## To: cortney_higgins@omb.eop.gov From: Larry Sorrels/RTP/USEPA/US Date: 01/11/2013 04:48PM Cc: Melanie King/RTP/USEPA/US@EPA, RobertJ Wayland/RTP/USEPA/US@EPA, Darryl Weatherhead/RTP/USEPA/US@EPA, Paula VanLare/DC/USEPA/US@EPA, Paul Balserak/DC/USEPA/US@EPA, Amy Lamson/RTP/USEPA/US@EPA Subject: CI reconsideration RIA - redline/strikeout for most recent comments and edits

(See attached file: EO12866CIRICERIAfinal_2060-AQ48_201301-07- 14InteragencycommentsunderEO1356EPA3redstrike1-11-14.docx) Hello Cortney,

Attached is a redline/strikeout of the CI reconsideration RIA that is based on the RIA version you sent yesterday afternoon. Language on the ULSD costs and the burden estimate are now included in section 4, and the compliance data section was removed as per an internal EPA recommendation (it's still in the SI RIA). Thanks, and please let me know if you have any questions.

Larry Sorrels US EPA/OAQPS/HEID/AEG RTP, NC 27711 919-541-5041 919-541-0839 (fax) C439-02 Room No. C445-A

=iii 

# Regulatory Impact Analysis (RIA) for Reconsideration of Existing Stationary Compression Ignition (CI) Engines NESHAP

Final Report

January 2013iv This page is intentionally blank.v January 2013

Regulatory Impact Analysis (RIA) for Recons ideration of Existing Stationary Compression Ignition (CI) Engines NESHAP

Prepared by: Larry Sorrels

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impacts Division Air Economics Group Research Triangle Park, NCvi CONTENTS

Section Page

Section 1 Executive Summary ..................................................................................... 1 ES.1 Summary of Impacts for CI RICE NESHAP Reconsideration ..............1-1 ES.2 Comparison with Results from 2010 Final CI RICE NESHAP.............1-2

Section 2 Introduction .................................................................................................. 1

2.1 Organization of this Report ...................................................................................... 1

Section 3 Industry Profile ............................................................................................ 2
3.1.1 Overview ...................................................................................................... 2
3.1.2 Goods and Services Used ............................................................................. 4
3.1.3 Business Statistics ........................................................................................ 5

3.2 Oil and Gas Extraction ............................................................................................. 7
3.2.1 Overview ...................................................................................................... 7
3.2.2 Goods and Services Used ........................................................................... 10
3.2.3 Business Statistics ...................................................................................... 11

3.3 Pipeline Transportation of Natural Gas ................................................................. 16
3.3.1 Overview .................................................................................................... 16
3.3.2 Goods and Services Used ........................................................................... 17

3.4 General Medical and Surgical Hospitals ................................................................ 21
3.4.1 Overview .................................................................................................... 21
3.4.2 Goods and Services Used ........................................................................... 21
3.4.3 Business Statistics ...................................................................................... 23

3.5 Irrigation Sets and Welding Equipment ................................................................. 26
3.5.1 Overview .................................................................................................... 26 Deleted: 1-1

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3.5.3 Business Statistics ...................................................................................... 30

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

4.1 Background .............................................................................................................. 1

4.2 Summary of the Final Reconsideration Rule .......................................................... 4 4.2.1 Emergency Demand Response.................................................4-4 4.2.2 Peak Shaving.....

................................................................................................... 13 4.2.3 Stationary Agricultural Engines - San Joaquin Valley..................... 4-18 4.2.4 Remote Areas of Alaska.......................................................4-20 4.2.5 Offshore Vessels................................................................4-23 4.2.6 Compliance Date...............................................................4-24

4.3 What the Pollutants Regulated by this Final Reconsideration Rule? ................ 4-22

4.4 Cost Impacts....................................................................................................... 4-26

4.4.1 Introduction ............................................................................................ 4-26
4.4.2 Major Sources ............................................................................................ 19
4.4.3 Area Sources .............................................................................................. 21

4.5 Baseline Emissions and Emission Reductions ................................................... 4-42

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

5.1 Compliance Costs of the Final Rule ........................................................................ 1

5.2 Social Cost Estimate ................................................................................................ 4

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis .............. 5
5.3.1 Changes in Market Prices and Quantities .......

........................ ..................... 5
5.3.2 Regulated Markets: The Electric Power Generation, Transmission, and Distribution Sector ................................................................................ 8
5.3.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus ................................................................................... 9

5.4 Energy Impacts ...................................................................................................... 10

5.5 Unfunded Mandates ............................................................................................... 11 Deleted: 3-26

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5.5.2 Effects on the National Economy .............................................................. 12

5.6 Environmental Justice ............................................................................................ 13
5.7 Employment Impacts 5.7.1 Employment Impacts from Pollution Control Requirements.............5-14
5.7.2 Employment Impacts within the Regulated Industry................................. 18

Section 6 Small Entity Screening Analysis ................................................................. 1

6.1 Small Entity Data Set ............................................................................................... 1

6.2 Small Entity Economic Impact Measures ................................................................ 2
6.2.1 Model Establishment Receipts and Annual Compliance Costs ................... 2

6.3 Small Government Entities .................................................................................... 12

Section 7 Human Health Benefits of Emissions Reductions ....................................... 1

7.1 Calculation of PM 2.5 -Related Human Health Co-Benefits ...................................... 1

7.2 Unquantified Benefits ............................................................................................ 15
7.2.1 HAP Benefits ................................................................................................ 15
7.2.2 Ozone Co-Benefits ..................................................................................... 26
7.2.3 Carbon Monoxide Co-Benefits .................................................................. 26
7.2.4 Visibility Impairment Co-Benefits ............................................................ 27

7.3 Characterization of Uncertainty in the Monetized Co-Benefits ............................ 27

7.4 Comparison of Co-Benefits and Costs ................................................................... 32

7.5 References .............................................................................................................. 35

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Number Page

1-1. Breakdown of Total Monetized PM 2.5 Co-Benefits of CI RICE Reconsideration by Engine Size.............................. ................................................................1

- 7 1-2. Total Monetized PM 2.5 Co-Benefits Estimates for the CI RICE Reconsideration in 2013...........................

.................................... .....................................1-8 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) ............................................ 3-5 3-4. Industrial Production Index (NAICS 211) .................................................................. 3-1 3-5. Distribution of Establishments within Pi peline Transportation (NAICS 486) .......... 3-17 3-6. Distribution of Revenue within Pipeline Transportation (NAICS 486) .................... 3-17 3-7. Share of Establishments by Legal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002 ................................ 3-19 3-8. Share of Establishments by Legal Form of Organization in the General Medical and Surgical Hospitals Industry (NAICS 6221): 2002 .............................................. 3-24 3-9. Industrial Production Index (NAICS 333111) .......................................................... 3-28

5-1. Distribution of Annualized Direct Comp liance Costs by Industry: 2013 ....................... 2 5-2. Distribution of Engine Population by Horsepower Group: 2013 .................................... 3 5-3. Average Annualized Cost per Engine by Horsepower Group: 2013 ($2007) ................. 3 5-4. Market Demand and Supply Model: With and Without Regulation ............................... 6 5-5. Electricity Restructuring by State .................................................................................. 10

7-1. Breakdown of Monetized PM 2.5 Health Co-benefits using Mortality Function from Pope et al. (2002) .............................................................................................. 7-10 7-2. Total Monetized PM 2.5 Co-Benefits of CI RICE NESHAP Reconsideration in 2013 .......................................................................................................................... . 7-14 7-3. Breakdown of Total Monetized Co-benefits for CI RICE NESHAP Reconsideration by Engine Size...................................................7-15

7-4. Estimated Chronic Census Tract Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA) .................................................................................. 7-17 7-5. Estimated Chronic Census Tract Noncancer (Respiratory)Risk from HAP exposure from outdoor sources (2005 NATA).............. ....................................... 7-17 7-6. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline.....................

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.............................. ..........................................7-33 7-9. Net Benefits for CI RICE NESHAP Reconsideration at 7% discount rate......

.............................. ..........................................7-34xi LIST OF TABLES

Number Page

1-1. Summary of the Annualized Monetized Benefits, Social Costs, and Net Benefits for the Reconsidered CI RICE NESHAP in 2013 (millions of 2010$) ....... 1-2 1-2. Comparison of Benefits and Costs for 2020 CI RICE Final Rule and 2012 Reconsideration CI RICE Ru le.................................... ............................1-3 1-3. Summary of the Monetized Benefits, Compliance Costs and Net benefits for the 2010 Rule with the Final Amendments to the Stationary CI Engine NESHAP in 2013 (millions of 2010 dollars).........

.............................. ................................1-9

3-1. Key Statistics: Electric Power Generatio n, Transmission, and Distribution (NAICS 2211) ($2007) ................................................................................................ 3-2 3-2. Direct Requirements for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2007 ............................................................................... 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. Shar eholder-Owned Electric Utilities ............. 3-10 3-6. Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 2211 ..................... 3-10 3-7. Key Enterprise Statistics by Receipt Size for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2007 ............................................... 3-11 3-8. Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): ($2007) ...................................................................................................................... 3-11 3-9. Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) ($2007) ................ 3-12 3-10. Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002 ...................... 3-12 3-11. Key Statistics for Crude Petroleum and Natural Gas Extraction (NAICS 211111): 2007 ............................................................................................................ 3-13 3-12. Key Statistics for Crude Natural Gas Liquid Extraction (NAICS 211112): 2007 .... 3-13 3-13. Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAICS 211 ....................... 3-14 3-14. Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) ($2007) .... 3-15 3-15. Direct Requirements for Pipeline Transportation (NAICS 486): 2002 ..................... 3-17 3-16. Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 486 ....................... 3-19 3-17 Key Enterprise Statistics by Employee Size for Pipeline Transportation of Natural Gas (NAICS 48621): 2007 ........................................................................... 3-20 3-18. Key Statistics: General Medical and Surgical Hospitals (NAICS 6221) ($2007) .... 3-23 3-19. Direct Requirements for Hospitals (NAICS 622): 2002 ........................................... 3-23 3-20. Data for General Medical and Surgical Hospitals (NAICS 6221): 2007 ................. 3-24 3-21. Hospital Statistics: 2010 ............................................................................................ 3-25xii 3-22. Aggregate Tax Data for Accounting Period 7/05

– 6/06: NAICS 622-4 .................... 3-25 3-23. Key Enterprise Statistics by Receipt Size for General Medical and Surgical Hospitals (NAICS 6221): 2007 ($2007) ................................................................... 3-27 3-24. Key Statistics: Farm Machinery and Equipment Manufacturing (NAICS 333111) ($2007) ........................................................................................................ 3-28 3-25. Key Statistics: Welding and Soldering Equipment Manufacturing (NAICS 333992) ($2007) ........................................................................................................ 3-29 3-26. Expenses per Acre by Type of Energy: 2008 ............................................................ 3-30 3-27. Number of On-Farm Pumps of Irrigation Water by Type of Energy: 2003 and 2008 .......................................................................................................................... . 3-30 3-28. Aggregate Tax Data for Accounting Period 7/05–6/06: NAICS 3331 and 3339 ...... 3-31 3-29. Key Enterprise Statistics by Receipt Size for Heavy Construction: 2007 ................ 3-34

4-1. CI RICE Control Technologies and Costs .................................................................. 4-9 4-2. Summary of Major Source and Area Source Costs for the CI RICE NESHAP ........... 23 4-3. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP ....................................................................................................................... 24 4-4. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP – by Size ........................................................................................................ 25 4-5. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP – by Number of Engines ............................................................................... 28 4-6. Summary of Major Source and Area Source Baseline Emissions for the CI RICE NESHAP – 2013 .............................. ................................................4-36 4-7. Summary of Major Source and Area Source Emission Reductions for the CI RICE NESHAP – by 2013 ..........................................................................4-36

5-1. Selected Industry-Level Annualized Compliance Costs as a Fraction of Total Industry Revenue: 2008 ............................................................................................... 5-4 5-2. Hypothetical Price Increases for a 1% Increase in Unit Costs ........................................ 7 5-3. Hypothetical Consumption Decreases for a 1% Increase in Unit Costs ......................... 9 5-4. U.S. Electric Power a Sector Energy Consumption (Quadrillion BTUs): 2013 ............. 12 5-5 Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintain ing Control Equipment Requirements for the Final Reconsideration CI RICE NESHAP........................................................5-16

6-1. Final NESHAP for Existing Stationary Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Business Size Standards ................. 3 6-2. Average Receipts for Affected Industry by Enterprise: 2007 ($2008 Million/establishment) ........

................................................................ ............................. 5 6-3. Average Receipts for Affected Industry by Enterprise Receipt Range: 2007 ($2008 /establishment) .................................................................................................... 6 6-4. Representative Establishment Costs Used for Small Entity Analysis ($2008) ............... 8 Deleted: 4-25

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7-5. Summary of the Monetized Benefits, Compliance Costs and Net benefits for the 2010 Rule with the FinalAmendments to the Stationary CI Engine NESHAP in 2013 (millions of 2010 dollars) a ........................................................... 7-321-7 SECTION 1
EXECUTIVE SUMMARY

ES.1. Summary of Impacts for CI RICE NESHAP Final Reconsideration

The EPA estimates that complying with the reconsideration of the stationary compression ignition (CI) reciprocating internal combustion engine (RICE) rule will have an annualized cost of approximately $372 million per year (2008 dollars) or $373 million per year (2010 dollars) in the year of full implementation of the rule (2013). 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 sa les data obtained for affected small entities in an analysis of the impacts on small entities, EPA expects that the NESHAP will not result in a SISNOSE (significant economic impacts for a substantial number of small entities). 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. All of these analysis results are practically identical to the results for the CI RICE NESHAP when it was promulgated in March
2010.

The RICE rule is also considered subject to the requirements of the Office of Management and Budget’s (OMB’s) Executive Order 12866 because EPA expects that either the annual benefits or the costs are potentially $100 million or higher. EPA estimates the total
monetized co-benefits of the NESHAP to be $770 million to $1.9 b illion (2010$) at a 3% discount rate and $690 million to $1.7 billion at a 7% discount rate in the year of full implementation of the rule (2013). These co-benefit estimates are lower than those for the CI rule promulgated two years ago. The previous co-benefit estimates were $940 million to $2,300 million (2008 dollars) at a 3-percent discount rate and $850 million to $2,100 million (2008 dollars) at a 7-percent discount rate. The previous estimates will be greater in a nominal (not inflation-adjusted) sense if shown in 2010 dollars, and thus the reduction in the benefits for the reconsidered rule compared to the benefits for the 2010 final rule will therefore be greater. Since the reconsideration proposal, we have made several updates to the approach we use to estimate mortality and morbidity benefits in the PM NAAQS RIAs (U.S. EPA, 2012a,b) includingupdated epidemiology studies, health endpoints, and population data. Although we have not reestimated the benefits for this rule to apply th is new approach, these updates generally offset each other, and we anticipate that the rounded benefits estimated for this rule are unlikely to be different than those provided below.1-7 The net benefits of the final CI RICE reconsideration are therefore $400 million to $1.5 billion at a 3% discount rate and $320 million to $1.3 billion at a 7% discount rate (in 2010$) in 2013. These estimates are shown in Table 1-1. EPA believes that the benefits are likely to exceed the annualized costs by a substantial margin under this rulemaking even when taking into
account uncertainties in the cost and benefit estimates

. These estimates are “snapshots” of benefits and costs at year 2013

. Table 1-1. Summary of the Annualized Monetized Benefits, Social Costs, and Net Benefits for the Reconsidered CI RICE NESHAP in 2013 (millions of 2010$) 1

3% Discount Rate 7% Discount Rate

Total Monetized Benefits 2 $770 to $1,900 $690 to $1,700 Total Compliance Costs 3 $373 $373 Net Benefits $400 to $1,500 $320 to $1,300

Non-monetized Benefits Health effects from HAP exposure

Health effects from PM 2.5 exposure from VOC emissions Ecosystem effects Visibility impairment

1 All estimates are for the implementation year (2013), and are rounded to two significant figures.
2 The total monetized benefits reflect the human heal th benefits associated with reducing exposure to PM 2.5 through

reductions of PM 2.5 precursors such as directly emitted fine particle s. Human health benefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These mode ls assume that all fine particles, regardless of their chemical composition, are equally potent in causing prematur e mortality because the scientific evidence is not yet sufficient to allow differentiation of effects estimates by particle type. Although we have not re-estimated the benefits for this rule to apply the updated methods in the PM NAAQS RIA (U.S. EPA, 2012b), these updates generally offset each other, and we anticipate that the r ounded benefits estimated for this rule are unlikely to be different than those provided here.
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 annua lized using a 7 percent discount rate. These costs are $372 million in 2008 dollars. Costs are updated to 201 0 dollars using the Marshall & Swift (M&S) Annual Cost Index. The escalation is done by multiplying the 2008 costs by the ratio of the 2010 annual M&S index value (1,457.4), and the 2008 annual M&S index value (1,449.3).

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

The EPA analyzed the costs, economic impacts and benefits of this final rule using the identical methodology as the RIA for the CI RICE final rule promulgated in May, 2010. Therefore, all changes to the costs, benefits, and economic impacts for this rule are due to changes (or amendments) to this rule for CI RI CE, which are fully descri bed later in this RIA1-7 and the preamble for the final rule. Our baseline does not assume compliance with the 2010 CI RICE final rule. This assumption is based on th e fact that full implementation of the final rule has not taken place as of yet (it will take place by May, 2013). In addition, this assumption is consistent with the baseline definition applied in the recently finalized ICI boilers and CISWI NESHAP rulemakings. Monetized benefits are the co-benefits of this rule from reductions in directly emitted PM 2.5 emissions.

The following table shows an approximation of the changes in monetized benefits and engineering costs due to changes to the CI RICE rule included in the CI RICE reconsideration , and includes values that show a comparison based on the final rule emissions inventory. All
values in Table 1-2 are in 2010 dollars.

Table 1-2. Comparison of Benefits and Costs for 2012 CI RICE Final Rule and 2012 Final Reconsideration CI RICE Rule

Monetized Benefits in 2013 Annual Engineering Costs in 2013 CI RICE Final Rule (May 2010) $0.940 to $2.3 billion $373 million
Changes due to the final amendments to the final CI RICE rule -$0.170 to $0.400 billion -$0.7 million

Final CI RICE rule (2012) +$0.770 to $1.9 billion $372 million
* Monetized benefits are shown at a 3% di scount rate and are from reductions in PM 2.5 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 are essentially unchanged from those for the CI final rule. This outcome is due to the minor changes in compliance costs associated with the
amendments in this final rule. All of these result s for this rule are found in Section 5 in this
RIA.

The results for sales tests (i.e . annual cost/sales analysis) for small businesses are also essentially unchanged from those calcu lated for the final CI RICE rule. This outcome is also due to the overall minor changes in compliance costs. All of these results for this rule are found in
Section 6 in this RIA.

We estimate changes in employment for this CI RICE 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 1,300 full-time equivalents (FTEs) will be required as one-time labor for installation of equipment, and 2,000 FTEs will be required as ongoing labor for compliance with the rule. The results are presented1-7 and explained in detail in Section 5 of this RIA. We did not estimate changes in employment
for the 2010 final CI RICE rule.

The benefits estimates decreased for the final reconsidered CI RICE as compared to the 2010 final CI RICE NESHAP. The range for the 2010 final CI RICE RIA was $940 million (2008$) to $2.3 billion (2008$) at 3 percent discount rate. The range for this rule is $770 million (2010$) to $1.9 billion (2010$) at 3 percent discount rate. The ra nge for the 2010 final SI RICE RIA was $850 million (2008$) to $2.1 billion ( 2008$) at 7 percent discount rate. The range for this final rule was $690 million (2010$) to $1.7 billion (2010$) at 7 percent discount rate.

Table 1-3 shows the estimated costs and benefits for the 2010 final CI Rule and the reconsideration. The estimated net benefits for the reconsideration are smaller than the range for the 2010 final CI RICE rule RIA, which was $480 million to $1.7 billion at a 7 percent discount rate and was $520 million to $1.9 bill ion at 3 percent (in 2010 dollars).

Table 1-3

. Summary of the Monetized Benefits, Comp liance Costs and Net benefits for the 2010 Rule with the Amendments to the Stationa ry CI Engine NESHAP in 2013 (millions of 2010 dollars) a

3% Discount Rate 7% Discount Rate

2010 Final CI RICE NESHAP

Total Monetized Benefits $940 to $2,300 $850 to $2,100

Total Social Costs $373 $373

Net Benefits $520 to $1,900 $480 to $1,700

Reconsideration CI RICE NESHAP

Total Monetized Benefits $770 to $1,900 $690 to $1,700

Total Social Costs $373 $373

Net Benefits $400 to $1,500 $320 to $1,300

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

benefits are from reductions of PM 2.5 emissions, a co-benefits of this rule . The annualized compliance costs are $373 million in 2010$ as noted earlier in this RIA, and ar e annualized using a 7% interest rate. Compliance costs are used as an approximation for social costs in this RIA. Although we have not re-estimated the benefits for this rule to apply the updated methods in the PM NAAQS RI A (U.S. EPA, 2012b), these updates generally offset each other, and we anticipate that the rounded benefits estimate d for this rule are unlikely to be different than those provided here.3-7 SECTION 2
INTRODUCTION

EPA has reconsidered national emission standards for hazardous air pollutants (NESHAP) for existing stationary compression ign ition (CI) reciprocating internal combustion engines (RICE) that either are located at area sources of hazardous air po llutant (HAP) emissions or that have a site rating of less than or equal to 500 brake horsepower (HP) and are located at major sources of HAP The final amendments to th e CI 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. Finall y, 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 CI RICE NESHAP promulgated in March 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 the final amendments to the proposed rule, and provides the compliance costs and emission reductions estimated for the rule.

 Section 5 describes the estimated costs of the regulation and describes the 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.3-7 SECTION 3
INDUSTRY PROFILE

Stationary CI engines almost always oper ate as lean burn engines. They can be configured as either two-stroke lean burn (2SLB) or 4-stroke lean burn (4SLB); the distinction is that CI engines are fueled by distillate fuel o il (diesel fuel), not by natural gas or any other gaseous fuel. Industries in which st ationary CI engines are found are:

 electric power generation, transmissi on, and distribution (NAICS 2211),

 oil and gas extraction (including marginal wells) (NAICS 211111),

 pipeline transportation of natural gas (NAICS 211112),

 general medical and surgical hospitals (NAICS 622110), and

 irrigation sets and welding equipment (NAICS 335312 and 333992).

This section provides an introduction to the i ndustries affected by the final reconsidered rule. The purpose 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, a nd distribution (NAICS 2211) is an industry group within the utilities sector (NAICS 22). It includes establishments that produce electrical energy or facilitate its transmi ssion to the final consumer.

From 2002 to 2007, revenues from electric power grew about 18% to over $440 billion ($2007) (Table 3-1). At the same time, payroll rose about 7.6% and the number of employees decreased by over 6%. The number of establishments rose by a little more than 2%, resulting in a increase in average establishment revenue of almost 24%. Industrial production within NAICS 2211 has increased 25% 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. Foll owing market manipulati on in the early 2000s,3-7 however, several states have suspended their restru cturing efforts. The majority (58%) of diesel power generators controlled by combined heat and power (CHP) or independent power producers are located in states undergoi ng active restructuring (Figure 3-2).

Table 3-1. Key Statistics: Electric Power Generation, Transmission, and Distribution (NAICS 2211) ($2007)

2002 2007 Revenue ($10 6 ) 373,309 440,342 Payroll ($10 6 ) 40,842 43,266 Employees 535,675 503,134
Establishments 9,394 9,611 Source: U.S. Census Bureau; Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the United States, All Indust ries: 2007. Statistics for U.S. Businesses. Found at http://www.census.gov/econ/susb/data/susb2007.html

.3-7 Figure 3-1. Industrial Production Index (NAICS 2211)

Source: The Federal Reserve Board. “Industrial Producti on 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 80 85 90 95 100 105 110 1151997‐011997‐061997‐111998‐041998‐091999‐021999‐071999‐122000‐052000‐102001‐032001‐082002‐012002‐062002‐112003‐042003‐092004‐022004‐072004‐122005‐052005‐102006‐032006‐082007‐012007‐062007‐112008‐042008‐092009‐022009‐072009‐12IndexValue(Jan2002=100)3-7 Figure 3-2. Internal Combustion Generators by State: 2006
Source: U.S. Department of Energy, Energy Informati on Administration. 2007. “2006 EIA-906/920 Monthly Time

Series.”

power generation. Extraction, transportation, refining, and equipment requirements potentially associated with reciprocating internal combustion engines (oil and gas extraction, pipeline transportation, petroleum refineries, and turb ine 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 economi c variables by industry, location, and size of business. Throughout this section and repo rt, we use the following definitions:

 Establishmen t: An establishment is a single physical location where business is conducted or where services or in dustrial operations are performed. Diesel and Natural Gas Internal Combustion Generators By State

No Restructuring Suspended Restructuring
Active Restructuring

100

50

10

13-7 Table 3-2. Direct Requirements for Electri c Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Commodity Description Direct Requirements Coefficients a
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 Accoun ts: 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, divi dends, 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 commonownership 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.

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.3-7 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 Internati onal; 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 67.5% of retail electricity sold in the United States in 2006 (Table 3-4). In 2010, le ss regulated investor-owned electric utility companies were on average more profitable than companies with greater regulation (Table 3-5). In 2006, enterprises within NAICS 2211 had a pre-tax profit margin of only 0.9% (Table 3-6).

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 Establishments by State

Less than 100

100 - 199

200 - 349

350 - 500

More than 5003-7 Table 3-3. Firm Concentration for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Establishments Receipts/Revenue

Number of Employees Employees per Establishment Amount ($10 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; generate d 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).

through such activities as explor ing for oil and gas, drilling an d 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 in dustries: 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 2007, it accounted for 93% of establishments and 75% of oil and gas extraction revenues.

Industrial production in this industry is partic ularly sensitive to hurricanes in the Gulf Coast. In September of both 2005 and 2008, production dropped 14% from the previous month.

From 2002 to 2007, revenues from crude petroleum and natural gas extraction (NAICS 211111) nearly doubled to $194 billion ($2007) (Table 3-8). At the same time, payroll increased 55% and the number of employees dropped by almost 40%. The number of establishments increased only slightly (1%); as a result, the average establishment revenue nearly doubled%.

From 2002 to 2007, revenue from natural gas liquid extraction (NAICS 211112) grew over 19% to about $40 billion (Table 3-9). At th e same time, payroll increased by only 1% and the number of employees dropped by almost 14%. The number of establishments dropped by over 59%, resulting in an increase of revenue per establishment of about 85%.

### 3-9Table 3-4. United States Retail Electricity Sales Statistics: 2008Full-Service ProvidersOther ProvidersItem Investor-OwnedPublicFederalCooperativeFacilityEnergyDeliveryTotalNumber of entities362 1 25 1 NA NA92Number of retail customers46,985 2,160,220 36 940,697 1 NA NA 3,147,939Retail sales (103megawatthours) 2,25770,303 9,625 21,868 117 NA NA 104,170Percentage of retail sales267 9 21 0 — —100Revenue from retail sales ($106) 1135,934 473 1,994 6 NA NA 8,520Percentage of revenue1.3369.65 5.55 23.41 0.07 — —100Average retail price (cents/kWh) 5.018.44 4.91 9.12 5.25 NA NA8.18Source: 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>.3-10 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

Regulated a 6.80% $12,341 $158,657
Mostly regulated b 8.50% $17,815 $175,218

Diversified c -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 enterprises a 1,187
Total receipts (10 3 ) $323,522,443
Net sales(10 3 ) $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).

3.2.2 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 reciprocating internal combustion engines (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).3-11 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 in dustrial operations are performed.

### 3-12Table 3-7. Key Enterprise Statistics byEmployee Size for Electric Power Generation, Transmission, and Distribution (NAICS2211): 2007Variable All Enterprises<20Employees20–99Employee s100–499Employees500+EmployeesFirms 1,687 630 670 251 136Establishments 9,611 687 1,110 999 6,815Employment 503,1343,622 31,455 42,527425,530Receipts ($103) $440,342,284 $8,364,773 $21,825,969 $41,370,375 $368,781,167Receipts/firm ($103) $261,021 $13,277 $32,576 $164,822 $2,711,626Receipts/establishment($103)$45,817 $12,176 $19,663 $41,412 $54,113Receipts/employment($) $875 $2,309 $694 $973 $867Source: 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>.3-13 Figure 3-4. Industrial Production Index (NAICS 211)

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

ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G211.S <h ttp://www.federalreserve.gov/datadownload/>. (January 27, 2010).
Table 3-8. Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): ($2007)

2002 2007
Revenue ($10 6 ) 98,667 194,107
Payroll ($10 6 ) 5,785 8,988
Employees 94,886 133,286
Establishments 7,178 7,221

Source: U.S. Census Bureau; Factfinder Series: “2002 and 2007.” <http:// factfinder.census.gov>; (February 23, 2012).

 Receipts : Receipts (net of taxes) are defined as the revenue for goods produced, distributed, or services provided, in cluding revenue earned from premiums, commissions and fees, rents, interest, divi dends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes. 75 80 85 90 95 100 105 1101997‐011997‐061997‐111998‐041998‐091999‐021999‐071999‐122000‐052000‐102001‐032001‐082002‐012002‐062002‐112003‐042003‐092004‐022004‐072004‐122005‐052005‐102006‐032006‐082007‐012007‐062007‐112008‐042008‐092009‐022009‐072009‐12IndexValue(Jan2002=100)3-14  Firm : A firm is a business organization consisting of one or more domestic establishments in the same state and industry that were specified under commonownership or control. The firm and the establishment are the same for singleTable 3-9. Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) ($2007)

2002 2007 Revenue ($10 6 ) 33,579 39,978 Payroll ($10 6 ) 607 617 Employees 9,693 8,523

Establishments 511 321

Source: U.S. Census Bureau; 2002 and 2007.” <h ttp://factfinder.census.gov>; (February 23, 2012).
Table 3-10. Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002

Commodity Commodity Description Direct Requirements Coefficients a
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 Accoun ts: Detailed Make Table,

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

establishment 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 size3-15 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 NAICS 211111 generate d $194 billion in total receipts in 2007. Enterprises within NAICS 211112 generated nearly $40 billion in total receipts in 2007. Including those enterprises without net income, NAICS 211 averaged an after-tax profit margin of 8.5% in 2008 (Table 3-13).

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 Si ze 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-discl osure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Nu mber 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/>3-16 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 Em p lo y ment b y 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 Si ze 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-discl osure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Nu mber 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 3-13. Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAICS 211

Number of enterprises a 19,441
Total receipts (10 3 ) $193,230,241
Net sales(10 3 ) $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 pipeline3-17 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 10% to just under $21 billion ($2007) (Table 3-15). At the same time, payroll decreased by 18% , while the number of paid employees decreased by nearly 32%. The number of establishments decreased by 13% from 1,701 establishments in 2002 to 1,479 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 transporta tion 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 68% of NAICS 486 establishments and 72% of revenues (Figures 3-5 and 3-6).
Table 3-14. Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) ($2007)

Year 2002 2007 Revenue ($10 6 ) 22,964 20,797 Payroll ($10 6 ) 2,438 2,064 Employees 32,542 24,683

Establishments 1,701 1,479

Source: U.S. Census Bureau; generated by RTI Interna tional; 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).

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 require ments represent significant share of the cost associated with pipeline transportation. Power a nd equipment requirements potentially associated with reciprocating internal combustion engines (electric power generation and commercial and industrial machinery and equipment repair and main tenance) represent less than 2% of the value
of services.3-18 Figure 3-5. 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>; (December 12, 2008).

Figure 3-6. 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>; (December 12, 2008). 68%

21%
11%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

4862 Pipeline Transportation of Natural Gas 4869 Other Pipeline Transportation 4861 Pipeline Transportation of Crude Oil

72%

16% 12%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

4862 Pipeline Transportation of Natural Gas 4869 Other Pipeline Transportation 4861 Pipeline Transportation of Crude Oil3-19 Table 3-15. Direct Requirements for Pipeline Transportation (NAICS 486): 2002

Commodity Commodity Description Direct Requirements Coefficients a
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 Accoun ts: Detailed Make Table,

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

According to 2007 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 3-7).

Enterprises within pipeline transportation (NAICS 486) generated $11.1 billion in totalreceipts in 2007. Including those enterprises without net income, the industry averaged an aftertax profit margin of 9.6% (Table 3-16).

The 2007 SUSB shows that about half of all firms have fewer than 20 employees, but only 1% of all employees in this industry. Firms with more than 500 employees generate 89% of all receipts in this industry (Table 3-17).3-20 Figure 3-7. 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>; (D ecember 12, 2008).

Table 3-16. Aggregate Tax Data for A ccounting Period 7/07–6/08: NAICS 486

Number of enterprises a 321

Total receipts (10 3 ) $11,062,608

Net sales (10 3 ) $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). 86%

8% 6%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Corporations Individual Proprietorships Partnerships3-21 Table 3-17. 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 ($10 3 ) $20,796,681 N/A $518,341 $1,448,020 $18,498,143 Receipts/firm ($10 3 ) $165,053 N/A $43,195 $160,891 $440,432 Receipts/establishment ($10 3 ) $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.

3.4 General Medical and Surgical Hospitals

3.4.1 Overview
General medical and surgical hospitals (NAICS 6221) is an industry group within the health care and social assistance sector (NAICS 62). It includes hospitals engaged in diagnostic and medical treatment (both surgical and nonsurgical) for inpatients with a broad range of medical conditions. They usually provide other services as well, including outpatient care, anatomical pathology, diagnostic X-rays, clini cal laboratory work, and pharmacy services.

From 2002 to 2007, hospital revenues grew about 21% to over $650 billion ($2007) (Table 3-18). At the same time, payroll ro se about 15%, while the number of employees increased by only 6%. The number of establishments increased during this period by almost 4%, resulting in an increase in revenue per establishment of almost 16%.

3.4.2 Goods and Services Used
The BEA reports hospital expenditures only for hospitals (3-digit NAICS 622). In addition to general hospitals (NAICS 6221), this industry includes psychiatric and substance abuse hospitals (NAICS 6222) and specialty hospitals (NAICS 6223). However, these data3-22 should be representative of the affected sect or since in 2007, general medical and surgical hospitals accounted for 92% of NAICS 622 establishments and 94% of revenues.

In Table 3-19, we use the latest detailed benchmark input-output data report by the BEA (2002) to identify the goods and services used by hospitals (NAICS 622). As shown, labor and land requirements represent a significant share of the value of hospital services. Power and equipment requirements potentially associated with reciprocating internal combustion engines (electric power generation and commercial and industrial machinery and equipment repair and maintenance) represent less than 2% of the value of services.3-23 Table 3-18. Key Statistics: General Medical and Surgical Hospitals (NAICS 6221) ($2007)

2002 2007
Revenue ($10 6 ) 539,502 651,639
Payroll ($10 6 ) 209,063 240,638
Employees 4,772,422 5,042
Establishments 5,193 5,404

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 62: Health Care

and Social Assistance: Geographic Area Series: 2002 and 2007.” <http://factfinder.census.gov>; (February 22, 2012).

Table 3-19. Direct Requirements for Hospitals (NAICS 622): 2002

Commodity Commodity Description Direct Requirements Coefficients a

V00100 Compensation of employees 51.90%

531000 Real estate 10.76%
550000 Management of companies and enterprises 4.02%
621B00 Medical and diagnostic labs a nd outpatient and other ambulatory care services 2.22%

561300 Employment services 1.90%
325412 Pharmaceutical preparation manufacturing 1.86%
325413 In-vitro diagnostic substance manufacturing 1.66%

524100 Insurance carriers 1.66%

420000 Wholesale trade 1.62%
221100 Electric power generation, transmission, and distribution 1.14%

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 Accoun ts: Detailed Make Table,

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

3.4.3 Business Statistics
In 2010, the United States had 5,754 hospitals (Table 3-20). As shown in Table 3-1, nongovernmental not-for-profit hospitals accounted for 2,904 (or 50%) of these hospitals, and State and local government hospitals accounted for 1,068 (or 19%) of these hospitals.3-24 General medical and surgical hospitals (NAICS 6221) generated $652 billion in totalreceipts in 2007. Including those enterprises without net income, the industry averaged an aftertax profit margin of 3.1% (Table 3-22). Also, each firm in this industry had an average of about $202 million in revenue and a great majority of these firms had more than 500 employees in 2007 (Table 3-23).

Figure 3-8. Share of Establishments by Legal Form of Organization in the General Medical and Surgical Hospitals Industry (NAICS 6221): 2002
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 62: Health Care

and Social Assistance: Subject Series—Estab & Firm Size: Legal Form of Organization for the United States: 2002” <http://factfinder.census.gov>; (November 21, 2008).

Table 3-20. Data for General Medical and Surgical Hospitals (NAICS 6221): 2007

Commodity Establishments Amount ($10 6 ) Number of Employees Employees per Establishment

All firms 5,404 $651,639 5,041,848 933

Source: U.S. Census Bureau, 2011; Statistics for U.S. Businesses (SUSB), 2007. 79.6%

19.5%

0.7% 0.1% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Corporations Partnerships Individual Proprietorships Other Legal Forms of Organization3-25 Table 3-21. Hospital Statistics: 2010

Hospitals Number
Total 5,754
Nongovernment not-forprofit 2,904
Investor-owned (for-profit) 1,013
State and local government 1,068
Federal government 213

NA = Not available Source: American Hospital Association. 2011. “AHA Ho spital Statistics: 2010 Edition.” Health Forum.

Table 3-22. Aggregate Tax Data for Accounting Period 7/05

– 6/06: NAICS 622-4

Number of enterprises a 18,263
Total receipts (10 3 ) $108,074,793
Net sales(10 3 ) $102,300,229
Profit margin before tax 4.4%
Profit margin after tax 3.1%

a Includes corporations with and without net income. Source: Troy, Leo. 2008. “Almanac of Business and Industrial Financial Ratios: 2009 Edition.” CCH.
Table 3-23. Key Enterprise Statistics by Employee Size for General Medical and Surgical Hospitals (NAICS 6221): 2007 ($2007)

Variable All Enterprises <20 Employees 20-99 Employees 100-499 Employees 500+ Employees
Firms 3,225 170 277 1,227 1,551
Establishments 5,404 173 282 1,286 3,663 Employment 5,041,848 606 18,718 294,247 4,728,277 Receipts ($10 3 ) $651,639,328 346.216 1,553,004 $27,889,532 $621,850,576 Receipts/firm ($10 3 ) $202,059 2,037 5,607 $22,730 $400,935 Receipts/establishment ($10 3 ) $120,585 2,001 5,508 $21,687 $169,766

Receipts/employment ($) $129 $571 $83 $95 $132

Source: U.S. Small Business Administration (SBA). 2010. “F irm 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>.3-26 3.5 Irrigation Sets and Welding Equipment

3.5.1 Overview
The U.S. Economic Census classifies irriga tion equipment under the farm machinery and equipment manufacturing industry group (NAICS 333111). This U.S. industry comprises establishments primarily engaged in manufacturing agricultural and farm machinery andequipment and other turf and grounds care equipment, including planting, harvesting, and grassmowing equipment (except lawn and garden type).

From 2002 to 2007, farm machinery and equipment manufacturing revenues increased by $8 billion from $15 billion to $23 billion (Table 3- 24). At the same time, payroll increased by 21% and the number of paid employees increased by nearly 9%. The number of establishments dropped by 2% from 1,214 establishments in 2002 to 1,191 in 2007. Industrial production in the industry has been increasing since 1997 (Figure 3-9).

The U.S. Economic Census classifies welding equipment under the welding and soldering equipment manufacturing industry group (NAICS 333992). This U.S. industry comprises establishments primarily engaged in manufacturing welding and soldering equipment and accessories (except transformers), such as welding electrodes, welding wire, and soldering equipment (except handheld).

From 2002 to 2007 welding and soldering equipment manufacturing revenue increased by about 53% to nearly $6 billion (Table 3-25). At the same time, payroll increased by 12% and the number of paid employees increased by nearly 9%. The number of establishments increased by 31% from 250 establishments in 2002 to 303 in 2007.

3.5.2 Irrigation and Welding Services
The demand for equipment is derived from the demand for the services the equipment provides. We describe uses and indust rial consumers of this equipment.

3.5.2.1 Irrigation
Demand for irrigation equipment is driven by farm operation decisions, optimal replacement considerations, and climate and weather conditions. The National Agriculture Statistics Service (NASS) 2008 Farm and Ranch Irrigation Survey (USDA-NASS, 2010) shows3-27 Table 3-24. Key Statistics: Farm Machinery and Equipment Manufacturing (NAICS 333111) ($2007)

2002 2007
Revenue ($10 6 ) $15,006 $23,009
Payroll ($10 6 ) $2,132 $2,580
Employees 53,817 58,838
Establishments 1,214 1,191

Source: U.S. Census Bureau, Statistics of U.S. Business (SUSB), 2007.

Figure 3-9. Industrial Production Index (NAICS 333111) 40 50 60 70 80 90 100 110 120 130Index Values (Jan-97=100) Industrial Production Index (NAICS 333111)3-28 Table 3-25. Key Statistics: Welding and Soldering Equipment Manufacturing (NAICS 333992) ($2007)

2002 2007
Revenue ($10 6 ) $3,880 $5,935
Payroll ($10 6 ) $811 $910
Employees 16,128 17,529

Establishments 231 303

Source: U.S. Census Bureau; using American FactFinder; “Sector 31: Manufacturing: Industry Series: Historical

Statistics for the Industry: 2002 and 2007” <http://factfinder.census.gov>; (February 15, 2012).
that the top five states ranked by total acres ir rigated are Nebraska, California, Texas, Arkansas, and Idaho. Virtually all of the irrigated areas in the U.S. are west of the Mississippi River.

The survey reported that approximately 546,000 pumps were used on U.S. farms in 2008 with energy expenses totaling approximately $2.7 billion. Electricity is the dominant form of energy expense for irrigation pumps, accounting for 59 % of total energy expenses. Diesel fuel is second (25%), followed by natural gas (17%) and other forms of energy such as gasoline (2%).

Per-acre operating costs for these irrigation sy stems vary by fuel type, and natural gas was the most expensive in 2008 ($93 per acre for well systems and $44 per acre for surface water systems) (Table 3-26). Systems using diesel fuel were operated at approximately half of these per-acre costs ($54 per acre for well systems and $42 per acre for surface water systems). Gasoline- and gasohol-powered systems offered the least expensive operating costs for well systems ($39 per acre) and electricity-power sy stems offered the least expensive operating costs for surface water systems ($45 per acre). As shown in Table 3-27, the number of on-farm pumps increased to 546,308 from 489,434 (12%) between 2003 and 2008. The use of electric- and diesel-powered pumps increased during this peri od (21% and 3%, respectively), while other fuel sources such as liquid petroleum (LP) gas, propane, and butane declined significantly (31%). Itshould be noted that the acreages included in Table 3-27 incorporate both irrigated and nonirrigated land.3-29 Table 3-26. Expenses per Acre by Type of Energy: 2008

Fuel Type Irrigated by Water from Wells Irrigated by Surface Water Electricity $57.80 $35.07
Natural gas $93.03 $43.85
LP gas, propane, butane $38.72 $45.40

Diesel fuel $54.20 $41.94

Gasoline and gasohol $84.98 $39.24

Total $60.90 $36.13

Source: U.S. Department of Agriculture, National Agri cultural Statistics Service. 2010. “2008 Farm and Ranch

Irrigation Survey.” Washington, DC: USDA-NA SS. Table 20. Found on the Internet at http://www.agcensus.usda.gov/Publications/2007/On line_Highlights/Farm_and_Ra nch_Irrigation_Survey/fris08_ 1_20.pdf

.

Table 3-27. Number of On-Farm Pumps of Irrigation Water by Type of Energy: 2003 and 2008

Fuel Type 2003 2008 Percentage Change
Electricity 312,145 377,492 21% Natural gas 41,768 36,176 –13% LP gas, propane, butane 17,786 12,203 –31%

Diesel fuel 112,133 115,249 3% Gasoline and gasohol 5,602 5,188 –7%
Total 489,434 546,308 12%

Source: U.S. Department of Agriculture, National Agricu ltural Statistics Service. 2010. “2008 Farm and Ranch

Irrigation Survey.” Washington, DC: USDA-NA SS. Table 20. Found on the Internet at http://www.agcensus.usda.gov/Publications/2007/On line_Highlights/Farm_and_Ra nch_Irrigation_Survey/fris08_ 1_20.pdf

No information is available on the use and construction of on-farm pumps specifically. USDA reports that planted acres of the eight major crops hit a 5-year high of 252 million acres in 2008 but will fall and level off to around 244 million acres over the next 2 to 4 years (USDA, 2008).

3.5.2.2 Welding
Welding is used in a wide variety of applications. One of the biggest manufacturers of welding products identifies the following key end-user segments:

 general metal fabrication;3-30  infrastructure including oil and gas pipelines and platforms, buildings, bridges, and power generation;

 transportation and defense industries (autom otive, trucks, rail, ships, and aerospace);

 equipment manufacturers in construction, farming, and mining;

 retail resellers; and

 rental market (Lincoln Electric Holdings, 2006).

Lincoln Electric further describes the following key applications: power generation and process industries, offshore production of oil and gas, pipelines/pipemills, and heavy fabrication (earthmoving and construction equipment and agricultural and farm equipment.

3.5.3 Business Statistics
Enterprises within agriculture, construc tion, and mining machinery manufacturing (NAICS 3331) generated $88 billion of total receipts in 2007, while those in other general purpose machinery manufacturing (NAICS 3339) ge nerated $85.7 billion. The average after-tax profit margin in these two industries was 6.9% and 4.7%, respectively (Table 3-28).

Table 3-28. Aggregate Tax Data for Account ing Period 7/05–6/06: NAICS 3331 and 3339

Agriculture, Construction, & Mining Machinery Manufacturing Other General Purpose Machinery Manufacturing
Number of enterprises a 3,064 6,231
Total receipts (10 3 ) $88,255,496 $85,653,046

Profit margin before tax 9.1% 6.1%
Profit Margin after tax 6.9% 4.7%

a Includes corporations with and without net income. Source: Troy, Leo. 2008. “Almanac of Business and Industrial Financial Ratios: 2009 Edition.” CCH.

As noted earlier, welding equipment is used in heavy fabrication such as earthmoving and construction equipment. We focus on the size di stribution for a representative sector in this section (NAICS 237, Heavy and Civil Engineering Construction); other subsections in Section 3 cover other sectors that potentially use equipment powered by diesel engines (e.g., power generation and offshore gas distribution). As show n in Table 3-29, SUSB data suggest that more than 80% of firms are below the Small Business Administration (SBA) small business size3-31 standard for this industry. However, it is not clear what fraction of these firms use stationary diesel engines.32 Table 3-29. Key Enterprise Statistics by Receipt Size for Heavy Construction: 2007 a

Variable All Enterprises <20 Employees 20–99 Employees 100–499 Employees 500+
Firms 49,228 40,654 6,793 1,422 359
Establishments 51,421 40,670 6,947 1,847 1,987 Employment 1,016,407 183,487 273,867 238,342 320,711 Receipts ($10 3 ) $263,941,774 $46,766,241 $68,078,765 $69,190,739 $79,906,029 Receipts/firm ($10 3 ) $5,362 $1,150 $10,022 $48,657 $222,579 Receipts/establishment ($10 3 ) $5,133 $1,150 $9,800 $37,461 $40,214

Receipts/employment ($) $260 $255 $249 $290 $249

a 2007 SUSB. The most comparable 2007 NAICS code for this industry is 237.

Source: U.S. Census Bureau. 2012b. Firm Size Data from th e Statistics of U.S. Businesses, U.S. All Industries

Tabulated by Receipt 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 final reconsidered rule, the costs associat ed 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 the chapter are in 2008$. Costs in 2010$ shown in other parts of the RIA are updated values of these 2008$. Although the estimates presented are annualized, they should be understood as a “snaps hot” in analyzing costs. Annualized costs are estimated as equal for each year that control equipment is operated.

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 finalizing amendments to NESHAP for stationa ry RICE signed in March 2010 for CI engines and August 2010 for SI engines under section 112 of the Clean Air Act. This final rule 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. The EPA is also finalizing revisions to 40 CFR part 60, subparts IIII and JJJJ for consistency with the RICE NESHAP and to make minor corrections and clarifications. The current regulation applies to owners and operators of existing and new stationary RICE at major and area sources of HAP emissions. The applicabilit y of the CI rule remains the same and is not changed by this final rule. The EPA is also finalizing amendments to the NSPS for stationary engines to conform with certain amendments finalized for the RICE NESHAP.

Certain stationary RICE are maintained in order to be able to respond to emergency power needs. This action finalizes limitati ons on the operation of emergency engines for emergency demand response programs. The final rule limits operation of stationary emergency RICE as part of an emergency demand response program to within the 100 hours per year that were already permitted for maintenance and testing of the engines. The limitation of 100 hours per year ensures that a sufficient number of hours are available for engines to meet regional transmission organization and independent system operator tariffs and other requirements for participating in various emergenc y demand response programs and will assist in stabilizing the4-2 grid during periods of instability, preventing elec trical blackouts and su pporting lo cal electric system reliability. The final rule also limits oper ation of certain emergency engines used to avert potential voltage collapse or line overloads that c ould lead to the interrupt ion of power supply in a local area or region to 50 hours per year; this operation counts as part of the 100 hours of year permitted for maintenance and testing of the engine . This rule also establishes fuel and reporting requirements for emergency engines larger than 100 horsepower (HP) used for this purpose or used (or contractually obligated to be available) for more than 15 hours of emergency demand response per calendar year.

To address how certain existing compression ignition (CI) engines are currently regulated, the EPA is specifying that any existing CI engine above 300 HP at an area source of HAP emissions that was certified to meet the Tier 3 engine standards and was installed before June 12, 2006, is in compliance with the NESHAP . This provision creates regulatory consistency between the same engines installed before and after June 12, 2006. Engines at area sources of HAP for which construction commenced before June 12, 2006, are considered existing engines
under the NESHAP.

The EPA is finalizing amendments to the requi rements for existing stationary Tier 1 and Tier 2 certified CI engines located at area sources that are subject to state and locally enforceable requirements requiring replacement of the engine by June 1, 2018. This addresses a specific concern regarding the interaction of the NESHAP with certain rules for agricultural engines in the San Joaquin Valley in California. The EPA is allowing these engines to meet management practices under the RICE NESHAP from the May 3, 2013, compliance date until January 1, 2015, or 12 years after installation date, but not later than June 1, 2018. This provision addresses concerns about requiring owners and operators to install controls on their engines in order to meet the RICE NESHAP, and then having to replace their engines shortly thereafter due to state and local rules specifying the replacement of engines. Owners and operators will have additional time to replace their engines without having to install controls, but are required to use management practices during that period.

Another change the EPA is making is to broaden the definition of remote area sources in Alaska in the RICE NESHAP. Previously, remote areas were considered those that are not on the Federal Aid Highway System (FAHS). This change permits existing stationary CI engines at other remote area sources in Alaska to meet management practices rather than numerical emission standards likely to require aftertreatment. These remote areas have the same challenges as areas not on the FAHS, and complying with the current rule would similarly be prohibitively costly and potentially infeasible. In addition to area sources located in areas of Alaska that are4-3 not accessible by the FAHS being defined as remote and subject to management practices, any stationary RICE in Alaska meeting all of the following conditions are subject to management practices:

(1) The only connection to the FAHS is through the Alaska Marine Highway System, or the stationary RICE operation is within an isolat ed grid in Alaska that is not connected to the statewide electrical grid referred to as the Alaska Railbelt Grid, and

(2) At least 10 percent of the power generated by the stationary RICE on an annual basis is used for residential purposes, and

(3) The generating capacity of the area source is less than 12 megawatts (MW), or the stationary RICE is used exclusively for backup power for renewable energy.

The last significant change the EPA is finalizing is to require compliance with management practices rather than numeric emission limits in the RICE NESHAP for existing CI RICE on offshore drilling vessels on the Outer Continental Shelf (OCS) that become subject to the RICE NESHAP as a result of the operation of the OCS regulations (40 CFR part 55). The final amendments specify that owners and operato rs of existing non-emergency CI RICE with a site rating greater than 300 HP on offshore drilling vessels on the OCS are required to change the oil every 1,000 hours of operation or annually, whichever occurs first; inspect and clean air filters every 750 hours of operation or annually and replace as necessary; insp ect fuel filters and belts, if installed, every 750 hours of operation or annually and replace as necessary; and inspect all flexible hoses every 1,000 hours of operation or annually and replace as necessary. Owners and operators can elect to use an oil analysis program to extend the oil change requirement.

EPA has taken several actions over the past several years to reduce exhaust pollutants from stationary diesel engines, but believes that further reducing exhaust pollutants from stationary diesel engines, particularly existing stationary diesel engines that have not been subject to federal standards, is justified. Therefore, EPA is issuing this rulemaking that reconsiders the 2010 final rule requiring emissions reductions from existing stationary diesel engines. The full preamble for the final CI RICE NESHAP and the rule itself can be reviewed at http://www.epa.gov/ttn/atw/rice/fr03mr10.pdf

.4-4 4.2 Summary of the Final Reconsideration Rule

4.2.1. Emergency Demand Response.

The EPA proposed to limit operation of emergency stationary RICE as part of an emergency demand response program to within the 100 hours per year that is already permitted for maintenance and testing of the engines. The EPA proposed that owners and operators of stationary emergency engines could operate the engines for emergency demand response when the Reliability Coordinator, or other authori zed entity as determined by the ReliabilityCoordinator, has declared an EEA Level 2 as defined in the NERC Reliability Standard EOP002-3, Capacity and Energy Emergencies, plus during periods where there is a deviation of voltage or frequency of 5 percent or more below standard voltage or frequency. After considering public comments received on the proposed rule, the EPA is finalizing the proposed amendment to limit operation for maintenance and testing and emergency demand response to no more than 100 hours per year.

The EPA received some comments in support of the provision for emergency demand response operation, while other commenters opposed the limitation. The commenters who supported the provision noted that the engines are rarely called for emergency demand response, and that the EPA has limited the emergency demand response operation to emergency situations
where a blackout is imminent. The commenters also noted that the public health impacts created by a widespread power outage outweigh the air quality impacts from the engines. The EPA agrees with the commenters that it is appropriate to include a provision for operation of emergency engines for a limited number of hours per year as part of emergency demand response programs to help prevent grid failure or blackouts. Preventing stationary emergency engines from being able to qualify and participate in emergency demand response programs without having to apply aftertreatment could forc e owners and operators to remove their engines from these programs, which could impair the ability of regional transmission organizations and independent system operators to use these relatively small, quick-starting and reliable sources of energy to protect the reli ability of their systems.

The commenters who opposed the provision for demand response provided no significant argument that the conditions under which these engines would be permitted to operate for emergency demand response would not be emergency conditions. Deleted:

.4-5 Commenters who opposed the provision were concerned about the air quality and health impacts of emissions from stationary engines. The commenters were concerned that recent actions by the Federal Energy Regulatory Commission (FERC) that impact demand response compensation in organized wholesale energy mark ets will greatly increase the amount of demand response participating in organized wholesale capacity markets. In response to the commenters, the EPA notes that, prior to the 2013 compliance dates for existing engines, there are no limitations on the hours of operation for those engines. The standards that go into effect in 2013 will for the first time establish requirements fo r these engines, including limitations on their hours of operation in certain situations such as emergency demand response, and ULSD fuel requirements which will reduce HAP emission s from the engines. Regarding the FERC regulations and their effect on use of demand response in capacity markets, these are comments more appropriately directed towards the FERC. As noted above, the emergency demand response situations during which the emergency engines may be used for a limited number of hours per year are appropriately considered emergency situations.

Commenters were also concerned that these engines would be called to operate for demand response on high ozone days, further contributing to nonattainment with ozone standards. However, other commenters noted that emergency demand response events do not predominantly occur on ozone exceedance days. These commenters also note that some of the commenters opposing use of emergency engi nes during emergency demand response would benefit by such a limitation because other emission sources may be used instead of the emergency engines, including sources that some of these commenters may operate, and that the effect on total emissions of using these alternat ive emission sources is not clear. Concerns aboutcontribution to ozone nonattainment by stationary engines can be addressed through areaspecific requirements such as state-based State Implementation Plans that would be directed towards ozone nonattainment areas. More detail regarding the public comments and the EPA’s responses can be found in the Response to Public Comments document available in the rulemaking docket.

As mentioned in the previous paragraph, in response to the concerns about the air quality impact of emissions from emergency engines operating in emergency demand response programs, and based on public comments received on the proposed rule, the EPA is finalizing a requirement for owners and operators of existing emergency CI stationary RICE with a site rating of more than 100 brake HP and a displacement of less than 30 liters per cylinder that use diesel fuel and operate or are contractually oblig ated to be available for more than 15 hours per year (up to a maximum of 100 hours per year) for emergency demand response to use diesel fuel4-6 that meets the requirements in 40 CFR 80.510(b) for nonroad diesel fuel. This fuel requirement also applies to owners and operators of new emer gency CI stationary RICE with a site rating of more than 500 brake HP with a displacement of less than 30 liters per cylinder located at a major source of HAP that use diesel fuel and operate or are contractually obligated to be available for more than 15 hours per year (up to a maximum of 100 hours per year) for emergency demand response. Owners and operators must begin meeting this ULSD fuel requirement on January 1, 2015, except that any existing diesel fuel purchased (or otherwise obtained) prior to January 1, 2015, may be used until depleted. As noted by commenters on the proposed amendments and as discussed in section II.B, requiring the use of diesel fuel meeting the requirements of 40 CFR 80.510(b) is expected to reduce the HAP emissions significantly from the engines compared to emissions resulting from use of unregulated diesel fuel. The fuel requirement begins on January 1, 2015, in order to give affected sources appropriate lead time to institute these new requirements and make any physical adjustment s to engines and other facilities like tanks or containment structures, as well as any needed adjustments to contracts and other business activities, that may be necessitated by these new requirements.

The final amendments also require owners and operators of emergency stationary RICE larger than 100 HP that operate or are contractually obligated to be available for more than 15 hours per year (up to a maximum of 100 hours per year) for emergency demand response to submit an annual report to the EPA documenting the dates and times that the emergency stationary RICE operated for emergency demand response, beginning with the 2015 calendar year. Commenters on the proposed amendments recommended that the EPA gather information on the impacts of the emissions from emergency engines during emergency demand response situations. The EPA agrees that a reporting requir ement will increase the EPA’s ability to ensure that these engines are operating in compliance with the regulations and that it will provide further information regarding the impacts of thes e engines on emissions. In response to these comments, the EPA is establishing a requirement to annually report to EPA the engine location and duration of operation for emergency demand re sponse. This information will be used by the EPA, as well as state and local air pollution cont rol agencies, to assess the health impacts of the emissions from these engines and to aid the EPA in ensuring that these engines comply with the regulations. Additional discussion of the rationale for the fuel and reporting requirements, as well as responses to other significant comments regarding emergency engines engaged in emergency demand response, can be found in the Response to Public Comments document in the
docket.4-7 Public commenters, in particular the Na tional Rural Electric Cooperative Association (NRECA), indicated that the proposed EEA Level 2 and 5 percent voltage or frequency deviation triggers did not account for situations when th e local balancing authority or transmission operator for the local electric syst em has determined that electric reliability is in jeopardy, and
recommended that the EPA include additional situations where the local transmission and distribution system operator has determined that there are conditions that could lead to a blackout
for the local area. The comments from NRECA i ndicated that rural distribution lines are not configured in a typical grid pattern, but instead have distribution lines that can run well over 50 miles from a substation and regularly extend 15 miles or longer. During periods of exceptionally heavy stress within the region or sub-region, el ectricity from regional power generators may not be available because of transmission constraints, according to the commenter. The commenter indicated that in many cases, there may be only one transmission line that feeds the rural distribution system, and no alternative means to transmit power into the local system.

In response to those comments and in recognition of the unique challenges faced by the
local transmission and distribution system operators in rural areas , the EPA is specifying in the final rule that existing emergency stationary RICE at area sources can be used for 50 hours per year as part of a financial arrangement with a nother entity if all of the following conditions are

met:

 The engine is dispatched by the local balancing authority or local transmission and distribution system operator.

 The dispatch is intended to mitigate local transmission and/or distribution limitations so as to avert potential voltage collapse or line overloads that could lead to the interruption of power supply in a local area or region.

 The dispatch follows reliability, emergency operation or similar protocols that follow specific NERC, regional, state, public utility co mmission or local standards or guidelines.

 The power is provided only to the facility itself or to support the local transmission and distribution system.

 The owner or operator identifies and records the specific NERC, regional, state, public utility commission or local standards or guide lines that are being followed for dispatching the engine. The local balancing authority or local transmission and distribution system operator may keep these records on behalf of the engine owner or operator.

Engines operating in systems that do not meet the conditions described here will not be considered emergency engines if they operate for these purposes as part of a financial arrangement with another entity.4-8 Stationary emergency CI RICE with a site rating of more than 100 brake HP and a displacement of less than 30 liters per cylinder located at area sources that operate for this purpose are also required to use diesel fuel meeting the specifications of 40 CFR 80.510(b) beginning January 1, 2015, except that any existing diesel fuel purchased (or otherwise obtained) prior to January 1, 2015, may be used until depleted. Owners and operators of these engines are also required to report the dates and times the engines operated for this purpose annually to the EPA, beginning with operation during the 2015 calendar year. The report must also identify the entity that dispatched the engine and the situation that necessitated the dispatch of the engine. Further discussion of the rationale for the changes is available in the Response to Public
Comments document in the docket.

4.2. 2 Peak Shaving

The EPA proposed a temporary provision for existing stationary emergency engineslocated at area sources to apply the 50 hours per year that is allowed under §63.6640(f) for nonemergency operation towards any non-emergency operation, including operation as part of a financial agreement with another entity. The peak shaving provision was proposed to expire in April 2017. The purpose of the proposed provision for peak shaving was to give sources an additional resource for maintaining reliability wh ile facilities are coming into compliance with
the NESHAP From Coal and Oil-Fired Electric Utility Steam Generating Units (77 FR 9304). Based on public comments received on the proposal, the EPA is not finalizing the proposed provision for peak shaving in this action. Commenters noted that the allowance was not necessary for maintaining electric reliability, and that alternative methods for meeting peak demand are readily available. In addition, commenters indicated that use for peak shaving does not fairly come under the definition of emergency use as it is designed to increase capacity in the system. Further discussion is available in th e Response to Public Comments document in the
docket.

However, in consideration of the short time between this final rule and the May 3, 2013, or October 19, 2013 compliance dates for affected sources, this final rule permits the use of existing stationary emergency engines located at area sources for 50 hours per year through May 3, 2014 for peak shaving or non-emergency demand response to generate income for a facility, or to otherwise supply power as part of a financial arrangement with another entity if the engines are operated as part of a peak shaving (load management) program with the local distribution system operator and the power is provided only to the facility itself or to support the local distribution system. Owners and operators of these engines, which have heretofore not been regulated, may have taken actions based on the June 7, 2012, proposal that would now leave Deleted:

.4-9 them in danger of being in noncompliance with the applicable requirements for the engine in the
RICE NESHAP.

4.2.3. Final Amendment - Stationary Agricultural RICE in San Joaquin Valley

In the 2010 amendments to the RICE NESHAP, the EPA required existing nonemergency CI engines above 300 HP to meet a standard of either 70 percent reduction of CO emissions or 49 ppmvd CO, for engines between 300 and 500 HP, or 23 ppmvd CO for engines above 500 HP. The requirements also included te sting and monitoring provisions. As with all requirements for existing engines in that rule, ow ners and operators were required to meet the requirements within 3 years of the effective date of the regulations (May 3, 2013).

Since the finalization of the 2010 rule for existing stationary CI engines, stakeholders from the agricultural industry in the San Joaquin Valley area of California have expressed concern regarding the effect of certain of these requirements on engines in the San Joaquin Valley. The San Joaquin Valley Air Pollution Contro l District (APCD) has indicated that there are 17 stationary CI engines at area sources in San Joaquin Valley certified to the Tier 3 standards in 40 CFR part 89 that were installed between January 1 and June 12, 2006. Under the NESHAP, stationary CI engines at area sources are existing if construction of the engine commenced prior to June 12, 2006. These 17 Tier 3 engines in the San Joaquin Valley, which were built to meet stringent emission standards, w ould not be able to comp ly with the applicable RICE NESHAP emission standards for existing e ngines without further testing and monitoring, and possible retrofit with further controls, due to differences in the emission standards and testing protocols in the RICE NESHAP versus th e Tier 3 standards in 40 CFR part 89. However, an identical engine certified to the Tier 3 sta ndards (or Tier 2 standards for engines above 560 kilowatts (kW)) in 40 CFR part 89 that was installed after June 12, 2006, would not have to be retrofit in order to comply with the NESHAP. St ationary CI engines installed after June 12, 2006, at area sources of HAP are required to comply with the NSPS for stationary CI engines, which requires engines to be certified to the standards in 40 CFR parts 89, 94, 1039, and 1042, as applicable. Thus, a 2006 model year stationary CI engine installed after June 12, 2006, that is certified to the applicable standards would meet the requirements of the NESHAP without further controls or testing. While the EPA does not know if other certified Tier 3 engines besides these 17 engines in the San Joaquin Valley were installed prior to June 12, 2006, EPA believes the same rationale should apply to any such engine.

The EPA believes that the Tier 3 standards (Tier 2 for engines above 560 kW) are technologically stringent regulations and believe s it is unnecessary to require further regulation4-10 of engines meeting these standards. In order to address this concern, the EPA is finalizing changes to amend the requirements for any certified Tier 3 (Tier 2 for engines above 560 kW) stationary CI engine located at an area source and installed before June 12, 2006. The EPA is finalizing amendments to specify that any existi ng certified Tier 3 (Tier 2 for engines above 560 kW) CI engine that was installed before June 12, 2006, is in compliance with the NESHAP. This amendment would include any existing stationary Tier 3 (Tier 2 for engines above 560 kW) certified CI engine located at an area source of HAP emissions.

Another concern brought to the EPA’s attention by the San Joaquin Valley agricultural industry is that due to state and local requirements in the San Joaquin Valley, many of the Tier 1 and Tier 2 stationary CI engines that are regul ated as existing sources under the NESHAP must be replaced in the next few years, only a short time after the emission standards for existing engines must be met. Specifically, the San Joaquin Valley APCD rule for internal combustion engines (Rule 4702) requires Tier 1 and Tier 2 certified engines to meet Tier 4 standards by January 1, 2015, or 12 years after the installation date, but no later than June 1, 2018. The concern is that owners and operators of these e ngines would have to install aftertreatment by 2013 to meet the emission standards of the RICE NESHAP and then only a few years later be required to replace their engines per San Joaquin Valley APCD Rule 4702. The San Joaquin Valley APCD has identified 49 Tier 1 engines and 360 Tier 2 engines that are scheduled to be replaced under the local rule. The EPA has not identified any engines outside the San Joaquin Valley APCD area that are in the same or similar situation (i.e., required to be replaced shortly after the compliance date for existing engines), bu t the EPA does not preclude the possibility that there are such engines in other areas, and requests comment and information on other areas that may have similar concerns.

The EPA does not think it is appropriate to re quire emission controls on a stationary CI engine that is going to be retired only a short time after the rule goes into effect. Stationary CI engines would have to comply with this rule by May 3, 2013, and owners of engines above 300 HP are expected to have to install aftertreatment on their engines in order to meet the emission standards. The EPA estimates that the one-time cost to equip a 500 HP stationary CI engine with the controls necessary to meet the emission standards under this rule is close to $14,000 and more than $3,000 on a yearly basis, not accounting for additional costs associated with monitoring, testing, reco rdkeeping and reporting. These engines (equipped with aftertreatment) could end up being in operation for less than 2 years or at most only 5 years before having to be replaced with a certified Tier 4 engine, as required by San Joaquin Valley District Rule 4702. It4-11 would not be reasonable to require the engine owne r to invest in costly controls and monitoring equipment for an engine that will be replaced shortly after the installation of the controls.

Consequently, the EPA is finalizing amendments to existing stationary CI engines located
at area sources of HAP emissions to address this concern. The EPA is finalizing to amend the requirements for existing stationary Tier 1 and Ti er 2 certified CI engines located at area sources that are greater than 300 HP that are subject to a st ate or local rule that requires the engine to be replaced. The EPA is allowing these engines to meet management practices for a period of 2 years starting with the applicable May 3, 2013, compliance date until January 1, 2015, or 12 years after installation date (whichever is later), but not later than June 1, 2018. This change would provide owners enough time to replace their engines without mandating a possibly cost prohibitive requirement to change all of the engines in a short amount of time, while still requiring that replacement of the engine or a retrofit of the engine occur relatively quickly after the owner would have to comply with the NESHAP . The EPA is requiring that these engines be subject to management practices until January 1, 2015, or 12 years after installation date (whichever is later), but not later than June 1, 2018, after which time the CO emission standards discussed above (and that are in Table 2d of the rule) apply. The management practices include requirements for when to inspect and replace th e engine oil and filter, air cleaner, hoses and belts. The complete details of which management practices are required are shown in Table 2d of the rule. Owners and operators of these existing stationary CI engines located at area sources of HAP emissions that intend to meet management pract ices rather than the emission limits prior to May 3, 2015, must submit a notification by March 3, 2013, stating that they intend to use this provision and identifying the state or local regulation that the engine is subject to.

4.2.4 Final Amendments – for Remote Areas of Alaska

The EPA proposed to expand the definition of remote areas of Alaska to extend beyond areas that are not accessible by the FAHS . Specifically, the EPA proposed that areas of Alaska that are accessible by the FAHS and that met all of the following criteria would also be considered remote and subject to management practices under the rule: (1) the stationary CI engine is located in an area not connected to the Alaska Railbelt Grid; (2) at least 10 percent of the power generated by the engine per year is used for residential purposes; and (3) the generating capacity of the area source is less than 12 MW, or the engine is used exclusively for backup power for renewable energy and is used less than 500 hours per year on a 10-year rolling

average.4-12 After considering the public comments received on the proposed criteria, the EPA is finalizing the first two criteria as proposed, but fi nalizing a slightly different third criterion. In this final rule, existing CI engines at area sources of HAP are considered remote if they meet the first and second criteria above and they are either at a source with a generating capacity less than 12 MW, or used exclusively for backup power for renewable energy. Based on public comments received on the proposal, the EPA is not finalizing the limitation that the engine be used less than 500 hours per year on a 10-year rolling average. Commenters indicated that basing the applicability on the previous 10 years of operation would ignore recent investments in renewable energy that have significantly decreased engine hours of operation in recent years. The EPA is also defining “backup power for renewable energy” in this final rule as engines that provide backup power to a facility that generates electri city from renewable energy resources, as that term is defined in Alaska Statute 42.45.045(l)(5). The rationale for these changes can be found in the Response to Public Comments document available in the docket.

4.2.5. Offshore Vessels

The RICE NESHAP does not on its face apply to mobile sources, including marine vessels. However, the regulations applicable to so urces on the OCS, codified at 40 CFR part 55, specify that vessels are OCS sources when they are (1) permanently or temporarily attached to the seabed and erected thereon and used for the purpose of exploring, developing or producing resources there from, within the meaning of s ection 4(a)(1) of the OCS Lands Act (43 U.S.C. §1331, et seq .); or (2) physically attached to an OCS facility, in which case only the stationary sources aspects of the vessels will be regulated . 40 CFR 55.2. The OCS regulations provide that NESHAP requirements apply to a vessel that is an OCS source where the provisions are “rationally related to the attainment and maintena nce of the federal or state ambient air quality standards or the requirements of part C of title I of the Act.” 40 CFR 55.13(e).

The EPA received comments during the public comment period for the June 7, 2012,proposal recommending that the RICE NESHAP be amended such that for any existing nonemergency CI RICE above 300 HP on offshore vessels on the OCS that become subject to the RICE NESHAP as a result of the operation of the OCS regulations (40 CFR part 55), such engines may meet the NESHAP through management practices rather than numeric emission limits. This amendment was not contained or contemplated in the June 7, 2012, proposal. However, the comments indicated several signi ficant issues related to application of the NESHAP to regulation of existing marine vessel engines located in the OCS as a result of the OCS regulations; in particular, wh ether the numerical standards applicable to other CI engines located at area sources (marine vessels located in the OCS are generally located at area sources)4-13 are technologically feasible for existing marine engines located in the OCS. Some commenters noted specific technological issues relevant to engines on marine vessels in the OCS. The
commenters indicated that emission controls for existing CI RICE to m eet the NESHAP may be technically infeasible due to weight and space constraints, catalyst fouling from the low-load engine operation required by the U.S. Coast Guard, safety concerns regarding engine backpressure and lack of catalyst vendor experience with retrofitting. Commenters suggested that, to the extent marine vessel engines become subject to the NESHAP as a result of the OCS regulations, these engines should be subject to GACT requirements that the commenters believe are more appropriate for these types of engines. The commenters indicated that management practices similar to those currently required in the rule for existing non-emergency stationary CI RICE smaller than 300 HP are more appropriate as GACT for existing non-emergency stationary CI RICE above 300 HP on vessels operating on the OCS.

Based on these comments, the EPA published a reopening of the comment period to take further comment on whether the RICE NESHAP should be revised to require management practices for these vessels. Based on the comments received during the two comment periods, the EPA agrees with the commenters that management practices are more reasonable as GACT for existing non-emergency stationary CI RICE larger than 300 HP on vessels operating on the OCS and is finalizing management practices for these engines. The EPA did not receive any public comments indicating that HAP emission contro ls were generally available and had been demonstrated for the large engines on the vessels. The final management practices include changing the oil every 1,000 hours of operation or annually, whichever comes first; inspecting and cleaning air filters every 750 hours of operation or annually, whichever comes first, and replacing as necessary; inspecting fuel filters and belts, if installed, every 750 hours of operation or annually, whichever comes first, and replacing as necessary; and inspecting all flexible hoses every 1,000 hours of operation or annually, whichever comes first, and replacing as necessary. Facilities have the option of using an oil analysis program to extend the oil change requirement.
Additional discussion of the rati onale for these changes can be f ound in the Response to Public
Comments document available in the docket.

4.3 What Are the Pollutants Regulated by this Final Reconsideration Rule?
The final reconsideration rule regulates em issions 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 Deleted: 4.2..6 Compliance Date¶ The EPA has received some questions regarding whether the compliance dates for engines impacted by the 2010 amendments and this 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).4-14 in emission tests conducted on diesel fired RICE include: 1,3-butadiene, acetaldehyde, acrolein, benzene, ethylbenzene, formaldehyde, n-hexane, naphthalene, polycyclic aromatic hydrocarbons, polycyclic organic matter, styrene, toluene, and xylene. Metallic HAP from diesel fired stationary RICE that have been measured are: cadmium, chromium, lead, manganese, mercury, nickel, and selenium.

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. More
details on the health effects of these HAP and other HAP emitted from oper ation of stationary
RICE can be found in Section 7 of this RIA.

The final amendments will continue to limit emissions of HAP through emissions standards for CO for existing stationary CI RICE in similar quantities as estimated for the 2010 final rule. Carbon monoxide has been shown to be an appropriate surrogate for HAP emissions from CI engines. For the NESHAP promulgated in 2004, EPA found that there is a relationship
between CO emissions reductions and HAP emissi ons reductions from CI stationary engines. Therefore, because testing for CO emissions has many advantages over testing for HAP emissions, CO emissions were chosen as a surrogate for HAP emissions reductions for CI stationary engines.

For the standards included in this action, EPA believes that previous decisions regarding the appropriateness of using CO in concentration (ppm) levels as has been done for stationary sources before as surrogates for HAP are still valid. 1 Therefore, the EPA is retaining the emission standards for CO for CI engines in order to regulate HAP emissions.

In addition to reducing HAP and CO, the final amendments will result in the reduction of PM emissions from existing diesel engines. The af tertreatment technologies expected to be used
to reduce HAP and CO emissions also reduce emi ssions of PM from diesel engines. Also, the final rule requires the use of ULSD for dies el-fueled stationary non-emergency CI engines greater than 300 hp with a displacement of less than 30 liters per cylinder. This will result in lower emissions of sulfur oxides (SO x ) and sulfate particulate from these engines by reducing the
sulfur content in the fuel.

1 In contrast, mobile source emission standards for diesel engines (both nonroad and on-highway) are promulgated on a mass basis rather than concentration.4-15 4.4 Cost Impacts

4.4.1 Introduction
The cost impacts associated with this rule consist of different types of costs, which include the annual and capital costs of controls, costs associated with keeping records of information necessary to demonstrate compliance, costs associated with reporting requirements under the General Provisions of 40 CFR part 63, subpart A, costs of purchasing and operating equipment associated with continuous parame tric monitoring, and the cost of conducting performance testing to demonstrate compliance w ith the emission standards. The capital and annual costs presented in this section are calculated based on the control cost methodology presented in the EPA (2002) Air Pollution Control Cost Manual prepared by the U.S. Environmental Protection Agency. 2 This methodology sets out a procedure by which capital and annualized costs are defined and estimated, and this procedure is often used to estimate the costs of rulemakings such as this one. The capital costs presented in this section are annualized using a 7% interest rate, a rate that is consistent with the guidance provided in the Office of Management and Budget’s (OMB’s) (2003) Circular A-4. 3 The following sections describe how the various
cost elements were estimated. Note that the methodologies and procedures presented in the following sections are the same as those used for the 2010 final rule.

4.4.1.1 Control Costs
For engines that will need to add control t echnology to meet the emission standards, the following equations were used to estimate capital and annual cont rol costs as shown in Table 4-
1:

Table 4-1 : CI RICE Control Technologies and Costs

Technology Capital Cost ($2008) Annual Cost ($2008)
Diesel oxidation catalyst (DOC) $27.4 x hp

− $939 $4.99 x hp + $480
Open crankcase ventilation (OCV) $0.26 x hp + $997 $0.065 x hp + $254

The control costs for DOC were calculated using cost data obtained from a California Air Resources Board (CARB) study. 4 The study provided cost ranges for diesel engines ranging from 40 hp to 1400 hp. The average cost from the range was selected and was adjusted to 2008

2 Available on the Internet at http://epa.gov/ttn/catc/products.html#cccinfo

. 3 Available on the Internet at http://www.whitehouse.gov/o mb/circulars/a004/a-4.pdf

. 4 Diesel PM Control Technologies, Appendix IX, California Air Resource Board, October 2000. http://www.arb.ca.gov/diesel/documents/rrpapp9.pdf4-16 dollars. The capital and annual cost were calc ulated using maintenance data from the CARB study and cost assumptions from the EPA Air Pollution Control Cost Manual. The control costs for the OCV system were calculated using 2008 cost data obtained from a diesel engine equipment vendor. An equipment life of 10 years was used to calculate the capital recovery factor (CRF) for developing the annual cost for each of the control devices. A linear regression equation was developed for the capital cost of the DOC and OCV using the capital cost data and the engine size in hp. This approach was used to develop a linear regression equation for annual

cost.

4.4.1.2 Recordkeeping
Minimal recordkeeping costs were attributed to the requirement of following the manufacturer’s emission-related operation and maintenance (O&M) requirements or the owner or operator’s own maintenance plan. It is expected that the majority of owners and operators are already following some type of O&M requiremen ts and a small additional burden is expected. The EPA expects that at most 1 hour will be necessary per year in order to keep track of maintenance. Owners and operator of stationary emergency engines are required to keep track of the hours of operation and 1 hour per year was estimated to cover that recordkeeping activity. For emergency engines 1 hour is expected to cover tracking hours of operation plus recording
maintenance activities. No cost is attributed to purchasing and installing an hour-meter since the majority of stationary engines already come equipped with such equipment. Labor costs associated with recording the hours of operati on of emergency engines are based on a technical labor rate of $68 per hour which was obtained from the Department of Labor Statistics web site. 5 The final total wage rate was based on the 2005 compensation rates for professional staff and adjusted by an overhead and profit rate of 167 percent. The year 2005 was used for consistency
in order to have the same basis for all costs. All costs were later converted to 2008 dollars for purposes of presenting costs associated with the rule in present day terms.

4.4.1.3 Reporting
Most engines affected by this rule will be subject to reporting requirements such as reading instructions, training personnel, subm itting an initial notification, submitting a notification of performance test(s), and submitting a compliance report. However, owners and operators of engines less than 100 HP, existing stationary emergency engines, and existing stationary engines less than 300 HP located at area sources are not subject to any specific

5 U.S. Department of Labor, Employer Costs for Employee Compensation, http://www.bls.gov/news.release/ecec.toc.htm4-17 reporting requirements. For stationary non-emergency limited use CI engines that operate less than 100 hours per year, EPA is finalizing less burdensome reporting requirements by requiring these engines to submit compliance reports on an annual basis, as opposed to semiannually as is required for other engines subject to numerical emission limitations. The reporting requirements are based on $68 per hour for technical labor to comply with the reporting requirements. It is
estimated that a total of 14 hours will be needed, and 13 hours for limited use engines.

4.4.1.4 Monitoring
The cost of monitoring includes the purchase of a continuous parametric monitoring system (CPMS). Non-emergency engines greater than 500 hp that have add-on controls are required to use a CPMS to monitor the catalyst inlet temperature and pressure drop across the catalyst to ensure those parameters do not exceed the operating limitations. The cost of purchasing and operating a CPMS was obtained from vendor quotes received for previous rulemaking and adjusted to 2008 dollars. 6 The capital cost of a CPMS for a large engine facility is $531. It is estimated that 30 hours per year is necessary to operate and maintain the CPMS and that 6 hours per year (or 0.5 hours per month) is needed to record information from the CPMS. It is assumed that all engines subject to continuous monitoring would be located at large engine
facilities.

4.4.1.5 Performance Testing
Initial performance testing is required for non-emergency engines greater than 100 hp at major sources and non-emergency engines greater than 300 hp located at area sources. The cost of conducting a performance test on a CI engine is based on cost information gathered for previous rulemakings. 7 The performance testing cost is based the use of a portable analyzer and was estimated to cost $1,000 per day of testing. This daily performance test cost was adjusted to 2008 dollars and was estimated to be $1,165. Because the regulation requires three-1 hour runs, EPA assumed that two engines could be tested at each facility in one day. Therefore, the estimated impacts performance testing cost will be assumed to be $583 per engine (or half of the $1,165 daily cost) using a portable analyzer.

6 Part A of the Supporting Statement for Standard Form 83 Stationary Reciprocating Internal Combustion Engines, November 17, 2003.
7 Memorandum from Bradley Nelson, Alpha-Gamma Technologies, Inc. to Sims Roy, EPA/OAQPS/ESD/Combustion Group, Portable Emissions Analyzer Cost Information, August 31, 2005.4-18 4.4.1.6 Work Practices
The costs for performing work practices for CI engines less than 100 hp located at a major source was assumed to be negligible and were not included in these impact calculations. The work practices are based on engine maintenance procedures that the owner/operators perform regardless of the regulation. These work practices include:

 Changing the oil and filter;

 Inspecting the air cleaner and replacing as necessary; and

 Inspecting all hoses and belts, and replacing as necessary.

EPA believes that these work practices will limit HAP emissions from these engines, because these work practices ensure that the engi ne is operating efficien tly. Owner/operators of these engines regularly perform these work practices as part of the preventive maintenance schedule for the engine. Therefore, EPA believes th at it is appropriate to not include these work practice costs in the impacts determination.

4.4.1.7 Management Practices
The costs for performing management practices for non-emergency CI engines less than or equal to 300 hp located at area sources and all emergency engines located at area sources was assumed to be negligible and were not included in these impact calculations. The management practices are based on engine maintenance pr ocedures that the owner/operators perform regardless of the regulation. These management practices include:

 Changing the oil and filter;

 Inspecting the air cleaner, and replacing as necessary; and

 Inspecting all hoses and belts, and replacing as necessary.

EPA believes that these work practices will limit HAP emissions from these engines, because these work practices ensure that the engi ne is operating efficiently. Owner/operators of these engines regularly perform these work practices as part of the preventive maintenance schedule for the engine. Therefore, EPA believes th at it is appropriate to not include these work practice costs in the impacts determination.4-19 4.4.2 Major Sources
The cost impacts for stationary RICE vary depending on the engine type and size. The following sections describe th e specific costs that apply to each subcategory of CI engines located at major sources.

4.4.2.1 All CI Engines hp < 100
The costs associated with CI engines less than 100 hp include minimal requirements. Owners and operators of engines less than 100 hp are required to follow the manufacturer’s emission-related O&M requirements or must develop their own maintenance plan to follow. Emergency engines must record the hours of operat ion, which is estimated at one hour per year at $72 per hour.

4.4.2.2 Non-emergency CI Engines 100 ≤ hp ≤ 300 hp
The costs associated with nonemergency CI engines greater than or equal to 100 hp and less than or equal to 300 hp include the cost of an initial test, recordkeeping, and reporting. In addition, EPA assumes that some of these engines will be required to install a control device to
meet the emissions standard. To estimate the num ber of CI engines that would be required to install control technology, EPA compared the emission rate of the test that was used to determine
the MACT floor with the CI nonroad emission factors. 8 EPA found that only the emission factors for Tier 0 CI engines were greater than the 1.2 g/hp-hr value that was used to set the MACT floor. Therefore, it was assumed that Tier 1 engines and greater would be able to meet the final emission standard. The model year for Tier 1 engines begins in 1997 for 100 to 175 CI engines, and 1996 for 175 to 300 hp CI engines. Using the model year data in the population memorandum, EPA estimated that 35 percent of the existing CI engines greater than or equal to 100 hp and less than or equal to 300 hp are Tier 0 engines and would need to install control technology to meet the emission standard. The co st estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ultra-low sulfur diesel (ULSD). EPA estimated the cost of lubricity additives to ULSD would increase the cost of the fuel by 0.2 cents per gallon, 9 which EPA believes is negligib le. In addition, there are no additional maintenance requirements for owner/oper ators using ULSD in existing diesel engines. Many owner/operators have found that time between oil changes can be extended for engines

8 Exhaust and Crankcase Emission Factors for Nonroad Engi ne Modeling--Compression-Ignition, U.S. EPA, Office of Transportation and Air Quality, Assessment and Stan dards Division, EPA420-P-04-009, Revised April 2004. http://www.epa.gov/oms/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
9 Memorandum from Melanie Taylor and Brad Nelson, AGTI to Sims Roy, EPA OAQPS ESD Combustion Group, Lubricity of Ultra Low Sulfur Diesel Fuel, June 2, 2004.4-20 using ULSD fuel, which would decrease the overall cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not includ e any costs for switching to ULSD in the impacts
for this NESHAP.

4.4.2.3 3 Nonemergency CI Engines > 300 hp
The costs associated with non-emergency CI engines above 300 hp include the cost of installing and operating an oxidation catalyst for re ducing HAP, as well as the cost of installing an open crankcase ventilation system. Non-emer gency CI engines greater than 500 hp are also subject to continuous monitoring requirements. In addition, owners and operators must conduct an initial performance test to demonstrate complia nce with the emission limitation. Owners and operators of engines above 500 hp must conduct subsequent performance testing every 8,760 hours or 3 years, whichever comes first to demonstrate compliance. The cost estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ULSD. EPA estimated the cost of lubricity additives to ULSD would increase the cost of the fuel by 0.2 cents per gallon, 10 which EPA believes is negligib le. In addition, there are no additional maintenance requirements for owner/oper ators using ULSD in existing diesel engines. Many owner/operators have found that time between oil changes can be extended for engines using ULSD fuel, which would decrease the overall cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not includ e any costs for switching to ULSD in the impacts
for this NESHAP.

4.4.2.4 Emergency CI Engines
The costs associated with emergency CI engines greater than 300 hp and less than or equal to 500 hp (emergency CI engines above 500 hp were subject to an earlier rule and are not subject to further regulation in this rule) include minimal recordkeeping requirements. The owners and operators must follow the manufacturer’s emission-related operating and maintenance (O&M) requirements or must develop their own maintenance plan to follow and must also keep records of the hours of operation. It is estimated that one hour per year at $68 per hour would be sufficient to record the hours of operation. . The EPA estimates the annual burden of the reporting requirements for all CI engines (major and area) to be approximately 77,128 labor hours at a cost of $4.8 million in the first year that reporting is required, 2015, and 24,628 labor hours at a cost of $1.7 million each year in subsequent years

. No costs were included in the impacts for following the manufacturer’s emission-related O&M plan, because it

10 Memorandum from Melanie Taylor and Brad Nelson, AGTI to Sims Roy, EPA OAQPS ESD Combustion Group, Lubricity of Ultra Low Sulfur Diesel Fuel, June 2, 2004. Comment [A1]: Can you add an estimate (even a low, medium, high number) of the number of engines and provide the overall estimate of the burden associated with this provision? Comment [A2]: Comment addressed.4-21 is expected that owner/operators will follow this plan regardless of the regulation. The cost of the ULSD fuel requirement including the cost of fuel and the potential cost of segregating the fuel is not included in the cost estimate. The cost of the ULSD fuel requirement including the cost of fuel and the potential cost of segregating the fuel is not included in the cost estimate. The EPA believes the ULSD fuel cost would be balanced out by the reduced engine maintenance that is expected from using this fuel. Also, the cost difference between ULSD fuel and higher sulfur fuel is small, especially considering that the yearly operation for emergency DR would be limited to no more than 100 hours per year, and subsequently also the fuel consumption. More information on the burden cost and ULSD cost estimates can be found in the impacts memo for the final reconsideration rulemaking. 11

4.4.3 Area Sources

4.4.3.1 All Emergency CI Engines
The costs associated with emergency CI engines include recordkeeping requirements for tracking the hours of operation, but these engines are not subject to any performance testing. The owners and operators must follow the manufacturer’s emission-related O&M requirements or must develop their own maintenance plan to follow . It is estimated that one hour per year at $68 per hour would be sufficient to record the hours of operation. As stated in the previous section of this RiA, the EPA estimates the annual burden of the reporting requirements for all CI engines (major and area) to be approximately 77,128 labor hours at a cost of $4.8 million in the first year that reporting is required, 2015, and 24,628 labor hours at a cost of $1.7 million each year in subsequent years

. Emergency CI engines at areas sources will be subject to management practices, rather numerical emission limits . The management practices do not require aftertreatment controls. Therefore, no control costs have been estimated for these engines. These engines will be subject to management practices which are not included in the costs, because it is assumed that these management practices are performed regardless of the regulation. The cost of the ULSD fuel requirement including the cost of fuel and the potential cost of segregating the
fuel is not included in the cost estimate for the same reasons as mentioned in the previous
subsection of this section of the RIA.

11 Memorandum to Melanie King, U.S. EPA. RICE NESHAP Reconsideration Final Amendments - Cost and Environmental Impacts. Prepared by Tanya Parise, Ec/R, Inc. January 14, 2013. Deleted: [is or
Deleted: ] Comment [A3]: Please address this and amend as appropriate. Comment [A4]: Comment addressed.

Deleted: [is or

Deleted: ]
Deleted:

.4-22 4.4.3.2 Non-emergency CI Engines ≤ 300 hp
The costs associated with nonemergency CI engines less than or equal to 300 hp are minimal and only include following the manufacturer’s emission-related O&M requirements or the owner or operator’s own maintenance plan. These engines are not subject to any numerical emission limitations, therefore no control costs apply and no performance testing is required. These engines will be subject to management practices which are not included in the costs, because it is assumed that these management practices are done regardless of the regulation.

4.4.3.3 Non-emergency CI Engines > 300 hp
The costs associated with nonemergency CI engines above 300 hp include the cost of installing and operating an oxidation catalyst for re ducing HAP, as well as the cost of installing an open crankcase ventilation system. Nonemergency CI engines greater than 500 hp are also subject to continuous monitoring requirements. In addition, owners and operators must conduct an initial performance test to demonstrate compliance with the emission limitation and engines above 500 hp must conduct subsequent performance testing every 8,760 hours or 3 years, whichever comes first. The cost estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ULSD. The cost estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ULSD. EPA estimated the cost of lubricity additives to ULSD would increase the cost of the fuel by 0.2 cents per gallon, which EPA believes is negligible. In addition, there are no additional maintenance requirements for owner/oper ators using ULSD in existing diesel engines. Many owner/operators have found that time between oil changes can be extended for engines using ULSD fuel, which would decrease the overall cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not includ e any costs for switching to ULSD in the impacts
for this NESHAP.

A summary of the total costs associated with the rule by major source and area source categories is found in Table 4-2. A summary of the costs by NAICS codes is found in Table 4-3. Table 4-4 provides a summary of costs by engine size, and a presentation of the number of engines by engine size is in Table 4-5. All cost estimates are from “RICE NESHAP Reconsideration Amendment – Cost and Environmental Impacts RICE,” prepared by Tanya Parise, EC/R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards. These costs, presented in 2008 dollars, can be updated to 2010 dollars by applying the ratio of the 2010 Marshall & Swift (M&S) annual cost index and the 2008 M&S annual cost index, which is 1,457.4/1,449.3 = 1.01.

### 23Table 4-2. Summary of Major Source and Area Source Costs for the CI RICE NESHAPaSizeRange(hp)Non-EmergencyCI CapitalControl CostNon-EmergencyCI AnnualControl Cost Initial Test Recordkeeping ReportingMonitoring –Capital CostMonitoring –Annual CostTotal AnnualCostsTotal CapitalCostsMajor Sources50–100 $0 $0 $0 $6,654,888 $0 $0 $0 $6,654,888 $0100–175 $24,057,778 $9,918,465 $14,150,269 $8,719,731 $5,973, 016 $0 $0 $38,761,480 $24,057,778175–300 $35,917,270 $10,740,189 $10,730,759 $6,612,548 $4,529,595 $0 $0 $32,613,092 $35,917,270300–500 $107,841,136 $26,722,727 $5,645,923 $3,479,152 $2,383,219 $0 $0 $38,231,021 $107,841,136500–600 $13,126,952 $3,020,849 $500,530 $61,688 $211,280 $481,765 $2,220,755 $6,015,102 $13,608,716600–750 $8,240,540 $1,824,295 $256,204 $31,576 $108,147 $246,599 $1,136,729 $3,356,951 $8,487,139>750 $26,903,091 $5,618,803 $565,163 $69,653 $238,563 $543,975 $2,507,521 $8,999,703 $27,447,066Total $216,086,768 $57,845,329 $31,848,848 $25,629,236 $13,443,820 $1,272,338 $5,865,005 $134,632,238 $217,359,106Area Sources50–100 $0 $0 $0 $9,183,746 $0 $0 $0 $9,183,746 $0100–175 $0 $0 $0 $12,033,196 5,231,824 $0 $0 $17,265,000 $0175–300 $0 $0 $0 $9,125,316 $3,967,529 $0 $0 $13,092,845 $0300–600 269, 176, 789 $64,764,947 $12,533,931 $7,180,954$5,290,738 $4,021,343 $18,536,893 $108,307,463$273,198,131600–750 67,576,980 $14,964,227 $2,101,015 $1,203,716$886,866 $674,082 $9,321,806 $28,473,630,$68,251,062,>750 177,179,667 $37,004,585 $3,722,077 $2,132,457$1,571,138 $1,194,178 $16,514,152 $60,944,409$178,373,845Total 513,933,435 $116,729,759 $18,357,024 $40,859,384$16,948, 096 $5,889,603 $44,372,851 $237,267,114$519,823,039Grand TotalTotal $730,020,203 $174,575,088 $50,205,872 $66,480,620 $30,391,916 $7,161,941 $50,237,856 $371,899,352 $737,182,145aCosts are presented in 2008 dollars.

### 24Table 4-3. Summary of Major Source and AreaSource NAICS Costs for the CI RICE NESHAPaNAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostElectric Power Generation(2211)$161,766,376 $90,982,105 $464,947,798 $202,463,116 $626,714,174 $293,445,222Hospitals (622110)$20,220,797 $11,372,763$0$0 $20,220,797 $11,372,763Crude Petroleum & NGProduction (211111)$2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314Natural Gas Liquid Producers(211112)$2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314National Security (92811) $20,220,797 $11,372,763 $51,660,866 $22,495,902 $71,881,663 $33,868,665Hydro Power Units (335312)$0$16,637$0$22,959$0$39,597Irrigation Sets (335312) $10,294,073 $11,791,567$34,145 $5,208,084 $10,328218 $16,999,651Welders (333992)$108,260 $1,481,447$0 $1,881,380 $108,260 $3,362,827Total $217,359,106$134,632,238$519,823,039$237,267,114$737,182,145$371,899,352aCosts are presented in 2008 dollars.

### 25Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by SizeaNAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostElectric Power Generation (2211)50–100 hp$0 $3,396,123$0 $5,272,480$0 $8,668,603100–175 hp$13,406,919 $21,600,998 $0 $10,824,132 $13,406,919 $32,425,129175–300 hp$23,012,914 $20,895,861$0 $9,437,454 $23,012,914 $30,333,314300–600 hp$96,907,266 $35,304,866 $245,239,035 $97,223,277 $342,146,301 $132,528,144600–750 hp$6,789,032 $2,685,292 $61,419,814 $25,623,705 $68,208,846 $28,308,997>750 hp$21,650,245 $7,098,966 $158,288,950 $54,082,069 $179,939,195 $61,181,035Total 2211$161,766,376 $90,982,105 $464,947,798 $202,463,116 $626,717,174 $293,445,222Hospitals (622110)50–100hp$0 $424,515 $0 $0 $0 $424,515100–175 hp$1,675,865 $2,700,125$0$0 $1,675,865 $2,700,125175–300 hp$2,876,614 $2,611,983$0$0 $2,876,614 $2,611,983300–600 hp$12,113,408 $4,413,108$0$0 $12,113,408 $4,413,108600–750 hp$848,629 $335,662$0$0 $848,629 $335,662>750 hp$2,706,281 $887,371$0$0 $2,706,281 $887,371Total 622110$20,220,797 $11,372,763$0$0 $20,220,797 $11,372,763Crude Petroleum & NG Production (211111)50–100 hp$0 $420,256$0 $579,954$0 $1,000,210100–175 hp$2,026,868 $3,265,655 $0 $1,454,578 $2,026,868 $4,720,233175–300 hp$3,592$3,261$0$1,309$3,592$4,571300–600 hp$151,812 $55,308 $341,498 $135,384 $493,310 $190,692600–750hp$0 $0 $0 0 $0 $0>750 hp$192,129 $62,998 $1,248,617 $426,611 $1,440,746 $489,609Total 211111$2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314(continued)

### 26Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by Sizea(continued)NAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostNatural Gas Liquid Producers (211112)50–100 hp$0 $420,256$0 $579,954$0 $1,000,210100–175 hp$2,026,868 $3,265,655 $0 $1,454,578 $2,026,868 $4,720,233175–300 hp$3,592$3,261$0$1,309$3,592$4,571300–600 hp$151,812 $55,308 $341,498 $135,384 $493,310 $190,692600–750hp0 0 0 0 $0 $0>750 hp$192,129 $62,998 $1,248,617 $426,611 $1,440,746 $489,609Total 211112$2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314National Security (92811)50–100 hp$0 $424,515$0 $585,831$0 $1,010,346100–175 hp$1,675,865 $2,700,125 $0 $1,202,681 $1,675,865 $3,902,806175–300 hp$2,876,614 $2,611,983 $0 $1,048,606 $2,876,614 $3,660,589300–600 hp$12,113,408 $4,413,108 $27,248,782 $10,802,586 $39,362,190 $15,215,695600–750 hp$848,629 $335,662 $6,824,424 $2,847,078 $7,673,053 $3,182,740>750 hp$2,706,281 $887,371 $17,587,661 $6,009,119 $20,293,942 $6,896,489Total 92811$20,220,797 $11,372,763 $51,660,866 $22,495,902 $71,881,663 $33,86,665Hydro Power Units (335312)50–100 hp$0 $16,637$0 $22,959$0 $39,597100–175hp$0 $0 $0 $0 $0 $0175–300hp$0 $0 $0 $0 $0 $0300–600hp$0 $0 $0 $0 $0 $0600–750hp$0 $0 $0 $0 $0 $0>750hp$0 $0 $0 $0 $0 $0Total 335312$0 $16,637$0 $22,959$0 $39,597(continued)

### 27Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by Sizea(continued)NAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostIrrigation Sets (335312)50–100 hp$0 $245,565$0 $338,880$0 $584,446100–175 hp$3,137,134 $5,054,497 $0 $2,251,359 $3,137,134 $7,305,856175–300 hp$7,143,945 $6,486,744 $0 $2,604,167 $7,143,945 $9,090,911300–600 hp$12,145 $4,425 $27,320 $10,831 $39,465 $15,255600–750hp$849 $336 $6,825 $2,847 $7,674 $3,183>750hp$0 $0 $0 $0 $0 $0Total 335312$10,294,073 $11,791,567 $34,145 $5,208,984 $10,328,218 $16,999,651Welders (333992)50–100 hp$0 $1,307,020$0 $1,803,688$0 $3,110,708100–175 hp$108,260 $174,427$0 $77,693 $108,260 $252,119175–300hp$0 $0 $0 $0 $0 $0300–600hp$0 $0 $0 $0 $0 $0600–750hp$0 $0 $0 $0 $0 $0>750hp$0 $0 $0 $0 $0 $0Total 333992$108,260 $1,481,447$0 $1,881,380 $108,260 $3,362,827Grand TotalTotal $217,359,106$134,632,238$519,823,039$237,267,114$737,182,145$371,899,352aCosts are presented in 2008 dollars.

### 28Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of EnginesaNAICSNumber of Engines Total (Major + Area)MajorAreaTotal Capital Cost Annual CostElectric Power Generation (2211)50–100 hp47,32479,859127,183$0 $8,668,603100–175 hp67,713114,266181,980 $13,406,919 $32,425,129175–300 hp59,03999,627158,666 $23,012,914 $30,333,314300–600 hp42,11397,919140,032 $342,146,301 $132,528,144600–750 hp1,76016,45518,215 $68,208,846 $28,308,997>750 hp3,82828,74632,574 $179,939,195 $61,181,035Total 2211221,777436,872658,649 $626,717,174 $293,445,222Hospitals (622110)50–100 hp 5,916 0 5,916 $0 $424,515100–175 hp8,46408,464$1,675,865 $2,700,125175–300 hp7,38007,380$2,876,614 $2,611,983300–600 hp5,26405,264 $12,113,408 $4,413,108600–750 hp2200220$848,629 $335,662>750 hp4790479$2,706,281 $887,371Total 62211027,722027,722 $20,220,797 $11,372,763Crude Petroleum & NG Production (211111)50–100 hp 5,856 8,784 14,640 $0 $1,000,210100–175 hp10,23715,35525,592$2,026,868 $4,720,233175–300 hp91423$3,592$4,571300–600 hp66136202$493,310 $190,692600–750 hp000$0$0>750 hp34227261$1,440,746 $489,609Total 21111116,20224,51740,719$3,964,516 $6,405,314(continued)

### 29Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of Enginesa(continued)NAICSNumber of Engines Total (Major + Area)MajorAreaTotal Capital Cost Annual CostNatural Gas Liquid Producers (211112)50–100 hp5,8568,78414,640$0 $1,000,210100–175 hp10,23715,35525,592$2,026,868 $4,720,233175–300 hp91423$3,592$4,571300–600 hp66136202$493,310 $190,692600–750 hp000$0$0>750 hp34227261$1,440,746 $489,609Total 21111216,20224,51740,719$3,964,516 $6,405,314National Security (92811)50–100 hp5,9168,87314,789$0 $1,010,346100–175 hp8,46412,69621,160$1,675,865 $3,902,806175–300 hp7,38011,07018,450$2,876,614 $3,660,589300–600 hp5,26410,88016,144 $39,362,190 $15,215,695600–750 hp2201,8282,048$7,673,053 $3,182,740>750 hp4793,1943,672 $20,293,942 $6,896,489Total 9281127,72248,54176,263 $71,881,663 $33,868,665Hydro Power Units (335312)50–100 hp 232 348 580 $0 $39,597100–175 hp000$0$0175–300 hp000$0$0300–600 hp000$0$0600–750 hp000$0$0>750 hp000$0$0Total 335312232348580$0$39,597(continued)

### 30Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of Enginesa(continued)NAICSNumber of Engines Total (Major + Area)MajorAreaTotal Capital Cost Annual CostIrrigation Sets (335312)50–100 hp3,4225,1338,555$0 $584,446100–175 hp15,84523,76739,611$3,137,134 $7,305,856175–300 hp18,32727,49145,819$7,143,945 $9,090,911300–600 hp51116$39,465$15,255600–750 hp022$7,674$3,183>750 hp000$0$0Total 33531237,59956,40394,003 $10,328,218 $16,999,651Welders (333992)50–100 hp18,21327,31945,532$0 $3,110,708100–175 hp5478201,367$108,260 $252,119175–300 hp000$0$0300–600 hp000$0$0600–750 hp000$0$0>750 hp000$0$0Total 33399218,76028,14046,899$108,260 $3,362,827Grand TotalTotal 366,217 619,337 957,832 $737,182,145$371,899,352aCosts are presented in 2008 dollars.31 4.5 Baseline Emissions and Emission Reductions

Baseline emissions are estimated for 2013 us ing the emissions dataset generated for the
final CI RICE rule in 2010. The baseline emissions thus assume the final CI RICE rule has not been implemented. The emissions reductions in 2013 associated with the proposed reconsideredrule are based on requiring emission standards that are based on applying add-on controls to nonemergency CI engines greater than 500 HP. Baseline emissions from the current population of stationary RICE less than or equal to 500 HP at major sources and existing stationary RICE at area sources were calculated based on non-emergency CI engines operating 1,000 hrs/yr, and emergency CI engines operating 50 hrs/yr. While the amendments the EPA is finalizing for stationary emergency engines incr eases the time allowed for par ticipation in emergency demandresponse programs and for certain engines to operate for peak shaving or other incomegenerating activities, the EPA believes that 50 hours per year is still repr esentative of emergency engine operation. There is a wide range in how much stationary emergency engines operate. Some emergency units operate well below 50 hrs/yr, while some emergency engines are run above 50 hrs/yr. However, on average and to be conservative, the EPA believes that 50 hrs/yr is still representative and consequently to estimate emissions from stationary emergency engines, the EPA has retained the assump tion that 50 hrs/yr is appropriate. The following additional assumptions were used:

Emission Factors:
Engine HAP (lb/hp-hr) CO (lb/hr) PM (lb/hp-hr) SO 2 (lb/hp-hr)

CI 1.07x10 -4 6.96x10 -1 7.00x10 -4 0.00809xS 1 * *Obtained from AP-42, section 3.4 where S 1 is sulfur content.

Control Efficiencies:
Technology HAP CO PM Oxidation catalyst 70% 70% 30%

Based on the above assumptions and the existing population of engines shown earlier in this section, the HAP, CO, and PM baseline emissions and reductions were calculated.

The estimated baseline emissions for each HAP and criteria pollutant in tons per year (tpy) for the final rule are shown in Table 4-6. The estimated emission reductions for each HAP and criteria pollutant reductions in tons per year (tpy) as a result of the final rule are shown in32 Table 4-7. In addition, it is expected that additional PM re ductions will be achieved by the requirement to use ULSD for CI engines that install a DOC. The use of ULSD reduces the formation of sulfates in the exhaust gas, ther efore reducing the emission of these sulfate PM
emissions from the exhaust. EPA has estimated that the use of ULSD can reduce PM emissions by 5 to 30 percent depending on the sulfur concentration of the diesel fuel that is being replaced. Because EPA has no information on the type of fuel that CI engines are currently using, the PM reductions from switching to ULSD were not quantified and included in this summary.

The EPA is requiring that existing stationary Tier 1 and Tier 2 certified CI engines located at area sources that are subject to state and locally enforceable rules requiring replacement of the engine by January 1, 2018 can meet management practices under the RICE NESHAP for a period of 2 years until May 3, 2015. The San Joaquin Valley APCD has identified 49 Tier 1 engines and 360 Tier 2 engines that are scheduled to be replaced under the local rule. The EPA has not identified any engines outside the San Joaquin Valley APCD area that are in the same or similar situation and although the EPA does not preclude the possibility that there are additional such engines, the EP A has no information on this. Therefore, for purposes of estimating reductions under the final amendments, the EPA has subtracted only those 409 engines from the previous control cost estimate and assumed that an additional 409 engines will be meeting management practices under the rule.

The EPA is also specifying that any existing cer tified Tier 3 CI engine that was installed before June 12, 2006, is in compliance with the NESHAP. This amendment would include any existing stationary Tier 3 certified CI engine lo cated at an area source of HAP emissions. There are 17 Tier 3 engines (2006 model year) located in San Joaquin Valley that were installed between January 1 and June 12, 2006. The EPA do es not know if there are additional engines in
other areas that in a similar situation and the EPA has no information indicating how many such engines there could be in the rest of the country. Therefore, for purposes of calculating reductions, the EPA has included 17 less engines from the control cost estimate. These 17 engines would under the final amendments be subject to management practices.

The work practice requirement of using an op en crankcase ventilation system to control metallic HAP emissions is expected to achieve additional HAP reductions from CI engines. However, the metallic HAP emission reduction cannot be quantified because of the difficulty of measuring metallic HAP from the crankcase exhaust. Therefore, the metallic HAP reductions
are not included in the total emission reductions. Also, all PM emissions are assumed to be in the fine particle emissions; th us all emissions and PM emission reductions are assumed to be
PM 2.5
.33 Table 4-6. Summary of Major Source and Area Source Baseline Emissions for the CI RICE NESHAP in 2013

Size Range (HP) Baseline Emissions (tpy)

HAP CO NO x PM SO 2 VOC
Major Sources
50-100 89 7,745 18,361 584 338 2,412
100-175 215 10,148 44,107 1,403 811 5,794
175-300 281 7,696 57,774 1,838 1,062 7,589
300-500 249 4,049 51,196 1,629 941 6,725
500-600 25 299 5,201 165 115 683
600-750 16 153 3,267 104 72 429

>750 52 338 10,677 340 236 1,402
Total 927 30,428 190,583 6,064 3,575 25,035

Area Sources
50-100 132 11,424 27,083 862 498 3,558
100-175 316 14,969 65,058 2,070 1,196 8,546
175-300 414 11,351 85,217 2,711 1,567 11,194
300-600 613 8,857 106,551 4,009 2,083 16,550
600-750 154 1,485 26,791 1,008 589 4,161

>750 404 2,630 70,314 2,645 1,546 10,921
Total 2,034 50,717 381,015 13,305 7,479 54,930

Grand Total 2,961 81,145 571,598 19,369 11,053 79,96534 Table 4-7. Summary of Major Source and Area Source Emissions Reductions for the CI RICE NESHAP in 2013 Summary of Major Source and Area Source Emis sion Reductions for the CI RICE NESHAP

Size Range (HP) Emission Reductions (tpy)

HAP CO PM VOC
Major Sources

50-100 0 0 0 0
100-175 44 2,072 123 1,183
175-300 57 1,571 161 1,549
300-500 145 2,362 407 3,923

500-600 18 209 50 478

600-750 11 107 31 300

>750 36 236 102 982
Total 312 6,558 874 8,416

Area Sources

50-100 0 0 0 0

100-175 0 0 0 0

175-300 0 0 0 0
300-600 363 5,244 1,017 9,798
600-750 91 879 256 2,463

>750 239 1,557 671 6,466
Total 693 7,680 1,944 18,727
Total 1,005 14,238 2,818 27,142

28

PM Estimate for 2010 Final CI Rule 1,014 14,342 2,844 27,395

Difference 9 104 26 253

Note: All emission reduction estimates are from “ RICE NESHAP Reconsideration Amendments- Cost and Environmental Impacts,” prepared by Tanya Parise, Ec/R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards . January 26, 2012.5-1 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 mark et model; the data that are available have little or no sector/firm detail and are reported at the na tional level. In addition, some sectors have unique market characteristics (e.g., hospitals) that make developing partial equilibrium models difficult. Given these constraints, we believed the direct compliance costs as a reasonable approximation of total social costs. In addition, we also provide a qualitative analysis of the proposed rule’s economic impact on stakeholder decisions, a qu alitative discussion on if unfunded mandates occur as a result of this final rule, and a qualitative discussion of the potential distribution of social costs between consumers and producers.

5.1 Compliance Costs of the Final Rule
For the year 2013, EPA’s engineering cost analysis estimates the total annualized costs of the final rule are $372 million (in 2008 dollars) (EC/R, 2012).

As shown in Figure 5-1, the majority of the costs fall on the electric power sector (79%), followed by national security (9%). The remaining industries each account for 5% or less 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 the final rule. The PSR database used as a basis for the analyses in this RIA contains information on both mobile and stationary onroad and nonroad 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 (see Figure 5-2). For 300 hp engines or less, the annualized per-engine costs are below $215 per engine. Per-engine costs for higher horsepower (hp) engines range between $950 and $1,900.

The final rule will affect approximately one m illion existing stationary diesel engines. As shown in Figure 5-3, most of the affected engines fall within the 100 to 175 hp category (31%).5-2 The next highest categories are 50 to 100 hp (24%) and 175 to 300 hp (23%). The remaining engines are concentrated in the 300 to 600 hp category (16%).

Figure 5-1. Distribution of Annualized Direct Compliance Costs by Industry: 2013 79%

3% 2% 2% 9%

0% 5%

1% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%Electric Power Generation(2211)Hospitals (622110)Crude Petroleum & NGProduction (211111)Natural Gas Liquid Producers(211112)National Security (92811)Hydro Power Units (335312)Irrigation Sets (335312)Welders (333992)5-3 Figure 5-2. Average Annualized Cost per Engine by Horsepower Group: 2013 ($2008)

Figure 5-3. Distribution of Engine Population by Horsepower Group: 2013 $68 $198 $212 $952 $1,549 $1,877

$0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $1,600 $1,800 $2,000

50-100 hp 100-175 hp 175-300 hp 300-600 hp 600-750 hp >750 hp

24% 31%

23%

16%

2% 4%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

50-100 hp 100-175 hp 175-300 hp 300-600 hp 600-750 hp >750 hp5-4 To assess the size of the compliance cost 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 0.07%) (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.

Table 5-1. Selected Industry-Level Annualized Compliance Costs as a Fraction of Total Industry Revenue: 2008

Industry (NAICS) Industry Name Total Annualized Costs ($ million) a Sales, Shipments, Receipt, or Revenue ($ Billion) Cost-to-Sales Ratio ($2007) ($2008)
2211 Electric Power Generation $293.4 $440.4 $449.8 0.07% 622110 Hospitals $11.4 $663.6 $677.8 0.00%

211111 Crude Petroleum & NG Production $6.4 $214.2 $218.8 0.00%

211112 Natural Gas Liquid Producers $6.4 $42.4 $43.3 0.02%

92811 National Security $33,9 #N/A #N/A #N/A

333992 Welders $3.4 $5.2 $5.3 0.06%

111 and 112 Agriculture using irrigation systems a $17.0 $27.9 $28.5 0.05%

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 Internationa l; using American FactFinder; “Sector 00: All sectors:

Geographic Area Series: Economy-Wide Key Statistics: 2007” <http://factfinder.census.gov>; (January 4th , 2010). U.S. Department of Agriculture (USDA), National Agri cultural Statistics Service (NASS). 2009. “2008 Farm and

Ranch Irrigation Survey.” Washington, DC: USDA-NASS. Nelson, B., EC/R Inc. February 17, 2010. Memorandum to Melanie King, U.S. Environmental Protection

Agency. Impacts Associated with NES HAP for Existing Stationary CI RICE.

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 final rule. EPA believes this approximation is better for indus tries whose markets are well characterized as5-5 perfectly competitive. This approximation is less well understood for industries where the characterization of markets is not always perfect ly competitive such as electric power generation whose legal incidence of this rule is approximately 80 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 later in the RIA in Tables 5-
2 and 5-3.

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis
Markets are composed of people as consum ers and producers trying to maximize utility (consumers) and maximize profits (producers) 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 particular price; this curve is typically upward sloping because some production resources are fixe d. 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 servi ce 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 (P 0 ) and quantity (Q 0 ) 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 (Q 0 ) (see Figure 5-4). As shown, this model makes two predictions: the pri ce of the affected goods and services are likely to rise and the consumption/production levels are likely to fall.5-6 consumer surplus = –[fghd + dhc] producer surplus = [fghd – aehb] – bdc total surplus = consumer surplus + producer surplus = –[aehb + dhc + bdc]

Figure 5-4. Market Demand and Supply Model: With and Without Regulation

The size of these changes depends on two fact ors: the size of the unit production cost increase (supply shift) and differences in how each side of the market (supply and demand) responds to changes in price. Economists measur e 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: 1



##   Demand) of Elasticity Price -Supply of Elasticity Price Supply of Elasticity Price

 cost production uniter- Share of p

As a general rule, a higher share of the per-unit cost increases will be passed on to
consumers in markets where

1 For examples of similar mathematical models in the public finance literature, see Nicholson (1998), pages 444–447, or Fullerton and Metcalf (2002).5-7  goods and services are necessities and people do not have good substitutes that they can switch to easily (demand is inelastic) and

 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. Sp ecific 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 (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%5-8 5.3.2 Regulated Markets: The Electric Power Generation, Transmission, and Distribution Sector
Given that the electric power sector bears majority of the estimated compliance costs (Figure 5-1) and the industry is also among the last major regulated energy industries in the United States (EIA, 2000), the competitive model is not necessarily applicable for this industry.5-9 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 competitiv e framework (see Figure 5-5 for the status of restructuring by state), 2 in many states, electricity prices continue to be fully regulated by Public Service Commissions. As a result, the rules an d 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 5-4). The change in consumer surplus is measured as follows:



CS = – [  Q 1 ×  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 = [  Q 1 ×  p ] – [  Q 1 × t] – [0.5 ×  Q × (  p – t)]. (5.2)

2 http://tonto.eia.doe.gov/energy_in_brief/print_pages/electricity.pdf.5-10 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.

Figure 5-5. Electricity Restructuring by State
Source. U.S. Energy Information Administration. 2010a.

<http://www.eia.doe.gov/cneaf/electricity/page/restruct uring/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 prom ulgation 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;5-11 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 en ergy. 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 5-1 suggests at the industry level, the annualized costs represent a very small fraction of revenue (less than 0.7%). 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 in dustry account for about 0.3% of the U.S. total liquid fuels and less than 8% 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.

5.5 Unfunded Mandates
Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), 2 U.S.C. 1531-1538, requires Federal agencies, unless otherwise prohib ited by law, to assess the effects of their regulatory actions on State, local, and tribal governments and the private sector. This rule contains a Federal mandate that may result in expe nditures of $100 million or more for State, local, and tribal governments, in the aggregate, or the private sector in any one year. Accordingly, EPA has prepared under section 202 of the UMRA a written statement which is
summarized below in this section.5-12 Table 5-4. U.S. Electric Power a Sector 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 energy b 4.63 4.8% Electricity Imports 0.12 0.1%

Total Electric Power Energy Consumption c 38.77 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 co mbined heat and power plants whose primary business is

to sell electricity, or electricity and heat, to the pu blic. 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.

c Includes non-biogenic municipal waste not included above. Source: U.S. Energy Information Administration. 2011a . Supplemental Tables to the Annual Energy Outlook 2011,

projections for 2013. Available at: http://www.eia. gov/oiaf/aeo/tablebrowser/#release=EARLY2012&subject=6- EARLY2012&table=2-EARLY2012®ion=1-0&cases=full2011-d020911a,early2012-d121011b

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 final rule are discussed previously in Section 4 of
this RIA. We do not believe that there will be an y disproportionate budgetary effects of the final 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 final rule on the national economy. To the extent feasible, we must estimate th e 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 final rule is presented earlier in this RIA chapter. This analysis provides estimates of the effect of the proposal rule on most of5-13 the categories mentioned above, and these estimates are presented earlier in this RIA chapter. In addition, we have determined that the final 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 identifying and addressing, as appropriate, disproportionately high and adverse human health orenvironmental 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 CI RICE rule, as we state earlier in this document, EPA has determined that this final 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 CI 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 final 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.5-14 This employment impact analysis includes es timates of certain short-term and on-going labor requirements (increase in labor demand) as sociated with reporting and recordkeeping, and the installation, operating and maintenance of control devices. EPA estimates that approximately 1,300 full-time equivalents (FTEs) will be created or supported in the short-term (the compliance period of the regulation) and approximately 2,000 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 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. 3 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 he lp 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, th e 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.

3 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 wi ll cause a short-run aggregat e supply curve to shift to the left, and businesses will produce le ss, all other things being equal.5-15 EPA is interested in public comments on the me rits 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 res ponse 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 final rule. Environmental regulatio n may increase revenue and employment in the environmental technology industry. While these increases represent gains for that industry, they are costs to the regulated industries required to in stall the equipment. As with any pool of labor, the gross size of the labor pool does not refl ect 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 e nvironmental protection create jobs and displace jobs, but the net effect on employment is positive.” 4

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

4 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 63-79.5-16 cost analysis summarized in Section 4 of this RIA includes estimates of the labor requirements associated with implementing the final 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 requ ired and converting this number to full-time equivalents (FTEs) by dividing by 2,080 (40 hour s 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 final reconsidered 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 final NESHAP, reporting and recordkeeping requirements were estimated requ irements were estimated for the entire rule rather than by 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 final reconsideration rule.

The up-front labor requirement is estimated at 1,300 FTEs for the final reconsidered 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 2,000 FTEs for the final reconsidered NESHAP. These ongoing FTE labor requirements can be viewed as sustained labor requirements required for affected entities to continuously comply with the ne w regulation. All of this data is found in the cost memorandum for this reconsidered rule, and can be found in the docket for the rulemaking. It is important to recognize that these seemingl y 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.5-17 Table 5-5. Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Control Equipment Requirements for Reconsidered CI RICE NESHAP

Source Emission Control Measure Projected No. of Affected

Units Per-UnitOneTime Labor Estimate (Hours) Total One-Time

Labor Estimate (Hours) Per-Unit Annual Labor Estimate (Hours) Total Annual Labor Estimate (Hours) One-Time Full-Time Equivalent Annual Full-Time Equivalent

All CI RICE -O&M Recordkeeping N/A 366,217 N/A N/A 1 366,217 N/A 176

NonEmergency CI RICE 100-300 HP -Testing Oxidation Catalyst 54,697 11 593,496 2 738,404 285 355 -Reporting 8NonEmergency CI RICE > 300 HP 3.5

-Testing Oxidation Catalyst + Crankcase Ventilation 11,966 47 563,170 5 636,134 271 306

-Reporting 8 -CPMS Install 3.5 -CPMS O&M 1 -CPMS Recording 30

Area Sources 6 All CI RICE -O&M RecordkeepingNonEmergency CI RICE 100-300 HP N/A 569,364 N/A N/A 1 569,364 N/A 274

-Testing N/A 64,095 N/A N/A 2 128,190 N/A 62 -Reporting

NonEmergency CI RICE > 300 HP Oxidation Catalyst + Crankcase Ventilation + CPMS 31,526 47 1,483,695 5 1,675,922 713 806

-Testing 8 -Reporting 3.5 --CPMS Install 1 CPMS O&M 30 -CPMS Recording 6

Total 105 2,640,361 124 4,114,232 1,269 1,978 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. CPMS = Continuous Parameter Measurement System HP = horsepower N/A = Not Applicable. O&M = Operating and Maintenance5-18 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) 5 to derive the employment effects of new regulations within the regulated industry. (See, for example, the Regulatory Impact Analyses for the recently released 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 requ ires 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. Sa tisfying this new demand requires additional inputs, including labor, and may alter the rela tive 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

5 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):412-436.5-19 the same amount of output,” (p. 416). For example, to reduce pollutant emissions while holding output levels constant, regula ted firms may require additional labor.

 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.” Howe ver, 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 pos itive 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 effect s, 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 po llution 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 expenditure s 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 regula ted 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. Unfort unately, 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 utili ze their quantitative estimates to estimate the employment impacts from this reconsideration. The differences between the underlying5-20 regulations motivating the abatement expenditures studied in Morgenstern et al. are potentially too many to allow for the direct transfer of thei r quantitative estimates for use in analysis of the proposed rule. There are also important differences between the industries affected by this final 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 employme nt impacts within the regulated sector for this 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 as defined by the Small Business Administration (SBA) include small businesses, small governmental jurisdictions, and small not-for-profit enterprises.

After considering the economic impact of the fi nal reconsideration rule on small entities, the screening analysis indicates that this rule will not have a significant economic impact on a substantial number of small entities (or “SISNOSE”). Under the primary cost analyses EPA considered, sales and revenue tests for establishments owned by model small entities are less than 3% and only one group of establishments (irrigated farms with receipts less than $25,000) has a ratio exceeding 1%. These results are identical to those from the small entity analysis done for the final CI RICE rule promulgated in March 2010.

6.1 Small Entity Data Set
The industry sectors covered by the final rule were identified during the development of the cost analysis (Nelson, 2012). The SUSB prov ides national information on the distribution of economic variables by industry and enterprise size (U.S. Census, 2006a, 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 final rule. SUSB also provides statistics by enterprise employment and receipt size.

The Census Bureau’s definitions used in the SUSB, which are stated in Section 3 and restated here for clarity of presentation, are as follows:

 Establishmen t: An establishment is a single physical location where business is conducted or where services or industrial operations are performed.

1 The SUSB data do not provide establishment information fo r the national security NAICS code (92811) or irrigated farms. Since most national security installations are owne d 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, divi dends, 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 anal ysis 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) 3 for NAICS codes associated with sectors listed in Table 6-1. Although the appropriate SBA size definition should be applied at the pare nt 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 de finitions 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

3 The following metrics for other small entity economic impa ct measures (if applicable) would potentially include

• small governments (if applicable): “revenue” test; a nnualized compliance cost as a percentage of annual government revenues and

• small nonprofits (if applicable): “expenditure” test; a nnualized 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. Final NESHAP for Existing Stationary CI Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Business Size Standards

Industry Description Corresponding NAICS SBA Size Standard for Businesses (effective January 7 , 2013) Type of Small Entity
Electric power generation 2211 a Business and government
Natural Gas Transmission 48621 $7.0 million in annual receipts Business

General medical & surgical hospitals 622110 $35.5 million in annual receipts Business and government

Crude petroleum and natural gas production 211111 500 employees Business

Natural gas liquid producers 211112 500 employees Business

National security 92811 NA Government
Hydro power units See NAICS 2211 a 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; Example industry: NAICS 238 = $14 million in annual receipts Business

a NAICS 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 fo r 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 stan dard that defines a small business as receiving $750,000 or less in receipts per year. However, SUSB data were not available for these

5 We use 2007 Economic Census data in estimating number of establishments by industry. The release schedules for different types of 2007 Economic Census data are at http://www.census.gov/econ/census07/pdf/EconCensusScheduleByDate.pdf

.6-4 industries. Therefore, we conducted the sales te st 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.

### 5Table 6-2. Average Receipts for Affected Industryby Enterprise: 2009 ($2008 Million/establishment)SBA SizeStandardfor Businesses(effectiveNovember 5,2010)Owned By Enterprises with Employee Range:NAICS NAICS DescriptionAllEnterprises1–20Employees20–99Employees100–499Employees500+Employees211111 Crude petroleum &natural gas extraction500 employees $30.22 $2.15 $33.02 $151,76 1,570211112 Natural gas liquidextraction500 employees $172.81 $0.30 NA $11.88 NA335312 Motor & generator mfg 1,000 employees $18.58 $1.37 $6.14 $15.96 $29.47333992 Welding & solderingequipment mfg500 employees $18.51 $1.56 $6.60 $33.25 NA .NA = Not available.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.

### 6Table 6-3. Average Receipts for Affected Industry byEnterprise Receipt Range:2007 ($2008 /establishment)SBA Size Standardfor Businesses(effective November5, 2010)Owned By Enterprises with Receipt Range:NAICS NAICS DescriptionAllEnterprises0–99KReceipts100–499.9KReceipts500–999.9KReceipts1,000–4,999.9KReceipts5,000,000–9,999,999KReceipts<10,000KReceipts10,000–49,999KReceipts50,000–99,999KReceipts100,000K+Receipts2211 Electric PowerGenerationa$261.0 $31.2 $272.5 $724.9 $2,399.5 $7,330.5 $2,617.7 $24,786.9$67,706.8$1,394,051.0622110 Hospitals$34.5 million in annualreceipts$202,058.7 NA $23.82 NA $3,255.0 $7,291.0 $4,692.1$23,481.9$67,545,6$508,705.8237310Highway , street, andbride construction$33.5 million inAnnual Receipts$7.74$0.06$0.32$0.84$2.74$8.11$2.00$22.62$56.48$56.81237110Water and sewer lineand related structures,construction$33.5 million inAnnual Receipts$3.89$0.06$0.32$0.85$2.73$8.17$1.84$20.62$45.05$47.27237130Power andcommunication lineand related structuresconstruction$33.5 million inAnnual Receipts$3.39$0.06$0.31$0.83$2.52$7.75$1.32$16.84$34.50$23.86237990Other heavy and civilengineeringconstruction$33.5 million inAnnual Receipts$2.66$0.06$0.30$0.83$2.48$7.76$0.99$18.72$40.53$42.3592811 National Security NA NA NA NA NA NA NA NA NA NA NANotes: . National Security is included in this table but does not have size standards.aNAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm in these industries is defined as small by SBA if, including its affiliates, it isprimarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fiscal year did notexceed 4 million megawatt hours.NA = Not available. SUSB did not report thisdata 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/6-7 Annual entity compliance costs vary depending on the size of the diesel 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 diesel 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 622110 are fundamentally different than other industries considered in this analysis, we used different assumptions about what constitutes the representative establishmen t and report these assumptions separately.

 Case 1: The representative establishment for all industries uses three 750+ hp engines with an average compliance cost of $1,878 per engine, resulting in a total annualized compliance cost of approximately $5,634 for this representative establishment.

 Case 2: The representative establishment in NACIS 2211 and 622110 uses two 50 to 750+ hp engines with an average compliance cost of $419 per engine, resulting in a total annualized compliance cost of $838 for this representative establishment. For all other industries, the representative establishm ent uses two 50 to 300 hp engines with an average compliance cost of $146 per engine, resulting in a total compliance cost of $292 for this representative establishment.

 Case 3: The representative establishment fo r all industries uses two 50 to 100 hp engines with an average compliance cost of $68 per engine, resulting in a total compliance cost of $137 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 proposal in NAICS 335312, 333992, 21 1111, 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 ma ke a similar claim for NAICS 2211 and 622110 based on the existing distribution of engines in these industries. 6 As noted earlier in the RIA, only 20 percent of the existing distribution of engines is expected to be classified as nonemergency.

6 This claim also cannot be made for NAICS 92811: Natio nal 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.6-8 For the sales test, we divided the represen tative establishment compliance costs reported in Table 6-4 by the representative 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 Cost s Used for Small Entity Analysis ($2008)

Case 1 Case 2 Case 3

NAICS 2211,

622110 (+750 hp

only) All Other NAICS (+750 hp

only) NAICS 2211, 622110 (50–750+ hp) All Other NAICS (50–300 hp) NAICS 2211, 622110 (50–100 hp

only) All Other NAICS (50–100 hp

only)
Total Annualized Costs ($) $62,068,406 $7,875,707 $304,817,985 $40,407,406 $9,093,118 $6,745,516
Engine Population 33,052 4,194 727,090 276,374 133,099 98,736
Average Engine Cost ($/engine) $1,878 $1,878 $419 $146 $68 $68

Assumed Engines Per Establishment 3 3 2 2 2 2

Total Annualized Costs per Establishment $5,634 $5,634 $838 $292 $137 $137

* Engine population estimates taken from “Impacts Associ ated with NESHAP for Existing Stationary CI RICE,”

prepared by Bradley Nelson, EC/R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards, February 19, 2010.6-9 Figure 6-1. Distribution of Engine Po pulation by Size for All Industries 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Electric Power Generation

(2211) Hospitals (622110) 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

300

‐ 600 hp

175

‐ 300 hp

100

‐ 175 hp

50

‐ 100 hp6-10 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 offe red by EPA on compliance with SBREFA 7 and is consistent with guidance published by the U.S. SBA’s Office of Advocacy that suggests that cost as a

7 The SBREFA compliance guidance to EPA ru lewriters regarding the types of small business analysis that should be considered can be found at http://www.epa.gov/sbre fa/documents/rfafinalguidance06.pdf, pp. 24-25. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Electric Power Generation

(2211) Hospitals (622110) 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

300

‐ 600 hp

175

‐ 300 hp

100

‐ 175 hp

50

‐ 100 hp6-11 percentage of total revenues is a metric for evaluating cost increases on small entities in relation to increases on large entities. 8

If the cost-to-receipt ratio is less than 1%, th en we consider the final 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

 Case 3 : No industries

Sensitivity Analysis (unlikely):

 Case 1 : NAICS 211111, 211112, with less than 20 employees, NAICS 2211 with receipts less than $500,000 per year, NAICS 234 with receipts less than $500,000 per year, and irrigated farms with receipts of $500,000 or less per year

In the Case 2 primary analysis, only establishments in NAICS 2211 with receipts less than $100,000 per year have cost-to-receipt ratios above 1%. These establishments represent less than 5 percent of affected small establishments. However, establishments earning this level of receipts are likely to be using smaller engines than those assumed in Case 2, such as 50 to 100 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 final rule on small entities, we certify that this action will not have a significant economic imp act on a substantial number of small entities. This certification is based on the economic impact of this action to all affected small entities across all industries affected. The percentage of small entities impacted by this final rule 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 final rule.

Although the final rule would not have a significant economic impact on a substantial number of small entities, EPA nonetheless tried to re duce the impact of the rule on small entities. When developing the revised standards, EPA took special steps to ensure that the burdens

8 U.S. SBA, Office of Advocacy. A Guide for Governme nt Agencies, How to Comply with the Regulatory Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003.6-12 imposed on small entities were minimal. EPA c onducted several meetings with industry trade associations to discuss regulatory options and the corresponding burden on industry, such as recordkeeping and reporting. In addition, as me ntioned earlier in this preamble, EPA is reducing regulatory requirements for a variety of area sources affected under this RICE rule with amendments to the final RICE rules promulgated in 2010.

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 li mitations associated with identifying and appropriately classifying these entities, we co mputed 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, 9 and is consistent with guidance published by the US SBA’s Office of Advocacy. 10 For example, from the 2002 Census (in 2008 dollars), the average revenue for small governments (counties and municipalities) with populations fewer than 10,000 are $3 million per entity, and the average revenue for local governments with populations fewer than 50,000 is $8 million per entity. 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-to-revenue ratio is 0.1% or less under all cases.

9 The SBREFA compliance guidance to EPA rule writers rega rding the types of small business analysis that should be considered can be found at http://www.epa.gov/sbrefa/docum ents/rfafinalguidance06.pdf , pp. 24-25.
10 U.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 CI RICE NESHAP reconsideration is expected to reduce emissions of hazardous ai r pollutants (HAP) and have ancillary co-benefits
that would lower ambient concentrations of PM 2.5 and ozone. In this section, we quantify the monetized co-benefits for this rule associated with reducing exposure to ambient fine particulate matter (PM 2.5 ) by reducing emissions of precursors. We estimate the total monetized co-benefits to be $770 million to $1.9 billion at a 3% discount rate and $690 million to $1.7 billion at a 7%
discount rate in 2013. All estimates are in 2010$. These estimates reflect the monetized human health benefits of reducing cases of morbidity and premature mortality among populations exposed to PM 2.5 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 th e benefits from several important benefit categories, including benefits from reducing exposure to HAP, carbon monoxide, and ozone, as well as visibility impairment. In addition to reducing emissions of PM precursors, this rule would reduce 1,000 tons of HAP and 14,000 tons of carbon monoxide each year.

7.1 Calculation of PM 2.5 -Related Human Health Co-Benefits

Assuming that the baseline for this RIA does not include implementation of the 2010 final CI RICE rule, as we state earlier in this document, this final reconsideration would reduce emissions of directly emitted particles and VOCs. Because these emissions are precursors to
PM 2.5, reducing these emissions would also reduce PM 2.5 formation, human exposure and the
incidence of PM 2.5 -related health effects. Due to analytical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 -related benefits or provide estimates of the health benefits associated with exposure to HAP, CO, or ozone. Instead, we used the “benefit-per-ton” approach to estimate these benefits. The methodol ogy 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 PM 2.5 -related health benefits for emissions reductions in specific sectors. The key assumptions are described in detail below. These PM 2.5 benefit-per-ton estimates provide the total mo netized human health benefits (the sum of premature mortality and premature morbidity) of reducing one ton of PM 2.5 from a specified7-2 source. EPA has used the benefit per-ton technique in several previous RIAs, including the
recent SO 2 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 PM 2.5, 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 unquantif ied health effects associated with exposure to HAP, CO, or ozone nor welfare effects such 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 PM 2.5

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 PM 2.5 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 PM 2.5 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 cerebrovasc ular disease (age 50-79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA 2
Other respiratory effects (e.g., pulmonaryfunction, non-asthma ER visits, nonbronchitis chronic diseases, other ages and populations) -- -- PM ISA 2

Reproductive and developmental effects (e.g., low birth weight, pre-term births, etc) -- -- PM ISA 2,3

Cancer, mutagenicity, and genotoxicity effects -- -- PM ISA 2,3

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 ev idence 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/m 3 as 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 PM 2.5 NAAQS, has
been used as an alternative estimate in the PM 2.5 NAAQS RIA and PM 2.5 benefits estimates in RIAs completed since the PM 2.5 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/m 3 as 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 PM 2.5 -mortality relationship and interpreted for benefits analysis in EPA’s final RIA for the PM 2.5 NAAQS. For that study, twelve experts (labeled A through L) provided independent estimates of the PM 2.5 -mortality concentration-response function. EPA pr actice has been to develop independent
estimates of PM 2.5 -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 rela tionship between exposure to PM 2.5 and premature mortality (Roman

1 These two studies specify multi-pollutant models that control for SO 2 , 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 estima tes 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 PM 2.5 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 consu lt the draft Technical Support Document (TSD) on estimating the benefits per ton of reducing PM 2.5 and its precursors in the “Other Non-EGU Point” category (U.S. EPA, 2012c). 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 da ta 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 si milar limitations as all national-average benefitper-ton estimates in that they reflect the geogra phic 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, e xposure, baseline health incidence rates, or other local factors for any specific location. In this analysis, we apply thes e national benefit-per-ton estimates calculated for this category for directly emitted particles 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. Directly emitted particles are the

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 primary PM 2.5 precursors affected by this rule. Even though we assume that all fine particles have equivalent health effects, the benefit-per-ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The sector-specific modeling does not provide estimates of the PM 2.5 -related benefits associated with reducing VOC emissions, but these unquantified benefits are generally small compared to
other PM 2.5 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 PM 2.5 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 consiste ntly 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 PM 2.5 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 coho rt studies that estimate PM-related mortality. While an LML assessment provides some insight in to the level of uncertainty in the estimatedPM mortality benefits, EPA does not view the LML as a threshold and continues to quantify PMrelated mortality impacts using a full range of mode led air quality concentrations. It is important

4 Additional updates since the Cement RIA include a revised VSL and updated baseline incidence rates.7-7 to emphasize that we have high confidence in PM 2.5 -related effects down to the lowest LML of the major cohort studies, which is 5.8 μg/m 3 . 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. For a summary of the scientific review statements regarding the lack of a
threshold in the PM 2.5 -mortality relationship, see the T echnical Support Document (TSD)
entitled Summary of Expert Opinions on the Existe nce of a Threshold in the ConcentrationResponse Function for PM 2.5 -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 PM 2.5 level. However, we believe that it is still important to characterize the dist ribution of exposure to baseline air quality levels. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionmen t modeling used to calculate the benefit-per-ton estimates for this sector. It is im portant to note that baseline exposure is only one parameter in the health impact function, alon g 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 studi es. OAR arrived at a VSL using a range of $1 million to $10 million (2000$) consistent with tw o 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

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 estimated in the Kochi et al. (2006) meta-analy sis. However, the Agency neither changed its official guidance on the use of VSL in rulemakings nor subjected the interim estimate to a scientific peer-review process through the Scie nce 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 repo rt 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 differe nt 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 thes e 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 PM 2.5 below the National Ambient Air Quality Standards (NAAQS) for PM in some areas and assist other areas with attaining the PM NAAQS. Be cause 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

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 va luation guidance would be forthcoming in the near future. Therefore, this report does not re present final agency policy.
7 This value is $4.8 million in 1990$. In this analysis, we adjust the VSL to account for a different currency year ($2010) and to account for inco me growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is $9.2 million.7-9 quality standard nationwide based on an array of emission control strategies for different sources. In short, NAAQS RIAs hypothesize, but do not pr edict, the control strategies that States may choose to enact when implementing a NAAQS. Th e setting of a NAAQS does not directly result 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 PM 2.5 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 rule s 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 forwar d 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 SO 2 NAAQS RIA (U.S. EPA, 2010a).7-10 Figure 7.1 illustrates the relative breakdown of the monetized PM 2.5 health benefits.

Figure 7-1: Breakdown of Monetized PM 2.5 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 us ing 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

8 To comply with Circular A-4, EPA provides monetized be nefits 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 infa rctions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow-up medical costs and lost wage s. For premature mortality, we assume that there is a “cessation” lag between PM exposures and the total rea lization of changes in health effects. Although the structure of the lag is uncertain, EPA follows the advi ce 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 PM 2.5 (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 va luation of premature mortalities that o ccur after the analys is year. As such, the monetized benefits using a 7% discount rate are onl y 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 7-2 provides a visual representation of the range of PM 2.5 -related benefits estimates using 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 fo r two reasons. First, these estimates are basedon 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. Since the reconsideration proposal, EPA has made several updates to the approach we use to estimate mortality and morbidity benefits in the PM NAAQS RIAs (U.S. EPA, 2012a,b) including updated epidemiology studies, health endpoints, and population data. Although we
have not re-estimated the benefits for this ru le to apply this new approach, these updates generally offset each other, and we anticipate that the rounded benefits estimated for this rule are unlikely to be different than those provided below.

Table 7-2: General Summary of Monetized PM 2.5 -Related Health Co-Benefits Estimates for the CI 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%)

PM 2.5 Precursors

Direct PM 2.5 2,818 $270,000 $670,000 $240,000 $610,000 $770 to $1,900 $690 to $1,700

Total $770 to $1,900 $690 to $1,700

* 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 NO 2 , ozone exposure, ecosystem effects, or visibility im pairment. All fine partic les are assumed to have equivalent health effects, but the benefit per ton estimate s vary because each ton of precu rsor reduced has a different propensity to form PM 2.5 . 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. Although we have not re-estimated the benefits for this rule to apply the updated methods in the PM NAAQS RIA (U.S. EPA, 2012b), these updates generall y offset each other, and we anticipate that the rounded benefits estimated for this rule are unlikely to be different than those provided here.7-12 Table 7-3: Summary of Reductions in Health Incidences from PM 2.5- Related Co-Benefits for CI RICE NESHAP Reconsideration*

Avoided Premature Mortality

Pope et al. 85

Laden et al. 220 Avoided Morbidity

Chronic Bronchitis 59 Emergency Department Visits, Respiratory 66 Hospital Admissions, Respiratory 16 Hospital Admissions, Cardiovascular 35

Acute Bronchitis 130 Lower Respiratory 1,700 Upper Respiratory 1,300 Minor Restricted Activity Days 68,000 Work Loss Days 12,000

Asthma Exacerbation 2,800 Acute Myocardial Infarction 94 * 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 PM 2.5 Co-Benefits Estimates for the CI 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. $770 $690

Laden et al. $1,900 $1,700
Benefit-per-ton Coefficients Derived from Expert Elicitation

Expert A $2,000 $1,800
Expert B $1,500 $1,400
Expert C $1,500 $1,400
Expert D $1,100 $970
Expert E $2,500 $2,200
Expert F $1,400 $1,200
Expert G $920 $820
Expert H $1,200 $1,000
Expert I $1,500 $1,400
Expert J $1,200 $1,100
Expert K $290 $260
Expert L $1,000 $910

* All estimates are rounded to two significant figures. The be nefits estimates from the Expert Elicitation are provided as a reasonable characterization of the uncertainty in th e mortality estimates associated with the concentrationresponse function. Confidence intervals are unavailable fo r this analysis because of the benefit-per-ton methodology7-14 Figure 7-2: Total Monetized PM 2.5 Co-Benefits of CI 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 fr om EPA’s expert elicitation on PM mortality. The results shown are not the direct results fro m the studies or expert elicitation; rather, the estimates are based in part on the concentration-response function provided in those studies. $0 $500 $1,000 $1,500 $2,000 $2,500

Pope et al. Laden et al.Millions(2010$)

PM 2.5 mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions 3% DR
7% DR7-15 Figure 7-3: Breakdown of Total Monetized PM 2.5 Co-Benefits of CI 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, and ozone exposure, as well as ecosystem effects, and visibility impairment. This does not imply that
there are no benefits associated with these emi ssion 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 Toxi cs 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

9 The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/. Major <500 HP 25%

Major >500 HP 6%

Area <600 HP 36% Area >600 HP 33%7-16 engage. In order to identify and prioritize air toxics, emission source types and locations that are 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 ke y 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 acute 14 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.

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 uncertaintie s 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-moni tor ratios) and qualitative (e.g., quality of data, review of emission inventories) judgments can be found at ht tp://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 th e 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 or al, dermal, or inhalation route for 24 hours or less.7-17 Results from the 2005 NATA indicate that acrolein is the primary driver for noncancer respiratory risk.

Figure 7-4 and Figure 7-5 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 concentr ation (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 Trac t Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA) Deleted: Figure
Deleted: Figure7-18 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 di stribution 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

15 The unit risk factor is a quantitative estimate of the car cinogenic potency of a pollutant, often expressed as the probability of contracting cancer from a 70-year lifetime continuous expo sure to a concentration of one μg/m 3 of 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 anal yzing 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 pr ogress 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 re ducing 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 estimate s 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 associat ed 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 HAP may be emitted from CI RICE, a few HAP account for over 90% of
the total mass of HAP emissions emitted. These HAP 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 for existing CI engines is anticipated to reduce 1,000 tons of HAP each year. Below we describe the health effects associated with the top 5 HAP by mass emitted from
CI 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 unders tanding of the health effects associated with exposure to formaldehyde. These include recently published research conducted by the National Cancer Institute (NCI) which found an incr eased 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 wo rkers 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 Ch emical 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 Garm ent 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 amongworkers 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. Exte nded 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 carci nogenicity 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 Ka lisak, J Preston, and FJ Miller. 2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose-respo nse predictions derived from biologically-motivated computational modeling of a combined rodent and huma n 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 un der 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

24 Chemical Industry Institute of Toxicology (CIIT).199 9. Formaldehyde: Hazard charact erization and dose-response assessment for carcinogenicity by the r oute of inhalation. CIIT, Septembe r 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: id entification of key issues. Risk An al 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 limi ted 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 limi ted 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 Formaldehyde exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of th e eyes), nose and throat. Effects from repeated exposure in humans include respiratory tract irri tation, chronic bronchitis and nasal epithelial lesions such as metaplasia and loss of cilia. An imal 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 20 10 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 11 th Report on Carcinogens and is classified as

32 Agency for Toxic Substances and Disease Registry (A TSDR). 1999. Toxicological profile for Formaldehyde. Atlanta, GA: U.S. Department of Health a nd 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 Do cument 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 Ce nter for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm

.7-23 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

Acrolein

EPA determined in 2003 that the human carci nogenic 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/m 3 ) for five minutes may elicit subjective complaints of eye irritation with increasing concentrations leading to more

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 Eval uation 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 Ce nter for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm

. 38 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center for Environm ental 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 chlo rinated 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 Developmen t, 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. In tegrated 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

.7-24 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 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 da ta 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

42 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center for E nvironmental 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 E nvironmental 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 E nvironmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf

. 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 Environm ental 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 chemic als 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 granul ocyte/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.7-25 disorders, such as preleukemia and aplastic anemia, have also been associated with long-term exposure to benzene. 51,52

Methanol

Exposure of humans to methanol by inhalatio n 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 high ly 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 stud ies 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.

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 carcinogenici ty of benzene. Environ. Health Perspect. 82: 193-197.
52 Goldstein, B.D. (1988). Benzene toxicity. Occupati onal medicine. State of the Art Reviews. 3: 541-554.
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 inha lation levels in rats. Toxicol Sci, 5: 727-736.
56 Rogers, JM; Barbee, BD; Rehnberg, BF. 1993. Critical pe riods 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. Reproducti ve and offspring developmental effects following maternal inhalation e xposure to methanol in nonhuman primates Part II: developmental effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA.7-26 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

7.2.2 Ozone Co-Benefits
In the presence of sunlight, NOx and VOCs can undergo a chemical reaction in the atmosphere to form ozone. Reducing ambien t 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 epidemiol ogical 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.

7.2.3 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 (CO 2 ), 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

58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation e xposure to methanol in nonhuman primates Part I: methanol disposition and reproductive toxicity in a dult 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 fasc icularis): reproductive performance and birth outcome. Neurotoxicol Teratol, 26: 639-650.
60 Burbacher, TM; Shen, DD; Lalovic, B; Gr ant, 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 Sy stem (IRIS) database is available at: www.epa.gov/iris7-27 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 li nked to short- and long-term exposure to CO.

7.2.4 Visibility Impairment Co-Benefits

Reducing secondary formation of PM 2.5 would improve visibility throughout the U.S. Fine particles with significant light-extinction efficiencies include sulf ates, nitrates, organic carbon, elemental carbon, and soil (Sisler, 1996). Suspended particles and gases degrade visibility by scattering and abso rbing light. Higher visibility impa irment 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 economi c benefits, including emission inventories, air quality models (with their associated paramete rs and inputs), epidemiological estimates of concentration-response (C-R) functions, estima tes 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 PM 2.5 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 redu ctions and specific air quality and benefits7-28 modeling assumptions. For example, these estimates do not reflect local variability in population density, meteorology, exposure, baseline health in cidence 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 Unite d 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 calcula tion of the new benefit-per-ton estimates (U.S. EPA, 2012).

PM 2.5 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 PM 2.5 , 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 pe rcentage of premature mortality associated with this specific rule’s emission reductions at each PM 2.5 level. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 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 populati on exposed to various ai r 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 PM 2.5 levels at or above the LML. Using the Pope et al. (2002) study, the 77% of the population is exposed to annual mean
PM 2.5 levels at or above the LML of 7.5 μg/m 3 . Using the Laden et al. (2006) study, 25% of the population is exposed above the LML of 10 μg/m 3

. As we model avoided premature deaths among populations exposed to levels of PM 2.5 , we have lower confidence in levels below the LML for each study. It is important to emphasize that we have high confidence in PM 2.5 -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.7-29 A large fraction of the baseline exposure occurs below the level of the National Ambient Air Quality Standard (NAAQS) for annual PM 2.5 at 15 μg/m 3 , which was set 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 Administrator to be protectiv e of public health within an adequate margin of safety, taki ng 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 2.5 Exposure in the Baseline7-30 Figure 7-7. Cumulative Distribution of Adult Population by Annual Mean PM 2.5 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-HES and the NAS (NRC, 2002). The benefits estimates are subject to a number of assumptions and uncertainties. For example, for key assumptions underlying the estimates for premature mortality, which typically account for more than 90% of the total benefits, we we re able to quantify include the following:

1. PM 2.5 benefits were derived through benefit per-ton estimates, which do not reflect local variability in population density, meteorology, exposure, baseline healthincidence rates, or other local factors that might lead to an over-estimate or underestimate of the actual be nefits of controlling directly em itted fine particulates. 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 es timate the proportion of benefits occurring in different locations, such as designated nonattainment areas. In addition, the benefit-per-ton estimates are based on emissi ons from existing sources. To the extent7-31 that the geographic distribution of the emissi ons reductions for this rule are different than the modeled emissions, the benefits ma y be underestimated or overestimated. In general, there is inherently more uncer tainty for new sources, which may not be included in the emissions inventory, than existing sources.

2. We assume that all fine particles, rega rdless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 produced via transported precursors emitted from EGUs may differ significantly from direct PM 2.5 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 an alysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5, 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 PM 2.5 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 th ese 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 PM 2.5 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 PM 2.5 benefits, please consult the
PM 2.5 NAAQS RIA (Table 5.5).

This RIA does not include the type of deta iled 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.7-32 7.4 Comparison of Co-Benefits and Costs
Using a 3% discount rate, we estimate the total combined monetized co-benefits of the reconsidered CI RICE NESHAP to be $770 million to $1.9 billion in the implementation year (2013). Using a 7% discount rate, we estimate the total monetized co-benefits of the reconsidered CI RICE NESHAP to be $690 million to $1.7 billion. The annualized social costs of the reconsidered CI RICE NESHAP are $373 million (2010$) at a 7% interest rate. 62 The annualized
social costs of the recons idered NESHAP are $372 million in 2008$. As stated in Section 4 of this RIA, the costs in 2008 dollars can be updated to 2010 dollars by applying the ratio of the 2010 Marshall & Swift (M&S) annual cost index an d the 2008 M&S annual cost index, which is 1,457.4/1,449.3 = 1.01. Thus, the net benefits are $400 million to $1.5 billion at a 3% discount rate and $320 million to $1.3 billion at a 7% disc ount rate. All of these estimates are in 2010$ for the year 2013.

Table 7-5 shows a summary of the monetized co-benefits, social costs, and net benefits for the reconsidered CI RICE NESHAP, respectively. Figures 7-8 and 7-9 show the full range of net benefits estimates (i.e., annual co-benefits mi nus annualized costs) utilizing the 14 different
PM 2.5 mortality functions at discount rates of 3% and 7%. In addition, the benefits from reducing 14,000 tons of carbon monoxide and 1,000 tons of HAP each year from existing CI RICE have
not been included in these estimates. EPA believe s that the co-benefits are likely to exceed the costs under this rulemaking even when taking in to account uncertainties in the cost and benefit
estimates.

62 For more information on the annualized social costs, please refer to Section 5 of this RIA.7-33 Table 7-5. Summary of the Monetized Benefits, Compliance Costs and Net benefits for

the 2010 Rule with the Final Amendments to the Stationary CI Engine NESHAP in 2013
(millions of 2010 dollars) a

3% Discount Rate 7% Discount Rate
Proposed NESHAP

Total Monetized Benefits 2 $770 to $1,900 $690 to $1,700 Total Compliance Costs 3 $373 $373 Net Benefits $400 to $1,500 $320 to $1,300

Non-monetized Benefits Health effects from HAP exposure

Health effects from PM 2.5 exposure from VOC emissions Ecosystem effects Visibility impairment

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

compliance costs are $373 million in 2010$ as noted earlier in this RIA. These costs, presented in 2008 dollars, can be updated to 2010 dollars by applying the ratio of the 2010 Marshall & Swift (M&S) annual cost index and the 2008 M&S annual cost index, which is 1,457.4/1,449.3 = 1.01. Compliance costs are used as an approximation for social costs in this RIA.

2 The total monetized benefits reflect the human heal th benefits associated with reducing exposure to PM 2.5 through

reductions of PM 2.5 precursors such as directly emitted fine particle s. Human health benefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These mode ls assume that all fine particles, regardless of their chemical composition, are equally potent in causing prematur e mortality because the scientific evidence is not yet sufficient to allow differentiation of effects estimates by particle type. Although we have not re-estimated the benefits for this rule to apply the updated method s in the PM NAAQS RIA (U.S. EPA, 2012b), these updates generally offset each other, and we anticipate that the r ounded benefits estimated for this rule are unlikely to be different than those provided here.

3 The engineering compliance costs are annualized using a 7 percent discount rate.7-34 Figure 7-8. Net Benefits for CI RICE NESHAP Reconsideration at 3% discount rate* *Net Benefits are quantified in terms of PM 2.5 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, but the benefit per ton estimates vary because each ton of precursor reduced has a different propensity to become PM 2.5 . The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. ‐ $100

‐ $80 ‐ $60 ‐ $40 ‐ $20

$0 $20 $40 $60 $80 $100

Pope et al. Laden et al.Millions(2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions ‐ $500

$0 $500 $1,000 $1,500 $2,000 $2,500

Pope et al. Laden et al.Millions(2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions D e l eted : ‐ $100 ‐ $80 ‐ $60 ‐ $40 ‐ $20

$0 $20 $40 $60 $80 $100

Pope et al

.Millions(2010$)

Cost estima t

‐ $500

$0 $500 $1,000 $1,500 $2,000 $2,500

Pope et al.Millions(2010$)

Cost estimate com b7-35 Figure 7-9. Net Benefits for CI RICE NE SHAP Reconsideration at 7% discount rate* *Net Benefits are quantified in terms of PM 2.5 benefits at a 7% discount rate at a 7% discount rate for 2013 and are in 2010$. This graph shows 14 benefits estimates combined wi th 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.

7.5 References Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “The influence of location, source, and emission type in estimates of the human health bene fits of reducing a ton of air pollution.” Air Qual Atmos Health 2:169–176.

Gwinn, M.R., J. Craig, D.A. Axelrad, R. Cook, C. Dockins, N. Fann, R. Fegley, D.E. Guinnup, G. Helfand, B. Hubbell, S.L. Mazur, T. Palma, R.L. Smith, J. Vandenberg, and B. Sonawane. 2011. “Meeting report: Estimating the benefits of reducing hazardous air pollutants—summary of 2009 worksh op and future considerations.” Environ Health Perspect . Jan; 119(1): p. 125-30.

Kochi, I., B. Hubbell, and R. Kramer. 2006. “An Empirical Bayes Approach to Combining Estimates of the Value of Statistical Life for Environmental Policy Analysis .” Environmental and Resource Economics. 34: 385-406.

‐ $500

$0 $500 $1,000 $1,500 $2,000 $2,500

Pope et al. Laden et al.Millions(2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions7-36 Krewski D, Jerrett M, Burnett RT, Ma R, Hughes E, Shi, Y, et al. 2009. Extended follow-up and spatial analysis of the American Cancer Soci ety study linking particulate air pollution and mortality. HEI Research Report, 140, Health Effects Institute, Boston, MA.

Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006. Reduction in Fine Particulate Air Pollution and Mortality. American Journal of Respiratory and Critical Care Medicine. 173: 667-672.

Mrozek, J.R., and L.O. Taylor. 2002. “What Determines the Value of Life? A Meta-Analysis.” Journal of Policy Analysis and Management 21(2):253-270.

National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations . Washington, DC: The National Academies Press.

National Research Council (NRC). 2009. Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use. National Academies Press. Washington, DC.

Office of Management and Budget (OMB). 2003. Circular A-4: Regulatory Analysis. Washington, DC. Available on the Internet at http://www.whitehouse.gov/omb/circulars/a004/a-4.html

. Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 2002. “Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution.” Journal of the American Medical Association 287:1132-1141.

Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, and Patrick L. Kinney. 2008. “Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine Particulate Matter in the U.S.” Environ. Sci. Technol ., 42(7):2268-2274.

Sisler, J.F. 1996. Spatial and seasonal patterns and long-t erm variability of the composition of the haze in the United States: an analysis of data from the IMPROVE network . CIRA Report, ISSN 0737-5352-32, Colorado State University.

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2007. SAB Advisory on EPA’s Issues in Valuing Mortality Risk Reduction. EPA-SAB-08-001. October. Available on the Internet at

< http://yosemite.epa.gov/sab/sabproduct.nsf/4128007E7876B8F0852573760058A978/$File/ sab-08-001.pdf >.
U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009a. Review of EPA’s Integrated Science Assessm ent for Particulate Matter (First External Review Draft, December 2008). EPA-COUNCIL-09-008. May. Available on the Internet at

< http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/73 ACCA834AB44A10852575BD0064346B/$File/EPA-CASAC-09-008-unsigned.pdf >.
U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009b. Consultation on EPA’s Particulate Matter Natio nal Ambient Air Quality Standards: Scope7-37 and Methods Plan for Health Ri sk and Exposure Assessment. EPA-COUNCIL-09-009. May. Available on the Internet at

< http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/72 3FE644C5D758DF852575BD00763A32/$File/EPA-CASAC-09-009-unsigned.pdf >.
U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2010. Review of EPA’s DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clean Air Act. EPA-COUNCIL-10-001 . June. Available on the Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/0/72D4EFA39E48CDB28525774500738776/$F ile/EPA-COUNCIL-10-001-unsigned.pdf>.

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2002. Workshop on the Benefits of Reductions in Exposure to Hazardous Air Pollutants: Developing Best Estimates of Dose-Response Functions An SAB Workshop Report of an EPA/SAB Workshop (Final Report). EPA-SAB-EC-WKSHP-02-001. January. Available on the Internet at <http://yosemite.epa.gov/sab%5CSABPR ODUCT.NSF/34355712E C011A358525719A0 05BF6F6/$File/ecwkshp02001%2Bappa-g.pdf>.

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2008. Benefits of Reducing Benzene Em issions in Houston, 1990–2020 . EPA-COUNCIL-08- 001. July. Available at <http://yosemite.epa.gov/sab/sabproduct.nsf/D4D7EC9DAEDA8A548525748600728A8 3/$File/EPA-COUNCIL-08-001-unsigned.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 1995. Regulatory Impact Analysis for the Petroleum Refinery NESHAP. Revised Draft for Promulgation . Office of Air Quality Planning and Standards, Research Triangle Park, N.C. Available on the Internet at <http://www.reg-markets.org/admin/ authorpdfs/page.php?id=705>.

U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economic Analyses. EPA 240-R-00-003. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. September. Available on the Internet
at < http://yosemite.epa.gov/ee/epa/eed.nsf/web pages/Guidelines.html/$file/cover.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2006. Regulatory Impact Analysis, 2006 National Ambient Air Quality Standards for Particulate Matter , Chapter 5. Available at

< http://www.epa.gov/ttn/ecas/regda ta/RIAs/Chapter%205--Benefits.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2008a. Regulatory Impact Analysis, 2008 National Ambient Air Quality Stand ards for Ground-level Ozone , Chapter 6. Available at

< http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2008c. Integrated Science Assessment for Oxides of Nitrogen - Health Criteria (Final Report). National Center for Environmental Assessment, Research Triangle Park, NC. July. Available at at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=194645>.7-38 U.S. Environmental Protection Agency (U.S. EPA). 2008d. Integrated Science Assessment for Oxides of Nitrogen and Sulfur–Ecological Criteria National (Final Report). National Center for Environmental Assessment, Research Tria ngle Park, NC. EPA/600/R-08/139. December. Available at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485>.

U.S. Environmental Protection Agency (U.S. EPA). 2009a . Regulatory Impact Analysis: National Emission Standards for Hazardous Ai r Pollutants from the Portland Cement Manufacturing Industry . Office of Air Quality Planning and Standards, Research Triangle Park, NC. April. Available on the Internet at

< http://www.epa.gov/ttn/ecas/regdata/R IAs/portlandcementria_4-20-09.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2009b. Integrated Science Assessment for Particulate Matter (Final Report) . EPA-600-R-08-139F. National Center for Environmental Assessment – RTP Division. December. Available on the Internet at

< http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546 >.
U.S. Environmental Protection Agency (U.S. EPA). 2010a. Final Regulatory Impact Analysis (RIA) for the SO 2 National Ambient Air Quality Standards (NAAQS). Office of Air Quality Planning and Standards, Research Triangle Park, NC. June. Available at <http://www.epa.gov/ttn/ecas/ria.html>.

U.S. Environmental Protection Agency (U.S. EPA). 2010b. Technical Support Document: Summary of Expert Opinions on the Existence of a Threshold in the Concentration-Response Function for PM 2.5 -related Mortality . Research Triangle Park, NC. June. Available on the Internet at <www.epa.gov/ttn/ecas/regdata/Benefits/threshold s tsd.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2010c. Guidelines for Preparing Economic Analyses . EPA 240-R-10-001. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. December. Available on the Internet at

< http://yosemite.epa.gov/ee/epa/eerm.nsf/ vwAN/EE-0568-50.pdf/$file/EE-0568-50.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2011a. The Benefits and Costs of the Clean Air Act from 1990 to 2020 . Office of Air and Radiation, Washington, DC. March. <http://www.epa.gov/air/sect812/feb11/fullreport.pdf>. Accessed March 30, 2011.

U.S. Environmental Protection Agency (U.S. EPA). 2011b. Regulatory Impact Analysis for the Final Transport Rule . Office of Air Quality Planning and Standards, Research Triangle Park, NC. June. Available at <http://www .epa.gov/airtransport/pdfs/FinalRIA.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2011c. 2005 National-Scale Air Toxics Assessment

. Office of Air Quality Planning and Standards, Research Triangle Park, NC. March. Available on the Internet at http://www.epa.gov/ttn/atw/nata2005/.

U.S. Environmental Protection Agency (U.S. EPA). 2012a. Regulatory Impact Analysis for the Proposed Revisions to the National Ambient Air Quality Standards for Particulate Matter

. EPA-452/R-12-003. Office of Air Qualit y Planning and Standards, Health and Environmental Impacts Division. June. Available at http://www.epa.gov/ttnecas1/regdata/RI As/PMRIACombinedFile_Bookmarked.pdf

.7-39 U.S. Environmental Protection Agency (U.S. EPA). 2012b. Regulatory Impact Analysis for the Final Revisions to the National Ambient Ai r Quality Standards for Particulate Matter . EPA452/R-12-003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. December. Available at http://www.epa.gov/p m/2012/finalria.pdf

. U.S. Environmental Protection Agency (U.S. EPA). 2012c. Technical Support Document: Estimating the Benefit per ton of Reducing PM 2.5 Precursors from Other Point Sources

. Office of Air Quality Planning and Standards, Research Triangle Park, NC. February.

Viscusi, V.K., and J.E. Aldy. 2003. “The Valu e of a Statistical Life: A Critical Review of Market Estimates throughout the World.” Journal of Risk and Uncertainty 27(1):5-76.8-1 SECTION 8
REFERENCES FOR RIA

American Hospital Association. 2010. “AHA Hosp ital Statistics: 2010 Edition.” Health Forum.

Fann, N., C.M. Fulcher, and B.J. Hubbell. 2009. The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution. Air Qual Atmos Health, 2:169-176.

Fullerton, D., and G. Metcalf. 2002. “Tax Incidence.” In A. Auerbach and M. Feldstein, eds., Handbook of Public Economics , Vol.4, Amsterdam: Elsevier.

Industrial Economics, Inc., 2006. Expanded Expert Judgment Assessment of the ConcentrationResponse Relationship Between PM 2.5 Exposure and Mortality. Prepared for the U.S. EPA, Office of Air Quality Planning and Stan dards, September. Available on the Internet
at < http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_report.pdf >.
Interstate Oil & Gas Compact Commission. 2007. “Marginal Wells: Fuel for Economic Growth.” Table 3.B. < http://iogcc.myshopify.com/collections/frontpage/products/2007-marginalwell-report-2007 >.
Kochi, I., B. Hubbell, and R. Kramer. 2006. An Empirical Bayes Approach to Combining Estimates of the Value of Statistical Life for Environmental Policy Analysis. Environmental and Resource Economics, 34:385-406.

Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006. Reduction in Fine Particulate Air Pollution and Mortality. American Journal of Respiratory and Critical Care Medicine, 173:667-672.

Lincoln Electric Holdings. 2006. Form 10-K. Filed February 24, 2006.

Mrozek, J.R., and L.O. Taylor. 2002. “What Dete rmines the Value of Life? A Meta-Analysis.” Journal of Policy Analysis and Management, 21(2):253-270.

National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations. Wa shington, DC: The National Academies Press.

Nelson, B., EC/R Inc. February 7, 2010. Memorandum to Melanie King, U.S. Environmental Protection Agency. Impacts Associated with NE SHAP for Existing Stationary CI RICE.

Nicholson, Walter. 1998. Microeconomic Theory . Orlando: The Dryden Press.

Office of Management and Budget (OMB), 2003. Circular A-4: Regulatory Analysis. Washington, DC. Available on the internet at

< http://www.whitehouse.gov/omb/circulars/a004/a-4.html >.8-2 Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 2002. “Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution.” Journal of the American Medical Association, 287:1132-1141.

Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, and Patrick L. Kinney. 2008. Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine Pa rticulate Matter in the U.S. Environ. Sci. Technol., 42(7):2268-2274.

The Federal Reserve Board. “Industrial Production and Capacity Utilization: Industrial Production” Series ID: G17/IP_MIN ING_AND_UTILITY_DETAIL/IP.G2211.S http://www.federalreserve.gov/datadownload/ . (December 15, 2008)

Troy, Leo. 2008. “Almanac of Business and Indu strial Financial Ratios: 2009 Edition.” CCH.

U.S. Bureau of Economic Analysis (BEA). 2002. 2002 and 1997 Benchmark Input-Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. http://www.bea.gov/indust ry/index.htm#benchmark_io

. U.S. Bureau of Economic Analysis (BEA). 2009. Table 1.1.9. Implicit Price Deflators for Gross Domestic Product. Last revised December 22, 2009.

U.S. Bureau of the Census. 2002; generated by RTI International; using American FactFinder; “Sector 21: Mining: Industry Series: 2002 and 1997.” http://factfinder.census.gov ; (November 10, 2008).

U.S. Bureau of the Census. 2002; generated by RTI International; using American FactFinder; “Sector 22: Utilities: 2002.” http://factfinder.census.gov ; (November 10, 2008).

U.S. Bureau of the Census. 2002; generated by RTI International; using American FactFinder; “Sector 62: Health Care and Social Assi stance: Geographic Area Series: 2002.” http://factfinder.census.gov ; (November 10, 2008).

U.S. Census Bureau. 2002a. “Industry Series.” Crude Petroleum & Natural Gas: 2002. EC02- 21I-211111 (RV) . Washington, DC: U.S. Bureau of the Census. Table 1.

U.S. Census Bureau. 2002b. “Industry Series.” Electric Power Generation, Transmission, and Distribution: 2002. EC02-22I-03 . Washington, DC: U.S. Bureau of the Census. Table 1.

U.S. Census Bureau. 2002c. “Industry Series.” Hospitals: 2002. EC02-62I-02 . Washington, DC: U.S. Bureau of the Census. Table 1.

U.S. Census Bureau. 2002d. “Industry Series.” Natural Gas Liquid Extraction: 2002. EC02-21I211112 . Washington, DC: U.S. Bureau of the Census. Table 1.

U.S. Census Bureau. 2002e. “Industry Series.” Pipeline Transportation: 2002. EC02-48I-02

. Washington, DC: U.S. Bureau of the Census. Table 1.8-3 U.S. Census Bureau. 2011a. Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2007. < http://www.census.gov/csd/susb/download_susb07.htm

.
U.S. Census Bureau. 2011b. 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/download_susb07.htm

. U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining: Industry Series: Historical Sta tistics for the Industry: 2002 and 2007.” http://factfinder.census.gov ; (February 21, 2012).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 22: Utilities: Subject Series—Estab & Firm Si ze: Concentration by Largest Firms for the United States: 2002.” http://factfinder.census.gov ; (November 21, 2008).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 22: Utilities: Geographic Area Series: Summary Statistics: 2002 and 2007.” http://factfinder.census.gov ; (February 21, 2012).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 62: Health Care and Social Assistance: Subject Series—Estab & Firm Size: Legal Form of Organization for the United States: 2002” http://factfinder.census.gov ; (November 21, 2008).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 31: Manufacturing: Industry Series: Historical St atistics for the Industry: 2007 and Earlier Years” http://factfinder.census.gov ; (February 23, 2012).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: Transportation and Warehousing: Industry Se ries: Comparative Statistics for the United States (1997 NAICS Basis): 2002 and 2007” http://factfinder.census.gov ; (February 23, 2012).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: Transportation and Warehousing: Subject Se ries—Estab & Firm Size: Concentration by Largest Firms for the United States: 2002” http://factfinder.census.gov ; (December 12, 2008).

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49: Geographic Distribution—Pipeline tran sportation of natural gas: 2002.” http://factfinder.census.gov ; (November 10, 2008).

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).8-4 U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 00: All sectors: Geographic Area Series: Ec onomy-Wide Key Statistics: 2007” http://factfinder.census.gov ; (February 23, 2012).

U.S. Department of Agriculture (USDA), Nationa l Agricultural Statistics Service (NASS). 2004. “2003 Farm and Ranch Irrigation Survey.” Washington, DC: USDA-NASS.

U.S. Department of Agriculture (USDA), Nationa l Agricultural Statistics Service (NASS). 2009. “2008 Farm and Ranch Irrigation Survey.” Washington, DC: USDA-NASS.

U.S. Department of Agriculture (USDA). 2008. “Agricultural Projections to 2017.” http://www.ers.usda.gov/Pub lications/OCE081/OCE20081c.pdf

. U.S. Department of Agriculture (USDA). 2008. “Agricultural Projections to 2017.” http://www.ers.usda.gov/Pub lications/OCE081/OCE20081c.pdf

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

U.S. Energy Information Administration. 2008a. http://www.eia.doe.gov/cneaf/electricity/page/ restructuring/restructure_elect.html . Last updated September 2008.

U.S. Energy Information Administration. 2009. Supplemental Tables to the Annual Energy Outlook 2010. Table 2. Available at: http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.html

. U.S. Environmental Protection Agency (U.S. EPA). 2010. Guidelines for Preparing Economic Analyses. EPA 240-R-10-003. National Center for Environmental Economics, Office of Policy. Washington, DC. September. Available on the Internet at < http://yosemite.epa.gov/ee/epa/eed.nsf/pages/Guidelines.html

. U.S. Environmental Protection Agency (EPA). May 2004. Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines. EPA420-R-04-007. Washington, DC: EPA. < http://www.epa.gov/nonroad-d iesel/2004fr/420r04007.pdf > .
U.S. Environmental Protection Agency. 2006. Regulatory Impact Analysis, 2006 National Ambient Air Quality Standards for Particulate Matter, Chapter 5. Available at

< http://www.epa.gov/ttn/ecas/regdata /RIAs/Chapter%205--Benefits.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2008. Guidelines for Preparing Economic Analyses: External Review Draft. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washin gton, DC. September. Available on the Internet at < http://yosemite.epa.gov/ee/epa/eermfile.nsf/vwAN/EE-0516- 01.pdf/$File/EE-0516-01.pdf >.
U.S. Environmental Protection Agency. 2008. Regulatory Impact Analysis, 2008 National Ambient Air Quality Standards for Ground-level Ozone, Chapter 6. Available at http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf

.8-5 U.S. Environmental Protection Agency. 2008. Technical Support Document: Calculating Benefit Per-Ton estimates, Ozone NAAQS Dock et #EPA-HQ-OAR-2007-0225-0284.

U.S. Environmental Protection Agency. 2008. Integrated Science Assessment for Particulate Matter (External Review Draft). Washington, DC, EPA/600/R-08/139. Available on the Internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201805

. U.S. Environmental Protection Agency (U.S. EPA). 2009a. Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants from the Portland Cement Manufacturing Industry. Office of Air Quality Planning and Standards, Research Triangle Park, NC. April. Available on the Internet at

< http://www.epa.gov/ttn/ecas/regdata /RIAs/portlandcementria_4-20-09.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2009b. Proposed SO 2 NAAQS Regulatory Impact Analysis (RIA). Office of Air Qualit y Planning and Standards, Research Triangle Park, NC. November. Available on the Internet at

< http://www.epa.gov/ttn/ecas/regda ta/RIAs/pso2full11-16-09.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2009c. Integrated Science Assessment for Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for Environmental Assessment – RTP Division. D ecember. Available on the Internet at

< http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546 >.
U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2007. SAB Advisory on EPA’s Issues in Valuing Mort ality Risk Reduction. EPA-SAB-08-001. October. Available on the Internet at

< http://yosemite.epa.gov/sab/sabproduct.nsf/4128007E7876B8F0852573760058A978/$F ile/sab-08-001.pdf >.
U.S. Environmental Protection Agency (U.S. EPA). 2012a. Regulatory Impact Analysis for the Proposed Revisions to the National Ambien t Air Quality Standards for Particulate Matter . EPA-452/R-12-003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. June. Available at http://www.epa.gov/ttnecas1/regdata/RIAs/PMRIACombinedFile_Bookmarked.pdf

. U.S. Environmental Protection Agency (U.S. EPA). 2012b. Regulatory Impact Analysis for the Final Revisions to the National Ambient Ai r Quality Standards for Particulate Matter

. EPA-452/R-12-003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. December. Available at http://www.epa.gov/pm/2012/finalria.pdf

. U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009a. Review of EPA’s Integrated Science Assessmen t for Particulate Matter (First External Review Draft, December 2008). EPA-COUNCIL-09-008. May. Available on the Internet
at

< http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86 e/73ACCA834AB44A10852575BD0064 346B/$File/EPA-CASAC-09-008- unsigned.pdf >.8-6 U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009b. Consultation on EPA’s Particulate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and Exposure Assessment. EPA-COUNCIL-09- 009. May. Available on the Internet at

< http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86 e/723FE644C5D758DF852575BD00763A32/$File/EPA-CASAC-09-009-unsigned.pdf >.
U.S. Small Business Administration (SBA). 2008. “Table of Small Business Size Standards Matched to North American Industry Classification System Codes.” Effective August 22, 2008. http://www.sba.gov/idc/groups/public /documents/sba_homepage/serv_sstd_ tablepdf.pdf

. Viscusi, V.K., and J.E. Aldy. 2003. “The Value of a Statistical Life: A Critical Review of Market Estimates throughout the World.” Journal of Risk and Uncertainty, 27(1):5-76.

Wade, S.H. 2003. “Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models.” http://www.eia.doe.gov/oiaf/analysis paper/elasticity/pdf/buildings.pdf

.8-7 United States
Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impacts Division Research Triangle Park, NC Formatted Table