-1

CHAPTER 12: Regulatory Alternatives

Our final program represents a combination of engine and fuel standards and their associated

timing that we believe to be superior to the alternatives considered given feasibility, cost, and

environmental impact. In this chapter we present the alternative program options that we

evaluated in order to make this determination. These alternatives are cast as twelve specific

program options. 

12.1 Overview

In the Draft RIA supplementing our Notice of Proposed Rulemaking, we presented a detailed

analysis of twelve specific program options. These options were used to illustrate variations in

both the timing and level of the engine and fuel standards, as well as the applicability of those

standards to different segments of off-highway engines and fuels. To evaluate each option, we

conducted emission-inventory modeling, estimated costs and benefits, and calculated costeffectiveness. We then assessed the appropriateness of each option in comparison to our

proposed engine and fuel program, and presented our rationale for not proposing to implement

each of the options.

Following release of the proposal, we received comments on some of the options that we

evaluated. Our detailed responses to those comments can be found in Section 8 of the Summary

and Analysis of Comments document. Our reasoning set forth in Chapter 12 of the Draft RIA

supporting the proposal also still applies as well for options we have not adopted. 

We examined the costs, inventory impacts, benefits, and cost-effectiveness of each of the

options as presented in the Draft RIA incrementally to our proposed program. Given that the

final program includes some elements that differ from the proposed program, these same new

elements would need to be included in each of the options in order to maintain the same

incremental differences in program structure between the final program and each option. As a

result, we do not believe that a complete revision to the calculated values for costs, inventory

impacts, benefits, and cost-effectiveness is warranted, since we would expect them to be very

similar to those presented in the Draft RIA. Also, we would not expect recent modifications to

the NONROAD emissions model to change the incremental differences between the final

program and each of the options. We refer the reader to the detailed evaluations of the options

presented in the Draft RIA. 

The remainder of this section will present a description of the twelve options originally

evaluated in the context of the NPRM to remind readers of the program issues we investigated. 

However, during the course of reviewing comments on our proposed program, we determined

that an additional evaluation of small engine standards was warranted. This additional scenario

was labeled Option 5c, and the results of that evaluation are presented below In Section 12.2.2.2.
Final Regulatory Impact Analysis

12-2

12.2 Description of Options

Our proposed emission-control program consisted of a two-step program to reduce the sulfur

content of nonroad diesel fuel in conjunction with the NOx and PM engine standards. During

the development of our program, we also considered a one-step fuel program wherein all sulfur

reductions in the diesel fuel occur in a single step. Since the fuel provisions and timing dictate to

a large extent the possible engine standards, we structured this section to first discuss issues of

variations in the fuel program. Thus, the Program Options are divided into One-Step and TwoStep options, to highlight the fuel sulfur program and its driving impact on the engine standards. 

Within each of these fuel program approaches, we considered several variations and

combinations with engine standards.

This Section provides both text summaries of each Program Option as well as diagrams

showing how the engine and fuel standards would be implemented over time. For the diagrams,

previous standards are labelled as Tier 1, Tier 2, or Tier 3 as appropriate. For reference, Figure

12.2-1 shows the actual standards associated with Tier 1, Tier 2, and Tier 3 labels (40 CFR

89.112).
Regulatory Alternatives

12-3

Figure 12.2-1

Existing Engine and Fuel Standards

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 Tier 2: 5.6 NOx+NMHC, 0.6 PM

25 # hp

hp < 50

Tier 2: 5.6 NOx+NMHC, 0.4 PM

50 # hp

hp < 75 Tier 2: 

5.6 NOx+NMHC

0.3 PM

Tier 3: 

3.5 NOx+NMHC

75 # hp 0.3 PM

hp < 100

100 # hp

hp < 175

Tier 2: 

4.9 NOx+NMHC

0.2 PM

Tier 3:

3.0 NOx+NMHC

0.2 PM

175 # hp

hp < 750

Tier 2: 

4.8

NOx+NMHC

0.1 PM

Tier 3:

3.0 NOx+NMHC

0.1 PM

hp $ 750 Tier 1:

6.9 NOx

0.4 PM

Tier 2:

4.8 NOx+NMHC

0.1 PM

Fuel sulfur standard (ppm)

Loco & 

marine

Uncontrolled

Nonroad Uncontrolled

"

 Applies to model years. 

12.2.1 One-Step Options

One-step options were those in which the fuel sulfur standard was applied in a single step;

there were no phase-ins or step changes. In all one-step options, the transient test cycle was

required concurrently with the introduction of the transitional Tier 4 engine standards in any

horsepower group.

Option 1a differed from Options 1 and 1b in terms of the engine standards and their

associated timing. Option 1b differed from Option 1 only in the timing of the fuel sulfur

standard, and was intended to generate additional early sulfate PM reductions. As a result, we

did not lower the certification fuel sulfur level to 15ppm in 2007 and 2008 when modeling this

Option, since doing so would permit manufacturers to take advantage of the lower sulfur and

thus reduce the PM reductions associated with their certified engines.
Final Regulatory Impact Analysis

12-4

The one-step options are summarized in Table 12.2.1-1. The specifics of the three one-step

options are shown in the standard charts in Figures 12.2.1-2, 3, and 4, while the previous Tier 1,

Tier 2, and Tier 3 standards were shown in Figure 12.2-1. Only changes to the standards are

shown in these three figures, i.e. if no new standard for a given pollutant is indicated, the

previous standard applies.

Table 12.2.1-1

Summary of One-Step Options

Option Summary Description

Option 1 • Fuel sulfur # 15ppm in June 2008 for nonroad, # 500ppm for locomotives and

marine engines

C <50 hp: PM stds only in 2009

C 25-75 hp: PM aftertreatment-based standards and EGR or equivalent NOx

technology in 2013; no NOx aftertreatment

C >75 hp: PM aftertreatment-based standards phasing in beginning in 2009; NOx

aftertreatment-based standards phasing in beginning in 2011

See Figure 12.2.1-1

Option 1a • Fuel sulfur # 15ppm in June 2008

C PM aftertreatment-based standards introduced in 2009-10

C NOx aftertreatment-based standards introduced in 2011-12

See Figure 12.2.1-2

Option 1b Same as Option 1a, except fuel sulfur standard required two years earlier

See Figure 12.2.1-3
Regulatory Alternatives

12-5

Figure 12.2.1-1

Engine and Fuel Standards Under Option 1

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM

0.02 PM, 3.3(

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100 0.01 PM

100 # hp

hp < 175

Tier 3 50%: 0.01 PM 50%: 0.30 NOx 0.30 NOx

175 # hp

hp < 750

hp $ 750 Tier 1 Tier 2 50%: 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Final Regulatory Impact Analysis

12-6

Figure 12.2.1-2

Engine and Fuel Standards Under Option 1a

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25

25 # hp

hp < 50

50 # hp

hp < 75

Tier 2

0.01 PM 0.30 NOx

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3

175 # hp

hp < 750

hp $ 750 Tier 1 Tier 2

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 15 ppm

Nonroad Uncontrolled 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June.
Regulatory Alternatives

12-7

Figure 12.2.1-3

Engine and Fuel Standards Under Option 1b

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25

25 # hp

hp < 50

50 # hp

hp < 75

Tier 2

0.01 PM 0.30 NOx

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3

175 # hp

hp < 750

hp $ 750 Tier 1 Tier 2

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncont

rolled

15 ppm

Nonroad Uncont

rolled

15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June.

12.2.2 Two-Step Options

Two-step options were those in which the fuel sulfur standard was set first at 500ppm for

several years, and then was lowered further to 15ppm. The exact timing of the introduction of

the 500ppm and the 15ppm standards varied among each of the two-step options. In addition,

we considered a variety of engine standards and phase-ins. In the two-step options, the transient

test cycle was required concurrently with the introduction of the transitional Tier 4 engine

standards. The one exception was Option 5b, under which the existing steady-state test applied

indefinitely for engines below 75 hp.

12.2.2.1 Options Evaluated for Proposal

The proposed program formed the basis for all of the two-step alternative program options. 

The two-step options that we evaluated for the NPRM are summarized in Table 12.2.2-1. The

specifics of these two-step options are shown in the standard charts in Figures 12.1.2-2 through
Final Regulatory Impact Analysis

12-8

11, while the previous Tier 1, Tier 2, and Tier 3 standards were shown in Figure 12.2-1. As for

the one-step standard charts, only changes to the standards are shown, i.e. if no new standard for

a given pollutant is indicated, the previous standard applies.

Table 12.2.2-1

Summary of Two-Step Options

Option Summary Description

Proposed program C 500 ppm in 2007; 15 ppm in 2010 for nonroad engines only

C >25 hp: PM aftertreatment-based standards introduced 2011-2013

C >75 hp: NOx aftertreatment-based standards introduced and phased-in 2011-2014

C <25 hp: PM standards in 2008

C 25-75 hp: PM standards in 2008 (optional for 50-75 hp)

C >750hp: PM and NOx standards phased-in 2011-2014

See Figure 12.2.2-1

Option 2a Same as our proposed program, except:

C Transitional sulfur standard of 500 ppm is introduced one year earlier

See Figure 12.2.2-2

Option 2b Same as our proposed program, except:

C Final sulfur standard of 15 ppm is introduced one year earlier

C Trap-based PM standards begin one year earlier for all engines

See Figure 12.2.2-3

Option 2c Same as our proposed program, except:

C Final sulfur standard of 15 ppm is introduced one year earlier

C Trap-based PM standards begin one year earlier for 175 - 750 hp engines

See Figure 12.2.2-4

Option 2d Same as our proposed program, except:

C Final NOx standard for 25 - 75 hp engines is lowered to 0.30 g/bhp-hr

C A phase-in for the NOx standard for this horsepower group is included

See Figure 12.2.2-5

Option 2e Same as our proposed program, except:

C No new Tier 4 NOx standards.

See Figure 12.2.2-6

Option 3 Same as our proposed program, except:

C Above-ground mining equipment >750 hp remains at the Tier 2 standards

See Figure 12.2.2-7

Option 4 Same as our proposed program, except:

C 15 ppm final sulfur standard applies to fuel used by locomotives and marine engines in

addition to all other nonroad engines

See Figure 12.2.2-8

Option 5a Same as our proposed program, except:

C No new Tier 4 standards for <75 hp engines

See Figure 12.2.2-9

Option 5b Same as our proposed program, except:

C No trap-based PM standards for <75 hp engines

C No new Tier 4 NOx standards for <75 hp engines

See Figure 12.2.2-10
Regulatory Alternatives

12-9

Figure 12.2.2-1

Engine and Fuel Standards under the Proposed Program

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Final Regulatory Impact Analysis

12-10

Figure 12.2.2-2

Engine and Fuel Standards under Option 2a

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled

500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Regulatory Alternatives

12-11

Figure 12.2.2-3

Engine and Fuel Standards under Option 2b

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM

0.02

PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

0.01

PM

100 # hp

hp < 175

Tier 3

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.01

PM

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%:

0.01

PM

50%*

 : 0.01 PM,

0.30 NOx

100%:

0.01

PM

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Final Regulatory Impact Analysis

12-12

Figure 12.2.2-4

Engine and Fuel Standards under Option 2c

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.01

PM

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Regulatory Alternatives

12-13

Figure 12.2.2-5

Engine and Fuel Standards under Option 2d

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM

0.30

NOx

50 # hp

hp < 75

Tier 2 50%: 0.30 NOx

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30

NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30

NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle.
Final Regulatory Impact Analysis

12-14

Figure 12.2.2-6

Engine and Fuel Standards under Option 2e

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 0.01 PM

175 # hp

hp < 750

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM 0.01 PM

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. *

 Only 50% of engines must meet the new PM standard on the transient test cycle. Remaining engines meet Tier 2

standards on the steady-state test cycle.
Regulatory Alternatives

12-15

Figure 12.2.2-7

Engine and Fuel Standards under Option 3

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Mining equipment remains

at Tier 2

0.01 PM

0.30 NOx

Mining

equipment 

at Tier 2

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines not used in mining equipment must meet both the new PM and NOx standards on the

transient test cycle. Remaining engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Final Regulatory Impact Analysis

12-16

Figure 12.2.2-8

Engine and Fuel Standards under Option 4

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM 0.02 PM, 3.3,

 NOx

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm 15 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle. ,

 Actual standard is 3.5g/bhp-hr NOx+NMHC, equivalent to the Tier 3 standard for 50-75hp. For modeling

purposes, NOx portion of this standard is assumed to be 3.3g/bhp-hr.
Regulatory Alternatives

12-17

Figure 12.2.2-9

Engine and Fuel Standards under Option 5a

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25

25 # hp

hp < 50

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle.
Final Regulatory Impact Analysis

12-18

Figure 12.2.2-10

Engine and Fuel Standards under Option 5b

hp group 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nonroad engine standards (g/bhp-hr)"

hp <25 0.30 PM

25 # hp

hp < 50 0.22 PM

50 # hp

hp < 75

Tier 2

75 # hp

hp < 100

100 # hp

hp < 175

Tier 3 100%( : 0.01 PM

50%(

 : 0.30 NOx

0.01 PM

175 # hp

hp < 750

0.30 NOx

hp $ 750 Tier 1 Tier 2 50%*

 : 0.01 PM, 0.30 NOx

Fuel sulfur standard (ppm)$

Loco & 

marine

Uncontrolled 500 ppm

Nonroad Uncontrolled 500 ppm 15 ppm

"

 Applies to model years. If no standard is shown for a given pollutant, the previous standard applies.

$

 Applies to calender years. Begins in June. (

 All engines must meet 0.01 PM, but only 50% of engines must meet the new NOx standard of 0.30. All engines

must use the transient test cycle.

*

 Only 50% of engines must meet both the new PM and NOx standards on the transient test cycle. Remaining

engines meet Tier 2 standards on the steady-state test cycle.

12.2.2.2 Option 5c

As described in Section 12.2.2.1, Option 5b represented an alternative program in which we

would not apply trap-based PM standards or new NOx standards to engines under 75hp. As

described in Sections II.A and II.B of the preamble, we continue to believe that the application

of PM filters to small engines is both feasible and is an important element of our efforts to

address air quality concerns associated with nonroad engines. Therefore, we have not finalized

Option 5b and the proposed Tier 4 PM and NOx standards for <75hp engines are included in the

program we are finalizing.

Some of the original concerns raised about <75hp engines were again raised in response to

the NPRM for a smaller group of engines with rated horsepower between 25 and 50 hp. In the

process of considering this issue, we evaluated a new Option 5c in which the trap-based PM
Regulatory Alternatives

12-19

standard and the Tier 4 NOx standard would not be applied to 25 - 50 hp engines, but would

continue to apply to above 50 hp engines. This specific option is a refinement of Option 5b, but

was not evaluated for the NPRM. We evaluated this Option 5c as part of our overall evaluation

of a wide variety of alternative options. We are presenting the results of our analysis here.

As described above, we did not repeat the analyses for Options 1 through 5b for this final

rule, but instead refer the reader to the draft RIA for those analyses. The draft RIA presented the

inventory impacts, benefits, costs, and cost-effectiveness of each of the options in comparison to

the proposed program. For Option 5c, however, we evaluated the inventory impacts, benefits,

costs, and cost-effectiveness in comparison to the final program. 

12.2.2.2.1 Emission Inventory Impacts

Option 5c is identical to our final program, except that it would not require 25-50hp engines

to meet the trap-based PM standards that are in our final program, nor would it require these

engines to meet the Tier 4 NOx standards. As a result, the PM and NOx emission reductions for

Option 5c would be lower than those for our final program. However, under this option

pollutants other than PM and NOx would also be affected. For instance, the reductions in

hydrocarbons and CO that will occur for our final program are generated primarily through the

presence of catalyzed diesel particulate traps, so the removal of the trap-based PM standards for

25-50 hp engines will also produce a corresponding reduction in the HC and CO benefits. 

In evaluating the inventory impacts of Option 5c, we assumed that the 2008 PM standards for

25-50 hp engines were met using a steady-state test cycle for both our final program and Option

5c. Whether these engines should be required to meet standards under a transient test procedure

is a separate issue from the use of after-treatment. Our analysis was designed to focus in the

impacts of requiring the use of aftertreatment. 

Thus Option 5c produces fewer benefits for all pollutants starting in 2013 in comparison to

our final program. Table 12.2.2.2.1-1 shows the net impact of Option 5c on the 30-year net

present value inventory estimates.

Table 12.2.2.2.1-1

50-State 30-Year Net Present Value Emission Increases 

For Option 5c In Comparison to Final Program (tons)

3% discount rate 7% discount rate

PM 56,833 25,238

NOx + NMHC 381,459 170,819
Final Regulatory Impact Analysis

12-20

12.2.2.2.2 Cost Analysis

Option 5c would reduce the overall costs of the program since 25-50 hp engines would not 

need to install PM traps nor make engine modifications to comply with more stringent NOx

standards. We calculated the total nationwide cost savings by summing the per-engine savings

across all engines for each year starting in 2013. Table 12.2.2.2.2-1 shows the resulting 30-year

net present value cost savings for Option 5c. Costs were allocated to the various pollutants

according to the methodology described in Chapter 8 of the RIA.

Table 12.2.2.2.2-1

50-State 30-Year Net Present Value Cost Savings 

For Option 5c In Comparison to Final Program ($million)

3% discount rate 7% discount rate

All pollutants 2,041 997

PM 1,514 735

NOx + NMHC 527 263

12.2.2.2.3 Benefits Comparison

We were able to estimate the benefits of Option 5c using the benefit-transfer methodology

developed in Chapter 9 for estimating the monetized benefits of the final program. The specific

methodology is described in Section 9.5 “Development of Intertemporal Scaling Factors and

Calculation of Benefits Over Time” and will not be repeated here. To use that methodology

requires input of 48-state emission reductions for NOx, PM2.5 and SO2 associated with Option

5c. We cannot estimate 50-state benefits due to the fact that our air quality modeling work

covers only 48 states, and we are unable to extrapolate those results to Alaska or Hawaii. PM2.5

is used for these calculations rather than PM10 because the underlying health effect studies rely

on PM2.5 data. 

Accounting for the reduction in monetised health and welfare benefits from the net emission

inventory impacts of Option 5c in comparison to our final program produces 30-year net present

value of loss in benefits of $36.6 billion at a 3 percent discount rate, and $14.8 billion at a 7

percent discount rate. This loss in benefits is much larger than the costs savings associated with

not applying trap-based PM standards to 25-50-hp engines as shown in Table 12.2.2.2.2-1,

highlighting the fact that there is a substantial net benefit to society of applying the trap-based

PM standards to 25-50 hp engines.
Regulatory Alternatives

12-21

12.2.2.2.4 Costs Per Ton

The cost-effectiveness of the final standards for 25-50 hp engines can be calculated from the

values in Tables Table 12.2.2.2.1-1 and Table 12.2.2.2.2-1. The results are given in Table

12.2.2.2.4-1. 

Table 12.2.2.2.4-1

50-State 30-Year Net Present Value Cost-Effectiveness 

For Option 5c In Comparison to Final Program ($/ton)

3% discount rate 7% discount rate

PM 26,600 29,100

NOx + NMHC 1,400 1,500