United States

Environmental Protection

Agency

Air and Radiation EPA420-R-00-020

October 2000

Procedures for Developing

Base Year and Future Year

Mass and Modeling

Inventories for The HeavyDuty Engine and Vehicle

Standards and Highway

Diesel Fuel (HDD)

Rulemaking

 Printed on Recycled Paper
EPA420-R-00-020

October 2000

Procedures for Developing Base Year and Future Year

Mass and Modeling Inventories for The Heavy-Duty

Engine and Vehicle Standards and Highway

Diesel Fuel (HDD) Rulemaking

Mr. Gregory Stella (MD-14)

Office of Air Quality Planning and Standards

U.S. Environmental Protection Agency

Prepared for EPA by

E.H. Pechan & Associates, Inc.

3622 Lyckan Parkway, Suite 2002

Durham, NC 27707

and

5528-B Hempstead Way

Springfield, VA 22151

September 29, 2000

EPA Contract No. 68-D7-0067

Work Assignment No. 3-15

Pechan Report No. 00.09.002/9008-315 (Rev.)
iii

CONTENTS

Page

TABLES AND FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

ACRONYMS AND ABBREVIATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

CHAPTER I

BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I-1

CHAPTER II

ELECTRICITY GENERATING UNITS (EGUs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-1

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY . . . . . . . . . . . . . . . . . . . . . . II-1

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES . . . II-1

1. ORISID AND BLRID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-1

2. County Identifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-3

3. Latitude and Longitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-3

4. Universal Transverse Mercator (UTM) Coordinates . . . . . . . . . . . . . . . . . . . . . . II-3

5. SCC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-3

6. Stack Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-3

7. Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-3

8. New Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-5

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT 

FILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-5

1. Mass Emission Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-5

2. EPS 2.5 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-5

3. EMS-95 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-6

CHAPTER III

NON-EGU POINT SOURCES ............................................. III-1

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY ..................... III-1

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES . . III-1

1. Growth Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III-1

2. Control Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III-5

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT 

FILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III-11

1. Mass Emission Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III-11

2. EPS 2.5 Emissions Processor Input Files ............................ III-11

3. EMS-95 Emissions Processor Input Files ............................ III-11
CONTENTS (continued)

iv

CHAPTER IV

STATIONARY AREA SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-1

A. 1996 BASE YEAR EMISSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-1

B. 2007, 2020, AND 2030 FUTURE YEAR EMISSIONS . . . . . . . . . . . . . . . . . . . . . . IV-1

1. Growth Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-1

2. Control Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-6

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT 

FILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-14

1. Mass Emission Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-14

2. EPS 2.5 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-14

3. EMS-95 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-14

CHAPTER V

NONROAD SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-1

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY . . . . . . . . . . . . . . . . . . . . . V-1

1. NONROAD Model Equipment Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-1

2. Emission Estimates for Aircraft, Commercial Marine Vessels, and 

Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-3

3. Methodologies for NH3 and SOA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-4

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES . . V-5

1. Nonroad Model Equipment Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-5

2. Emission Estimates for Aircraft, Commercial Marine Vessels, and 

Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-10

3. Methodologies for NH3 and SOA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-10

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT 

FILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-11

CHAPTER VI

ON-HIGHWAY VEHICLE SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-1

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY . . . . . . . . . . . . . . . . . . . . . VI-1

1. Inspection and Maintenance (I/M) Programs . . . . . . . . . . . . . . . . . . . . . . . . . . VI-4

2. RFG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-4

3. Oxygenated Gasoline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-4

4. Low Emission Vehicle (LEV) Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-4

5. MOBILE5 to MOBILE6 Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . VI-9

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES . . VI-15

1. Growth Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-15

2. Base Case Control Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-15

3. Control Case Emission Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-20
CONTENTS (continued)

v

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT 

FILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-20

1. EMS-95 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-20

2. EPS 2.5 and Mass Emission Inventory - File Structures . . . . . . . . . . . . . . . . . VI-26

CHAPTER VII

EMISSION SUMMARIES AND COMPARISONS . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-1

CHAPTER VIII

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII-1
vi

TABLES AND FIGURES

Table

II-1 Data Elements Provided in EGU Projection Files IPM Parsed Data Sets . . . . . . . . . II-2

II-2 HDDV Default Parameters for Utility Boilers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-4

II-3 Model Plant Parameters for Projected New Utility Units by Type . . . . . . . . . . . . . . . II-6

II-4 EGU Mass and Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-6

II-5 Structure for 1996 EGU Mass Emissions File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II-7

II-6 Structure for 2007, 2020, and 2030 EGU Mass Emissions Files . . . . . . . . . . . . . . . II-10

II-7 1996 EGU EPS 2.5 Emissions Processor Input File Structure . . . . . . . . . . . . . . . . . II-12

II-8 2007, 2020, and 2030 EGU EPS 2.5 Emissions Processor Input File Structure . . . . II-13

III-1 BEA National GSP Growth Forecasts ................................... III-3

III-2 Point Source CAA Baseline Control Assumptions .......................... III-6

III-3 Point Source MACT Control Assumptions ............................... III-7

III-4 Non-VOC Related MACT Assumptions ................................. III-9

III-5 NOx SIP Call Control Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III-10

III-6 Non-EGU Point Source Mass and Emissions Processor Input Files ........... III-12

III-7 Structure for 1996 Base Year Non-EGU Mass Emissions File ............... III-13

III-8 Structure for 2007, 2020, and 2030 Future Year Non-EGU Mass Emissions Files III-15

III-9 Non-EGU EPS 2.5 Emissions Processor Input File Structure ................ III-18

III-10 Non-EGU EMS-95 Emissions Processor Input File Structure ................ III-19

IV-1 BEA Growth Categories Assigned by Major Source Category: Area Sources . . . . IV-2

IV-2 Animal Husbandry Categories and Growth Assumptions . . . . . . . . . . . . . . . . . . . . IV-6

IV-3 Area Source VOC Control Measure Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . IV-7

IV-4 Residential Wood Combustion Control Efficiency Assumptions by Pollutant and Future

Year Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-9

IV-5 Vehicle Refueling VOC Control Efficiency Assumptions Included in the Future Year

Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-9

IV-6 Counties with Stage II Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-10

IV-7 Area/Nonroad Mass and Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . IV-15

IV-8 Area/Nonroad Mass Emissions Inventory File Structure . . . . . . . . . . . . . . . . . . . . IV-16

IV-9 Source Categories to which Crustal Factor was Applied to PM10 and PM2.5 Emissions in

EPS 2.5 Emissions Processor Input Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV-18

IV-10 Area/Nonroad EPS 2.5 Emissions Processor Input File Structure . . . . . . . . . . . . . IV-19

IV-11 Area/Nonroad EMS-95 Emissions Processor Input File Structure . . . . . . . . . . . . . IV-20

V-1a Temperature and RVP Inputs for National NONROAD Model Runs . . . . . . . . . . . V-2

V-1b Diesel Fuel Sulfur Input Values for National NONROAD Model Runs . . . . . . . . . V-2

V-2 Surrogate SCC Assignments for New SCCs in June 2000 NONROAD Model . . . . V-4

V-3 Growth Indicators/Projection Methods for Nonroad Sources . . . . . . . . . . . . . . . . . . V-6

V-4 Steady-State Emission Factors for CI Engines in the NONROAD Model . . . . . . . . V-8

V-5 Emission Factors for SI Engines Below 25 hp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V-9

VI-1 HPMS to MOBILE5 VMT Vehicle Category Assignments . . . . . . . . . . . . . . . . . . . VI-2
TABLES AND FIGURES (continued)

vii

VI-2 National 1996 VMT by Vehicle Type for HDD Analysis . . . . . . . . . . . . . . . . . . . . . VI-2

VI-3 Average Speeds by Road Type and Vehicle Type

Miles per Hour) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-3

VI-4 Counties Modeled with Federal Reformulated Gasoline (RFG) . . . . . . . . . . . . . . . . VI-5

VI-5 Oxygenated Gasoline Modeling Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-8

VI-6 Exhaust VOC MOBILE5b to MOBILE6 Adjustment Factors . . . . . . . . . . . . . . . . VI-11

VI-7 NOx MOBILE5b to MOBILE6 Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . VI-12

VI-8 NOx Full Usage Air Conditioning Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . VI-13

VI-9 HDDV Base Case Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-14

VI-10 National VMT Projections and VMT Fractions by Vehicle Type for HDD 

Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-15

VI-11 I/M Performance Standard Program Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-16

VI-12 Evaporative VOC MOBILE5b to MOBILE6 Adjustment Factors . . . . . . . . . . . . . VI-21

VI-13 PM Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-22

VI-14 SO2 Adjustment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-22

VI-15 HDD Control Case Emission Reduction Percentages . . . . . . . . . . . . . . . . . . . . . . . VI-23

VI-16 Structure for VMT Files (OFNVMTyy.TXT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-24

VI-17 Structure for VMT Vehicle Mix Files (NTVMIXyy.TXT) . . . . . . . . . . . . . . . . . . . VI-25

VI-18 Structure for VMT Vehicle Mix Files (OFNSPyy.TXT) . . . . . . . . . . . . . . . . . . . . VI-27

VI-19 Structure for Adjustment Factor Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-27

VI-20 Structure for On-Highway Mobile Source EPS Data Files . . . . . . . . . . . . . . . . . . . VI-28

VI-21 Structure for On-Highway Mobile Source Mass Emissions Data Files . . . . . . . . . VI-31

VII-1 Annual National HDD Rulemaking Emissions for 1996 Base Year . . . . . . . . . . . VII-3

VII-2 Annual National HDD Rulemaking Emissions for 2007 Base Case . . . . . . . . . . . VII-6

VII-3 Annual National HDD Rulemaking Emissions for 2007 Control Case . . . . . . . . . VII-9

VII-4 Annual National HDD Rulemaking Emissions Reduction for 2007 Control Case VII-12

VII-5 Annual National HDD Rulemaking Emissions for 2020 Base Case . . . . . . . . . . VII-13

VII-6 Annual National HDD Rulemaking Emissions for 2020 Control Case . . . . . . . . VII-16

VII-7 Annual National HDD Rulemaking Emissions Reduction for 2020 Control Case VII-19

VII-8 Annual National HDD Rulemaking Emissions for 2030 Base Case . . . . . . . . . . VII-20

VII-9 Annual National HDD Rulemaking Emissions for 2030 Control Case . . . . . . . . VII-23

VII-10 Annual National HDD Rulemaking Emissions Reduction for 2030 Control Case VII-26

VII-11 Annual State-Level Emissions by Major Source Category for 1996 Base 

Year . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-27

VII-12 Annual State-Level Emissions by Major Source Category for 2007 Base 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-32

VII-13 Annual State-Level Emissions by Major Source Category for 2007 Control 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-37

VII-14 Annual State-Level Emissions Reduction by Major Source Category for 2007 Control

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-39
TABLES AND FIGURES (continued)

viii

VII-15 Annual State-Level Emissions by Major Source Category for 2020 Base 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-41

VII-16 Annual State-Level Emissions by Major Source Category for 2020 Control 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-46

VII-17 Annual State-Level Emissions Reduction by Major Source Category for 2020 Control

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-48

VII-18 Annual State-Level Emissions by Major Source Category for 2030 Base 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-50

VII-19 Annual State-Level Emissions by Major Source Category for 2030 Control 

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-55

VII-20 Annual State-Level Emissions Reduction by Major Source Category for 2030 Control

Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-57

VII-21 Annual National HDD Rulemaking Emissions Summary . . . . . . . . . . . . . . . . . . VII-59
TABLES AND FIGURES (continued)

ix

Figure

VII-1 1996 County-Level Density Map of Annual VOC Emissions . . . . . . . . . . . . . . . VII-60

VII-2 1996 County-Level Density Map of Annual NOx Emissions . . . . . . . . . . . . . . . . VII-61

VII-3 1996 County-Level Density Map of Annual CO Emissions . . . . . . . . . . . . . . . . . VII-62

VII-4 1996 County-Level Density Map of Annual SOA Emissions . . . . . . . . . . . . . . . . VII-63

VII-5 1996 County-Level Density Map of Annual SO2 Emissions . . . . . . . . . . . . . . . . VII-64

VII-6 1996 County-Level Density Map of Annual PM10 Emissions . . . . . . . . . . . . . . . VII-65

VII-7 1996 County-Level Density Map of Annual PM2.5 Emissions . . . . . . . . . . . . . . . VII-66

VII-8 1996 County-Level Density Map of Annual NH3 Emissions . . . . . . . . . . . . . . . . VII-67

VII-9 County-Level Density Map of Annual VOC Emissions for 2007 Base Case . . . . VII-68

VII-10 County-Level Density Map of Annual NOx Emissions for 2007 Base Case . . . . VII-69

VII-11 County-Level Density Map of Annual CO Emissions for 2007 Base Case . . . . . VII-70

VII-12 County-Level Density Map of Annual SOA Emissions for 2007 Base Case . . . . VII-71

VII-13 County-Level Density Map of Annual SO2 Emissions for 2007 Base Case . . . . . VII-72

VII-14 County-Level Density Map of Annual PM10 Emissions for 2007 Base Case . . . . VII-73

VII-15 County-Level Density Map of Annual PM2.5 Emissions for 2007 Base Case . . . . VII-74

VII-16 County-Level Density Map of Annual NH3 Emissions for 2007 Base Case . . . . VII-75

VII-17 County-Level Density Map of Annual NOx Emission Reductions 

2007 Control Case vs. 2007 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-76

VII-18 County-Level Density Map of Annual SO2 Emission Reductions 

2007 Control Case vs. 2007 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-77

VII-19 County-Level Density Map of Annual PM2.5 Emission Reductions 

2007 Control Case vs. 2007 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-78

VII-20 County-Level Density Map of Annual VOC Emissions for 2020 Base Case . . . . VII-79

VII-21 County-Level Density Map of Annual NOx Emissions for 2020 Base Case . . . . VII-80

VII-22 County-Level Density Map of Annual CO Emissions for 2020 Base Case . . . . . VII-81

VII-23 County-Level Density Map of Annual SOA Emissions for 2020 Base Case . . . . VII-82

VII-24 County-Level Density Map of Annual SO2 Emissions for 2020 Base Case . . . . . VII-83

VII-25 County-Level Density Map of Annual PM10 Emissions for 2020 Base Case . . . . VII-84

VII-26 County-Level Density Map of Annual PM2.5 Emissions for 2020 Base Case . . . . VII-85

VII-27 County-Level Density Map of Annual NH3 Emissions for 2020 Base Case . . . . VII-86

VII-28 County-Level Density Map of Annual NOx Emission Reductions 

2020 Control Case vs. 2020 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-87

VII-29 County-Level Density Map of Annual SO2 Emission Reductions 

2020 Control Case vs. 2020 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-88

VII-30 County-Level Density Map of Annual PM2.5 Emission Reductions 

2020 Control Case vs. 2020 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-89

VII-31 County-Level Density Map of Annual VOC Emissions for 2030 Base Case . . . . VII-90

VII-32 County-Level Density Map of Annual NOx Emissions for 2030 Base Case . . . . VII-91
TABLES AND FIGURES (continued)

x

VII-33 County-Level Density Map of Annual CO Emissions for 2030 Base Case . . . . . VII-92

VII-34 County-Level Density Map of Annual SOA Emissions for 2030 Base Case . . . . VII-93

VII-35 County-Level Density Map of Annual SO2 Emissions for 2030 Base Case . . . . . VII-94

VII-36 County-Level Density Map of Annual PM10 Emissions for 2030 Base Case . . . . VII-95

VII-37 County-Level Density Map of Annual PM2.5 Emissions for 2030 Base Case . . . . VII-96

VII-38 County-Level Density Map of Annual NH3 Emissions for 2030 Base Case . . . . VII-97

VII-39 County-Level Density Map of Annual NOx Emission Reductions 

2030 Control Case vs. 2030 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-98

VII-40 County-Level Density Map of Annual SO2 Emission Reductions 

2030 Control Case vs. 2030 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-99

VII-41 County-Level Density Map of Annual PM2.5 Emission Reductions 

2030 Control Case vs. 2030 Base Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII-100
xi

ACRONYMS AND ABBREVIATIONS

AAMA American Automobile Manufacturers Association

ASTM American Society for Testing and Materials

BEA Bureau of Economic Analysis

CAA Clean Air Act

CI compression-ignition

CNG compressed natural gas

CO carbon monoxide

DOE U.S. Department of Energy

EGU electric generating unit

EIA Energy Information Administration

EMS Emissions Modeling System

EPA U.S. Environmental Protection Agency

EPS Emissions Preprocessor System

F Fahrenheit

FAA Federal Aviation Administration

FCM Fuel Consumption Model

FIPS Federal Information Processing Standard

ft feet

ft/min feet per minute

g/bhp-hr grams per brake horsepower-hour

GSP Gross State Product

HC hydrocarbon

HDD heavy-duty diesel

HDDV heavy-duty diesel vehicle

HDGV heavy-duty gasoline vehicle

HON Hazardous Organic NESHAP

hp horsepower

HPMS Highway Performance Monitoring System

I/M Inspection and Maintenance

IPM Integrated Planning Model

LDDT light-duty diesel truck

LDDV light-duty diesel vehicle

LDGT1 light-duty gasoline truck (less than 6,000 pounds in weight)

LDGT2 light-duty gasoline truck (6,000 to 8,500 pounds in weight)

LDGV light-duty gasoline vehicle

LEV Low-Emission Vehicle

LNB low-NOx burner

LPG liquid petroleum gas

LTOs Landing-Takeoff Operations

m meter

MACT maximum achievable control technology
ACRONYMS AND ABBREVIATIONS (continued)

xii

MC motorcycle

MMBtu million British thermal units

NAAQS National Ambient Air Quality Standards

NESHAP National Emission Standards for Hazardous Air Pollutants

NET National Emission Trends

NH3 ammonia

NLEV National Low Emission Vehicle

NMHC nonmethane hydrocarbon

NMOG Nonmethane Organic Gas

NOx oxides of nitrogen

OBD on-board diagnostic

OTAG Ozone Transport Assessment Group

OTAQ Office of Transportation and Air Quality

OTC Ozone Transport Commission

OTR Ozone Transport Region

PM particulate matter

PM10 primary particulate matter with an aerodynamic diameter less than or equal to

10 micrometers

PM2.5 primary particulate matter with an aerodynamic diameter less than or equal to

2.5 micrometers

POTWs Publicly-Owned Treatment Works

ppm parts per million

psi pounds per square inch

RACT reasonably available control technology

REMSAD Regulatory Modeling System for Aerosols and Deposition

RFG reformulated gasoline

RSD Regulatory Support Document

RVP Reid vapor pressure

SCCs Source Classification Codes

SCR selective catalytic reduction

SI spark-ignition

SIC Standard Industrial Classification

SIP State Implementation Plan

SNCR Selective Noncatalytic Reduction

SO2 sulfur dioxide

SOA secondary organic aerosols

SOCMI Synthetic Organic Chemical Manufacturing Industry

SOx oxides of sulfur

SSD summer season daily

TLEV transitional LEV
ACRONYMS AND ABBREVIATIONS (continued)

xiii

tpd tons per day

tpy tons per year

TSDFs treatment, storage, and disposal facilities

UAM-V Urban Airshed Model

ULEV Ultra-Low Emission Vehicle

U.S. United States

USDA U.S. Department of Agriculture

UTM Universal Transverse Mercator

VMT vehicle miles traveled

VOC volatile organic compound
I-1

CHAPTER I

BACKGROUND

To assist future State and Federal implementation of the Heavy-Duty Engine and Vehicle

Standards and Highway Diesel Fuel (HDD) mobile source emission standards, the United States

(U.S.) Environmental Protection Agency (EPA) is developing national annual and temporal

emission inventories and applying the Urban Airshed Model (UAM-V) and Regulatory Modeling

System for Aerosols and Deposition (REMSAD) to examine the regional ozone and particulate

matter (PM) concentration response to a series of emission control strategies. The purpose of

this report is to describe the procedures and assumptions used to develop the mass emissions

inventories and the emissions input files for the Emissions Modeling System (EMS-95) and

Emissions Preprocessor System (EPS 2.5) air quality model preprocessors.

The emission inventories developed to support the HDD rulemaking include the following:

 1996 Base Year;

 2007 Base Case;

 2007 Control Case;

 2020 Base Case;

 2020 Control Case;

 2030 Base Case; and 

 2030 Control Case.

These national inventories were prepared for all 50 States at the county level for mobile

highway and mobile nonroad sources. They were prepared for the 48 contiguous States (48

State) at the county-level for electric generating unit (EGU), non-EGU point, and stationary area

sources. The inventories contain annual and typical summer season day (SSD) emissions for the

following pollutants: oxides of nitrogen (NOx), volatile organic compounds (VOC), carbon

monoxide (CO), oxides of sulfur (SOx), primary particulate matter with an aerodynamic diameter

less than or equal to 10 micrometers and 2.5 micrometers (PM10 and PM2.5), ammonia (NH3), and

secondary organic aerosols (SOA). The 2007, 2020, and 2030 Base Case inventories are

prepared by applying growth and control assumptions to the 1996 Base Year inventory. The

2007, 2020, and 2030 Control Case inventories are developed from the 2007, 2020, and 2030

Base Case inventories, respectively, by applying HDD control assumptions to the on-highway

vehicle and nonroad emission source sectors. The growth and control assumptions used to

prepare the 2007, 2020, and 2030 inventories are documented in this report.

Chapters II through VI of this report document the inventories for the EGU, non-EGU point,

stationary area, nonroad, and on-highway vehicle source sectors. The chapter for each sector
I-2

documents the procedures and assumptions applied to prepare the mass emissions inventories for

the 1996 Base Year; 2007, 2020, and 2030 Base Cases; and 2007, 2020, and 2030 Control Cases. 

Each chapter also discusses the procedures and assumptions applied to prepare the emissions

input files for the EMS-95 and EPS 2.5 air quality model preprocessors. Chapter VII provides

48-State emissions summaries and density maps for the emissions inventories.
II-1

CHAPTER II

ELECTRICITY GENERATING UNITS (EGUs)

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY

The 1996 base year emissions inventory for EGUs is the 1996 National Emission Trends

(NET) point source inventory version 3.12 (EPA, 2000a). This inventory includes both annual

and typical summer season day (SSD) emissions for NOx, VOC, CO, SOx, PM10, PM2.5, and NH3. 

SOA emissions were added to the inventory by applying fractional aerosol coefficients based on

speciation of VOC emissions (Grosjean and Seinfeld, 1989). Inventory records with Source

Classification Codes (SCCs) of 101xxxxx and 201xxxxx were extracted from the NET inventory

to develop the 1996 EGU inventory.

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES

Projection year unit-level output files from the Integrated Planning Model (IPM) were

provided to Pechan by EPA for the EGU sector for 2007 and 2020. The 2020 IPM output file

was also used to represent EGU projections for 2030. These files include heat input, sulfur

dioxide (SO2) emissions, NOx emissions, and unit characteristics such as prime mover (boiler,

gas turbine), primary fuel, bottom type, and firing type. This section focuses on the steps used to

create the future year mass emissions inventories for 2007, 2020, and 2030, by adding to the IPM

files emissions for VOC, CO, PM10, PM2.5, NH3, and SOA, as well as data elements needed for

modeling (e.g., county codes, coordinates, and stack parameters). Note that the 2030 mass

emissions file is identical to the 2020 file.

The data elements included in the original IPM parsed data sets are shown in Table II-1. The

data sets include unit-level information for all existing or known planned units. For new units

(additional capacity needed to meet generation demands), state-level estimates by plant type

(prime mover) and fuel type are provided. Details about the additional or updated items for the

final 2007, 2020, and 2030 emission files are discussed below.

1. ORISID AND BLRID

Unique utility plant (ORISID) and unit (BLRID) identifiers are provided in the original IPM

parsed data set. These two variables were included in the emission inventories but were not

reviewed for accuracy because of time and resource constraints associated with preparing the

inventories for all sectors.
II-2

Table II-1

Data Elements Provided in EGU Projection Files IPM Parsed Data Sets

Data Elements Description

Unit ID IPM Unit ID

Plant Name Plant name

Plant Type Combined cycle, coal steam, oil/gas steam, turbine, other

State Name State name

State Code Federal Information Processing Standard (FIPS) State code

County Name County name (sometimes missing)

County Code FIPS county code (sometimes missing)

ORIS Code ORIS plant code for those units assigned codes, IPM plant code otherwise

Blr ORIS boiler or unit code where available, otherwise IPM unit code

Capacity Boiler/unit capacity (MW)

July Day Heat July day heat input (109

 Btu/day)

Fuel Type Primary fuel burned: coal, gas, natural gas, none, refuse, waste coal,

wood waste

Bottom Boiler bottom type: dry, wet, other, unknown, or blank

Firing Firing type: cell, cyclone, tangential, vertical, well, wet, other, or unknown

Existing SO2/NOx Controls Existing control for SO2 and/or NOx - scrubbed, unscrubbed, or blank

Retrofit SO2/NOx Controls Coal to combined cycle, gas reburn, oil/gas selective noncatalytic

reduction (SNCR), oil/gas to combined cycle, retirement, coal selective

catalytic reduction (SCR), coal scrubber, coal SNCR, or blank

Typical July Day NOx Typical July day NOx emissions (tons/day)

Ash Content Coal ash content (for fuel type - coal only)

Fuel Sum 5-month summer heat input (1012 Btu)

Fuel Tot Annual heat input (1012 Btu)

NOx Sum 5-month NOx emissions (103

 Ton)

NOx Tot Annual NOx emissions (103

 Ton)

SO2 Tot Annual SO2 emissions (103

 Ton)
II-3

2. County Identifiers

For those units with no county identifiers, counties available in cross-reference files

developed for the NOx State Implementation Plan (SIP) Call EGU file and other prior analyses

were utilized to identify and assign the county code. Plants were matched to other inventories by

State and plant name in some cases. Others were matched to Energy Information Administration

(EIA)-860 planned unit files or to North American Electric Reliability Council reports to identify

the county.

3. Latitude and Longitude

Latitude and longitude coordinates were assigned at the plant level and were taken from a

data base file developed by Pechan. This file includes coordinates from other inventories,

including the NET inventory and the Ozone Transport Assessment Group (OTAG) inventory,

where units were matched to these inventories at the boiler or plant level. For units that have

ORIS IDs that did match to this file, county centroids were assigned.

4. Universal Transverse Mercator (UTM) Coordinates

The UTM coordinates and zone corresponding to the latitude and longitude were determined

by using a conversion program provided by EPA.

5. SCC

The SCC is needed to determine the appropriate emission rates to use for the additional

pollutants and to incorporate default stack parameters for units that do not match to existing

inventories. SCCs were assigned by first matching plant (ORISID) and unit (BLRID) identifiers

to existing inventories and then by assigning SCCs based on the unit, fuel, firing, and bottom

types. In cases where SCCs taken from other inventories indicate a fuel other than that specified

in the IPM unit-level file, SCCs were updated based on the indicated fuel, unit, bottom, and

firing types.

6. Stack Parameters

Stack parameters were added to the EGU file by matching to other inventories. For units

where matches to other inventories could not be made, default parameters were assigned by SCC. 

These default parameters are shown in Table II-2. Stack flow rate, temperature, diameter, height,

and velocity were quality assured using the ranges supplied by EPA (Stella, 2000); all stack flow

values were then recalculated using the algorithm specified in a technical memorandum to EPA

(Pechan-Avanti, 2000).

7. Emissions

Emissions of VOC, CO, PM10, PM2.5, and NH3 were added to the inventory by applying

average fuel-specific heat content and updated emission rates (based on updated AP-42
II-4

Table II-2

HDDV Default Parameters for Utility Boilers

SCC

Primary

Fuel

PM10

Rate

(lbs/MMBtu)

CO

Rate

(lbs/MMBtu)

VOC

Rate

(lbs/MMBtu)

Stack

Temp.

(degrees F)

Stack

Height

(feet)

Stack

Diameter

(feet)

Stack

Flow

(ft3/sec)

10100101 Coal 0.0920*Ash 1 0.0240 0.0028 175 570 24 16286

10100201 Coal 0.1000*Ash 0.0192 0.0015 175 570 24 16286

10100202 Coal 0.0885*Ash 0.0192 0.0023 175 570 24 16286

10100203 Coal 0.0100*Ash 0.0192 0.0042 175 570 24 16286

10100204 Coal 0.5077 0.1923 0.0019 175 570 24 16286

10100212 Coal 0.0885*Ash 0.0192 0.0023 175 570 24 16286

10100217 Coal 0.3000 0.6923 0.0019 175 570 24 16286

10100221 Coal 0.1000*Ash 0.0192 0.0015 175 570 24 16286

10100222 Coal 0.0885*Ash 0.0192 0.0023 175 570 24 16286

10100223 Coal 0.0100*Ash 0.0192 0.0042 175 570 24 16286

10100226 Coal 0.0885*Ash 0.0192 0.0023 175 570 24 16286

10100301 Coal 0.1298*Ash 0.0179 0.0050 175 570 24 16286

10100302 Coal 0.1643*Ash 0.0429 0.0050 175 570 24 16286

10100303 Coal 0.0621*Ash 0.0429 0.0050 175 570 24 16286

10100401 Oil 0.0393 0.0333 0.0051 300 290 12 3619

10100404 Oil 0.0393 0.0333 0.0051 300 290 12 3619

10100601 Gas 0.0018 0.0800 0.0052 300 280 12 2601

10100604 Gas 0.0018 0.0229 0.0052 300 280 12 2601

10101201 Waste 0.6648 0.0006 0.0769 175 570 24 16286

20100201 Gas 0.0419 0.1095 0.0010 300 280 12 2601

20100202 Gas 0.0095 0.3800 0.1105 300 280 12 2601

1

 Ash = coal ash content as a decimal; PM10 rate is calculated by multiplying the number by the ash content of the coal.
II-5

uncontrolled emission factors) to the reported heat input for each unit. For PM10 and PM2.5, the

reported ash content was also utilized along with control efficiency data obtained from other

inventories. A default PM control efficiency of 90 percent was applied to all coal-fired units

which did not match to other inventories. SOA emissions were added to the inventory. SOA

emissions were calculated using fractional aerosol coefficients based on speciation of the VOC

emissions (Grosjean and Seinfeld, 1989).

8. New Units

The IPM data sets provide projected heat input from new units by prime mover and fuel

type. This projected heat input was divided into individual new units based on the model plant

parameters shown in Table II-3. New units were then allocated to existing unit sites based on a

hierarchy that avoids ozone nonattainment areas (Pechan-Avanti, 1997a). After siting the units,

SCCs were assigned based on prime mover and fuel type. Default stack parameters and

emissions were added using the same methods applied for existing units. Since the new units are

defined as “new” after 1996, and 1998 data for new units were available, some new units could

be matched to the 1998 data to obtain SCCs.

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT FILES

After adding the additional parameters to the IPM unit-level file, the final mass and

modeling inventories were prepared. June and August daily heat input and emissions were added

to the mass and EMS-95 files for ozone modeling (the IPM file contains July heat input and

emissions). This was based on monthly percentage profiles by State, prime mover, and fuel

provided by EPA (Stella, 1999). The 5-month (May through September) heat input was allocated

to the month and then divided by the number of days in the month. Typical SSD emissions were

allocated using the same procedure, assuming that the emission rate remained the same across

these 5 months. Table II-4 documents the names of the EGU mass and modeling files. Because

the 2020 IPM output file was used to represent EGU projections for 2030, the mass and

modeling files for 2020 and 2030 are identical.

1. Mass Emission Inventory

The structure for the base year and projection year mass emission inventories is shown in

Tables II-5 and II-6. The structures differ since the base year inventory was taken directly from

the NET, while the projection year inventory was based on the IPM data set, which provides

different information in some cases.

2. EPS 2.5 Emissions Processor Input Files

The EPS 2.5 emissions processor input files were derived directly from the mass emission

files, utilizing the annual emissions. The structures for the base year and projection year files are

shown in Tables II-7 and II-8.
II-6

3. EMS-95 Emissions Processor Input Files

The structure for the EGU EMS-95 emissions processor input files is identical to the nonEGU point source files as shown in Table III-10 in Chapter III. In order to eliminate potential

duplicate identifiers, the letter “e” was added to all stack and segment IDs in the EGU EMS-95

input files.

A weekly profile code of 8 was utilized for all EGU sources, consistent with files prepared

for the NOx SIP Call analysis. This assumes operation 7 days a week, with slightly lower

utilization on the weekends. A daily profile code of 33 was applied for all EGU sources.

Table II-3

Model Plant Parameters for Projected New Utility Units by Type

Plant Parameters

Combined

Cycle Gas Turbine Coal

Fuel Type Natural Gas Natural Gas Coal

Unit Capacity (megawatts) 225 80 500

SCC 20100201 20100201 10100201

Stack Height [feet (ft)] 280 280 570

Stack Diameter (ft) 12 12 24

Stack Temperature (F) 300 300 175

Exhaust Gas Flow Rate (ft3

/sec) 2,601 2,601 16,286

Stack Gas Velocity (ft/sec) 23 23 36

Table II-4

EGU Mass and Emissions Processor Input Files

Year Mass EPS 2.5 EMS95 Comments

1996 EG96MS3H.DBF EG96EP2H.TXT E696EM2H.TGZ

E796EM2H.TGZ

E896EM2H.TGZ

For EMS95, June day

For EMS95, July day

For EMS95, August day

2007 EG07MS2H.DBF EG07EP2H.TXT E607EM2H.TGZ

E707EM2H.TGZ

E807EM2H.TGZ

For EMS95, June day

For EMS95, July day

For EMS95, August day

2020 EG20MS2H.DBF EG20EP2H.TXT E620EM2H.TGZ

E720EM2H.TGZ

E820EM2H.TGZ

For EMS95, June day

For EMS96, July day

For EMS95, August day

2030 EG30MS2H.DBF EG30EP2H.TXT E630EM2H.TGZ

E730EM2H.TGZ

E830EM2H.TGZ

For EMS95, June day

For EMS95, July day

For EMS95, August day
II-7

Table II-5

Structure for 1996 EGU Mass Emissions File

Variable Type Length Decimals Description

YEAR C 2 0 Year of Data

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 15 0 State Plant ID

PLANTID5 C 5 0 State Plant ID (5 Digit)

POINTID C 15 0 Point ID

POINTID5 C 5 0 Point ID (5 Digit)

STACKID C 12 0 Stack ID

STACKID3 C 3 0 Stack ID (3 Digit)

ORISID C 6 0 U.S. Department of Energy (DOE) Plant ID

BLRID C 6 0 Boiler ID

SEGMENT C 2 0 Segment ID

PLANT C 40 0 Plant Name

SCC C 10 0 SCC

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

STKVEL N 9 2 Stack Velocity (ft/sec)

BOILCAP N 8 2 Boiler Design Capacity

CAP_UNITS C 1 0 Capacity Unit Code

WINTHRU N 3 0 Winter Thruput (%)

SPRTHRU N 3 0 Spring Thruput (%)

SUMTHRU N 3 0 Summer Thruput (%)

FALTHRU N 3 0 Fall Thruput (%)

HOURS N 2 0 Hours per Day

START_HR N 2 0 Hourly Start Time

DAYS N 1 0 Days per Week

WEEKS N 2 0 Weeks per Year

THRUPUT N 11 1 Throughput Rate (SCC units/year)

MAXRATE N 12 3 Maximum Ozone Season Rate (units/day)

HEATCON N 8 2 Heat Content (MMBtu/SCC unit)

SULFCON N 5 2 Sulfur Content (mass percent)

ASHCON N 5 2 Ash Content (mass percent)

NETDC N 9 3 Maximum Nameplate Capacity (MW)

SIC N 4 0 Standard Industrial Classification (SIC) Code

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

VOC_EMF N 11 4 VOC Emission Factor (SCC units)
Table II-5 (continued)

Variable Type Length Decimals Description

II-8

NOX_EMF N 11 4 NOx Emission Factor (SCC units)

CO_EMF N 11 4 CO Emission Factor (SCC units)

SO2_EMF N 11 4 SO2 Emission Factor (SCC units)

PM10_EMF N 11 4 PM10 Emission Factor (SCC units)

PM25_EMF N 11 4 PM2.5 Emission Factor (SCC units)

NH3_EMF N 11 4 NH3 Emission Factor (SCC units)

VOC_CE N 7 2 VOC Control Efficiency (%)

NOX_CE N 7 2 NOx Control Efficiency (%)

CO_CE N 7 2 CO Control Efficiency (%)

SO2_CE N 7 2 SO2 Control Efficiency (%)

PM10_CE N 7 2 PM10 Control Efficiency (%)

PM25_CE N 7 2 PM2.5 Control Efficiency (%)

NH3_CE N 7 2 NH3 Control Efficiency (%)

VOC_CPRI N 3 0 VOC Primary Control Equipment Code

NOX_CPRI N 3 0 NOx Primary Control Equipment Code

CO_CPRI N 3 0 CO Primary Control Equipment Code

SO2_CPRI N 3 0 SO2 Primary Control Equipment Code

PM10_CPRI N 3 0 PM10 Primary Control Equipment Code

PM25_CPRI N 3 0 PM2.5 Primary Control Equipment Code

NH3_CPRI N 3 0 NH3 Primary Control Equipment Code

VOC_CSEC N 3 0 VOC Secondary Control Equipment Code

NOX_CSEC N 3 0 NOx Secondary Control Equipment Code

CO_CSEC N 3 0 CO Secondary Control Equipment Code

SO2_CSEC N 3 0 SO2 Secondary Control Equipment Code

PM10_CSEC N 3 0 PM10 Secondary Control Equipment Code

PM25_CSEC N 3 0 PM2.5 Secondary Control Equipment Code

NH3_CSEC N 3 0 NH3 Secondary Control Equipment Code

VOC_ANN N 13 4 Annual VOC (tons)

NOX_ANN N 13 4 Annual NOx (tons)

CO_ANN N 13 4 Annual CO (tons)

SO2_ANN N 13 4 Annual SO2 (tons)

PM10_ANN N 13 4 Annual PM10 (tons)

PM25_ANN N 13 4 Annual PM2.5 (tons)

SOA_ANN N 13 4 Annual SOA (tons)

NH3_ANN N 13 4 Annual NH3 (tons)

VOC_OSD06 N 13 4 June Day VOC (tons)

NOX_OSD06 N 13 4 June Day NOx (tons)

CO_OSD06 N 13 4 June Day CO (tons)

SO2_OSD06 N 13 4 June Day SO2 (tons)

PM10_OSD06 N 13 4 June Day PM10 (tons)
Table II-5 (continued)

Variable Type Length Decimals Description

II-9

PM25_OSD06 N 13 4 June Day PM2.5 (tons)

SOA_OSD06 N 13 4 June Day SOA (tons)

NH3_OSD06 N 13 4 June Day NH3 (tons)

VOC_OSD07 N 13 4 July Day VOC (tons)

NOX_OSD07 N 13 4 July Day NOx (tons)

CO_OSD07 N 13 4 July Day CO (tons)

SO2_OSD07 N 13 4 July Day SO2 (tons)

PM10_OSD07 N 13 4 July Day PM10 (tons)

PM25_OSD07 N 13 4 July Day PM2.5 (tons)

SOA_OSD07 N 13 4 July Day SOA (tons)

NH3_OSD07 N 13 4 July Day NH3 (tons)

VOC_OSD08 N 13 4 August Day VOC (tons)

NOX_OSD08 N 13 4 August Day NOx (tons)

CO_OSD08 N 13 4 August Day CO (tons)

SO2_OSD08 N 13 4 August Day SO2 (tons)

PM10_OSD08 N 13 4 August Day PM10 (tons)

PM25_OSD08 N 13 4 August Day PM2.5 (tons)

SOA_OSD08 N 13 4 August Day SOA (tons)

NH3_OSD08 N 13 4 August Day NH3 (tons)

VOC_RE N 3 0 VOC Rule Effectiveness (%)

NOX_RE N 3 0 NOx Rule Effectiveness (%)

CO_RE N 3 0 CO Rule Effectiveness (%)

SO2_RE N 3 0 SO2 Rule Effectiveness (%)

PM10_RE N 3 0 PM10 Rule Effectiveness (%)

PM25_RE N 3 0 PM2.5 Rule Effectiveness (%)

NH3_RE N 3 0 NH3 Rule Effectiveness (%)
II-10

Table II-6

Structure for 2007, 2020, and 2030 EGU Mass Emissions Files

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 15 0 State Plant ID

POINTID C 15 0 Point ID

STACKID C 12 0 Stack ID

SEGMENT C 2 0 Segment ID

ORISID C 6 0 DOE 4-Digit ORIS Plant Code

BLRID C 6 0 Boiler ID

PLANT C 40 0 Plant Name

SCC C 10 0 SCC

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

STKVEL N 9 2 Stack Velocity (ft/sec)

BOILCAP N 8 2 Boiler Design Capacity

LAT N 9 4 Latitude (degrees)

LON N 9 4 Longitude (degrees)

UTMEAST N 9 2 UTM Horizontal (kilometers)

UTMNORTH N 9 2 UTM Vertical (kilometers)

UTMZONE N 2 0 UTM Zone

ANNHEAT N 9 0 Annual Heat Input (MMBtu)

WINHEAT N 9 0 7-Month Winter Heat Input (MMBtu)

SUMHEAT N 9 0 5-Month Summer Heat Input (MMBtu)

JUNDHEAT N 9 0 June Daily Heat Input (MMBtu)

JULDHEAT N 9 0 July Daily Heat Input (MMBtu)

AUGDHEAT N 9 0 August Daily Heat Input (MMBtu)

VOC_ANN N 10 4 Annual VOC (tons)

VOC_WIN N 10 4 7-Month Winter VOC (tons)

VOC_SUM N 10 4 5-Month Summer VOC (tons)

VOC_OSD06 N 10 4 June Day VOC (tons)

VOC_OSD07 N 10 4 July Day VOC (tons)

VOC_OSD08 N 10 4 August Day VOC (tons)

NOX_ANN N 10 4 Annual NOx (tons)

NOX_WIN N 10 4 7-Month Winter NOx (tons)

NOX_SUM N 10 4 5-Month Summer NOx (tons)

NOX_OSD06 N 10 4 June Day NOx (tons)

NOX_OSD07 N 10 4 July Day NOx (tons)

NOX_OSD08 N 10 4 August Day NOx (tons)

CO_ANN N 10 4 Annual CO (tons)

CO_WIN N 10 4 7-Month Winter CO (tons)
Table II-6 (continued)

Variable Type Length Decimals Description

II-11

CO_SUM N 10 4 5-Month Summer CO (tons)

CO_OSD06 N 10 4 June Day CO (tons)

CO_OSD07 N 10 4 July Day CO (tons)

CO_OSD08 N 10 4 August Day CO (tons)

SO2_ANN N 10 4 Annual SO2 (tons)

SO2_WIN N 10 4 7-Month Winter SO2 (tons)

SO2_SUM N 10 4 5-Month Summer SO2 (tons)

SO2_OSD06 N 10 4 June Day SO2 (tons)

SO2_OSD07 N 10 4 July Day SO2 (tons)

SO2_OSD08 N 10 4 August Day SO2 (tons)

PM10_ANN N 10 4 Annual PM10 (tons)

PM10_WIN N 10 4 7-Month Winter PM10 (tons)

PM10_SUM N 10 4 5-Month Summer PM10 (tons)

PM10_OSD06 N 10 4 June Day PM10 (tons)

PM10_OSD07 N 10 4 July Day PM10 (tons)

PM10_OSD08 N 10 4 August Day PM10 (tons)

PM25_ANN N 10 4 Annual PM2.5 (tons)

PM25_WIN N 10 4 7-Month Winter PM2.5 (tons)

PM25_SUM N 10 4 5-Month Summer PM2.5 (tons)

PM25_OSD06 N 10 4 June Day PM2.5 (tons)

PM25_OSD07 N 10 4 July Day PM2.5 (tons)

PM25_OSD08 N 10 4 August Day PM2.5 (tons)

NH3_ANN N 10 4 Annual NH3 (tons)

NH3_WIN N 10 4 7-Month Winter NH3 (tons)

NH3_SUM N 10 4 5-Month Summer NH3 (tons)

NH3_OSD06 N 10 4 June Day NH3 (tons)

NH3_OSD07 N 10 4 July Day NH3 (tons)

NH3_OSD08 N 10 4 August Day NH3 (tons)

SOA_ANN N 10 4 Annual SOA (tons)

SOA_WIN N 10 4 7-Month Winter SOA (tons)

SOA_SUM N 10 4 5-Month Summer SOA (tons)

SOA_OSD06 N 10 4 June Day SOA (tons)

SOA_OSD07 N 10 4 July Day SOA (tons)

SOA_OSD08 N 10 4 August Day SOA (tons)
II-12

Table II-7

1996 EGU EPS 2.5 Emissions Processor Input File Structure

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 5 0 State Plant ID

POINTID C 5 0 Point ID

SIC N 4 0 SIC Code

STACKID C 3 0 Stack ID

SEGMENT C 2 0 Segment ID

SCC C 8 0 SCC

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

WINTHRU N 3 0 Winter Thruput (%)

SPRTHRU N 3 0 Spring Thruput (%)

SUMTHRU N 3 0 Summer Thruput (%)

FALTHRU N 3 0 Fall Thruput (%)

HOURS N 2 0 Hours per Day

DAYS N 1 0 Days per Week

WEEKS N 2 0 Weeks per Year

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

VOC N 9 3 Annual VOC (tons)

NOX N 9 3 Annual NOx (tons)

CO N 9 3 Annual CO (tons)

SO2 N 9 3 Annual SO2 (tons)

PM10 N 9 3 Annual PM10 (tons)

PM25 N 9 3 Annual PM2.5 (tons)

SOA N 9 3 Annual SOA (tons)

NH3 N 9 3 Annual NH3 (tons)
II-13

Table II-8

2007, 2020, and 2030 EGU EPS 2.5 Emissions Processor Input File Structure

Variable Type Length Decimals Description

ORISID C 6 ORIS Plant ID

BLRID C 6 ORIS Boiler ID

SEGMENT C 2 Segment ID

STACKID C 6 Stack ID

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

IPMCAP N 9 1 IPM Boiler Capacity (MW)

SCC C 8 SCC

FIPSST C 2 FIPS State Code

FIPSCNTY C 3 FIPS County Code

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

WINHEAT N 9 3 Winter Heat Input (trillion Btu/7 months)

SUMHEAT N 9 3 Summer Heat Input (trillion Btu/5 months)

WINVOC N 9 3 Winter VOC (tons)

SUMVOC N 9 3 Summer VOC (tons)

WINNOX N 9 3 Winter NOx (tons)

SUMNOX N 9 3 Summer NOx

WINCO N 9 3 Winter CO

SUMCO N 9 3 Summer CO

WINSO2 N 9 3 Winter SO2

SUMSO2 N 9 3 Summer SO2

WINPM10 N 9 3 Winter PM10

SUMPM10 N 9 3 Summer PM10

WINPM2.5 N 9 3 Winter PM2.5

SUMPM2.5 N 9 3 Summer PM2.5

WINNH3 N 9 3 Winter NH3

SUMNH3 N 9 3 Summer NH3

WINSOA N 9 3 Winter SOA

SUMSOA N 9 3 Summer SOA

PNAME C 30 Plant Name
III-1

CHAPTER III

NON-EGU POINT SOURCES

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY

The 1996 base year inventory for non-EGUs is the 1996 NET point source inventory Version

3.12 (EPA, 2000a). This inventory includes both annual and typical summer season day (SSD)

emissions for NOx, VOC, CO, SOx, PM10, PM2.5, and NH3. SOA emissions were added to the

inventory by applying fractional aerosol coefficients based on speciation of VOC emissions

(Grosjean and Seinfeld, 1989). Inventory records with SCCs of 101xxxxx and 201xxxxx were

excluded from the non-EGU inventory because they are included in the EGU inventory.

Latitude and longitude coordinates and stack parameters were corrected for several sources. 

For some sources, multiple SCCs were listed under a single point, stack, and segment. New nonduplicate segment IDs were created for the mass emissions file to ensure that each record had a

unique identification code for inclusion in the emissions processor input files.

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES

Future year base case emissions for 2007, 2020, and 2030 were grown from the 1996 base

year mass emission inventory utilizing Bureau of Economic Analysis (BEA) Gross State Product

(GSP) growth factors at the State level by 2-digit Standard Industrial Classification (SIC) code. 

Control measures reflecting Clean Air Act (CAA) requirements were then incorporated. Two

separate mass emissions inventories were created for each year to reflect emissions without and

with the effects of the NOx SIP Call control requirements.

1. Growth Assumptions

The 1995 BEA GSP projections (BEA, 1995) by 2-digit SIC code were applied to estimate

changes in activity between 1996 and 2007, 2020, and 2030 for the non-EGU point source sector. 

For fuel combustion sectors, energy adjustment factors were also applied to the base year

emission inventory. After applying the changes in activity, additional controls were added to

reflect the alternative scenarios.

EPA guidance for projecting emissions (EPA, 1991) lists the following economic variables

(in order of preference) for projecting emissions:

• product output;

• value added;

• earnings; and

• employment.
III-2

In the absence of product output projections, EPA guidance recommends value added

projections. Value added is the difference between the value of industry outputs and inputs. 

BEA GSP projections represent a measure of value added, and are a fuller measure of growth

than BEA’s earnings projections because earnings represents only one component of GSP. GSP

reflects the difference between revenues from selling a product and the amounts paid for inputs

from other industries. By incorporating inputs to production, GSP reflects future changes in

production processes, efficiency, and technological changes. A comparison of BEA’s 1995 GSP

projections and BEA’s 1990 earnings projections indicates that GSP growth factors are slightly

higher than the earnings data. This is most often true for capital-intensive industries (e.g.,

manufacturing) than for labor-intensive industries (e.g., services). Components of GSP include

payments to capital. This is an important distinction to make because it implicitly reflects the

effect of factor substitution in production. As discussed in EPA’s projections guidance, factor

substitution should be included in growth projections, making value added data preferable to

earnings data for projecting emissions.

The 1995 BEA industry GSP projections by State are available at the 2-digit SIC code level. 

For each record in the non-EGU point source 1996 base year inventory, a link was established

between the State FIPS code, the SIC code, and the applicable BEA GSP growth factor. National

BEA GSP annual growth rates by industry are listed in Table III-1.

For fuel combustion sources, factors were applied to the 1996 base year emissions to account

for improvements in energy efficiency between 1996 and 2007, 2020, and 2030. These factors,

developed from the U.S. Department of Energy (DOE) publication Annual Energy Outlook 1999,

account for increases in fuel and process efficiency in future years (DOE, 1998). Basically, less

fuel will be needed to provide the same amount of energy (generally in the form of steam) to an

industrial process and the amount of energy needed per unit output will also decrease as

processes become more efficient. For example, DOE projects natural gas consumption in the

commercial sector to rise from 3.392 quadrillion Btu in 1996 to 3.997 quadrillion Btu in 2020. 

Over this same time-frame, DOE projects commercial building square footage to increase from

59.5 billion square feet to 72.9 billion square feet. To reflect the projected change in natural gas

consumed per square foot of commercial building space, natural gas energy intensity factors were

calculated for 1996 and each projection year. For example, 0.2475 quadrillion Btu/square foot of

natural gas is projected to be consumed in 2020 versus 0.2551 quadrillion Btu/square foot in

1996. For all commercial sector natural gas source categories, the BEA commercial sector

growth factors are multiplied by 0.97, which represents the ratio of the 2020 energy intensity

factor for commercial sector natural gas to the 1996 energy intensity factor for commercial

natural gas. Similar ratios were calculated and applied for other fuels used in the commercial

sector, and for all fuels used in the residential and industrial energy sectors. These adjustments

were based on those used in the NET inventory projections (EPA, 2000a).
III-3

Table III-1

BEA National GSP Growth Forecasts

Industry (SIC Code)

Annual Growth

(% per year)

1996 to 2007

Annual Growth

(% per year)

1996 to 2020

Annual Growth

(% per year)

1996 to 2030

All-Industry Total

Farm (01) 1.8 1.5 1.2

Nonfarm (02) 1.8 1.5 1.2

Agricultural services (07, 08, 09) 3.8 3.2 2.7

Mining (10, 12, 13, 14)

Metal mining (10) 3.2 2.7 2.3

Coal mining (12) 2.6 2.1 1.7

Oil and gas extraction (13) 0.1 0.2 0.3

Nonmetallic minerals (14) 1.3 1.2 1.1

Construction (15, 16, 17) 1.2 1.1 1.0

Manufacturing (20 - 39)

Durable goods

Lumber and wood products (24) 0.6 0.7 0.7

Furniture and fixtures (25) 1.6 1.4 1.3

Stone, clay, and glass products (32) 0.8 0.9 0.9

Primary metals (33) 0.4 0.5 0.5

Fabricated metals (34) 0.7 0.8 0.8

Industrial machinery (35) 3.3 2.6 2.1

Electronic equipment (36) 2.2 1.9 1.6

Motor vehicles and equipment (371) 1.1 1.0 1.0

Other transportation equipment (37,

excluding 371)

2.3 2.0 1.8

Instruments and related products (38) 1.3 1.3 1.3

Miscellaneous manufacturing (39) 1.8 1.6 1.4

Nondurable Goods

Food and kindred products (20) 1.2 1.1 1.1

Tobacco products (21) -3.0 -2.5 -2.2

Textile mill products (22) 1.1 1.0 1.0

Apparel and other textile products (23) 1.6 1.4 1.2

Paper products (26) 2.0 1.8 1.6

Printing and publishing (27) 0.6 0.7 0.7

Chemicals and allied products (28) 1.4 1.3 1.3

Petroleum and coal products (29) 1.1 1.1 1.1

Rubber and plastics products (30) 2.9 2.5 2.2

Leather and leather products (31) -0.1 -0.1 -0.1
Table III-1 (continued)

Industry (SIC Code)

Annual Growth

(% per year)

1996 to 2007

Annual Growth

(% per year)

1996 to 2020

Annual Growth

(% per year)

1996 to 2030

III-4

Transportation and Public Utilities (40 - 49)

Railroad transportation (40) 3.0 2.4 2.0

Local and interurban transit (41) 1.4 1.3 1.3

Trucking and warehousing (42) 2.1 1.8 1.6

Water transportation (44) 0.1 0.3 0.4

Transportation by air (45) 3.3 2.8 2.4

Pipelines (46) 1.0 0.9 0.8

Transportation services (47) 2.9 2.4 2.1

Communications (48) 2.8 2.4 2.1

Utilities (49) 1.9 1.7 1.5

Wholesale and Retail Trade (50 - 59)

Wholesale trade (50, 51) 2.4 2.1 1.8

Retail trade (52 - 59) 2.1 1.8 1.6

Finance, Insurance, and Real Estate (60 - 67)

Banks and investment (60, 61, 62, 67) 2.8 2.3 2.0

Insurance (63, 64) 1.8 1.7 1.6

Real estate (65) 2.0 1.8 1.6

Services (70 - 89)

Hotels and other lodging (70) 2.1 1.9 1.7

Personal services (72) 1.0 0.9 0.9

Business services (73) 2.9 2.4 2.0

Auto repair and parking (75) 1.7 1.5 1.3

Amusement (79) 2.9 2.4 2.1

Health services (80) 2.3 2.0 1.8

Legal services (81) 1.5 1.3 1.2

Educational services (82) 1.8 1.6 1.5

Social services (83) 2.8 2.3 2.0

Private households (88) 0.9 0.8 0.8

Other services (84, 86, 89) 2.7 2.3 2.0

Government

Federal, civilian 0.3 0.4 0.5

Federal, military -0.1 0.2 0.4

State and local 1.4 1.3 1.2

Population 0.9 0.8 0.8

SOURCE: Developed from BEA, 1995.
III-5

2. Control Assumptions

Since the base year inventory for this effort is 1996, reasonably available control technology

(RACT) requirements were assumed to have already been implemented. So, for stationary

sources, CAA controls include Federal initiatives as shown in Table III-2 for point sources. 

Maximum achievable control technology (MACT) controls were also included as shown in

Tables III-3 and III-4.

NOx emissions for the 23 States (22 States plus the District of Columbia) covered by the

NOx SIP Call were also reduced to reflect the NOx SIP Call requirements. The NOx SIP Call

controls were applied to the 2007 base case inventory. For the 2020 and 2030 base case

inventories, sources affected by the NOx SIP Call were capped at 2007 emission levels.

The NOx SIP Call was modeled by first identifying the sources in the 1996 NET inventory

which are large, and are within the source categories covered under the SIP Call. This procedure

was performed by first matching the non-EGU point sources in the 1996 NET inventory file with

the large sources in the NOx SIP Call data base. This was computer matching that required that

the numeric identifiers in each file be identical at the State, county, plant, and point level. After

this exercise was performed, there were 633 sources in the 1996 NET inventory that were

identified as large sources affected by the NOx SIP Call. Because this included less than 30

percent of the 2,216 large sources in the NOx SIP Call control region, additional steps were taken

to identify the remaining large, affected sources in the 1996 NET non-EGU point source file. 

These steps were applied separately to the four major source categories that are affected by the

SIP Call, as follows:

1. For boilers, all sources in the SIP Call-affected States with a boiler design capacity in

the 1996 NET file greater than or equal to 250 million British thermal units (MMBtu)

were deemed to be large sources.

2. For turbines, all sources in the SIP Call-affected States with a boiler design capacity in

the 1996 NET file greater than or equal to 250 MMBtu were tagged as large sources.

3. For IC engines, all sources with 1996 NOx emissions greater than 1 ton per day were

tagged as large sources.

4. For cement manufacturing, all sources with 1996 NOx emissions greater than 1 ton per

day were tagged as large sources.

Once the large sources were determined, the following percentages were applied according

to the source category affected:

Industrial Boilers 60%

Gas Turbines 60%

Internal Combustion Engines 90%

Cement Manufacturing 30%

Multiple estimates of NOx emissions were supplied in the modeling files for non-EGU point

sources to account for with and without SIP Call cases, and to reflect ozone versus non-ozone

season emission differences for the NOx controls expected to be operating only during the 5-
III-6

month ozone season. The typical SSD emission estimates incorporate the effects of NOx SIP

Call controls. Annual NOx emission estimates are the sum of 5-month ozone season NOx

emissions, plus 7-month (October-April) NOx emissions. Table III-5 shows the source types

affected by the NOx SIP Call and describes which controls were applied to each source type. For

the source categories that are affected by the NOx SIP Call, non-ozone season emissions were

estimated using the same control percentages listed above if the dominant source type for that

control device is expected to be one that provides year-round emission reductions. For seasonal

controls, such as selective catalytic reduction (SCR) or selective non-catalytic reduction (SNCR)

applications to industrial boilers and cement kilns, NOx controls were not applied during the 7-

month non-ozone season when NOx emissions were estimated. Table III-5 lists the primary NOx

control technology assumed for each category.

Table III-2

Point Source CAA Baseline Control Assumptions

Source Category Pollutant Control Efficiency (%)*

National Rules

Marine vessel loading: petroleum liquids VOC 80

Treatment, storage, and disposal facilities (TSDFs) VOC 96

Municipal solid waste landfills VOC 82

NOTE: *From uncontrolled levels.
III-7

Table III-3

Point Source MACT Control Assumptions

Source Category

VOC Control

Efficiency (%)*

Benzene National Emission Standards for Hazardous Air Pollutants (NESHAP) (national)

 By-product coke mfg 85

 By-product coke - flushing-liquor circulation tank 95

 By-product coke - excess-NH3 liquor tank 98

 By-product coke mfg. - tar storage 98

 By-product coke mfg. - light oil sump 98

 By-product coke mfg. - light oil dec/cond vents 98

 By-product coke mfg. - tar bottom final cooler 81

 By-product coke mfg. - naphthalene processing 100

 By-product coke mfg. - equipment leaks 83

 By-product coke manufacture - other 94

 By-product coke manufacture - oven charging 94

 Coke ovens - door and topside leaks 94

 Coke oven by-product plants 94

2-Year MACT (national)

Synthetic Organic Chemical Manufacturing Industry (SOCMI) Hazardous Organic NESHAP (HON)

– SOCMI processes 79

– Volatile organic liquid storage 95

– SOCMI fugitives (equipment leak detection and repair) 60

– SOCMI wastewater 0

– Ethylene oxide manufacture 98

– Phenol manufacture 98

– Acrylonitrile manufacture 98

– Polypropylene manufacture 98

– Polyethylene manufacture 98

– Ethylene manufacture 98

Dry Cleaning

– Perchloroethylene 95

– Other 70

4-Year MACT (national)

TSDFs (offsite waste operations) 96

Shipbuilding and repair 24

Polymers and resins II 78

Polymers and resins IV 70

Styrene-butadiene rubber manufacture (polymers & resins group I) 70

Wood furniture surface coating 30

Aircraft surface coating (aerospace) 60

Petroleum Refineries: other sources

– Fixed roof petroleum product tanks 98

– Fixed roof gasoline tanks 96

– External floating roof petroleum product tanks 90

– External floating roof gasoline tanks 95

– Petroleum refinery wastewater treatment 72

– Petroleum refinery fugitives 72

– Petroleum refineries - Blowdown w/o control 78

– Vacuum distillation 72
Table III-3 (continued)

Source Category

VOC Control

Efficiency (%)*

III-8

Halogenated Solvent Cleaners

– Open top degreasing - halogenated 63

– In-line (conveyorized) degreasing - halogenated 39

Printing

– Flexographic 32

– Gravure 27

Gasoline Marketing

– Storage 5

– Splash loading 99

– Balanced loading 87

– Submerged loading 99

– Transit 5

– Leaks 39

7/10-Year MACT (national)

Paint and varnish manufacture 35

Rubber tire manufacture 70

Green tire spray 90

Automobile surface coating 79

Beverage can surface coating 57

Paper surface coating 78

Flatwood surface coating 90

Fabric printing 80

Metal surface coating 90

Plastic parts surface coating 45

Pulp and paper production 70

Agricultural chemical production 79

Pharmaceutical production 79

Polyesters 70

Fabric coating 70

Petroleum refineries - fluid catalytic cracking 70

Oil and natural gas production 90

Explosives 70

Plywood/particle board 70

Reinforced plastics 70

Publicly-Owned Treatment Works (POTWs) 70

Phthalate plasticizers 70

Polymers and resins III 78

Rayon production 70

Polyvinyl chloride 70

Spandex production 70

Nylon 6 production 70

Alkyd resins 70

Polyester resins 70

Chelating agents 70

NOTE: *From uncontrolled levels.
III-9

Table III-4

Non-VOC Related MACT Assumptions

Source Category Pollutant Percentage Reduction (%)*

Municipal Waste Combustors PM

SO2

30

50

Cement Manufacturing PM 90

Secondary Aluminum PM 90

Medical Waste Incineration PM

NOx

SO2

88

20

20

Hazardous Waste Incineration PM 36

NOTE: *From uncontrolled levels.
III-10

Table III-5

NOx SIP Call Control Application

Source Type Description NOx Control Cost Pod Number Cost Pod Name Co

Year-round application

Industrial Boilers (non-coal) LNB and LNB plus flue gas

recirculation

151617414243

ICI BoilersICI BoilersICI BoilersICI BoilersICI BoilersICI Boilers

ReDiNaPrCoLP

Turbines LNB plus water injection 23

2450

Gas TurbinesGas TurbinesGas Turbines

OiNaJe

Cement Kilns (wet) Mid-kiln firing 34 Cement Mfg. (wet) NA

Reciprocating IC Engines Low emission combustion 21

2246

IC EnginesIC EnginesIC Engines

OiGaGa

Cement Kilns (dry) Mid-kiln firing 33 Cement Mfg. (dry) NA

5-month ozone season application

Industrial Boilers (coal) SCR or SNCR 11

121314

ICI BoilersICI BoilersICI BoilersICI Boilers

CoCoCoCo

Cement Kilns (coal) SCR or SNCR 81 Cement Kiln Co

Notes: LNB = low-NOx burners; ICI = industrial, commercial, and institutional; LPG = liquified petroleum gas; NA = not applicable; 

SCR = selective catalytic reduction; and SNCR = selective non-catalytic reduction.
III-11

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT FILES

Three new variables were added to the structures of the mass emissions inventories. Unique

5 character IDs for plant and point, and unique 3 character IDs for stack were added to facilitate

the transition from mass to emissions processor input files. Table III-6 documents the names of

the non-EGU mass and emissions processor input files.

1. Mass Emission Inventories

The structures for the mass emission inventories are detailed in Tables III-7 and III-8, as the

base year and future year inventories differed. Data elements included in the base year inventory

and excluded from the future year inventories include the pollutant emission factor (-EMF),

primary control equipment code (-CPRI), and secondary control equipment code (-CSEC).

2. EPS 2.5 Emissions Processor Input Files

The EPS 2.5 emissions processor input file structure is detailed in Table III-9. Input files for

EPS 2.5 limit the width of plant and point IDs to 5 characters, so the unique 5-character IDs were

used in the EPS 2.5 input files. The unique 3-character IDs for stack were also used because of

limitations on the data field width for stack ID. 

3. EMS-95 Emissions Processor Input Files

The EMS-95 emissions processor input files include typical SSD VOC, NOx, and CO

emissions for ozone modeling. The EMS-95 input file structure is detailed in Table III-10. 

Universal Transverse Mercator (UTM) coordinates were added to the EMS-95 input files to

account for input requirements of the model. The future year emissions files contain the effects

of the NOx SIP Call control requirements since only SSD emissions are provided in the EMS-95

input files.

A weekly profile code of 8 was utilized for all non-EGU sources, consistent with files

prepared for the NOx SIP Call analysis. This assumes operation 7 days a week, with slightly

lower utilization on the weekends.
III-12

Table III-6

Non-EGU Point Source Mass and Emissions Processor Input Files

Year Mass EPS 2.5 EMS-95 Comments1996 PT96MS2H.DBF PT96EP1H.TXT PT96EM1H.TGZ2007 PT7MS1H1.DBF Excludes NOx SIP Call Controls.

PT07MS2H.DBF PT07EP2H.TXT PT07EM2H.TGZ Includes typical summer season day (SSD), 5-month, 

emissions. SSD and 5-month emissions include NOx S

Annual emissions are sum of 5- and 7-month emission

2020 PT2MS1H1.DBF Excludes NOx SIP Call Controls.

PT2MS2H2.DBF PT2EP2H2.TXT PT2EM2H2.TGZ Includes typical SSD, 5-month, 7-month, and annual e

5-month emissions include NOx SIP Call controls. Ann

of 5- and 7-month emissions.

2030 PT3MS1H1.DBF Excludes NOx SIP Call Controls.

PT3MS2H2.DBF PT3EP2H2.TXT PT3EM2H2.TGZ Includes typical SSD, 5-month, 7-month, and annual e

5-month emissions include NOx SIP Call controls. Ann

of 5- and 7-month emissions.
III-13

Table III-7

Structure for 1996 Base Year Non-EGU Mass Emissions File

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 15 0 State Plant ID

POINTID C 15 0 Point ID

STACKID C 12 0 Stack ID

SEGMENT C 2 0 Segment ID

ORISID C 6 0 DOE Plant ID

BLRID C 6 0 Boiler ID

PLANT C 40 0 Plant Name

SCC C 10 0 SCC

UTMEAST N 9 3 UTM easting (km)

UTMNORTH N 9 3 UTM northing (km)

UTMZONE N 9 3 UTM zone

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

STKVEL N 9 2 Stack Velocity (ft/sec)

BOILCAP N 8 2 Boiler Design Capacity (MMBtu/hour)

CAP_UNITS C 1 0 Capacity Unit Code

WINTHRU N 3 0 Winter Thruput (%)

SPRTHRU N 3 0 Spring Thruput (%)

SUMTHRU N 3 0 Summer Thruput (%)

FALTHRU N 3 0 Fall Thruput (%)

HOURS N 2 0 Hours per Day

START_HR N 2 0 Hourly Start Time

DAYS N 1 0 Days per Week

WEEKS N 2 0 Weeks per Year

THRUPUT N 11 1 Throughput Rate (SCC units/year)

MAXRATE N 12 3 Maximum Ozone Season Rate (units/day)

HEATCON N 8 2 Heat Content (MMBtu/SCC unit)

SULFCON N 5 2 Sulfur Content (mass percent)

ASHCON N 5 2 Ash Content (mass percent)

NETDC N 9 3 Maximum Nameplate Capacity (MW)

SIC N 4 0 SIC Code

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

VOC_EMF N 11 4 VOC Emission Factor (SCC units)

NOX_EMF N 11 4 NOx Emission Factor (SCC units)

CO_EMF N 11 4 CO Emission Factor (SCC units)

SO2_EMF N 11 4 SO2 Emission Factor (SCC units)

PM10_EMF N 11 4 PM10 Emission Factor (SCC units)

PM25_EMF N 11 4 PM2.5 Emission Factor (SCC units)

NH3_EMF N 11 4 NH3 Emission Factor (SCC units)

VOC_CE N 7 2 VOC Control Efficiency (%)

NOX_CE N 7 2 NOx Control Efficiency (%)

CO_CE N 7 2 CO Control Efficiency (%)

SO2_CE N 7 2 SO2 Control Efficiency (%)
Table III-7 (continued)

Variable Type Length Decimals Description

III-14

PM10_CE N 7 2 PM10 Control Efficiency (%)

PM25_CE N 7 2 PM2.5 Control Efficiency (%)

NH3_CE N 7 2 NH3 Control Efficiency (%)

VOC_CPRI N 3 0 VOC Primary Control Equipment Code

NOX_CPRI N 3 0 NOx Primary Control Equipment Code

CO_CPRI N 3 0 CO Primary Control Equipment Code

SO2_CPRI N 3 0 SO2 Primary Control Equipment Code

PM10_CPRI N 3 0 PM10 Primary Control Equipment Code

PM25_CPRI N 3 0 PM2.5 Primary Control Equipment Code

NH3_CPRI N 3 0 NH3 Primary Control Equipment Code

VOC_CSEC N 3 0 VOC Secondary Control Equipment Code

NOX_CSEC N 3 0 NOx Secondary Control Equipment Code

CO_CSEC N 3 0 CO Secondary Control Equipment Code

SO2_CSEC N 3 0 SO2 Secondary Control Equipment Code

PM10_CSEC N 3 0 PM10 Secondary Control Equipment Code

PM25_CSEC N 3 0 PM2.5 Secondary Control Equipment Code

NH3_CSEC N 3 0 NH3 Secondary Control Equipment Code

VOC_ANN N 13 4 Annual VOC (tons)

NOX_ANN N 13 4 Annual NOx (tons)

CO_ANN N 13 4 Annual CO (tons)

SO2_ANN N 13 4 Annual SO2 (tons)

PM10_ANN N 13 4 Annual PM10 (tons)

PM25_ANN N 13 4 Annual PM2.5 (tons)

SOA_ANN N 13 4 Annual SOA (tons)

NH3_ANN N 13 4 Annual NH3 (tons)

VOC_OSD N 13 4 Summer Season Daily VOC (tons)

NOX_OSD N 13 4 Summer Season Daily NOx (tons)

CO_OSD N 13 4 Summer Season Daily CO (tons)

SO2_OSD N 13 4 Summer Season Daily SO2 (tons)

PM10_OSD N 13 4 Summer Season Daily PM10 (tons)

PM25_OSD N 13 4 Summer Season Daily PM2.5 (tons)

SOA_OSD N 13 4 Summer Season Daily SOA (tons)

NH3_OSD N 13 4 Summer Season Daily NH3 (tons)

VOC_RE N 3 0 VOC Rule Effectiveness (%)

NOX_RE N 3 0 NOx Rule Effectiveness (%)

CO_RE N 3 0 CO Rule Effectiveness (%)

SO2_RE N 3 0 SO2 Rule Effectiveness (%)

PM10_RE N 3 0 PM10 Rule Effectiveness (%)

PM25_RE N 3 0 PM2.5 Rule Effectiveness (%)

NH3_RE N 3 0 NH3 Rule Effectiveness (%)

STACKID3 C 3 0 Stack ID (3 Digit)

PLANTID5 C 5 0 State Plant ID (5 Digit)

POINTID5 C 5 0 Point ID (5 Digit)
III-15

Table III-8

Structure for 2007, 2020, and 2030 Future Year Non-EGU Mass Emissions Files

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 15 0 State Plant ID

POINTID C 15 0 Point ID

STACKID C 12 0 Stack ID

SEGMENT C 2 0 Segment ID

PLANTID5 C 5 0 State Plant ID (5 Digit)

POINTID5 C 5 0 Point ID (5 Digit)

STACKID3 C 3 0 Stack ID (3 Digit)

ORISID C 6 0 DOE Plant ID

BLRID C 6 0 Boiler ID

PLANT C 40 0 Plant Name

SCC C 10 0 SCC

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (degrees F)

STKFLOW N 10 2 Stack Flow Rate (cubic feet per second)

STKVEL N 9 2 Stack Velocity (ft/sec)

BOILCAP N 8 2 Boiler Design Capacity

CAP_UNITS C 1 0 Capacity Unit Code

WINTHRU N 3 0 Winter Thruput (%)

SPRTHRU N 3 0 Spring Thruput (%)

SUMTHRU N 3 0 Summer Thruput (%)

FALTHRU N 3 0 Fall Thruput (%)

HOURS N 2 0 Hours per Day

START_HR N 2 0 Hourly Start Time

DAYS N 1 0 Days per Week

WEEKS N 2 0 Weeks per Year

THRUPUT N 11 1 Throughput Rate (SCC units/year)

MAXRATE N 12 3 Maximum Ozone Season Rate (units/day)

HEATCON N 8 2 Heat Content (MMBtu/SCC unit)

SULFCON N 5 2 Sulfur Content (mass percent)

ASHCON N 5 2 Ash Content (mass percent)

NETDC N 9 3 Maximum Nameplate Capacity (MW)

SIC N 4 0 SIC Code

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

UTMEAST N 9 3 UTM easting (km)

UTMNORTH N 9 3 UTM northing (km)

UTMZONE N 9 3 UTM zone

VOC_EMF N 11 4 VOC Emission Factor (SCC units)

NOX_EMF N 11 4 NOx Emission Factor (SCC units)

CO_EMF N 11 4 CO Emission Factor (SCC units)
Table III-8 (continued)

Variable Type Length Decimals Description

III-16

SO2_EMF N 11 4 SO2 Emission Factor (SCC units)

PM10_EMF N 11 4 PM10 Emission Factor (SCC units)

PM25_EMF N 11 4 PM2.5 Emission Factor (SCC units)

NH3_EMF N 11 4 NH3 Emission Factor (SCC units)

VOC_CE N 7 2 VOC Control Efficiency (%)

NOX_CE N 7 2 NOx Control Efficiency (%)

CO_CE N 7 2 CO Control Efficiency (%)

SO2_CE N 7 2 SO2 Control Efficiency (%)

PM10_CE N 7 2 PM10 Control Efficiency (%)

PM25_CE N 7 2 PM2.5 Control Efficiency (%)

NH3_CE N 7 2 NH3 Control Efficiency (%)

VOC_CPRI N 3 0 VOC Primary Control Equipment Code

NOX_CPRI N 3 0 NOx Primary Control Equipment Code

CO_CPRI N 3 0 CO Primary Control Equipment Code

SO2_CPRI N 3 0 SO2 Primary Control Equipment Code

PM10_CPRI N 3 0 PM10 Primary Control Equipment Code

PM25_CPRI N 3 0 PM2.5 Primary Control Equipment Code

NH3_CPRI N 3 0 NH3 Primary Control Equipment Code

VOC_CSEC N 3 0 VOC Secondary Control Equipment Code

NOX_CSEC N 3 0 NOx Secondary Control Equipment Code

CO_CSEC N 3 0 CO Secondary Control Equipment Code

SO2_CSEC N 3 0 SO2 Secondary Control Equipment Code

PM10_CSEC N 3 0 PM10 Secondary Control Equipment Code

PM25_CSEC N 3 0 PM2.5 Secondary Control Equipment Code

NH3_CSEC N 3 0 NH3 Secondary Control Equipment Code

VOC_ANN N 13 4 Annual VOC (tons)

NOX_ANN N 13 4 Annual NOx (tons)

CO_ANN N 13 4 Annual CO (tons)

SO2_ANN N 13 4 Annual SO2 (tons)

PM10_ANN N 13 4 Annual PM10 (tons)

PM25_ANN N 13 4 Annual PM2.5 (tons)

SOA_ANN N 13 4 Annual SOA (tons)

NH3_ANN N 13 4 Annual NH3 (tons)

VOC_OSD N 13 4 Summer Season Daily VOC (tons)

NOX_OSD N 13 4 Summer Season Daily NOx (tons)

CO_OSD N 13 4 Summer Season Daily CO (tons)

SO2_OSD N 13 4 Summer Season Daily SO2 (tons)

PM10_OSD N 13 4 Summer Season Daily PM10 (tons)

PM25_OSD N 13 4 Summer Season Daily PM2.5 (tons)

SOA_OSD N 13 4 Summer Season Daily SOA (tons)

NH3_OSD N 13 4 Summer Season Daily NH3 (tons)

NOX_5MON N 13 4 5-month Summer NOx, May-September (tons)

NOX_7MON N 13 4 7-month NOx, October-April (tons)

VOC_RE N 3 0 VOC Rule Effectiveness (%)
Table III-8 (continued)

Variable Type Length Decimals Description

III-17

NOX_RE N 3 0 NOx Rule Effectiveness (%)

CO_RE N 3 0 CO Rule Effectiveness (%)

SO2_RE N 3 0 SO2 Rule Effectiveness (%)

PM10_RE N 3 0 PM10 Rule Effectiveness (%)

PM25_RE N 3 0 PM2.5 Rule Effectiveness (%)

NH3_RE N 3 0 NH3 Rule Effectiveness (%)

POD_VOC C 3 0 VOC Cost Pod

ERAT N 9 3 Energy Adjustment Factor

GFAC N 9 3 BEA Growth Factor

SIPSIZE C 1 0 Plant Size Based on NOx SIP Call

POD_NOX C 3 0 NOx Cost Pod

POD C 3 0 Cost Pod

SIC2 C 3 0 2-digit SIC Code

SIZE C 1 0 Plant Size Based on Capacity or Emission (see text)
III-18

Table III-9

Non-EGU EPS 2.5 Emissions Processor Input File Structure

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

PLANTID C 5 0 State Plant ID (5 digit)

POINTID C 5 0 Point ID (5 digit)

SIC N 4 0 SIC Code

STACKID C 3 0 Stack ID (3 digit)

SEGMENT C 2 0 Segment ID

SCC C 8 0 SCC

STKHGT N 4 0 Stack Height (ft)

STKDIAM N 6 2 Stack Diameter (ft)

STKTEMP N 4 0 Stack Temperature (F)

STKFLOW N 10 2 Stack Flow Rate (cubic ft per second)

WINTHRU N 3 0 Winter Thruput (%)

SPRTHRU N 3 0 Spring Thruput (%)

SUMTHRU N 3 0 Summer Thruput (%)

FALTHRU N 3 0 Fall Thruput (%)

HOURS N 2 0 Hours per Day

DAYS N 1 0 Days per Week

WEEKS N 2 0 Weeks per Year

LATC N 9 4 Latitude (degrees)

LONC N 9 4 Longitude (degrees)

VOC N 9 3 Annual VOC (tons)

NOX N 9 3 Annual NOx (tons)

CO N 9 3 Annual CO (tons)

SO2 N 9 3 Annual SO2 (tons)

PM10 N 9 3 Annual PM10 (tons)

PM25 N 9 3 Annual PM2.5 (tons)

SOA N 9 3 Annual SOA (tons)

NH3 N 9 3 Annual NH3 (tons)
III-19

Table III-10

Non-EGU EMS-95 Emissions Processor Input File Structure

Field Type Length Description

Facility File:

STID N 2. FIPS State Code

CYID N 3. FIPS County Code

FCID C 15. Facility ID

SIC C 4. Standard Industrial Classification

UTMX N 9.1 UTM easting (m)

UTMY N 9.1 UTM northing (m)

UTMZ N 2. UTM zone

NAME C 40. Facility Name

Stack File:

STID N 2. FIPS State Code

CYID N 3. FIPS County Code

FCID C 15. Facility ID

STKID C 12. Stack ID

DIAM N 8.4 Inside Stack Diameter (ft)

HEIT N 7.2 Stack Height above Ground Surface (ft)

TEMP N 7.2 Stack Exit Temperature (F)

VELOC N 7.2 Stack Exit Velocity (ft/sec)

FLOW N 10.2 Stack Exit Flow Rate (actual cubic ft/min)

UTMX N 9.1 UTM easting (m)

UTMY N 9.1 UTM northing (m)

ELEV N 9.1 Elevation of Stack Base from Mean Sea Level (ft)

Device File:

STID N 2. FIPS State Code

CYID N 3. FIPS County Code

FCID C 15. Facility ID

STKID C 12. Stack ID

DVID C 12. Device ID

SIC C 4. Standard Industrial Classification

DEC N 5.3 Fractional December Throughput

JAN N 5.3 Fractional January Throughput

FEB N 5.3 Fractional February Throughput

MAR N 5.3 Fractional March Throughput

APR N 5.3 Fractional April Throughput

MAY N 5.3 Fractional May Throughput

JUN N 5.3 Fractional June Throughput

JUL N 5.3 Fractional July Throughput

AUG N 5.3 Fractional August Throughput

SEP N 5.3 Fractional September Throughput

OCT N 5.3 Fractional October Throughput

NOV N 5.3 Fractional November Throughput

WIN N 3. Winter Throughput (Dec - Feb) (%)

SPR N 3. Spring Throughput (Mar - May) (%)
Table III-10 (continued)

Field Type Length Description

III-20

SUM N 3. Summer Throughput (Jun - Aug) (% )

FAL N 3. Fall Throughput (Sep - Nov) (%)

HOURS N 2. Hours of Operation per Day (hours/day)

DAYS N 2. Days of Operation per Week (days/week)

WEEKS N 2. Weeks of Operation per Year (weeks/year)

DAYYEAR N 3. Days of Operation per Year (days/year)

HOURYEAR N 4. Hours of Operation per Year (hours/year)

Process File:

STID N 2. FIPS State Code

CYID N 3. FIPS County Code

FCID C 15. Facility ID

STKID C 12. Stack ID

DVID C 12. Device ID

PRID C 12. Process ID

SCC C 8. Source Classification Code

PRRT N 13. Annual Process Rate (SCC units/year)

PRUN C 15. Optional Process Rate Units If Different from SCC

Emissions File:

STID N 2. FIPS State Code

CYID N 3. FIPS County Code

FCID C 15. Facility ID

STKID C 12. Stack ID

DVID C 12. Device ID

PRID C 12. Process ID

POLID C 5. Pollutant ID

ACEF N 13. Actual Emission Factor (tons/SCC units)

ALEF N 13. Allowable Emission Factor (tons/SCC units)

ACEE N 13. Actual Emissions (tons)

ALEE N 13. Allowable Emissions (tons)

ESTT C 2. Temporal Basis (AA, AD, or DS)

PCEC C 5. Primary Control Equipment

SCEC C 5. Secondary Control Equipment

CEEF N 7.4 Control Equipment Efficiency (%)
IV-1

CHAPTER IV

STATIONARY AREA SOURCES

A. 1996 BASE YEAR EMISSIONS

The 1996 base year inventory for stationary area sources is the 1996 NET area source

inventory Version 3.11 (EPA, 2000a). Version 3.11 is the most current version that reflects

corrections to wildfire emission estimates for Kansas and removal of area source electric utility

emissions to avoid double counting with point source EGU emissions. SOA emissions were

added to the inventory by applying fractional aerosol coefficients based on speciation of VOC

emissions (Grosjean and Seinfeld, 1989).

B. 2007, 2020, AND 2030 FUTURE YEAR EMISSIONS

Projection year emissions are a function of projected changes (growth or decline) in activity

as well as changes in control levels. The following sections describe the growth and control

assumptions utilized for this analysis.

1. Growth Assumptions

The BEA GSP growth, including population and combinations of industries (e.g., durable

goods manufacturing, total manufacturing) were used to project emissions from 1996 to 2007,

2020, and 2030 for the area source sector. The surrogates used for each category were based on

the same cross-reference list used in the Ozone/PM National Ambient Air Quality Standard

(NAAQS) analysis (Pechan-Avanti, 1997b). Updated non-BEA growth factors were applied to

estimate future year activity for prescribed burning (projections of acres of public land burned

from EPA and Federal land managers), agricultural sources (acres planted projections), and

unpaved road emissions based on work completed for EPA’s Section 812 Prospective Analysis

(Pechan-Avanti, 1998). Livestock emissions growth was also updated for this analysis, utilizing

exptrapolations of Census of Agriculture data.

Pechan matched area source categories with surrogate activity indicators (e.g., GSP by

industry, population, or broader BEA categories) in order to utilize the BEA data. The variable

chosen as a proxy for emissions growth is shown by source category in Table IV-1. For broad

industrial categories such as Industrial Fuel Combustion and Miscellaneous Industrial Processes,

BEA GSP growth for the manufacturing sector represents the activity level for projecting

emissions. Population was used as a surrogate growth indicator for area source categories such

as Dry Cleaning, Household Solvent Use, and Residential Fuel Combustion. Projected emissions

for each State/area source SCC combination were calculated by multiplying base year emissions

by the growth factor for the BEA growth indicator.
IV-2

Table IV-1

BEA Growth Categories Assigned by Major Source Category: Area Sources

Source Category BEA Growth Category*

Stationary Source Fuel Combustion:

Industrial Total Manufacturing

Commercial/Institutional Government and Government Enterprises

Residential Population

Industrial Processes:

Process Emissions: Synthetic Fiber Textile Mill Products (SIC 22)

Process Emissions: Pharmaceuticals Chemicals and Allied Products (SIC 28)

SOCMI Fugitives Chemicals and Allied Products (SIC 28)

Food & Kindred Products - Bakeries Food and Kindred Products (SIC 20)

Petroleum Refining Petroleum and Coal Products (SIC 29)

Oil & Gas Production Oil and Gas Extraction (SIC 13)

Miscellaneous Industrial Processes Total Manufacturing

Surface Coating:

Architectural Construction (SIC 15, 16, and 17)

Auto Refinishing Auto Repair, Services, and Garages (SIC 75)

Traffic Markings Construction (SIC 15, 16, and 17)

Flat Wood Coating Lumber and Wood Products (SIC 24)

Wood and Metal Furniture Furniture and Fixtures (SIC 25)

Paper Coating Printing and Publishing (SIC 27)

Metal Can & Coating Fabricated Metal Products (SIC 34)

Electrical Insulation Machinery, except Electrical (SIC 35)

Appliances Fabricated Metal Products (SIC 34)

Machinery Electric and Electronic Equipment (SIC 36)

Motor Vehicles (New) Motor Vehicles and Equipment (SIC 371)

Aircraft Coating Transportation Equipment, excl. Motor Vehicles (SIC 37)

Marine Paints Transportation Equipment, excl. Motor Vehicles (SIC 37)

Rail Equipment Coating Transportation Equipment, excl. Motor Vehicles (SIC 37)

Miscellaneous Manufacturing Misc. Manufacturing Industries (SIC 39)

Industrial Maintenance Misc. Manufacturing Industries (SIC 39)

Aerosols, Specific Purpose Misc. Manufacturing Industries (SIC 39)

Degreasing (Vapor and Cold Cleaning):

Furniture Manufacturing - Durable Goods

Metallurgical Process Manufacturing - Durable Goods

Fabricated Metals Manufacturing - Durable Goods

Industrial Machinery Manufacturing - Durable Goods

Electrical Equipment Manufacturing - Durable Goods

Transportation Equipment Manufacturing - Durable Goods

Instrument Manufacturing Manufacturing - Durable Goods

Miscellaneous Manufacturing Manufacturing - Durable Goods

Automobile Dealers & Repair Manufacturing - Durable Goods

Other Degreasing Sources Manufacturing - Durable Goods
Table IV-1 (continued)

Source Category BEA Growth Category*

IV-3

Solvent Use:

Dry Cleaning (all types) Population

Graphic Arts Printing and Publishing (SIC 27)

Rubber and Plastics Rubber and Misc. Plastics Products (SIC 30)

Industrial Adhesives Total Manufacturing

Cutback Asphalt Local/Interurban Passenger Transit (SIC 41)

Pesticides - Farm Population

Personal, Household and Automotive Products Population

Commercial Adhesives Population

Petroleum & Petroleum Product Storage & Transport:

Bulk Stations/Terminals Trucking and Warehousing (SIC 42)

Gasoline Service Stations (Stage I and II) Gasoline Consumption**

Gasoline Service Stations (Underground Tank) Gasoline Consumption**

Waste Disposal, Treatment, & Recovery:

On-Site Incineration - Industrial Total Manufacturing

On-Site Incineration - Commercial/Institutional Government and Government Enterprises

On-Site Incineration - Residential Population

Open Burning - Industrial Total Manufacturing

Open Burning - Commercial/Institutional Government and Government Enterprises

Open Burning - Residential Population

Wastewater Treatment - Public Owned Electric, Gas, and Sanitary Services (SIC 49)

TSDFs Total Manufacturing

Miscellaneous Area Sources:

Agriculture Production (field burning, tilling) USDA - Agricultural Baseline Projections

Agricultural Livestock Extrapolated from historical Census of Agriculture data

Prescribed burning Reflects expected increases in Federal prescribed burning

activity on public lands

Wildfires Zero Growth

Unpaved Roads Extrapolated from 1984 to 1996 trend in unpaved road

mileage

Paved Roads Vehicle miles traveled (VMT) from MOBILE4.1 Fuel

Consumption Model (FCM)

NOTES: *BEA growth category refers to GSP projections for each industry, unless “Population” is indicated.

**Gasoline consumption projections are from the MOBILE FCM.
IV-4

The U.S. Department of Agriculture (USDA) has developed baseline projections of farm

acres planted (USDA, 1998). These data, combined with historical data back to 1990, for eight

major crop types shows an expected average annual growth of only 0.38 percent per year from

1990 to 2007. The BEA GSP projections for farms result in an annual average growth of

2.0 percent per year. Projections of acres planted represent better predictors of future activity

than GSP for agricultural tilling, so they were used in this analysis. Levels of acres planted were

assumed to remain constant between 2010 and 2030.

During an interagency (Department of the Interior/USDA) satellite conference held in April

1998, public forest land managers discussed an annual prescribed burning target of 5 million

acres for 2010, although specific areas for burning were not identified. Using this target figure,

public land activity levels were projected to arrive at 2010 public land activity estimates. For

private forest lands, it is estimated that the level of prescribed burning activity remains constant

at base year levels. Estimates for 2020 and 2030 were assumed to be the same as 2010. For

2007, data were extrapolated between 2000 and 2010.

Unpaved road emission projections reflect the historical downward trend in miles of

unpaved roads. The States were divided into three geographic groups: East, Central, and West. 

East was defined as EPA Regions 1 through 4, Central as EPA Regions 5 through 8, and West as

EPA Regions 9 and 10. Linear regression was used to estimate the continued decline in unpaved

road miles to 2030. For the emission projections, 2007 and 2030 unpaved road emissions were

estimated by applying the average annual change between 1984 and 1996 out to the projection

year.

For fuel combustion sources, energy adjustment factors were also applied to the baseline

inventory. These factors, developed from the DOE publication Annual Energy Outlook 1999,

account for increases in fuel and process efficiency in future years (DOE, 1998). Basically, less

fuel will be needed to provide the same amount of energy (generally in the form of steam) to an

industrial process and the amount of energy needed per unit output will also decrease as

processes become more efficient. For example, DOE projects natural gas consumption in the

commercial sector to rise from 3.392 quadrillion Btu in 1996 to 3.997 quadrillion Btu in 2020. 

Over this same time-frame, DOE projects commercial square footage to increase from 59.5

billion square feet to 72.9 billion square feet. To reflect the projected change in natural gas

consumed per square foot of commercial building space, natural gas energy intensity factors were

calculated for 1996 and each projection year. For example, 0.2475 quadrillion Btu/square foot of

natural gas is projected to be consumed in 2020 versus 0.2551 quadrillion Btu/square foot in

1996. For all commercial sector natural gas source categories, the BEA commercial sector

growth factors are multiplied by 0.97, which represents the ratio of the 2020 energy intensity

factor for commercial sector natural gas to the 1996 energy intensity factor for commercial

natural gas. Similar ratios were calculated and applied for other fuels used in the commercial

sector, and for all fuels used in the residential and industrial energy sectors. These adjustments

are based on those used in the NET projections (EPA, 2000a).

For the animal husbandry SCCs displayed in Table IV-2, alternative methods were used to

project emissions growth. For the majority of these SCCs (all except SCCs 2805001000,

2805020000, and 2805025000), emissions growth was based on projections of the number of
IV-5

animals in each category that were developed based on national data from the 1987, 1992, and

1997 Census of Agriculture (USDA, 1997). For these SCCs, growth factors are based on the

increase in the number of animals between the base year and 2007, 2020, and 2030 as estimated

from linear extrapolations of the Census data. Because linear extrapolation of the Census’

number of sheep and lambs yielded negative growth factors that were believed to be unrealistic,

the number of these animals was projected using an exponential trend function that provided

more realistic growth factors. The growth factor for total livestock production

(SCC 2805000000) was computed as the median of the growth factors for the individual SCCs

that comprise this total category.

For the following three animal husbandry source categories, growth factors were based on

more comprehensive historical and projections data available from the USDA:

• Beef Cattle Feedlots (SCC 2805001000);

• Total Cattle/Calves (SCC 2805020000); and

• Hogs and Pigs (SCC 2805025000).

For this effort, animal population data specific to each of these source categories were compiled

for 1970-1999. The USDA publishes estimates of the total number of cattle/calves; total number

of hogs and pigs; and total cattle in feedlots for historical years (USDA, 2000a). The USDA also

projects the inventory of total cattle, total beef cows, and total hogs for each year over the

1998-2009 period (USDA, 2000b). It is important to note that the categories included in the

USDA projections series do not match the emission source categories as closely as the categories

in the USDA historical data series. For example, USDA projections are available for total beef

cows, not cattle in feedlots.

Because the USDA projections data represent somewhat different animal categories than the

emission source categories and available historical data, the future animal counts were

normalized on the same basis as the historic animal counts by computing the ratio of a source

category’s animal count in each future year to the animal count for 1999 as reported in the

USDA’s projections series. To estimate the future number of animals in each source category,

these ratios are applied to the actual animal count for 1999, which is the latest year for which

USDA historical data are available.

After projecting these animal counts through 2009, the historical and forecast series for each

source category were graphed to determine the functional form that best represented the data. 

Because the major fluctuations in the historical data for each category contradicted the clear trend

in the USDA projection series for each category, the post-2009 trend in each category was

identified based on the normalized projected animal counts for 2000-2009. The 2020 and 2030

animal counts were estimated by extrapolating to each year based on the following functional

forms identified from the 2000-2009 data:

• Beef Cattle Feedlots–linear (stable slow decline in number);

• Total Cattle/Calves–linear (stable slow increase in number); and

• Hogs and Pigs–logarithmic (declining rate of increase in number).
IV-6

To compute the growth factors for each source category, the estimated animal counts in 2007,

2020, and 2030 were divided by the actual animal counts in 1996.

Table IV-2

Animal Husbandry Categories and Growth Assumptions

Source Classification

Code (SCC) SCC Description Growth Function

2710020030 Natural Sources Biogenic Horses and Ponies Linear extrapolation

2805000000 Misc. Area Sources Agric. Prod.-Livestock Total Median of growth factors from

individual SCCs below

2805001000 Misc. Area Sources Agric. Prod. - Livestock Beef

Cattle Feedlots Total

Linear extrapolation

2805020000 Misc. Area Sources Agric. Prod. - Animal

Husbandry Cattle and Calves Composite

Linear extrapolation

2805025000 Misc. Area Sources Agric. Prod. - Animal

Husbandry Hogs and Pigs Composite

Logarithmic extrapolation

2805030000 Misc. Area Sources Agric. Prod. - Animal

Husbandry Poultry -Chickens Composite

Linear extrapolation

2805040000 Misc. Area Sources Agric. Prod. - Animal

Husbandry Sheep and Lambs Composite

Exponential extrapolation

2805045001 Misc. Area Sources Agric. Prod. - Animal

Husbandry Goats Composite

Linear extrapolation

Reference: USDA, 1997.

2. Control Assumptions

VOC area source controls were applied for federal initiatives, such as VOC content limits for

consumer solvents, Title III MACT assumptions, and Title I RACT assumptions that were not

applied in the 1996 base year inventory. These controls are listed in Table IV-3. 

Additional controls were applied for residential wood combustion and Stage II VOC for

gasoline service stations. Table IV-4 shows the control efficiencies applied for residential wood

combustion by pollutant (VOC, PM10, PM2.5, and CO) for each of the future year inventories. 

Residential wood combustion control efficiencies were derived from emission factors obtained

from AP-42, a 4 percent per year growth rate for catalytic wood stoves starting in 1988, and an

estimate of the control efficiencies applied in the 1996 base year inventory. 

Table IV-5 shows the control efficiencies applied to account for VOC reductions associated

with onboard vapor recovery systems and Stage II controls at gasoline service stations. Vehicle

refueling VOC emissions were estimated using different methods for counties required to have

Stage II VOC controls versus counties not required to have Stage II VOC controls. Serious and

above ozone nonatttainment areas are required to implement Stage II (at the nozzle) vapor

recovery systems under Title I of the CAA. Table IV-6 shows the 227 counties required to have
IV-7

Stage II controls. However, since onboard vapor recovery systems on gasoline-fueled vehicles

are required in 1998 and later vehicles in all areas, independent of attainment status, higher

control efficiencies are estimated for counties where Stage II refueling controls are required. 

Control efficiencies were calculated using weighted gram per gallon emission factors determined

using a series of MOBILE5a runs. These runs also accounted for the expected effect of onboard

vapor recovery systems on future year evaporative emissions from gasoline-powered vehicles.

Table IV-3

Area Source VOC Control Measure Assumptions

Control Measure and Affected SCCs

VOC

Percentage

Reduction

VOC Rule

Effectiveness

Federal Control Measures (National)

Consumer Solvents

2465000000, 2465100000, 2465200000, 2465600000,

2456800000

25 100

Architectural and Industrial Maintenance Coatings

2401001000, 2401001999, 2401100000, 2401008000

25 100

Residential Wood Combustion

2104008000, 2104008001, 2104008010, 2104008030,

2104008050, 2104008051

See Table

IV-4

Onboard Vapor Recovery Systems; and Stage II for Gasoline

Service Stations

2501060100, 2501060101, 2501060102

See Table

IV-5

Title III MACT (National)

Wood Furniture Surface Coating

2401020000

30 100

Aerospace Surface Coating

2401075000

60 100

Marine Vessel Surface Coating (Shipbuilding)

2401080000

24 100

Halogenated Solvent Cleaners (Cold Cleaning)

2415300000, 2415305000, 2415310000, 2415320000,

2415325000, 2415330000, 2415335000, 2415340000,

2415345000, 2415355000, 2415360000, 2415365000

43 ** 100

Autobody Refinishing

2401005000

37 100

Petroleum Refinery Fugitives

2306000000

60 *** 100

Synthetic Organic Chemical Manufacturing Industry (SOCMI)

Fugitives (Hazardous Organic NESHAP)

2301040000

37 **** 100

Motor Vehicle Surface Coating

2401070000

36 100

Metal Product Surface Coating

2401040000, 2401045000, 2401050000

36 100
IV-8

Table IV-3 (continued)

Control Measure and Affected SCCs

VOC

Percentage

Reduction

VOC Rule

Effectiveness

Wood Product Surface Coating

2401015000

36 100

Open Top & Conveyorized Degreasing

2415100000, 2415105000, 2415110000, 2415120000,

2415125000, 2415130000, 2415135000, 2415140000,

2415145000, 2415199000, 2415200000

31 100

Publicly Owned Treatment Works (POTWs)

2630000000 to 2630020000

80 100

Metal Furniture & Appliances Surface Coating

2401025000, 2401060000

36 100

Machinery, Railroad Surface Coating

2401055000, 2401085000, 2401090000

36 100

Electronic Coating

2401065000

36 100

Title I RACT

Petroleum Dry Cleaning

2420000370, 2420010370

44 80

Paper Surface Coating

2401030000

78 80

NOTES:

* The efficiency of onboard vapor recovery systems varies depending on whether stage II vapor recovery systems are in place. It

is determined based on MOBILE5b emission factors.

** Overall control efficiency of 63% with 35% already applied in base year.

*** Overall control efficiency of 78% with 43% already applied in base year.

**** Overall control efficiency of 60% with 37% already applied in base year.
IV-9

Table IV-4

Residential Wood Combustion Control Efficiency

Assumptions by Pollutant and Future Year Inventory

Pollutant 2007 Percent Reduction 2020 Percent Reduction 2030 Percent Reduction

VOC 49 72 72

PM10 and

PM2.5

a

33 51 51

CO 37 55 55

a

 All residential wood combustion PM emissions are assumed to be less than or equal to PM2.5. 

Table IV-5

Vehicle Refueling VOC Control Efficiency

Assumptions Included in the Future Year Inventories

Does County

Have Stage II

Controls?

2007 Percent

Reduction

2020 Percent

Reduction

2030 Percent

Reduction

No 52.0 82.4 85.8

Yes 81.7 87.6 88.3
IV-10

Table IV-6

Counties with Stage II Controls

State County

State FIPS

Code

County

FIPS Code

Arizona Maricopa 04 013

California Alameda 06 001

California Contra Costa 06 013

California El Dorado 06 017

California Fresno 06 019

California Kern 06 029

California Kings 06 031

California Los Angeles 06 037

California Madera 06 039

California Marin 06 041

California Merced 06 047

California Monterey 06 053

California Napa 06 055

California Orange 06 059

California Placer 06 061

California Riverside 06 065

California Sacramento 06 067

California San Benito 06 069

California San Bernardino 06 071

California San Diego 06 073

California San Joaquin 06 077

California San Mateo 06 081

California Santa Barbara 06 083

California Santa Clara 06 085

California Santa Cruz 06 087

California Solano 06 095

California Sonoma 06 097

California Stanislaus 06 099

California Sutter 06 101

California Tulare 06 107

California Ventura 06 111

California Yolo 06 113

Connecticut Fairfield 09 001

Connecticut Hartford 09 003

Connecticut Litchfield 09 005

Connecticut Middlesex 09 007

Connecticut New Haven 09 009

Connecticut New London 09 011

Connecticut Tolland 09 013

Connecticut Windham 09 015

Delaware Kent 10 001

Delaware New Castle 10 003

Delaware Sussex 10 005

Dist. Columbia Washington 11 001

Florida Broward 12 011

Florida Dade 12 025

Florida Palm Beach 12 099

Georgia Cherokee 13 057

Georgia Clayton 13 063

Georgia Cobb 13 067

Georgia Coweta 13 077

Georgia De Kalb 13 089

Georgia Douglas 13 097

Georgia Fayette 13 113

Georgia Forsyth 13 117

Georgia Fulton 13 121

Georgia Gwinnett 13 135

Georgia Henry 13 151

Georgia Paulding 13 223
Table IV-6 (continued)

State County

State FIPS

Code

County

FIPS Code

IV-11

Georgia Rockdale 13 247

Illinois Cook 17 031

Illinois Du Page 17 043

Illinois Grundy 17 063

Illinois Kane 17 089

Illinois Kendall 17 093

Illinois Lake 17 097

Illinois McHenry 17 111

Illinois Will 17 197

Indiana Clark 18 019

Indiana Floyd 18 043

Indiana Lake 18 089

Indiana Porter 18 127

Kentucky Jefferson 21 111

Louisiana Ascension Parish 22 005

Louisiana East Baton Rouge Parish 22 033

Louisiana Iberville Parish 22 047

Louisiana Livingston Parish 22 063

Louisiana Pointe Coupee Parish 22 077

Louisiana West Baton Rouge Parish 22 121

Maryland Anne Arundel 24 003

Maryland Baltimore 24 005

Maryland Calvert 24 009

Maryland Carroll 24 013

Maryland Cecil 24 015

Maryland Charles 24 017

Maryland Frederick 24 021

Maryland Harford 24 025

Maryland Howard 24 027

Maryland Montgomery 24 031

Maryland Prince Georges 24 033

Maryland Baltim 24 510

Massachusetts Barnstable 25 001

Massachusetts Berkshire 25 003

Massachusetts Bristol 25 005

Massachusetts Dukes 25 007

Massachusetts Essex 25 009

Massachusetts Franklin 25 011

Massachusetts Hampden 25 013

Massachusetts Hampshire 25 015

Massachusetts Middlesex 25 017

Massachusetts Nantucket 25 019

Massachusetts Norfolk 25 021

Massachusetts Plymouth 25 023

Massachusetts Suffolk 25 025

Massachusetts Worcester 25 027

Michigan Kent 26 081

Michigan Livingston 26 093

Michigan Macomb 26 099

Michigan Monroe 26 115

Michigan Oakland 26 125

Michigan Ottawa 26 139

Michigan St. Clair 26 147

Michigan Washtenaw 26 161

Michigan Wayne 26 163

Missouri Franklin 29 071

Missouri Jefferson 29 099

Missouri St. Charles 29 183

Missouri St. Louis 29 189

Missouri St. Lo 29 510

Nevada Clark 32 003
Table IV-6 (continued)

State County

State FIPS

Code

County

FIPS Code

IV-12

Nevada Washoe 32 031

New Hampshire Hillsborough 33 011

New Hampshire Merrimack 33 013

New Hampshire Rockingham 33 015

New Hampshire Strafford 33 017

New Jersey Atlantic 34 001

New Jersey Bergen 34 003

New Jersey Burlington 34 005

New Jersey Camden 34 007

New Jersey Cape May 34 009

New Jersey Cumberland 34 011

New Jersey Essex 34 013

New Jersey Gloucester 34 015

New Jersey Hudson 34 017

New Jersey Hunterdon 34 019

New Jersey Mercer 34 021

New Jersey Middlesex 34 023

New Jersey Monmouth 34 025

New Jersey Morris 34 027

New Jersey Ocean 34 029

New Jersey Passaic 34 031

New Jersey Salem 34 033

New Jersey Somerset 34 035

New Jersey Sussex 34 037

New Jersey Union 34 039

New Jersey Warren 34 041

New York Bronx 36 005

New York Kings 36 047

New York Nassau 36 059

New York New York 36 061

New York Orange 36 071

New York Queens 36 081

New York Richmond 36 085

New York Rockland 36 087

New York Suffolk 36 103

New York Westchester 36 119

Ohio Ashtabula 39 007

Ohio Clark 39 023

Ohio Cuyahoga 39 035

Ohio Geauga 39 055

Ohio Greene 39 057

Ohio Lake 39 085

Ohio Lorain 39 093

Ohio Lucas 39 095

Ohio Medina 39 103

Ohio Miami 39 109

Ohio Montgomery 39 113

Ohio Portage 39 133

Ohio Summit 39 153

Ohio Wood 39 173

Pennsylvania Bucks 42 017

Pennsylvania Chester 42 029

Pennsylvania Delaware 42 045

Pennsylvania Montgomery 42 091

Pennsylvania Philadelphia 42 101

Rhode Island Bristol 44 001

Rhode Island Kent 44 003

Rhode Island Newport 44 005

Rhode Island Providence 44 007

Rhode Island Washington 44 009

Tennessee Davidson 47 037
Table IV-6 (continued)

State County

State FIPS

Code

County

FIPS Code

IV-13

Tennessee Rutherford 47 149

Tennessee Sumner 47 165

Tennessee Williamson 47 187

Tennessee Wilson 47 189

Texas Brazoria 48 039

Texas Chambers 48 071

Texas Collin 48 085

Texas Dallas 48 113

Texas Denton 48 121

Texas El Paso 48 141

Texas Fort Bend 48 157

Texas Galveston 48 167

Texas Hardin 48 199

Texas Harris 48 201

Texas Jefferson 48 245

Texas Liberty 48 291

Texas Montgomery 48 339

Texas Orange 48 361

Texas Tarrant 48 439

Texas Waller 48 473

Virginia Arlington 51 013

Virginia Charles City 51 036

Virginia Chesterfield 51 041

Virginia Fairfax 51 059

Virginia Hanover 51 085

Virginia Henrico 51 087

Virginia Loudoun 51 107

Virginia Prince William 51 153

Virginia Stafford 51 179

Virginia Alexandria 51 510

Virginia Colonial Heights 51 570

Virginia Fairfax 51 600

Virginia Falls Church 51 610

Virginia Hopewell 51 670

Virginia Manassas 51 683

Virginia Manassas Park 51 685

Virginia Richmond 51 760

Wisconsin Kenosha 55 059

Wisconsin Kewaunee 55 061

Wisconsin Manitowoc 55 071

Wisconsin Milwaukee 55 079

Wisconsin Ozaukee 55 089

Wisconsin Racine 55 101

Wisconsin Sheboygan 55 117

Wisconsin Washington 55 131

Wisconsin Waukesha 55 133
IV-14

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT FILES

Table IV-7 shows the mass and emissions processor input files prepared for area sources. 

Note that nonroad emissions (discussed in Chapter V) are also included in these inventory files. 

The control scenario only affects nonroad sources, as discussed in Chapter V.

1. Mass Emission Inventories

The structure for the area source mass emission inventory files is shown in Table IV-8. The

emissions processor input files were derived from the mass emission inventories. The only

change to emissions is the application of the crustal PM factor. This factor accounts for the fact

that only a portion of the crustal PM emissions are transportable. For the EPS 2.5 emissions

processor input files, a factor of 25 percent was applied to PM10 and PM2.5 emissions for the

SCCs listed in Table IV-9 to simulate the transportable component of these emissions. In

addition, PM10 and PM2.5 emissions from wind erosion of natural geogenic sources (SCCs

2730100000 [total] and 2730100001 [dust devils]) were excluded from the modeling files.

2. EPS 2.5 Emissions Processor Input Files

The EPS 2.5 emissions processor input file structure is detailed in Table IV-10. Annual

emissions estimates are provided in the EPS 2.5 emissions processor input files.

3. EMS-95 Emissions Processor Input Files

The EMS-95 emissions processor input files include typical SSD VOC, NOx, and CO

emissions for ozone modeling. The structure for the area source EMS-95 input files is given in

Table IV-11. Two EMS-95 inventory files were prepared for the 1996 base year inventory, and

the 2007, 2020, and 2030 base and control case inventories. One file provides area source and

nonroad emissions at the 10-digit SCC level. The other file provides nonroad emissions at the

7-digit SCC level and area source emissions at the 10-digit SCC level.
IV-15

Table IV-7

Area/Nonroad Mass and Emissions Processor Input Files

File Name

Year Scenario Mass EPS 2.5 EMS-95 Comments

1996 Base AR96MS1H.DBF

AR96MX1H.DBF Includes 25% transportable PM factor and no

wind erosion emissions for natural geogenic

sources.

NR96MS1H.DBF AN96EP1H.TXT AN96EM1H.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N96MS1H7.DBF AN96EM17.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

2007 Base AR07MS2H.DBF

AR07MX2H.DBF Includes 25% transportable PM factor and no

wind erosion emissions for natural geogenic

sources.

N7MS1HB.DBF AN7EP2HB.TXT AN7EM1HB.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N7MS1HB7.DBF AN7EM1B7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

Control N7MS1HC.DBF AN7EP2HC.TXT AN7EM1HC.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N7MS1HC7.DBF AN7EM1C7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

2020 Base AR20MS2H.DBF

AR20MX2H.DBF Includes 25% transportable PM factor and no

wind erosion emissions for natural geogenic

sources.

N2MS1HB.DBF AN2EP2HB.TXT AN2EM1HB.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N2MS1HB7.DBF AN2EM1B7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

Control N2MS1HC.DBF AN2EP2HC.TXT AN2EM1HC.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N2MS1HC7.DBF AN2EM1C7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

2030 Base AR30MS3H.DBF

AR30MX3H.DBF Includes 25% transportable PM factor and no

wind erosion emissions for natural geogenic

sources.

N3MS1HB.DBF AN3EP3HB.TXT AN3EM1HB.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N3MS1HB7.DBF AN3EM1B7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.

Control N3MS1HC.DBF AN3EP3HC.TXT AN3EM1HC.TGZ For EPS 2.5, includes area source MX and

nonroad emissions.

N3MS1HC7.DBF AN3EM1C7.TGZ For EMS-95, use 7-digit SCC detail for

nonroad sources.
IV-16

Table IV-8

Area/Nonroad Mass Emissions Inventory File Structure

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State code

FIPSCNTY C 3 0 FIPS county code

SCC C 10 0 SCC

VOC_ANN N 10 4 Annual VOC [tons per year (tpy)]

NOX_ANN N 10 4 Annual NOx (tpy)

CO_ANN N 10 4 Annual CO (tpy)

SO2_ANN N 10 4 Annual SO2 (tpy)

PM10_ANN N 10 4 Annual PM10 (tpy)

PM25_ANN N 10 4 Annual PM2.5 (tpy)

NH3_ANN N 10 4 Annual NH3 (tpy)

SOA_ANN N 10 4 Annual SOA (tpy)

VOC_OSD N 10 4 OSD VOC (tpd)

NOX_OSD N 10 4 OSD NOx (tpd)

CO_OSD N 10 4 OSD CO (tpd)

SO2_OSD N 10 4 OSD SO2 (tpd)

PM10_OSD N 10 4 OSD PM10 (tpd)

PM25_OSD N 10 4 OSD PM2.5 (tpd)

NH3_OSD N 10 6 OSD NH3 (tpd)

SOA_OSD N 10 6 OSD SOA (tpd)

VOC_EMF N 11 4 VOC Emission Factor

NOX_EMF N 11 4 NOx Emission Factor

CO_EMF N 11 4 CO Emission Factor

SO2_EMF N 11 4 SO2 Emission Factor

PM10_EMF N 11 4 PM10 Emission Factor

PM25_EMF N 11 4 PM2.5 Emission Factor

NH3_EMF N 11 4 NH3 Emission Factor

VOC_CE N 7 2 VOC Control Efficiency

NOX_CE N 7 2 NOx Control Efficiency

CO_CE N 7 2 CO Control Efficiency

SO2_CE N 7 2 SO2 Control Efficiency

PM10_CE N 7 2 PM10 Control Efficiency

PM25_CE N 7 2 PM2.5 Control Efficiency

NH3_CE N 7 2 NH3 Control Efficiency

VOC_RE N 3 0 VOC Rule Effectiveness
IV-17

Table IV-8 (continued)

Variable Type Length Decimals Description

NOX_RE N 3 0 NOx Rule Effectiveness

CO_RE N 3 0 CO Rule Effectiveness

SO2_RE N 3 0 SO2 Rule Effectiveness

PM10_RE N 3 0 PM10 Rule Effectiveness

PM25_RE N 3 0 PM2.5 Rule Effectiveness

NH3_RE N 3 0 NH3 Rule Effectiveness

VOC_RP N 6 2 VOC Rule Penetration

NOX_RP N 6 2 NOx Rule Penetration

CO_RP N 6 2 CO Rule Penetration

SO2_RP N 6 2 SO2 Rule Penetration

PM10_RP N 6 2 PM10 Rule Penetration

PM25_RP N 6 2 PM2.5 Rule Penetration

NH3_RP N 6 2 NH3 Rule Penetration
IV-18

Table IV-9

Source Categories to which Crustal Factor was Applied to PM10 and PM2.5

Emissions in EPS 2.5 Emissions Processor Input Files

Sector/SCC Source Category Description

Mobile Sources/Aircraft

227508xxxx Unpaved Airstrips

Mobile Sources/Paved Roads

2294xxxxxx Paved Roads

Mobile Sources/Unpaved Roads

2296xxxxxx Unpaved Roads

Industrial Processes/Construction (SIC codes 15 - 17)

23110001xx All Processes: Wind Erosion

23110101xx General Building Construction: Wind Erosion

23110201xx Heavy Construction: Wind Erosion

23110301xx Road Construction: Wind Erosion

23110401xx Special Trade Construction: Wind Erosion

Miscellaneous Area Sources/Agriculture Production - Crops

28010xxxxx Agriculture - Crops

28017xxxxx Fertilizer Application

Miscellaneous Area Sources/Agriculture Production - Livestock

2805xxxxxx Agriculture Production - Livestock
IV-19

Table IV-10

Area/Nonroad EPS 2.5 Emissions Processor Input File Structure

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS county Code

SCC C 10 0 AMS Source Category Code

VOC N 12 4 Annual VOC Emissions (tpy)

NOX N 12 4 Annual NOx Emissions (tpy)

CO N 12 4 Annual CO Emissions (tpy)

SO2 N 12 4 Annual SO2 Emissions (tpy)

PM10 N 12 4 Annual PM10 Emissions (tpy)

PM25 N 12 4 Annual PM2.5 Emissions (tpy)

SOA N 12 4 Annual SOA Emissions (tpy)

NH3 N 12 4 Annual NH3 Emissions (tpy)
IV-20

Table IV-11

Area/Nonroad EMS-95 Emissions Processor Input File Structure

Variable Type Length Decimals Description

Area File:

STID N 2 0 FIPS State Code

CYID N 3 0 FIPS County Code

ASCT C 15 0 Area Source Category

POLID C 5 0 Pollutant ID

ACEF N 13 0 Actual Emission Factor (tons/process unit)

ALEF N 13 0 Allowable Emission Factor (tons/process unit)

ACEE N 13 0 Actual Emissions (tons)

ALEE N 13 0 Allowable Emissions (tons)

PCEC C 5 0 Primary Control Equipment

SCEC C 5 0 Secondary Control Equipment

CEEF N 7 4 Control Equipment Efficiency (%)

ESTT C 2 0 Temporal Basis (AA or AD)

Temporal File:

STID N 2 0 FIPS State Code

CYID N 3 0 FIPS County Code

ASCT C 15 0 Area Source Category

PRRT N 13 0 Annual Process Rate (process units/year)

ACUN C 15 0 Activity Units

DEC N 5 3 Fractional December Throughput

JAN N 5 3 Fractional January Throughput

FEB N 5 3 Fractional February Throughput

MAR N 5 3 Fractional March Throughput

APR N 5 3 Fractional April Throughput

MAY N 5 3 Fractional May Throughput

JUN N 5 3 Fractional June Throughput

JUL N 5 3 Fractional July Throughput

AUG N 5 3 Fractional August Throughput

SEP N 5 3 Fractional September Throughput

OCT N 5 3 Fractional October Throughput

NOV N 5 3 Fractional November Throughput

WIN N 3 0 Winter Throughput (Dec - Feb) (%)

SPR N 3 0 Spring Throughput (Mar - May) (%)

SUM N 3 0 Summer Throughput (Jun - Aug) (%)

FAL N 3 0 Fall Throughput (Sep - Nov) (%)

HOURS N 2 0 Code Value for Hourly Operation 

DAYS N 2 0 Code Value for Daily Operation 

WEEKS N 2 0 Weeks of Operation per Year (weeks/year)

DAYYEAR N 3 0 Days of Operation per Year (days/year)

HOURYEAR N 4 0 Hours of Operation per Year (hours/year)
V-1

CHAPTER V

NONROAD SOURCES

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY

County-level emission estimates for 1996 for the majority of nonroad sources were

developed using EPA’s draft NONROAD model. Emission estimates for VOC, NOx, CO, SO2,

PM10, and PM2.5 are reported by the model. The NONROAD model does not estimate NH3 and

SOA emissions; therefore, these emissions were calculated outside the model. Aircraft,

commercial marine, and locomotives are not presently included in the NONROAD model, and

the procedures to develop emission estimates for these categories are discussed separately.

1. NONROAD Model Equipment Categories

The NONROAD model estimates pollutant emissions for the following general equipment

categories: (1) agricultural; (2) airport service; (3) light commercial; (4) construction and

mining; (5) industrial; (6) lawn and garden; (7) logging; (8) pleasure craft; (9) railway

maintenance; and (10) recreational equipment. These applications are further classified

according to fuel and engine type [diesel, gasoline 2-stroke, gasoline 4-stroke, compressed

natural gas (CNG), and liquified petroleum gas (LPG)]. 

The base year nonroad mass emissions inventory for the HDD rulemaking was developed

from two emission inventories including: 1) an existing 1996 county-level inventory, based on

EPA’s April 1999 draft NONROAD model; and 2) an updated national inventory, based on

EPA’s June 2000 draft version of the NONROAD model. 

To develop the original 1996 county-level inventory, NONROAD model input files were

prepared for each State to account for the average statewide temperatures and Reid vapor

pressure (RVP) for four seasons, including summer, fall, winter, and spring. Input files were also

generated to account for county-level differences in RVP, fuel characteristics due to reformulated

gasoline (RFG) and oxygenated fuel programs, and Stage II controls. Emissions calculated for

counties with fuel characteristic and control data that varied from statewide average values

replaced emissions for these same counties generated by running the default input files. Typical

SSD emissions were estimated by dividing total summer season emissions by 92 days.

This 1996 county-level emissions inventory was then updated to reflect revisions made to

the NONROAD model since the April 1999 version. Using the June 2000 draft NONROAD

model, national, seasonal emissions were generated at the SCC level for the following pollutants:

VOC, NOx, SO2, CO, PM10, and PM2.5. The results for three seasonal runs (i.e., summer, winter,

fall/spring combined) were summed to calculate annual emissions. Additional NONROAD

model runs were performed to estimate typical summer weekday emissions as well. To account
V-2

for lower diesel fuel sulfur levels in California, separate runs were performed for this State for

diesel-fueled equipment SCCs. Tables V-1a and V-1b present a summary of the input values

used for the national NONROAD model runs.

Table V-1a

Temperature and RVP Inputs for National NONROAD Model Runs1

Season Input2 Value

Summer RVP (psi) 8.1

Min Temp ((F) 62

Max Temp ((F) 82

Average Temp ((F) 72

Fall/Spring RVP (psi) 9.7

Min Temp ((F) 43

Max Temp ((F) 63

Average Temp ((F) 53

Winter RVP (psi) 13.1

Min Temp ((F) 24

Max Temp ((F) 44

Average Temp ((F) 34

Typical Summer Weekday RVP (psi) 8.1

Min Temp ((F) 62

Max Temp ((F) 82

Average Temp ((F) 72

1

 The input values presented were the same for both base and control cases and for all years. The

control case input values were the same for all three projection years (no control case was developed for

1996).

2

 Values for minimum, maximum, and average temperature are expressed in degrees Fahrenheit ((F).

Table V-1b

Diesel Fuel Sulfur Input Values for National NONROAD Model Runs1

Fuel Sulfur, ppm

Year Base case2 Control case3

1996 2527 Not applicable

2007 2654 2579

2020 2733 2667

2030 2770 2708

1

 Diesel fuel sulfur does not change seasonally. NONROAD runs were done using fuel sulfur inputs of

2859 ppm and 2808 ppm, for the base and control case, respectively. SO2 output values, but not PM,

were then adjusted to represent the values as listed for each year.

2

 For California base case runs, a diesel fuel sulfur content of 120 ppm was used for all seasons.

3

 For California control case runs, a diesel fuel sulfur content of 103 ppm was used for all seasons.
V-3

SSDcounty 
 SSDnational × (Annualcounty ÷ Annualnational)

SCC-specific ratios were calculated by dividing the updated national, annual emission

estimates by the previous 1996 national values (i.e., based on the April 1999 version of

NONROAD). County-level emissions were then calculated by multiplying each record in the

existing 1996 inventory by the appropriate ratio for each SCC. In this manner, the county-level

distribution of the existing 1996 inventory is normalized to the updated national, SCC-level

totals for 1996. California diesel equipment emissions were also updated. Based on the results

of the separate California NONROAD model runs, state-level, SCC emission ratios were

calculated by dividing the updated California diesel emission estimates by the previous 1996

California values. These ratios were applied to existing county-level records for California, and

the resulting emissions were incorporated into the 1996 mass emissions inventory.

Similar to annual emission ratios, SSD ratios were first developed by dividing updated SSD

emissions by previous SSD emissions. However, when SSD ratios were applied to certain

records, new SSD emission values were calculated that were larger than the corresponding

annual emissions. This was occurring because SSD values had been calculated differently in the

April 1999 data base (i.e., they had previously been calculated by dividing summer season

emissions by 92, as opposed to performing separate runs for a typical summer day). To adjust

this result, and to ensure that the total national SSD emissions were equivalent to what EPA’s

Office of Transportation and Air Quality (OTAQ) had originally provided, county-level SSD

emissions were calculated by multiplying national SSD emissions by the ratio of county level

annual emissions to national level annual emissions. This is shown in the formula below:

Additional adjustments to the 1996 NONROAD emissions inventory included: 1) applied

additional factors to SO2 emissions to account for the true fuel sulfur level as a result of low

sulfur diesel fuel spillover (i.e., as shown in Table V-1b); and 2) revised county-level emissions

for air conditioning (AC)/refrigeration and railway maintenance in Suffolk County, MA to

correct an error in the original equipment populations used to estimate emissions. 

Finally, new SCCs have been added to the most recent version of NONROAD. Since the

April 1999 county-level data base did not include these SCCs, surrogate SCCs were assigned to

the new SCCs to use in allocating national emissions to the county-level. The additional SCCs

and each corresponding surrogate SCC are shown in Table V-2.

2. Emission Estimates for Aircraft, Commercial Marine Vessels, and

Locomotives

Base year aircraft and locomotive emissions were taken from the existing 1996 NET

inventory (EPA, 2000a).

Hydrocarbon (HC), NOx, CO, and total PM national emission estimates for commercial

marine diesel engines were provided by OTAQ. VOC was calculated by multiplying HC

emissions by a factor of 1.053. PM10 was assumed to be equivalent to PM, and PM2.5 was

estimated by multiplying PM10 emissions by a factor of 0.92. The new national estimates
V-4

Table V-2

Surrogate SCC Assignments for New SCCs in June 2000 NONROAD Model

Additional

SCCs

Description Surrogate

SCC

Description

2260002054 Gasoline, 2-Stroke Construction

Equipment Crushing/Processing

Equipment

2265002054 Gasoline, 4-Stroke Construction

Equipment Crushing/Processing

Equipment

2260005050 Gasoline, 2-Stroke Farm

Equipment Hydro Power Units

2265005050 Gasoline, 4-Stroke Farm

Equipment Hydro Power Units

2265001020 Gasoline, 4-Stroke Recreational

Vehicles Snowmobiles

2260001020 Gasoline, 2-Stroke Recreational

Vehicles Snowmobiles

2265007015 Gasoline, 4-Stroke Logging

Equipment Skidders

2270007015 Diesel Logging Equipment 

Skidders

2267005055 LPG Farm Equipment Other

Agricultural Equipment

2265005055 Gasoline, 4-Stroke Farm

Equipment Other Agricultural

Equipment

2268002081 CNG Construction Equipment 

Other Construction Equipment

2265002081 Gasoline, 4-Stroke Construction

Equipment Other Construction

Equipment

2268003020 CNG Industrial Equipment 

Forklifts

2265003020 Gasoline, 4-Stroke Industrial

Equipment Forklifts

2268003040 CNG Industrial Equipment Other

General Industrial Equipment

2265003040 Gasoline, 4-Stroke Industrial

Equipment Other General Industrial

Equipment

2268003070 CNG Industrial Equipment

Terminal Tractors

2265003070 Gasoline, 4-Stroke Industrial

Equipment Terminal Tractors

2268005050 CNG Farm Equipment Hydro

Power Units

2265005050 Gasoline, 4-Stroke Farm

Equipment Hydro Power Units

2268005055 CNG Farm Equipment Other

Agricultural Equipment

2265005055 Gasoline, 4-Stroke Farm

Equipment Other Agricultural

Equipment

2268006015 CNG Light Commercial Air

Compressors 

2265006015 Gasoline, 4-Stroke Light

Commercial Air Compressors 

were distributed to counties using the geographic distribution in the existing 1996 NET data

base. 

3. Methodologies for NH3 and SOA

Ammonia emissions were adjusted based on updated national, SCC-level fuel consumption

estimates for diesel and gasoline engines, as reported by the June 2000 draft version of

NONROAD. Fuel consumption estimates were not available for LPG- and CNG-fueled

equipment. As with the criteria pollutant emission estimates, SCC-specific ratios were

developed by dividing updated fuel consumption values by previous fuel consumption values. 

NH3 emissions for California were also recalculated using updated diesel fuel consumption

values generated for California-specific runs. Once a county-level data base of fuel consumption

was developed, emission factors provided by OTAQ were then applied to these activity data to
V-5

estimate NH3 emissions. The emission factors were derived primarily from light-duty on-road

vehicle emission measurements, and extrapolated to nonroad engines on a fuel consumption

basis. NH3 emissions for diesel engines were calculated by multiplying diesel fuel consumption

by an emission factor of 165.86 milligrams/gallon. NH3 emissions from gasoline engines

(without catalysts) were calculated by multiplying gasoline consumption by an emission factor of

153.47 milligrams/gallon.

For aircraft, commercial marine, and locomotive categories, national fuel consumption

estimates for 1996 were obtained from various sources. Jet fuel and aviation gasoline

consumption for general aviation and commercial aircraft were obtained from the “FAA Aviation

Forecasts Fiscal Years, 1998-2009,” (FAA, 1998a). For the aircraft categories, NH3 emission

factors developed for diesel engines were applied to all fuel consumption estimates, since

aviation gasoline consumption was determined to be relatively small compared to jet fuel, and

the aircraft SCCs are not broken down by fuel type. Diesel consumption estimates for

locomotives were obtained from “Locomotive Emission Standards - Regulatory Support

Document (RSD),” (EPA, 1997). For commercial marine, data for distillate and residual fuel oil

were reported in “Fuel Oil and Kerosene Sales,” (EIA, 1996).

Secondary organic aerosol emissions were calculated by applying the appropriate fractional

aerosol coefficient to annual and SSD VOC emissions (Grosjean and Seinfeld, 1989). Default

assignments were made to new nonroad SCCs that had not been previously assigned SOA

fractions.

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES

The methods for developing base case and control scenario projection year inventories for

nonroad sources are described in this section. Table V-3 provides a summary of the projection

methods, as well as growth indicators, used for each nonroad equipment category.

1. Nonroad Model Equipment Categories

For NONROAD model categories, emission estimates for projection years were developed

using a method comparable to that for the base year. First, three seasonal (i.e., summer, winter,

and fall/spring combined) NONROAD model runs were performed at the national level. 

Seasonal runs accounted for differences in average seasonal temperature, as well as RVP. 

Second, year-specific ratios were calculated by dividing national SCC-level emission estimates

for 2007, 2020, and 2030 by the 1996 national values. County-level estimates were then

calculated for 2007, 2020, and 2030 by multiplying each ratio times the 1996 county-level

emissions inventory. In this manner, the county-level distribution assumed for the 1996

inventory is normalized to the updated national, SCC-level totals for each projection year. As

with the base year, separate NONROAD model runs were done for California diesel-fueled

SCCs. Additional runs were also performed to estimate typical summer weekday emissions for

each projection year.
V-6

Table V-3

Growth Indicators/Projection Methods for Nonroad Sources

Nonroad SCC SCC Description Growth Indicator

2260xxxxxx

2265xxxxxx

2267xxxxxx

2268xxxxxx

2270xxxxxx

2282xxxxxx

2285xxx015

2-stroke gasoline

4-stroke gasoline

CNG

LPG

Diesel

Recreational marine

Railway maintenance

Not applicable1

2275050000, 2275060000

2275020000, 2275070000

General Aviation and Air Taxis

Commercial Aircraft and Auxiliary

Power Units

Landing-Takeoff Operations

(LTOs) for total aircraft operations

2275001xxx Military Aircraft 992 - Federal, Military

2275085xxx Unpaved Airstrips SIC 45 - Air Transportation

2275900xxx Aircraft Refueling SIC 45 - Air Transportation

2280002xxx Commercial Marine - Diesel Vessels SIC 44 - Water Transportation2

2280001xxx, 2280003xxx,

2280004xxx

Commercial Marine - Coal, Residual

Oil, and Gas-fired Vessels

SIC 44 - Water Transportation

2283xxxxxx Military Marine Vessels 992 - Federal, Military

2285xxxxxx Locomotives No growth3 

1

 Projection year emission estimates were derived from national NONROAD model runs allocated to counties

based on the geographic distribution of a 1996 county-level inventory, developed from the April 1999 draft version

of NONROAD.

2

 SO2 and NH3 emissions were projected using growth factors; projection year estimates for all other pollutants

provided by OTAQ.

3

 SO2 and NH3 emissions for projection years assumed to remain constant at 1996 uncontrolled levels; controlled

projection year estimates for all other pollutants provided by OTAQ.

In addition to a base case scenario, control case emission inventories were developed for

each projection year to account for the effects of proposed HDDV reductions in diesel sulfur

content. Table V-1b presents the diesel fuel sulfur values assumed for the base case and control

case scenario. Separate runs were performed for California to account for the lower diesel fuel

sulfur content in this State (i.e., 120 ppm for the base case, and 103 ppm for the control

scenario).

Similar adjustments were made to projection year NONROAD model inventories as were

made for the 1996 base year nonroad inventory. These adjustments included: (1) calculating

county SSD emissions by multiplying national SSD emissions by the ratio of county to national

annual emissions, for each SCC; (2) applying additional factors to SO2 emissions to account for

the true fuel sulfur level as a result of low sulfur diesel fuel spillover (i.e., as shown in

Table V-1b); and (3) revising emissions for AC/refrigeration and railway maintenance in Suffolk

County, MA to correct an error in the original equipment populations.
V-7

a. Growth Assumptions

Nonroad category emissions have typically been projected using economic indicators that are

believed to correlate to nonroad equipment activity. For example, nonroad agricultural

equipment emissions have been grown in the past using BEA GSP projections for SIC code 01,

which corresponds to the farm industry. However, instead of using economic indicators to

project emissions or nonroad activity, the current version of the NONROAD model predicts

future year nonroad equipment populations by extrapolating

from a linear regression of historical equipment populations. Because total activity is never

directly measured, the historical trend in population must be used as a surrogate. A time-series

analysis using historic equipment populations is believed to better reflect market trends within

each sector (e.g., a shift from gasoline-fueled equipment to diesel-fueled equipment). Accurately

estimating the relative distribution of different engine types in the future is important since diesel

and gasoline engines have distinct emission characteristics. This approach, however, is not

planned to be used for all equipment types in the final version of the NONROAD model. Some

exceptions include oil field equipment and aircraft ground support equipment, which will rely on

BEA GSP data and Federal Aviation Administration (FAA) LTO data, respectively.

b. Control Assumptions

The NONROAD model accounts for the effect of Federal nonroad engine emission standards

which are final, or proposed standards soon expected to be final. The emission levels associated

with compression-ignition (CI) and spark-ignition (SI) engine standards are incorporated into

emission factors, which are then applied to future year nonroad equipment populations. The

control programs accounted for by the NONROAD model include: (1) Tier 1, Tier 2 and Tier 3

CI standards for diesel engines greater than 50 horsepower (hp); (2) Tier 1 and Tier 2 CI

standards for diesel engines below 50 hp; (3) Phase I and Phase 2 of the SI standards for gasoline

engines less than 25 hp; (4) recreational SI marine engine controls. Base year and controlled steady-state emission factors for various horsepower ranges of CI

engines subject to the Tier 1, Tier 2, and Tier 3 standards are presented in Table V-4. Base year

and controlled steady-state emission factors for SI engines below 25 hp (19 kilowatts) are

presented in Table V-5. Additional details on the control levels reflected in NONROAD for

future years for these categories, as well as SI recreational marine engines, are presented in

technical reports that serve as supporting documentation for NONROAD model inputs (EPA,

1998 and EPA, 1999a). Compression-ignition engine emission factor values listed in Table V-4

reflect revisions made to the NONROAD model since the April 1999 draft version, which are

documented in an EPA memorandum dated May 31, 2000 (EPA, 2000b).

The impact of RFG in the appropriate counties is reflected in the 1996 base year county-level

inventory, in that the fuel RVP and percent oxygen were adjusted, as described in section V.A.1,

for counties subject to RFG and oxygenated fuels requirements. No further adjustments were

made to account for the use of RFG in future years.
V-8

Table V-4

Steady-State Emission Factors for CI Engines in the NONROAD Model

Engine

Power (hp)

Model

Year Regulation

Emission Factors (g/hp-hr)

HC CO NOx PM1

>0 to 11 88-99 – 1.5 5.0 10.0 1.0

00-04 Tier 1 0.3 4.1 5.6 0.52

05- Tier 2 0.3 4.1 4.3 0.44

>11 to 25 88-99 – 1.7 5.0 8.5 0.9

00-04 Tier 1 0.2 1.3 4.0 0.36

05- Tier 2 0.2 1.3 4.3 0.36

>25 to 50 88-98 – 1.8 5.0 6.9 0.8

99-03 Tier 1 0.13 1.8 4.8 0.38

04- Tier 2 0.13 1.8 4.3 0.32

>50 to 100 88-97 – 1.0 3.5 6.9 0.72

98-03 Tier 1 0.56 2.0 5.3 0.37

04-07 Tier 2 0.36 2.0 4.7 0.24

08- Tier 3 0.18 2.0 3.0 0.24

>100 to 175 88-96 – 0.7 2.7 8.4 0.4

97-02 Tier 1 0.4 1.1 5.9 0.22

03-06 Tier 2 0.36 1.1 4.1 0.18

07- Tier 3 0.18 1.1 2.5 0.18

>175 to 300 88-95 – 0.7 2.7 8.4 0.4

96-02 Tier 1 0.35 0.8 5.8 0.19

03-05 Tier 2 0.35 0.8 4.0 0.12

06- Tier 3 0.18 0.8 2.5 0.12

>300 to 600 88-95 – 0.7 2.7 8.4 0.4

96-00 Tier 1 0.22 0.8 5.8 0.12

01-05 Tier 2 0.22 0.8 4.1 0.12

06- Tier 3 0.18 0.8 2.5 0.12

>600 to 750 88-95 – 0.7 2.7 8.4 0.4

96-01 Tier 1 0.2 1.2 5.8 0.14

02-05 Tier 2 0.2 1.2 4.1 0.12

06- Tier 3 0.18 1.2 2.5 0.12

>750 88-99 – 0.7 2.7 8.4 0.4

00-05 Tier 1 0.2 1.1 5.8 0.13

06- Tier 2 0.2 1.1 4.1 0.12 1

 PM10 is assumed to be equivalent to PM.
V-9

Table V-5

Emission Factors for SI Engines Below 25 hp

Engine Tech Type HC CO NOx PM1 BSFC

Class III Engine Emissions for New Engines (g/kW-hr)

Gas 2-stroke handheld Class III, baseline 350 964 1.30 10.33 830

Phase 1 295 644 1.05 10.33 720

Phase 1 with catalyst 295 644 1.05 10.33 720

Phase 2 44 380 1.22 10.33 500

Phase 2 with catalysts 36 190 2.00 10.33 500

Class IV Handheld New Engine Emissions (g/kW-hr)

Gas 2-stroke handheld Class IV, baseline 350 964 1.26 10.33 830

Phase 1 241 546 0.688 10.33 720

Phase 1 with catalyst 241 546 0.688 10.33 720

Phase 1 4-stroke 30 715 2.40 0.08 515

Phase 2 44 380 1.22 10.33 500

Phase 2 with catalysts 36 190 2.00 10.33 500

Phase 2 4-stroke 35 580 1.51 0.08 515

Class V Handheld New Engine Emissions (g/kW-hr)

Gas 2-stroke handheld Class V, baseline 214 696 1.30 10.33 560

Phase 1 161 471 2.436 10.33 529

Phase 1 with catalyst 161 471 2.436 10.33 529

Phase 2 64 380 1.22 10.33 370

Phase 2 with catalysts 54 190 2.00 10.33 370

Class I Nonhandheld New Engine Emissions (g/kW-hr)

Gas 2-stroke nonhandheld Class I, baseline 279 651 0.39 10.33 529

Gas, side-valved, 4-stroke nonhandheld Class I, baseline 52 578 2.68 0.080 830

Gas, overhead-valved, 4-stroke nonhandheld Class I, baseline 18 548 2.41 0.080 603

2-stroke, Phase 1 161 603 5.36 10.33 529

Phase 1 side-valved, 4-stroke 11.27 474 4.83 0.080 560

Phase 1 overhead valved 4-stroke 11.27 471 4.34 0.080 475

Phase 1 side-valved, 4-stroke with catalyst 11.27 474 4.83 0.080 560

Phase 2 side-valved 10.63 474 3.17 0.080 560

Phase 2 overhead valved 8.22 471 2.46 0.080 475

Class II Nonhandheld New Engine Emissions (g/kW-hr)

Gas 2-stroke nonhandheld Class II, baseline 279 651 0.39 10.33 529

Gas, side-valved, 4-stroke nonhandheld Class II, baseline 12.96 578 2.76 0.080 570

Gas, overhead-valved, 4-stroke nonhandheld Class II, baseline 6.97 548 4.69 0.080 570

Phase 1 side-valved, 4-stroke 7.37 519 6.03 0.080 528

Phase 1 overhead valved 4-stroke 6.97 473 4.69 0.080 450

Phase 2 side-valved 7.37 519 6.03 0.080 528

Phase 2 overhead valved 5.58 473 3.72 0.080 450 1

 PM10 is assumed to be equivalent to PM.
V-10

2. Emission Estimates for Aircraft, Commercial Marine Vessels, and

Locomotives

Aircraft emissions for 2007 were based on the existing NET projections, which used FAA

LTO data as the growth surrogate for commercial and civil aircraft. Military aircraft were

projected from 1996 using BEA GSP growth factors. Aircraft estimates for the years 2020 and

2030 were also based on existing NET emission estimates, which were developed from

commercial and general aviation growth rates from the FAA. Forecasts were only available up to

the year 2020 in “Long Range Aviation Forecasts Fiscal Years 2010, 2015, and 2020,” (FAA,

1998b). The annual average growth rate for the period 2015 to 2020 was assumed for estimating

growth out to the year 2030. Military aviation activity was assumed to remain constant starting

in 2010, so 2010 emissions from the NET were used for 2020 and 2030 estimates for this

category. The EPA has promulgated NOx and CO emission standards for commercial aircraft,

but the impacts from these standards are not accounted for in this analysis.

Commercial marine emissions projections were developed similar to the 1996 base year

estimates, with updated national commercial marine diesel emissions for 2007, 2020 and 2030

provided by OTAQ being distributed to the county based on the existing 1996 county-level

distribution in the NET. These national estimates reflect the effect of Federal emission standards

promulgated for new diesel-fueled commercial marine vessels. Commercial gasoline,

commercial coal, and military marine emissions were grown from 1996 using BEA GSP growth

factors.

Locomotive emission estimates for 2007, 2020 and 2030 were based on corrected emission

estimates from the Regulatory Support Document for locomotive emission standards (EPA,

1997). The correction reflects the standards taking effect in 2007, not 2002. This report

contained emission projections for all criteria pollutants except for SO2; therefore, SO2 estimates

from the current NET inventory were used. For the rulemaking support analysis, EPA assumed

that future year fuel consumption will remain constant at 1996 levels. It was thought that

improvements in the fuel efficiency of locomotives will offset the increase in the amount of

freight hauled; therefore, no growth was assumed. The national emission estimates also

accounted for future, phased-in controls that will primarily reduce NOx and PM emissions. 

These updated national estimates were distributed to the county-level using the existing county

allocation in the 1996 NET inventory.

3. Methodologies for NH3 and SOA

Updated values for national diesel and gasoline fuel consumption, as well as California

diesel fuel consumption, were obtained from the June 2000 draft version of the NONROAD

model for 2007, 2020, and 2030. Fuel consumption was distributed to counties using the 1996

county-level distribution. County-level fuel consumption estimates were then multiplied by the

appropriate emission factor to estimate NH3 emissions for the projection years. For aircraft,

commercial marine, and locomotive categories, 1996 base year NH3 emissions were projected to

future years using the growth indicators listed in Table V-3.
V-11

SOA emissions were calculated for projection years using the same method used for the base

year. Projected VOC emission estimates were multiplied by the appropriate fractional aerosol

coefficient for each SCC.

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT FILES

Nonroad mass emissions were maintained in a separate data base from area source

emissions, but the mass emissions file structure is the same for nonroad and area sources. 

Nonroad emissions are combined with area sources to produce the final emissions processor

input files. Refer to Chapter IV for the mass and emissions processor input file names and

structures.
VI-1

CHAPTER VI

ON-HIGHWAY VEHICLE SOURCES

A. 1996 BASE YEAR MASS EMISSIONS INVENTORY

This section summarizes the inputs and control programs that were modeled and adjustments

that were made to the 1996 on-highway vehicle emissions inventory. The starting point for the

1996 on-highway vehicle emission inventory was the 1996 National Emission Trends highway

vehicle emission factor database created in 1998 that was also used in support of EPA’s Tier 2

rulemaking. The procedures document for the National Emissions Inventory provides more

detail on the inputs contained in that analysis, but some of the key elements of that inventory are

summarized here (EPA, 1998b). The 1996 vehicle miles traveled (VMT) used in this HDD

analysis also uses the corresponding Trends VMT file as the starting point, with the updates

discussed below.

The 1996 VMT data is based on historical 1996 Highway Performance Monitoring System

(HPMS) data obtained from the Federal Highway Administration (FHWA, 1997). The HPMS

database contains state-level summaries of average annual daily VMT by roadway type and by

rural, small urban, and individual urban areas. The small urban and individual urban area VMT

combined to make up the total urban VMT. Based on population data from the Bureau of Census

(BOC, 1992), the HPMS data were distributed to counties at the roadway type level. A

conversion was then made at the national roadway type level to convert the national VMT from

the HPMS vehicle categories to the MOBILE5b vehicle type categories. EPA’s OTAQ provided

a new mapping of the HPMS VMT by vehicle category to the MOBILE5 vehicle categories. 

This was an update from the VMT mapping used in the 1996 Trends VMT data base. Table VI-1

shows this new HPMS to MOBILE5 VMT allocation by vehicle type. Using the data in the

table, national 1996 HPMS VMT, by rural and urban categories, were converted to total fraction

of VMT by MOBILE5 vehicle type for rural roads and urban roads. These fractions were then

multiplied by the 1996 VMT distributed by county and roadway type to create the new 1996

VMT file by county, roadway type, and vehicle type. Table VI-2 summarizes the resulting VMT

data by vehicle type and shows the fraction of VMT in each of the MOBILE5 vehicle categories.

Speeds modeled in this analysis, both in 1996 and the projection years, were constant by

vehicle class and functional road class throughout the nation. In other words, the same speeds

were modeled in all analysis years, and the speeds depended upon the vehicle type and road type. 

The origin of these speed data is an analysis performed on output from the HPMS impact

analysis for 1990 (FHWA, 1990). Speeds from this analysis year were consistent with speeds

from earlier analysis years. Table VI-3 shows the speeds modeled.
VI-2

Table VI-1

HPMS to MOBILE5 VMT Vehicle Category Assignments

HPMS VMT Vehicle Category MOBILE5 VMT Vehicle Category 1996 VMT Fraction

Motorcycle MC 1.0000

Passenger Car LDGV 0.9945

LDDV 0.0055

Buses HDGV 0.3077

HDDV 0.6923

Other 2-axle, 4-tire vehicles LDGT1 0.6621

LDGT2 0.2284

LDDT 0.0054

HDGV 0.0759

HDDV 0.0282

Single-unit 2-axle 6-tire or more trucks HDGV 0.2925

HDDV 0.7075

Combination trucks HDGV 0.0000

HDDV 1.0000

Table VI-2

National 1996 VMT by Vehicle Type for HDD Analysis

Vehicle Type 1996 VMT (million miles) 1996 VMT Fractions

LDGV 1,455,403 0.5880

LDGT1 538,255 0.2175

LDGT2 185,684 0.0750

HDGV 82,355 0.0333

LDDV 8,054 0.0033

LDDT 4,388 0.0018

HDDV 190,994 0.0772

MC 9,872 0.0040

Total 2,475,004 1.0000
VI-3

Table VI-3

Average Speeds by Road Type and Vehicle Type

(Miles per Hour)

Rural Roadway Types

Interstate

Principal

Arterial

Minor 

Arterial

Major 

Collector

Minor

Collector Local

LDV 60 45 40 35 30 30

LDT 55 45 40 35 30 30

HDV 40 35 30 25 25 25

Urban Roadway Types

Interstate

Other Freeways

& Expressways

Principal

Arterial

Minor

Arterial Collector Local

LDV 45 45 20 20 20 20

LDT 45 45 20 20 20 20

HDV 35 35 15 15 15 15

Vehicle registration distributions by vehicle age used in the 1996 NET include distributions

provided by States through OTAG and the NOx SIP Call. Areas with no specified registration

distribution were modeled with registration distributions by vehicle type developed based on

national sales and registration data for 1996. The same registration distributions used in 1996

were also applied in both projection years. These registration distributions by age differ by the

MOBILE5b vehicle categories.

Temperatures for 1996 were based on the average historical 1996 monthly maximum and

minimum daily temperatures reported in a city selected to be representative of temperatures

within a given State. Emission factors were calculated at the monthly level using these monthly

temperatures. Monthly RVP data were also used in the MOBILE5b inputs. These inputs were

based on January and July RVP data from American Automobile Manufacturers Association’s

(AAMA’s) fuel surveys (AAMA, 1996), and then allocated by month and area. More details on

the temperature inputs and the RVP allocation procedures can be found in the Trends procedures

document (EPA, 1998b).

In addition to the inputs described above, control programs were modeled in 1996, as

discussed below.
VI-4

1. Inspection and Maintenance (I/M) Programs

Inspection and maintenance (I/M) programs were modeled in areas with such programs in

place in 1996. The actual I/M inputs and the counties included in these programs were based on

data collected in the OTAG process, as well as from state-level I/M program summary

information provided by OTAQ (Somers, 1997a). The vehicle types affected by these programs

vary by area but can include light-duty gasoline vehicles (LDGVs) and trucks (LDGT1s and

LDGT2s) and heavy-duty gasoline vehicles (HDGVs).

2. RFG

Phase 1 of the Federal RFG program was modeled in the 1996 MOBILE5b inputs. The areas

and counties that were modeled with RFG are shown in Table VI-4. Data on the RFG coverage

was provided by OTAQ. The summertime RFG benefits were applied from May through

September, while the winter RFG benefits were applied in the remaining months. California was

modeled with the benefits of the Federal RFG program applied Statewide.

3. Oxygenated Gasoline

Oxygenated gasoline was modeled in the areas participating in this program in 1996. A

listing of these areas was provided by OTAQ (Somers, 1997b), along with the months that the

oxygenated gasoline program was in place in these areas and the market share of ether and

alcohol blends. The average oxygen content of ether blend fuels was assumed to be 2.7 percent in

all oxygenated gasoline areas and the average oxygen content of alcohol blend fuels was assumed

to be 3.5 percent in all oxygenated gasoline areas. Table VI-5 lists the counties modeled with

oxygenated gasoline and the corresponding fuel parameters.

4. Low Emission Vehicle (LEV) Programs

 In the 1996 analysis year, LEV programs were modeled in California, Massachusetts, and

New York. The California program was modeled with a 1994 start year, using the MOBILE5

default LEV schedule. The LEV programs in Massachusetts and New York were modeled with

start years of 1995 and 1996, respectively, with 15 percent of 1995 model year new vehicle sales

(in Massachusetts only) meeting the intermediate Transitional LEV (TLEV) emission standards,

20 percent of 1996 model year new vehicle sales meeting the TLEV emission standards, and the

remaining new vehicle sales meeting the Federal Tier I emission standards. The LEV programs

affect LDGVs and LDGT1s.
VI-5

Table VI-4

Counties Modeled with Federal Reformulated Gasoline (RFG)

State/ State/

Nonattainment Area County Nonattainment Area County

Arizona (Southern RFG) Maine (Northern RFG)

Phoenix Knox & Lincoln Counties

Maricopa Co Knox Co

Connecticut (Northern RFG) Lincoln Co

Greater Connecticut Lewiston-Auburn

Hartford Co Androscoggin Co

Litchfield Co Kennebec Co

Middlesex Co Portland

New Haven Co Cumberland Co

New London Co Sagadahoc Co

Tolland Co York Co

Windham Co Maryland (Southern RFG)

New York-Northern New Jersey-Long Island Baltimore

Fairfield Co Anne Arundel Co

District of Columbia (Southern RFG) Baltimore

Washington DC Baltimore Co

Washington Carroll Co

Delaware (Northern RFG) Harford Co

Philadelphia-Wilmington-Trenton Howard Co

Kent Co Kent & Queen Annes Counties

New Castle Co Kent Co

Sussex County Queen Annes Co

Sussex Co Philadelphia-Wilmington-Trenton

Illinois (Northern RFG) Cecil Co

Chicago-Gary-Lake County Washington DC

Cook Co Calvert Co

Du Page Co Charles Co

Grundy Co Frederick Co

Kane Co Montgomery Co

Kendall Co Prince Georges Co

Lake Co Massachusetts (Northern RFG)

McHenry Co Boston-Lawrence-Worcester-Eastern MA

Will Co Barnstable Co

Indiana (Northern RFG) Bristol Co

Chicago-Gary-Lake County Dukes Co

Lake Co Essex Co

Porter Co Middlesex Co

Kentucky (Northern RFG) Nantucket Co

Cincinnati-Hamilton Norfolk Co

Boone Co Plymouth Co

Campbell Co Suffolk Co

Kenton Co Worcester Co

Louisville Springfield/Pittsfield-Western MA

Bullitt Co Berkshire Co

Jefferson Co Franklin Co
Table VI-4 (continued)

State/ State/

Nonattainment Area County Nonattainment Area County

VI-6

Oldham Co Hampden Co

Hampshire Co

New Hampshire (Northern RFG) New York (Northern RFG)

Manchester Poughkeepsie

Hillsborough Co Dutchess Co

Merrimack Co Putnam Co

Portsmouth-Dover-Rochester Pennsylvania (Northern RFG)

Rockingham Co Philadelphia-Wilmington-Trenton

Strafford Co Bucks Co

New Jersey (Northern RFG) Chester Co

Allentown-Bethlehem-Easton Delaware Co

Warren Co Montgomery Co

Atlantic City Philadelphia Co

Atlantic Co Rhode Island (Northern RFG)

Cape May Co Providence

New York-Northern New Jersey-Long Island Bristol Co

Bergen Co Kent Co

Essex Co Newport Co

Hudson Co Providence Co

Hunterdon Co Washington Co

Middlesex Co Texas (Southern RFG)

Monmouth Co Dallas-Fort Worth

Morris Co Collin Co

Ocean Co Dallas Co

Passaic Co Denton Co

Somerset Co Tarrant Co

Sussex Co Houston-Galveston-Brazoria

Union Co Brazoria Co

Philadelphia-Wilmington-Trenton Chambers Co

Burlington Co Fort Bend Co

Camden Co Galveston Co

Cumberland Co Harris Co

Gloucester Co Liberty Co

Mercer Co Montgomery Co

Salem Co Waller Co

New York (Northern RFG) Virginia (Southern RFG)

New York-Northern New Jersey-Long Island Norfolk-Virginia Beach-Newport News

Bronx Co Chesapeake

Kings Co Hampton

Nassau Co James City Co

New York Co Newport News

Orange Co Norfolk

Queens Co Poquoson

Richmond Co Portsmouth

Rockland Co Suffolk

Suffolk Co Virginia Beach

Westchester Co Williamsburg
Table VI-4 (continued)

State/ State/

Nonattainment Area County Nonattainment Area County

VI-7

York Co

Virginia (Southern RFG) Wisconsin (Northern RFG)

Richmond-Petersburg Milwaukee-Racine

Charles City Co Kenosha Co

Chesterfield Co Milwaukee Co

Colonial Heights Ozaukee Co

Hanover Co Racine Co

Henrico Co Washington Co

Hopewell Waukesha Co

Richmond

Washington DC

Alexandria

Arlington Co

Fairfax

Fairfax Co

Falls Church

Loudoun Co

Manassas

Manassas Park

Prince William Co

Stafford Co

NOTE: Federal reformulated gasoline was modeled statewide in California. Certain RFG fuel property requirements differ

depending on whether an area receives Northern or Southern RFG.
VI-8

Table VI-5

Oxygenated Gasoline Modeling Parameters

Market Shares (%) Oxygen Content (%) Oxygenated

State County MTBE Alcohol Blends MTBE Alcohol Blends Gasoline Season

Alaska Anchorage Ed 0 100 2.7 3.5 NOV-FEB (2007, 2020, & 2030)

Alaska Anchorage Ed 0 100 2.7 3.5 NOV-DEC (1996 only)

Arizona Maricopa Co 80 20 2.7 3.5 OCT-FEB

Colorado Adams Co 75 25 2.7 3.5 NOV-FEB

Colorado Arapahoe Co 75 25 2.7 3.5 NOV-FEB

Colorado Boulder Co 75 25 2.7 3.5 NOV-FEB

Colorado Douglas Co 75 25 2.7 3.5 NOV-FEB

Colorado Jefferson Co 75 25 2.7 3.5 NOV-FEB

Colorado Denver Co 75 25 2.7 3.5 NOV-FEB

Colorado El Paso Co 75 25 2.7 3.5 NOV-FEB

Colorado Larimer Co 75 25 2.7 3.5 NOV-FEB

Connecticut Fairfield Co 90 10 2.7 3.5 NOV-FEB

Minnesota Anoka Co 10 90 2.7 3.5 OCT-JAN

Minnesota Carver Co 10 90 2.7 3.5 OCT-JAN

Minnesota Dakota Co 10 90 2.7 3.5 OCT-JAN

Minnesota Hennepin Co 10 90 2.7 3.5 OCT-JAN

Minnesota Ramsey Co 10 90 2.7 3.5 OCT-JAN

Minnesota Scott Co 10 90 2.7 3.5 OCT-JAN

Minnesota Washington Co 10 90 2.7 3.5 OCT-JAN

Minnesota Wright Co 10 90 2.7 3.5 OCT-JAN

Minnesota Chisago Co 10 90 2.7 3.5 OCT-JAN

Minnesota Isanti Co 10 90 2.7 3.5 OCT-JAN

Montana Missoula Co 0 100 2.7 3.5 NOV-FEB

Nevada Clark Co 0 100 2.7 3.5 OCT-MAR

Nevada Washoe Co 95 5 2.7 3.5 OCT-JAN

New Jersey Bergen Co 95 5 2.7 3.5 NOV-FEB

New Jersey Essex Co 95 5 2.7 3.5 NOV-FEB

New Jersey Hudson Co 95 5 2.7 3.5 NOV-FEB

New Jersey Hunterdon Co 95 5 2.7 3.5 NOV-FEB

New Jersey Mercer Co 95 5 2.7 3.5 JAN-FEB (1996 only)

New Jersey Middlesex Co 95 5 2.7 3.5 NOV-FEB

New Jersey Monmouth Co 95 5 2.7 3.5 NOV-FEB

New Jersey Morris Co 95 5 2.7 3.5 NOV-FEB

New Jersey Ocean Co 95 5 2.7 3.5 NOV-FEB

New Jersey Passaic Co 95 5 2.7 3.5 NOV-FEB

New Jersey Somerset Co 95 5 2.7 3.5 NOV-FEB

New Jersey Sussex Co 95 5 2.7 3.5 NOV-FEB

New Jersey Union Co 95 5 2.7 3.5 NOV-FEB

New Mexico Bernalillo Co 15 85 2.7 3.5 JAN-FEB (1996 only)

New York Bronx Co 95 5 2.7 3.5 NOV-FEB

New York Kings Co 95 5 2.7 3.5 NOV-FEB
Market Shares (%) Oxygen Content (%) Oxygenated

State County MTBE Alcohol Blends MTBE Alcohol Blends Gasoline Season

VI-9

New York Nassau Co 95 5 2.7 3.5 NOV-FEB

New York New York Co 95 5 2.7 3.5 NOV-FEB

New York Queens Co 95 5 2.7 3.5 NOV-FEB

New York Richmond Co 95 5 2.7 3.5 NOV-FEB

New York Rockland Co 95 5 2.7 3.5 NOV-FEB

New York Suffolk Co 95 5 2.7 3.5 NOV-FEB

New York Westchester

Co

95 5 2.7 3.5 NOV-FEB

New York Orange Co 95 5 2.7 3.5 NOV-FEB

New York Putnam Co 95 5 2.7 3.5 NOV-FEB

Oregon Clackamas Co 1 99 2.7 3.5 NOV-FEB

Oregon Jackson Co 1 99 2.7 3.5 NOV-FEB

Oregon Multnomah Co 1 99 2.7 3.5 NOV-FEB

Oregon Washington Co 1 99 2.7 3.5 NOV-FEB

Oregon Josephine Co 1 99 2.7 3.5 NOV-FEB

Oregon Klamath Co 1 99 2.7 3.5 NOV-FEB

Oregon Yamhill Co 1 99 2.7 3.5 NOV-FEB

Texas El Paso Co 15 85 2.7 3.5 NOV-FEB

Utah Utah Co 20 80 2.7 3.5 NOV-FEB

Washington Clark Co 1 99 2.7 3.5 NOV-FEB

Washington King Co 1 99 2.7 3.5 JAN-FEB (1996 only)

Washington Snohomish Co 1 99 2.7 3.5 JAN-FEB (1996 only)

Washington Spokane Co 1 99 2.7 3.5 SEP-FEB

Wisconsin St. Croix Co 10 90 2.7 3.5 OCT-JAN

5. MOBILE5 to MOBILE6 Adjustment Factors

VOC, NOx, and CO on-highway vehicle emission factors were calculated using the above

inputs and EPA’s MOBILE5b emission factor model. Emission factors for on-highway SO2,

PM10, and PM2.5 were calculated using EPA’s PART5 model and NH3 emission factors for onhighway vehicles were calculated using national vehicle-specific emission factors (Harvey,

1983). Various adjustment factors were then applied to the MOBILE5b VOC and NOx emission

factors to simulate emission factors that would result from using MOBILE6, as well as

accounting for issues not included in MOBILE5b. Each of these adjustments are discussed

below. All of the adjustment factors discussed in these sections were provided by OTAQ.

a. VOC and NOx Exhaust Adjustments

Adjustment factors to convert the MOBILE5b emission factors to MOBILE6 emission

factors were applied to the VOC exhaust and NOx MOBILE5b output emission factors for

LDGVs, LDGT1s, LDGT2s, HDGVs, LDDVs, and LDDTs. These factors varied by vehicle type

and by control combination. The control combination included one of three fuel types

(conventional gasoline, western gasoline, and reformulated gasoline) and one of three I/M
VI-10

categories (no I/M, I/M, and appropriate I/M). (An appropriate I/M program is defined as one

that meets EPA’s requirements to be modeled with the maximum LEV benefits.) Each county in

the nation was assigned one of these control combinations. The corresponding adjustment factor

was then applied to each monthly, vehicle type emission factor for each county in the nation. 

Table VI-6 lists the exhaust VOC MOBILE5b to MOBILE6 adjustment factors applied in 1996

and the projection years and Table VI-7 lists the NOx MOBILE5b to MOBILE6 adjustment

factors. Both tables are by vehicle type and control combination.

b. Air Conditioning Usage Factors

An additional adjustment was applied to the NOx LDGV, LDGT1, and LDGT2 emission

factors (already adjusted, as above to MOBILE6 emission rates) in 1996. This adjustment

accounted for the additional NOx emissions that would occur with air conditioning usage that is

not included in the MOBILE5 emission factors. The air conditioning usage factors consist of two

components: a factor simulating full air conditioning usage and a temperature dependent factor

that adjusts the full usage factor for usage at the given temperature. These two factors were

multiplied and then added to the MOBILE6-adjusted NOx emission factors. The full usage factor

is dependent upon vehicle type and the same control combinations listed with the MOBILE6

adjustments (with the exception that areas with both I/M and appropriate I/M are categorized

together for this adjustment). Table VI-8 lists the full usage NOx air conditioning usage factors. 

The air conditioning adjustment becomes 0 below temperatures of 68(F. Above temperatures of

109(F, the full usage factor is applied directly. The temperatures used to calculate this

adjustment were the ambient temperatures calculated by MOBILE5b and included in the

MOBILE5b output files. The temperature dependent equation is as follows:

Temp Adj = -3.631541 + 0.072465 * AMBTEMP - 0.000276 * (AMBTEMP^2)

This temperature adjustment was then multiplied by the corresponding full usage factor and the

result was added to the MOBILE6-adjusted NOx emission factors.

c. HDDV Adjustment Factors

The final set of adjustment factors applied to the 1996 on-highway vehicle emission

inventories is the set of HDDV adjustment factors. These factors account for the emission factor

updates from data collected by OTAQ for MOBILE6 for VOC, NOx, CO, SO2, PM10, and PM2.5

as well as the NOx emission changes due to the use of the HDDV defeat devices. The factors

vary by roadway type, as shown in Table VI-9.
VI-11

Table VI-6

Exhaust VOC MOBILE5b to MOBILE6 Adjustment Factors

Adjustment Factor by Vehicle Type (unitless)

Year Control Combination LDGV LDGT1 LDGT2 LDDV LDDT HDGV

1996 APP IM CG 0.880 0.896 1.132 1.231 1.385 0.574

APP IM RFG 0.969 0.973 1.203 1.231 1.385 0.574

APP IM WEST 0.880 0.896 1.132 1.231 1.385 0.574

IM CG 0.880 0.896 1.132 1.231 1.385 0.574

IM RFG 0.969 0.973 1.203 1.231 1.385 0.574

IM WEST 0.880 0.896 1.132 1.231 1.385 0.574

NO IM CG 0.787 0.834 1.020 1.231 1.385 0.574

NO IM RFG 0.870 0.905 1.084 1.231 1.385 0.574

NO IM WEST 0.787 0.834 1.020 1.231 1.385 0.574

2007 APP IM CG 0.700 0.805 0.758 0.917 0.874 0.431

APP IM RFG 0.849 0.969 0.973 0.907 0.853 0.431

APP IM WEST 0.745 0.857 0.828 0.917 0.874 0.431

IM CG 0.568 0.621 0.758 0.917 0.874 0.431

IM RFG 0.682 0.742 0.973 0.907 0.853 0.431

IM WEST 0.605 0.661 0.828 0.917 0.874 0.431

NO IM CG 0.502 0.545 0.640 0.939 0.907 0.431

NO IM RFG 0.608 0.652 0.826 0.905 0.881 0.431

NO IM WEST 0.532 0.575 0.699 0.939 0.907 0.431

2020 APP IM CG 1.496 1.233 0.302 0.319 0.271 0.191

APP IM RFG 1.751 1.443 0.347 0.288 0.229 0.191

APP IM WEST 1.499 1.235 0.303 0.319 0.271 0.191

IM CG 0.297 0.282 0.302 0.319 0.271 0.191

IM RFG 0.344 0.327 0.347 0.288 0.229 0.191

IM WEST 0.297 0.282 0.303 0.319 0.271 0.191

NO IM CG 0.277 0.284 0.263 0.386 0.476 0.191

NO IM RFG 0.337 0.346 0.309 0.440 0.409 0.191

NO IM WEST 0.278 0.284 0.264 0.386 0.476 0.191

2030 APP IM CG 1.644 1.509 0.201 0.285 0.266 0.165

APP IM RFG 1.925 1.766 0.241 0.253 0.222 0.165

APP IM WEST 1.645 1.511 0.202 0.285 0.266 0.165

IM CG 0.273 0.258 0.201 0.285 0.266 0.165

IM RFG 0.321 0.303 0.241 0.253 0.222 0.165

IM WEST 0.274 0.258 0.202 0.285 0.266 0.165

NO IM CG 0.263 0.268 0.200 0.355 0.494 0.165

NO IM RFG 0.324 0.330 0.249 0.422 0.424 0.165

NO IM WEST 0.263 0.268 0.200 0.355 0.494 0.165
VI-12

Table VI-7

NOx MOBILE5b to MOBILE6 Adjustment Factors

Adjustment Factor by Vehicle Type (unitless)

Year Control Combination LDGV LDGT1 LDGT2 LDDV LDDT HDGV

1996 APP IM CG 0.948 0.948 1.037 1.104 1.152 0.908

APP IM RFG 0.965 0.961 1.045 1.104 1.152 0.908

APP IM WEST 0.948 0.948 1.037 1.104 1.152 0.908

IM CG 0.948 0.948 1.037 1.104 1.152 0.908

IM RFG 0.965 0.961 1.045 1.104 1.152 0.908

IM WEST 0.948 0.948 1.037 1.104 1.152 0.908

NO IM CG 0.885 0.875 0.976 1.104 1.152 0.908

NO IM RFG 0.901 0.886 0.984 1.104 1.152 0.908

NO IM WEST 0.885 0.875 0.976 1.104 1.152 0.908

2007 APP IM CG 0.724 0.936 0.741 0.740 0.694 0.675

APP IM RFG 0.761 0.977 0.772 0.739 0.688 0.675

APP IM WEST 0.748 0.967 0.754 0.740 0.694 0.675

IM CG 0.590 0.766 0.741 0.740 0.694 0.675

IM RFG 0.620 0.801 0.772 0.739 0.688 0.675

IM WEST 0.610 0.791 0.754 0.740 0.694 0.675

NO IM CG 0.556 0.710 0.652 0.741 0.719 0.675

NO IM RFG 0.584 0.743 0.679 0.740 0.714 0.675

NO IM WEST 0.573 0.732 0.663 0.741 0.719 0.675

2020 APP IM CG 0.550 0.471 0.300 0.144 0.158 0.288

APP IM RFG 0.583 0.497 0.314 0.143 0.155 0.288

APP IM WEST 0.556 0.476 0.303 0.144 0.158 0.288

IM CG 0.184 0.212 0.300 0.144 0.158 0.288

IM RFG 0.195 0.224 0.314 0.143 0.155 0.288

IM WEST 0.186 0.214 0.303 0.144 0.158 0.288

NO IM CG 0.235 0.283 0.306 0.234 0.285 0.288

NO IM RFG 0.250 0.300 0.321 0.226 0.280 0.288

NO IM WEST 0.238 0.286 0.309 0.234 0.285 0.288

2030 APP IM CG 0.474 0.424 0.180 0.118 0.161 0.208

APP IM RFG 0.505 0.450 0.189 0.116 0.159 0.208

APP IM WEST 0.476 0.428 0.184 0.118 0.161 0.208

IM CG 0.148 0.176 0.180 0.118 0.161 0.208

IM RFG 0.157 0.187 0.189 0.116 0.159 0.208

IM WEST 0.149 0.178 0.184 0.118 0.161 0.208

NO IM CG 0.207 0.252 0.222 0.219 0.303 0.208

NO IM RFG 0.220 0.267 0.233 0.210 0.298 0.208

NO IM WEST 0.207 0.254 0.225 0.219 0.303 0.208
VI-13

Table VI-8

NOx Full Usage Air Conditioning Adjustment Factors

Adjustment Factor by Vehicle Type

(grams/mile)

Year Control Combination LDGV LDGT1 LDGT2

1996 IM CG 0.321 0.194 0.252

IM RFG 0.321 0.194 0.252

IM WEST 0.321 0.194 0.252

NO IM CG 0.347 0.207 0.266

NO IM RFG 0.347 0.207 0.266

NO IM WEST 0.347 0.207 0.266

2007 IM CG 0.195 0.142 0.179

IM RFG 0.190 0.138 0.176

IM WEST 0.202 0.146 0.182

NO IM CG 0.222 0.163 0.195

NO IM RFG 0.217 0.159 0.192

NO IM WEST 0.230 0.167 0.198

2020 IM CG 0.063 0.047 0.072

IM RFG 0.062 0.046 0.071

IM WEST 0.063 0.047 0.073

NO IM CG 0.093 0.073 0.099

NO IM RFG 0.092 0.072 0.097

NO IM WEST 0.094 0.073 0.099

2030 IM CG 0.055 0.041 0.054

IM RFG 0.054 0.040 0.053

IM WEST 0.055 0.041 0.055

NO IM CG 0.085 0.068 0.083

NO IM RFG 0.084 0.067 0.082

NO IM WEST 0.085 0.068 0.084
VI-14

Table VI-9

HDDV Base Case Adjustment Factors

Adjustment Factor (unitless)

Year Facility Description VOC CO NOx PM SO2

1996 Interstate Rural Interstate 0.6858 0.8030 2.2973 0.8666 0.7063

Interstate Rural Other Prin Arterial 0.6858 0.8030 2.2973 0.8666 0.7063

Interstate Urban Interstate 0.6858 0.8030 2.2973 0.8666 0.7063

Interstate Urban Other Freeways 0.6858 0.8030 2.2973 0.8666 0.7063

Arterial Rural Minor Arterial 0.5712 0.6106 1.2723 0.7110 0.6085

Arterial Rural Major Collector 0.5712 0.6106 1.2723 0.7110 0.6085

Arterial Rural Minor Collector 0.5712 0.6106 1.2723 0.7110 0.6085

Arterial Rural Local 0.5712 0.6106 1.2723 0.7110 0.6085

Urban Urban Other Prin Arterial 0.5916 0.6275 1.0240 0.7549 0.6268

Urban Urban Minor Arterial 0.5916 0.6275 1.0240 0.7549 0.6268

Urban Urban Collector 0.5916 0.6275 1.0240 0.7549 0.6268

Urban Urban Local 0.5916 0.6275 1.0240 0.7549 0.6268

2007 Interstate Rural Interstate 0.3750 0.4076 1.6939 0.9564 0.6968

Interstate Rural Other Prin Arterial 0.3750 0.4076 1.6939 0.9564 0.6968

Interstate Urban Interstate 0.3750 0.4076 1.6939 0.9564 0.6968

Interstate Urban Other Freeways 0.3750 0.4076 1.6939 0.9564 0.6968

Arterial Rural Minor Arterial 0.3153 0.3191 1.1260 0.7918 0.6077

Arterial Rural Major Collector 0.3153 0.3191 1.1260 0.7918 0.6077

Arterial Rural Minor Collector 0.3153 0.3191 1.1260 0.7918 0.6077

Arterial Rural Local 0.3153 0.3191 1.1260 0.7918 0.6077

Urban Urban Other Prin Arterial 0.3090 0.3203 1.0908 0.7924 0.6264

Urban Urban Minor Arterial 0.3090 0.3203 1.0908 0.7924 0.6264

Urban Urban Collector 0.3090 0.3203 1.0908 0.7924 0.6264

Urban Urban Local 0.3090 0.3203 1.0908 0.7924 0.6264

2020 Interstate Rural Interstate 0.3229 0.3721 1.7099 0.9220 0.6506

Interstate Rural Other Prin Arterial 0.3229 0.3721 1.7099 0.9220 0.6506

Interstate Urban Interstate 0.3229 0.3721 1.7099 0.9220 0.6506

Interstate Urban Other Freeways 0.3229 0.3721 1.7099 0.9220 0.6506

Arterial Rural Minor Arterial 0.2499 0.2852 1.3144 0.7506 0.5799

Arterial Rural Major Collector 0.2499 0.2852 1.3144 0.7506 0.5799

Arterial Rural Minor Collector 0.2499 0.2852 1.3144 0.7506 0.5799

Arterial Rural Local 0.2499 0.2852 1.3144 0.7506 0.5799

Urban Urban Other Prin Arterial 0.2351 0.2786 1.3130 0.7262 0.6005

Urban Urban Minor Arterial 0.2351 0.2786 1.3130 0.7262 0.6005

Urban Urban Collector 0.2351 0.2786 1.3130 0.7262 0.6005

Urban Urban Local 0.2351 0.2786 1.3130 0.7262 0.6005

2030 Interstate Rural Interstate 0.3103 0.3658 1.7078 0.9131 0.5948

Interstate Rural Other Prin Arterial 0.3103 0.3658 1.7078 0.9131 0.5948

Interstate Urban Interstate 0.3103 0.3658 1.7078 0.9131 0.5948

Interstate Urban Other Freeways 0.3103 0.3658 1.7078 0.9131 0.5948

Arterial Rural Minor Arterial 0.2394 0.2809 1.3586 0.7411 0.5390

Arterial Rural Major Collector 0.2394 0.2809 1.3586 0.7411 0.5390

Arterial Rural Minor Collector 0.2394 0.2809 1.3586 0.7411 0.5390

Arterial Rural Local 0.2394 0.2809 1.3586 0.7411 0.5390

Urban Urban Other Prin Arterial 0.2251 0.2746 1.3713 0.7161 0.5606

Urban Urban Minor Arterial 0.2251 0.2746 1.3713 0.7161 0.5606

Urban Urban Collector 0.2251 0.2746 1.3713 0.7161 0.5606

Urban Urban Local 0.2251 0.2746 1.3713 0.7161 0.5606
VI-15

B. 2007, 2020, AND 2030 FUTURE YEAR MASS EMISSIONS INVENTORIES

This section summarizes the growth assumptions made and control programs applied to

calculate the 2007, 2020, and 2030 on-highway vehicle emission inventories. As discussed

above, the registration distributions and speeds modeled in 1996 were also used in the projection

years. The temperatures modeled in the projection years represented State-specific average

monthly maximum and minimum daily temperatures averaged from 1970 through 1997 using

data from the National Climatic Data Center. The same temperatures were modeled in 2007,

2020, and 2030.

1. Growth Assumptions

The VMT used in 2007, 2020, and 2030 were projected from 1996, using VMT projection

data from EPA’s Tier 2 rulemaking (EPA, 1999c). First, VMT from the Tier 2 analysis were

totaled by county and vehicle type for 1996 and the projection years. Next, each VMT record

from the 1996 data base (at the county, vehicle type, and roadway type level of detail) developed

for this HDD rulemaking analysis and discussed earlier in this chapter was multiplied by the ratio

of the corresponding Tier 2 projection year VMT to the 1996 Tier 2 VMT (both at the county and

vehicle type level of detail). In this manner, the 1996 VMT shifts by vehicle class from the Tier

2 analysis to the HDD analysis were projected to the future using the area and vehicle typespecific growth factors from the Tier 2 analysis. The resulting projection year VMT and the

corresponding VMT fractions by vehicle type are shown in Table VI-10.

Table VI-10

National VMT Projections and VMT Fractions by Vehicle Type for HDD Analysis

Vehicle Annual VMT (million miles) VMT Fractions

Type 2007 2020 2030 2007 2020 2030

LDGV 1,245,991 1,283,189 1,311,807 0.397 0.329 0.292

LDGT1 1,207,617 1,670,987 2,027,426 0.385 0.428 0.452

LDGT2 268,323 371,876 451,534 0.086 0.095 0.101

HDGV 119,002 165,884 201,948 0.038 0.043 0.045

LDDV 0 0 0 0.000 0.000 0.000

LDDT 4,108 5,112 5,885 0.001 0.001 0.001

HDDV 275,722 384,106 467,480 0.088 0.098 0.104

MC 14,265 19,885 24,208 0.005 0.005 0.005

Total 3,135,027 3,901,040 4,490,287 1.000 1.000 1.000

2. Base Case Control Assumptions

This section summarizes the control programs that were modeled for highway vehicles in

2007, 2020, and 2030. The Control Case was modeled by applying reduction percentages to the

heavy-duty gasoline vehicle (HDGV) and HDDV Base Case emissions and additional SO2

reductions to light-duty diesel emissions. 
VI-16

a. I/M Programs

I/M program inputs were the same in all of the projection years. The default program

parameters for counties expected to have I/M programs in place in the projection years are the

EPA performance standard I/M program inputs. The specific inputs modeled for each of the I/M

program performance standards are shown in Table VI-11. I/M program 

Table VI-11

I/M Performance Standard Program Inputs

I/M Program Name

Basic I/M

Performance

Standard

Low Enhanced I/M

Performance

Standard

High Enhanced

I/M Performance

Standard

I/M Program Parameters

Program Start Year 1983 1983 1983

Stringency Level (Percent) 20 20 20

Model Years Covered 1968-2020 1968-2020 1968-1985

Waiver Rate For Pre-1981 Model Years (%) 0 3 3

Waiver Rate For 1981 and Later Models (%) 0 3 3

Compliance Rate (%) 100 96 96

Program Type TO TO TO

Inspection Frequency Annual Annual Annual

Vehicle Types Inspected

 LDGV YES YES YES

 LDGT1 NO YES YES

 LDGT2 NO YES YES

 HDGV NO NO NO

Test Type IdleTest IdleTest 2500/IdleTest

I/M Cutpoints 220/1.2/999 220/1.2/999 220/1.2/999

Effectiveness Rates (% hydrocarbon

(HC)/CO/NOx)

1.00/1.00/1.00 1.00/1.00/1.00 1.00/1.00/1.00

Program Start Year 1983

Stringency Level (Percent) 20

Model Years Covered 1986-2020

Waiver Rate For Pre-1981 Model Years (%) 3

Waiver Rate For 1981 and Later Models (%) 3

Compliance Rate (%) 96

Program Type TO

Inspection Frequency Annual

Vehicle Types Inspected

 LDGV YES

 LDGT1 YES

 LDGT2 YES

 HDGV NO

Test Type TransientTest

I/M Cutpoints (g/mi HC/CO/NOx) 0.80/20.0/2.00

Effectiveness Rates (% HC/CO/NOx) 1.00/1.00/1.00

Anti-Tampering Program Parameters

Program Start Year 1995 1995

Model Years Covered 1972-2020 1984-2020
Table VI-11 (continued)

I/M Program Name

Basic I/M

Performance

Standard

Low Enhanced I/M

Performance

Standard

High Enhanced

I/M Performance

Standard

I/M Program Parameters

VI-17

Vehicle Types Inspected

 LDGV YES YES

 LDGT1 YES YES

 LDGT2 YES YES

 HDGV NO NO

Program Type TO TO

Effectiveness Rate 1.00 1.00

Inspection Frequency Annual Annual

Compliance Rate (%) 96 96

Inspections Performed

 Air Pump System NO NO

 Catalyst NO YES

 Fuel Inlet Restrictor NO YES

 Tailpipe Lead Deposit Test NO NO

 EGR System YES NO

 Evaporative Emission Control System NO NO

 PCV System NO NO

 Gas Cap NO NO

Functional Pressure Test Program Parameters

Program Start Year 1995

Model Years Covered 1983-2020

Effectiveness Rate 1.00

Vehicle Types Tested

 LDGV YES

 LDGT1 YES

 LDGT2 YES

 HDGV NO

Program Type TO

Inspection Frequency Annual

Compliance Rate (%) 96

Purge Test Program Parameters

Program Start Year 1995

Model Years Covered 1986-2020

Effectiveness Rate 1.00

Vehicle Types Tested

 LDGV YES

 LDGT1 YES

 LDGT2 YES

 HDGV NO

Program Type TO

Inspection Frequency Annual

Compliance Rate (%) 96

NOTES: TO=Test Only

TRC=Test And Repair (Computerized)
VI-18

coverage by county or area was based on data collected by EPA and Pechan for the OTAG and

Section 812 emission projections. During this data collection process, each State was contacted

to confirm which counties in that State would be implementing an I/M program in the future. 

Each State was also asked to indicate which of the EPA I/M program types the program would

most closely resemble  high enhanced, low enhanced, basic, or Ozone Transport Region (OTR)

low enhanced. Responses were collected from each State with a planned CAA I/M program. 

Any additional I/M-specific information collected during comment periods for EPA’s NOx SIP

Call, and accepted by EPA, superseded the default and OTAG I/M data.

b. RFG

Phase II of this Federal RFG program was modeled in the projection years. Coverage of

RFG in the projection years was the same as that in 1996, with the following exceptions: all

Maine counties and Orange County, NY were removed from the 1996 list, shown in Table VI-4. 

The entire State of California was modeled with Federal Phase II RFG (ASTM Class B) in the

projection years. Areas not participating in the RFG program were modeled during the ozone

season months with Phase II RVP values of either 8.7 pounds per square inch (psi) or 7.8 psi. 

Areas that provided SIP Call comments documenting the presence of a low RVP program were

modeled at that RVP during the ozone season. 

c. Oxygenated Fuel

The oxygenated fuel program inputs and county coverages modeled are the same as those

described for 1996, with the specific changes listed in Table VI-5 for several of the areas for

2007, 2020, and 2030.

d. National LEV (NLEV) Program

The NLEV program was included for all States in the projection year modeling. This

program starts with the 2001 model year nationwide, and in 1999 in the Northeast Ozone

Transport Commission (OTC) States. The implementation schedule of the NLEV program in the

OTC States is shown below.

Model Year

Federal Tier I

Standards

Transitional LEV

Standards LEV Standards

1999 30% 40% 30%

2000 40% 60%

2001 and later 100%

States in the OTC that have adopted a LEV program on their own were modeled with the

characteristics of their programs. These States include Massachusetts, New York, Vermont, and

Maine. California’s LEV program began in 1994. This was modeled using the MOBILE5b

default LEV implementation schedule, along with a start year of 1994 for this program.

The following table shows the emission standards of the Federal Tier I program, the

transitional LEV (TLEV) standards, the LEV standards, and the Ultra-Low Emission Vehicle
VI-19

(ULEV) standards. These standards apply to the LDGV and LDGT1a classes of vehicles. The

LDGT1b category is also included in the NLEV program, but the emission standards for these

vehicles are slightly less stringent than those listed below for the lighter vehicles.

Emission Standard

Nonmethane Organic 

Gas (NMOG) CO NOx

Federal Tier 1 0.250 grams/mile nonmethane

hydrocarbon (NMHC)

3.4 grams/mile 0.40 grams/mile

TLEV 0.125 grams/mile 3.4 grams/mile 0.40 grams/mile

LEV 0.075 grams/mile 3.4 grams/mile 0.20 grams/mile

ULEV 0.040 grams/mile 1.7 grams/mile 0.20 grams/mile

e. 2004 NOx Standard for Heavy-Duty Diesel Engines

EPA determined that additional reductions in NOx and NMHC emissions are needed at the

national level from heavy-duty vehicles and promulgated a new NOx plus NMHC standard of

2.5 grams per brake horsepower-hour (g/bhp-hr). This standard was modeled in the MOBILE5b

input files following the guidance provided in “MOBILE5 Information Sheet #5, Inclusion of

New 2004 NOx Standard for Heavy-Duty Diesel Engines in MOBILE5a and MOBILE5b

Modeling” issued on January 30, 1998. (http://www.epa.gov/oms/models/mobile5/m5info5.pdf) 

In effect, this modeling reduces the HDDV emission factors starting with the 2004 model year to

be consistent with the new standard, and is applied nationally.

f. Tier 2/Low Sulfur Gasoline Controls and 2007, 2020, and 2030

Adjustment Factors

The 1996 section of this chapter discusses the VOC exhaust and NOx MOBILE5b to

MOBILE 6 adjustment factors, the air conditioning usage adjustment factors, and the HDDV

NOx defeat device adjustment factors. The actual factors applied, including those applied in

2007, 2020, and 2030 were shown in Tables VI-6 through VI-9. The adjustment factors applied

in the projection years include the effect of the Tier 2 emission standards and low sulfur gasoline,

in addition to MOBILE6 adjustments. Although the appropriate I/M category was included in

the 1996 adjustment tables, the adjustments were the same as those for I/M. For the projection

years, these two categories have different adjustment factors in most cases. In general, areas

modeled with the EPA enhanced performance standard, or an equivalent I/M program, were

grouped in the “APP IM” category. Several exceptions to this general rule occurred for areas that

indicated through comments to the NOx SIP Call that were accepted by EPA specifically

indicating that the area should or should not be modeled with the maximum LEV benefits.

i. VOC Evaporative Adjustments

An additional set of MOBILE5b to MOBILE6 adjustment factors was applied to the VOC

evaporative emission factors in 2007, 2020, and 2030 that were not applied in 1996. These

adjustments result from the Tier 2 and low sulfur fuel controls. These factors were applied to the

evaporative portion of the VOC emission factors for LDGVs, LDGT1s, and LDGT2s, and are

shown in Table VI-12.
VI-20

ii. On-board Diagnostics

To simulate the effects of on-board diagnostic (OBD) devices in the projection years,

adjustments were made to the MOBILE5b input files for areas modeled with an I/M program. 

This was modeled by adding or modifying pressure and purge test input lines, such that 1996 and

later model year LDGVs and LDGTs would receive the full benefits of a test-only pressure test

and purge test.

iii. PM and SO2 Adjustment Factors

An additional set of factors was applied to PM and gasoline-fueled vehicle SO2 emission

factors in the projection years. The PM factors are shown in Table VI-13 and were applied only

to the exhaust portion of the PM10 and PM2.5 emission factors for LDGVs, LDGTs, HDGVs,

LDDVs, and LDDTs. The brake wear and tire wear portions of the PM factors were not

adjusted. Table VI-14 lists the SO2 factors applied. These factors apply to all gasoline vehicle

types and account for the lower levels of sulfur in gasoline under EPA’s final Tier 2/low sulfur

fuel rulemaking.

3. Control Case Emission Reductions

Once the Base Case highway vehicle emission inventories were prepared, the highway

vehicle Control Case emission inventories for 2007, 2020, and 2030 were calculated by

multiplying the base emissions by the specified reduction percentages. Emission reduction

percentages were supplied by OTAQ as national reduction percentages. Table VI-15 lists these

reduction percentages for the vehicle types and pollutants whose emissions were reduced from

the Base Case to the Control Case. For HDDVs, the controls were applied to VOC, NOx, CO,

exhaust PM10, exhaust PM2.5, and SO2. Exhaust and evaporative VOC emissions and NOx

emissions were reduced from HDGVs. SO2 emissions were reduced from LDDVs and LDDTs

(as well as HDDVs) due to the lower diesel fuel sulfur content included in the HDD proposal.

C. MASS EMISSIONS INVENTORY AND EMISSIONS PROCESSOR INPUT FILES

1. EMS-95 Emissions Processor Input Files

The highway vehicle-related files submitted as inputs to EMS-95 consist of MOBILE5b

input shells, three VMT-related files, and an adjustment factor file. The MOBILE5b input shells

are a set of MOBILE5b input files that correspond to each of the MOBILE5b input files

developed in calculating the mass emissions inventory, but with only one scenario, representing

July controls and at a single speed and temperature combination. The EMS-95 models then use

these MOBILE5b shells to generate emission factors at all of the temperature and speed

combinations necessary for the hourly meteorological conditions being modeled. The three VMT

files include a file with the total VMT by county and road type. The VMT data in these files

represents an annual average day (i.e., annual VMT/365). The format of these files is shown in

Table VI-16. These models then break the VMT down by vehicle type using the VMT mix by

hour, county, road type, and vehicle type. The file structure of these VMT mix files are shown in

Table VI-17. (It should be noted that for this analysis, there is no difference in the VMT mixes
VI-21

Table VI-12

Evaporative VOC MOBILE5b to MOBILE6 Adjustment Factors

Adjustment Factors by Vehicle Type (unitless)

Year Control Combination LDGV LDGT1 LDGT2

2007 IM CG 0.985 0.984 1.000

IM RFG 0.984 0.983 1.000

IM WEST 0.985 0.984 1.000

NO IM CG 0.992 0.992 1.000

NO IM RFG 0.988 0.991 1.000

NO IM WEST 0.992 0.992 1.000

2020 IM CG 0.883 0.880 0.941

IM RFG 0.846 0.855 0.915

IM WEST 0.883 0.880 0.941

NO IM CG 0.945 0.954 0.978

NO IM RFG 0.919 0.935 0.967

NO IM WEST 0.945 0.954 0.978

2030 IM CG 0.874 0.860 0.915

IM RFG 0.842 0.830 0.884

IM WEST 0.874 0.860 0.915

NO IM CG 0.941 0.948 0.974

NO IM RFG 0.913 0.926 0.959

NO IM WEST 0.941 0.948 0.974
VI-22

Table VI-13

PM Adjustment Factors

Adjustment Factor by Vehicle Type (unitless)

Year Control Combination LDGV LDGT1 LDGT2 HDGV LDDV LDDT MC

2007 CG 0.416 0.342 0.370 0.767 0.826 0.800 1.000

RFG 0.624 0.563 0.591 0.848 0.826 0.800 1.000

WEST 0.416 0.342 0.370 0.767 0.826 0.800 1.000

2020 CG 0.416 0.337 0.349 0.767 0.421 0.408 1.000

RFG 0.625 0.559 0.571 0.848 0.421 0.408 1.000

WEST 0.416 0.337 0.349 0.767 0.421 0.408 1.000

2030 CG 0.417 0.333 0.333 0.767 0.109 0.107 1.000

RFG 0.625 0.556 0.556 0.848 0.109 0.107 1.000

WEST 0.417 0.333 0.333 0.767 0.109 0.107 1.000

Table VI-14

SO2 Adjustment Factors

Adjustment Factor by Vehicle Type (unitless)

Year Control Combination LDGV LDGT1 LDGT2 HDGV LDDV LDDT MC

2007 CG 0.088 0.088 0.088 0.088 1.000 1.000 0.088

RFG 0.224 0.224 0.224 0.224 1.000 1.000 0.224

WEST 0.088 0.088 0.088 0.088 1.000 1.000 0.088

2020 CG 0.088 0.088 0.088 0.088 1.000 1.000 0.088

RFG 0.224 0.224 0.224 0.224 1.000 1.000 0.224

WEST 0.088 0.088 0.088 0.088 1.000 1.000 0.088

2030 CG 0.088 0.088 0.088 0.088 1.000 1.000 0.088

RFG 0.224 0.224 0.224 0.224 1.000 1.000 0.224

WEST 0.088 0.088 0.088 0.088 1.000 1.000 0.088
VI-23

Table VI-15

HDD Control Case Emission Reduction Percentages

Calendar Vehicle National Reduction

Year Type Exhaust VOC Evaporative VOC NOx CO Exhaust PM10 Exhaust PM

2007 HDDV 4.82% 0.00% 1.08% 5.84% 11.96% 11.96% 2020 HDDV 80.64% 0.00% 75.21% 82.40% 83.89% 83.89% 2030 HDDV 89.43% 0.00% 89.50% 89.99% 92.43% 92.43% 2007 HDGV 0.45% 0.60% 1.02% 0.00% 0.00% 0.00% 2020 HDGV 17.17% 8.78% 33.43% 0.00% 0.00% 0.00% 2030 HDGV 24.29% 9.78% 53.88% 0.00% 0.00% 0.00% 2007 LDDV 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2020 LDDV 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2030 LDDV 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2007 LDDT 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2020 LDDT 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2030 LDDT 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 
VI-24

Table VI-16

Structure for VMT Files (OFNVMTyy.TXT)

Variable Type Length Decimals DescriptionFIPSST C 2 0 FIPS State CodeFIPSCNTY C 3 0 FIPS County Code

ROADTYPE C 2 0 Roadway Type as Defined by Codes Below:

R1-Rural InterstatesR2-Rural Other Principal ArterialsR6-Rural Minor ArterialsR7-Rural Major CollectorsR8-Rural Minor CollectorsR9-Rural LocalsU1-Urban InterstatesU2-Urban Other Freeways and ExpresswaysU4-Urban Other Principal ArterialsU6-Urban Minor ArterialsU7-Urban CollectorsU9-Urban Locals

VMT N 15 3 Annual Average Daily VMT (miles)
VI-25

Table VI-17

Structure for VMT Vehicle Mix Files (NTVMIXyy.TXT)

Variable Type Length Decimals DescriptionFIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County CodeROADTYPE C 2 0 Roadway Type as Defined by Codes Below:

01-Rural Interstates02-Rural Other Principal Arterials06-Rural Minor Arterials07-Rural Major Collectors08-Rural Minor Collectors09-Rural Locals11-Urban Interstates12-Urban Other Freeways and Expressways14-Urban Other Principal Arterials16-Urban Minor Arterials17-Urban Collectors19-Urban Locals

LINKID C 10 0 Not UsedHOUR N 2 0 Hour of Day (1 through 24)VEHMIX01 N 5 3 VMT Mix Fraction for Light-Duty Gas VehiclesVEHMIX02 N 5 3 VMT Mix Fraction for Light-Duty Gas Trucks 1VEHMIX03 N 5 3 VMT Mix Fraction for Light-Duty Gas Trucks 2VEHMIX04 N 5 3 VMT Mix Fraction for Heavy-Duty Gas VehiclesVEHMIX05 N 5 3 VMT Mix Fraction for Light-Duty Diesel VehiclesVEHMIX06 N 5 3 VMT Mix Fraction for Light-Duty Diesel TrucksVEHMIX07 N 5 3 VMT Mix Fraction for Heavy-Duty Diesel VehiclesVEHMIX08 N 5 3 VMT Mix Fraction for Motorcycles
VI-26

VMT mixes by hour of the day.) The third VMT-related file provided for each year includes a

file with average speed information by county and road type. The format of these files is shown

in Table VI-18. Each of these three VMT-related files varies only by year, and not by control

case. The last file included for the EMS-95 modeling related to the on-highway vehicle

modeling varies by year and control case and includes the adjustment factors to be applied by

county and vehicle type. The format of these files is shown in Table VI-19. The HDDV

adjustment factors, and the air conditioning temperature-dependent equation were applied

separately in the modeling code and were not included in the adjustment factor files.

2. EPS 2.5 and Mass Emission Inventory - File Structures

The EPS 2.5 files for on-highway vehicle sources consist of monthly emissions data by

county, vehicle type, and roadway type. The EPS 2.5 modeling files were assembled from

detailed monthly emission files, developed as discussed in the sections above. Separate EPS 2.5

files were created for for each Base and Control Case. All of the on-highway EPS 2.5 emission

files have the same format. This format is shown in Table VI-20. The format of the final mass

emissions file, which contain annual and SSD emissions for each pollutant are shown in Table

VI-21. The same set of years and cases applies to the mass emissions files. It should be noted

that the SSD values for the on-highway vehicle emissions are calculated by dividing July

emissions by 31.

An additional set of files was prepared for 1996, 2030 Base Case, and 2030 Control Case for

use in air toxics modeling. These files were identical to the corresponding mass emissions files,

except that the PM10 and PM2.5 emission fields included only exhaust PM10 or PM2.5 emissions. 

Emissions from brake wear and tire wear were excluded from these files. The format of these

files is the format shown in Table VI-21. All exhaust PM10 and PM2.5 adjustments discussed in

this chapter were also applied in these files.
VI-27

Table VI-18

Structure for VMT Vehicle Mix Files (OFNSPyy.TXT)

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

ROADTYPE C 2 0 Roadway Type as Defined by Codes Below:

01-Rural Interstates

02-Rural Other Principal Arterials

06-Rural Minor Arterials

07-Rural Major Collectors

08-Rural Minor Collectors

09-Rural Locals

11-Urban Interstates

12-Urban Other Freeways and Expressways

14-Urban Other Principal Arterials

16-Urban Minor Arterials

17-Urban Collectors

19-Urban Locals

AVESPEED N 4 1 Average Vehicle Speed (miles per hour)

Table VI-19

Structure for Adjustment Factor Files

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State Code

FIPSCNTY C 3 0 FIPS County Code

V_TYPE C 1 0 Vehicle Type : 1 = LDGV, 2 = LDGT1, 3 = LDGT2, 4 =

HDGV, 5 = MC, 6 = LDDV, 7 = LDDT, 8 = HDDV

EXHVOCADJ N 10 3 Multiplicative Exhaust VOC Adjustment Factor

EXHNOXADJ N 10 3 Multiplicative NOx Adjustment Factor

NOXACADJ N 10 3 Additive NOx Full Air Conditioning Usage Adjustment

Factor (to be multiplied by temperature-dependent

equation)

EVAPVOCADJ N 10 3 Multiplicative Evaporative VOC Adjustment Factor
VI-28

Table VI-20

Structure for On-Highway Mobile Source EPS Data Files

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS state code

FIPSCNTY C 3 0 FIPS county code

SCC C 10 0 AMS Source Category Code

V_TYPE C 5 0 Vehicle Type

VOC N 12 4 Annual VOC Emissions [tons per year (tpy)]

NOX N 12 4 Annual NOx Emissions (tpy)

CO N 12 4 Annual CO Emissions (tpy)

SO2 N 12 4 Annual SO2 Emissions (tpy)

PM10 N 12 4 Annual PM10 Emissions (tpy)

PM25 N 12 4 Annual PM2.5 Emissions (tpy)

SOA N 12 4 Annual SOA Emissions (tpy)

NH3 N 12 4 Annual NH3 Emissions (tpy)

VOC_JAN N 12 4 Monthly VOC Emissions (tons per month)

VOC_FEB N 12 4 Monthly VOC Emissions (tons per month)

VOC_MAR N 12 4 Monthly VOC Emissions (tons per month)

VOC_APR N 12 4 Monthly VOC Emissions (tons per month)

VOC_MAY N 12 4 Monthly VOC Emissions (tons per month)

VOC_JUN N 12 4 Monthly VOC Emissions (tons per month)

VOC_JUL N 12 4 Monthly VOC Emissions (tons per month)

VOC_AUG N 12 4 Monthly VOC Emissions (tons per month)

VOC_SEP N 12 4 Monthly VOC Emissions (tons per month)

VOC_OCT N 12 4 Monthly VOC Emissions (tons per month)

VOC_NOV N 12 4 Monthly VOC Emissions (tons per month)

VOC_DEC N 12 4 Monthly VOC Emissions (tons per month)

NOX_JAN N 12 4 Monthly NOx Emissions (tons per month)

NOX_FEB N 12 4 Monthly NOx Emissions (tons per month)

NOX_MAR N 12 4 Monthly NOx Emissions (tons per month)

NOX_APR N 12 4 Monthly NOx Emissions (tons per month)

NOX_MAY N 12 4 Monthly NOx Emissions (tons per month)

NOX_JUN N 12 4 Monthly NOx Emissions (tons per month)

NOX_JUL N 12 4 Monthly NOx Emissions (tons per month)

NOX_AUG N 12 4 Monthly NOx Emissions (tons per month)

NOX_SEP N 12 4 Monthly NOx Emissions (tons per month)

NOX_OCT N 12 4 Monthly NOx Emissions (tons per month)

NOX_NOV N 12 4 Monthly NOx Emissions (tons per month)

NOX_DEC N 12 4 Monthly NOx Emissions (tons per month)

CO_JAN N 12 4 Monthly CO Emissions (tons per month)

CO_FEB N 12 4 Monthly CO Emissions (tons per month)

CO_MAR N 12 4 Monthly CO Emissions (tons per month)

CO_APR N 12 4 Monthly CO Emissions (tons per month)

CO_MAY N 12 4 Monthly CO Emissions (tons per month)
Table VI-20 (continued)

Variable Type Length Decimals Description

VI-29

CO_JUN N 12 4 Monthly CO Emissions (tons per month)

CO_JUL N 12 4 Monthly CO Emissions (tons per month)

CO_AUG N 12 4 Monthly CO Emissions (tons per month)

CO_SEP N 12 4 Monthly CO Emissions (tons per month)

CO_OCT N 12 4 Monthly CO Emissions (tons per month)

CO_NOV N 12 4 Monthly CO Emissions (tons per month)

CO_DEC N 12 4 Monthly CO Emissions (tons per month)

SO2_JAN N 12 4 Monthly SO2 Emissions (tons per month)

SO2_FEB N 12 4 Monthly SO2 Emissions (tons per month)

SO2_MAR N 12 4 Monthly SO2 Emissions (tons per month)

SO2_APR N 12 4 Monthly SO2 Emissions (tons per month)

SO2_MAY N 12 4 Monthly SO2 Emissions (tons per month)

SO2_JUN N 12 4 Monthly SO2 Emissions (tons per month)

SO2_JUL N 12 4 Monthly SO2 Emissions (tons per month)

SO2_AUG N 12 4 Monthly SO2 Emissions (tons per month)

SO2_SEP N 12 4 Monthly SO2 Emissions (tons per month)

SO2_OCT N 12 4 Monthly SO2 Emissions (tons per month)

SO2_NOV N 12 4 Monthly SO2 Emissions (tons per month)

SO2_DEC N 12 4 Monthly SO2 Emissions (tons per month)

PM10_JAN N 12 4 Monthly PM10 Emissions (tons per month)

PM10_FEB N 12 4 Monthly PM10 Emissions (tons per month)

PM10_MAR N 12 4 Monthly PM10 Emissions (tons per month)

PM10_APR N 12 4 Monthly PM10 Emissions (tons per month)

PM10_MAY N 12 4 Monthly PM10 Emissions (tons per month)

PM10_JUN N 12 4 Monthly PM10 Emissions (tons per month)

PM10_JUL N 12 4 Monthly PM10 Emissions (tons per month)

PM10_AUG N 12 4 Monthly PM10 Emissions (tons per month)

PM10_SEP N 12 4 Monthly PM10 Emissions (tons per month)

PM10_OCT N 12 4 Monthly PM10 Emissions (tons per month)

PM10_NOV N 12 4 Monthly PM10 Emissions (tons per month)

PM10_DEC N 12 4 Monthly PM10 Emissions (tons per month)

PM25_JAN N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_FEB N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_MAR N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_APR N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_MAY N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_JUN N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_JUL N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_AUG N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_SEP N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_OCT N 12 4 Monthly PM2.5 Emissions (tons per month)

PM25_NOV N 12 4 Monthly PM2.5 Emissions (tons per month)
Table VI-20 (continued)

Variable Type Length Decimals Description

VI-30

PM25_DEC N 12 4 Monthly PM2.5 Emissions (tons per month)

SOA_JAN N 12 4 Monthly SOA Emissions (tons per month)

SOA_FEB N 12 4 Monthly SOA Emissions (tons per month)

SOA_MAR N 12 4 Monthly SOA Emissions (tons per month)

SOA_APR N 12 4 Monthly SOA Emissions (tons per month)

SOA_MAY N 12 4 Monthly SOA Emissions (tons per month)

SOA_JUN N 12 4 Monthly SOA Emissions (tons per month)

SOA_JUL N 12 4 Monthly SOA Emissions (tons per month)

SOA_AUG N 12 4 Monthly SOA Emissions (tons per month)

SOA_SEP N 12 4 Monthly SOA Emissions (tons per month)

SOA_OCT N 12 4 Monthly SOA Emissions (tons per month)

SOA_NOV N 12 4 Monthly SOA Emissions (tons per month)

SOA_DEC N 12 4 Monthly SOA Emissions (tons per month)

NH3_JAN N 12 4 Monthly NH3 Emissions (tons per month)

NH3_FEB N 12 4 Monthly NH3 Emissions (tons per month)

NH3_MAR N 12 4 Monthly NH3 Emissions (tons per month)

NH3_APR N 12 4 Monthly NH3 Emissions (tons per month)

NH3_MAY N 12 4 Monthly NH3 Emissions (tons per month)

NH3_JUN N 12 4 Monthly NH3 Emissions (tons per month)

NH3_JUL N 12 4 Monthly NH3 Emissions (tons per month)

NH3_AUG N 12 4 Monthly NH3 Emissions (tons per month)

NH3_SEP N 12 4 Monthly NH3 Emissions (tons per month)

NH3_OCT N 12 4 Monthly NH3 Emissions (tons per month)

NH3_NOV N 12 4 Monthly NH3 Emissions (tons per month)

NH3_DEC N 12 4 Monthly NH3 Emissions (tons per month)
VI-31

Table VI-21

Structure for On-Highway Mobile Source Mass Emissions Data Files

Variable Type Length Decimals Description

FIPSST C 2 0 FIPS State code

FIPSCNTY C 3 0 FIPS county code

SCC C 10 0 Source Category Classification Code

VOC_ANN N 10 4 Annual VOC emissions from highway vehicles (tons per year)

NOX_ANN N 10 4 Annual NOx emissions from highway vehicles (tons per year)

CO_ANN N 10 4 Annual CO emissions from highway vehicles (tons per year)

SO2_ANN N 10 4 Annual SO2 emissions from highway vehicles (tons per year)

PM10_ANN N 10 4 Annual PM10 emissions from highway vehicles (tons per year)

PM25_ANN N 10 4 Annual PM2.5 emissions from highway vehicles (tons per

year)

NH3_ANN N 10 4 Annual NH3 emissions from highway vehicles (tons per year)

SOA_ANN N 10 4 Annual SOA emissions from highway vehicles (tons per year)

VOC_OSD N 10 4 Summer season day VOC emissions from highway vehicles

[tons per day (tpd)]

NOX_OSD N 10 4 Summer season day NOx emissions from highway vehicles

(tpd)

CO_OSD N 10 4 Summer season day CO emissions from highway vehicles

(tpd)

SO2_OSD N 10 4 Summer season day SO2 emissions from highway vehicles

(tpd)

PM10_OSD N 10 4 Summer season day PM10 emissions from highway vehicles

(tpd)

PM25_OSD N 10 4 Summer season day PM25 emissions from highway vehicles

(tpd)

NH3_OSD N 10 4 Summer season day NH3 emissions from highway vehicles

(tpd)

SOA_OSD N 10 4 Summer season day SOA emissions from highway vehicles

(tpd)

VMT_ANN N 20 7 Annual VMT from highway vehicles using 8 vehicle types

(million miles)
VII-1

CHAPTER VII

EMISSION SUMMARIES AND COMPARISONS

Please note that, in this Chapter, "national" means "48-State" (contiguous United States). As

noted in Chapter I, inventories were prepared for 50-States for mobile and nonroad sources, but

the summaries have been prepared only for the contiguous 48 States.

Tables VII-1 through VII-10 present summaries of annual national emissions and emissions

reductions by pollutant and source category as defined by the Tier 2-level emission summary for

the 1996, 2007, 2020, and 2030 inventories. Table VII-1 summarizes national annual emissions

for the 1996 Base Year inventory. Table VII-2 summarizes national annual emissions for the

2007 Base Case inventory, Table VII-3 summarizes national annual emissions for mobile and

nonroad sources for the 2007 Control Case inventory, and Table VII-4 summarizes the mobile

and nonroad emissions reductions associated with the 2007 Control Case relative to the 2007

Base Case. Table VII-5 summarizes national annual emissions for the 2020 Base Case inventory,

Table VII-6 summarizes national annual emissions for mobile and nonroad sources for the 2020

Control Case inventory, and Table VII-7 summarizes the mobile and nonroad emissions

reductions associated with the 2020 Control Case relative to the 2020 Base Case. Table VII-8

summarizes national annual emissions for the 2030 Base Case inventory, Table VII-9

summarizes national annual emissions for mobile and nonroad sources for the 2030 Control Case

inventory, and Table VII-10 summarizes the mobile and nonroad emissions reductions associated

with the 2030 Control Case relative to the 2030 Base Case. 

Tables VII-11 through VII-20 present summaries of annual emissions and emissions

reductions by State and pollutant for each of the major source categories (i.e., stationary area,

nonroad, EGU, non-EGU point, and on-highway mobile sources). Table VII-11 summarizes

annual emissions for the 1996 Base Year inventory. Table VII-12 summarizes national annual

emissions for the 2007 Base Case inventory, Table VII-13 summarizes national annual emissions

for mobile and nonroad sources for the 2007 Control Case inventory, and Table VII-14

summarizes the mobile and nonroad emissions reductions associated with the 2007 Control Case

relative to the 2007 Base Case. Table VII-15 summarizes national annual emissions for the 2020

Base Case inventory, Table VII-16 summarizes national annual emissions for mobile and

nonroad sources for the 2020 Control Case inventory, and Table VII-17 summarizes the mobile

and nonroad emissions reductions associated with the 2020 Control Case relative to the 2030

Base Case. Table VII-18 summarizes national annual emissions for the 2030 Base Case

inventory, Table VII-19 summarizes national annual emissions for mobile and nonroad sources

for the 2030 Control Case inventory, and Table VII-20 summarizes the mobile and nonroad

emissions reductions associated with the 2030 Control Case relative to the 2030 Base Case. 
VII-2

Table VII-21 summarizes the total annual emissions in each of the years and cases for all

eight pollutants. Table VII-21 also shows the percent change in emissions between the Base and

Control Case inventories for 2007, 2020, and 2030.

For the Tier 2-level summary tables presented in Tables VII-1 through VII-10 (excluding the

tables showing emissions reductions), biogenic emissions for NH3 are shown because these

emissions are included in the area source inventories prepared under this project. Biogenic VOC

emissions are not shown in these tables because they are prepared separately by EPA for input to

the modeling analyses. 

For the off-highway Tier 1 category shown in Tables VII-1 through VII-10 (excluding the

tables showing emissions reductions), total off-highway emissions do not match the totals shown

for nonroad emissions by State presented in Tables VII-11 through VII-20 (excluding the tables

showing emissions reductions). This is because the emissions for four SCC's are included in the

tables that summarize emissions by State, but do not fall under the off-highway Tier 1 category

shown in Tables VII-1 through VII-10 (excluding the tables showing emissions reductions). The

SCCs, their descriptions, and the Tier 1 and 2 categories to which they are assigned are as

follows: 

Tier 1 Category = Miscellaneous

Tier 2 Category = Fugitive Dust

SCC = 2275085000: Mobile Sources; Aircraft; Unpaved Airstrips

Tier 1 Category = Storage and Transportation

Tier 2 Category = Petroleum and Petroleum Product Storage

SCC = 2275900000: Mobile Sources; Aircraft; Refueling; All fuels; All processes

SCC = 2275900101: Mobile Sources; Aircraft; Refueling; All fuels; Displacement

Loss/Uncontrolled

SCC = 2275900102: Mobile Sources; Aircraft; Refueling; All fuels; Displacement

Loss/Controlled

The remainder of this chapter presents pollutant density maps for the 48-contiguous States

and the District of Columbia. The density maps are in units of annual tons of pollutant emissions

per square mile. For the 1996 Base Year and the 2007, 2020, and 2030 Base Case inventories,

separate maps are presented by pollutant in the following order: VOC, NOx, CO, SOA, SO2,

PM10, PM2.5, and NH3. For the 2007, 2020, and 2030 Control Case inventories, separate density

maps are provided to show mobile and nonroad source emissions reductions for NOx, SO2, and

PM2.5. Figures VII-1 through VII-8 present the maps for the 1996 Base Year inventory. For

2007, Figures VII-9 through VII-16 present the maps for the Base Case inventory, and Figures

VII-17 through VII-19 present maps of the emissions reductions associated with the 2007 Control

Case versus the 2007 Base Case inventory. For 2020, Figures VII-20 through VII-27 present the

maps for the Base Case inventory, and Figures VII-28 through VII-30 present maps of the

emissions reductions associated with the 2020 Control Case versus the 2020 Base Case

inventory. For 2030, Figures VII-31 through VII-38 present the maps for the Base Case

inventory, and Figures VII-39 through VII-41 present maps of the emissions reductions

associated with the 2030 Control Case versus the 2030 Base Case inventory.
VIII-1

CHAPTER VIII

REFERENCES

AAMA, 1996: American Automobile Manufacturers Association, “Fuel Volatility Survey 1996,”

Washington, DC, 1996.

BEA, 1995: Bureau of Economic Analysis, “Regional State Projections of Economic Activity

and Population to 2045,” U.S. Department of Commerce, Washington, DC, July 1995. 

BOC, 1992: Bureau of the Census, “1990 Census of Population, Volume 1 Characteristics of

Population, Chapter B Number of Inhabitants,” U.S. Department of Commerce, Washington,

DC, July 1992.

DOE, 1998: U.S. Department of Energy, Office of Integrated Analysis and Forecasting, Energy

Information Administration, “Annual Energy Outlook 1999, with Projections through 2020,”

DOE/EIA-0383(99). December 1998.

EIA, 1996: U.S. Department of Energy, Energy Information Administration, “Fuel Oil and

Kerosene Sales,” Washington, DC, DOE/EIA-0380. 1996.

EPA, 1991: U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards, “Procedures for Preparing Emissions Projections,” Research Triangle Park, NC,

EPA-450/4-91-019. July 1991.

EPA, 1997: U.S. Environmental Protection Agency, Office of Mobile Sources, “Locomotive

Emission Standards - Regulatory Support Document (RSD),” Ann Arbor, MI. April 1997.

EPA, 1998a: U.S. Environmental Protection Agency, Office of Mobile Sources, Assessment and

Modeling Division, “Exhaust Emission Factors for Nonroad Engine Modeling -

Compression Ignition,” Report No. NR-009A, Ann Arbor MI. June 1998.

EPA, 1998b: U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards, “National Air Pollutant Emission Trends Procedures Document, 1900-1996,”

EPA-454/R-98-008, Research Triangle Park, NC, May 1998.

EPA, 1999a: U.S. Environmental Protection Agency, Office of Mobile Sources, Assessment and

Modeling Division, “Exhaust Emission Factors for Nonroad Engine Modeling - Spark

Ignition,” Report No. NR-010b, EPA420-R-99-009, Ann Arbor MI. March 1999.
REFERENCES (continued)

VIII-2

EPA, 1999b: U.S. Environmental Protection Agency, Office of Air Quality, Planning and

Standards, “Procedures Document for National Emissions Inventory, Volume I: Criteria Air

Pollutants 1900-1999,” Research Triangle Park, NC. September 2000.

EPA, 1999c: U.S. Environmental Protection Agency, Office of Air Quality, Planning and

Standards, “Procedures for Developing Base Year and Future Year Mass and Modeling

Inventories for the Tier 2 Final Rulemaking,” EPA420-R-99-034, Research Triangle Park, NC. 

September 1999.

EPA, 2000a: U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards, “National Air Pollutant Emission Trends, 1900-1998,” EPA-454/R-00-002,

Research Triangle Park, NC. March 2000.

EPA, 2000b: U.S. Environmental Protection Agency, “Changes to the NONROAD model for the

April 2000 Version Used in Support of the 2007 Heavy-Duty Diesel Engine Rule,” EPA

Memorandum from the Nonroad Engine Emissions Modeling Team to Docket A-99-06. 

May 31, 2000.

FAA, 1998a: Federal Aviation Administration, Office of Aviation Policy and Plans, “FAA

Aviation Forecasts Fiscal Years, 1998-2009.” March 1998.

FAA, 1998b: Federal Aviation Administration, Office of Aviation Policy and Plans, “Long

Range Aviation Forecasts Fiscal Years 2010, 2015, and 2020,” FAA-APO-98-9. June 1998.

FHWA, 1990: U.S. Department of Transportation, Federal Highway Administration, “Highway

Performance Monitoring System Field Manual,” Washington, DC. December 1990.

FHWA, 1997: U.S. Department of Transportation, Federal Highway Administration, 1996

Highway Statistics, Office of Highway Information Management, Washington, DC, 1997

(http://fhwa.dot.gov/ohim/1996/index.html).

Grosjean, D. and J.H. Seinfeld, 1989: “Parameterization of the Formation Potential of Secondary

Organic Aerosols,” Atmospheric Environment, Volume 23, No. 8, pp. 1733-1747. 1989.

Harvey, 1983: Craig A. Harvey, Robert J. Garbe, Thomas M. Baines, Joseph H. Somers, Karl H.

Hellman, and Penny M. Carey, U.S. Environmental Protection Agency, “A Study of the

Potential Impact of Some Unregulated Motor Vehicle Emissions,” SAE Technical Paper

Series 830987, presented at the Passenger Car Meeting, Dearborn, Michigan. June 6-9,

1983.
REFERENCES (continued)

VIII-3

Pechan-Avanti, 1997a: The Pechan-Avanti Group, “Ozone Transport Assessment Group

(OTAG) Emissions Inventory Development Report, Volume III: Projections and Controls,”

draft prepared for U.S. Environmental Protection Agency, Office of Air Quality Planning

and Standards, Research Triangle Park, NC. June 1997. 

Pechan-Avanti, 1997b: The Pechan-Avanti Group, “2010 Clean Air Act Amendment Baseline

Emission Projections for the Integrated Ozone, Particulate Matter, and Regional Haze Cost

Analysis,” prepared for U.S. Environmental Protection Agency, Office of Air Quality

Planning and Standards, Research Triangle Park, NC. July 17, 1997.

Pechan-Avanti, 1998: The Pechan-Avanti Group, “Emission Projections for the Clean Air Act

Section 812 Prospective Analysis,” prepared for Industrial Economics, Inc., Cambridge,

MA. June 1998. 

Pechan-Avanti, 2000: The Pechan-Avanti Group, “Development of National Emission Trends

(NET) Data for FY2000, Technical Memorandum, Task 2, Development of Quality

Assurance (QA) Plan,” prepared for U.S. Environmental Protection Agency, Office of Air

Quality Planning and Standards, Emission Factors and Inventory Group, Research Triangle

Park, NC. March 2000. EPA Contract Number 68-D7-0067; Work Assignment Number 3-

12. 

Stella, 1999: Gregory Stella, U.S. Environmental Protection Agency, Office of Air Quality

Planning and Standards, Emission Factors and Inventory Group, e-mail transmission to Erica

Laich, The Pechan-Avanti Group, providing information on monthly percentage profiles by

State, prime mover, and fuel for use in developing June and August daily heat input and

emissions to EGU inventory. July 21, 1999. 

Stella, 2000: Greg Stella, U.S. Environmental Protection Agency, Office of Air Quality Planning

and Standards, Emission Factors and Inventory Group, e-mail transmission to Frank Divita,

The Pechan-Avanti Group, providing ranges for stack flow rate, temperature, diameter,

height, and velocity to identify values outside of ranges for correcting stack parameter values

in point source inventory. May 9, 2000. 

Somers, 1997a: Joseph Somers, Office of Mobile Sources, U.S. Environmental Protection

Agency, “Major Modeling Elements for Operating I/M Programs,,” table provided to E.H.

Pechan & Associates, Inc., July 10, 1997.

Somers, 1997b: Joseph Somers, Office of Mobile Sources, U.S. Environmental Protection

Agency, “State Winter Oxygenated Fuel Programs,” table provided to E.H. Pechan &

Associates, Inc. February 25, 1997.
REFERENCES (continued)

VIII-4

USDA, 1997: U.S. Department of Agriculture, “1997 Census of Agriculture Geographic Area

Series, Volume 1, 1A, 1B, 1C; CD ROM Set.” Issued June 1999. AC97-CD-VOL1-1A, 1B,

and 1C.

USDA, 1998: U.S. Department of Agriculture, World Agricultural Outlook Board, Office of the

Chief Economist, “USDA - Agricultural Baseline Projections to 2007,” Staff Report No.

WOAB-98-1. 1998.

USDA, 2000a: U.S. Department of Agriculture, National Agricultural Statistics Service,

“Published Estimates Data Base,” located at www.nass.usda.gov:81/idepb.

USDA, 2000b: U.S. Department of Agriculture, World Agricultural Outlook Board, “USDA

Agricultural Baseline Projections to 2009,” Staff Report No. WAOB-2000-1. 

February 2000.