E.O. 12866 NESHAP RICE RIA 2060-AQ58 Proposal 20120522

 May 2012

Regulatory Impact Analysis (RIA) for Proposed 

Reconsideration Existing Stationary Spark 

Ignition RICE NESHAP

Final Report

Prepared for

Larry Sorrels

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards (OAQPS)

Air Economics Group (AEG) 

(MD-C439-02)

Research Triangle Park, NC 27711
_________________________________

RTI International is a trade name of Research Triangle Institute.

Regulatory Impact Analysis (RIA) 

for Existing Stationary Spark

Ignition RICE NESHAP

Final Report

May 2012

Prepared for

Larry Sorrels

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards (OAQPS)

Air Benefit and Cost Group (ABCG) 

(MD-C439-02)

Research Triangle Park, NC 27711

Prepared by

Paramita Sinha

Fern Braun

Brooks Depro

RTI International

3040 Cornwallis Road

Research Triangle Park, NC 27709
iii

CONTENTS

Section Page

1 Executive Summary...................................................................................................... 1-1

ES.1 Summary of Impacts for SI RICE NESHAP Reconsideration Proposal............1-1

ES.2 Comparison with Results from 2010 Final SI RICE NESHAP......................1-2

2 Introduction................................................................................................................. 2-11

2.1 Organization of this Report................................................................................ 2-11

3 Industry Profile ............................................................................................................. 3-1

3.1 Electric Power Generation, Transmission, and Distribution ............................... 3-1

3.1.1 Overview.................................................................................................. 3-1

3.1.2 Goods and Services Used......................................................................... 3-3

3.1.3 Business Statistics.................................................................................... 3-4

3.2 Oil and Gas Extraction....................................................................................... 3-11

3.2.1 Overview................................................................................................ 3-11

3.2.2 Goods and Services Used....................................................................... 3-11

3.2.3 Business Statistics.................................................................................. 3-13

3.2.4 Case Study: Marginal Wells.................................................................. 3-17

3.3 Pipeline Transportation of Natural Gas ............................................................. 3-18

3.3.1 Overview................................................................................................ 3-18

3.3.2 Goods and Services Used....................................................................... 3-18

3.3.3 Business Statistics.................................................................................. 3-20

4 Regulatory Alternatives, Costs, and Emission Impacts................................................ 4-1

4.1 Background.......................................................................................................... 4-1

4.2 Proposed Amendments to SI RICE NESHAP..................................................... 4-1

4.2.1 Total Hydrocarbon Compliance (THC) Demonstration Option .............. 4-1

4.2.2 Proposed Amendment - Emergency Demand Response/Peak 

Shaving .................................................................................................... 4-5
iv

4.2.3 Proposed Amendment - Non-Emergency Stationary SI RICE 

Greater than 500 HP Located at Area Sources...... ................................ 4-6

4.3 What Are the Pollutants Regulated by the Rule?............................................... 4-11

4.4 Cost Impacts....................................................................................................... 4-14

4.4.1 Introduction............................................................................................ 4-14

4.4.2 Control Cost Methodology .................................................................... 4-14

4.4.3 Control Cost Equations.......................................................................... 4-18

4.4.4 Summary................................................................................................ 4-21

4.4.5 Caveats and Limitations for Cost Estimates.......................................... 4-35

4.5 Baseline Emissions and Emission Reductions................................................... 4-36

5 Economic Impact Analysis, Energy Impacts, and Social Costs ................................... 5-1

5.1 Compliance Costs of the Proposed Reconsidered Rule....................................... 5-1

5.2 Social Cost Estimate ............................................................................................ 5-3

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis........... 5-4

5.2.1 Changes in Market Prices and Quantities................................................ 5-4

5.2.2 Regulated Markets: The Electric Power Generation, Transmission, 

and Distribution Sector ............................................................................ 5-6

5.2.3 Partial Equilibrium Measures of Social Cost: Changes Consumer 

and Producer Surplus............................................................................... 5-7

5.4 Energy Impacts .................................................................................................... 5-9

5.5 Unfunded Mandates........................................................................................... 5-10

5.5.1 Future and Disproportionate Costs........................................................ 5-10

5.5.2 Effects on the National Economy .......................................................... 5-10

5.6 Environmental Justice........................................................................................ 5-11

5.7 Employment Impact Analysis............................................................................ 5-11

5.7.1 Employment Impacts from Pollution Control Requirements ................ 5-13

5.7.2 Employment Impacts within the Regulated Industry............................. 5-17
v

6 Small Entity Screening Analysis .................................................................................. 6-1

6.1 Small Entity Data Set........................................................................................... 6-1

6.2 Small Entity Economic Impact Measures............................................................ 6-2

6.2.1 Model Establishment Receipts and Annual Compliance Costs............... 6-2

6.3 Small Government Entities................................................................................ 6-11

7 Benefits of Emissions Reductions ................................................................................ 7-1

7.1 Calculation of PM2.5 Human Health Co-Benefits................................................ 7-1

7.2 Unquantified Benefits........................................................................................ 7-13

7.2.1 HAP Benefits......................................................................................... 7-13

7.2.2 Additional NO2 Co-Benefits.................................................................. 7-14

7.2.3 Ozone Co- Benefits................................................................................ 7-16

7.2.4 Carbon Monoxide Co-Benefits.............................................................. 7-16

7.2.5 Visibility Impairment Co-Benefits..................................7-23

7.3 Characterization of Uncertainty in the Monetized PM2.5 Co-Benefits............... 7-25

7.4 Comparison of Co-Benefits and Costs............................................................... 7-30

8 References for RIA ....................................................................................................... 8-1
vi

LIST OF FIGURES

Number Page

1-1. Breakdown of Total Monetized PM2.5 Co-Benefits of Proposed SI RICE 

Reconsideration by Engine Size............................................................1-8

1-2. Total Monetized PM2.5 Co-Benefits Estimates for the SI RICE Reconsideration 

Proposal in 2013...............................................................................1-9

3-1 Industrial Production Index (NAICS 2211) ................................................................ 3-3

3-2 Internal Combustion Generators by State: 2006 ......................................................... 3-4

3-3 2002 Regional Distribution of Establishments: Electric Power Generation, 

Transmission, and Distribution Industry (NAICS 2211) ............................................ 3-6

3-4 Industrial Production Index (NAICS 211) ................................................................ 3-12

3-5 2002 Regional Distribution of Establishments: Crude Petroleum and Natural 

Gas Extraction Industry (NAICS 211111)................................................................ 3-15

3-6 2002 Regional Distribution of Establishments: Natural Gas Liquid Extraction 

Industry (NAICS 211112)......................................................................................... 3-16

3-7 Distribution of Establishments within Pipeline Transportation (NAICS 486).......... 3-19

3-8 Distribution of Revenue within Pipeline Transportation (NAICS 486).................... 3-20

3-9 2002 Regional Distribution of Establishments: Pipeline Transportation (NAICS 

486)............................................................................................................................ 3-22

3-10 Share of Establishments by Legal Form of Organization in the Pipeline 

Transportation of Natural Gas Industry (NAICS 48621): 2002................................ 3-22

5-1 Distribution of Engine Population by Horsepower Group.......................................... 5-4

5-2 Market Demand and Supply Model: With and Without Regulation........................... 5-6

5-3 Electricity Restructuring by State................................................................................ 5-9

6-1 Distribution of Engine Population by Size for All Industries..................................... 6-8

6-2 Distribution of Compliance Costs by Engine Size for All Industries ......................... 6-9

7-1. Breakdown of Monetized PM2.5 Health Co-Benefits using Mortality Function 

from Pope et al. (2002)................................................................................................ 7-7

7-2. Total Monetized PM2.5 Co-Benefits for the Proposed SI RICE Reconsidered 

NESHAP in 2013 ...................................................................................................... 7-12

7-3. Breakdown of Monetized Co-Benefits for the Proposed SI RICE Reconsidered

NESHAP by Engine Sizee ........................................................................................ 7-13

7-4. Estimated Chronic Census Tractl Carcinogenic Risk from HAP exposure from 

outdoor sources (2005 NATA).................................................................................. 7-18
vii

7-5. Estimated Chronic Census Tract Noncancer (Respiratory) Risk from HAP 

exposure from outdoor sources (2005 NATA).......................................................... 7-18

7-6. Percentage of Adult Population by Annual Mean PM2.5 Exposure in the 

Baseline .................................................................................................................... 7-28

7-7. Cumulative Distribution of Adult Population at Annual Mean PM2.5 Exposure 

in the Baseline .......................................................................................................... 7-28

7-8. Net Benefits for the Proposed SI RICE Reconsidered NESHAP at 3% 

Discount Rate ............................................................................................................ 7-33

7-9. Net Benefits for the Proposed SI RICE Reconsidered NESHAP at 7% Discount 

Rate............................................................................................................................ 7-34
viii

LIST OF TABLES

Number Page

1-1 Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for the 

Proposed SI RICE Reconsidered NESHAP in 2013 (millions of 2010$)................... 1-3

1-2. Summary of the Monetized Co-Benefits, Compliance Costs, and Net benefits for the 

2010 Rule with the Proposed Amendments to the Stationary SI RICE Engine 

NESHAP in 2013 (millions of 

2010$).....................................................................................................1-4

1-3. Summary of Monetized Co-Benefits Estimates for SI RICE Reconsideration Proposal 

in 2013..........................................................................................1-5

1-4. Summary of Estimated Reductions in Health Incidences from PM2.5 for the SI RICE 

Reconsideration Proposal in 2013...........................................................1-7

1-5. Summary of Estimated Social Costs and Benefits for the 2010 Final SI RICE Rule 

and the Proposed Reconsideration (millions of 2010 dollars)........................1-10

3-1 Key Statistics: Electric Power Generation, Transmission, and Distribution 

(NAICS 2211) (2007).................................................................................................. 3-2

3-2 Direct Requirements for Electric Power Generation, Transmission, and 

Distribution (NAICS 2211): 2002............................................................................... 3-5

3-3 Firm Concentration for Electric Power Generation, Transmission, and 

Distribution (NAICS 2211): 2002............................................................................... 3-7

3-4 United States Retail Electricity Sales Statistics: 2008 ................................................ 3-8

3-5 FY 2010 Financial Data for 70 U.S. Shareholder-Owned Electric Utilities............... 3-9

3-6 Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 2211 ....................... 3-9

3-7 Key Enterprise Statistics by Receipt Size for Electric Power Generation, 

Transmission, and Distribution (NAICS 2211): 2007............................................... 3-10

3-8 Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): 

(2007) ........................................................................................................................ 3-12

3-9 Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) (2007).................. 3-13

3-10 Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002...................... 3-13

3-11 Key Enterprise Statistics by Employment Size for Crude Petroleum and 

Natural Gas Extraction (NAICS 211111): 2007 ....................................................... 3-17

3-12 Key Enterprise Statistics by Employment Size for Crude Natural Gas Liquid 

Extraction (NAICS 211112): 2007............................................................................ 3-17

3-13 Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 211 ....................... 3-18

3-14 Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) (2007) ...... 3-19

3-15 Direct Requirements for Pipeline Transportation (NAICS 486): 2002..................... 3-21

3-16 Firm Concentration for Pipeline Transportation of Natural Gas (NAICS 

48621): 2002.............................................................................................................. 3-23
ix

3-17 Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 486 ....................... 3-23

3-18 Key Enterprise Statistics by Receipt Size for Pipeline Transportation of Natural 

Gas (NAICS 48621): 2007........................................................................................ 3-24

4-1 Summary of Annual and Capital Costs Equations for Existing Stationary SI 

Engines...................................................................................................................... 4-21

4-2 Summary of Major Source and Area Source Costs for the SI RICE NESHAP........ 4-22

4-3 Summary of Major Source and Area Source NAICS Costs for the SI RICE 

NESHAP ................................................................................................................... 4-23

4-4 Summary of Major Source and Area Source NAICS Costs for the SI RICE 

NESHAP, by Size...................................................................................................... 4-24

4-5 Summary of Major Source and Area Source NAICS Costs for the SI RICE 

NESHAP, by Number of Engines............................................................................. 4-28

4-6 Summary of Major Source and Area Source Baseline for the SI RICE 

NESHAP ................................................................................................................... 4-33

4-7 Emissions Factors...................................................................................................... 4-34

4-8 Summary of Major Source and Area Source Baseline Emissions for the SI

RICE NESHAP by 2013 ........................................................................................... 4-34

4-9 Summary of Major Source and Area Source Emissions Reductions for the SI

RICE NESHAP by 2013 ........................................................................................... 4-34

5-1 Selected Industry-Level Annualized Compliance Costs as a Fraction of Total 

Industry Revenue: 2009............................................................................................... 5-3

5-2 Hypothetical Price Increases for a 1% Increase in Unit Costs.................................... 5-5

5-3 Hypothetical Consumption Decreases for a 1% Increase in Unit Costs ..................... 5-7

5-4 U.S. Electric PoweraSector Energy Consumption (Quadrillion BTUs): 2013........... 5-9

5-5 Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, 

Operating, and Maintaining Control Equipment Requirements for Proposed 

Reconsideration SI RICE NESHAP........................................................5-16

6-1 Proposed NESHAP for Existing Stationary Reciprocating Internal Combustion 

Engines (RICE): Affected Sectors and SBA Small Business Size Standards............. 6-3

6-2 Average Receipts for Affected Industry by Enterprise: 2007 ($2009 

Million/Establishment)................................................................................................ 6-4

6-3 Average Receipts for Affected Industry by Enterprise Receipt Range: 2007

($2009/Establishment)................................................................................................. 6-5

6-4 Representative Establishment Costs Used for Small Entity Analysis ($2009)........... 6-7

7-1 Human Health Effects of PM2.5................................................................................... 7-2

7-2. General Summary of Monetized PM 2.5 –Related Health Co-Benefits Estimates 

for the Proposed SI RICE Reconsidered NESHAP in 2013 (millions of 2010$) ...... 7-9
x

7-3. Summary of Reductions in Health Incidences from PM2.5 Co-Benefits for the 

Proposed SI RICE Reconsidered NESHAP in 2013................................................ 7-10

7-4. All Monetized PM2.5 Co-Benefits from PM2.5 Benefits for the Proposed SI

RICE Reconsidered NESHAP in 2013 ..................................................................... 7-11

7-5. Summary of the Annualized Monetized Benefits, Social Costs, and Net 

Benefits for the Proposed SI RICE Reconsidered NESHAP in 2013 (millions 

of 2010$) ................................................................................................................... 7-31
1-1

Section 1

EXECUTIVE SUMMARY

ES.1 Summary of Impacts for the Proposed Reconsideration

This proposed action is a reconsideration of the promulgated NESHAP for existing 

stationary SI RICE with a site rating of less than or equal to 500 HP located at major sources, 

and existing stationary SI RICE of any site rating located at area sources. 

EPA estimates that complying with the proposed reconsidered national emission 

standards for hazardous air pollutants (NESHAP) for stationary spark-ignition (SI) reciprocating 

internal combustion engines (RICE) will have an annualized cost of approximately $115 million 

per year (2009 or 2010 dollars) in the year of full implementation of the rule (2013). The total 

annualized costs of the proposed reconsidered rule are 55% less than those for the final SI RICE 

NESHAP promulgated in 2010. Using these costs, EPA estimates in its economic impact 

analysis that the NESHAP will have limited impacts on the industries affected and their 

consumers. Using sales data obtained for affected small entities in an analysis of the impacts of 

this rule on small entities, EPA expects that the NESHAP will not result in a SISNOSE 

(significant economic impacts for a substantial number of small entities), a result consistent with 

the conclusion for the final SI RICE NESHAP issued in 2010. EPA also does not expect 

significant adverse energy impacts based on Executive Order 13211, an Executive Order that 

requires analysis of energy impacts for rules such as this one that are economically significant 

under Executive Order 12866.

In the year of full implementation (2013), EPA estimates that the total monetized benefits 

of the proposed reconsidered NESHAP are $62 million to $150 million and $55 million to $140

million, at 3% and 7% discount rates, respectively (Table 1-1). All estimates are in 2010 dollars 

for the year 2013. These estimates reflect the co-benefits from 9,600 tons of NOx emission 

reductions associated with implementing the controls to reduce hazardous air pollutants (HAPs) 

required under this proposed reconsideration. Using alternate relationships between PM2.5 and 

premature mortality supplied by experts, higher and lower benefits estimates are plausible, but 

most of the expert-based estimates fall between these estimates. The benefits from reducing other 

air pollutants have not been monetized in this analysis, including reducing 22,200 tons of carbon 

monoxide (CO) and 1,800 tons of hazardous air pollutants (HAPs) each year. In addition, 

ecosystem benefits and visibility benefits have not been monetized in this analysis. 
1-2

In the year of full implementation (2013), EPA estimates the net benefits of the proposed 

NESHAP are $-53 million to $35 million and $-60 million to $25 million at 3% and 7% discount 

rates, respectively (Table 1-1). These estimates are “snapshots” of benefits and costs at year 2013

and are in 2010 dollars. 
1-3

Table 1-1. Summary of the Annualized Monetized Co-Benefits, Social Costs, and Net 

benefits for the Proposed Reconsideration SI RICE NESHAP in 2013 (millions 

of 2010$)1

3% Discount Rate 7% Discount Rate

Total Monetized Benefits2$62 to $150 $55 to $140

Total Compliance Costs3$115 $115

Net Benefits $-53 to $35 $-60 to $25

Non-monetized Benefits

Health effects from HAP exposure

Health effects from CO, NO2, and ozone exposure

Ecosystem effects 

Visibility impairment 

1All estimates are for the implementation year (2013), and are rounded to two significant figures. 

2 The total monetized co-benefits reflect the human health co-benefits associated with reducing exposure to PM2.5

through reductions of PM2.5 precursors such as NOx and VOC. It is important to note that the monetized cobenefits include many but not all health effects associated with PM2.5 exposure. It is important to note that the 

monetized benefits include many but not all health effects associated with PM2.5 exposure. Benefits are shown as a range 

from Pope et al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical 

composition, are equally potent in causing premature mortality because there is no clear scientific evidence that would 

support the development of differential effects estimates by particle type. Because these estimates were generated 

using benefit-per-ton estimates, we do not break down the total monetized benefits into specific components here. 

See Figure 7-1 for an illustration of the breakdown, or the RIA for the final Cross-States Air Pollution Rule (EPA, 

2011) for more information. 

3 The annual compliance costs serve as a proxy for the annual social costs of this rule given the lack of difference 

between the two. The annual compliance costs are calculated using a 7 percent discount rate.

ES.2 Comparison of Impacts for Final 2010 SI RICE Final Rule and SI RICE NESHAP 

Proposed Reconsideration

The EPA analyzed the costs, economic impacts and benefits of this proposed rule using 

the identical methodology as the RIA for the SI RICE final rule promulgated in October, 2010.

Therefore, all changes to the costs, benefits, and economic impacts for this proposed rule are due 

to changes (or proposed amendments) to this proposed rule for SI RICE, which are fully

described later in this RIA and the preamble for the proposed rule. Our baseline does not assume 

compliance with the 2010 SI RICE final rule. This assumption is based on the fact that full 

implementation of the final rule has not taken place as of yet (it will take place by October, 

2013). In addition, this assumption is consistent with the baseline definition applied in the 

recently proposed ICI boilers and CISWI NESHAP rulemakings. Monetized benefits are the cobenefits of this proposal from reductions in directly emitted PM2.5 emissions. 
1-4

The following table shows an approximation of the changes in monetized benefits and 

engineering costs due to changes to the SI RICE rule included in the SI RICE reconsideration 

proposal, and includes values that show a comparison based on the final rule emissions 

inventory. All values in this table are in 2010 dollars.

Table 1-2. Summary of the Monetized Benefits and Compliance Costs for the 2010 Rule 

with the Proposed Amendments to the Stationary SI Engine NESHAP in 2013 (millions of 

2010 dollars)a

Monetized Benefits in 2013 Annual Engineering Costs in 

2013

SI RICE Final Rule (May 2010) $510 to $1,200 million $253 million

Changes due to the proposed 

amendments to the final SI RICE rule -$448 to $1,050 million -$138 million

Proposed SI RICE rule (2012) +$62 to $150 million $115 million

* Monetized benefits are shown at a 3% discount rate and are from reductions in PM2.5 emissions. These benefits do 

not include benefits associated with reduced exposure to HAP, visibility impairment, or ecosystem effects. 

Monetary estimates are in 2010 dollars.

The results for the economic impacts fall by more than half from those for the SI final 

rule. This outcome is due to the significant reduction in compliance costs associated with the 

proposed amendments in this proposal. All of the results for this proposed rule are found in 

Section 5 in this RIA.

The results for sales tests (i.e. annual cost/sales analysis) for small businesses also fall 

from those calculated for the final SI RICE rule. This outcome is also due to the overall large 

reductions in compliance costs. All of the results for this proposed rule are found in Section 6 in 

this RIA.

We estimate changes in employment for this SI RICE proposed rule. These estimates 

reflect the employment impacts associated with installation and operation of monitoring 

equipment, and also activities for recordkeeping, reporting, and testing. We estimate that 200 

full-time equivalents (FTEs) will be required as one-time labor for installation of equipment, and 

400 FTEs will be required as ongoing labor for compliance with the proposed rule. The results 

are presented and explained in detail in Section 5 of this RIA. We did not estimate changes in 

employment for the 2010 final SI RICE rule. 
1-5

The benefits estimates decreased significantly for the proposal. The range for the 2010 

final SI RICE RIA was $510 million (2009$) to $1,200 million (2009$) at 3 percent discount 

rate. The range for this proposal is $62 million (2010$) to $150 million (2010$) at 3 percent

discount rate. The range for the 2010 final SI RICE RIA was $460 million (2009$) to $1,100 

million (2009$) at 7 percent discount rate. The range for the proposal was $55 million (2010$) 

to $140 million (2010$) at 7 percent discount rate. 

The health benefits were calculated using a methodology described in the 2010 final SI

RICE RIA, using the revised emission reductions estimated for the reconsideration proposal and 

accounting for other changes discussed in detail in Section 7 of this RIA. We were unable to 

estimate the benefits from reducing exposure to HAPs, ecosystem impairment, and visibility

impairment, including reducing 22,000 tons of carbon monoxide, 9,000 tons of VOC and 1,800 

tons of HAPs. Please refer to the full description later in this RIA of the unquantified benefits as 

well as technical details of the analysis and its limitations and uncertainties. These monetized 

benefits are approximately 90% lower than the 2010 final SI RICE rule due to the estimated 

decrease in NOx emission reductions. These benefit-per-ton estimates were calculated for a 

2013 analysis year (i.e., using population and income growth for 2013). See Tables 1-2 and 1-3 

for the updated benefits results.

Table 1-3: Summary of Monetized PM2.5-Related Co-Benefits Estimates for SI RICE

Reconsideration Proposal in 2013

Pollutant

Emissions 

Reductions 

(tons)

Benefit 

per ton 

(Pope, 

3%)

Benefit 

per ton 

(Laden, 

3%)

Benefit 

per ton 

(Pope, 

7%)

Benefit 

per ton 

(Laden, 

7%)

Total 

Monetized 

Benefits 

(millions 2010$ 

at 3%)

Total Monetized 

Benefits 

(millions 2010$ 

at 7%)

NOx 9,648 $6,400 $16,000 $5,700 $14,000 $62 to $150 $55 to $140

Total $62 to $150 $55 to $140

*All estimates are for the implementation year (2013), and are rounded to two significant figures so numbers may 

not sum across columns. It is important to note that the monetized benefits do not include reduced health effects 

from direct exposure to NO2, ozone exposure, ecosystem effects, or visibility impairment. All fine particles are 

assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton of precursor 

reduced has a different propensity to form PM2.5. Confidence intervals are unavailable for this analysis because of 

the benefit-per-ton methodology.
1-6
1-7

Table 1-4: Summary of Estimated Reductions in Health Incidences from PM2.5 for the

SI RICE Reconsideration Proposal in 2013 

Proposed Option

Avoided Premature Mortality

Pope et al. 7

 Laden et al. 18

Avoided Morbidity

Chronic Bronchitis 5

Emergency Room Visits, Respiratory 5

Hospital Admissions, Respiratory 1

Hospital Admissions, Cardiovascular 3

Acute Bronchitis 11

Lower Respiratory 140

Upper Respiratory 110

Minor Restricted Activity Days 5,600

Work Loss Days 950

Asthma Exacerbation 230

Acute Myocardial Infarction 8

* All estimates are for the analysis year (2013) and are rounded to whole numbers with two significant figures. All 

fine particles are assumed to have equivalent health effects because the scientific evidence is not yet sufficient to 
1-8

allow differentiation of effects estimates by particle type. Confidence intervals are unavailable for this analysis 

because of the benefit-per-ton methodology.

Figure 1-1 provides a breakdown of the total monetized co-benefits from reductions of 

PM2.5 emissions by engine size associated with the reconsideration proposal. Figure 1-2 

provides a visual representation of the range of PM2.5-related benefits estimates using 

concentration-response functions supplied by experts. 

Figure 1-1: Breakdown of Total Monetized PM2.5 Co-Benefits of Proposed SI RICE 

Reconsideration by Engine Size 

Area 500-600 HP

21%

Area 600-750 HP

5%

Area >750 HP

74%
1-9

Figure 1-2: Total Monetized PM2.5 Co-Benefits Estimates for the SI RICE Reconsideration 

Proposal in 2013

*This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the 

Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on 

PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates 

are based in part on the concentration-response function provided in those studies. 

$0

$50

$100

$150

$200

$250

Pope et al.

Laden et al.

Millions (2010$)

PM2.5 mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions

2013*

3% DR

7% DR
1-10

Table 1-5 shows the estimated costs and benefits for the 2010 final SI RICE Rule and the 

reconsideration proposal. The estimated net benefits for the reconsideration proposal are 

considerably smaller than the range for the 2010 final SI RICE rule RIA, which was $210 

million to $860 million at a 7 percent discount rate and was $250 million to $980 billion at 3 

percent.

Table 1-5. Summary of Estimated Social Costs and Benefits for the 2010 final SI RICE rule 

and the Reconsideration Proposal (millions of 2010 dollars)1

3% Discount Rate 7% Discount Rate

2010 Final SI RICE NESHAP

Total Monetized Benefits $510 to $1,200 $460 to $1,100

Total Social Costs $253 $253

Net Benefits $250 to $980 $210 to $860

Proposed Reconsideration SI RICE NESHAP

Total Monetized Benefits $62 to $150 $55 to $140

Total Social Costs $115 $115

Net Benefits $-53 to $35 $-60 to $25

1All estimates are for the implementation year (2013), and are rounded to two significant figures. All monetized 

benefits are from reductions of PM2.5 emissions, a co-benefit of this proposal. The annual ized compliance costs 

are $115 million in 2010$ as noted earlier in this RIA, and are annualized using a 7% interest rate. Compliance 

costs are used as an approximation for social costs in this RIA. 
2-11

Section 2

INTRODUCTION

EPA is proposing NESHAP for existing stationary SI RICE that either are located at area 

sources of hazardous air pollutant emissions or that have a site rating of less than or equal to 500 

horsepower and are located at major sources of hazardous air pollutant emissions. The proposed 

amendments to the SI RICE NESHAP are provided in detail in Section 4 of this RIA. 

The rule is economically significant according to Executive Order 12866. As part of the 

regulatory process of preparing these standards, EPA has prepared a regulatory impact analysis 

(RIA). This analysis includes an analysis of impacts to small entities as part of compliance with 

the Small Business Regulatory Enforcement Fairness Act (SBREFA) and an analysis of impacts 

on energy consumption and production to comply with Executive Order 13211 (Statement of 

Energy Effects). An analysis of economic impacts, along with an analysis of impacts on 

employment, is also included in this RIA. Finally, an analysis of the benefits of the rule is 

included in this RIA. It should be noted that the data that supports the analyses listed above have 

been updated where possible and appropriate from the data used in the RIA for the SI RICE 

NESHAP promulgated in 2010. 

2.1 Organization of this Report

The remainder of this report supports and details the methodology and the results of the 

RIA:

 Section 3 presents a profile of the affected industries.

 Section 4 presents a summary of regulatory alternatives considered in the final rule, 

and provides the compliance costs of the rule. 

 Section 5 describes the estimated costs of the regulation and describes the economic 

impact analysis (EIA) methodology and reports market, welfare, energy, and 

employment impacts.

 Section 6 presents estimated impacts on small entities.

 Section 7 presents the benefits and net benefits (benefits- costs) estimates.
3-1

Section 3

INDUSTRY PROFILE

This section provides an introduction to the industries affected by the rule, i.e., industries 

in which the spark-ignition (SI) RICE being regulated are found. SI RICE generate electric 

power, pump gas or other fluids, or compress air for machinery. The primary non-utility

application of internal combustion (IC) engines is in the natural gas industry to power 

compressors used for pipeline transportation, field gathering (collecting gas from wells), 

underground storage tanks, and in-gas processing plants. RICEs are separated into three design 

classes: 2 cycle (stroke) lean burn, 4-stroke lean burn, and 4-stroke rich burn. Each of these have 

design differences that affect both baseline emissions as well as the potential for emissions 

control.

These industries include the following:

 electric power generation, transmission, and distribution (NAICS 2211),

 oil and gas extraction (including marginal wells) (NAICS 211), and

 pipeline transportation of natural gas (NAICS 48621).

While this is not an exhaustive list of the industries affected by this proposed 

reconsideration rule, these three industries incur about 83 percent of the annualized costs of the 

rule. A full listing of all industries affected in this rulemaking can be found in Chapter 4. The 

purpose of this profile chapter is to give the reader a general understanding of the economic 

aspects of the industry; their relative size, relationships with other sectors in the economy, trends 

for the industries, and financial statistics.

3.1 Electric Power Generation, Transmission, and Distribution

3.1.1 Overview

Electric power generation, transmission, and distribution (NAICS 2211) is an industry

group within the utilities sector (NAICS 22). It includes establishments that produce electrical 

energy or facilitate its transmission to the final consumer. 

From 2002 to 2007, revenues from electric power generation grew about 18% to over 

$440 billion ($2007) (Table 3-1).1 At the same time, payroll rose about 7% and the number of 

 

1 We provide revenues from electric power generation for the years 2002 and 2007 for these are years of the 

Economic Census. We reference data from these Economic Censuses frequently in this industry profile and 

show revenues from this industry over this time frame due to availability of such data. 
3-2

employees decreased by around 4%. The number of establishments rose by about 3%. Industrial 

production within NAICS 2211 has increased 26% since 1997 (Figure 3-1). 

Electric utility companies have traditionally been tightly regulated monopolies. Since 

1978, several laws and orders have been passed to encourage competition within the electricity

market. In the late 1990s, many states began the process of restructuring their utility regulatory

framework to support a competitive market. Following market manipulation in the early 2000s, 

however, several states have suspended their restructuring efforts. The majority (58%) of power 

generators controlled by combined heat and power (CHP) or independent power producers are 

located in states undergoing active restructuring (Figure 3-2).

Table 3-1. Key Statistics: Electric Power Generation, Transmission, and Distribution 

(NAICS 2211) ($2007)

2002 2007

Revenue ($106) 373,309 440,355

Payroll ($106) 40,842 43,792

Employees 535,675 515,335

Establishments 9,394 9,642

Source: U.S. Census Bureau; American FactFinder; “Sector 22: EC0722I2: Utilities: Industry Series: Preliminary 

Comparative Statistics for the United States (2002 NAICS Basis): 2007 and 2002.” http://factfinder.census.gov
3-3

Figure 3-1. Industrial Production Index (NAICS 2211)

Source: The Federal Reserve Board. “Industrial Production and Capacity Utilization: Industrial Production” Series 

ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G2211.S <http://www.federalreserve.gov/datadownload/>. 

(January 27, 2010).

3.1.2 Goods and Services Used

In Table 3-2, we use the latest detailed benchmark input-output data report by the Bureau 

of Economic Analysis (BEA) (2002) to identify the goods and services used in electric power 

generation. As shown, labor and tax requirements represent a significant share of the value of

power generation. Extraction, transportation, refining, and equipment requirements potentially

80

85

90

95

100

105

110

115

1997 -011997 -061997 -111998 -041998 -091999 -021999 -071999 -122000 -052000 -102001 -032001 -082002 -012002 -062002 -112003 -042003 -092004 -022004 -072004 -122005 -052005 -102006 -032006 -082007 -012007 -062007 -112008 -042008 -092009 -022009 -072009 -12

Index Value (Jan 2002=100)
3-4

Figure 3-2. Internal Combustion Generators by State: 2006

Source: U.S. Department of Energy, Energy Information Administration. 2007. “2006 EIA-906/920 Monthly Time 

Series.”

associated with reciprocating internal combustion engines (oil and gas extraction, pipeline 

transportation, petroleum refineries, and turbine manufacturing) represent around 10% of the 

value of services.

3.1.3 Business Statistics

The U.S. Economic Census and Statistics of U.S. Businesses (SUSB) programs provide 

national information on the distribution of economic variables by industry, location, and size of 

business. Throughout this section and report, we use the following definitions:

 Establishment: An establishment is a single physical location where business is 

conducted or where services or industrial operations are performed. 

Diesel and Natural Gas Internal

Combustion Generators By State

No Restructuring

Suspended Restructuring

Active Restructuring

100

50

10

1
3-5

Table 3-2. Direct Requirements for Electric Power Generation, Transmission, and 

Distribution (NAICS 2211): 2002

Commodity Commodity Description

Direct Requirements 

Coefficientsa

V00100 Compensation of employees 20.52%

V00200 Taxes on production and imports, less subsidies 13.71%

211000 Oil and gas extraction 6.16%

212100 Coal mining 5.86%

482000 Rail transportation 3.01%

230301 Nonresidential maintenance and repair 2.83%

486000 Pipeline transportation 1.70%

722000 Food services and drinking places 1.40%

52A000 Monetary authorities and depository credit intermediation 1.39%

541100 Legal services 1.13%

a These values show the amount of the commodity required to produce $1.00 of the industry’s output. The values 

are expressed in percentage terms (coefficient ×100).

Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table, 

Use Table and Direct Requirements Table. Tables 4 and 5.

 Receipts: Receipts (net of taxes) are defined as the revenue for goods produced, 

distributed, or services provided, including revenue earned from premiums, 

commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all 

revenue collected for local, state, and federal taxes.

 Firm: A firm is a business organization consisting of one or more domestic 

establishments in the same state and industry that were specified under common 

ownership or control. The firm and the establishment are the same for singleestablishment firms. For each multiestablishment firm, establishments in the same 

industry within a state are counted as one firm; the firm employment and annual 

payroll are summed from the associated establishments.

 Enterprise: An enterprise is a business organization consisting of one or more 

domestic establishments that were specified under common ownership or control. The 

enterprise and the establishment are the same for single-establishment firms. Each 

multiestablishment company forms one enterprise; the enterprise employment and 

annual payroll are summed from the associated establishments. Enterprise size 

designations are determined by the summed employment of all associated 

establishments.
3-6

In 2002, Texas had almost 1,000 power establishments, while California, Georgia, and 

Ohio all had between 400 and 500 (Figure 3-3). Hawaii, Nebraska, and Rhode Island all had 

fewer than 20 establishments in their states.

Figure 3-3. 2002 Regional Distribution of Establishments: Electric Power Generation, 

Transmission, and Distribution Industry (NAICS 2211)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 22: Utilities: 

Geographic Area Series: Summary Statistics: 2002.” <http://factfinder.census.gov>; (November 10, 2008)..

As shown in Table 3-3, the four largest firms owned over 1,200 establishments and 

accounted for about 16% of total industry receipts/revenue. The 50 largest firms accounted for 

almost 6,000 establishments and about 78% of total receipts/revenue. 

Investor-owned energy providers accounted for only 2% of retail electricity sold in the 

United States in 2008 (Table 3-4). In 2008, investor-owned energy provider companies with less 

than 50% of their assets regulated were unprofitable overall, while other companies in this 

category were profitable. (Table 3-5). In 2008, enterprises within NAICS 2211 had a pre-tax 

profit margin of 8.1% (Table 3-6).

In 2002, about 82% of firms generating, transmitting, or distributing electric power had 

receipts of under $50 million (Table 3-7). However, these firms accounted for only 11% of 

employment, with 89% of employees working for firms with revenues in excess of $100 million.

Establishments by State

Less than 100

100 - 199

200 - 349

350 - 500

More than 500
3-7

Table 3-3. Firm Concentration for Electric Power Generation, Transmission, and 

Distribution (NAICS 2211): 2002

Commodity Establishments

Receipts/Revenue

Number of 

Employees

Employees per 

Amount ($10 Establishment 6)

Percentage 

of Total

All firms 9,394 $325,028 100.0% 535,675 57

4 largest firms 1,260 $52,349 16.1% 68,432 54

8 largest firms 2,566 $95,223 29.3% 151,575 59

20 largest firms 3,942 $173,207 53.3% 271,393 69

50 largest firms 5,887 $253,015 77.8% 408,021 69

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 22: Utilities: 

Subject Series—Estab & Firm Size: Concentration by Largest Firms for the United States: 2002.”

<http://factfinder.census.gov>; (November 21, 2008).
3-8

Table 3-4. United States Retail Electricity Sales Statistics: 2008

Full-Service Providers Other Providers

Item Investor-Owned Public Federal Cooperative Facility Energy Delivery Total

Number of entities 3 62 1 25 1 NA NA 92 

Number of retail customers 46,985 2,160,220 36 940,697 1 NA NA 3,147,939 

Retail sales (103 megawatthours) 2,257 70,303 9,625 21,868 117 NA NA 104,170 

Percentage of retail sales 2 67 9 21 0 — — 100 

Revenue from retail sales ($106) 113 5,934 473 1,994 6 NA NA 8,520 

Percentage of revenue 1.33 69.65 5.55 23.41 0.07 — — 100 

Average retail price (cents/kWh) 5.01 8.44 4.91 9.12 5.25 NA NA 8.18 

Source: U.S. Department of Energy, Energy Information Administration. 2009. “State Electricity Profiles 2008.” DOE/EIA-0348(01)/2. p. 260. < 

http://www.eia.doe.gov/cneaf/electricity/st_profiles/sep2008.pdf>.
3-9

Table 3-5. FY 2010 Financial Data for 70 U.S. Shareholder-Owned Electric Utilities

Profit Margin Net Income Operating Revenues

Investor-Owned Utilities 4.81% $27,728 $371,545

Regulateda7.25% $12,341 $158,657

Mostly regulatedb8.50% $17,815 $175,218

Diversifiedc-16.78% -$2,429 $37,671

a

80%+ of total assets are regulated.

b

50% to 80% of total assets are regulated.

c Less than 50% of total assets are regulated.

Source: Edison Electric Institute. “Income Statement: Q4 2010 Financial Update. Quarterly Report of the U.S. 

Shareholder-Owned Electric Utility Industry.” <http://www.eei.org>.

Table 3-6. Aggregate Tax Data for Accounting Period 2009: NAICS 2211

Number of enterprisesa1,187

Total receipts (103) $323,522,443

Net sales(103) $328,017,143

Profit margin before tax 3.1%

Profit margin after tax 2.0%

a

Includes corporations with and without net income.

Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2000–

2009.” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2, 2010).
3-10

Table 3-7. Key Enterprise Statistics by Employee Size for Electric Power Generation, Transmission, and Distribution 

(NAICS 2211): 2007

Variable All Enterprises

<20 

Employees

20–99

Employees

100–499 

Employees

500+

Employees

Firms 1,687 630 670 251 136

Establishments 9,611 687 1,110 999 6,815

Employment 503,134 3,622 31,455 42,527 425,530

Receipts ($103) $440,342,284 $8,364,773 $21,825,969 $41,370,375 $368,781,167

Receipts/firm ($103) $261,021 $13,277 $32,576 $164,822 $2,711,626

Receipts/establishment 

($103) $45,817 $12,176 $19,663 $41,412 $54,113

Receipts/employment 

($) $875 $2,309 $694 $973 $867

Source: U.S. Census Bureau. 2010. “Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size: 2007.”

<http://www.census.gov/csd/susb/susb07.htm>.
3-11

3.2 Oil and Gas Extraction

3.2.1 Overview

Oil and gas extraction (NAICS 211) is an industry group within the mining sector 

(NAICS 21). It includes establishments that operate or develop oil and gas field properties 

through such activities as exploring for oil and gas, drilling and equipping wells, operating onsite equipment, and conducting other activities up to the point of shipment from the property. 

Oil and gas extraction consists of two industries: crude petroleum and natural gas 

extraction (NAICS 211111) and natural gas liquid extraction (NAICS 211112). Crude petroleum 

and natural gas extraction is the larger industry; in 2002, it accounted for 93% of establishments 

and 75% of oil and gas extraction revenues.

Industrial production in this industry is particularly sensitive to hurricanes in the Gulf 

Coast. In September of both 2005 and 2008, production dropped 14% from the previous month. 

(Figure 3-4).

From 2002 to 2007, revenues from crude petroleum and natural gas extraction (NAICS 

211111) grew over 117% to almost $215 billion ($2007) (Table 3-8). At the same time, payroll 

grew 55% and the number of employees grew by 48%. The number of establishments dropped 

by over 17%; as a result, the average establishment revenue increased by 162%. Materials costs 

were approximately 18% of revenue over the period.

From 2002 to 2007, revenue from natural gas liquid extraction (NAICS 211112) grew 

over 26% to about $42 billion (Table 3-9). At the same time, payroll dropped 18% and the 

number of employees dropped by 24%. The number of establishments dropped by 43%, resulting 

in an increase of revenue per establishment of about 122%.

3.2.2 Goods and Services Used

The oil and gas extraction industry has similar labor and tax requirements as the electric 

power generation sector. Extraction, support, power, and equipment requirements potentially

associated with RICE (oil and gas extraction, support activities, electric power generation, 

machinery and equipment rental and leasing, and pipeline transportation) represent around 8% of 

the value of services (Table 3-10).
3-12

Figure 3-4. Industrial Production Index (NAICS 211)

Source: The Federal Reserve Board. “Industrial Production and Capacity Utilization: Industrial Production” Series 

ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G211.S <http://www.federalreserve.gov/datadownload/>. 

(January 27, 2010).

Table 3-8. Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): 

($2007)

2002 2007

Revenue ($106) $98,667 $214,198

Payroll ($106) $5,785 $8,980

Employees 94,886 140,160

Establishments 7,178 5,956

Sources: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining: 

Industry Series: Historical Statistics for the Industry: 2002 and 1997.” <http://factfinder.census.gov>; 

(November 26, 2008).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: EC0721I1: Mining: 

Industry Series: Detailed Statistics by Industry for the United States: 2007 ” <http://factfinder.census.gov>; 

(April 27, 2010).

75

80

85

90

95

100

105

110

1997-011997-061997-111998-041998-091999-021999-071999-122000-052000-102001-032001-082002-012002-062002-112003-042003-092004-022004-072004-122005-052005-102006-032006-082007-012007-062007-112008-042008-092009-022009-072009-12

Index Value (Jan 2002=100)
3-13

Table 3-9. Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) ($2007)

2002 2007

Revenue ($106) $33,579 $42,363

Payroll ($106) $607 $501

Employees 9,693 7,343

Establishments 511 291

Sources: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining: 

Industry Series: Historical Statistics for the Industry: 2002 and 1997.” <http://factfinder.census.gov>; 

(November 26, 2008).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: EC0721I1: Mining: 

Industry Series: Detailed Statistics by Industry for the United States: 2007 ” <http://factfinder.census.gov>; 

(April 27, 2010).

Table 3-10. Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002

Commodity Commodity Description

Direct Requirements 

Coefficientsa

V00200 Taxes on production and imports, less subsidies 8.93%

V00100 Compensation of employees 6.67%

230301 Nonresidential maintenance and repair 6.36%

211000 Oil and gas extraction 1.91%

213112 Support activities for oil and gas operations 1.51%

221100 Electric power generation, transmission, and distribution 1.47%

541300 Architectural, engineering, and related services 1.24%

532400 Commercial and industrial machinery and equipment rental and leasing 1.20%

33291A Valve and fittings other than plumbing 1.10%

541511 Custom computer programming services 0.99%

a These values show the amount of the commodity required to produce $1.00 of the industry’s output. The values 

are expressed in percentage terms (coefficient ×100).

Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table, 

Use Table and Direct Requirements Table. Tables 4 and 5.

3.2.3 Business Statistics

The U.S. Economic Census and SUSB programs provide national information on the 

distribution of economic variables by industry, location, and size of business. Throughout this 

section and report, we use the following definitions:

 Establishment: An establishment is a single physical location where business is 

conducted or where services or industrial operations are performed. 
3-14

 Receipts: Receipts (net of taxes) are defined as the revenue for goods produced, 

distributed, or services provided, including revenue earned from premiums, 

commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all 

revenue collected for local, state, and federal taxes.

 Firm: A firm is a business organization consisting of one or more domestic 

establishments in the same state and industry that were specified under common 

ownership or control. The firm and the establishment are the same for singleestablishment firms. For each multiestablishment firm, establishments in the same 

industry within a state are counted as one firm; the firm employment and annual 

payroll are summed from the associated establishments.

 Enterprise: An enterprise is a business organization consisting of one or more 

domestic establishments that were specified under common ownership or control. The 

enterprise and the establishment are the same for single-establishment firms. Each 

multiestablishment company forms one enterprise; the enterprise employment and 

annual payroll are summed from the associated establishments. Enterprise size 

designations are determined by the summed employment of all associated 

establishments.

As of 2007, there were 6,563 firms within the NAICS 211111 code, of which 6427 (98 

percent) were considered small businesses (Table 3-11). Within NAICS 211111, large firms 

compose about 2 percent of the firms, but account for 59 percent of employment and generate 

about 80 percent of estimated receipts listed under the NAICS. Within NAICS 211112, there 

are 139 firms, of which 95 (71 percent) were considered small businesses (Table 3-12). As 

shown in this table, large firms compose 29 percent of the firms, but account for 78 percent of 

employment and generate about 95 percent of estimated receipts. 

Enterprises within this industry generated $193 billion in total receipts in 2008. Including 

those enterprises without net income, the industry averaged an after-tax profit margin of 8.5% 

(Table 3-13).
3-15

Figure 3-5. 2002 Regional Distribution of Establishments: Crude Petroleum and Natural 

Gas Extraction Industry (NAICS 211111)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining: 

Geographic Area Series: Industry Statistics for the State or Offshore Areas: 2007.” <http://factfinder.census.gov>; 

(January 27, 2010).

Establishments by State

Less than 100

100 - 249

250 - 499

500 - 1,000

More than 1,000
3-16

Figure 3-6. 2002 Regional Distribution of Establishments: Natural Gas Liquid 

Extraction Industry (NAICS 211112)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining: 

Geographic Area Series: Industry Statistics for the State or Offshore Areas: 2007.” <http://factfinder.census.gov>; 

(January 27, 2010).

Establishments by State

Less than 5

5 - 9

10 - 19

20 - 40

More than 40
3-17

Table 3-11. Key Statistics for Crude Petroleum and Natural Gas Extraction (NAICS 

211111): 2007

NAICS NAICS Description

SBA Size 

Standard 

Small 

Firms Large Firms Total Firms

Number of Firms by Firm Size

Crude Petroleum and Natural Gas Extraction 500 6,329 95 6,424

Total Employment by Firm Size

55,622 77,664 133,286

Estimated Receipts by Firm Size ($1000)

44,965,936 149,141,316 194,107,252

Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in 

receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census 

reports firm counts for firms with receipts less than $7.5 million. **Employment and receipts could not be split 

between small and large businesses because of non-disclosure requirements faced by the U.S. Census Bureau.

Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, 

and Estimated Receipts by Enterprise Receipt Size for the United States, All Industries: 2007.” 

<http://www.census.gov/econ/susb/>

Table 3-12. Key Statistics for Crude Natural Gas Liquid Extraction (NAICS 211112): 2007

NAICS Description

SBA Size 

Standard 

Small 

Firms Large Firms Total Firms

Number of Firms by Firm Size

Natural Gas Liquid Extraction 500 98 41 139

Total Employment by Firm Size

1,875 6,648 8,523

Estimated Receipts by Firm Size ($1000)

2,164,328 37,813,413 39,977,741

Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in 

receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census 

reports firm counts for firms with receipts less than $7.5 million. **Employment and receipts could not be split 

between small and large businesses because of non-disclosure requirements faced by the U.S. Census Bureau.

Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, 

and Estimated Receipts by Enterprise Receipt Size for the United States, All Industries: 2007.” 

<http://www.census.gov/econ/susb/>
3-18

Table 3-13. Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 211

Number of enterprisesa19,441

Total receipts (103) $193,230,241

Net sales(103) $166,989,539

Profit margin before tax 12.9%

Profit margin after tax 8.5%

a

Includes corporations with and without net income.

Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2004-

2007.” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2, 2010).

3.3 Pipeline Transportation of Natural Gas

3.3.1 Overview

Pipeline transportation of natural gas (NAICS 48621) is an industry group within the 

transportation and warehousing sector (NAICS 48-49), but more specifically in the pipeline 

transportation subsector (486). It includes the transmission of natural gas as well as the 

distribution of the gas through a local network to participating businesses. 

From 2002 to 2007, natural gas transportation revenues fell by 29% to just over $16

billion ($2007) (Table 3-14). At the same time, payroll decreased by 14%, while the number of 

paid employees decreased by nearly 25%. The number of establishments also fell by 8% from 

1,701 establishments in 2002 to 1,560 in 2007.

3.3.2 Goods and Services Used

The BEA reports pipeline transportation of natural gas only for total pipeline 

transportation (3-digit NAICS 486). In addition to pipeline transportation of natural gas (NAICS 

4862), this industry includes pipeline transportation of crude oil (NAICS 4861) and other 

pipeline transportation (NAICS 4869). However, the BEA data are likely representative of the 

affected sector since pipeline transportation of natural gas accounts for 60% of NAICS 486 

establishments and 66% of revenues (Figures 3-8 and 3-9).
3-19

Table 3-14. Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) ($2007)

Year 2002 2007

Revenue ($106) 16,368 20,797

Payroll ($106) 2,086 2,064

Employees 24,519 24,683

Establishments 1,560 1,479

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: EC0748I1: 

Transportation and Warehousing: Industry Series: Preliminary Summary Statistics for the United States: 2002 and 

2007.” http://factfinder.census.gov (January 27, 2010).

Figure 3-8. Distribution of Establishments within Pipeline Transportation (NAICS 486)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: 

Transportation and Warehousing: Industry Series: Summary Statistics for the United States: 2002 

<http://factfinder.census.gov>; (January 27, 2010).

In Table 3-15, we use the latest detailed benchmark input-output data report by the BEA 

(2002) to identify the goods and services used by pipeline transportation (NAICS 486). As 

shown, labor, refineries, and maintenance requirements represent significant share of the cost 

associated with pipeline transportation. Power and equipment requirements potentially associated 

with reciprocating internal combustion engines (electric power generation and distribution) 

represent less than 2% of the value of services.

60%

25%

15%

0%

10%

20%

30%

40%

50%

60%

70%

4862 Pipeline

Transportation of

Natural Gas

4869 Other Pipeline

Transportation

4861 Pipeline

Transportation of Crude

Oil
3-20

Figure 3-9. Distribution of Revenue within Pipeline Transportation (NAICS 486)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: 

Transportation and Warehousing: Industry Series: Summary Statistics for the United States: 2002”

<http://factfinder.census.gov>; (January 27, 2010).

3.3.3 Business Statistics

The pipeline transportation of natural gas is clearly concentrated in the two states closest 

to the refineries in the Gulf of Mexico. In 2002, Texas and Louisiana contributed to 31% of all 

pipeline transportation establishments in the United States (Figure 3-10) and 41% of all U.S. 

revenues. Other larger contributors with over 50 establishments in their states include Oklahoma, 

Pennsylvania, Kansas, Mississippi, and West Virginia.

According to 2002 U.S. Census data, about 86% of transportation of natural gas 

establishments were owned by corporations and about 8% were owned by individual 

proprietorships. About 6% were owned by partnerships (Figure 3-11). As shown in Table 3-16, 

the four largest firms accounted for nearly half of the establishments, and just over half, 51%, of 

total revenue. The 50 largest firms accounted for over 1,354 establishments and about 99% of 

total revenue. The average number of employees per establishment was approximately 17 across 

all groups of firms. 

Enterprises within pipeline transportation (NAICS 486) generated $11.1 billion in total 

receipts in 2008. Including those enterprises without net income, the industry averaged an aftertax profit margin of 9.6% (Table 3-17).

66%

19%

15%

0%

10%

20%

30%

40%

50%

60%

70%

4862 Pipeline

Transportation of

Natural Gas

4869 Other Pipeline

Transportation

4861 Pipeline

Transportation of Crude

Oil
3-21

Table 3-15. Direct Requirements for Pipeline Transportation (NAICS 486): 2002

Commodity Commodity Description

Direct 

Requirements 

Coefficientsa

V00100 Compensation of employees 14.78%

324110 Petroleum refineries 13.55%

230301 Nonresidential maintenance and repair 6.07%

211000 Oil and gas extraction 4.94%

333415 Air conditioning, refrigeration, and warm air heating equipment 

manufacturing

4.40%

561300 Employment services 4.26%

5416A0 Environmental and other technical consulting services 3.04%

541300 Architectural, engineering, and related services 3.04%

420000 Wholesale trade 2.79%

332310 Plate work and fabricated structural product manufacturing 2.72%

5419A0 All other miscellaneous professional, scientific, and technical services 2.48%

524100 Insurance carriers 2.38%

531000 Real estate 2.33%

52A000 Monetary authorities and depository credit intermediation 1.76%

V00200 Taxes on production and imports, less subsidies 1.41%

541100 Legal services 1.19%

221100 Electric power generation, transmission, and distribution 1.13%

a These values show the amount of the commodity required to produce $1.00 of the industry’s output. The values 

are expressed in percentage terms (coefficient ×100).

Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table, 

Use Table and Direct Requirements Table. Tables 4 and 5.

The 2007 SUSB shows that 47% of all firms in this industry made under $5 million in 

revenue. Enterprises with revenue over $100 million provided an overwhelming share of 

employment in this industry (98%) (Table 3-18).
3-22

Figure 3-10. 2002 Regional Distribution of Establishments: Pipeline Transportation 

(NAICS 486)

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49: 

Geographic Distribution—Pipeline transportation of natural gas: 2002. <http://factfinder.census.gov>; (November 

10, 2008).

Figure 3-11. Share of Establishments by Legal Form of Organization in the Pipeline 

Transportation of Natural Gas Industry (NAICS 48621): 2002

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49: 

Transportation and Warehousing: Subject Series—Estab & Firm Size: Legal Form of Organization for the United 

States: 2002. <http://factfinder.census.gov>; (December 12, 2008).

Establishments by State

Less than 15

15 - 39

40 - 79

80 - 149

More than 150

86%

8% 6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Corporations Individual Proprietorships Partnerships
3-23

Table 3-16. Firm Concentration for Pipeline Transportation of Natural Gas (NAICS 

48621): 2002

Commodity Establishments

Receipts/Revenue

Number of 

Employees

Employees per 

Amount ($10 Establishment 6)

Percentage of 

Total

All firms 1,431 $14,797 100% 23,677 16.5

4 largest firms 698 $7,551 51% 11,814 16.9

8 largest firms 912 $10,059 68% 15,296 16.8

20 largest firms 1,283 $13,730 93% 21,792 17.0

50 largest firms 1,354 $14,718 99% 23,346 17.2

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: 

Transportation and Warehousing: Subject Series—Estab & Firm Size: Concentration by Largest Firms for the 

United States: 2002” <http://factfinder.census.gov>; (December 12, 2008).

Table 3-17. Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 486

Number of enterprisesa

321

Total receipts (103)

$11,062,608

Net sales (103)

$10,210,083

Profit margin before tax 13.2%

Profit margin after tax 9.6%

a

Includes corporations with and without net income.

Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2004-

2007.” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2, 2010).
3-2

4

Table 3-18. Key Enterprise Statistics by Employee Size for Pipeline Transportation of Natural Gas (NAICS 48621): 2007

Variable All Enterprises

<20 

Employees

20–99 

Employees

100–499 

Employees 500+ Employees

Firms 126 63 12 9 42

Establishments 1.479 66 26 70 1,317

Employment 24,683 241 382 1,479 22,581

Receipts ($103) $20,796,681 N/A $518,341 $1,448,020 $18,498,143

Receipts/firm ($103) $165,053 N/A $43,195 $160,891 $440,432

Receipts/establishment 

($103)

$14,061 N/A $19,936 $20,686 $14,046

Receipts/employment 

($)

$843 N/A $1,357 $979 $819

Source: U.S. Census Bureau. 2011. Firm Size Data from the Statistics of U.S. Businesses, U.S. All Industries Tabulated by Employee Size: 2007. 

http://www2.census.gov/csd/susb/2007/usalli_r07.xls.
4-1

Section 4

REGULATORY ALTERNATIVES, COSTS, AND EMISSION IMPACTS

4.1 Background

This section of the RIA includes a discussion of the regulatory alternatives considered for 

the proposed reconsidered rule, the costs associated with these regulatory alternatives, and the 

impacts on affected emissions (both HAP and non-HAP). All impacts presented are for the year 

of full implementation, 2013. Costs in this section are in 2009$. Costs in 2010$ presented 

elsewhere in the RIA are updated values based on the 2009$ costs presented in this section. 

Although the estimates presented are annualized, they should be understood as a “snapshot” in 

analyzing costs. Annualized costs are estimated as equal for each year that control equipment is 

operated. 

This proposal was developed to address certain issues that have been raised by different 

stakeholders through lawsuits, several petitions for reconsideration of the 2010 RICE NESHAP 

amendments and other communications. After promulgation of the 2010 RICE NESHAP 

amendments, the EPA received several petitions for reconsideration, legal challenges, and other 

communications raising issues of practical implementability, and certain factual information that 

had not been brought to the EPA’s attention during the rulemaking. The EPA has considered this 

information and believes that amendments to the rule to address certain of these issues are 

appropriate. Therefore, the EPA is proposing amendments to the national emission standards for 

hazardous air pollutants for stationary reciprocating internal combustion engines under section 

112 of the Clean Air Act. The proposed amendments include alternative testing options for 

certain large spark ignition (generally natural gas-fueled) stationary reciprocating internal 

combustion engines, management practices for a subset of existing spark ignition stationary

reciprocating internal combustion engines in sparsely populated areas, and alternative and less 

burdensome monitoring and compliance options for the same engines in populated areas. The 

EPA is also proposing to include a limited temporary allowance for existing stationary

emergency area source engines to be used for peak shaving and non-emergency demand 

response as part of the pre-existing allowance for such engines to be used for non-emergency use 

for 50 hours annually. In addition, the EPA is proposing, in both the NESHAP and in the new 

source performance standards for stationary internal combustion engines to increase the hours 

that stationary emergency engines may be used for emergency demand response. The proposed 

amendments also correct minor mistakes in the pre-existing regulations. The full preamble for 

the final SI RICE NESHAP and the rule itself can be reviewed at 

http://www.epa.gov/ttn/atw/rice/fr20au10.pdf. 
4-2

4.2 Proposed Amendments to SI RICE NESHAP

4.2.1. Total Hydrocarbon Compliance (THC) Demonstration Option

4.2.1.1. Background

Currently, SI 4SRB non-emergency engines greater than 500 HP and located at major 

sources and existing SI 4SRB non-emergency engines greater than 500 HP located at area 

sources have the option of meeting either a formaldehyde percent reduction or a formaldehyde 

concentration standard. Formaldehyde was established in the original 2004 RICE NESHAP as an 

appropriate surrogate for HAP emissions from 4SRB engines based on industry test data 

available at that time. Based on testing conducted at Colorado State University (CSU) of 

stationary lean burn engines, the EPA was able to establish CO as a surrogate for HAP for lean 

burn engines. Rich burn engines were not tested at CSU and the data the EPA had available at 

the time that were used to set the standards for rich burn engines did not support the same 

relationship between CO and HAP reductions for rich burn engines. Therefore, the EPA was 

unable to establish CO as a surrogate for HAP emissions for rich burn engines and the emission 

standard for rich burn engines was specified in terms of formaldehyde, the hazardous air 

pollutant emitted in the largest quantity from stationary engines. 

The EPA has previously acknowledged that it is significantly more expensive and 

difficult to test for formaldehyde than for CO, but has been unable in the past to support 

including the same flexibility for rich burn engines as is currently in the rule for lean burn 

engines with the option to meet the standards in terms of either formaldehyde or CO. For these 

reasons, and expecting that new data for rich burn engines may become available in the future 

for the EPA to review and reassess possible surrogates for HAP, the EPA requested comment on 

this issue when proposing NESHAP for stationary existing engines less than or equal to 500 HP

at major sources and all stationary existing engines at area sources in 2009 (74 FR 9698). 

Specifically, the EPA solicited comment on whether it would be appropriate to include an 

alternative standard in terms of VOC and asked that commenters submit data supporting the 

relationship between HAP and VOC. Comments the EPA received back on the proposed rule 

asked that the formaldehyde standards for rich burn engines be replaced with emission standards 

for THC. The EPA determined at the time that it was not appropriate to adopt an alternative 

standard in terms of THC (or VOC) for rich burn engines and discussed the reasons why in the 

2010 responses to comments. Compliance with the formaldehyde standard in the rule is, 
4-3

therefore, currently demonstrated by initial and continuous performance testing for 

formaldehyde. 

On October 19, 2010, engine manufacturer Dresser-Waukesha submitted a petition for 

reconsideration of the formaldehyde requirements. The EPA granted the petition for 

reconsideration on January 5, 2011. (In addition, on November 3, 2010, the Engine 

Manufacturers Association submitted a petition for judicial review of these requirements.) In the 

petition for reconsideration, Dresser-Waukesha argued that formaldehyde is difficult and costly

to measure. The petition requested that the HAP surrogate for 4SRB engines should be THC 

rather than formaldehyde. Dresser-Waukesha submitted data from testing it conducted 

illustrating that THC reduction across the catalyst is an appropriate surrogate for HAP reduction 

across the catalyst. According to the petitioner, testing for THC is easier and less costly and 

would substantially reduce the burden of the rule for owners and operators of these engines. 

Testing for formaldehyde emissions could cost more than double that of testing for THC 

emissions and on a nationwide basis the EPA estimates that replacing formaldehyde testing with 

THC testing would result in substantial compliance cost savings annually while achieving the 

same reduction in HAP emissions. 

The EPA has reviewed the data submitted by Dresser-Waukesha. The data provided 

indicate that a strong relationship exists between percentage reductions of THC and percentage 

reductions of formaldehyde (the surrogate for HAP emissions in the NESHAP) on rich burn 

engines using non-selective catalytic reduction (NSCR). Data analyzed by the EPA indicate that 

if the NSCR is reducing THC by at least 30 percent from 4SRB engines, formaldehyde emissions 

are guaranteed to be reduced by at least 76 percent, which is the percentage reduction required 

for the relevant engines. Indeed, the percentage reduction of formaldehyde is invariably well 

above the 76 percent level, and is usually above 90 percent. Therefore, the EPA agrees with the 

petitioner that for SI 4SRB engines using NSCR and meeting the NESHAP by showing a 

percentage reduction of HAP, it would be appropriate to allow sources to demonstrate 

compliance with the NESHAP by showing a THC reduction of at least 30 percent. Including an 

optional THC compliance demonstration option would reduce the burden of compliance 

significantly while continuing to achieve the same level of HAP emission reduction because the 

emission standards would remain the same. Consequently, the EPA is proposing amendments to 

allow owners and operators of certain stationary 4SRB engines (i.e., the ones currently subject to 

a formaldehyde percent reduction requirement) to show compliance with an optional THC 

compliance demonstration option. The specific amendments the EPA is proposing are presented 

below.
4-4

4.2.1.2. Proposed Amendments

The EPA is proposing to add an alternative method of demonstrating compliance with the 

NESHAP for stationary 4SRB non-emergency engines greater than 500 HP that are located at 

major sources of HAP emissions and for existing stationary 4SRB non-emergency engines 

greater than 500 HP that are located at area sources of HAP emissions that choose to meet the 

formaldehyde percent reduction requirement of 76 percent or more.

Based on the arguments and evidence presented in the petition discussed above, the EPA 

is proposing to add a compliance demonstration option for stationary 4SRB engines meeting a 76 

percent or more formaldehyde reduction. The compliance demonstration option would be an 

alternative to the existing method of demonstrating compliance with the formaldehyde percent 

reduction standard, which is to test engines for formaldehyde. The alternative for owners and 

operators of 4SRB engines meeting a 76 percent or more formaldehyde reduction would be to 

test their engines for THC showing that the engine is achieving at least a 30 percent reduction of 

THC emissions. 

Under the proposed amendments, existing and new stationary 4SRB engines greater than 

500 HP and located at major sources would still be required to reduce formaldehyde emissions 

by 76 percent or more or limit the concentration of formaldehyde in the stationary RICE exhaust 

to 350 parts per billion by volume, dry basis or less at 15 percent oxygen (O2). However, owners 

and operators choosing to meet the formaldehyde concentration limit would not have the THC 

demonstration compliance option, because EPA could not verify a clear relationship between 

concentrations of THC and concentrations of formaldehyde in exhaust from these SI 4SRB 

engines. The EPA is proposing that existing stationary 4SRB non-emergency engines greater 

than 500 HP located at area sources located in populated areas be subject to an equipment 

standard and required to install a catalyst. These engines would be subject to testing to 

demonstrate initially and on an ongoing basis that the catalyst is reducing CO by 75 percent or 

more, or alternatively that THC emissions are being reduced by 30 percent or more. 

Owners and operators of existing stationary 4SRB engines less than or equal to 500 HP 

who are required to limit the concentration of formaldehyde in the stationary RICE exhaust to 

10.3 parts per million by volume, dry basis (ppmvd) or less at 15 percent O2 do not have the 

option to demonstrate compliance using THC and must continue to demonstrate compliance by

testing for formaldehyde following the methods and procedures specified in the rule.
4-5

Owners and operators opting to use the THC compliance demonstration method must 

demonstrate compliance by showing that the average reduction of THC is equal to or greater 

than 30 percent. Owners and operators of 4SRB stationary RICE complying with the requirement 

to reduce formaldehyde emissions and demonstrating compliance by using the THC compliance 

demonstration option must conduct performance testing using Method 25A of 40 CFR part 60, 

appendix A – Determination of Total Gaseous Organic Concentration Using a Flame Ionization 

Analyzer. Measurements of THC at the inlet and the outlet of the NSCR must be on a dry basis 

and corrected to 15 percent O2 or equivalent carbon dioxide content. To correct to 15 percent 

O2, dry basis, owners and operators must measure oxygen using Method 3, 3A or 3B of 40 CFR 

part 60, appendix A, or ASTM Method D6522-00 (2005) and measure moisture using Method 4 

of 40 CFR part 60, appendix A, or Test Method 320 of 40 CFR part 63, appendix A, or ASTM 

D6348-03. Because owners and operators are complying with a percent reduction requirement, 

the method used must be suitable for the entire range of emissions since pre and post-catalyst 

emissions must be measured. Method 25A is capable of measuring emissions down to 5 ppmv 

and is, therefore, an appropriate method for measuring THC emissions for compliance 

demonstration purposes. The EPA is allowing sources the option to meet a minimum THC 

percent reduction of 30 percent by using Method 25A of 40 CFR part 60, appendix A to 

demonstrate compliance with the formaldehyde percent reduction in 40 CFR part 63, subpart 

ZZZZ.

4.2.2. Proposed Amendment - Emergency Demand Response/Peak Shaving

The EPA is proposing to revise the current provisions for stationary engines used for 

emergency demand response operation. The provisions the EPA is proposing to amend are in 

§§63.6640(f) and 63.6675 of 40 CFR part 63, subpart ZZZZ. Currently, §63.6640(f)(1)(iii) 

allows a maximum of 15 hours per year to be spent towards demand response operation under 

certain qualifying conditions. Also, §63.6640(f)(1)(ii) currently includes an allowance of 100 

hours per year for purposes of maintenance checks and readiness testing. The EPA is proposing 

that owners and operators of stationary emergency RICE be permitted to operate their engines as 

part of an emergency demand response program within the 100 hours per year that is permitted 

for maintenance and testing in §63.6640(f)(1)(ii). Owners and operators of stationary emergency

engines can operate for emergency demand response during periods in which the regional 

transmission authority or equivalent balancing authority and transmission operator has declared 

an EEA Level 2 as defined in the North American Electric Reliability Corporation Reliability

Standard EOP-002-3, Capacity and Energy Emergency and during periods where there is a 

deviation of voltage or frequency of 5 percent or greater below standard voltage or frequency. 
4-6

The hours spent for emergency demand response operation are added to the hours spent for 

maintenance and testing purposes and counted towards the 100 hours per year. If the total time 

spent for demand response operation and maintenance and testing exceeds 100 hours per year the 

engine will not be considered an emergency engine under this subpart and will need to meet all 

requirements for non-emergency engines. The EPA is recognizing that these engines may be 

called to operate not only by the regional transmission operator or equivalent to maintain the 

reliability of the bulk power system, but also by the local transmission and distribution system 

operators to support the local power systems.

For stationary emergency engines above 500 HP that were installed prior to June 12, 

2006, there is currently no emergency demand response allowance and there is no time limit on 

the use of emergency engines for routine testing and maintenance in §63.6640(f)(2)(ii). Those 

engines were not the focus of the 2010 RICE NESHAP amendments; therefore, the EPA did not 

make any changes to the requirements for those engines as part of the 2010 amendments. For 

consistency, the EPA is now also proposing that owners and operators of stationary emergency

engines installed prior to June 12, 2006, be permitted to operate their engines as part of a demand 

response program as well for a total of 100 hours per year, including time spent for maintenance 

and testing.

The EPA is also proposing to amend the NSPS for stationary CI and SI engines in 40 

CFR part 60, subparts IIII and JJJJ, respectively, to provide the same allowance for stationary 

emergency engines for emergency demand response operation as for engines subject to the RICE 

NESHAP. The NSPS regulations currently do not include such an allowance for emergency 

demand response operation. For the reasons discussed as to why the EPA finds it appropriate to 

allow stationary emergency engines to participate in emergency demand response programs and 

remain being considered emergency units, and for consistency across engine regulations, the 

EPA is proposing to add an emergency demand response allowance under the NSPS regulations. 

Consequently, the EPA is proposing to revise the existing language in §§60.4211(f) and 60.4219 

of 40 CFR part 60, subpart IIII, and §§60.4243(d) and 60.4248 of 40 CFR part 60, subpart JJJJ, 

to specify that emergency engines may participate in demand response programs for up to 100 

hours per year, including hours spent towards maintenance and testing of the emergency engines.

In addition to the changes the EPA is proposing related to emergency demand response 

operation, the EPA is also including a further provision for owners and operators of existing 

stationary emergency RICE located at area sources for the reasons discussed. Paragraph 

§63.6640(f) currently allows owners and operators of emergency stationary RICE to operate 

their engine for 50 hours per year in non-emergency situations. As currently written, the 50 hours 
4-7

per year for non-emergency situations cannot be used for peak shaving or to generate income for 

a facility to supply power to an electric grid or otherwise supply power as part of a financial 

arrangement with another entity; except that owners and operators of certain emergency engines 

may operate the engine for a maximum of 15 hours per year as part of an emergency demand 

response program. As discussed, the 15 hours per year allowance for emergency engines to 

participate in emergency demand response programs is being increased to 100 hours per year, 

but will also include hours spent towards maintaining and conducting readiness testing of the 

emergency engines. However, additionally, the EPA is also proposing that stationary emergency 

engines located at area sources be permitted to apply the 50 hours per year that is currently 

allowed under §63.6640(f) for non-emergency operation towards any non-emergency operation, 

including operation as part of a financial agreement with another entity. The peak shaving 

allowance would expire in 2017. The EPA is specifying that the power can only be used at the 

facility or towards the local system, and the engine can only be operated for peak shaving as part 

of a program with the local distribution system operator. The EPA is also clarifying that an 

engine that exceeds the calendar year limitations on non-emergency operation, including 

emergency demand response or peak shaving, will be considered a non-emergency engine and 

subject to the requirements for non-emergency engines for the remaining life of the engine.

To estimate emissions from emergency engines the EPA has previously estimated that

these types of engines would on average operate for 50 hours per year. The average hours of 

operation for emergency engines is not expected to change based on the proposed amendments 

and 50 hours per year is still believed to be representative of emergency engine operation. 

Therefore, the emissions previously calculated remain appropriate. In terms of any revenue 

generated from participation in demand response and peak shaving programs, the EPA expects 

owners and operators will benefit financially, however, the EPA does not know to what extent. 

The EPA expects there will be savings and/or income generated through participation in 

emergency demand response programs and peak shaving operation, but the EPA has not 

accounted for any potential revenue in estimating the costs and benefits of the proposed 

amendments. It is uncertain how frequently stationary emergency engines would operate if they

are called upon. Other factors, such as the annual revenue from demand response programs 

(which varies), are also uncertain making it problematic to estimate the economic benefit of such 

programs. As such, the EPA has not estimated any costs associated with the emergency engine 

amendments.
4-8

4.2.3 Proposed Amendment - Non-Emergency Stationary SI RICE Greater than 500 HP Located 

at Area Sources

4.2.3.1. Background

The EPA is also proposing to amend the requirements that apply to existing stationary

non-emergency 4 stroke SI RICE greater than 500 HP located at area sources of HAP emissions, 

which are generally natural gas fired engines. Currently, the RICE NESHAP requires owners and 

operators of such engines to 1) either meet a CO concentration limit of 47 parts ppmvd at 15 

percent O2 or reduce emissions of CO by 93 percent or more, if the engines are 4SLB; and 2) to 

meet a formaldehyde concentration limit of 2.7 ppmvd at 15 percent O2 or reduce formaldehyde 

emissions by 76 percent or more, if the engines are 4SRB. In both cases, the EPA expects that 

the standards would be met using aftertreatment; oxidation catalysts for 4SLB engines and 

NSCR for 4SRB engines. In addition to these emission requirements, owners and operators of 

existing stationary 4-stroke engines greater than 500 HP at area sources are also subject to 

monitoring, testing, recordkeeping and reporting requirements. 

After the final requirements for existing stationary SI engines greater than 500 HP at area 

sources were published on August 20, 2010 (75 FR 51570), the EPA received petitions from 

Exterran (EPA-HQ-OAR-2008-0708-0581), the American Petroleum Institute (EPA-HQ-OAR2008-0708-0582), the Interstate Natural Gas Association of America (EPA-HQ-OAR-2008-

0708-0584), and the Gas Processors Association (EPA-HQ-OAR-2008-0708-0587) requesting 

that the EPA reconsider the requirements of the final rule. The petitioners expressed many 

similar concerns. As relevant to this rulemaking, petitioners stated that the EPA did not take into 

account the difference in population density and subsequently did not consider the difference in 

health impacts in remote versus more heavily populated locations. In the petitioner’s opinion, 

there should be less concern about engines that are located farther away from people; the 

petitioners believed that the EPA has substantial latitude in requiring less stringent standards for 

owners and operators of stationary engines in remote areas.

While the EPA does not share all of the views of the petitioners regarding the difference 

between engines based on their location, the EPA does believe that it is reasonable to create a 

subcategory of existing stationary SI 4SLB and 4SRB engines above 500 HP located in areas 

remote from human activity. Engines located in remote areas that are not close to significant 

human activity may be difficult to access, may not have electricity or communications, and may

be unmanned most of the time. The costs of the emission controls, testing, and continuous 

monitoring requirements may be unreasonable when compared to the HAP emission reductions 
4-9

that would be achieved, considering that the engines are in sparsely populated areas. The EPA 

believes that establishing a subcategory for SI engines at area sources of HAP located in sparsely 

populated areas accomplishes the agency’s goals and is adequate in protecting public health.

The EPA is proposing to subcategorize sparsely populated engines using the existing 

DOT pipeline classification system. This system classifies locations based on their distance to 

pipelines covered by the Pipeline and Hazardous Materials Safety Administration safety 

regulations. The DOT system defines a class location unit as an onshore area that extends 220 

yards or 200 meters on either side of the centerline of any continuous 1-mile (1.6 kilometers) 

length of pipeline. The DOT approach further classifies pipeline locations into Class 1 through 

Class 4 locations based on the number of buildings intended for human occupancy. A Class 1 

location is defined as an offshore area or any class location unit that has 10 or fewer buildings 

intended for human occupancy. The DOT classification system also has special provisions for 

locations that lie within 100 yards (91 meters) of either a building or a small, well-defined 

outside area (such as a playground, recreation area, outdoor theater, or other place of public 

assembly) that is occupied by 20 or more persons on at least 5 days a week for 10 weeks in any

12-month period, and for class location units where buildings with four or more stories above 

ground are prevalent. To be considered remote, a source could not fall under one of these special 

provisions. 

Stakeholders from the oil and gas industry have indicated to the EPA that the DOT 

system is well-established and there would be substantial overlap between engines affected by 

the rule and covered by the DOT pipeline classification system. Incorporating this approach 

would also create harmonization between the EPA and DOT and would reduce the 

implementation and enforcement burden for states. Implementation for affected sources would 

also be less burdensome because the system is already in place and used by industry and covers 

the majority of these engines. Stakeholders have indicated they are required to review the class 

location status of pipeline segments annually. The EPA believes this approach is reasonable for 

defining the subcategory of remote engines for those engines that are associated with natural gas 

pipelines. For those engines not associated with pipelines, the EPA is using similar criteria. An 

engine would be considered to be in sparsely populated areas if within 0.25 mile radius of the 

engine there are 5 or fewer buildings intended for human occupancy. EPA requests comment on 

whether the use of these DOT classifications are appropriate for airborne emissions and whether, 

to be considered remote, an engine not associated with a natural gas pipeline should also need to 

be farther than 100 yards (91 meters) of either a building or a small, well-defined outside area
4-10

(such as a playground, recreation area, outdoor theater, or other place of public assembly) that is 

occupied by 20 or more persons on at least 5 days a week for 10 weeks in any 12-month period.

The EPA is proposing management practices as generally available control technologies 

for existing stationary SI 4SLB and 4SRB area source non-emergency engines located in 

sparsely populated areas. Given the remote location of the engines from human activity, the EPA 

believes that it is appropriate not to include requirements that would necessitate aftertreatment 

and extensive testing and monitoring. The EPA has previously estimated that the costs of 

oxidation catalyst for existing 4SLB and 4SRB engines above 500 HP at area sources are $310 

and $150 million, for capital and annual costs, respectively. The capital and annual costs of the 

RICE NESHAP for existing 4SLB and 4SRB engines above 500 HP at area sources would be 

$30 million and $12 million, respectively, if these proposed amendments are incorporated into 

the rule. Creating a subcategory of these engines for the ones located in sparsely populated areas 

and not mandating emission controls would significantly reduce the cost of the rule for such 

engines. 

For existing stationary SI 4SLB and 4SRB area source non-emergency engines that are 

located in populated areas, the EPA is proposing an equipment standard that requires the 

installation and operation of a catalyst that will have to be tested initially and annually to ensure 

that the catalyst is working properly and reducing emissions as required. In addition, these units 

will be required to have devices to shut down the engine if the catalyst is exposed to dangerous 

temperatures or have continuous monitoring equipment installed to record catalyst inlet 

temperatures. The EPA is proposing shorter test duration and less rigorous methods than 

currently required while still ensuring that HAP reductions remain at expected levels for these 

engines located in populated areas. The specific amendments the EPA is proposing are discussed 

below.

4.2.3.2. What are the Proposed Amendments?

Owners and operators of engines in sparsely populated areas would have to conduct a 

review of the surrounding area every 12 months to determine if the nearby population has 

changedIf the engine no longer meets the criteria for a sparsely populated area the owner and 

operator must within 1 year comply with the emission standards specified below for populated 

areas. The EPA requests comment on whether engines that are not associated with pipelines 

should be required to conduct the review less frequently than every 12 months.
4-11

Owners and operators of existing stationary 4SLB and 4SRB greater than 500 HP at area 

sources that are in sparsely populated areas as described above would be required to perform the 

following:

•Change oil and filter every 1,440 hours of operation or annually, whichever comes first;

•Inspect spark plugs every 1,440 hours of operation or annually, whichever comes first, 

and replace as necessary; and

•Inspect all hoses and belts every 1,440 hours of operation or annually, whichever comes 

first, and replace as necessary.

Sources have the option to use an oil analysis program as described in §63.6625(i) of the 

rule in order to extend the specified oil change requirement. The oil analysis must be performed 

at the same frequency specified for changing the oil in Table 2d of the rule. The analysis 

program must at a minimum analyze the following three parameters: Total Acid Number, 

viscosity, and percent water content. The condemning limits for these parameters are as follows: 

Total Acid Number increases by more than 3.0 milligrams of potassium hydroxide per gram 

from Total Acid Number of the oil when new; viscosity of the oil has changed by more than 20 

percent from the viscosity of the oil when new; or percent water content (by volume) is greater 

than 0.5. If all of these condemning limits are not exceeded, the engine owner or operator is not 

required to change the oil. If any of the limits are exceeded, the engine owner or operator must 

change the oil within 2 days of receiving the results of the analysis; if the engine is not in 

operation when the results of the analysis are received, the engine owner or operator must change 

the oil within 2 days or before commencing operation, whichever is later. The owner or operator 

must keep records of the parameters that are analyzed as part of the program, the results of the 

analysis, and the oil changes for the engine. The analysis program must be part of the 

maintenance plan for the engine.

Owners and operators of existing stationary 4SLB and 4SRB area source engines above 

500 HP in sparsely populated areas would also have to operate and maintain the stationary RICE 

and aftertreatment control device (if any) according to the manufacturer's emission-related 

written instructions or develop their own maintenance plan which must provide to the extent 

practicable for the maintenance and operation of the engine in a manner consistent with good air 

pollution control practice for minimizing emissions. 

For engines in populated areas, i.e., existing stationary 4SLB and 4SRB non-emergency

engines greater than 500 HP at area sources that are located on DOT Class 2 through Class 4 
4-12

pipeline segments or, for engines not associated with pipelines, that do not meet the 0.25 mile 

radius with 5 or less buildings criteria, the EPA is proposing to adopt an equipment standard 

requiring the installation of a catalyst to reduce HAP emissions. Owners and operators of 

existing area source 4SLB non-emergency engines greater than 500 HP in populated areas would 

be required to install an oxidation catalyst. Owners and operators of existing area source 4SRB 

non-emergency engines greater than 500 HP in populated areas would be required to install 

NSCR. Owners and operators must conduct an initial test to demonstrate that the engine achieves 

at least a 93 percent reduction in CO emissions or a CO concentration level of 47 ppmvd at 15 

percent O2, if the engine is a 4SLB engine. Similarly, owners and operators must conduct an 

initial performance test to demonstrate that the engine achieves at least a 75 percent CO 

reduction or a 30 percent THC reduction, if the engine is a 4SRB engine. The initial test must 

consist of three test runs. Each test run must be of at least 15 minute duration, except that each 

test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist 

of one measurement cycle as defined by the method and include at least 2 minutes of test data 

phase measurement. To measure CO, emission sources must use the CO methods already 

specified in subpart ZZZZ, or the proposed appendix A to 40 CFR part 63, subpart ZZZZ. The 

THC testing must be conducted using EPA Method 25A.

The owner or operator of both engine types must also use a high temperature shutdown 

device that detects if the catalyst inlet temperature is too high, or, alternatively, the owner or 

operator can monitor the catalyst inlet temperature continuously and maintain the temperature 

within the range specified in the rule. For 4SLB engines the catalyst inlet temperature must 

remain at or above 450°F and at or below 1,350°F. For 4SRB engines the temperature range 

must be greater than or equal to 750°F and less than or equal to 1,250°F at the catalyst inlet. 

Owners and operators must in addition to the initial performance test conduct annual 

checks of the catalyst to ensure proper catalyst activity. The annual check of the catalyst must at 

a minimum consist of one 15-minute run using the methods discussed above, except that each 

test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist 

of one measurement cycle as defined by the method and include at least 2 minutes of test data 

phase measurement. Owners and operators of 4SLB engines must demonstrate during the 

catalyst activity test that the catalyst achieves at least a 93 percent reduction in CO emissions or 

that the engine exhaust CO emissions are no more than 47 ppmvd at 15 percent O2. Owners and 

operators of 4SRB engines must demonstrate that their catalyst is reducing CO emissions by 75 

percent or more, or alternatively, that THC emissions are being reduced by at least 30 percent 

during the catalyst activity check. 
4-13

If the emissions from the engine do not exceed the levels required for the initial test or 

annual checks of the catalyst, then the catalyst is considered to be working properly. If the 

emissions exceed the specified pollutant levels in the rule, the exceedance(s) is/are not 

considered a violation, but the owner or operator would be required to shut down the engine and 

take appropriate corrective action (e.g., repairs, clean or replace the catalyst, as appropriate). A 

follow-up test must be conducted within 7 days of the engine being started up again to 

demonstrate that the emission levels are being met. If the retest shows that the emissions 

continue to exceed the specified levels, the stationary RICE must again be shut down as soon as 

safely possible, and the engine may not operate, except for purposes of start-up and testing, until

the owner/operator demonstrates through testing that the emissions do not exceed the levels 

specified.

4.2.3.3 Compliance Date

The EPA has received some questions regarding whether the compliance dates for 

engines impacted by the 2010 amendments and this proposed reconsideration will be extended. 

Affected sources that may be impacted by this action have expressed concern about having 

sufficient time to comply with the rule by the compliance date, which is May 3, 2013, for 

existing stationary CI RICE and October 19, 2013, for existing stationary SI RICE. Sources 

impacted by this reconsideration are particularly concerned with compliance in the event that the 

EPA does not finalize changes that are substantially similar to the changes being proposed in this 

action. The EPA does not intend to extend the May 3, 2013, and October 19, 2013, compliance 

dates, because there are many engines that must meet those compliance dates that are not 

impacted by this reconsideration. However, we note that sources that are affected by the 

reconsideration and that may need additional time to install controls to comply with the 

applicable requirements can request up to an additional year to install controls, as specified in 40 

CFR 63.6(i).

4.3 What Are the Pollutants Regulated by the Rule?

The proposed reconsideration rule regulates emissions of HAP. Available emissions data 

show that several HAP, which are formed during the combustion process or which are contained 

within the fuel burned, are emitted from stationary engines. The HAP which have been measured 

in emission tests conducted on SI stationary RICE include: formaldehyde, acetaldehyde, 
4-14

acrolein, methanol, benzene, toluene, 1,3-butadiene, 2,2,4-trimethylpentane, hexane, xylene, 

naphthalene, PAH, methylene chloride, and ethylbenzene. EPA described the health effects of 

these HAP and other HAP emitted from the operation of stationary RICE in the preamble to 40 

CFR part 63, subpart ZZZZ, published on June 15, 2004 (69 FR 33474). These HAP emissions 

are known to cause, or contribute significantly to air pollution, which may reasonably be 

anticipated to endanger public health or welfare.

For the standards included in this action, EPA believes that previous determinations 

regarding the appropriateness of using formaldehyde and carbon monoxide (CO) both in 

concentration (parts per million (ppm)) levels as surrogates for HAP for stationary RICE are still 

valid. Consequently, EPA is promulgating CO or formaldehyde standards in order to regulate 

HAP emissions. 

In addition to reducing HAP, the emission control technologies that will be installed on 

stationary RICE to reduce HAP will also reduce CO and VOC, and for rich burn engines will 

also reduce NOx.

4.4 Cost Impacts

4.4.1 Introduction

EPA has determined that oxidation catalysts for two-stroke lean burn (2SLB) and fourstroke lean burn (4SLB) engines, and non-selective catalytic reduction (NSCR) for four-stroke 

rich burn (4SRB) engines are applicable controls for HAP reduction from existing stationary SI

RICE. To determine the capital and annual costs for these control technologies, equipment cost 

information was obtained from industry groups2and vendors and manufacturers of SI engine 

control technology. In some cases, the industry groups provided a breakdown of the capital and 

annual cost components for each of the retrofit options. Using this cost data, annualized cost and 

capital cost equations for oxidation catalysts and NSCR were developed.

4.4.2 Control Cost Methodology 

The following sections describe the methodology used to derive the total capital and total 

annual costs for each of the control technology options. These methodologies were used to 

calculate total capital and total annual costs when only purchased equipment costs were available 

(e.g., vendor equipment costs). The methodologies were not used for cost data provided by 

 

2 Reciprocating Internal Combustion Engine National Emission Standards for Hazardous Air Pollutants (RICE 

NESHAP) Proposed Revisions – Emission Control Costs Analysis Background for “Above the Floor” Emission 

Controls for Natural Gas-Fired RICE, Innovative Environmental Solutions Inc., October 2009. (EPA-HQ-OAR2008-0708-0279).
4-15

industry groups because they included a breakdown of the actual total capital and total annual 

costs. A summary of the methodologies, equations, and assumptions used to estimate the total 

capital and total annual costs for some of the cost data are described in the following sections.

4.4.2.1 Total Capital Costs

The total capital cost includes the direct and indirect costs of purchasing and installing 

the control equipment. The direct cost includes the cost of purchasing the equipment and 

instrumentation, cost of shipping, and the cost of installing the control equipment. The indirect 

cost includes the costs for engineering, contractor fees, testing costs, and also includes costs for 

contingencies, such as additional modifications, or delays in startup. The total capital cost 

equation can be summarized as follows:

Total Capital Cost (TCC) = Direct Costs (DC) + Indirect Costs (IC)

The direct costs include the costs of purchasing and installing the control equipment and can be 

summarized using the following equation; 

DC = Purchased Equipment Cost (PEC) + Direct Installation Costs (DIC).

A summary of the cost assumptions for PEC includes the following:

 Control Device and Auxiliary Equipment (EC);

 Instrumentation (10% of EC);

 Sales Tax (3% of EC);

 Freight (5% of EC);

and can be summarized as:

PEC = 118% EC.

A summary of the cost assumptions for DIC includes the following:

 Foundations and Supports (8% of PEC);

 Handling and Erection (14% of PEC);

 Electrical (4% of PEC);

 Piping (2% of PEC);
4-16

 Insulation for Ductwork (1% of PEC);

 Painting (1% of PEC);

and can be summarized as:

DIC = 30% PEC = 0.3 PEC.

Therefore, the direct costs can be simplified using the following equation:

DC = PEC + 0.3 PEC = 1.3 PEC.

The indirect costs include the costs of engineering and contractor fees and contingencies and can 

be summarized using the following equation:

IC = Indirect Installation Costs (ICC) + Contingencies (C).

A summary of the cost assumptions for ICC includes the following:

 Engineering (10% of PEC);

 Construction and Field Expenses (5% of PEC);

 Contractor Fees (10% of PEC);

 Startup (2% of PEC);

 Performance Test (1% of PEC);

and can be summarized as:

IIC = 28% PEC = 0.28 PEC.

A summary of the cost assumptions for C includes the following:

 Equipment Redesign and Modifications;

 Cost Escalations;

 Delays in Startup;

and is assumed to be:

C = 3% PEC = 0.03 PEC.
4-17

Therefore, the IC can be summarized using the following equation:

IC = 0.28 PEC + 0.03 PEC = 0.31 PEC,

and the simplified TCC equation can be expressed as:

TCC = 1.3 PEC + 0.31 PEC = 1.61 PEC = 1.61 (1.18 EC) = 1.9 EC

4.4.2.2 Total Annual Costs

The total annual cost includes the direct and indirect annual costs of operating and 

maintaining the control equipment. The direct annual cost includes the cost of the utilities, 

operating labor, and control device cleaning and maintenance. The indirect annual cost includes 

the overhead costs such as spare parts for the control equipment, administrative charges, and the 

capital recovery of the control technology. The total annual cost equation can be summarized as 

follows:

Total Annual Cost (TAC) = Direct Annual Costs (DAC) + Indirect Annual Costs (IAC).

The DAC includes the following parameters:

 Utilities;

 Operating Labor;

 Maintenance;

 Annual Compliance Test;

 Catalyst Cleaning;

 Catalyst Replacement;

 Catalyst Disposal.

The IAC includes the following parameters:

 Overhead;

 Fuel Penalty;

 Property Tax;

 Insurance;

 Administrative Charges;
4-18

 Capital Recovery = {I(1+I)n/((1+I)n-1)*TCC} where I is the interest rate, and n is the 

equipment life.

To calculate DAC, the costs were broken up into three separate costs: operation and 

maintenance materials cost, operation and maintenance labor cost, and the cost for annual 

performance testing or downtime or allowance for catalyst washing. Actual annual cost data 

from the industry groups were used to estimate the DAC for each of the control technologies. 

The IAC was broken up into three separate costs: administrative, fuel penalty, and capital 

recovery. Again, cost data from the industry groups was used to estimate these costs for each of 

the control technologies. No fuel penalty was estimated for the oxidation catalyst control 

technologies, because this control technology does not increase the fuel usage of the SI engine.

4.4.3 Control Cost Equations

Control cost equations were developed for 2SLB oxidation catalyst, 4SLB oxidation 

catalyst, and a NSCR for 4SRB engines using the total capital cost and total annual cost data for 

each control technology. Control cost equations for 2SLB and 4SLB oxidation catalysts were 

developed separately because the 2SLB oxidation catalyst requires a premium catalyst to reduce 

the HAP compounds because of the low exhaust temperature of 2SLB engines.

4.4.3.1 2SLB Oxidation Catalyst

The 2SLB oxidation catalyst is an effective control technology that reduces HAP 

emissions from a 2SLB SI engine by oxidizing organic compounds using a catalyst. The 

oxidation catalyst unit contains a honeycomb-like structure or substrate with a large surface area 

that is coated with a premium active catalyst layer such as platinum or palladium. The oxidation 

catalyst works by oxidizing carbon monoxide (CO) and gaseous hydrocarbons (HAP) in the 

exhaust gas to carbon dioxide (CO2) and water. The reduction of CO and HAP varies depending 

on the type of catalyst used and the exhaust temperature of the pollutant stream.

The cost of retrofitting an oxidation catalyst to an existing 2SLB engine was estimated 

using cost data obtained from vendors and industry groups covering engines ranging from 58 

horsepower (HP) to 4,670 HP. An equipment life of 10 years and an interest rate of 7 percent 

were used to estimate the capital recovery of the control technology and the fuel penalty was 

assumed to be negligible. The cost equations are presented in 2009 dollars.

The total annualized cost equation for retrofitting an oxidation catalyst on a 2SLB engine 

was estimated to be:

2SLB Oxidation Catalyst Total Annual Cost = $11.4 x HP + $13,928
4-19

where

HP = engine size in HP.

The linear equation has a correlation coefficient of 0.8046, which shows the data fits the 

equation closely. Therefore, this equation was used to estimate annualized cost for an oxidation 

catalyst on a 2SLB engine.

The total capital cost equation for retrofitting an oxidation catalyst on a 2SLB engine was 

estimated to be: 

2SLB Oxidation Catalyst Total Capital Cost = $47.1 x HP + $41,603

where

HP = engine size in HP.

4.4.3.2 4SLB Oxidation Catalyst

The 4SLB oxidation catalyst is an effective control technology that reduces HAP 

emissions from a 4SLB SI engine by oxidizing organic compounds using a catalyst. The 

oxidation catalyst unit contains a honeycomb-like structure or substrate with a large surface area 

that is coated with a premium active catalyst layer such as platinum or palladium. The oxidation 

catalyst works by oxidizing CO and gaseous hydrocarbons (HAP) in the exhaust gas to CO2 and 

water. The reductions of CO and HAP vary depending on the type of catalyst used and the 

exhaust temperature of the pollutant stream.

The cost of retrofitting an oxidation catalyst to an existing 4SLB engine was estimated 

using cost data obtained from vendors and industry groups covering engines ranging from 400 

HP to 8,000 HP. Again, an equipment life of 10 years and an interest rate of 7 percent were used 

to estimate the capital recovery of the control technology and the fuel penalty was assumed to be 

negligible. The cost equations are presented in 2009 dollars.

The total annualized cost equation for retrofitting an oxidation catalyst on a 4SLB engine 

was estimated to be:

4SLB Oxidation Catalyst Total Annual Cost = $1.81 x HP + $3,442

where
4-20

HP = engine size in HP.

The linear equation has a correlation coefficient of 0.9779, which shows the data fits the 

equation very closely. Therefore, this equation was used to estimate annualized cost for an 

oxidation catalyst on a 4SLB engine.

The total capital cost equation for retrofitting an oxidation catalyst on a 4SLB SI engine was 

estimated to be: 

4SLB Oxidation Catalyst Total Capital Cost = $12.8 x HP + $3,069

where

HP = engine size in HP.

A summary of the cost calculations, regression analyses, and graphical representations of the 

annual and capital cost data are presented in Appendix A of the cost memo that is the basis for 

the cost data presented in this RIA.

3

4.4.3.3 Non-Selective Catalytic Reduction

The NSCR or three-way catalyst is used to control HAP emissions from 4SRB engines.

In addition to HAP reductions, NSCR also reduces the emissions of nitrogen oxides (NOx), CO, 

and other hydrocarbons (HC). The reduction of HAP and CO takes place through an oxidation 

reaction that converts HAP to CO2 and water and converts CO to CO2. The conversion of NOx

takes place through a reduction of the NOx to nitrogen gas and oxygen.

The cost of retrofitting an NSCR on an existing 4SRB engine was estimated based on 

cost data received from vendors and industry groups. A linear regression analysis was done on 

the data set and the linear equation for annualized cost was;

NSCR Annual Cost = $4.77 x HP + $5,679

where

HP = engine size in HP.

 

3

 Memorandum from Bradley Nelson, EC/R to Melanie King, EPA. OAQPS/SPPD/ESG. Impacts Associated with 

NESHAP for Existing Stationary SI RICE. June 29, 2010.
4-21

The linear equation has a correlation coefficient of 0.7987, which shows an acceptable 

representation of the cost data. Therefore, this equation was used to estimate annualized cost for 

retrofitting the NSCR control technology on 4SRB engines.

The capital cost equation for retrofitting an air-to-fuel ratio (AFR) controller and NSCR on a 

4SRB engine was estimated to be: 

NSCR Capital Cost = $24.9 x HP + $13,118

where

HP = engine size in HP.

4.4.4 Summary

Table 4-1 presents a summary of the annual and capital control costs as a function of 

engine size for the control technologies applicable to existing stationary SI engines, as discussed 

in this memorandum.

Table 4-1. Summary of Annual and Capital Costs Equations for Existing Stationary SI 

Engines

HAP Control Device Annual Cost ($2009) Capital Cost ($2009)

2SLB Oxidation Catalyst $11.4 x HP + $13,928 $47.1 x HP + $41,603

4SLB Oxidation Catalyst $1.81 x HP + $3,442 $12.8 x HP + $3,069

NSCR $4.77 x HP + $5,679 $24.9 x HP + $13,118

A summary of the annual and capital costs associated with the rule and obtained using the 

methodology described above are presented in Tables 4-2 to 4-5 below.

4 These costs are used as 

input to the economic impact as well as the small entity analysis. 

 

4

 Memorandum from Bradley Nelson, EC/R to Melanie King, EPA. OAQPS/SPPD/ESG. Impacts Associated with 

NESHAP for Existing Stationary SI RICE. June 29, 2010.
Table 4-2. Summary of Major Source and Area Source Costs for the SI RICE NESHAPa

Size Range (HP)

Capital 

Control Cost

Annual 

Control Cost Initial Test

Recordkeeping ReportingMonitoring—

Capital Cost

Monitoring

—Annual 

Cost

Total Annual 

Costs

Total Capital 

Costs

Major Sources

25–50 $0 $0 $0 $4,060,795 $0 $0 $0 $4,060,795 $0

50–100 $0 $0 $0 $1,087,540 $0 $0 $0 $1,087,540 $0

100–175 $48,502,361 $37,071,061 $15,971,384 $1,721,899 $5,725,314 $0 $0 $60,489,657 $48,502,361

175–300 $13,225,919 $8,382,568 $3,442,648 $371,157 $1,234,097 $0 $0 $13,430,470 $13,225,919

300–500 $10,934,795 $5,562,872 $2,123,326 $228,919 $761,155 $0 $0 $8,676,262 $10,934,795

500–600 $0 $0 $0 $0 $0 $0 $0 $0 $0

600–750 $0 $0 $0 $0 $0 $0 $0 $0 $0

>750 $0 $0 $0 $0 $0 $0 $0 $0 $0

Total $72,663,076 $51,016,500 $21,537,358 $7,470,310 $7,720,566 $0 $0 $87,744,734 $72,663,076

Area Sources

25–50 $0 $0 $0 $6,668,944 $0 $0 $0 $6,668,944 $0

50–100 $0 $0 $0 $2,868,511 $0 $0 $0 $2,868,511 $0

100–175 $0 $0 $0 $3,529,711 $0 $0 $0 $3,529,711 $0

175–300 $0 $0 $0 $1,264,799 $0 $0 $0 $1,264,799 $0

300–500 $0 $0 $0 $908,913 $0 $0 $0 $908,913 $0

500–600 $7,547,433 $2,662,805 $248,366 $454,493 $1,26,426 0 0 $3,492,090 $7,547,433

600–750 $1,522,236 $505,221 $44,323 $77,882 $22,562 0 0 $649,988 $1,522,236

>750 $21,075,418 $6,214,397 $472,244 $829,795 $240,387 0 0 $7,756,823 $21,075,418

Total $30,145,088 $9,382,423 $764,933 $16,603,048 $389,375 0 0 $27,139,780 $30,145,088

Grand Total

Total $102.808,163 $60,398,923 $22,302,292 $24,073,358 $8,106,972 0 0 $114,884,514 $102,808.163

a Costs are presented in 2009 dollars.
4-2

3

Table 4-3. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAPa

Major Source Area Source Total (Major + Area)

NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost

2211 Electric Power Generation $52,905,258 $63,062,494 $11,698,144 $12,138,277 $64,603,403 $75,200,772

48621 Natural Gas Transmission $1,484,494 $1,462,530 $13,718,381 $6,142,839 $15,202,876 $7,605,369

211111 Crude Petroleum & NG 

Production $4,561,236 $6,138,383

$71,439 $951,462

$4,632,675 $7,089,844

211112 Natural Gas Liquid Producers $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,844

92811 National Security $5,878,362 $7,006,944 $1, 299,794 $1,348,697 $7,178,1566 $8,355,641

335312 Hydro Power Units $0 $25,248 $0 $37,872 $0 $63,120

335312 Irrigation Sets $3,025,050 $3,230,856 $3,285,990 $4,999,041 $6,310,940 $8,229,896

333992 Welders $247,440 $679,896 $0 $570,130 $247,440 $1,250,027

Total $72,663,076 $87,744,734 $30,145,088 $27,139,780 $102,808,163 $114,884,514

a Costs are presented in 2009 dollars.
4-2

4

Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea

Major Source Area Source Total (Major + Area)

NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost

Electric Power Generation (2211)

25–50 hp $0 $2,758,459 $0 $4,137,688 $0 $6,896,147

50–100 hp $0 $606,144 $0 $909,215 $0 $1,515,359

100–175 hp $33,868,173 $42,238,648 $0 $1,803,548 $33,868,173 $44,042,196

175–300 hp $10,603,849 $10,767,847 $0 $446,361 $10,603,849 $11,214,209

300–500 hp $8,433,236 $6,691,397 $0 $264,820 $8,433,236 $6,956,217

500–600 hp $0 $0 $2,543,944 $1,177,047 $2,543,944 $1,177,047

600–750 hp $0 $0 $515,514 $220,122 $515,514 $220,122

>750 hp $0 $0 $8,638,687 $3,179,475 $8,638,687 $3,179,475

Total Electric Power Generation 2211 $52,905,258 $63,062,494 $11,698,144 $12,138,277 $64,603,403 $75,200,772

Natural Gas Transmission (48621)

25–50 hp $0 $102 $0 $1,934 $0 $2,036

50–100 hp $0 $4,872 $0 $92,571 $0 $97,443

100–175 hp $301,721 $376,291 $0 $203,518 $301,721 $579,809

175–300 hp $643,157 $653,104 $0 $342,928 $643,157 $996,032

300–500 hp $539,617 $428,162 $0 $214,637 $539,617 $642,799

500–600 hp $0 $0 $1,925,560 $890,929 $1,925,560 $890,929

600–750 hp $0 $0 $949,443 $405,408 $949,443 $405,408

>750 hp $0 $0 $10,843,377 $3,990,913 $10,843,377 $3,990,913

Total Natural Gas Transmission (48621) $1,484,494 $1,462,530 $13,781,381 $6,142,839 $15,202,876 $7,605,369

Crude Petroleum & NG Production (211111)

25–50 hp $0 $388,115 $0 $582,173 $0 $970,288

50–100 hp $0 $66,698 $0 $100,047 $0 $166,744

100–175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531

(continued)
4-2

5

Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)

Major Source Area Source Total (Major + Area)

NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost

175–300 hp $1,037 $1,053 $0 $44 $1,037 $1,096

300–500 hp $10,424 $8,271 $0 $327 $10,424 $8,598

500–600 hp $0 $0 $3,102 $1,435 $3.102 $1,435

600–750 hp $0 $0 $0 $0 $0 $0

>750 hp $0 $0 $68,337 $25,151 $68,337 $25,151

Total Crude Petroleum & NG Production 

(211111) $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,844

Natural Gas Liquid Producers (211112)

25–50 hp $0 $388,115 $0 $582,173 $0 $970,288

50–100 hp $0 $66,698 $0 $100,047 $0 $166,744

100–175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531

175–300 hp $1,037 $1,053 $0 $44 $1,037 $1,096

300–500 hp $10,424 $8,271 $0 $327 $10,424 $8,598

500–600 hp $0 $0 $3,102 $1,435 $3,102 $1,435

600–750 hp $0 $0 $0 $0 $0 $0

>750 hp $0 $0 $68,337 $25,151 $68,337 $25,151

Total Natural Gas Liquid Producers (211112) $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,844

National Security (92811)

25–50 hp $0 $306,495 $0 $459,743 $0 $766,239

50–100 hp $0 $67,349 $0 $101,024 $0 $168,373

100–175 hp $3,763,130 $4,693,183 $0 $200,394 $3,763,130 $4,893,577

175–300 hp $1,178,205 $1,196,427 $0 $49,596 $1,178,205 $1,246,023

300–500 hp $937,026 $743,489 $0 $29,424 $937,026 $772,913

500–600 hp $0 $0 $282,660 $130,783 $282,660 $130,783

(continued)
4-2

6

Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)

Major Source Area Source Total (Major + Area)

NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost

600–750 hp $0 $0 $57,279 $24,458 $57,279 $24,458

>750 hp $0 $0 $959,854 $353,275 $959,854 $353,275

Total National Security (92811) $5,878,362 $7,006,944 $1,299,794, $1,348,697 $7,178,156 $8,355,641

Hydro Power Units (335312)

25–50 hp $0 $22,688 $0 $34,032 $0 $56,721

50–100 hp $0 $2,560 $0 $3,840 $0 $6,399

100–175 hp $0 $0 $0 $0 $0 $0

175–300 hp $0 $0 $0 $0 $0 $0

300–500 hp $0 $0 $0 $0 $0 $0

500–600 hp $0 $0 $0 $0 $0 $0

600–750 hp $0 $0 $0 $0 $0 $0

>750 hp $0 $0 $0 $0 $0 $0

Total Hydro Power Units (335312) $0 $25,248 $0 $37,872 $0 $63,120

Irrigation Sets (335312)

25–50 hp $0 $32,913 $0 $625,338 $0 $658,251

50–100 hp $0 $65,825 $0 $1,250,677 $0 $1,316,502

100–175 hp $1,222,348 $1,524,449 $0 $824,505 $1,222,348 $2,348,954

175–300 hp $798,634 $810,986 $0 $425,827 $798,634 $1,236,813

300–500 hp $1,004,068 $796,683 $0 $399,376 $1,004,068 $1,196,060

500–600 hp $0 $0 $2,789,064 $1,290,460 $2,789,064 $1,290,460

600–750 hp $0 $0 $0 $0 $0 $0

>750 hp $0 $0 $496,827 $182,857 $496,827 $182,857

Total Irrigation Sets (335312) $3,025,050 $3,230,856 $3,285,890 $4,999,041 $6,310,940 $8,229,896

(continued)
4-2

7

Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)

Major Source Area Source Total (Major + Area)

NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost

Welders (333992)

25–50 hp $0 $163,908 $0 $245,862 $0 $409,771

50–100 hp $0 $207,394 $0 $311,091 $0 $518,485

100–175 hp $247,440 $308,594 $0 $13,177 $247,440 $321,771

175–300 hp $0 $0 $0 $0 $0 $0

300–500 hp $0 $0 $0 $0 $0 $0

500–600 hp $0 $0 $0 $0 $0 $0

600–750 hp $0 $0 $0 $0 $0 $0

>750 hp $0 $0 $0 $0 $0 $0

Total Welders (333992) $247,440 $679,896 $0 $570,130 $247,440 $1,250,027

Total $72,663,076 $87,744,734 $30,145,088 $27,139,780 $102,808,163 $114,884,514

a Costs are presented in 2009 dollars.
4-2

8

Table 4-5. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Number of Enginesa

Number of Engines Total (Major + Area)

NAICS Major Area Total Capital Cost Annual Cost

Electric Power Generation (2211)

25–50 hp 37,933 56,900 94,833 $0 $6,896,147

50–100 hp 8,336 12,503 20,839 $0 $1,515,359

100–175 hp 16,534 24,802 41,336 $33,868,173 $44,042,196

175–300 hp 4,092 6,138 10,230 $10,603,849 $11,214,209

300–500 hp 2,428 3,642 6,070 $8,433,236 $6,956,217

500–600 hp 0 2,107 2,107 $2,543,944 $1,177,047

600–750 hp 0 363 363 $515,944 $220,122

>750 hp 0 4,677 4,677 $8,638,687 $3,179,475

Total Electric Power Generation (2211) 69,323 111,132 180,455 $64,603,403 $75,200,772

Natural Gas Transmission (48621)

25–50 hp 1 27 28 $0 $2,036

50–100 hp 67 1,273 1,340 $0 $97,443

100–175 hp 147 2,799 2,946 $301,721 $579,809

175–300 hp 248 4,716 4,964 $643,157 $996,032

300–500 hp 155 2,952 3,107 $539,617 $642,799

500–600 hp 0 1,595 1,595 $1,925,560 $890,929

600–750 hp 0 668 668 $949,443 $405,408

>750 hp 0 5,871 5,871 $10,843,377 $3,990,913

Total Natural Gas Transmission (48621) 619 19,899 20,519 $15,202,876 $7,605,369

Crude Petroleum & NG Production (211111)

25–50 hp 5,337 8,006 13,343 $0 $970,288

50–100 hp 917 1,376 2,293 $0 $166,744

100–175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531

(continued)
4-2

9

Table 4-5. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Number of Enginesa

(continued)

Number of Engines Total (Major + Area)

NAICS Major Area Total Capital Cost Annual Cost

175–300 hp 0 1 1 $1,037 $1,096

300–500 hp 3 5 8 $10,424 $8,598

500–600 hp 0 3 3 $3,102 $1,435

600–750 hp 0 0 0 $0 $0

>750 hp 0 37 37 $68,337 $25,151

Total Crude Petroleum & NG Production (211111) 8,479 12,758 21,237 $4,632,675 $7,089,844

Natural Gas Liquid Producers (211112)

25–50 hp 5,337 8,006 13,343 $0 $970,288

50–100 hp 917 1,376 2,293 $0 $166,744

100–175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531

175–300 hp 0 1 1 $1,037 $1,096

300–500 hp 3 5 8 $10,424 $8,598

500–600 hp 0 3 3 $3,102 $1,435

600–750 hp 0 0 0 $0 $0

>750 hp 0 37 37 $68,337 $25,151

Total Natural Gas Liquid Producers (211112) 8,479 12,758 21,237 $4,632,675 $7,089,844

National Security (92811)

25–50 hp 4,215 6,322 10,537 $0 $766,239

50–100 hp 926 1,389 2,315 $0 $168,373

100–175 hp 1,837 2,756 4,593 $3,763,130 $4,893,577

175–300 hp 455 682 1,137 $1,178,205 $1,246,023

300–500 hp 270 404 674 $937,026 $772,913

500–600 hp 0 234 234 $282,660 $130,783

(continued)
4-3

0

Table 4-5. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Number of Enginesa

(continued)

Number of Engines Total (Major + Area)

NAICS Major Area Total Capital Cost Annual Cost

600–750 hp 0 40 40 $57,279 $24,458

>750 hp 0 520 520 $959.854 $353,275

Total Natural Gas Liquid Producers (211112) 7,702 12,347 20,050 $7,178,156 $8,355,641

Hydro Power Units (335312)

25–50 hp 312 468 780 $0 $56,721

50–100 hp 35 53 88 $0 $6,399

100–175 hp 0 0 0 $0 $0

175–300 hp 0 0 0 $0 $0

300–500 hp 0 0 0 $0 $0

500–600 hp 0 0 0 $0 $0

600–750 hp 0 0 0 $0 $0

>750 hp 0 0 0 $0 $0

Total Hydro Power Units (335312) 347 521 868 $0 $63,120

Irrigation Sets (335312)

25–50 hp 453 8,599 9,052 $0 $658,251

50–100 hp 905 17,199 18,104 $0 $1,316,502

100–175 hp 597 11,338 11,935 $1,222,348 $2,348,954

175–300 hp 308 5,856 6,164 $798,634 $1,236,813

300–500 hp 289 5,492 5,781 $1,004,068 $1,196,060

500–600 hp 0 2,310 2,310 $2,789,064 $1,290,460

600–750 hp 0 0 0 $0 $0

>750 hp 0 269 269 $496,827 $182857

Total Irrigation Sets (335312) 2,552 51,063 53,615 $6,310,940 $8,229,896

(continued)
4-31

Table 4-5. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Number of Enginesa

(continued)

Number of Engines Total (Major + Area)

NAICS Major Area Total Capital Cost Annual Cost

Welders (333992)

25–50 hp 2,254 3,381 5,635 $0 $409,771

50–100 hp 2,852 4,278 7,130 $0 $518,485

100–175 hp 121 181 302 $247,440 $321,771

175–300 hp 0 0 0 $0 $0

300–500 hp 0 0 0 $0 $0

500–600 hp 0 0 0 $0 $0

600–750 hp 0 0 0 $0 $0

>750 hp 0 0 0 $0 $0

Total Welders (333992) 5,227 7,840 13,067 $247,440 $1,250,027

Total 102,729 228,319 331,047 $382,802,298 $253,374,939

1 Costs are presented in 2009 dollars.
4.4.5 Caveats and Uncertainties in the Cost Estimates 

* Current knowledge about NOx control techniques and costs is applied in this

study. Advances such as alternative catalyst formulations may occur between

now and when sources comply with this rulemaking that may lower costs. Scale

economies can also lower per unit production costs as the market for these NOx

control techniques expands.

* The alternative control techniques and corresponding emission reductions and

costs may not apply to every unit within the source category. Many factors

influence the performance and cost of any control technique. Because control

technology references typically evaluate average retrofit situations, costs may

be underestimated for the fraction of the source population with difficult to

retrofit conditions. Difficult to retrofit conditions may be less of an issue for

RICEs than for other point sources, however.

* NOx control efficiency and cost estimates associated with source category-control

strategy combinations are represented as point estimates. In practice, control

effectiveness and costs will vary by engine.
4-33

4.5 Baseline Emissions and Emission Reductions

The baseline emissions, emissions factors and emissions reductions associated with the 

proposed reconsideration rule are provided in the tables below. Baseline emissions are 

estimated for 2013 using the emissions dataset generated for the final SI RICE rule in 2010. The 

baseline emissions thus assume the final SI RICE rule has not been implemented. Emissions are 

in tons per year. 

Table 4-6. Summary of Major Source and Area Source Baseline Emissions for the SI 

RICE NESHAP in 2013

Baseline Emissions (TPY)

Size Range (HP) HAP CO NOx VOC

Major Sources

25–50 hp 1,107 28,557 41,751 5,696

50–100 hp 593 15,296 22,363 3,051

100–175 hp 1,721 44,399 64,913 8,855

175–300 hp 641 16,530 24,168 3,297

300–500 hp 666 17,171 25,105 3,425

500–600 hp 0 0 0 0

600–750 hp 0 0 0 0

>750 hp 0 0 0 0

Total 4,728 121,953 178,301 24,323

Area Sources

25–50 hp 1,818 46,898 68,566 9,354

50–100 hp 1,564 40,344 58,985 8,047

100–175 hp 3,529 91,013 133,065 18,153

175–300 hp 2,184 56,331 82,359 11,235

300–500 hp 2,643 68,178 99,679 13,598

500–600 hp 1,830 47,273 69,094 9,415

600–750 hp 383 9,876 14,438 1,969

>750 hp 6,041 155,890 227,890 31,076

Total 19,993 515,803 754,077 102,846

Major + Area 

Total

24,722 637,756 932,377 127,169
4-34

Table 4-7. Emissions Factors

Engine

HAP

(lb/hp-hr)

CO

(lb/hp-hr)

NOx

(lb/hp-hr)

VOC

(lb/hp-hr)

Formaldehyde

(lb/hp-hr)

2SLB 5.9610-41.0610-24.1810-23.0710-34.2910-4

4SLB 5.4110-43.9210-31.1510-22.7810-33.9610-4

4SRB 2.4310-41.9310-21.4710-21.2510-31.7510-4

Table 4-8. Summary of Major Source and Area Source Emissions Reductions for the SI 

RICE NESHAP in 2013

Emission Reductions (TPY)

Size Range (HP) HAP CO NOx VOC

Major Sources

25–50 hp 0 0 0 0

50–100 hp 0 0 0 0

100–175 hp 744 7,124 0 3,826

175–300 hp 277 2,653 0 1,424

300–500 hp 288 2,755 0 1,480

500–600 hp N/A N/A N/A 0

600–750 hp N/A N/A N/A 0

>750 hp N/A N/A N/A 0

Total 1,308 12,532 0 6,730

Area Sources

25–50 hp 0 0 0 0

50–100 hp 0 0 0 0

100–175 hp 0 0 0 0

175–300 hp 0 0 0 0

300–500 hp 0 0 0 0

500–600 hp 101 2,070 2,,063 517

600–750 hp 22 453 452 113

>750 hp 347 7,156 7,133 1,787

Total 470 9,679 9,648 2,418

Major + Area Total 1,778 22,211 9,648 9,147
5-1

Section 5

ECONOMIC IMPACT ANALYSIS, ENERGY IMPACTS, AND SOCIAL COSTS

The EIA provides decision makers with social cost estimates and enhances understanding 

of how the costs may be distributed across stakeholders (EPA, 2010). Although several 

economic frameworks can be used to estimate social costs for regulations of this size and sector 

scope, OAQPS has typically used partial equilibrium market models. However, the current data 

do not provide sufficient details to develop a market model; the data that are available have little 

or no sector/firm detail and are reported at the national level. In addition, some sectors have 

unique market characteristics that make developing partial equilibrium models difficult. Given 

these constraints, we used the direct compliance costs as a measure of total social costs. In 

addition, we also provide a qualitative analysis of the proposed reconsidered rule’s impact on 

stakeholder decisions, a qualitative discussion on if unfunded mandates occur as a result of this 

proposed reconsidered rule, and the potential distribution of social costs between consumers and 

producers.

5.1 Compliance Costs of the Proposed Reconsidered Rule

EPA’s engineering cost analysis estimates the total annualized costs of the proposed 

reconsidered rule are $115 million (in 2010 dollars) (EC/R, 2012).

The majority of the costs are incurred by the electric power sector (65%). The remaining 

industries each account for less than 8% of the total annualized cost. The industrial classification 

for each engine is taken from the Power Systems Research (PSR) database, which is the major 

source of data for the engines affected by this rule. The PSR database used as a basis for the 

analyses in this RIA contains information on both mobile and stationary engines, among other 

data, and does so not only for the U.S. but worldwide. PSR has collected such data for more 

than 30 years. The Office of Transportation and Air Quality (OTAQ) uses this database 

frequently in the development of their mobile source rules. 

The annualized compliance costs per engine vary by the engine size. For 500 hp engines 

or less, the annualized per-engine costs are below $371 per engine. Per-engine annualized 

compliance costs for higher horsepower (hp) engines range up to $2,800.

The proposed reconsidered rule will affect approximately 331,000 existing stationary SI

engines. As shown in Figure 5-1, most of the affected engines fall within the 25 to 50 hp 

category (45%). The next highest categories are 100 to 175 hp (22%) and 50 to 100 hp (16%). 
5-2

Figure 5-1. Distribution of Engine Population by Horsepower Group

To assess the size of the compliance relative to the value of the goods and services for 

industries using affected engines, we collected Census data for selected industries. At the 

industry level, the annualized costs represent a very small fraction of revenue (less than 1%), for 

all affected industries. Results for affected industries can be found in Table 5-1. These industry

level cost-to-sales ratios can be interpreted as an average impact on potentially affected firms in 

these industries. Based on the cost-to-sales ratios, we can conclude that the annualized cost of 

this rule should be no higher than 1% of the sales on average for a firm in each of these 

industries, excluding natural gas transmission and natural gas liquid producers, which face 

slightly higher costs to sales ratios.

45%

16%

22%

7% 5%

2% 0%

3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

25-50 hp 50-100 hp 100-175 hp 175-300 hp 300-500 hp 500-600 hp 600-750 hp >750 hp
5-3

5.2 Social Cost Estimate

As shown in Table 5-1, the compliance costs are only a small fraction of the affected 

product value; this suggests that shift of the supply curve may also be small and result in small 

changes in market prices and consumption. EPA believes the national annualized compliance 

cost estimates provide a reasonable approximation of the social cost of this proposed 

reconsidered rule. EPA believes this approximation is better for industries whose markets are 

well characterized as perfectly competitive. This approximation is less well understood for 

industries where the characterization of markets is not always perfectly competitive such as 

electric power generation whose legal incidence of this rule is approximately 65 percent of the 

annualized compliance cost. However, given the data limitation noted earlier, EPA believes the 

accounting for compliance cost is a reasonable approximation to inform policy discussion in this 

rulemaking. To shed more light on this issue, EPA ran hypothetical analyses and the results are 

in Tables 5-2 and 5-3 later in this RIA. 

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis

Markets are composed of people as consumers and producers trying to do the best they

can given their economic circumstances. One way economists illustrate behavioral responses to 

pollution control costs is by using market supply and demand diagrams. The market supply curve 

describes how much of a good or service firms are willing and able to sell to people at a 

Table 5-1. Selected Industry-Level Annualized Compliance Costs as a Fraction of Total 

Industry Revenue: 2009

Total 

Annualized 

Costs

Sales, Shipments, Receipt, 

or Revenue ($Billion)

Industry 

(NAICS) Industry Name ($ million)a($2007) ($2009)

Cost-toSales Ratio

2211 Electric Power Generation $128.4 $440.4 $453.7 0.004%

48621 Natural Gas Transmission $68.9 $16.4 $16.9 0.41%

211111 Crude Petroleum & NG Production $7.4 $214.2 $220.5 0.001%

211112 Natural Gas Liquid Producers $7.4 $42.4 $43.6 0.005%

92811 National Security $14.3 #N/A #N/A #N/A

333992 Welders $1.3 $5.2 $5.5 0.025%

111 and 112 Agriculture using irrigation systemsa$25.7 $27.9 $28.8 0.09%
5-4

a Irrigation engine costs assumed to be passed on to agricultural sectors that use irrigation systems.

N/A: receipts are Not Available for National Security

Sources: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 00: All sectors: 

Geographic Area Series: Economy-Wide Key Statistics: 2007” <http://factfinder.census.gov>; (July 7th , 

2010).

U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). 2009. “2008 

Farm and Ranch Irrigation Survey.” Washington, DC: USDA-NASS.

Costs from Existing SI RICE NESHAP Impacts received from EPA 1/26/12

particular price; we often draw this curve as upward sloping because some production resources 

are fixed. As a result, the cost of producing an additional unit typically rises as more units are 

made. The market demand curve describes how much of a good or service consumers are willing 

and able to buy at some price. Holding other factors constant, the quantity demand is assumed to 

fall when prices rise. In a perfectly competitive market, equilibrium price (P0) and quantity (Q0) 

is determined by the intersection of the supply and demand curves (see Figure 5-4).

5.3.1 Changes in Market Prices and Quantities 

To qualitatively assess how the regulation may influence the equilibrium price and 

quantity in the affected markets, we assumed the market supply function shifts up by the 

additional cost of producing the good or service; the unit cost increase is typically calculated by 

dividing the annual compliance cost estimate by the baseline quantity (Q0) (see Figure 5-4). As 

shown, this model makes two predictions: the price of the affected goods and services are likely 

to rise and the consumption/production levels are likely to fall. 
5-5

consumer surplus = –[fghd + dhc]

producer surplus = [fghd – aehb] – bdc

total surplus = consumer surplus + producer surplus = 

–[aehb + dhc + bdc]

Figure 5-2. Market Demand and Supply Model: With and Without Regulation

The size of these changes depends on two factors: the size of the unit cost increase 

(supply shift) and differences in how each side of the market (supply and demand) responds to 

changes in price. Economists measure responses using the concept of price elasticity, which 

represents the percentage change in quantity divided by the percentage change in price. This 

dependence has been expressed in the following formula:5

Price Elasticity of Supply - Price Elasticity of Demand)

Price Elasticity of Supply Share of per-unit cost 

As a general rule, a higher share of the per-unit cost increases will be passed on to 

consumers in markets where 

 goods and services are necessities and people do not have good substitutes that they

can switch to easily (demand is inelastic) and

 

5

For examples of similar mathematical models in the public finance literature, see Nicholson (1998), pages 444–447, 

or Fullerton and Metcalf (2002).
5-6

 suppliers have excess capacity and can easily adjust production levels at minimal 

costs, or the time period of analysis is long enough that suppliers can change their 

fixed resources; supply is more elastic over longer periods. 

Short-run demand elasticities for energy goods (electricity and natural gas), agricultural 

products, and construction are often inelastic. Specific estimates of short-run demand elasticities 

for these products can be obtained from existing literature. For the short-run demand of energy

products, the National Energy Modeling System (NEMS) buildings module uses values between 

0.1 and 0.3; a 1% increase in price leads to a 0.1 to 0.3% decrease in energy demand (Wade, 

2003). For the short-run demand of agriculture and construction, the EPA has estimated 

elasticities to be 0.2 for agriculture and approximately 1 for construction (U.S. EPA, 2004). As a 

result, a 1% increase in the prices of agriculture products would lead to a 0.2% decrease in 

demand for those products, while a 1% increase in construction prices would lead to 

approximately a 1% decrease in demand for construction. Given these demand elasticity

scenarios (shaded in gray), approximately a 1% increase unit costs would result in a price 

increase of 0.1 to 1% (Table 5-2). As a result, 10 to 100% of the unit cost increase could be 

passed on to consumers in the form of higher goods/services prices. This price increase would 

correspond to a 0.1 to 0.8% decline in consumption in these markets (Table 5-3). 

Table 5-2. Hypothetical Price Increases for a 1% Increase in Unit Costs

Market Demand 

Elasticity

Market Supply Elasticity

0.1 0.3 0.5 0.7 1 1.5 3

−0.1 0.5% 0.8% 0.8% 0.9% 0.9% 0.9% 1.0%

−0.3 0.3% 0.5% 0.6% 0.7% 0.8% 0.8% 0.9%

−0.5 0.2% 0.4% 0.5% 0.6% 0.7% 0.8% 0.9%

−0.7 0.1% 0.3% 0.4% 0.5% 0.6% 0.7% 0.8%

−1.0 0.1% 0.2% 0.3% 0.4% 0.5% 0.6% 0.8%

−1.5 0.1% 0.2% 0.3% 0.3% 0.4% 0.5% 0.7%

−3.0 0.0% 0.1% 0.1% 0.2% 0.3% 0.3% 0.5%

53.2 Regulated Markets: The Electric Power Generation, Transmission, and Distribution 

Sector

Given that the electric power sector bears majority of the estimated compliance costs and 

the industry is also among the last major regulated energy industries in the United States (EIA, 

2010), the competitive model is not necessarily applicable for this industry.
5-7

Table 5-3. Hypothetical Consumption Decreases for a 1% Increase in Unit Costs

Market Demand 

Elasticity

Market Supply Elasticity

0.1 0.3 0.5 0.7 1 1.5 3

−0.1 −0.1% −0.1% −0.1% −0.1% −0.1% −0.1% −0.1%

−0.3 −0.1% −0.2% −0.2% −0.2% −0.2% −0.3% −0.3%

−0.5 −0.1% −0.2% −0.3% −0.3% −0.3% −0.4% −0.4%

−0.7 −0.1% −0.2% −0.3% −0.4% −0.4% −0.5% −0.6%

−1.0 −0.1% −0.2% −0.3% −0.4% −0.5% −0.6% −0.8%

−1.5 −0.1% −0.3% −0.4% −0.5% −0.6% −0.8% −1.0%

−3.0 −0.1% −0.3% −0.4% −0.6% −0.8% −1.0% −1.5%

Although the electricity industry continues to go through a process of restructuring, whereby the 

industry is moving toward a more competitive framework (see Figure 5-3 for the status of 

restructuring by state),6in many states, electricity prices continue to be fully regulated by Public 

Service Commissions. As a result, the rules and processes outlined by these agencies would 

ultimately determine how these additional regulatory costs would be recovered by affected 

entities.

5.3.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer 

Surplus 

In partial equilibrium analysis, the social costs are estimated by measuring the changes in 

consumer and producer surplus, and these values can be determined using the market supply and 

demand model (Figure 5-2). The change in consumer surplus is measured as follows:

CS = – [Q1 × p] + [0.5 × Q × p]. (5.1)

Higher market prices and lower quantities lead to consumer welfare losses. Similarly, the change 

in producer surplus is measured as follows:

PS = [Q1 × p] – [Q1 × t] – [0.5 × Q × (p – t)]. (5.2)

Higher unit costs and lower production level reduce producer surplus because the net 

price change (p – t) is negative. However, these losses are mitigated because market prices tend 

to rise. 

 

6

http://tonto.eia.doe.gov/energy_in_brief/print_pages/electricity.pdf.
5-8

Figure 5-3. Electricity Restructuring by State

Source. U.S. Energy Information Administration. 2010b. 

<http://www.eia.doe.gov/cneaf/electricity/page/restructuring/restructure_elect.html>. Last updated September 

2010.

5.4 Energy Impacts

Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agencies will prepare 

and submit to the Administrator of the Office of Information and Regulatory Affairs, Office of 

Management and Budget, a Statement of Energy Effects for certain actions identified as 

“significant energy actions.” Section 4(b) of Executive Order 13211 defines “significant energy

actions” as any action by an agency (normally published in the Federal Register) that 

promulgates or is expected to lead to the promulgation of a final rule or regulation, including 

notices of inquiry, advance notices of proposed rulemaking, and notices of proposed rulemaking: 

(1) (i) that is a significant regulatory action under Executive Order 12866 or any successor order, 

and (ii) is likely to have a significant adverse effect on the supply, distribution, or use of energy; 
5-9

or (2) that is designated by the Administrator of the Office of Information and Regulatory Affairs 

as a significant energy action.

This rule is not a significant energy action as designated by the Administrator of the 

Office of Information and Regulatory Affairs because it is not likely to have a significant adverse 

impact on the supply, distribution, or use of energy. EPA has prepared an analysis of energy

impacts that explains this conclusion as follows below.

With respect to energy supply and prices, the analysis in Table 5-4 suggests at the 

industry level, the annualized costs represent a very small fraction of revenue (all industries are 

impacted under 1%). As a result, we can conclude supply and price impacts should be small. 

To enhance understanding regarding the regulation’s influence on energy consumption, 

we examined publicly available data describing energy consumption for the electric power sector 

that will be affected by this rule. The Annual Energy Outlook 2011 (EIA, 2011) provides energy

consumption data. As shown in Table 5-4, this industry account for less than 0.3% of the U.S. 

total liquid fuels and less than 8.0% of natural gas. As a result, any energy consumption changes 

attributable to the regulatory program should not significantly influence the supply, distribution, 

or use of energy.

Table 5-4. U.S. Electric PoweraSector Energy Consumption (Quadrillion BTUs): 2013

Quantity Share of Total Energy Use

Distillate fuel oil 0.09 0.1%

Residual fuel oil 0.22 0.2%

Liquid fuels subtotal 0.31 0.3%

Natural gas 7.63 7.9%

Steam coal 17.37 18.0%

Nuclear power 8.50 8.8%

Renewable energyb4.63 4.8%

Electricity Imports 0.12 0.1%

Total Electric Power Energy Consumptionc38.77 40.1%

Delivered Energy Use 70.56 73.2%

Total Energy Use 96.66 100.0%

a

Includes consumption of energy by electricity-only and combined heat and power plants whose primary business is 

to sell electricity, or electricity and heat, to the public. Includes small power producers and exempt wholesale

generators.

b

Includes conventional hydroelectric, geothermal, wood and wood waste, biogenic municipal solid waste, other 

biomass, petroleum coke, wind, photovoltaic and solar thermal sources. Excludes net electricity imports.
5-10

c

Includes non-biogenic municipal waste not included above.

Source: U.S. Energy Information Administration. 2011a. Supplemental Tables to the Annual Energy Outlook 2011.

Table 2. Available at: <http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.html>.

5.5 Unfunded Mandates

The UMRA requires that we estimate, where accurate estimation is reasonably feasible, 

future compliance costs imposed by the rule and any disproportionate budgetary effects. Our 

estimates of the future compliance costs of the proposed rule are discussed previously in Section 

4 of this RIA. We do not believe that there will be any disproportionate budgetary effects of the 

proposed rule on any particular areas of the country, State or local governments, types of 

communities (e.g., urban, rural), or particular industry segments. 

5.5.1 Future and Disproportionate Costs

The UMRA requires that we estimate, where accurate estimation is reasonably feasible, 

future compliance costs imposed by the rule and any disproportionate budgetary effects. Our 

estimates of the future compliance costs of the proposed rule are discussed previously in Chapter 

4 of this RIA. We do not believe that there will be any disproportionate budgetary effects of the 

proposed rule on any particular areas of the country, State or local governments, types of 

communities (e.g., urban, rural), or particular industry segments. 

5.5.2 Effects on the National Economy

The UMRA requires that we estimate the effect of the proposed rule on the national 

economy. To the extent feasible, we must estimate the effect on productivity, economic growth, 

full employment, creation of productive jobs, and international competitiveness of the U.S. 

goods and services if we determine that accurate estimates are reasonably feasible and that such 

effect is relevant and material. The nationwide economic impact of the proposed rule is 

presented earlier in this RIA chapter. This analysis provides estimates of the effect of the 

proposed rule on most of the categories mentioned above, and these estimates are presented 

earlier in this RIA chapter. In addition, we have determined that the proposed rule contains no 

regulatory requirements that might significantly or uniquely affect small governments. 

Therefore, today’s rule is not subject to the requirements of section 203 of the UMRA.

5.6 Environmental Justice

Executive Order (EO) 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive 

policy on environmental justice. Its main provision directs federal agencies, to the greatest 

extent practicable and permitted by law, to make environmental justice part of their mission by
5-11

identifying and addressing, as appropriate, disproportionately high and adverse human health or 

environmental effects of their programs, policies, and activities on minority populations and lowincome populations in the United States. 

Assuming that our baseline for this RIA does not include implementation of the final 

2010 SI RICE rule, as we state earlier in this document, EPA has determined that this proposed 

rule will not have disproportionately high and adverse human health or environmental effects on 

minority or low-income populations because it increases the level of environmental protection 

for all affected populations without having any disproportionately high and adverse human 

health or environmental effects on any population, including any minority or low-income 

population. This rule is a nationwide standard that reduces air toxics emissions from existing 

stationary SI engines, thus decreasing the amount of such emissions to which all affected 

populations are exposed. 

5.7 Employment Impact Analysis

In addition to addressing the costs and benefits of the proposed reconsideration rule, EPA 

has analyzed the impacts of this rulemaking on employment, which are presented in this section. 

While a standalone analysis of employment impacts is not included in a standard cost-benefit 

analysis, such an analysis is of particular concern in the current economic climate of sustained 

high unemployment. Executive Order 13563, states, “Our regulatory system must protect public 

health, welfare, safety, and our environment while promoting economic growth, innovation, 

competitiveness, and job creation” (emphasis added). Therefore, and consistent with recent 

efforts to characterize the employment effects of economically significant rules, the Agency has 

provided this analysis to inform the discussion of labor demand and employment impacts. 

This employment impact analysis includes estimates of certain short-term and on-going 

labor requirements (increase in labor demand) associated with reporting and recordkeeping, and 

the installation, operating and maintenance of control devices. EPA estimates that about 200 

full-time equivalents (FTE) will be created or supported in the short-term and about 400 FTEs 

will be created or supported annually on a permanent basis. EPA also provides a qualitative 

discussion of other potential employment effects, including both increases and decreases. 

Because of the uncertainties involved, these sets of estimates should not be added in an attempt 

to characterize the overall employment effect.

We have not quantified the rule’s net effects on the overall labor market, or the potential 

changes to workers’ incomes. EPA continues to explore the relevant theoretical and empirical 
5-12

literature and to seek public comments in order to ensure that such estimates are as accurate, 

useful and informative as possible.

From an economic perspective, labor is an input into producing goods and services; if 

regulation requires that more labor be used to produce a given amount of output, that additional 

labor is reflected in an increase in the cost of production.7 When an increase in employment 

occurs as a result of a regulation, it is a cost to firms. Moreover, when the economy is at full 

employment, we would not expect an environmental regulation to have an impact on overall 

employment because labor is being shifted from one sector to another. On the other hand, in 

periods of high unemployment, an increase in labor demand due to regulation may result in a 

short-term net increase in overall employment due to the potential hiring of previously

unemployed workers by the regulated sector to help meet new requirements (e.g., to install new 

equipment) or by the environmental protection sector to produce new abatement capital. When

significant numbers of workers are unemployed, the opportunity costs associated with displacing 

jobs in other sectors are likely to be smaller. To provide a partial picture of the employment 

consequences of this rule, EPA takes two approaches. First, EPA uses information such as 

monitoring, recordkeeping, and reporting estimates derived from its cost analysis documentation 

to generate estimates of employment impacts. Second, the analysis considers the results of 

Morgenstern, Pizer, and Shih (2002) in estimating the effects of the regulation on the regulated 

industry. This approach has been used by EPA previously in recent Regulatory Impact Analyses. 

EPA is interested in public comments on the merits of including information derived in this 

fashion for assessing the employment consequences of regulations.

5.7.1 Employment Impacts from Pollution Control Requirements

Regulations set in motion new orders for pollution control equipment and services. When 

a new regulation is promulgated, one typical response of industry is to order pollution control 

equipment and services in order to comply with the regulation when it becomes effective, while 

closure of plants that choose not to comply is assumed to occur after the compliance date. With 

such a response by industry as a basis, this section presents estimates for short term labor 

requirement needed associated with the monitoring, recordkeeping, and reporting requirements 

for this proposed rule. Environmental regulation may increase revenue and employment in the 

environmental technology industry. While these increases represent gains for that industry, they

 

7

It should be noted that if more labor must be used to produce a given amount of output, then this implies a decrease 

in labor productivity. A decrease in labor productivity will cause a short-run aggregate supply curve to shift to 

the left, and businesses will produce less, all other things being equal. 
5-13

are costs to the regulated industries required to install the equipment. As with any pool of labor, 

the gross size of the labor pool does not reflect the net impact on overall employment after 

adjusting for shifts in other sectors.

Regulated firms may hire workers to design and build pollution controls. Once the 

equipment is installed, regulated firms may hire workers to operate and maintain the pollution 

control equipment – much like they may hire workers to produce more output. Of course, these 

firms may also reassign existing employees to do these activities. A study including an analysis 

of environmental protection employment in six U.S. states in 2003 by Bezdek, Wendling, and 

DiPernab (2008) found that “investments in environmental protection create jobs and displace 

jobs, but the net effect on employment is positive.”8 

Once the equipment is installed, regulated firms may hire workers to operate and 

maintain the pollution control equipment – much like they may hire workers to produce more 

output.

The focus of this part of the analysis is on labor requirements related to the compliance

actions of the affected entities within the affected sector. The employment analysis uses a 

bottom-up engineering-based methodology to estimate employment impacts. The engineering 

cost analysis summarized in Section 4 of this RIA includes estimates of the labor requirements 

associated with implementing the proposed regulations. Each of these labor changes may either 

be required as part of an initial effort to comply with the new regulation or required as a 

continuous or annual effort to maintain compliance. We estimate up-front and continual, annual 

labor requirements by estimating hours of labor required and converting this number to full-time 

equivalents (FTEs) by dividing by 2,080 (40 hours per week multiplied by 52 weeks). We note 

that this type of FTE estimate cannot be used to make assumptions about the specific number of 

people involved or whether new jobs are created for new employees.

The results of this employment estimate are presented in Table 5-5 for the proposed 

NESHAP. The tables breaks down the installation, operation, and maintenance estimates by type 

of pollution control evaluated in the RIA and present both the estimated hours required and the 

conversion of this estimate to FTE. For the proposed NESHAP, reporting and recordkeeping 

requirements were estimated requirements were estimated for the entire rule rather than by 

 

8 Environmental protection, the economy, and jobs: National and regional analyses, Roger H. Bezdek, Robert M. 

Wendling and Paula DiPerna, Journal of Environmental Management Volume 86, Issue 1, January 2008, Pages 

63-79.
5-14

anticipated control requirements; the reporting and recordkeeping estimates are consistent with 

estimates EPA submitted as part of its Information Collection Request (ICR) that is in the 

Supporting Statement for the proposed reconsideration rule.

The up-front labor requirement is estimated at 200 FTEs for the proposed NESHAP. 

These up-front FTE labor requirements can be viewed as short-term labor requirements required 

for affected entities to comply with the new regulation. Ongoing requirements are estimated at 

about 400 FTEs for the proposed NESHAP. These ongoing FTE labor requirements can be 

viewed as sustained labor requirements required for affected entities to continuously comply

with the new regulation. All of this data is found in the cost memorandum for this proposed 

reconsidered rule, and can be found in the docket for the rulemaking. It is important to recognize 

that these seemingly precise estimates are not to be assumed to be exact measures of the 

employment impacts of this rulemaking. They represent a rough approximation of the small 

positive impacts that this rule may have on employment.
5-15

Table 5-5. Labor-based Employment Estimates for Reporting and Recordkeeping and 

Installing, Operating, and Maintaining Control Equipment Requirements for Proposed 

Reconsideration SI RICE NESHAP 

Source

Emission 

Control 

Measure

Projected No. of 

Affected Units

Per-Unit 

One-Time 

Labor 

Estimate 

(Hours)

Total OneTime Labor 

Estimate 

(Hours)

Per-Unit 

Annual 

Labor 

Estimate 

(Hours)

Total 

Annual 

Labor 

Estimate 

(Hours) 

One-Time Full-Time 

Equivalent

Annual 

FullTime 

Equival

ent

Major Sources

SI RICE <100 HP

N/A 70,798 N/A N/A 1 70,798 N/A 34 -O&M/Recordkeeping

2SLB RICE 100-500 HP

N/A 7,398 N/A N/A

N/A

92,480 N/A 34

-O&M/Recordkeeping 1

-Testing 8

-Reporting 3.5

Emergency 4SRB SI RICE 

100-500 HP N/A 1,597 N/A N/A 1 1,597 N/A 0.77

Non-Emergency 4SRB SI 

RICE 100-500 HP

N/A 12,740 N/A N/A

N/A

146,515 N/A 70 -Testing 8

-Reporting 3.5

4SLB SI RICE 100-500 HP

Oxidation Catalyst 14,257 21 300,255

15

163,956 144 34 -Testing 8

-Reporting 3.5

Area Sources

All SI RICE

N/A 228,318 N/A N/A 1 228,318 N/A 110 -O&M/Recordkeeping

Non-Emergency 4SLB SI 

RICE >500 HP in Populated 

Areas

Oxidation Catalyst 768 37 28,117

15

-Testing 15,734 14 7.56 2

-Reporting 3.5

Non-Emergency 4SRB SI 

RICE >500 HP in Populated 

Areas

NSCR 578 86 49,918

33

-Testing 22,236 24 10.69 2

-Reporting 3.5

Total 144 378,290 113 741,633 182 357

Note: Full-time equivalents (FTE) are estimated by first multiplying the projected number of affected units by the 

per unit labor requirements and then dividing by 2,080 (40 hours multiplied by 52 weeks). Totals may not sum due 

to independent rounding.

HP = horsepower

N/A = Not Applicable.

O&M = Operating and Maintenance
5-16

5.7.2 Employment Impacts within the Regulated Industry

In recent RIAs we have applied estimates from a study by Morgenstern, Pizer and 

Shih (2002)1to derive the employment effects of new regulations within the regulated 

industry. (See, for example, the Regulatory Impact Analyses for the recent final MATS 

and final CSAPR regulations). Determining the direction of employment effects in the 

regulated industry is also challenging due to competing effects. Complying with the new 

or more stringent regulation requires additional inputs, including labor, and may alter the 

relative proportions of labor and capital used by regulated firms in their production 

processes. Morgenstern, et al. (2002) demonstrate that environmental regulations can be 

understood as requiring regulated firms to add a new output (environmental quality) to 

their product mixes. Although legally compelled to satisfy this new demand, regulated 

firms have to finance this additional production with the proceeds of sales of their other 

(market) products. Satisfying this new demand requires additional inputs, including labor, 

and may alter the relative proportions of labor and capital used by regulated firms in their 

production processes.

More specifically, Morgenstern, Pizer, and Shih (2002) decompose the effect of 

regulation on net employment in the regulated sector into the following three subcomponents:

 The Demand Effect: higher production costs from complying with the regulation will 

raise market prices, reducing consumption (and production), thereby reducing 

demand for labor within the regulated industry. The “extent of this effect depends on 

the cost increase passed on to consumers as well as the demand elasticity of industry

output.” (p. 416)

 The Cost Effect: Assuming that the capital/labor ratio in the production process is 

held fixed, as “production costs rise, more inputs, including labor, are used to produce 

the same amount of output,” (p. 416). For example, to reduce pollutant emissions 

while holding output levels constant, regulated firms may require additional labor. 

 

1 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 2002. Jobs versus the Environment: An Industry-Level 

Perspective.‖ Journal of Environmental Economics and Management 43(3):412-436.
5-17

 The Factor-Shift Effect: Regulated firms’ production technologies may be more or 

less labor intensive after complying with the regulation (i.e., more/less labor is 

required relative to capital per dollar of output). “Environmental activities may be 

more labor intensive than conventional production,” meaning that “the amount of 

labor per dollar of output will rise.” However, activities may, instead, be less labor 

intensive because “cleaner operations could involve automation and less employment, 

for example.” (p. 416)

The demand effect is expected to have an unambiguously negative effect on employment, 

the cost effect to have an unambiguously positive effect on employment, and the factor-shift 

effect to have an ambiguous effect on employment. Without more information with respect to 

the magnitudes of these three competing effects, it is not possible to predict the net

environmental employment effect in the regulated sector.

Using plant-level Census information between the years 1979 and 1991, Morgenstern et 

al. estimate the effects of pollution abatement expenditures on net employment in four highly 

polluting/regulated sectors (pulp and paper, plastics, steel, and petroleum refining). They

conclude that increased abatement expenditures generally have not caused a significant change in 

net employment in those sectors. More specifically, their results show that, on average across the 

industries studied, each additional $1 million (in 1987$) spent on pollution abatement results in a 

(statistically insignificant) net increase of 1.55 (+/- 2.24) jobs. As a result, the authors conclude 

that increases in pollution abatement expenditures can have positive effects on employment and 

do not necessarily cause economically significant employment changes. The conclusion is 

similar to Berman and Bui (2001), who found that increased air quality regulation in Los 

Angeles did not cause large employment changes. 

Ideally, the EPA would first apply the methodology of Morgenstern et al. to current 

pollution expenditure and market data for the regulated firms to identify the relationship between 

abatement costs and employment, then use this relationship to extrapolate the effect of new 

projected abatement costs on these firms. Unfortunately, current firm-level abatement cost and 

market characteristics are not available. In addition, there are important differences in the 

markets and regulatory settings analyzed in their study and the setting presented here that lead us 

to conclude that it is inappropriate to utilize their quantitative estimates to estimate the 

employment impacts from this reconsideration proposal. The differences between the underlying 

regulations motivating the abatement expenditures studied in Morgenstern et al. are potentially 

too many to allow for the direct transfer of their quantitative estimates for use in analysis of the 

proposed rule. There are also important differences between the industries affected by this 
5-18

proposed rule and the four manufacturing industries studied by Morgenstern et al. For these 

reasons, we conclude there are too many uncertainties as to the comparability of the Morgenstern 

et al. study to apply their estimates to quantify the employment impacts within the regulated 

sector for this proposed regulation. 
6-1

Section 6

SMALL ENTITY SCREENING ANALYSIS

The Regulatory Flexibility Act as amended by the Small Business Regulatory 

Enforcement Fairness Act (SBREFA) generally requires an agency to prepare a regulatory

flexibility analysis of any rule subject to notice and comment rulemaking requirements under the 

Administrative Procedure Act or any other statute, unless the agency certifies that the rule will 

not have a significant economic impact on a substantial number of small entities. Small entities 

include small businesses, small governmental jurisdictions, and small not-for-profit enterprises.

After considering the economic impact of the proposed rule on small entities, the 

screening analysis indicates that this proposed rule will not have a significant economic impact 

on a substantial number of small entities (or “SISNOSE”). Under the analyses EPA considered, 

sales and revenue tests for establishments owned by model small entities are less than 1% except 

electric power generation (NAICS 2211 with receipts less than $100,000 per year) and crop and 

animal production (NAICS 111 and 112 with receipts less than $25,000 per year). These 

findings are similar to those for the final SI RICE rule promulgated in August 2010, though the 

impacts are lower due to the reduction in the cost estimates for these industries. 

6.1 Small Entity Data Set

The industry sectors covered by the proposed rule were identified during the development 

of the cost analysis (EC/R, 2012). The Statistics of United States Business (SUSB) provides

national information on the distribution of economic variables by industry and enterprise size 

(U.S. Census, 2012a, b).1 The Census Bureau and the Office of Advocacy of the SBA supported 

and developed these files for use in a broad range of economic analyses.

2 Statistics include the 

total number of establishments and receipts for all entities in an industry; however, many of these 

entities may not necessarily be covered by the proposed rule. SUSB also provides statistics by

enterprise employment and receipt size. 

The Census Bureau’s definitions used in the SUSB are as follows:

 Establishment: An establishment is a single physical location where business is 

conducted or where services or industrial operations are performed. 

 

1The SUSB data do not provide establishment information for the national security NAICS code (92811) or irrigated 

farms. Since most national security installations are owned by the federal government (e.g., military bases), EPA 

assumes these entities would not be considered small. For irrigated farms, we relied on receipt data provided in 

the 2008 Farm and Irrigation Survey (USDA, 2009).

2

See http://www.census.gov/csd/susb/ and http://www.sba.gov/advo/research/data.html for additional details.
6-2

 Receipts: Receipts (net of taxes) are defined as the revenue for goods produced, 

distributed, or services provided, including revenue earned from premiums, 

commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all 

revenue collected for local, state, and federal taxes. 

 Enterprise: An enterprise is a business organization consisting of one or more 

domestic establishments that were specified under common ownership or control. The 

enterprise and the establishment are the same for single-establishment firms. Each 

multiestablishment company forms one enterprise—the enterprise employment and 

annual payroll are summed from the associated establishments. Enterprise size 

designations are determined by the summed employment of all associated 

establishments.

Because the SBA’s business size definitions (SBA, 2010) apply to an establishment’s 

“ultimate parent company,” we assumed in this analysis that the “enterprise” definition above is 

consistent with the concept of ultimate parent company that is typically used for SBREFA 

screening analyses and the terms are used interchangeably. 

6.2 Small Entity Economic Impact Measures

The analysis generated a set of establishment sales tests (represented as cost-to-receipt 

ratios)3for NAICS codes associated with sectors listed in Table 6-1. Although the appropriate 

SBA size definition should be applied at the parent company (enterprise) level, we can only

compute and compare ratios for a model establishment owned by an enterprise within an SUSB 

size range (employment or receipts). Using the SUSB size range helps us account for receipt 

differences between establishments owned by large and small enterprises and also allows us to 

consider the variation in small business definitions across affected industries. Using 

establishment receipts is also a conservative approach, because an establishment’s parent 

company (the “enterprise”) may have other economic resources that could be used to cover the 

costs of the final rule.

6.2.1 Model Establishment Receipts and Annual Compliance Costs

The sales test compares a representative establishment’s total annual engine costs to the 

average establishment receipts for enterprises in several size categories.

4 For industries with SBA 

 

3The following metrics for other small entity economic impact measures (if applicable) would potentially include

• small governments (if applicable): “revenue” test; annualized compliance cost as a percentage of annual 

government revenues and

• small nonprofits (if applicable): “expenditure” test; annualized compliance cost as a percentage of annual 

operating expenses,

4

For the 1 to 20 employee category, we excluded SUSB data for enterprises with zero employees. These enterprises 

did not operate the entire year.
6-3

employment size standards, we calculated average establishment receipts for each enterprise 

employment range (Table 6-2).5 For industries with SBA receipt size standards, we calculated 

Table 6-1. SI NESHAP for Existing Stationary Reciprocating Internal Combustion 

Engines (RICE): Affected Sectors and SBA Small Business Size Standards

Industry Description

Corresponding

NAICS

SBA Size Standard for 

Businesses (November 5nd, 

2010)

Type of Small 

Entity

Electric Power Generation 2211 a Business and 

government

Natural Gas Transmission 48621 $7.0 million in annual receipts Business

Crude Petroleum & NG Production 211111 500 employees Business

Natural Gas Liquid Producers 211112 500 employees Business

National Security 92811 NA Government

Hydro Power Units See NAICS 2211 1,000 employees Business and 

government

Irrigation Sets Affects NAICS 111 and 

112

Generally $750,000 or less in 

annual receipts

Business

Welders Affects industries that 

use heavy equipment 

such as construction, 

mining, farming 

Varies by 6-digit NAICS code; Business

Example industry:

NAICS 238 = $14 million in 

annual receipts

aNAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm is small if, including its affiliates, it is 

primarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total 

electric output for the preceding fiscal year did not exceed 4 million megawatt hours. Source: U.S. Small 

Business Administration (SBA). 2010. “Table of Small Business Size Standards Matched to North American 

Industry Classification System Codes.” Effective November 5nd, 2010. Downloaded 2/16/12. 

average establishment receipts for each enterprise receipt range (Table 6-3). We included the 

utility sector in the second group, although the SBA size standard for this industry is defined in 

terms of physical units (megawatt hours) versus receipts. Crop and animal production (NAICS 

111 and 112) also have an SBA receipt size standard that defines a small business as receiving 

$750,000 or less in receipts per year. However, SUSB data were not available for these 

industries. Therefore, we conducted the sales test using the following range of establishment 

receipts: farms with annual receipts of $25,000 or less, farms with annual receipts of $100,000 or 

less, farms with annual receipts of $500,000 or less, and farms with annual receipts of $750,000 

or less.

 

5

2007 Economic Census data are at http://www.census.gov/econ/census07/.
6-4

Table 6-2. Average Receipts for Affected Industry by Enterprise: 2009 ($2009 Million/Establishment)

SBA Size 

Standard 

for Businesses

(effective 

November 5, 

2010)

Owned By Enterprises with Employee Range:

NAICS NAICS Description

All 

Enterprises

1–20 

Employees

20–99 

Employees

100–499 

Employees

500+

Employees

211111 Crude petroleum & 

natural gas extraction 

500 employees $30.22 $2.15 $33.02 $151,76 1,570

211112 Natural gas liquid 

extraction 

500 employees $172.81 $0.30 NA $11.88 NA

335312 Motor & generator mfg 1,000 employees $18.58 $1.37 $6.14 $15.96 $29.47

333992 Welding & soldering 

equipment mfg 

500 employees $18.51 $1.56 $6.60 $33.25 NA

Source: U.S. Census Bureau. 2012a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.” 

<http://www.census.gov/csd/susb/ Downloaded 2/22/12.

NA = Not available.
6-5

Table 6-3. Average Receipts for Affected Industry by Enterprise Receipt Range: 2007 ($2008 /establishment)

SBA Size Standard 

for Businesses

(effective November 

5, 2010)

Owned By Enterprises with Receipt Range:

NAICS NAICS Description

All 

Enterprises

0–99K 

Receipts

100–

499.9K 

Receipts

500–

999.9K

Receipts

1,000–

4,999.9K 

Receipts

5,000,000–

9,999,999K 

Receipts

<10,000K 

Receipts

10,000–

49,999K 

Receipts

50,000–

99,999K 

Receipts

100,000K+ 

Receipts

2211 Electric Power 

Generation 

a

$261.0 $31.2 $272.5 $724.9 $2,399.5 $7,330.5 $2,617.7 $24,786.

9

$67,706.

8

$1,394,051

.0

622110 Hospitals $34.5 million in annual 

receipts

$202,058.7 NA $23.82 NA $3,255.0 $7,291.0 $4,692.1 $23,481.

9

$67,545,

6

$508,705.8

237310 Highway , street, and 

bride construction 

$33.5 million in 

Annual Receipts

$7.74 $0.06 $0.32 $0.84 $2.74 $8.11 $2.00 $22.62 $56.48 $56.81

237110 Water and sewer line 

and related structures, 

construction 

$33.5 million in 

Annual Receipts

$3.89 $0.06 $0.32 $0.85 $2.73 $8.17 $1.84 $20.62 $45.05 $47.27

237130 Power 

andcommunication 

line and related 

structures construction 

$33.5 million in 

Annual Receipts

$3.39 $0.06 $0.31 $0.83 $2.52 $7.75 $1.32 $16.84 $34.50 $23.86

237990 zOther heavy and 

civil engineering 

construction 

$33.5 million in 

Annual Receipts

$2.66 $0.06 $0.30 $0.83 $2.48 $7.76 $0.99 $18.72 $40.53 $42.35

92811 National Security NA NA NA NA NA NA NA NA NA NA NA

Notes: Note: Industries in green were included for consistency with the analysis done for finalrule. National Security is included in this table but does not have 

size standards.

a NAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm in these industries is defined as small by SBA if, including its affiliates, it is 

primarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fiscal year did not 

exceed 4 million megawatt hours.

NA = Not available. SUSB did not report this data for disclosure or other reasons.

Source: U.S. Census Bureau. 2009a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.” 

<http://www.census.gov/csd/susb/
6-6

Annual entity compliance costs vary depending on the size of the SI engines used at the 

affected establishment. Absent facility-specific information, we computed per-entity compliance 

costs based for three different cases based on representative establishments—Cases 1, 2, and 3 

(see Table 6-4). Each representative establishment differs based on the size and number of SI

engines being used. Compliance costs are calculated by summing the total annualized 

compliance costs for the relevant engine categories, dividing the sum by the total existing 

population of those engines, and multiplying the average engine cost by the number of engines 

assumed to be at the establishment. Since NAICS 2211 and 48621 are fundamentally different 

than other industries considered in this analysis due to the number of engines affected and 

amount of cost incurred resulting from this proposed rule, we used different assumptions about 

what constitutes the representative establishment and report these assumptions separately. 

 Case 1: The representative establishment for all industries uses three 750+ hp engines 

with an average compliance cost of $680 to $730 per engine, resulting in a total 

annualized compliance cost of approximately $2,040 to $2,200 for this representative 

establishment. 

 Case 2: The representative establishment in NACIS 2211 and 48621 uses two 25 to 

750+ hp engines with an average compliance cost of $412 per engine, resulting in a 

total annualized compliance cost of $824 for this representative establishment. For all 

other industries, the representative establishment uses two 25 to 300 hp engines with 

an average compliance cost of $246 per engine, resulting in a total compliance cost of 

$492 for this representative establishment. 

 Case 3: The representative establishment for all industries uses two 50 to 100 hp 

engines with an average compliance cost of $73 per engine, resulting in a total 

compliance cost of $145 for this representative establishment. 

EPA believes that small entities are most likely to face costs similar to Case 2 (columns 

shaded in gray in Table 6-4) because most of the engines to be affected by this proposed rule in 

NAICS 335312, 333992, 211111, and 211112 are under 300 hp capacity, and most small entities 

in these industries will own engines of this size or smaller. This is corroborated by Figure 6-1 

and 6-2 which shows the distribution of engine population and compliance costs by engine size 

for all industries. However, it is difficult to make a similar claim for NAICS 2211 and 48621 

based on the existing distribution of engines in these industries.6

 

6This claim also cannot be made for NAICS 92811: National Security. However, since most national security 

installations are owned by the federal government (e.g., military bases), EPA assumes these entities would not be 

considered small. 
6-7

For the sales test, we divided the representative establishment compliance costs reported 

in Table 6-4 by the representative establishment receipts reported in Tables 6-2 and 6-3. This is 

known as the cost-to-receipt (i.e., sales) ratio, or the “sales test.” The “sales test” is the impact 

Table 6-4. Representative Establishment Costs Used for Small Entity Analysis ($2009)

Case 1 Case 2 Case 3

NAICS 

2211, 48621

(+750 hp 

only)

All Other 

NAICS 

(+750 hp 

only)

NAICS 

2211,48621 

(25-750+ 

hp)

All Other 

NAICS 

(25–300 

hp)

NAICS 

2211, 

48621 

(25–100 

hp only)

All Other 

NAICS 

(25–100 

hp only)

Total Annualized Costs ($) $7,710,388 $586,434 $82,806,141 $28,057,798 $8,510,985 $6,174,805 

Engine Population 10,548 863 200,974 114,517 117,040 84,913 

Average Engine Cost 

($/engine) $731 $680 $412 $246 $73 $73

Assumed Engines Per 

Establishment 3 3 2 2 2 2

Total Annualized Costs per 

Establishment $2,193 $2,040 $824 $492 $145 $145
6-8

Figure 6-1. Distribution of Engine Population by Size for All Industries

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Electric Power 

Generation 

(2211)

Natural Gas 

Transmission 

(48621)

Crude Petroleum

& NG Production 

(211111)

Natural Gas 

Liquid Producers

(211112)

National Security 

(92811)

Hydro Power 

Units (335312)

Irrigation Sets 

(335312)

Welders

(333992)

>750 hp

600-750 hp

500-600 hp

300-500 hp

175-300 hp

100-175 hp

50-100 hp

25-50 hp
6-9

Figure 6-2. Distribution of Compliance Costs by Engine Size for All Industries

methodology EPA employs in analyzing small entity impacts as opposed to a “profits test,” in 

which annualized compliance costs are calculated as a share of profits.

This is because revenues or sales data are commonly available data for entities normally

impacted by EPA regulations and profits data normally made available are often not the true 

profit earned by firms because of accounting and tax considerations. Revenues as typically 

published are usually correct figures and are more reliably reported when compared to profit 

data. The use of a “sales test” for estimating small business impacts for a rulemaking such as this 

one is consistent with guidance offered by EPA on compliance with SBREFA7and is consistent 

with guidance published by the U.S. SBA’s Office of Advocacy that suggests that cost as a 

percentage of total revenues is a metric for evaluating cost increases on small entities in relation 

to increases on large entities.8

 

7The SBREFA compliance guidance to EPA rulewriters regarding the types of small business analysis that should be 

considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf, pp. 24-25.

8U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Comply with the Regulatory 

Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Electric Power 

Generation 

(2211)

Natural Gas 

Transmission 

(48621)

Crude Petroleum

& NG Production 

(211111)

Natural Gas 

Liquid Producers

(211112)

National Security 

(92811)

Hydro Power 

Units (335312)

Irrigation Sets 

(335312)

Welders

(333992)

>750 hp

600-750 hp

500-600 hp

300-500 hp

175-300 hp

100-175 hp

50-100 hp

25-50 hp
6-10

If the cost-to-receipt ratio is less than 1%, then we consider the proposed rule to not have 

a significant impact on the establishment company in question. We summarize the industries 

with cost-to-receipt ratios exceeding 1% below:

Primary Analysis:

 Case 2: NAICS 2211 with receipts less than $100,000 per year and NAICS 111 and 

112 with receipts less than $25,000 per year

 Case 3: No industries

Sensitivity Analysis (unlikely):

 Case 1: NAICS 2211 with receipts less than $100,000 per year

In the Case 2 primary analysis, only establishments in NAICS 2211 with receipts less 

than $100,000 per year (less than 5 percent of the total), and establishments in NAICS 111 and 

112 with receipts less than $25,000 per year (around 30 percent of the total) have cost-to-receipt 

ratios above 1%. However, establishments earning this level of receipts are likely to be using 

smaller engines than those assumed in Case 2, such as 25 to 300 hp engines. The results of our 

Case 3 analysis demonstrate that these establishments are not significantly impacted when taking 

this engine size into account. 

After considering the economic impacts of this proposed rule on small entities, we certify

that this action will not have a significant economic impact on a substantial number of small 

entities. This certification is based on the economic impact of this proposal action to all affected 

small entities across all industries affected. The percentage of small entities impacted by this 

proposal having annualized costs greater than 1 percent of sales is less than 2 percent according 

to this analysis. We thus conclude that there is no significant economic impact on a substantial 

number of small entities (SISNOSE) for this proposed rule.

Although the proposed rule would not have a significant economic impact on a 

substantial number of small entities, EPA nonetheless tried to reduce the impact of the rule on 

small entities. When developing the revised standards, EPA took special steps to ensure that the 

burdens imposed on small entities were minimal. EPA conducted several meetings with industry

trade associations to discuss regulatory options and the corresponding burden on industry, such 

as recordkeeping and reporting. In addition, as mentioned earlier in this preamble, EPA proposes 

to reduce regulatory requirements for a variety of area sources affected under this RICE rule with 

amendments to the final RICE rules promulgated in 2010. We continue to be interested in the 
6-11

potential impacts of this proposed rule on small entities and welcome comments on issues related 

to such impacts.

6.3 Small Government Entities

The rule also covers sectors that include entities owned by small and large governments. 

However, given the uncertainty and data limitations associated with identifying and 

appropriately classifying these entities, we computed a “revenue” test for a model small 

government, where the annualized compliance cost is a percentage of annual government 

revenues (U.S. Census, 2005a, b). The use of a “revenue test” for estimating impacts to small 

governments for a rulemaking such as this one is consistent with guidance offered by EPA on 

compliance with SBREFA,9and is consistent with guidance published by the US SBA’s Office 

of Advocacy.

10 For example, from the 2007 Census (in 2008 dollars), the average revenue for 

small governments (counties and municipalities) with populations fewer than 10,000 is $4

million per entity, and the average revenue for local governments with populations fewer than 

50,000 is $9 million per entity (U.S. Census Bureau, 2009a; U.S. Census Bureau, 2009b). For the 

smallest group of local governments (<10,000 people), the cost-to-revenue ratio would be 0.2%

or less under each case. For the larger group of governments (<50,000 people), the cost-torevenue ratio is 0.1% or less under all cases.

 

9The SBREFA compliance guidance to EPA rule writers regarding the types of small business analysis that should 

be considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf, pp. 24-25.

10U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Comply with the Regulatory 

Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003. 
7-1

Section 7

HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS

Synopsis

Implementation of emissions controls required by the proposed SI RICE NESHAP 

reconsideration is expected to reduce emissions of hazardous air pollutants (HAP) and have 

ancillary co-benefits that would lower ambient concentrations of NO2, PM2.5 and ozone. In this 

section, we quantify the monetized co-benefits for this rule associated with reducing exposure to 

ambient fine particulate matter (PM2.5) by reducing emissions of precursors. We estimate the 

total monetized co-benefits to be $62 million to $150 million at a 3% discount rate and $55

million to $140 million at a 7% discount rate in 2013. All estimates are in 2010$. These 

estimates reflect the monetized human health benefits of reducing cases of morbidity and 

premature mortality among populations exposed to PM2.5 reduced by this rule. These estimates 

reflect EPA’s most current interpretation of the scientific literature. Higher or lower estimates of 

benefits are possible using other assumptions; examples of this are provided in Figure 7-2. Data, 

resource, and methodological limitations prevented EPA from monetizing the benefits from 

several important benefit categories, including benefits from reducing exposure to HAP, carbon 

monoxide, NO2 and ozone, as well as ecosystem effects and visibility impairment. In addition to 

reducing emissions of PM precursors such as NOx, this rule would reduce 1,800 tons of HAP and 

22,000 tons of carbon monoxide each year.

7.1 Calculation of PM2.5-Related Human Health Co-Benefits

Assuming that our baseline does not include implementation of the 2010 final SI RICE 

rule, as we state earlier in this RIA, this proposed reconsideration NESHAP would reduce 

emissions of NOX, and VOCs. Because these emissions are precursors to PM2.5, reducing these 

emissions would also reduce PM2.5 formation, human exposure and the incidence of PM2.5-

related health effects. Due to analytical limitations, it was not possible to provide a 

comprehensive estimate of PM2.5-related benefits or provide estimates of the health benefits

associated with exposure to HAP, CO, NO2 or ozone. Instead, we used the “benefit-per-ton” 

approach to estimate these benefits. The methodology employed in this analysis is similar to the 

work described in Fann, Fulcher, and Hubbell (2009), but represents an improvement that EPA 

believes would provide more reliable estimates of PM2.5-related health benefits for emissions 

reductions in specific sectors. The key assumptions are described in detail below. These PM2.5 

benefit-per-ton estimates provide the total monetized human health benefits (the sum of 
7-2

premature mortality and premature morbidity) of reducing one ton of PM2.5 from a specified 

source. EPA has used the benefit per-ton technique in several previous RIAs, including the 

recent SO2 NAAQS RIA (U.S. EPA, 2010). 

The Integrated Science Assessment (ISA) for Particulate Matter (U.S. EPA, 2009b) 

identified the human health effects associated with ambient PM2.5, which include premature 

morality and a variety of morbidity effects associated with acute and chronic exposures. Table 7-

1 shows the quantified and unquantified benefits captured in those benefit-per-ton estimates, but 

this table does not include entries for the unquantified health effects associated with exposure to 

ozone and NO2 nor welfare effects such as ecosystem effects and visibility impairment that are 

described in section 7.2. It is important to emphasize that the list of unquantified benefit 

categories is not exhaustive, nor is quantification of each effect complete.
7-3

Table 7-1: Human Health Effects of PM2.5 

Category Specific Effect

Effect Has 

Been 

Quantified

Effect Has 

Been 

Monetized

More 

Information 

(refers to 

CSAPR RIA)

Improved Human Health

Reduced incidence of 

premature mortality 

from exposure to PM2.5

Adult premature mortality based on cohort 

study estimates and expert elicitation 

estimates (age >25 or age >30)

  Section 5.4

Infant mortality (age <1)   Section 5.4

Reduced incidence of 

morbidity from 

exposure to PM2.5

Non-fatal heart attacks (age > 18)   Section 5.4

Hospital admissions—respiratory (all 

ages)   Section 5.4

Hospital admissions—cardiovascular (age 

>20)   Section 5.4

Emergency room visits for asthma (all 

ages)   Section 5.4

Acute bronchitis (age 8-12)   Section 5.4

Lower respiratory symptoms (age 7-14)   Section 5.4

Upper respiratory symptoms (asthmatics 

age 9-11)   Section 5.4

Asthma exacerbation (asthmatics age 6-

18)   Section 5.4

Lost work days (age 18-65)   Section 5.4

Minor restricted-activity days (age 18-65)   Section 5.4

Chronic Bronchitis (age >26)   Section 5.4

Emergency room visits for cardiovascular 

effects (all ages) -- -- Section 5.4

Strokes and cerebrovascular disease (age 

50-79) -- -- Section 5.4

Other cardiovascular effects (e.g., other 

ages) -- -- PM ISA2

Other respiratory effects (e.g., pulmonary 

function, non-asthma ER visits, nonbronchitis chronic diseases, other ages and 

populations)

-- -- PM ISA2

Reproductive and developmental effects 

(e.g., low birth weight, pre-term births, 

etc)

-- -- PM ISA2,3

Cancer, mutagenicity, and genotoxicity 

effects -- -- PM ISA2,3

1 We assess these benefits qualitatively due to time and resource limitations for this analysis.

2 We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods.

3 We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other 

significant concerns over the strength of the association.

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the benefits estimates 

utilize the concentration-response functions as reported in the epidemiology literature, as well as 

the 12 functions obtained in EPA’s expert elicitation study as a sensitivity analysis. 
7-4

 One estimate is based on the concentration-response (C-R) function developed from 

the extended analysis of American Cancer Society (ACS) cohort, as reported in Pope 

et al. (2002), a study that EPA has previously used to generate its primary benefits 

estimate. When calculating the estimate, EPA applied the effect coefficient as 

reported in the study without an adjustment for assumed concentration threshold of 10 

μg/m3as was done in recent (2006-2009) Office of Air and Radiation RIAs.

 One estimate is based on the C-R function developed from the extended analysis of 

the Harvard Six Cities cohort, as reported by Laden et al (2006). This study, 

published after the completion of the Staff Paper for the 2006 PM2.5 NAAQS, has 

been used as an alternative estimate in the PM2.5 NAAQS RIA and PM2.5 benefits 

estimates in RIAs completed since the PM2.5 NAAQS. When calculating the 

estimate, EPA applied the effect coefficient as reported in the study without an 

adjustment for assumed concentration threshold of 10 μg/m3as was done in recent 

(2006-2009) RIAs.

 Twelve estimates are based on the C-R functions from EPA’s expert elicitation study

(Roman et al., 2008) on the PM2.5 -mortality relationship and interpreted for benefits 

analysis in EPA’s final RIA for the PM2.5 NAAQS. For that study, twelve experts 

(labeled A through L) provided independent estimates of the PM2.5 -mortality

concentration-response function. EPA practice has been to develop independent 

estimates of PM2.5 -mortality estimates corresponding to the concentration-response 

function provided by each of the twelve experts, to better characterize the degree of 

variability in the expert responses.

The effect coefficients are drawn from epidemiology studies examining two large 

population cohorts: the American Cancer Society cohort (Pope et al., 2002) and the Harvard Six 

Cities cohort (Laden et al., 2006).1 These are logical choices for anchor points in our 

presentation because, while both studies are well designed and peer reviewed, there are strengths 

and weaknesses inherent in each, which we believe argues for using both studies to generate 

benefits estimates. Previously, EPA had calculated benefits based on these two empirical 

studies, but derived the range of benefits, including the minimum and maximum results, from an 

expert elicitation of the relationship between exposure to PM2.5 and premature mortality (Roman 

 

1 These two studies specify multi-pollutant models that control for SO2, among other co-pollutants.
7-5

et al., 2008).2 Within this assessment, we include the benefits estimates derived from the 

concentration-response function provided by each of the twelve experts to better characterize the 

uncertainty in the concentration-response function for mortality and the degree of variability in 

the expert responses. Because the experts used these cohort studies to inform their 

concentration-response functions, benefits estimates using these functions generally fall between 

results using these epidemiology studies (see Figure 7-2). In general, the expert elicitation 

results support the conclusion that the benefits of PM2.5 control are very likely to be substantial.

Readers interested in reviewing the general methodology for creating the benefit-per-ton 

estimates used in this analysis should consult the draft Technical Support Document (TSD) on

estimating the benefits per ton of reducing PM2.5 and its precursors from in the “Other Non-EGU 

Point” sector(U.S. EPA, 2012).3 The primary difference between the estimates used in this 

analysis and the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality

modeling data utilized. The air quality modeling data used in this analysis use more narrow 

sectors. In addition, the updated air quality modeling data reflects more recent emissions data 

(2005 rather than 2001) and has a higher spatial resolution (12km rather than 36 km grid cells). 

The benefits methodology, such as health endpoints assessed, risk estimates applied, and 

valuation techniques applied did not change. As noted below in the characterization of 

uncertainty, these updated estimates still have similar limitations as all national-average benefitper-ton estimates in that they reflect the geographic distribution of the modeled emissions, which 

may not exactly match the emission reductions in this rulemaking, and they may not reflect local 

variability in population density, meteorology, exposure, baseline health incidence rates, or other 

local factors for any specific location. In this analysis, we apply these national benefit-per-ton 

estimates calculated for this category for NOx and multiply them by the corresponding emission 

reductions.

These models assume that all fine particles, regardless of their chemical composition, are 

equally potent in causing premature mortality because the scientific evidence is not yet sufficient 

to allow differentiation of effects estimates by particle type. NOx is the primary PM2.5 precursors 

affected by this rule. Even though we assume that all fine particles have equivalent health 

 

2

Please see the Section 5.2 of the Portland Cement RIA in Appendix 5A for more information regarding the change 

in the presentation of benefits estimates. 

3

Stationary engines are included in the other non-EGU point source category. If the affected stationary engines are 

more rural than the average of the non-EGU sources modeled, then it is possible that the benefits may be 

somewhat less than we have estimated here. The TSD provides the geographic distribution of the air quality 

changes associated with this sector. It is important to emphasize that this modeling represents the best available 

information on the air quality impact on a per ton basis for these sources.
7-6

effects, the benefit-per-ton estimates vary between precursors depending on the location and 

magnitude of their impact on PM2.5 levels, which drive population exposure. The sector-specific 

modeling does not provide estimates of the PM2.5-related benefits associated with reducing VOC 

emissions, but these unquantified benefits are generally small compared to other PM2.5 precursors 

(U.S. EPA, 2012).

The benefit-per-ton coefficients in this analysis were derived using modified versions of 

the health impact functions used in the PM NAAQS Regulatory Impact Analysis (U.S. EPA, 

2006). Specifically, this analysis uses the method first applied in the Portland Cement NESHAP 

RIA (U.S. EPA, 2009a), which applied the functions directly from the epidemiology studies 

without an adjustment for an assumed threshold. Removing the threshold assumption is a key

difference between the method used in this analysis of PM benefits and the methods used in 

RIAs prior to Portland Cement proposal, and we now calculate incremental benefits down to the 

lowest modeled PM2.5 air quality levels.4

Based on our review of the current body of scientific literature, EPA now estimates PMrelated mortality without applying an assumed concentration threshold. EPA’s Integrated 

Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was reviewed by EPA’s 

Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b), 

concluded that the scientific literature consistently finds that a no-threshold log-linear model 

most adequately portrays the PM-mortality concentration-response relationship while 

recognizing potential uncertainty about the exact shape of the concentration-response function. 

Consistent with this finding, we have conformed the previous threshold sensitivity

analysis to the current state of the PM science by incorporating a “Lowest Measured Level” 

(LML) assessment, which is a method EPA has employed in several recent RIAs including the 

Cross-State Air Pollution Rule (U.S. EPA, 2011b). This information allows readers to determine 

the portion of population exposed to annual mean PM2.5 levels at or above the LML of each 

study; in general, our confidence in the estimated PM mortality decreases as we consider air 

quality levels further below the LML in major cohort studies that estimate PM-related mortality. 

While an LML assessment provides some insight into the level of uncertainty in the estimated 

PM mortality benefits, EPA does not view the LML as a threshold and continues to quantify PMrelated mortality impacts using a full range of modeled air quality concentrations. It is important 

to emphasize that we have high confidence in PM2.5-related effects down to the lowest LML of 

the major cohort studies, which is 5.8 μg/m3. Just because we have greater confidence in the 

 

4 Additional updates since the Cement RIA include a revised VSL and updated baseline incidence rates. 
7-7

benefits above the LML, this does not mean that we have no confidence that benefits occur 

below the LML. For a summary of the scientific review statements regarding the lack of a 

threshold in the PM2.5-mortality relationship, see the Technical Support Document (TSD) 

entitled Summary of Expert Opinions on the Existence of a Threshold in the ConcentrationResponse Function for PM2.5-related Mortality (U.S. EPA, 2010b).

For this analysis, policy-specific air quality data is not available due to time or resource 

limitations. For these rules, we are unable to estimate the percentage of premature mortality 

associated with this specific rule’s emission reductions at each PM2.5 level. However, we believe 

that it is still important to characterize the distribution of exposure to baseline air quality levels. 

As a surrogate measure of mortality impacts, we provide the percentage of the population 

exposed at each PM2.5 level using the source apportionment modeling used to calculate the 

benefit-per-ton estimates for this sector. It is important to note that baseline exposure is only one 

parameter in the health impact function, along with baseline incidence rates population, and 

change in air quality. In other words, the percentage of the population exposed to air pollution 

below the LML is not the same as the percentage of the population experiencing health impacts 

as a result of a specific emission reduction policy. The most important aspect, which we are 

unable to quantify for rules without rule-specific air quality modeling, is the shift in exposure 

associated with this specific rule. Therefore, caution is warranted when interpreting the LML 

assessment for this rule. The results of this analysis are provided in Section 7.3.

As is the nature of RIAs, the assumptions and methods used to estimate air quality

benefits evolve over time to reflect the Agency’s most current interpretation of the scientific and 

economic literature. For a period of time (2004-2008), the Office of Air and Radiation (OAR) 

valued mortality risk reductions using a value of statistical life (VSL) estimate derived from a 

limited analysis of some of the available studies. OAR arrived at a VSL using a range of $1 

million to $10 million (2000$) consistent with two meta-analyses of the wage-risk literature. 

The $1 million value represented the lower end of the interquartile range from the Mrozek and 

Taylor (2002) meta-analysis of 33 studies. The $10 million value represented the upper end of 

the interquartile range from the Viscusi and Aldy (2003) meta-analysis of 43 studies. The mean 

estimate of $5.5 million (2000$)5 was also consistent with the mean VSL of $5.4 million 

estimated in the Kochi et al. (2006) meta-analysis. However, the Agency neither changed its 

official guidance on the use of VSL in rulemakings nor subjected the interim estimate to a 

 

5 After adjusting the VSL for a different currency year (2010$) and to account for income growth to 2015 of the $5.5 

million value, the VSL is $8.0 million. 
7-8

scientific peer-review process through the Science Advisory Board (SAB) or other peer-review 

group. 

During this time, the Agency continued work to update its guidance on valuing mortality 

risk reductions, including commissioning a report from meta-analytic experts to evaluate 

methodological questions raised by EPA and the SAB on combining estimates from the various 

data sources. In addition, the Agency consulted several times with the Science Advisory Board 

Environmental Economics Advisory Committee (SAB-EEAC) on the issue. With input from the 

meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, 

appropriate meta-analytic techniques to combine estimates from unique data sources and 

different studies, including those using different methodologies (i.e., wage-risk and stated 

preference) (U.S. EPA-SAB, 2007). 

Until updated guidance is available, the Agency determined that a single, peer-reviewed 

estimate applied consistently best reflects the SAB-EEAC advice it has received. Therefore, the 

Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines 

for Preparing Economic Analyses (U.S. EPA, 2000)6 while the Agency continues its efforts to 

update its guidance on this issue. This approach calculates a mean value across VSL estimates 

derived from 26 labor market and contingent valuation studies published between 1974 and 

1991. The mean VSL across these studies is $6.3 million (2000$).7 The Agency is committed to 

using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions 

and has made significant progress in responding to the SAB-EEAC’s specific recommendations. 

In implementing these rules, emission controls may lead to reductions in ambient PM2.5 

below the National Ambient Air Quality Standards (NAAQS) for PM in some areas and assist 

other areas with attaining the PM NAAQS. Because the PM NAAQS RIAs also calculate PM 

benefits, there are important differences worth noting in the design and analytical objectives of 

each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air 

quality standard nationwide based on an array of emission control strategies for different sources. 

In short, NAAQS RIAs hypothesize, but do not predict, the control strategies that States may

choose to enact when implementing a NAAQS. The setting of a NAAQS does not directly result 

 

6

 In revised Economic Guidelines (U.S. EPA, 2010c), EPA retained the VSL endorsed by the SAB with the 

understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future. 

Therefore, this report does not represent final agency policy. 

7 This value is $4.8 in 1990$. In this analysis, we adjust the VSL to account for a different currency year ($2010) 

and to account for income growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is 

$9.2 million. 
7-9

in costs or benefits, and as such, the NAAQS RIAs are merely illustrative and are not intended to 

be added to the costs and benefits of other regulations that result in specific costs of control and 

emission reductions. However, some costs and benefits estimated in this RIA account for the 

same air quality improvements as estimated in the illustrative PM2.5 NAAQS RIA. 

By contrast, the emission reductions for implementation rules are from a specific class of 

well-characterized sources. In general, EPA is more confident in the magnitude and location of 

the emission reductions for implementation rules rather than illustrative NAAQS analyses. 

Emission reductions achieved under these and other promulgated rules will ultimately be 

reflected in the baseline of future NAAQS analyses, which would reduce the incremental costs 

and benefits associated with attaining the NAAQS. EPA remains forward looking towards the 

next iteration of the 5-year review cycle for the NAAQS, and as a result does not issue updated 

RIAs for existing NAAQS that retroactively update the baseline for NAAQS implementation. 

For more information on the relationship between the NAAQS and rules such as analyzed here, 

please see Section 1.2.4 of the SO2 NAAQS RIA (U.S. EPA, 2010a).
7-10

Figure 7.1 illustrates the relative breakdown of the monetized PM2.5 health benefits. 

Figure 7-1: Breakdown of Monetized PM2.5 Health Benefits using Mortality Function 

from Pope et al. (2002)*

*This pie chart breakdown is illustrative, using the results based on Pope et al. (2002) as an example. Using the 

Laden et al. (2006) function for premature mortality, the percentage of total monetized benefits due to adult 

mortality would be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be similar 

if a 7% discount rate was used. 

Table 7-2 provides a general summary of the monetized PM-related health benefits by

precursor, including the emission reductions and benefit-per-ton estimates at discount rates of 

3% and 7%.8 Table 7-3 provides a summary of the reductions in health incidences as a result of 

the pollution reductions. In Table 7-4, we provide the benefits using our anchor points of Pope 

et al. and Laden et al. as well as the results from the expert elicitation on PM mortality. Figure 

7-2 provides a visual representation of the range of PM2.5-related benefits estimates using 

 

8 To comply with Circular A-4, EPA provides monetized benefits using discount rates of 3% and 7% (OMB, 2003). 

These benefits are estimated for a specific analysis year (i.e., 2013), and most of the PM benefits occur within 

that year with two exceptions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we 

assume 5 years of follow-up medical costs and lost wages. For premature mortality, we assume that there is a 

“cessation” lag between PM exposures and the total realization of changes in health effects. Although the 

structure of the lag is uncertain, EPA follows the advice of the SAB-HES to assume a segmented lag structure 

characterized by 30% of mortality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 

20 after the reduction in PM2.5 (U.S. EPA-SAB, 2004). Changes in the lag assumptions do not change the total 

number of estimated deaths but rather the timing of those deaths. Therefore, discounting only affects the AMI 

costs after the analysis year and the valuation of premature mortalities that occur after the analysis year. As such, 

the monetized benefits using a 7% discount rate are only approximately 10% less than the monetized benefits

using a 3% discount rate. 

Adult Mortality - Pope et 

al. 93%

Chronic Bronchitis 4%

AMI 2%

Acute Respiratory Symptoms 

0.5%

Infant Mortality 0.4%

Work Loss Days 0.2%

Hospital Admissions, Cardio 

0.2%

Hospital Admissions, Resp 

0.04%

Asthma Exacerbation 0.01%

Acute Bronchitis 0.01%

Upper Resp Symp 0.00%

Lower Resp Symp 0.00%

ER Visits, Resp 0.00%

Other 1%
7-11

concentration-response functions supplied by experts. Figure 7-3 shows a breakdown of 

monetized benefits by engine size. 

The benefit-per-ton estimates shown in this RIA are different than the benefit-per-ton 

estimates cited in the 2010 final SI RICE RIA for two reasons. First, these estimates are based 

on updated air quality modeling, which results in slightly higher benefits per ton for other nonEGU point sources than the previous modeling. Second, these estimates have been inflated to 

2010$. Third, the new air quality modeling did not provide estimates associated with reducing 

VOCs. 

Table 7-2: General Summary of Monetized PM2.5-Related Health Co-Benefits Estimates 

for the Proposed SI RICE NESHAP Reconsideration (millions of 2010$)

*

Pollutant

Emissions 

Reductions 

(tons)

Benefit 

per ton 

(Pope, 

3%)

Benefit 

per ton 

(Laden, 

3%)

Benefit 

per ton 

(Pope, 

7%)

Benefit 

per ton 

(Laden, 

7%)

Total Monetized 

Benefits (millions 

of 2010$ at 3%)

Total Monetized 

Benefits (millions 

of 2010$ at 7%)

PM2.5 Precursors

 NOX 9,648 $6,400 $16,000 $5,700 $14,000 $62 to $150 $55 to $140

Total $62 to $150 $55 to $140

* All estimates are for the analysis year (2013), and are rounded to two significant figures so numbers may not sum 

across columns. It is important to note that the monetized benefits do not include reduced health effects from direct 

exposure to NO2, ozone exposure, ecosystem effects, or visibility impairment. All fine particles are assumed to have 

equivalent health effects, but the benefit per ton estimates vary because each ton of precursor reduced has a different 

propensity to form PM2.5. The monetized benefits incorporate the conversion from precursor emissions to ambient 

fine particles. Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology.
7-12

Table 7-3: Summary of Reductions in Health Incidences from PM2.5-Related Co-Benefits 

for Proposed SI RICE NESHAP Reconsideration*

Avoided Premature Mortality

Pope et al. 7

Laden et al. 18

Avoided Morbidity

Chronic Bronchitis 5

Emergency Department Visits, Respiratory 5

Hospital Admissions, Respiratory 1

Hospital Admissions, Cardiovascular 3

Acute Bronchitis 11

Lower Respiratory 140

Upper Respiratory 110

Minor Restricted Activity Days 5,600

Work Loss Days 950

Asthma Exacerbation 230

Acute Myocardial Infarction 8

* All estimates are for the analysis year (2013) and are rounded to whole numbers with two significant figures. All 

fine particles are assumed to have equivalent health effects because the scientific evidence is not yet sufficient to 

allow differentiation of effects estimates by particle type. Confidence intervals are unavailable for this analysis 

because of the benefit-per-ton methodology.
7-13

Table 7-4: All PM2.5 Co-Benefits Estimates for the Proposed SI RICE NESHAP

Reconsideration at discount rates of 3% and 7% in 2013 (in millions of 

2010$)*

3% 7%

Benefit-per-ton Coefficients Derived from Epidemiology Literature

Pope et al. $62 $55

Laden et al. $150 $140

Benefit-per-ton Coefficients Derived from Expert Elicitation

Expert A $160 $150

Expert B $120 $110

Expert C $120 $110

Expert D $87 $78

Expert E $200 $180

Expert F $110 $100

Expert G $74 $66

Expert H $93 $83

Expert I $120 $110

Expert J $100 $89

Expert K $24 $21

Expert L $82 $73

*All estimates are rounded to two significant figures. The benefits estimates from the Expert Elicitation are provided 

as a reasonable characterization of the uncertainty in the mortality estimates associated with the concentrationresponse function. Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology
7-14

Figure 7-2: Total Monetized PM2.5 Co-Benefits of Proposed SI RICE NESHAP 

Reconsideration in 2013

*This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the 

Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on 

PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates 

are based in part on the concentration-response function provided in those studies. 

$0

$50

$100

$150

$200

$250

Pope et al.

Laden et al.

Millions (2010$)

PM2.5 mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions

2013*

3% DR

7% DR
7-15

Figure 7-3: Breakdown of Total Monetized PM2.5 Co-Benefits of Proposed SI RICE 

NESHAP Reconsideration by Engine Size

7.2 Unquantified Benefits

The monetized benefits estimated in this RIA only reflect a subset of benefits attributable 

to the health effect reductions associated with ambient fine particles. Data, time, and resource

limitations prevented EPA from quantifying the impacts to, or monetizing the benefits from 

several important benefit categories, including benefits from reducing exposure to HAP, CO, 

NO2, and ozone exposure, as well as ecosystem effects, and visibility impairment. This does not 

imply that there are no benefits associated with these emission reductions. These benefits are 

described qualitatively in this section. 

7.2.1 HAP Benefits

Even though emissions of air toxics from all sources in the U.S. declined by approximately

42% since 1990, the 2005 National-Scale Air Toxics Assessment (NATA) predicts that most 

Americans are exposed to ambient concentrations of air toxics at levels that have the potential to 

cause adverse health effects (U.S. EPA, 2011c).9 The levels of air toxics to which people are 

exposed vary depending on where people live and work and the kinds of activities in which they

engage. In order to identify and prioritize air toxics, emission source types and locations that are 

 

9 The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/.

Area 500-600 HP

21%

Area 600-750 HP

5%

Area >750 HP

74%
7-16

of greatest potential concern, U.S. EPA conducts the NATA.10 The most recent NATA was 

conducted for calendar year 2005 and was released in March 2011. NATA includes four steps:

1) Compiling a national emissions inventory of air toxics emissions from outdoor sources

2) Estimating ambient and exposure concentrations of air toxics across the United States

3) Estimating population exposures across the United States

4) Characterizing potential public health risk due to inhalation of air toxics including both 

cancer and noncancer effects

Based on the 2005 NATA, EPA estimates that about 5% of census tracts nationwide have 

increased cancer risks greater than 100 in a million. The average national cancer risk is about 50 

in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are 

formaldehyde and benzene.11 Secondary formation (e.g., formaldehyde forming from other 

emitted pollutants) was the largest contributor to cancer risks, while stationary, mobile and 

background sources contribute almost equal portions of the remaining cancer risk.

Noncancer health effects can result from chronic,12 subchronic,13 or acute14 inhalation 

exposures to air toxics, and include neurological, cardiovascular, liver, kidney, and respiratory

effects as well as effects on the immune and reproductive systems. According to the 2005 

NATA, about three-fourths of the U.S. population was exposed to an average chronic 

concentration of air toxics that has the potential for adverse noncancer respiratory health effects.

Results from the 2005 NATA indicate that acrolein is the primary driver for noncancer 

respiratory risk. 

 

10 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting 

regulatory standards. These limitations and uncertainties are discussed on the 2005 NATA website. Even so, 

this modeling framework is very useful in identifying air toxic pollutants and sources of greatest concern, setting 

regulatory priorities, and informing the decision making process. U.S. EPA.(2011). 2005 National-Scale Air 

Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/

11 Details about the overall confidence of certainty ranking of the individual pieces of NATA assessments including 

both quantitative (e.g., model-to-monitor ratios) and qualitative (e.g., quality of data, review of emission 

inventories) judgments can be found at http://www.epa.gov/ttn/atw/nata/roy/page16.html.

12 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database 

(http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than 

approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used 

laboratory animal species).

13 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, 

up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically 

used laboratory animal species).

14 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.
7-17

Figure 7-4 and Figure depict the estimated census tract-level carcinogenic risk and 

noncancer respiratory hazard from the assessment. It is important to note that large reductions in 

HAP emissions may not necessarily translate into significant reductions in health risk because 

toxicity varies by pollutant, and exposures may or may not exceed levels of concern. For 

example, acetaldehyde mass emissions are more than double acrolein emissions on a national 

basis, according to EPA’s 2005 National Emissions Inventory (NEI). However, the Integrated 

Risk Information System (IRIS) reference concentration (RfC) for acrolein is considerably lower 

than that for acetaldehyde, suggesting that acrolein could be potentially more toxic than 

acetaldehyde. Thus, it is important to account for the toxicity and exposure, as well as the mass 

of the targeted emissions. 

Figure 7-4 Estimated Chronic Census Tract Carcinogenic Risk from HAP exposure 

from outdoor sources (2005 NATA)
7-18

Figure 7-5 Estimated Chronic Census Tract Noncancer (Respiratory) Risk from HAP 

exposure from outdoor sources (2005 NATA)

Due to methodology and time limitations under the court-ordered schedule, we were 

unable to estimate the benefits associated with the hazardous air pollutants that would be reduced 

as a result of these rules. In a few previous analyses of the benefits of reductions in HAP, EPA 

has quantified the benefits of potential reductions in the incidences of cancer and non-cancer risk 

(e.g., U.S. EPA, 1995). In those analyses, EPA relied on unit risk factors (URF) developed 

through risk assessment procedures.15 These URFs are designed to be conservative, and as such, 

are more likely to represent the high end of the distribution of risk rather than a best or most 

likely estimate of risk. As the purpose of a benefit analysis is to describe the benefits most likely

to occur from a reduction in pollution, use of high-end, conservative risk estimates would 

overestimate the benefits of the regulation. While we used high-end risk estimates in past 

analyses, advice from the EPA’s Science Advisory Board (SAB) recommended that we avoid 

 

15The unit risk factor is a quantitative estimate of the carcinogenic potency of a pollutant, often expressed as the 

probability of contracting cancer from a 70-year lifetime continuous exposure to a concentration of one μg/m3of 

a pollutant.
7-19

using high-end estimates in benefit analyses (U.S. EPA-SAB, 2002). Since this time, EPA has 

continued to develop better methods for analyzing the benefits of reductions in HAP.

As part of the second prospective analysis of the benefits and costs of the Clean Air Act 

(U.S. EPA, 2011a), EPA conducted a case study analysis of the health effects associated with 

reducing exposure to benzene in Houston from implementation of the Clean Air Act (IEc, 2009). 

While reviewing the draft report, EPA’s Advisory Council on Clean Air Compliance Analysis 

concluded that “the challenges for assessing progress in health improvement as a result of 

reductions in emissions of hazardous air pollutants (HAPs) are daunting...due to a lack of 

exposure-response functions, uncertainties in emissions inventories and background levels, the 

difficulty of extrapolating risk estimates to low doses and the challenges of tracking health 

progress for diseases, such as cancer, that have long latency periods” (U.S. EPA-SAB, 2008).

In 2009, EPA convened a workshop to address the inherent complexities, limitations, and 

uncertainties in current methods to quantify the benefits of reducing HAP. Recommendations 

from this workshop included identifying research priorities, focusing on susceptible and 

vulnerable populations, and improving dose-response relationships (Gwinn et al., 2011). 

In summary, monetization of the benefits of reductions in cancer incidences requires 

several important inputs, including central estimates of cancer risks, estimates of exposure to 

carcinogenic HAP, and estimates of the value of an avoided case of cancer (fatal and non-fatal). 

Due to methodology and time limitations under the court-ordered schedule, we did not attempt to 

monetize the health benefits of reductions in HAP in this analysis. Instead, we provide a 

qualitative analysis of the health effects associated with the HAP anticipated to be reduced by 

these rules.EPA remains committed to improving methods for estimating HAP benefits by 

continuing to explore additional concepts of benefits, including changes in the distribution of 

risk. 

Although numerous HAPs may be emitted from SI RICE, a few HAPs account for over 90% 

of the total mass of HAPs emissions emitted. These HAPs are formaldehyde (72%), acetaldehyde 

(8%), acrolein (7%), methanol (3%), and benzene (3%). Although we do not have estimates of 

emission reductions for each HAP, this rule is anticipated to reduce 1,800 tons of HAPs each year. 

Below we describe the health effects associated with the top 5 HAPs by mass emitted from SI RICE.
7-20

Formaldehyde

Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on 

evidence in humans and in rats, mice, hamsters, and monkeys.16 Substantial additional research 

since that time informs current scientific understanding of the health effects associated with 

exposure to formaldehyde. These include recently published research conducted by the National 

Cancer Institute (NCI) which found an increased risk of nasopharyngeal cancer and 

lymphohematopoietic malignancies such as leukemia among workers exposed to 

formaldehyde.17,18 In an analysis of the lymphohematopoietic cancer mortality from an extended 

follow-up of these workers, NCI confirmed an association between lymphohematopoietic cancer 

risk and peak formaldehyde exposures.19 A recent NIOSH study of garment workers also found 

increased risk of death due to leukemia among workers exposed to formaldehyde.20 Extended 

follow-up of a cohort of British chemical workers did not find evidence of an increase in 

nasopharyngeal or lymphohematopoietic cancers, but a continuing statistically significant excess 

in lung cancers was reported.21

In the past 15 years there has been substantial research on the inhalation dosimetry for 

formaldehyde in rodents and primates by the Chemical Industry Institute of Toxicology (CIIT, 

now renamed the Hamner Institutes for Health Sciences), with a focus on use of rodent data for 

refinement of the quantitative cancer dose-response assessment.22,23,24 CIIT’s risk assessment of 

 

16 U.S. EPA. 1987. Assessment of Health Risks to Garment Workers and Certain Home Residents from Exposure to 

Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA-HQ-OAR-2010-0162.

17 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic 

malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615-

1623. Docket EPA-HQ-OAR-2010-0162.

18 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from solid cancers among 

workers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130. Docket EPA-HQOAR-2010-0162.

19 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. 

Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National 

Cancer Institute cohort. J. National Cancer Inst. 101: 751-761. Docket EPA-HQ-OAR-2010-0162.

20 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to formaldehyde: an update. 

Occup. Environ. Med. 61: 193-200. Docket EPA-HQ-OAR-2010-0162.

21 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers 

exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. Docket EPA-HQ-OAR-2010-0162.

22 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller. 2003. Biologically 

motivated computational modeling of formaldehyde carcinogenicity in the F344 rat. Tox Sci 75: 432-447. 

Docket EPA-HQ-OAR-2010-0162.

23 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller. 2004. Human respiratory 

tract cancer risks of inhaled formaldehyde: Dose-response predictions derived from biologically-motivated 

computational modeling of a combined rodent and human dataset. Tox Sci 82: 279-296. Docket EPA-HQ-OAR2010-0162.
7-21

formaldehyde incorporated mechanistic and dosimetric information on formaldehyde. These data 

were modeled using a biologically-motivated two-stage clonal growth model for cancer and also 

a point of departure based on a Benchmark Dose approach. However, it should be noted that 

recent research published by EPA indicates that when two-stage modeling assumptions are 

varied, resulting dose-response estimates can vary by several orders of magnitude.25,26,27,28 These 

findings are not supportive of interpreting the CIIT model results as providing a conservative 

(health protective) estimate of human risk.29 EPA research also examined the contribution of the 

two-stage modeling for formaldehyde towards characterizing the relative weights of key events 

in the mode-of-action of a carcinogen. For example, the model-based inference in the published 

CIIT study that formaldehyde’s direct mutagenic action is not relevant to the compound’s 

tumorigenicity was found not to hold under variations of modeling assumptions.30

Based on the developments of the last decade, in 2004, the working group of the IARC 

concluded that formaldehyde is carcinogenic to humans (Group 1), on the basis of sufficient 

evidence in humans and sufficient evidence in experimental animals - a higher classification than 

previous IARC evaluations. After reviewing the currently available epidemiological evidence, 

the IARC (2006) characterized the human evidence for formaldehyde carcinogenicity as 

“sufficient,” based upon the data on nasopharyngeal cancers; the epidemiologic evidence on 

leukemia was characterized as “strong.”31

Formaldehyde exposure also causes a range of noncancer health effects, including 

irritation of the eyes (burning and watering of the eyes), nose and throat. Effects from repeated 

 

24 Chemical Industry Institute of Toxicology (CIIT).1999. Formaldehyde: Hazard characterization and dose-response 

assessment for carcinogenicity by the route of inhalation. CIIT, September 28, 1999. Research Triangle Park, 

NC. Docket EPA-HQ-OAR-2010-0162.

25 U.S. EPA. Analysis of the Sensitivity and Uncertainty in 2-Stage Clonal Growth Models for Formaldehyde with 

Relevance to Other Biologically-Based Dose Response (BBDR) Models. U.S. Environmental Protection Agency, 

Washington, D.C., EPA/600/R-08/103, 2008. Docket EPA-HQ-OAR-2010-0162.

26 Subramaniam, R; Chen, C; Crump, K; .et .al. (2008) Uncertainties in biologically-based modeling of 

formaldehyde-induced cancer risk: identification of key issues. Risk Anal 28(4):907-923. Docket EPA-HQOAR-2010-0162.

27 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for 

formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. 

Docket EPA-HQ-OAR-2010-0162.

28 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.

29 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.

30 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for 

formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. 

Docket EPA-HQ-OAR-2010-0162.

31 International Agency for Research on Cancer (2006) Formaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2-

ol. Monographs Volume 88. World Health Organization, Lyon, France. Docket EPA-HQ-OAR-2010-0162.
7-22

exposure in humans include respiratory tract irritation, chronic bronchitis and nasal epithelial 

lesions such as metaplasia and loss of cilia. Animal studies suggest that formaldehyde may also 

cause airway inflammation – including eosinophil infiltration into the airways. There are several 

studies that suggest that formaldehyde may increase the risk of asthma – particularly in the 

young.32,33

The above-mentioned rodent and human studies, as well as mechanistic information and 

their analyses, were evaluated in EPA’s recent Draft Toxicological Review of Formaldehyde –

Inhalation Assessment through the Integrated Risk Information System (IRIS) program. This 

draft IRIS assessment was released in June 2010 for public review and comment and external 

peer review by the National Research Council (NRC). The NRC released their review report in 

April 2011 (http://www.nap.edu/catalog.php?record_id=13142). The EPA is currently revising 

the draft assessment in response to this review.

Acetaldehyde

Acetaldehyde is classified in EPA’s IRIS database as a probable human carcinogen, based 

on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous routes.34 

Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. Department of 

Health and Human Services (DHHS) in the 11th Report on Carcinogens and is classified as 

possibly carcinogenic to humans (Group 2B) by the IARC.35,36 The primary noncancer effects of 

exposure to acetaldehyde vapors include irritation of the eyes, skin, and respiratory tract.37 

 

32 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological profile for Formaldehyde. 

Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. 

http://www.atsdr.cdc.gov/toxprofiles/tp111.html. Docket EPA-HQ-OAR-2010-0162.

33 WHO (2002) Concise International Chemical Assessment Document 40: Formaldehyde. Published under the joint 

sponsorship of the United Nations Environment Programme, the International Labour Organization, and the 

World Health Organization, and produced within the framework of the Inter-Organization Programme for the 

Sound Management of Chemicals. Geneva. Docket EPA-HQ-OAR-2010-0162.

34 U.S. Environmental Protection Agency (U.S. EPA). 1991. Integrated Risk Information System File of 

Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. 

This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.

35 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens 

available at: http://ntp.niehs.nih.gov/go/16183.

36 International Agency for Research on Cancer (IARC). 1999. Re-evaluation of some organic chemicals, hydrazine, 

and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, 

Vol 71. Lyon, France.

37 U.S. Environmental Protection Agency (U.S. EPA). 1991. Integrated Risk Information System File of 

Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC.

This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.
7-23

Acrolein

EPA determined in 2003 that the human carcinogenic potential of acrolein could not be 

determined because the available data were inadequate. No information was available on the 

carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of 

carcinogenicity.

38

 The IARC determined in 1995 that acrolein was not classifiable as to its 

carcinogenicity in humans.39

Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure 

resulting in upper respiratory tract irritation, mucus hypersecretion and congestion. The intense 

irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who 

suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure.40 These 

data and additional studies regarding acute effects of human exposure to acrolein are 

summarized in EPA’s 2003 IRIS Human Health Assessment for acrolein.41 Evidence available 

from studies in humans indicate that levels as low as 0.09 ppm (0.21 mg/m3) for five minutes 

may elicit subjective complaints of eye irritation with increasing concentrations leading to more 

extensive eye, nose and respiratory symptoms.

42

 Lesions to the lungs and upper respiratory tract 

of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein.43 Acute 

exposure effects in animal studies report bronchial hyper-responsiveness.44 In a recent study, the 

acute respiratory irritant effects of exposure to 1.1 ppm acrolein were more pronounced in mice 

with allergic airway disease by comparison to non-diseased mice which also showed decreases in 

 

38 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

Research and Development, National Center for Environmental Assessment, Washington, DC. This material is 

available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.

39 International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk of 

chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals, World 

Health Organization, Lyon, France.

40 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

EPA/635/R-03/003. p. 10. Research and Development, National Center for Environmental Assessment, 

Washington, DC. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.

41 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

2003. Research and Development, National Center for Environmental Assessment, Washington, DC. 

EPA/635/R-03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.

42 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. p. 11. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.

43 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.

44 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 

Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
7-24

respiratory rate.45 Based on these animal data and demonstration of similar effects in humans 

(i.e., reduction in respiratory rate), individuals with compromised respiratory function (e.g., 

emphysema, asthma) are expected to be at increased risk of developing adverse responses to 

strong respiratory irritants such as acrolein.

Benzene

The EPA’s IRIS database lists benzene as a known human carcinogen (causing leukemia) 

by all routes of exposure, and concludes that exposure is associated with additional health effects, 

including genetic changes in both humans and animals and increased proliferation of bone marrow 

cells in mice.46,47,48 EPA states in its IRIS database that data indicate a causal relationship between 

benzene exposure and acute lymphocytic leukemia and suggest a relationship between benzene 

exposure and chronic non-lymphocytic leukemia and chronic lymphocytic leukemia. The IARC 

has determined that benzene is a human carcinogen and the DHHS has characterized benzene as a 

known human carcinogen.49,50 A number of adverse noncancer health effects including blood 

disorders, such as preleukemia and aplastic anemia, have also been associated with long-term 

exposure to benzene.51,52 

 

45 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immediate sensory nerve-mediated respiratory responses to 

irritants in healthy and allergic airway-diseased mice. J Appl Physiol 94(4):1563-1571.

46

 U.S. Environmental Protection Agency (U.S. EPA). 2000. Integrated Risk Information System File for Benzene. 

Research and Development, National Center for Environmental Assessment, Washington, DC. This material is 

available electronically at: http://www.epa.gov/iris/subst/0276.htm.

47 International Agency for Research on Cancer, IARC monographs on the evaluation of carcinogenic risk of 

chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agency for Research 

on Cancer, World Health Organization, Lyon, France, p. 345-389, 1982. 

48 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. (1992) Synergistic action of the benzene metabolite 

hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony-stimulating factor in vitro, 

Proc. Natl. Acad. Sci. 89:3691-3695.

49 International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health 

Organization, Lyon, France.

50 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens 

available at: http://ntp.niehs.nih.gov/go/16183.

51

 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197.

52 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554.
7-25

Methanol

Exposure of humans to methanol by inhalation or ingestion may result in central nervous 

system depression and degenerative changes in the brain and visual systems. After inhaled or 

ingested, methanol is converted to formate, a highly toxic metabolite that within the course of a 

few hours can cause narcosis, metabolic acidosis, headaches, severe abdominal and leg pain and 

visual degeneration that can lead to blindness.53

Methanol has been demonstrated to cause developmental toxicity in rats and mice, and 

reproductive and developmental toxicity in monkeys. A number of studies have reported adverse 

effects in the offspring of rats and mice exposed to methanol by inhalation including reduced 

weight of brain pituitary gland, thymus, thyroid, reduced overall fetal body weight and increased 

incidence of extra ribs and cleft palate.54,55,56 Methanol inhalation studies using rhesus monkeys 

have reported a decrease in the length of pregnancy, and limited evidence of impaired learning 

ability in offspring.

57,58,59,60 EPA has not classified methanol with respect to its carcinogenicity. 

Other Air Toxics

In addition to the compounds described above, other toxic compounds might be affected 

by these rules. Information regarding the health effects of those compounds can be found in 

EPA’s IRIS database.61

 

53 Rowe, VK and McCollister, SB. 1981. Alcohols. In: Patty's Industrial Hygiene and Toxicology, 3rd ed. Vol. 2C, 

GD Clayton, FE Clayton, Eds. John Wiley & Sons, New York, pp. 4528-4541.

54 New Energy Development Organization (NEDO). 1987. Toxicological research of methanol as a fuel for power 

station: summary report on tests with monkeys, rats and mice. Tokyo, Japan.

55 Nelson, BK; Brightwell, WS; MacKenzie, DR; Khan, A; Burg, JR; Weigel, WW; Goad, PT. 1985. Teratological 

assessment of methanol and ethanol at high inhalation levels in rats. Toxicol Sci, 5: 727-736.

56 Rogers, JM; Barbee, BD; Rehnberg, BF. 1993. Critical periods of sensitivity for the developmental toxicity of 

inhaled methanol. Teratology, 47: 395.

57 Burbacher, T; Grant, K; Shen, D; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring 

developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part II: 

developmental effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA.

58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring 

developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part I: 

methanol disposition and reproductive toxicity in adult females. Health Effects Institute. Cambridge, MA.

59 Burbacher, TM; Grant, KS; Shen, DD; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic maternal 

methanol inhalation in nonhuman primates (Macaca fascicularis): reproductive performance and birth outcome. 

Neurotoxicol Teratol, 26: 639-650.

60 Burbacher, TM; Shen, DD; Lalovic, B; Grant, KS; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic 

maternal methanol inhalation in nonhuman primates (Macaca fascicularis): exposure and toxicokinetics prior to 

and during pregnancy. Neurotoxicol Teratol, 26: 201-221.

61 U.S. EPA Integrated Risk Information System (IRIS) database is available at: www.epa.gov/iris
7-26

7.2.2 Additional NO2 Co-Benefits

In addition to being a precursor to PM2.5, NOx emissions are also associated with a 

variety of respiratory health effects. Unfortunately, we were unable to estimate the health 

benefits associated with reduced NO2 or ozone exposure in this analysis because we do not have 

air quality modeling data available. Therefore, this analysis only quantifies and monetizes the 

PM2.5 benefits associated with the reductions in NO2 emissions. 

Following an extensive evaluation of health evidence from epidemiologic and laboratory

studies, the Integrated Science Assessment (ISA) for Nitrogen Dioxide concluded that there is a 

likely causal relationship between respiratory health effects and short-term exposure to NO2 

(U.S. EPA, 2008c). Persons with preexisting respiratory disease, children, and older adults may

be more susceptible to the effects of NO2 exposure. Based on our review of this information, we 

identified four short-term morbidity endpoints that the NO2 ISA identified as a “likely causal 

relationship”: asthma exacerbation, respiratory-related emergency department visits, and 

respiratory-related hospitalizations. The differing evidence and associated strength of the 

evidence for these different effects is described in detail in the NO2 ISA. The NO2 ISA also 

concluded that the relationship between short-term NO2 exposure and premature mortality was 

“suggestive but not sufficient to infer a causal relationship” because it is difficult to attribute the 

mortality risk effects to NO2 alone. Although the NO2 ISA stated that studies consistently

reported a relationship between NO2 exposure and mortality, the effect was generally smaller 

than that for other pollutants such as PM. 

NOx emissions also contribute to a variety of adverse welfare effects, including acidic 

deposition, visibility impairment, nutrient enrichment. Deposition of nitrogen causes 

acidification, which can cause a loss of biodiversity of fishes, zooplankton, and macro 

invertebrates in aquatic ecosystems, as well as a decline in sensitive tree species, such as red 

spruce (Picea rubens) and sugar maple (Acer saccharum) in terrestrial ecosystems. In the 

northeastern United States, the surface waters affected by acidification are a source of food for 

some recreational and subsistence fishermen and for other consumers and support several 

cultural services, including aesthetic and educational services and recreational fishing. Biological 

effects of acidification in terrestrial ecosystems are generally linked to aluminum toxicity, which 

can cause reduced root growth, which restricts the ability of the plant to take up water and 

nutrients. These direct effects can, in turn, increase the sensitivity of these plants to stresses, such 

as droughts, cold temperatures, insect pests, and disease leading to increased mortality of canopy 

trees. Terrestrial acidification affects several important ecological services, including declines in 

habitat for threatened and endangered species (cultural), declines in forest aesthetics (cultural), 
7-27

declines in forest productivity (provisioning), and increases in forest soil erosion and reductions 

in water retention (cultural and regulating). (U.S. EPA, 2008d)

Deposition of nitrogen is also associated with aquatic and terrestrial nutrient enrichment. 

In estuarine waters, excess nutrient enrichment can lead to eutrophication. Eutrophication of 

estuaries can disrupt an important source of food production, particularly fish and shellfish 

production, and a variety of cultural ecosystem services, including water-based recreational and 

aesthetic services. Terrestrial nutrient enrichment is associated with changes in the types and 

number of species and biodiversity in terrestrial systems. Excessive nitrogen deposition upsets 

the balance between native and nonnative plants, changing the ability of an area to support 

biodiversity. When the composition of species changes, then fire frequency and intensity can 

also change, as nonnative grasses fuel more frequent and more intense wildfires. (U.S. EPA, 

2008d)

7.2.3 Ozone Co-Benefits

In the presence of sunlight, NOx and VOCs can undergo a chemical reaction in the 

atmosphere to form ozone. Reducing ambient ozone concentrations is associated with 

significant human health benefits, including mortality and respiratory morbidity (U.S. EPA, 

2008a). Epidemiological researchers have associated ozone exposure with adverse health effects 

in numerous toxicological, clinical and epidemiological studies (U.S. EPA, 2006c). These health 

effects include respiratory morbidity such as fewer asthma attacks, hospital and ER visits, school 

loss days, as well as premature mortality.

7.2.4 Carbon Monoxide Co-Benefits

Carbon monoxide in ambient air is formed primarily by the incomplete combustion of 

carbon-containing fuels and photochemical reactions in the atmosphere. The amount of CO emitted 

from these reactions, relative to carbon dioxide (CO2), is sensitive to conditions in the combustion 

zone, such as fuel oxygen content, burn temperature, or mixing time. Upon inhalation, CO diffuses 

through the respiratory system to the blood, which can cause hypoxia (reduced oxygen availability). 

Carbon monoxide can elicit a broad range of effects in multiple tissues and organ systems that are 

dependent upon concentration and duration of exposure. The Integrated Science Assessment for 

Carbon Monoxide (U.S. EPA, 2010a) concluded that short-term exposure to CO is “likely to have a 

causal relationship” with cardiovascular morbidity, particularly in individuals with coronary heart 

disease. Epidemiologic studies associate short-term CO exposure with increased risk of emergency 

department visits and hospital admissions. Coronary heart disease includes those who have angina 

pectoris (cardiac chest pain), as well as those who have experienced a heart attack. Other 
7-28

subpopulations potentially at risk include individuals with diseases such as chronic obstructive 

pulmonary disease (COPD), anemia, or diabetes, and individuals in very early or late life stages, such 

as older adults or the developing young. The evidence is suggestive of a causal relationship between 

short-term exposure to CO and respiratory morbidity and mortality. The evidence is also suggestive 

of a causal relationship for birth outcomes and developmental effects following long-term exposure 

to CO, and for central nervous system effects linked to short- and long-term exposure to CO.

7.2.5 Visibility Impairment Co-Benefits

Reducing secondary formation of PM2.5 would improve visibility throughout the U.S.

Fine particles with significant light-extinction efficiencies include sulfates, nitrates, organic

carbon, elemental carbon, and soil (Sisler, 1996). Suspended particles and gases degrade

visibility by scattering and absorbing light. Higher visibility impairment levels in the East are

due to generally higher concentrations of fine particles, particularly sulfates, and higher average

relative humidity levels. Visibility has direct significance to people’s enjoyment of daily

activities and their overall sense of wellbeing. Good visibility increases the quality of life where

individuals live and work, and where they engage in recreational activities. Previous analyses

(U.S. EPA, 2006; U.S. EPA, 2011a; U.S. EPA, 2011b) show that visibility benefits are a 

significant welfare benefit category. Without air quality modeling, we are unable to estimate

visibility related benefits, nor are we able to determine whether VOC emission reductions would 

be likely to have a significant impact on visibility in urban areas or Class I areas.

7.3 Characterization of Uncertainty in the Monetized Co-Benefits

In any complex analysis, there are likely to be many sources of uncertainty. Many inputs 

are used to derive the final estimate of economic benefits, including emission inventories, air 

quality models (with their associated parameters and inputs), epidemiological estimates of 

concentration-response (C-R) functions, estimates of values, population estimates, income 

estimates, and estimates of the future state of the world (i.e., regulations, technology, and human 

behavior). For some parameters or inputs it may be possible to provide a statistical 

representation of the underlying uncertainty distribution. For other parameters or inputs, the 

necessary information is not available. As discussed in the PM2.5 NAAQS RIA (Table 5.5) (U.S. 

EPA, 2006), there are a variety of uncertainties associated with these PM benefits. Therefore, 

the estimates of annual benefits should be viewed as representative of the magnitude of benefits 

expected, rather than the actual benefits that would occur every year. 

It is important to note that the monetized benefit-per-ton estimates used here reflect 

specific geographic patterns of emissions reductions and specific air quality and benefits 
7-29

modeling assumptions. For example, these estimates do not reflect local variability in population 

density, meteorology, exposure, baseline health incidence rates, or other local factors. Use of 

these $/ton values to estimate benefits may lead to higher or lower benefit estimates than if 

benefits were calculated based on direct air quality modeling. Great care should be taken in 

applying these estimates to emission reductions occurring in any specific location, as these are 

all based on national or broad regional emission reduction programs and therefore represent 

average benefits-per-ton over the entire United States. The benefits-per-ton for emission 

reductions in specific locations may be very different than the estimates presented here. For more 

information, see the TSD describing the calculation of the new benefit-per-ton estimates (U.S. 

EPA, 2012).

PM2.5 mortality benefits are the largest benefit category that we monetized in this 

analysis. To better characterize the uncertainty associated with mortality impacts that are 

estimated to occur in areas with low baseline levels of PM2.5, we included the LML assessment. 

For this analysis, policy-specific air quality data is not available due to time or resource 

limitations, thus we are unable to estimate the percentage of premature mortality associated with 

this specific rule’s emission reductions at each PM2.5 level. As a surrogate measure of mortality

impacts, we provide the percentage of the population exposed at each PM2.5 level using the 

source apportionment modeling used to calculate the benefit-per-ton estimates for this sector. A 

very large proportion of the population is exposed at or above the lowest LML of the cohort 

studies (Figures 7-6 and 7-7), increasing our confidence in the PM mortality analysis. Figure 7-6

shows a bar chart of the percentage of the population exposed to various air quality levels in the 

pre- and post-policy policy. Figure 7-7 shows a cumulative distribution function of the same 

data. Both figures identify the LML for each of the major cohort studies. As the policy shifts 

the distribution of air quality levels, fewer people are exposed to PM2.5 levels at or above the 

LML. Using the Pope et al. (2002) study, the 77% of the population is exposed to annual mean 

PM2.5 levels at or above the LML of 7.5 μg/m3. Using the Laden et al. (2006) study, 25% of the 

population is exposed above the LML of 10 μg/m3.

 As we model avoided premature deaths 

among populations exposed to levels of PM2.5, we have lower confidence in levels below the 

LML for each study. It is important to emphasize that we have high confidence in PM2.5-related 

effects down to the lowest LML of the major cohort studies. Just because we have greater 

confidence in the benefits above the LML, this does not mean that we have no confidence that 

benefits occur below the LML. 

A large fraction of the baseline exposure occurs below the level of the National Ambient 

Air Quality Standard (NAAQS) for annual PM2.5 at 15 μg/m3, which wasset in 2006. It is 
important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS 

reflect the level determined by the 

adequate margin of safety, taking into consideration effects on susceptible populations. While 

benefits occurring below the standard may be less certain than those occurring above the 

standard, EPA considers them to be legitimate components of the total benefits estimate.

Figure 7-6. Percentage of Adult Population by Annual Mean PM

Baseline

7-30

important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS 

reflect the level determined by the Administrator to be protective of public health within an 

adequate margin of safety, taking into consideration effects on susceptible populations. While 

benefits occurring below the standard may be less certain than those occurring above the 

considers them to be legitimate components of the total benefits estimate.

Percentage of Adult Population by Annual Mean PM2.5 Exposure 

important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS 

Administrator to be protective of public health within an 

adequate margin of safety, taking into consideration effects on susceptible populations. While 

benefits occurring below the standard may be less certain than those occurring above the 

considers them to be legitimate components of the total benefits estimate.

Exposure in the 
Figure 7-7. Cumulative Distribution of Adult Population 

Exposure in the Baseline

Above we present the estimates of the total benefits, based on our interpretation of the 

best available scientific literature and methods and supported by the SAB

(NRC, 2002). The benefits estimates are s

For example, for key assumptions underlying the estimates for premature mortality, which 

typically account for more than 90% of the total benefits, we were able to quantify include the 

following: 

1. PM2.5 benefits were derived through benefit per

local variability in population density, meteorology, exposure, baseline health 

incidence rates, or other local factors that might lead to an over

estimate of the actual benefits of controlling 

the specific location of the air quality changes associated with this rulemaking; as 

such, it is not feasible to estimate the proportion of benefits occurring in different 

locations, such as designated nonattainment areas. In addition, the benefit

estimates are based on emissions from existing sources. To the extent that the 

geographic distribution of the emissions reductions for this rule are different than the 

7-31

Cumulative Distribution of Adult Population by Annual Mean PM

in the Baseline

Above we present the estimates of the total benefits, based on our interpretation of the 

best available scientific literature and methods and supported by the SAB-HES and the NAS 

). The benefits estimates are subject to a number of assumptions and uncertainties. 

For example, for key assumptions underlying the estimates for premature mortality, which 

90% of the total benefits, we were able to quantify include the 

benefits were derived through benefit per-ton estimates, which do not reflect 

local variability in population density, meteorology, exposure, baseline health 

incidence rates, or other local factors that might lead to an over-estimate or under

of the actual benefits of controlling PM precursors. We do not have data on 

the specific location of the air quality changes associated with this rulemaking; as 

such, it is not feasible to estimate the proportion of benefits occurring in different 

ns, such as designated nonattainment areas. In addition, the benefit

estimates are based on emissions from existing sources. To the extent that the 

geographic distribution of the emissions reductions for this rule are different than the 

Annual Mean PM2.5 

Above we present the estimates of the total benefits, based on our interpretation of the 

HES and the NAS 

ubject to a number of assumptions and uncertainties. 

For example, for key assumptions underlying the estimates for premature mortality, which 

90% of the total benefits, we were able to quantify include the 

ton estimates, which do not reflect 

local variability in population density, meteorology, exposure, baseline health 

estimate or underWe do not have data on 

the specific location of the air quality changes associated with this rulemaking; as 

such, it is not feasible to estimate the proportion of benefits occurring in different 

ns, such as designated nonattainment areas. In addition, the benefit-per-ton 

estimates are based on emissions from existing sources. To the extent that the 

geographic distribution of the emissions reductions for this rule are different than the 
7-32

modeled emissions, the benefits may be underestimated or overestimated. In general, 

there is inherently more uncertainty for new sources, which may not be included in 

the emissions inventory, than existing sources.

2. We assume that all fine particles, regardless of their chemical composition, are 

equally potent in causing premature mortality. This is an important assumption, 

because PM2.5 produced via transported precursors emitted from EGUs may differ 

significantly from direct PM2.5 released from diesel engines and other industrial 

sources, but no clear scientific grounds exist for supporting differential effects 

estimates by particle type. 

3. We assume that the health impact function for fine particles is linear down to the 

lowest air quality levels modeled in this analysis. Thus, the estimates include health 

benefits from reducing fine particles in areas with varied concentrations of PM2.5,

including both regions that are in attainment with fine particle standard and those that 

do not meet the standard down to the lowest modeled concentrations. 

4. To characterize the uncertainty in the relationship between PM2.5 and premature 

mortality (which typically accounts for 85% to 95% of total monetized benefits), we 

include a set of twelve estimates based on results of the expert elicitation study in 

addition to our core estimates. Even these multiple characterizations omit the 

uncertainty in air quality estimates, baseline incidence rates, populations exposed and 

transferability of the effect estimate to diverse locations. As a result, the reported 

confidence intervals and range of estimates give an incomplete picture about the 

overall uncertainty in the PM2.5 estimates. This information should be interpreted 

within the context of the larger uncertainty surrounding the entire analysis. For more 

information on the uncertainties associated with PM2.5 benefits, please consult the 

PM2.5 NAAQS RIA (Table 5.5).

This RIA does not include the type of detailed uncertainty assessment found in the PM 

NAAQS RIA because we lack the necessary air quality input and monitoring data to run the 

benefits model. In addition, we have not conducted any air quality modeling for this rule. 

Moreover, it was not possible to develop benefit-per-ton metrics and associated estimates of 

uncertainty using the benefits estimates from the PM RIA because of the significant differences 

between the sources affected in that rule and those regulated here. However, the results of the 

Monte Carlo analyses of the health and welfare benefits presented in Chapter 5 of the PM RIA 

can provide some evidence of the uncertainty surrounding the benefits results presented in this 

analysis. 
7-33

7.4 Comparison of Co-Benefits and Costs

Using a 3% discount rate, we estimate the total combined monetized co-benefits of the 

reconsidered SI RICE NESHAP proposal to be $62 million to $150 million in the 

implementation year (2013). Using a 7% discount rate, we estimate the total monetized cobenefits of the final rule to be $55 million to $140 million. The annualized social costs of the 

reconsidered SI RICE NESHAP proposal are $115 million at a 7% interest rate.62 Thus, the net 

benefits are $-53 million to $35 million at a 3% discount rate and $-60 million to $ 25 million at 

a 7% discount rate. All estimates are in 2010$ for the year 2013. 

Table 7-5 shows a summary of the monetized co-benefits, social costs, and net benefits 

for the reconsidered SI RICE NESHAP proposal, respectively. Figures 7-8 and 7-9 show the full 

range of net benefits estimates (i.e., annual co-benefits minus annualized costs) utilizing the 14 

different PM2.5 mortality functions at discount rates of 3% and 7%. In addition, the benefits from 

reducing 22,000 tons of carbon monoxide and 1,800 tons of HAPs each year from SI RICE have 

not been included in these estimates. 

Table 7-5. Summary of the Annualized Monetized Benefits, Social Costs, and Net 

Benefits for the Proposed SI RICE NESHAP Reconsideration in 2013 (millions of 2010$)1

3% Discount Rate 7% Discount Rate

Total Monetized Benefits2$62 to $150 $55 to $140

Total Compliance Costs3$115 $115

Net Benefits $-53 to $35 $-60 to $25

Non-monetized Benefits

Health effects from HAP exposure

Health effects from CO, NO2, and ozone exposure

Ecosystem effects 

Visibility impairment 

1All estimates are for the implementation year (2013), and are rounded to two significant figures. 

2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM2.5 through 

reductions of PM2.5 precursors such as NOx. Human health benefits are shown as a range from Pope et al. (2002) 

to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical composition, are 

equally potent in causing premature mortality because the scientific evidence is not yet sufficient to allow 

differentiation of effects estimates by particle type. Because these estimates were generated using benefit-per-ton 

estimates, we do not break down the total monetized benefits into specific components here. See Figure 7-1 for 

an illustration of the breakdown, or the RIA for the final Cross-States Air Pollution Rule (EPA, 2011) for more 

information. 

 

62 For more information on the annualized social costs, please refer to Section 5 of this RIA.
7-34

3

The annual compliance costs serve as a proxy for the annual social costs of this rule given the lack of difference 

between the two. The engineering compliance costs are annualized using a 7 percent discount rate. 
Figure 7-8. Net Benefits for Proposed SI RICE

discount rate*

*Net Benefits are quantified in terms of PM

benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. 

The monetized benefits incorporate the conversion from precursor emissions to 

-$100

-$80

-$60

-$40

-$20

$0

$20

$40

$60

$80

$100

Pope et al.

Millions (2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

7-35

Proposed SI RICE NESHAP Reconsideration at 3% 

*Net Benefits are quantified in terms of PM2.5 at a 3% discount rate for 2013 and are in 2010$. This graph shows 14 

benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. 

The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles.

Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

Reconsideration at 3% 

. This graph shows 14 

benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. 

ambient fine particles. 

Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2 
Figure 7-9. Net Benefits for Proposed SI RICE

discount rate*

*Net Benefits are quantified in terms of PM

in 2010$. This graph shows 14 benefits estimates combined with the cost estimate. The monetized benefits 

incorporate the conversion from precursor emissions to ambient fine particles.

-$100

-$80

-$60

-$40

-$20

$0

$20

$40

$60

$80

Pope et al.

Millions (2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

7-36

Proposed SI RICE NESHAP Reconsideration

*Net Benefits are quantified in terms of PM2.5 benefits at a 7% discount rate at a 3% discount rate 

graph shows 14 benefits estimates combined with the cost estimate. The monetized benefits 

incorporate the conversion from precursor emissions to ambient fine particles. 

Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

Reconsideration at 7% 

at a 3% discount rate for 2013 and are 

graph shows 14 benefits estimates combined with the cost estimate. The monetized benefits 

Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2 
7-37

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7-39

U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economic 

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7-40

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8-1

Section 8

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8-3

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8-4

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8-5

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8-7

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8-8

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