**E.O. 12866 NSPS For Stationary Internal Combustion Engines RIA**

**2060 -**  **AQ58 Proposal 20120522** 

# Regulatory Impact Analysis (RIA) for Proposed Reconsideration of Existing Stationary Compression Ignition (CI) Engines NESHAP Final ReportThis page is intentionally blank.May2 012

Regulatory

Impact Analysis (RIA) for Proposed Reconsideration of Existing Stationary

Compression Ignition Engines NESHAP

By : Paramita Sinha, Brooks Depro, and Fern Braun

RTII nternational Research Triangle Park, North Carolina

Prepared for: Larry Sorrels Contract No. EP - D - 06 - 003 U.S. Environmental Protection Agency Office of Air Quality

Planning and Standards Health and Environmental Impacts Division

Air Economics Group Research Triangle Park, NC

# Regulatory Impact Analysis (RIA)

for Proposed Reconsideration of Existing Stationary Compression

Ignition Engines NESHAP Final Report

**May 201**  **2** Prepared for Larry Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (A E G)

(MD - C439 - 02) Research Triangle Park, NC 27711 Prepared by Paramita Sinha Brooks Depro Fern Braun RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709iii **CONTENTS Section**  **Page Section 1**  Executive Summary ................................ ................................ ................. 1 - 1 ES.1 Summary

of Impacts for CIRICE NESHAP Reconsideration Proposal............1 - 1 ES.2 Comparison with Results from 2010 Final CIRICE NESHAP......................1 - 2 **Section 2** Introduction ................................ ................................ .............................. 2 - 1 **2.1** Organization of this Report ................................ ................................ .................. 2 - 1 **Section 3** Indus try Profile ................................ ................................ ........................ 3 - 2 3.1.1 Overview ................................ ................................ ................................ .. 3 - 2 3.1.2 Goods and Services Used ................................ ................................ ......... 3 - 4 3.1.3 Business Statistics ................................ ................................ .................... 3 - 5 **3.2** Oil and Gas Extraction ................................ ................................ ......................... 3 - 7 3.2.1 Overview ................................ ................................ ................................ .. 3 - 7 3.2.2 Goods and Services Used ................................ ................................ ....... 3 - 10 3.2.3 Business Statistics ................................ ................................ .................. 3 - 11 **3.3** Pipeline Transportation of Natural Gas ................................ ............................. 3 - 16 3.3.1 Overview ................................ ................................ ................................ 3 - 16 3.3.2 Goods and Services Used ................................ ................................ ....... 3 - 17 **3.4** General Medical and Surgical Hospitals ................................ ............................ 3 - 21 3.4.1 Overview ................................ ................................ ................................ 3 - 21 3.4.2 Goods and Services Used ................................ ................................ ....... 3 - 21 3.4.3 Business Statistics ................................ ................................ .................. 3 - 23 **3.5** Irrigation Sets and Welding Equipment ................................ ............................. 3 - 26 3.5.1 Overview ................................ ................................ ................................ 3 - 26 3.5.2 Irrigation and Welding Services ................................ ............................ 3 - 26 3.5.3 Business Statistics ................................ ................................ .................. 3 - 32 **Section 4** Regulatory Alternatives, Costs, and Emission Impacts ........................... 4 - 1iv

**4.1** Background ................................ ................................ ................................ .......... 4 - 1 **4.2** Summary

of the Proposed Reconsideration Rule ................................ ................ 4 - 2 4.2.2 What Are the Pollutants Regulated b y this Proposed Reconsideration Rule? ................................ ................................ ........... 4 - 15 **4.3** Cost Impacts ................................ ................................ ................................ ....... 4 - 16 4.3.1 Introduction ................................ ................................ ............................ 4 - 16 4.3.2 Major Sources ................................ ................................ ........................ 4 - 20 4.3.3 Area Sources ................................ ................................ .......................... 4 - 22 **Section 5** Economic Impact Anal ys is, Energy I mpacts, and Social Costs .............. 5 - 1 **5.1** Compliance Costs of the Final Rule ................................ ................................ .... 5 - 1 **5.2** Social Cost Estimate ................................ ................................ ............................ 5 - 4 **5.3** How Might People and Firms Respond? A Partial Equilibrium Analy si s ........... 5 - 5 5.3.1 Changes in Market Prices and Quantities ................................ ................ 5 - 5 5.3.2 Regulat ed Markets: The Electric Power Generation, Transmission, and Distribution Sector ................................ ................................ ............ 5 - 7 5.3.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus ................................ ................................ ............... 5 - 8 **5.4** Energy

I mpacts ................................ ................................ ................................ .... 5 - 9 **5.5** Unfunded Mandates ................................ ................................ ........................... 5 - 10 5.5.1 Future and Disproportionate Costs ................................ ........................ 5 - 11 5.5.2 Effects on the National Economy ................................ .......................... 5 - 11 **5.6** Environmental Justice ................................ ................................ ........................ 5 - 12 5.7 Employ

ment Impacts 5.7.1 Employ

ment Impacts from Pollution Control Requirements ............................................. .................................... 5 - 14

5.7.2 Employ

ment Impacts within the Regulated Industry ............................. 5 - 17 **Section 6** Small Entity Screening Analy sis ................................ ............................. 6 - 1 **6.1** Small Entity

Data Set ................................ ................................ ........................... 6 - 1 **6.2** Small Entity

Economic Impact Measures ................................ ............................ 6 - 2 6.2.1 Model Establishment Receipts and Annual Compl iance Costs ............... 6 - 2v

**6.3** Small Government Entities ................................ ................................ ................ 6 - 12 **Section 7** Human Hea lth Benefits of Emissions Reductions ................................ ... 7 - 1 **7.1** Calculation of PM 2.5 - Related Human Health Co - Benefits ................................ .. 7 - 1 **7.2** Unquantified Benefits ................................ ................................ ........................ 7 - 15 7.2.1 HAP Benefits ................................ ................................ ............................ 7 - 15 7.2.2 Ozone Co - Benefits ................................ ................................ ................. 7 - 26 7.2.3 Carbon Monoxide Co - Benefits ................................ .............................. 7 - 26 7.2.4 Visibility

I mpairment Co - Benefits ................................ ........................ 7 - 26 7.3 Characterization of Uncertainty in the Monetized Co - Benefits ........................ 7 - 27 **7.4** Comparison of Co - Benefi ts and Costs ................................ ............................... 7 - 32 7.5 References ................................ ................................ ................................ .......... 7 - 36 **Section 8** References for RIA ................................ ................................ .................. 8 - 1vi **LIST OF FIGURES Number**  **Page** 1 - 1. Breakdown of Total Monetized PM 2.5 Co - Benefits of Proposed CIRICE Reconsideration b y Engine Size .............................................................1 **-** 7 1 - 2. Total Monetized PM 2.5 Co - Benefits Estimates for the CIRICE Reconsideration Proposal in 2013 ...............................................................................1 - 8 3 - 1. Industrial Production Index (NAI CS 2211) ................................ ................................ 3 - 3 3 - 2. Internal Combustion Generators b y State: 2006 ................................ ......................... 3 - 4 3 - 3. 20 02 Regional Distribution of Establishments: Electric Power Generation, Transmission, and Distribution Industry (NAICS 2211) ................................ ............ 3 - 5 3 - 4. Industrial Production Index (NAI CS 211) ................................ ................................ .. 3 - 1 3 - 5 . Distribution of Establishments within Pipeline Transportation (NAICS 486) .......... 3 - 17 3 - 6 . Distribution of Revenue within Pipeline Transportation (NAICS 486) .................... 3 - 17 3 - 7 . Share of Establishments by L egal 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 (NAI CS 333111) ................................ .......................... 3 - 28 5 - 1. Distribution of Annualized Direct Compliance Costs by I ndustry : 2013 ................... 5 - 2 5 - 2. Distribution of Engine Population by Horsepower Group: 2013 ................................ 5 - 3 5 - 3. Average Annual ized Cost per Engine by Horsepower Group: 2013 ($2007) ............. 5 - 3 5 - 4. Market Demand and Supply Model: With and Without Regulation ........................... 5 - 6 5 - 5. Electricity

Restructuring by

State ................................ ................................ ................ 5 - 9 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 Proposed CI RI CE NESHAP Reconsideration in 2013 ................................ ................................ ............................ 7 - 14 7 - 3. Breakdown of Total Monetized Co - benefits for Proposed CI RI CE 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 Ex posure in the Baseline.............................................................................. 7 - 29vii

7 - 7 Cumulative Distribution of Adult Population by Annual Mean PM 2.5 Ex posure in the Baseline........................................................................ 7 - 29 7 - 8. Net B enefits for Proposed CI RI CE NESHAP Reconsideration at 3% discount rate..................................................................7 - 33 7 - 9. Net Benefits for Proposed CI RI CE NESHAP Reconsideration at 7% discount rate..................................................................7 - 34viii **LIST OF TABLES Number**  **Page**

1 - 1. Summary

of the Annualized Monetized Benefits, Social Costs, and Net Benefits for the Proposed Reconsidered CI RICE NESHAP in 2013 (millions of 2010$) ................................ ................................ ................................ ..................... 1 - 2 1 - 2. Comparison of Benefits and Costs for 2020 CIRICE Final Rule and 2012 Proposed Reconsideration CI RI CE Rule............................................................ ... 1 - 3 1 - 3. Summary

of Monetized Co - Benefits Estimates for CIRICE Reconsideration Proposal in 2013..........................................................................................1 - 5 1 - 4. Summary

of Estimated Reductions in Health Incidences from PM 2.5 for the CIRICE Reconsideration Proposal in 2013...........................................................1 - 6 1 - 5. Summary

of Estimated Social Costs and Benefits for the 2010 Final CIRICE Rule and the Proposed Reconsideration (millions of 2010 dollars)...........................1 - 9 3 - 1. Key

Statistics: Electric Power Generation, Transmission, and Distribution (NAICS 2211) ($2007) ................................ ................................ ................................ 3 - 2 3 - 2. Direct Requirements for Electric Power Generation, Transmission, and Distribution (NAI CS 2211): 200 7 ................................ ................................ ............... 3 - 5 3 - 3. Firm Concentration for Electric Power Gene ration, Transmission, and Distribution (NAI CS 2211): 2002 ................................ ................................ ............... 3 - 7 3 - 4. United States Retail Electricity Sales Statistics: 200 8 ................................ ................ 3 - 8 3 - 5. FY 20 10 Financial Data for 70 U.S. Shareholder - Owned Electric Utilities ............. 3 - 10 3 - 6. Aggregate Tax Data for Accounting Period 7 /0 7

– 6/0 8 : NAI CS 2211 ..................... 3 - 10 3 - 7. Key

Enterprise Statistics by

Receipt Size for Electric Power Generation, Transmission, and Distribution (NAI CS 2211): 200 7 ................................ ............... 3 - 11 3 - 8. Key

Statistics: Crude Petroleum and Natural Gas Extraction (NAI CS 211111): ($2007) ................................ ................................ ................................ ...................... 3 - 11 3 - 9. Key

Statistics: Natural Gas L iquid Extraction (NAICS 211112) ($2007) ................ 3 - 12 3 - 10. Direct Requirements for Oil and Gas Extraction (NAI CS 211): 2002 ...................... 3 - 12 3 - 11. Key

Statistics for Crude Petroleum and Natural Gas Extraction (NAICS 211111): 200 7 ................................ ................................ ................................ ............ 3 - 13 3 - 12. Key

S tatistics for Crude Natural Gas Liquid Extraction (NAICS 211112): 200 7 .... 3 - 13 3 - 13. Aggregate Tax Data for Accounting Period 7/0 7 – 6/0 8 : NAI CS 211 ....................... 3 - 14 3 - 1 4 . Key

Statistics: Pipeline Transportation of Natural Gas (NAI CS 48621) ($2007) .... 3 - 15ix

3 - 1 5 . Direct Requir ements for Pipeline Transportation (NAI CS 486): 2002 ..................... 3 - 17 3 - 1 6 . Aggregate Tax Data for Accounting Period 7/0 7

– 6/0 8 : NAI CS 486 ....................... 3 - 19 3 - 1 7 Key

Enterprise Statistics by Employ ee Size for Pipeline Transportation of Natural Gas (NAICS 48621): 200 7 ................................ ................................ ........... 3 - 20 3 - 1 8 . Key

Statistics: General Medical and Surgical Hospitals (NAI CS 6221) ($2007) .... 3 - 23 3 - 19 . Direct Requirements for Hospitals (NAICS 622): 2002 ................................ ........... 3 - 23 3 - 2 0 . Data for General Medical and Surgical Hospitals (NAI CS 6221): 200 7 ................. 3 - 24 3 - 2 1 . Hospital Statistics: 20 10 ................................ ................................ ............................ 3 - 25 3 - 2 2 . Aggregate Tax Data for Accounting Period 7/05 – 6/06: NAI CS 622 - 4 .................... 3 - 25 3 - 2 3 . Key

Enterprise Statistics by

Receipt Size for General Medical and Surgical Hospitals (NAICS 6221): 200 7 ($2007) ................................ ................................ ... 3 - 27 3 - 2 4 . Key

Statistics: Farm Machinery and Equipment Manufacturing (NAICS 333111) ($2007) ................................ ................................ ................................ ........ 3 - 28 3 - 2 5 . Key

Statistics: Welding and Soldering Equipment Manufacturing (NAICS 333992) ($2007) ................................ ................................ ................................ ........ 3 - 29 3 - 2 6 . Expenses per Acre b y T ype of Energy: 200 8 ................................ ............................ 3 - 30 3 - 2 7 . Number of On - Farm Pumps of Irrigation Water by Ty pe of Ener gy : 2003 and 200 8 ................................ ................................ ................................ ........................... 3 - 30 3 - 2 8 . Aggregate Tax Data for Accounting Period 7/05

– 6/06: NAI CS 3331 and 333 9 ...... 3 - 31 3 - 29 . Key

Enterprise Statistics by

Receipt Size for Heavy

Construction: 200 7 ................ 3 - 3 4 4 - 1 . CIRICE Control Technologies and Costs ................................ ................................ .. 4 - 9 4 - 2 . Summary

of Major Source and Area Source Costs for the CI RI CE NESHAP ....... 4 - 24 4 - 3 . Summary

of Major Source and Area Source NAICS Costs for the CIRICE NESHAP ................................ ................................ ................................ ................... 4 - 25 4 - 4 . Summary

of Major Source and Area Source NAICS Costs for the CIRICE NESHAP

– by

Size ................................ ................................ ................................ .... 4 - 26 4 - 5 . Summary

of Major Source and Area Source NAICS Costs for the CIRICE NESHAP

– by

Number of Engines ................................ ................................ ........... 4 - 29 4 - 6 . Summary

of Major Source and Area Source Baseline Emissions for the CIRICE NESHAP

– 2013 ...........................................................................4 - 36 4 - 7 . Summary

of Major Source and Area Source Emission Reductions for the CIR IC E NESHAP

– by

2013 ...........................................................................4 - 36 5 - 1. Se lected Industry - Level Annualized Compliance Costs as a Fraction of Total Industry Revenue: 2008 ................................ ................................ ............................... 5 - 4 5 - 2. Hy pothetical Price Increases for a 1% Increase in Unit Costs ................................ .... 5 - 7 5 - 3. Hy pothetical Consumption Decreases for a 1% Increase in Unit Costs ..................... 5 - 8 5 - 4. U.S. Electric Power a Sector Energy Consumption (Quadrillion BTUs): 2013 ......... 5 - 11 5 - 5 Labor - based Employ ment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Control Equipment Requirements for Proposed Reconsideration CI RICE NESHAP......................................................5 - 16x

6 - 1. Final NESHAP for Existing Stationary Reciprocating Internal Combustion Engines (R IC E): Affected Sectors and SBA Small Business Size Standards ............. 6 - 3 6 - 2. Average Receipts for Affected Industry by Enterprise: 200 7 ($2 008 Million/establishment) ................................ ................................ ................................ . 6 - 5 6 - 3. Average Receipts for Affected Industry by Enterprise Receipt Range: 200 7 ($2008 /establishment) ................................ ................................ ................................ 6 - 6 6 - 4. Representative Establishment Costs Used for Small Entity Analy sis ($2008) ........... 6 - 8 7 - 1. Human H ealth and Welfare Effects of PM 2.5 ................................ .............................. 7 - 1 7 - 2. Summary

of Monetized Co - benefits Estimates for RI CE NESHAP for Compression Ignition in 2013 (2008$) ................................ ................................ ..... 7 - 11 7 - 3. Summary

of Reductions in Health Incidences from PM 2.5 Co - benefits for RI CE NESHAP in 2013 ................................ ................................ ................................ ...... 7 - 12 7 - 4 All PM 2.5 Co - benefits Estimates for the RICE NESHAP at discount rates of 3% and 7% in 2013 (in millions of 2008$) ................................ ................................ ...... 7 - 13 7 - 5. Summary

of the Monetized Benefits, Compliance Costs and Net benefits for the 2010 Rule with the Proposed Amendments to the Stationary CIEngine NESHAP in 2013 (millions of 2010 dollars) a ................................ ........................... 7 - 321 - 1 **SECTION 1 EXECUTIVE SUMMARY**  ES.1. Summary

of Impacts for CIRICE NESHAP Reconsideration Proposal The EPA estimates that complying with the proposed reconsid er ation of the stationary compression ignition (CI) reciprocating internal combustion engine ( RI CE ) rule will have an annualized cost of approximately $3 7 2 million per y ear (2008 dollars) or $373 million per y ear (20 10 dollars) in the ye ar of full implementation of the rule (2013). Using these costs, EPA estimates in its economic impact anal ys is that the NESHAP will have limited impacts on the industries affected and their consumers. Using sales data obtained for affected small entities in an anal ys is of the impacts of this proposal on small entities , EPA e xpects that the NESHAP will not result in a SI SNOSE ( significant economic impacts for a subs tantial number of small entities ). EPA also does not expect significant adverse energy impacts based on Executive Order 13211, an Executive Order that requires analy sis of energy impacts for rules such as this one that are economicall y significant under Executive Order 12866. All of these analy sis results are practicall y identic al to the results for the CI RICE NESHAP when it was promulgated in March 2010. The RI CE rule is also considered subject to the requirements of the Office of Management and Budget’s (OMB’s) Circular A - 4 because EPA expects that either the benefits or the costs are potentially $1 billion or higher. EPA estimates the total monetized co - benefits of the NESHAP to be $ 770 m illion to $ 1.9 billion (20 10 $) at a 3% discount rate and $ 690 million to $ 1.7 billion at a 7% discount rate in the ye ar of full implementation of the rule (2013). The net benefits of the proposed CIRICE reconsideration are therefore $ 400 million to $ 1.5 b illion at a 3% discount rate and $ 32 0 million to $ 1.3 b illion at a 7% discount rate (in 2010$) in 2013. These estimates are shown in Table 1 - 1. These co - benefit estimates are lower than those for the rule promulgated two ye ars ago . The previous co - benefit estimates were $ 94 0 million to $ 2,30 0 million (200 8 dollars ) at a 3 - percent discount rate and $ 85 0 million to $ 2,10 0 million (200 8 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 recon sidered rule compared to the benefits for the 2010 final rule will therefore be greater. EPA believes that the benefits are likel y 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 y ear 2013 .1 - 2

**Table 1 -**  **1 .**  **Summary of the Annualized**  **Monetized Benefits, Social Costs, and Net Benefits for the**  **Proposed Reconsidered CI RICE NESHAP in 201**  **3 (millions of 20**  **10 $)**  **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 tw o significant figures. 2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as directly emitted fine particles . Human health b enefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These models assume that all fin e particles, regardless of their chemical composition, are equally potent in causing prem ature mortality because the scientific evidence is not yet sufficient to allow

differentiation of effects estimates by particle type. Because these estimates were gen erated using benefit - per - ton estimates, w e do not break down the total monetized benefits into specific components here. See Figure 7 - 1 for an illustration of the breakdown, or the RIA for the final Cross - States Air Pollution Rule (EPA, 2011) for more in formation. 3 T he annual compliance costs serve as a proxy for the annual social costs of this rule given the lack of difference betw een the two . T he engineering compliance costs are annualized using a 7 percent discount rate. These costs are $372 million in 2008 dollars. Costs are updated to 2010 dollars using the Marshall & Swift (M&S) Annual Cost Index. The update 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 F inal CIRICE NESHAP The EPA anal yz ed the costs, economic impacts and benefits of this proposed rule using the identical methodology as the RI A for the CI RICE final rule promulgate d in May , 2010 . Therefore, all changes to the costs, benefits, and economic impacts for this proposed rule are due to changes (or proposed amendments) to this proposed rule for CI RICE, which are fully described later in this RIA and the preamble for the p roposed rule . Our baseline does not assume compliance with the 2010 CIRICE final rule. This assumption is based on the fact that full implementation of the final rule has not taken place as of yet (it will take place b y Ma y, 2013). In addition, this ass umption is consistent with the baseline definition applied in the recentl y1 - 3

proposed ICI boilers and CI SWINESHAP rulemakings. Monetized benefits are the co - benefits of this proposal from reductions in directly emitted PM 2.5 emissions. The following ta

ble shows an approximation of the changes in monetized benefits and engineering costs due to changes to the CI RICE rule included in the CIRICE reconsideration proposal, and includes values that show a comparison based on the final rule emissions inventory. All values in T able 1 - 2 are in 2010 dollars. **Table 1 -**  **2. Summary of the Monetized Benefits**  **and Compliance Costs for the 2010 Rule**  **with the Proposed Amendments to the Stationary C**  **I Engine NESHAP in 2013 (millions of 2010 dollars)**  **Monetized Benefits in 2013**  **Annual Engineering Costs in**  **2013** CIRICE Final Rule (May 2010) $ 0.940 to $ 2.3 billion $373 m illion Changes due to the proposed amendments to the final CI RICE rule - $ 0.170 to $ 0.400 b illion - $0.7 m illion Proposed CI RICE rule (2012) +$ 0.770 to $1 .9 billion $372 m illion * Monetized benefits are shown at a 3% discount rate and are from reductions in PM 2.5 emissions. These benefits do not include benefits associated w ith 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 proposed amendments in this propo sal. All of the results for this proposed rule are found in Section 5 in this RIA. The results for sales tests (i.e. annual cost/sales analy sis) for small businesses are also essentially

unchanged from those calculated for the final CI RI CE rule . This outcome is also due to the overall minor changes in compliance costs. All of the results for this proposed rule are found in Section 6 in this RIA. We estimate change s in employ ment for this CI RICE proposed rule. These estimates reflect the employ

ment 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 proposed rule. The results1 - 4

are presented and explained in detail in Section 5 of this RIA. We did not estimate changes in employ ment for the 2010 final CIRICE rule. The benefit s estimates decreas ed for the proposal. The range for the 2010 final CIRICE R IAwas $940 m illion (2008$) to $2.3 billion (2008$) at 3 percent discount rate. The range for this proposal is $ 7 70 million (2010$) to $1.9 billion (2010 $) at 3 percent discount rat e. The range for the 2010 final SIRICE RIA was $850 million (2008$) to $2.1 billion (2008 $) at 7 percent discount rate. Th e range for the proposal was $690 million (2010$) to $ 1 .7 billion (2010 $) at 7 percent discount rate. The health benefits were calculated using a methodology described in the 2010 final CI RI CE RIA, using the revised emission reductions estimated for the reconsideration proposal and accounting for other changes discussed in detail in Section 7 of this RIA. We were unable to estim ate the benefits from reducing exposure to HAPs, ecos ys tem impairment, and visibility impairment, including reducing 14,000 tons of carbon monoxide and 1,000 tons of HAPs. Please refer to the full description later in this RIA of the unquantified benefits as well as technical details of the anal ys is and its limitations and uncertainties. These monetized benefits are approximately

21% lower than the 2010 final CI RI CE rule due to the decrease in direct PM 2.5 emission reductions. These benefit - per - ton estim ates were calculated for a 2013 anal ys is y ear (i.e., using population and income growth for 2013). See Tables 1 - 3 and 1 - 4 for the updated benefits results. The benefits analy sis for the 2010 final rules applied out - dated benefit - per - ton estimates compared to the updated estimates described in this preamble and reflected monetized co - benefits for VOC emissions, which limits direct comparability with the monetized co - benefits estimated for these proposed rules. In addition, these estimates have been updated f rom their original currency

y ears to 2010$, so the rounded estimates for the 2010 final rules may not match the original RIAs.

**Table 1**  **- 3**  **: Summary of Monetized**  **Co -**  **Be nefits Estimates for CI RICE**  **Reconsideration Proposal in**  **2013 Pollutant**  **Emissions**

**Reductions (tons)**  **Benefit**

**per ton (Pope,**  **3%) Benefit** 

**per ton (Laden,**  **3%) Benefit** 

**per ton (Pope,**  **7%) Benefit** 

**per ton (Laden,**  **7%) Total M**  **onetized Benefits (m**  **illions 2010**  **$ at 3%) Total M**  **onetized**

**Benefits (m illions**  **2010 $ at 7%)**  Direct PM 2.5 2 ,818 $ 2 70 ,000 $67 0,000 $240 ,000 $ 6 1 0,000 $ 770 to $1,900 $690 to $1 . 700 **Total $**  **7 70**  **to $**  **1,900 $**  **690 to**  **$ 1**  **,700**1 - 5

* All estimates are f

or the implementation year (2013 ), and are rounded to tw o 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 expo sure to NO 2 , ozone exposure, ecosystem effects, or visibility impairment. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton of precursor reduced has a different propensity to form PM 2. 5 . Confidence intervals are unavailable for this analysis because of the benefit - per - ton methodology.1 - 6

**Table 1**  **- 4**  **: Summary of Estimated Reductions in Health Incidences from PM**  **2.5 for the** 

**CI RICE Reconsideration Proposal in 2013 Proposed Option**  **Avoided Prem ature Mortality**  Pope et al. 85

Laden et al. 22 0 **Avoided Morbidity** Chronic Bronchitis 59 Em ergency Room Visits, Respiratory 66 Hospital Admissions, Respiratory 16 Hospital Admissions, Cardiovascular 35 Ac ute Bronchitis 1 30 Lo wer Respiratory 1 , 7 00 Upper Respiratory 1 , 3 00 Minor Restricted Activity Days 68 ,000 Work Loss Days 12 ,000 Asthma Exacerbation 2 , 8 00 Ac ute Myocardial Infarction 9 4 * 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 to1 - 7

allow differentiation of effects estimates by particle type . Confidence intervals are unavailable for this analysis because of the benefit - per - ton methodology. Figure 1 - 1 provides a breakdown of the total monetized co - benefits from reductions of PM 2.5 emissions by

engine size associated with the reconsideration proposal. Figure 1 - 2 provide s a visual representation of the range of PM 2.5 - related benefits estimates using concentration - response functions supplied by experts .

**Figure 1 -**  **1 : Breakdow**  **n of Total**  **Monetized PM**  **2.5 Co**  **- Benefits**  **of Proposed CI RICE Reconsideration**  **by Engine Size** 

**Major <500 HP 25%**  **Major >500 HP 6%** 

**Area <600 HP 36%**  **Area >600 HP 33%** 1 - 8

**Figure 1**  **- 2: Total Monetized PM**  **2.5 Co**  **- Benefits Estimates for the**  **CI RICE Reconsideration**  **Proposal in 201 3** 

* This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on PM mortality. The res ults shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration - response function provided in those studies.

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

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

PM 2.5 mortality be nefit s es tima te s derive d from 2 epide miology functions and 12 exp er t functions 

### 2013* 3% DR 7% DR1 - 9

Table 1 - 5 shows the estimated costs and benefits for the 2010 final CI Rule and the reconsideration proposal. T he estimated net benefits for the reconsideration proposal are smaller than the range for the 2010 final CIRICE rule RIA, which was $ 480 million to $ 1.7 billion at a 7 percent discount rate and was $5 20 million to $ 1.9 billion at 3 percent (in 2010 dollars) . **Table 1**  **- 5**  . **Summary of the Monetized Benefits, Compliance Costs and Net benefits for the 2010 Rule with the Proposed Amendments to the Stationary CI E**  **ngine 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 **Proposed 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 tw o significant figures. All monetized benefits are from reductions of PM 2.5 emissions, a co - benefits of this proposal. The annual ized compliance costs are $373 million in 2010$ as noted earlier in this RIA, and are annualized using a 7% interest rate. Compliance costs are used as an approximation for social costs in this RIA.**SECTION 2 INTRODUCTION**  EPA is proposing reconsideration of national emission standards for hazardous air pollutants (NESHAP) for existing stationary compression ignition (CI) reciprocating internal combustion engines (RICE) that either are located at area sources of hazardous air pollutant (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 proposed amendments to the CIRICE 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 anal ys is ( R IA ). This anal ys is includes an anal ys is of impacts to small entities as part of compliance with the Small Business Regulatory Enforcement Fairness Act (SBREFA) and an anal ys is of impacts on energy consumption and production to comply with Executive Order 13211 (Statement of Energy Effects). An analy sis of economic impacts, along with an anal ys is of impacts on employ ment, is also included in this RIA. Finally, an anal ys is of the benefit s of the rule is included in this RIA. It should be noted that the data that supports the analy ses 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 o**  **f this Report** The remainder of this report supports and details the methodology and the results of the R IA :

 Section 3 presents a profile of the affected industries.

 Section 4 presents a summary of the proposed 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 employ ment impacts.

 Section 6 presents estimated imp acts on small entities.

 Section 7 presents the benefits and net benefits (benefits

– costs) estimates.**SECTION 3 INDUSTRY PROFILE**  Stationary CIengines almost alway s operate as lean burn engines. They can be configured as either two - stroke lean burn (2SLB) or 4 - s troke lean burn (4SLB); the distinction is that CIengines are fueled by distillate fuel oil (diesel fuel ), not b y natural gas or any other gaseous fuel . Industries in which stationary CIengines are found are:

 electric power generation, transmission, and distribution (NAI CS 2211) ,

 oil and gas extrac tion (including marginal wells) (NAI CS 211111) ,

 pipeline transportation of natural gas (NAICS 211112) ,

 general med ical and surgical hospitals (NAICS 622110) , and

 irrigation sets and welding equipment (NAICS 335312 and 333992) . This section provides an introduction to the industries affected b y the proposed 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 econom y, trends for the industries, and financial statistics. **3.1 Electric Power Generation, Transmission, and Distribution**  **3.1.1 Overview**  Electric power generation, transmission, and distribution (NAI CS 2211) is an industry group within the utilities sector (NAICS 22). It includes establishments that produce electrical energy or facilitate its transmission to the final consumer. From 2002 to 200 7 , revenues from electric power grew about 1 8 % to over $ 440 billion ($ 2007) (Table 3 - 1). At the same time, pay roll rose about 7.6 % and the number of emplo ye es decreased b y over 6 %. The number of establishments rose by a little more than 2 %, resulting in a in crease in average establishment revenue of almost 24 %. Industrial pr oduction within NAI CS 2211 has increased 25% since 1997 (Figure 3 - 1). Electric utility

companies have traditionall y been tightly regulated monopolies. Since 1978, several laws and orders have been passed to encourage competition within the electricity market. In the late 1990s, many states began the process of restructuring their utility regulatory framework to support a competitive market. Following market manipulation in the earl y 2000s,however, several states have suspended their restructuring efforts. The majority (58%) of diesel power generators controlled by combined h eat 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**  **200 7**  Revenue ($10 6 ) 373,309 440,342 Payroll ($10 6 ) 40,842 4 3 , 266 Em ploy ees 535,675 5 03,134 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 Unit ed States, All Industries: 2007. Statistics for U.S. Businesses. Found at http://www.census.gov/econ/susb/data/susb2007.html .**Figure 3**  **- 1.**  **Industrial Production Index (NAICS 2211)** 

Source: The Federal Reserve Board. “ Industrial Production and Capacity Utilization: Industrial Production ” Series ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G2211.S <http://www.federalreserve.gov/datadownload/>. ( January 27, 2010). **3.1.2 Goods and Services Used**  In Table 3 - 2 , we use the latest detailed benchmark input - output data report by the Bureau of Economic Anal ys is (BEA) (200 2 ) to identify the goods and services used in electric power generation. As shown, labor and tax requirements represent a sign ificant share of the value of

80 85 90 95 100 105 110 1151997-011997-061997-111998-041998-091999-021999-071999-122000-052000-102001-032001-082002-012002-062002-112003-042003-092004-022004-072004-122005-052005-102006-032006-082007-012007-062007-112008-042008-092009-022009-072009-12**I n** **d e** **x V** **a l** **u e** **( J** **a n** **2 0** **0 2** **= 1** **0 0** **) Figure**  **3 -**  **2. Internal Combustion**  **Generators by State :**  **2006**

Source: U.S. Department of Energy, En ergy Information Administration . 2007. “ 2006 EIA - 906/920 Monthly Time Series .” power generation. Extraction, transportation, refining, and equipment requirements potentially associated with reciprocating internal comb ustion engines (oil and gas extraction, pipeline transportation, petroleum refineries, and turbine manufacturing) represent around 10% of the value of services. **3.1.3 Business Statistics**  The U.S. Economic Census and Statistics of U.S. Businesses (SUSB) pro grams provide national information on the distribution of economic variables b y industry, location, and size of business. Throughout this section and report, we use the following definitions:

 Establishmen t: An establishment is a single ph ys ical location wh ere business is conducted or where services or industrial operations are performed. **Di esel and Natural Gas Internal**  **Co mbustion Generators By State** 

No Restructuring Suspended Restructuring Active Restructuring

100 50 10 1**Table 3**  **- 2.**  **Direct Requirements for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2002**  **Comm odity**  **Comm odity Description**  **Direct Requirements Coeffic**  **ients a**  V00100 Com

pensation of employees 20.52% V00200 Taxes on production and imports, less subsidies 13.71% 211000 Oil and gas extraction 6.16% 212100 Coal mining 5.86% 482000 Rail transportation 3.01% 230301 Nonresidential maintenance and repair 2.83% 486000 Pipeline transportation 1.70% 722000 Food services and drinking places 1.40% 52A000 Monetary authorities and depository credit intermediation 1.39% 541100 Legal services 1.13%

a These values show

the amount of the commodity required to produce $1.00 of the industry ’ s output. The values are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input - Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5.

 Receipts : Receipts (net of taxes) are defined as the revenue for goods produced, distributed, or services provided, including revenue earned from premiums, commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

 Firm : A firm is a business organiz ation consisting of one or more domestic establishments in the same state and industry that were specified under common ownership or control. The firm and the establishment are the same for single establishment firms. For each multiestablishment firm, esta blishments in the same industry within a state are counted as one firm; the firm emplo ym ent and annual pay roll are summed from the associated establishments.

 Enterprise : An enterprise is a business organization consisting of one or more domestic establishm ents 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 employ ment and annual pay

roll are summed from the associated establishments. Enterprise size designations are determined by the summed employ

ment of all associated establishments. In 2002, Texas had almost 1,000 power establishments, while California, Georgia, and Ohio all had between 400 and 500 (Fi gure 3 - 3 ). Hawaii, Nebraska, and Rhode Island all had fewer than 20 establishments in their states.**Figure 3**  **- 3**  **. 2002 Regional Distribution of Establishments: Electric Power Generation,**  **Transmission, and Distribution Industry (NAICS 2211)**  Source: U.S. Cen sus Bureau; generated by RTI International; using American FactFinder; “ Sector 22: Utilities: Geographic Area Series: Summary Statistics: 2002. ” <http://factfinder.census.gov>; (November 10, 2008) . As shown in Table 3 - 3, the four largest firms owned over 1,200 establishments and accounted for about 16% of total industry receipts/revenue. The 50 largest firms accounted for almost 6,000 establishments and about 78% of total receipts/revenue. Investor - owned energy

providers account ed for 67.5% of retail electricit y sold in the United States in 2006 (Table 3 - 4). In 20 10 , less regulated investor - owned electric utility companies were on average more profitable than companies with greater regulation (Table 3 - 5). In 2006, enterprises within NAI CS 2211 had a pre - tax pro fit margin of onl y 0.9% (Table 3 - 6). **3.2 Oil and Gas Extraction**  **3.2.1 Overview**  Oil and gas extraction (NAI CS 211) is an industry group within the mining sector (NAICS 21). It includes establishments that operate or develop oil a nd gas field properties **Establishments by State**

Less than 100 100 - 199 200 - 349 350 - 500 More than 500**Table 3 -**  **3. Firm Concentration for Electric Power Generation, Transmission, and**  **Distribution (NAICS 2211): 2002**

**Comm odity**  **Establishments Receipts/Revenue**  **Number of Employees**  **Employees per**

**Establishment Am**  **ount ($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; generated by RTI International; using American FactFinder; “ Sector 22: Utilities: Subject Series

—Estab & Firm Size: Concentration by Largest Firms for the United States: 2002. ” <http://factfinder.census.gov> ; (November 21, 2008). through such activities as exploring for oil and gas, drilling and equipping wells, operating on site equipment, and conducting other activities up to the point of shipment from the propert y. Oil and gas extraction consists of two industries: crude petroleum and natural gas extraction (NAICS 211111) and natural gas liquid extraction (NAICS 211112). Crude petroleum and natural gas extraction is the larger industry ; in 200 7 , it accounted for 93% of es tablishments and 75% of oil and gas extraction revenues. Industrial production in this industry is particularly

sensitive to hurricanes in the Gulf Coast. In September of both 2005 and 2008, production dropped 14% from the previous month. From 2002 to 200 7 , revenues from crude petroleum and natural gas extraction (NAICS 211111) nearl y doubled to $ 194 billion ($2007) (Table 3 - 8). At the same time, pay roll increased 55 % and the number of employ ees dropped b y al most 40 %. The number of establishments increas ed only

slightly (1 % ) ; as a result, the average establishment revenue nearl y doubled %. From 2002 to 200 7 , revenue from natural gas liquid extraction (NAI CS 211112) grew over 19 % to about $ 40 billion (Table 3 - 9). At the same time, pay roll increased by

onl y 1% and the number of emplo ye es dropped by almost 14 %. The number of establishments dropped by over 59 %, resulting in an increase of revenue per establishment of about 85 %.3-9 **Table 3 -**  **4. United States Reta**  **il Electricity Sales Statistics: 200**  **8 Full**  **- Service Providers**  **Other Providers Item**  **Investor -**  **Owned Public**  **Federal Cooperative**  **Facility Energy**  **Delivery Total**  Number of entities 3 62 1 25 1 NA NA 92 Nu mb er of retail customers 46,985 2,160,220 36 940,697 1 NA NA 3,147,939 Retail s a les (10 3 megawatthours) 2,257 70,303 9,625 21,868 117 NA NA 104,170 Percentage of retail sales 2 67 9 21 0

— — 100 Revenue f

rom retail sales ($10 6 ) 113 5,934 473 1,994 6 NA NA 8,520 Percentag e of revenue 1.33 69.65 5.55 23.41 0.07

— — 100 Average r etail price (cents/kWh) 5.01 8.44 4.91 9.12 5.25 NA NA 8.18 So urce: 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 20**  **10 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 regulatedb 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. “ Incom e 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 e nterprises a 1,187 Total receipts (10 3 ) $3 23,522,443 Net s ales(1 0 3 ) $328,017,143 Profit margin before t ax 3 .1% Profit margin after t ax 2.0 %

a Includes corporations with and w ithout net i ncome . Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “ Corporat ion 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 b y industry , location, and size of business. Throughout this section and report, we use the following definitions:

 Establishment : An establishment is a single ph ys ical location where business is conducted or where services or industrial operations are performed.3-12 **Table 3 -**  **7. Key Enterprise Statistics by Employee Size for Electric Power Generation, Transmissi on, and Distribution (NAICS** 

**2211): 2007**

**Variable All Enterprises**  **<20 Employee**  **s 2**  **0 –**  **99**

**Employee s**  **1 00**  **– 4**  **99**

**Employees 5**  **00 +** 

**Employee s**  Firms 1, 687 630 670 251 136 Establishments 9, 611 687 1,110 999 6,815 Em ployment 5 03,134 3,622 31,455 42,527 425,530 Receipts ($10 3 ) $ 440,342,284 $ 8,364,773 $ 21,825,969 $ 41,370,375 $ 368,781,167 Receipts/firm ($10 3 ) $ 261,021 $ 13,277 $ 32,576 $ 164,822 $ 2,711,626 Receipts/establishment ($10 3 ) $ 45,817 $ 12,176 $ 19,663 $ 41,412 $ 54,113 Receipts/employment ($) $ 875 $ 2,309 $ 694 $ 973 $ 867 Source: U.S. Census Bureau. 20 10 . “ Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size: 200 7 . ” <http://www.census.gov/csd/susb/susb0 7 .htm>.3 - 13

**Figure 3 -**  **4 .**  **Industrial Production Index (NAICS 211)**  Source: The Federal Reserve Board. “ Industrial Production and Capacity Utilization: Industrial Production ” Series ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G211.S <http://www.federalreserve.gov/datadownload/>. ( January 27, 2010) . **Table 3**  **- 8.**  **Key Statistics: Crude Petr oleum and Natural Gas Extraction (NAICS 211111):** 

**($2007) 2002**  **200 7**  Revenue ($10 6 ) 9 8,667 194,107 Payroll ($10 6 ) 5,785 8,988 Em ploy ees 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, including revenue earned from premiums, commissions and fees, rents, interest, dividends, and roy alties. Receipts exclude all revenue collected for local, state, and federal taxes. 75 80 85 90 95 100 105 1101997-011997-061997-111998-041998-091999-021999-071999-122000-052000-102001-032001-082002-012002-062002-112003-042003-092004-022004-072004-122005-052005-102006-032006-082007-012007-062007-112008-042008-092009-022009-072009-12**I n** **d e** **x V** **a l** **u e** **( J** **a n** **2 0** **0 2** **= 1** **0 0** **)**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 common ownership or co ntrol. The firm and the establishment are the same for single **Table 3**  **- 9.**  **Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) ($2007) 2002**  **200 7**  Revenue ($10 6 ) 3 3,57 9 39,978 Payroll ($10 6 ) 6 07 617 Em ploy ees 9,693 8,523 Establishments 5 11 321 Source: U.S. Census Bureau; 2002 and 200 7. ” <http://factfinder.census.gov>; ( February 2 3 , 20 12 ) . **Table 3**  **- 10.**  **Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002 Comm**  **odity Comm**  **odity Description Direct Requirements**  **Coefficients a**  V00200 Taxes on production and imports, less subsidies 8.93% V00100 Com

pensation 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 pow er generation, transmission, and distribution 1.47% 541300 Architectural, engineering, and related services 1.24% 532400 Commercial and industrial machinery and equipment rental and leasing 1.20% 33291A Valve and fittings other than plumbing 1.10% 541511 Custom computer programming services 0.99%

a These values show

the amount of the commodity required to produce $1.00 of the industry ’ s output. The values are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002 . 2002 Benchmark Input - Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. establishment firms. For each multiestablishment firm, establishments in the same industry within a state are counted as one firm; the firm emplo ym ent and annual pay roll are summed from the associated establishments.

 Enterprise : An enterprise is a business organization consisting of one or more domestic establishments that were specified under c ommon ownership or control. The enterprise and the establishment are the same for single - establishment firms. Each multiestablishment company forms one enterprise; the enterprise employ ment and annual pay

roll are summed from the associated establishments. Enterprise size3 - 15 designations are determined by the summed employ

ment 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 NAI CS 2111 11, 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 consid ered small businesses (Table 3 - 12). As shown in this table, l arge firms compose 29 percent of the firms, but account for 78 percent of employ ment and generate about 95 percent of estimated receipts. Enterprises within NAICS 211111 generated $ 194 billi on in total receipts in 200 7 . Enterprises within NAICS 211112 generated nearly $40 billion in total receipts in 2007. In cluding those enterprises without net income, NAI CS 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): 200**  **7** NAICS NAICS Description SBA Size Standard Sm all

Firms Large Firms Total Firms **Number of Firms by Firm Size**

Crude Petroleum and Natural Gas Extraction 500 6,329 95 6,424 **Total Employment by Firm Size** 55,622 77,664 133,286 **Estimated Receipts by Firm Size ($1000)** 44,965,936 149,141,316 194,107,252 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census reports firm counts for firms with receipts less than $7.5 million. **Employment and receipts could not be split betw een small and l arge businesses because of non - disclosure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the Unit ed 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): 200 7** 

NAICS Description SBA Size Standard Sm all

Firms Large Firms Total Firms **Number of Firms by Firm Size**

Natural Gas Liquid Extraction 500 98 41 139 **Total Employment by Firm Size** 1,875 6,648 8,523 **Estimated Receipts by Firm Size ($1000)** 2,164,328 37,813,413 39,977,741 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census reports firm counts for firms with receipts less than $7.5 million. **Employment and receipts could not be split betw een s mall and large businesses because of non - disclosure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size fo r the United States, All Industries: 2007.” <http://www.census.gov/econ/susb/>

**Table 3**  **- 13.**  **Aggregate Tax Data for Accounting Period 7/0 7**  **– 6/0**  **8 : 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 w ithout 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 (NAI CS 48 - 49), but more specifically in the pipeline3 - 17

transport ation 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 200 7 , natural gas transportation revenues fell by 10 % to just under $2 1 billion ($2 007) (Table 3 - 15). At the same time, payroll decreased b y 18 %, while the number of paid employ ees decreased by nearl y 32 %. T he number of establishments decreas ed b y 1 3 % from 1, 701 establishments in 2002 to 1, 479 in 200 7 . **3.3.2 Goods and Services Used**  The B EA reports pipeline transportation of natural gas onl y for total pipeline transportation (3 - digit NAI CS 486). In addition to pipeline transportation of natural gas (NAICS 4862), this industry

includes pipeline transportation of crude oil (NAICS 4861) and o ther pipeline transportation (NAI CS 4869 ) . However, the BEA data are likel y 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 -**  **1 4**  **. Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) ($2007)**  **Year 2002**  **200 7**  Revenue ($10 6 ) 2 2,964 20,797 Payroll ($10 6 ) 2, 438 2,064 Em ploy ees 3 2,542 24,683 Establishments 1, 701 1,479 Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48: EC0748I1: Transportation and Warehousing: Industry Series: Preliminary Summary Statistics for the United States: 2002 and 2007 .” http://factfinder.census.gov (January 27, 2010). In Table 3 - 1 5 , we use the latest detailed benchmark input - output data report by the BEA (2002 ) to identify

the goods and services used by pipeline transportation (NAI CS 486). As shown, labor, refineries, and maintenance requirements represent significant share of the cost associated with pipeline transportation. Power and equipment requirements potentially associated with reciprocating internal combustion engines (electric power generation and commercial and industria l machinery

and equipment repair and maintenance) 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 Am erican 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 Pip eline

Tr ans por ta tio n of Nat ural Gas 4869 Ot her Pip el in e Tr ans por ta tio n 4861 Pip el in e

Tr ans por ta tio n of Crud e Oil

72%

16% 12% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

4862 Pip eline

Tr ans por ta tio n of Nat ural Gas 4869 Ot her Pip eline Tr ans por ta ti on 4861 Pip el ine

Tr ans por ta ti on o f Crud e Oi l3 - 19

**Table 3 -**  **1 5**  **. Direct Requirements for**  **Pipeline Transportation (NAICS 486): 2002** 

**Comm odity**  **Comm odity Description**  **Direct Requirements**  **Coefficients a**  V00100 Com

pensation 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 w arm air heating equipment manufacturing 4.40% 561300 Em

ployment 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 w ork 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 pow er generation, transmission, and distribution 1.13%

a These values show

the amount of the commodity required to produce $1.00 of the industry ’ s output. The values are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002 . 2002 Benchmark Input - Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. According to 200 7 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 b y partnerships (Figure 3 - 7 ). Enterprises within pipeline transportation (NAICS 486) generated $ 11 . 1 billion in total receipts in 200 7 . Including those enterprises without net income, the industry averaged an after tax profit margin of 9 . 6 % (Table 3 - 1 6 ). The 200 7 SUSB shows that about half of all firms have fewer than 20 employ ees, but only 1% of all employ ees in this industry . Firms with more than 500 employ ees generate 89 % of all receipts in this industry (Table 3 - 1 7 ).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>; (December 12, 2008). **Table 3**  **- 1**  **6 .**  **Aggregate Tax Data for Accounting Period 7/0 7**  **– 6/0**  **8 : 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 c orporations with and without net i ncome . 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%

Co rp or at io ns In di vid ual Pr opr ie to rs hi ps Pa rt ners hi ps3 - 21

**Table 3**  **- 1**  **7 .**  **Key Enterprise Statistics by Employee**  **Size for Pipeline Transportation of**

**Natural Gas (NAICS 48621): 200 7** 

**Variable All Enterprises**  **<2 0**  **Employee s**  **2 0**  **– 99** 

**Employee s**  **1 00**  **– 4**  **99**

**Employee s**  **500+ Employee**  **s** Firms 126 63 12 9 42 Establishments 1.479 66 26 7 0 1,317 Em ployment 24,683 241 3 8 2 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. 20 11 . Firm Size Data from the Statistics of U.S. Businesses, U.S. All Industries Tabulated by Em

ploy ee Size: 200 7 . http://www2.census.gov/csd/susb/200 7 /usalli_r0 7 .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 (NAI CS 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 - ray s, clinical laboratory work, and pharmacy

services. From 2002 to 200 7 , hospital revenues grew about 21 % to over $ 65 0 billion ($2007) (Table 3 - 18 ). At the same time, pay roll rose about 15 %, while the number of employ ees increased b y only 6 %. The number of establishments increased during this period by almost 4 %, resulting in an increase in revenue per establishm ent 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 ps yc hiatric and substance abuse hospitals (NAICS 6222) and specialty hospitals (NAI CS 6223). However, these data3 - 22

should be representative of the affected sector since in 200 7 , general medical and surgical hospitals accounted for 92% of NAICS 622 establishments and 94% of revenues. In Table 3 - 1 9 , we use the latest detailed benchmark input - output data report by the BEA (2002 ) to identify

the goods and services used by hospitals (NAI CS 622). As shown, labor and land requirements represent a significant share of the value of hospital services. Powe r 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**  **200 7**  Revenue ($10 6 ) 539,502 651,639 Payroll ($10 6 ) 209,063 240,638 Em ploy ees 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 200 7. ” <http://factfinder.census.gov>; (February 22 , 20 12 ) . **Table 3**  **- 19**  **. Direct Requirements for Hospitals (NA**  **ICS 622): 2002 Comm**  **odity Comm**  **odity Description Direct Requirements**  **Coefficients a**  V00100 Com

pensation of employees 51.90% 531000 Real estate 10.76% 550000 Management of companies and enterprises 4.02% 621B00 Medical and diagnostic labs and outpatient and other ambulatory care

services 2.22% 561300 Em

ployment services 1.90% 325412 Pharm aceutical preparation manufacturing 1.86% 325413 In - vitro diagnostic substance manufacturing 1.66% 524100 Insurance carriers 1.66% 420000 Wholesale trade 1.62% 221100 Electric pow er 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 Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. **3.4.3 Business Statistics**  In 20 10 , the United States had 5,754 hospitals (Table 3 - 2 0 ) . As shown in Table 3 - 1, nongovernmental not - for - profit hospitals accounted for 2,904 (or 5 0 % ) of these hospitals, and State and local government hospitals accounted for 1,068 (or 19 % ) of the se hospitals.3 - 24

General medical and surgical h ospitals (NAICS 622 1 ) generated $ 652 billion in total receipts in 200 7 . Including those enterprises without net income, the industry averaged an after tax profit margin of 3.1% (Table 3 - 2 2 ). Also, each firm in this industry had an average of about $202 million in revenue and a great majorit y 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>; (Nov em ber 21, 2008). **Table 3**  **- 2**  **0 .**  **Data for General Medical and Surgical Hospitals (NAICS 6221): 200**  **7**

**Comm odity**  **Establishments Am**  **ount ($10**  **6 )**  **Number of**

**Employees Employees per** 

**Establishment** All firms 5, 404 $ 651,639 5,041,848 9 33 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%

Co rp or

at io ns Pa rt ners hip s In di vi du al Pr opr ie to rs hip s Ot her Leg al Fo rm s

of O rg aniz at io n3 - 25

**Table 3**  **- 2**  **1 .**  **Hospital Statistics :**  **20 10** 

**Hospitals Number**  Total 5,754 Nongovernment not - for profit 2,9 04 Investor - owned (for - profit) 1,013 State and local government 1, 068 Federal government 213 NA = Not a vailable Source: American Hospital Association. 20 11 . “ AHA Hospital Statistics: 20 10 Edition. ” Health Forum. **Table 3**  **- 2**  **2 .**  **Aggregate Tax Data for Accounting Period 7/05**  **– 6/06: NAICS 622**  **- 4**  Number of e nterprises a 18,263 Total receipts (10 3 ) $ 108,074,793 Net sales(10 3 ) $ 102,300,229 Profit margin before t ax 4.4% Profit margin after t ax 3.1%

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

**Table 3 -**  **2 3**  **. Key Enterprise Statistics by**  **Employee Size for General Medical and Surgical** 

**Hospitals (NAICS 6221): 200 7**  **($2007)**

**Variable All** 

**Enterprises <20**  **Employees 20**  **- 99**  **Employee s**  **100 -**  **499**

**Employee s**  **500+ Em ployee**  **s** Firms 3 ,225 170 2 77 1,227 1,551 Establishments 5, 404 173 282 1,286 3 , 6 63 Em ployment 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 $2 1,687 $ 169,7663 - 26

Receipts/employment ($) $ 129 $571 $83 $ 95 $ 132 Source: U.S. Small Business Administration (SBA). 20 10 . “Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size: 200 7 .” <http://www.census.gov/csd/susb/susb0 7 .htm>.

**3.5 Irrigation Sets and Welding Equipment**  **3.5.1 Overview**  The U.S. Economic Census classifies irrigation 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 and equipment and other turf and grounds care equipment, including planting, harvesting, and grass mowing equipment (except lawn and garden ty pe). From 2002 to 200 7 , farm machinery and equipment manufacturing revenues increased by $ 8 billion from $1 5 billion to $ 23 billion (Table 3 - 2 4 ). At the same time, pay roll increa sed b y 21 % and the number of paid employ ees incr eased by nearl y 9%. The number of establishments dropped b y 2 % from 1, 214 establishments in 2002 to 1, 191 in 200 7 . 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 200 7 welding and soldering equipment manufactu ring revenue increased by about 53 % to nearl y $ 6 billion (Table 3 - 2 5 ). At the same time, pay roll in creased b y 1 2 % and the number of paid employ ees in creased b y nearly 9 %. The number of establishments increas ed by 31 % from 250 establishments in 2002 to 3 03 in 200 7 . **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 industrial consumers of this equipment.3 - 27

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) 200 8 Farm and Ranch Irrigation Survey (USDA - NASS, 20 10 ) shows3 - 283-283 - 29

**Table 3**  **- 2**  **4 .**  **Key Statistics: Farm Machinery and Equipment Manufacturing (NAICS**

**333111) ($2007) 2002**  **200 7**  Revenue ($10 6 ) $ 15,006 $ 23,009 Payroll ($10 6 ) $ 2,132 $2, 580 Em ploy ees 53,817 5 8,838 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 90 100 110 120 130**I n** **d e** **x V** **a l** **u e** **s (** **J a** **n -** **9 7** **= 1** **0 0** **) In**  **dust rial P**  **roducti on**  **In dex (**  **NA IC**  **S 3331**  **11 )** 3 - 30

**Table 3**  **- 2**  **5 .**  **Key Statistics: Welding and Soldering Equipment Manufacturing (NAICS** 

**333992) ($2007) 2002**  **200 7**  Revenue ($10 6 ) $ 3,880 $ 5,935 Payroll ($10 6 ) $ 811 $ 910 Em ploy ees 16,128 1 7,529 Establishments 2 31 303 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 , 20 12 ) . that the top five states ranked by total acres irrigated 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 5 46 ,000 pumps were used on U.S. farms in 200 8 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 t ype, and natural gas was the most expensive in 200 8 ($ 93 per acre for well sy stems and $ 4 4 per acre for surface water sy stems) (Table 3 - 2 6 ). Sy stems using diesel fuel were operated at approximately half of these per - acre costs ($ 54 per acre for well s ys tems and $ 42 per acre for surface water s ys tems). Gasoline - and gasohol - powered s ys tems offered the least expensive operating costs for well sy stems ($ 39 per acre ) and electricit y - power s ys tems offered the least expensive operating c osts for surface water s ys tems ( $ 45 per acre ). As shown in Table 3 - 27 , the number of on - farm pumps increased to 5 46 , 308 from 4 89,434 ( 12 %) between 2003 and 200 8 . T he use of electric - and diesel - powered pumps increased during this period ( 21 % and 3 %, respe ctively), while other fuel sources such as liquid petroleum ( LP ) gas, propane, and butane declined significantly (31%) . It should be noted that the acreages included in Table 3 - 27 incorporate both irrigated and non irrigated land.3 - 31

**Table 3**  **- 2**  **6 .**  **Expenses pe r Acre by Type of Energy: 200**  **8**

**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 $ 3 6. 13 Source: U.S. Department of Agriculture, National Agricultural Statistics Service. 20 10 . “ 200 8 Farm and Ranch Irrigation Survey. ” Washington, DC: USDA - NASS. Table 20. Found on the Internet at http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Farm_and_Ranch_Irrigation_Survey/fri s08_ 1_20.pdf . **Table 3**  **- 27**  **. Number of On**  **- Farm Pumps of Irrigation Water by Type of Energy:**  **2003 and** 

**200 8**  **Fuel Type 2003**  **200 8**  **Percentage Change** Electricity 312,145 3 77,492 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 Agricultural Statistics Service. 20 10 . “200 8 Farm and Ranch Irrigation Survey.” Washington, DC: USDA - NASS. Table 20. Found on the Internet at http://www.agcensus.usda.gov/ Publications/2007/Online_Highlights/Farm_and_Ranch_Irrigation_Survey/fris08_ 1_20.pdf N o information is available on the use and construction of on - farm pumps specificall y. USDA reports that planted acres of the eight major crops hit a 5 - ye ar high of 252 mi llion acres in 2008 but will fall and level off to around 244 million acres over the next 2 to 4 y ears (USDA, 2008 ). 3.5.2.2 Welding Welding is used in a wide variet y of applications. One of the b iggest manufacturers of welding products identifies the following key end - user segments:

 general metal fabrication;3 - 32  infrastructure including oil and gas pipelines and platforms, buildings, bridges, and power generation;

 transportation and defense industrie s (automotive, trucks, rail, ships, and aerospace);

 equipment manufacturers in construction, farming, and mining;

 retail resellers; and

 rental market (L incoln Electric Holdings, 200 6 ). 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, construction, and mining machinery manufacturing (NAICS 3331) generated $ 8 8 billion of total receipts in 200 7 , while those in other general purpose machinery

manufacturing (NAICS 3339) generated $ 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 Accounting Period 7/05**  **– 6/06: NAICS 3331**  **and 333 9**  **Agriculture, Construction, & Mining Machinery Manufacturing**  **Other Ge neral Purpose Machinery**  **Manufacturing** Number of e nterprises a 3,064 6,231 Total receipts (10 3 ) $ 88,255,496 $ 85,653,046 Profit margin before t ax 9.1% 6.1% Profit Margin after t ax 6.9% 4.7%

a Includes c or

porations with and without net i ncome . 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 distribution for a repr esentative sector in this section (NAICS 2 3 7, Heavy and Civil Engineering Construction); other subsections in Section 3 cover other sectors that potentially use equipment powered b y diesel engines (e.g., power generation and offshore gas distribution). As shown in Table 3 - 29 , SUSB data suggest that more than 80% of firms are below the Small Business Administration (SBA) small business size3 - 33

standard for this industry. However, it is not clear what fraction of these firms use stationary diesel engines.3-34 **Table 3**  **- 29**  **. Key Enterprise Statistics by Receipt Size for Heavy Construction:**  **200 7**  **a**

**Variable All Enterprises**  **<20 Employees**  **2 0**  **– 99** 

**Employee s**  **1 00**  **– 4**  **99**

**Employee s**  **5 00**  **+** Firms 49,228 4 0,654 6,79 3 1,422 359 Establishments 51,421 40 ,670 6,947 1,847 1 ,987 Em ployment 1,016,407 183,487 273,867 238,342 320,71 1 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 $2 22,579 Receipts/establishment ($10 3 ) $ 5,133 $ 1,150 $ 9,800 $ 37,461 $ 40,214 Receipts/employment ($) $ 260 $ 255 $ 249 $ 290 $ 249

a 200 7 SUSB . The most comparable 200 7 NAICS code for this industry is 237. Source: U.S. Census Bureau. 20 12 b . Firm Size Data from the Statistics of U.S. Businesses, U.S. All Industries Tabulated by Receipt Size: 200 7 . http://www2.census.gov/csd/susb/2007/usalli_r07.xls .4 - 1 **SECTION 4 REGULATORY ALT**  **ERNATIVES, COSTS, AN D EMISSION IMPACTS**  **4.1 Background**  This section of the RIA includes a discussion of the regulatory alternatives considered for the proposed reconsidered rule, the costs associated with these regulatory alternatives, and the impacts on affect ed emissions (both HAP and non - HAP). All impacts presented are for the ye ar of full implementation , 2013. Costs in the chapter are in 20 0 8 $. Costs in 2010$ shown in other parts of the RIA are updat ed values of these 2008$. Although the estimates presented are annualized, they

should be understood as a “snapshot” in anal yz ing costs. Annualized costs are estimated as equal for each y ear that control equipment is operated. After promulgation of the 2010 RI CE NESHAP amendments, the EPA received sever al 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 i nformation and believes that amendments to the rule to address certain of these issues are appropriate. Therefore , the EPA is proposing amendments to NESHAP for stationary RI CE signed in March 2010 for CI engines and August 2010 for SI engines under section 112 of the Clean Air Act. This proposal was developed to address certain issues that have been raised b y different stakeholders through lawsuits, several petitions for reconsideration of the 2010 RI CE NESHAP amendments and other communications. The propos ed amendments include alternative testing options for certain large spark ignition (generally

natural gas - fueled) stationary reciprocating internal combustion engines, management practices for a subset of existing spark ignition stationary reciprocating internal combustion engines in sparsel y populated areas, and alternative and less burdensome monitoring and compliance options for the same engines in populated areas. The EPA is also proposing to include a limited temporary allowance for existing stationary emergency area source engines to be used for peak shaving and non - emergency demand response as part of the pre - existing allowance for such engines to be used for non - emergency use for 50 hours annuall y. In addition, the EPA is proposing, in both the NESHA P and in the new source performance standards for stationary

internal combustion engines to increase the hours that stationary emergency

engines may

be used for emergency

demand response. The proposed amendments also correct minor mistakes in the pre - exist ing regulations. EPA has taken several actions over the past several y ears to reduce exhaust pollutants from stationary

diesel engines, but believes that further reducing exhaust pollutants from4 - 2

stationary diesel engines, particularl y existing stationary d iesel engines that have not been subject to f

ederal standards, is justified. Therefore, EPA is issuing this rulemaking that reconsiders the 2010 final rule requiring emissions reductions from exist ing stationary diesel engines. The full preamble for the fi nal C I RICE NESHAP and the rule itself can be reviewed at http://www.epa.gov/ttn/atw/rice/fr03mr10.pdf .

**4.2 Summary of the Proposed**  **Reconsideration Rule**  4.2.1 Proposed Amendment - Emergency Demand Response/Peak Shaving 4.2. 1. 1 Background This action proposes to amend provisions in the RICE NESHAP that currently allow owners and operators to operate stationary emergency

engines for up to 15 hours per y ear as part of a demand respo nse program if the RTO or equivalent balancing authority and transmission operator have determined there are emergency conditions that could lead to a potential electrical blackout, such as unusually low frequency , equipment overload, capacit y or energy de ficiency , or unacceptable voltage level. The final rule did not allow emergency engines to be used for purposes of peak shaving or other non - emergency purposes as part of a financial arrangement. These provisions were included in the RI CE NESHAP when requi rements for existing stationary CIengines were finalized on March 3, 2010 (75 FR 9648). Following the completion of that portion of the rule, the EPA received three main petitions for reconsideration. One petition was from CPower, Inc., Energy Connect, Inc ., EnerNOC, Inc., and Innoventive Power, LL C. (EnerNOC et al.)(EPA - HQ - OAR - 2008 - 0708 - 0404). Another petition was received from the Delaware Department of Natural Resources and Environmental Control (DE DNREC) (EPA HQ - OAR - 2008 - 0708 - 0400). The third petition was from the National Rural Electric Cooperative Association (NRECA) (OAR - 2008 - 0708 - 0580). In addition to these main petitions the EPA received a substantial number of letters from others in the electric generation industry . The petition from EnerNOC, et al., asked that EPA increase the period of time permitted for emergency

demand response operation in the rule to 60 hours per ye ar, or the minimum number of hours required by the emergency demand response program. By contrast, the DE DNREC petition asked EPA to reconsider the emergency demand response provision because of the adverse effects that it believes would result from increased emissions from these engines.4 - 3

The petition from NRECA requested that the EPA eliminate the restriction on the use of stati onary emergency

engines for demand response purposes. The EPA granted the petitions from EnerNOC, et al., DE DNREC and NRECA, and issued a notice on December 7, 2010 (75 FR 75937), requesting comments on whether to amend the 15 hours per ye ar limitation on the operation of stationary

emergency

RICE participating in emergency demand response programs. The EPA received more than 120 comments from a number of different entities including various state agencies, utilities, electric cooperatives and industry or ganizations. Many commenters expressed that 15 hours per ye ar is not sufficient to meet current emergency demand response requirements for participation. For example, several emergency demand response programs have I SO tariff requirements greater than 15 h ours per ye ar, including the Electric Reliability

Council of Texas emergency demand response program, which has a tariff requirement of 24 hours per year; the Penns yl vania Jersey Mary land (“PJM”) Interconnection, known as the Emergency L oad Response Program, which has a tariff requirement of 60 hours per year; and the ISO New England (“ISO - NE”), which forecasts that backup resources would be expected for 55 hours over a 12 - month period. Tariff requirements are developed to specify the mandatory

time load re sources (engines) must be willing and able to operate if the units are enrolled in the program. Conversel y, some commenters urged the EPA to allow stationary emergency

engines to only

operate during true emergencies or when voltage or frequency varies bey o nd specified parameters. Based on the EPA’s review of the petitions and comments that the EPA has received, the EPA has found it appropriate to propose to amend the current rule to increase the allowance for stationary emergency

engine participation in e mergency demand response programs to up to 100 hours per ye ar, which would be included as part of the pre - existing allowance of 100 hours for owners of emergency

engines to test and maintain their emergency engines. The EPA believes that the emergency

demand response programs that exist across the country are important programs that protect the reliability and stability

of the national electric service grid. Allowing stationary emergency

engines to operate as part of emergency demand response programs can h elp prevent grid failure or blackouts, b y allowing these engines to be used in circumstances of grid instability

prior to the occurrence of blackouts. Preventing stationary emergency

engines from being able to qualify and participate in emergency demand re sponse programs without having to appl y aftertreatment could force owners and operators to leave their engines out of these programs, which will impair the ability of IS Os and RTOs to use these relativel y small, quick - starting and reliable sources of energ y to protect the reliability of their systems. The EPA does not wish to potentially jeopardize electrical reliability or create a disincentive for stationary4 - 4

emergency

engines to participate in these programs. The circumstances during which the EPA would a llow stationary

emergency

engines to operate for emergency demand response purposes include periods during which the regional transmission authority or equivalent balancing authority and transmission operator has declared an Energy Emergency

Alert Level 2 (EEA Level 2) as defined in the North American Electric Reliability Corporation Reliability

Standard EOP - 002 - 3, Capacit y and Energy Emergency, plus during periods where there is a deviation of voltage or frequency

of 5 percent or more below standard voltag e or frequency . During EEA Level 2 alerts there is insufficient energy suppl y and a true potential for electrical blackouts. Sy stem operators must call on all available resources during EEA Level 2 alerts in order to stabilize the grid to prevent failure. Therefore, this situation is a good indicator of severe instability on the s ys tem. Consistent normal voltage provided by the utility is often called power quality and is an important factor in local electric sy stem reliabilit y. Reliability of the s ys tem re quires electricit y being provided at a normal expected voltage. The American National Standards Institute standard C84.1 - 1989 defines the maximum allowable voltage sag at below 5 percent. On the local distribution level local voltage levels are therefore i mportant and a 5 percent or more change in the normal voltage or frequency is substantial and an indication that additional resources are needed to ensure local distribution sy stem reliability . This situation would be indicative of severe instability on th e s ys tem. Emergency

demand response programs rel y on agreements under which owners of engine agree to make their engines available to be called upon for a specific number of hours per ye ar, as required b y the relevant I SO or RTO tariff, under specified ci rcumstances considered to indicate emergencies. In order to be enrolled in an emergency demand response program, participants must qualify

their engines and must be able to use their emergency engines for the number of hours the program requires. Engines are not generall y called upon for the maximum hours required b y the tariffs. However, even though the engine may not be called at all or may run for fewer hours than the program requires it to be available in a particular year, the engine must still be avai lable for those theoretical number of hours in order to join the program. Demand response contracts require more hours than the 15 hours per y ear that is currentl y in the regulations, and the commenters state that the 15 hours per ye ar is not a sufficient amount of time to ensure the reliability of the program; some programs require up to 60 hours per y ear, as discussed earlier. For these reasons, the EPA believes it is appropriate to allow additional hours for emergency

demand response operation in order f or such programs to be accessible to stationary emergency

engines. Consequently , the EPA is proposing amendments to the rule to increase the limitation on emergency demand response operation to 100 hours per y ear for stationary emergency

engines. It is exp ected that owners and operators of stationary emergency4 - 5

engines that seek to qualify their units as demand resources would with the proposed increase to 100 hours per ye ar be able to meet the operational and qualification requirements of the different ISOs and RTOs in the country . As stated, stationary

emergency

engines that participate in demand response programs may not be called upon at all, but must nonetheless be available to operate for the required amount stipulated by

the specific program. The pur pose of the limited allowance for demand response is to respond to emergencies, and the EPA is persuaded b y the information that has been submitted that 15 hours per ye ar is an insufficient amount of time to allow for emergency demand response needs, given past experience. The EPA believes 100 hours per y ear is sufficient to cover an y potential demand response operation as well as the required maintenance and testing that is also included within the 100 hours of operation. The EPA has previousl y determined that stationary emergency

engines t yp ically

operate well below 50 hours per y ear and more commonly about 1 to 2 hours per month. A survey conducted b y the California Air Resources Board (CA ARB) indicated the average ye arl y operation for emergency

diesel engines was 31 hours over a period of 3 ye ars. The majorit y of those hours were for the purpose of maintenance and testing; less than 5 hours was for interruptible service contracts, and the remaining amount for emergency /standby operation (EPA - HQ - OAR - 2005 - 0029 - 0011). Data from demand response programs in I SO - NE and PJM territories show that backup generation was dispatched for less than 30 hours during the summers of 2008, 2009 and 2010. However, again, emergency units must be available to operate more than that in most cases to qualify

for demand response programs. For instance, PJM requires a minimum I SO tariff of 60 hours per ye ar of engine availability for program participation. Consequently , in order to ensure that a sufficient amount of operating ti me is available for maintenance and readiness testing, and for demand response operation, the EPA is proposing 100 hours of operation. A number of commenters requested that an allowance of 100 hours per ye ar be allowed in order to provide adequate hours co nsistent with minimum required hours that customers must be available to operate and to address local distribution sy stem emergencies. For instance, in Hawaii, the emergency

demand response program operated b y the Hawaiian Electric Compan y requires that em ergency

engines be able to operate for 100 hours per y ear in the event of an emergency

in order to participate in the program. In order to provide a sufficient amount of time to cover annual maintenance and testing, which is ty picall y more than 20 hours pe r ye ar according to the survey

conducted by

CA ARB (see EPA - HQ - OAR - 2005 - 0029 - 0011), plus to cover hours necessary

for qualifying for emergency demand response programs or local4 - 6

distribution sy stem emergencies, EPA believes an allowance of 100 hours per y ear would be appropriate for these activities. Taking into account that there may be situations where annual maintenance and testing could exceed the t ypical 1 to 2 hours per month and accounting for other emergency

demand response programs that require more than 60 hours per y ear for program participation (e.g., the Hawaiian Electric Compan y), the EPA believes that 100 hours per ye ar is appropriate for emergency demand response plus maintenance and testing. The proposed amendment to the rule would mean that stationary emergency

engines could operate for a total of 100 hours per ye ar for emergency demand response operation as part of the 100 hours alread y permitted for maintenance and readiness testing while maintaining their status as emergency

units, rather than non - emergency units, and continue to meet the requirements that appl y t o emergency engines. On the issue of peak shaving and non - emergency demand response, the EPA is proposing to include a temporary

limited allowance for peak shaving and other t ype s of non - emergency use as part of a financial arrangement for existing stationary emergency

engines at area sources of HAP, if the peak shaving is done as part of a peak shaving (or load management) program with the local distribution sy stem operator. The power generated under this allowance can onl y be used at the facility

or towards the local s ys tem. The EPA has determined that it is appropriate to include the option for existing stationary emergency

engines at area sources to operate for a small number (50) of hours per ye ar for an y non - emergency

reason to generate income locally and not be penalized or considered a non emergency

engine and subsequently required to install aftertreatment that could be prohibitively costly for these sources in the near t erm. The EPA is proposing that the 50 - hour allowance for peak shaving for emergency engines at area sources be allowed for a limited period of time, but then removed after April 16, 2017. The peak shaving would also be limited to operation as part of a peak shaving (load management program) with the local distribution sy stem operator. Owners would still have the pre - existing 50 hours per year allowance for non - emergency operation after April 16, 2017, but those 50 hours could no longer be used for peak shav ing. The temporary

allowance for peak shaving would give sources time to address reliability issues and develop solutions to reliability issues while facilities are coming into compliance with the National Emission Standards for Hazardous Air Pollutants From Coal and Oil - Fired Electric Utility Steam Generating Units, which were promulgated on February 16, 2012 (77 FR 9304). This limited allowance would allow the owners and operators of these engines more flexibility to run reliability

critical units in o rder to minimize potential grid - related interruptions as coal - and4 - 7

oil - fired baseload power plants may be temporarily

shut down to install emission controls to comply with the NESHAP From Coal and Oil - Fired Electric Utility Steam Generating Units. In cludi ng this allowance is important for small electric cooperatives and other entities located at area sources that use these engines to maintain voltage and electric reliability . Man y rural electric cooperatives enter agreements with owners of small emergency engines and rely on the engines to reduce demand on the central power supply during periods of high demand , which reduces the cost of power during periods of high demand for the members of the cooperative. Commenters promoting the continued use of peak shaving programs said that maintaining the cost of power as low as possible is important across the country , but is particularl y of significant importance to rural electric cooperatives that, according to the commenter, service customers in the most economica lly depressed areas of the country , where options are the most limited . The commenters argued that if small emergency engines would no longer be permitted to operate for peak shaving purposes without having to be reclassified as non - emergency

engines and s ubsequently subject to costly

emissions controls, owners could no longer afford to participate in such programs. Cooperatives argued that this would lead to increased costs that would ultimately be passed along to the customers. Commenters also maintained that keeping peak shaving programs would not lead to additional public health risks or emissions because the operation for peak shaving is minimal. If peak shaving is not allowed under the rule, commenters said that this would lead to an increase in centra l power station capacity and possibly

more transmission and distribution line capacit y to accommodate the increase in demand resulting from eliminating small emergency engines from being used. This could lead to a larger impact on the environment and publi c health than allowing a small number of hours for peak shaving purposes. Certain small and remote facilities also rely on financial programs to generate additional income in order to maintain their engines and stay in operation. The additional funds can b e essential for man y smaller facilities and operations. Providing a limited allowance for peak shaving and non - emergency demand response could generate sufficient income to prevent small facilities and owners from ceasing operation where these engines are in service. In order to further limit the operation of these engines to small, remote facilities, the EPA is proposing that the power generated under this allowance can only be used at the facilit y or towards the local system. In addition, while the EPA is proposing this allowance until the end of April 16, 2017, the EPA does not believe it is appropriate to continue the program bey ond that time. Generators receive considerable compensation for their availability in peak shaving programs and the EPA believe s that it is not appropriate to allow these engines to continue receiving compensation for this non - emergency use bey ond 2017 without having to reduce their emissions. The generators must by that time decide whether to restrict their use to4 - 8

emergency

or li mited non - compensated non - emergency use or to reduce the emissions from their engines. The EPA also encourages engine owners and operators, as well as larger s ys tem planners, to consider the use of alternative peak shaving options, such as load curtailment s, lower emitting distributed generation, combined heat and power, and reduced line losses on the electricit y grid. The previous estimate of emissions from stationary emergency engines is not expected to change due to this proposed limited allowance. To estimate emissions from stationary emergency engines, the EPA has previously estimated that emergency engines would on average operate for 50 hours per ye ar. There is a wide range in how much these engines operate (some well below 50 hours per ye ar), but on average and to be conservative, the EPA believes that 50 hours per y ear is still representative and consequently the environmental impact the EPA has calculated previously

remains appropriate. In consideration of all these issues , the EPA is proposing amendments to the rule to provide a limited allowance for peak shaving for existing stationary emergency

engines at area sources of HAP. The specific amendments the EPA is proposing are discussed below. 4.2.1. 2. What are the Proposed Amendments ? 4.2.1.2.1 Emergency

Demand Response. T he EPA is proposing to revise the current provisions for stationary engines used for emergency

demand response operation. The provisions the EPA is proposing to amend are in §§63.6640(f) and 63.6675 of 40 CFR part 63, subpart Z ZZZ. Currently , §63.6640(f)(1)(iii) allows a maximum of 15 hours per ye ar to be spent towards demand response operation under certain qualifying conditions. Also, §63.6640(f)(1)(ii) currently includes an allowance of 100 hours per ye ar for purposes of maintenance checks and readiness testing. The EPA is proposing that owners and operators of stationary emergency

RI CE be permitted to operate their engines as part of an emergency

demand response program within the 100 hours per y ear that is permitted for maintenance and testing in §63.6640(f)(1)(ii). Owners and operators of stationary emergency engines can operate for emergency demand response during periods in which the regional transmission authority

or equivalent balancing authority and transmission operato r has declared an EEA Level 2 as defined in the North American Electric Reliability Corporation Reliability Standard EOP - 002 - 3, Capacity and Energy

Emergency

and during periods where there is a deviation of voltage or frequency of 5 percent or greater belo w standard voltage or frequency . The hours spent for emergency demand response operation are added to the hours spent for maintenance and testing purposes and counted towards the 100 hours per year. If the total time4 - 9

spent for demand response operation and maintenance and testing exceeds 100 hours per y ear the engine will not be considered an emergency engine under this subpart and will need to meet all requirements for non - emergency engines. The EPA is recognizing that these engines may be called to operat e not only by the regional transmission operator or equivalent to maintain the reliability of the bulk power s ys tem, but also by the local transmission and distribution sy stem operators to support the local power s ys tems. For stationary

emergency engines above 500 HP that were installed prior to June 12, 2006, there is currentl y no emergency demand response allowance and there is no time limit on the use of emergency

engines for routine testing and maintenance in §63.6640(f )(2)(ii). Those engines were not the focus of the 2010 RI CE NESHAP amendments; therefore, the EPA did not make an y changes to the requirements for those engines as part of the 2010 amendments. For consistency , the EPA is now also proposing that owners and operators of stationary emergency engines installed prior to June 12, 2006, be permitted to operate their engines as part of a demand response program as well for a total of 100 hours per year, including time spent for maintenance and testing. The EPA is also proposing to amend the NSPS for stationary CI and SI engines in 40 CFR part 60, subparts IIII and JJJJ, respectivel y, to provide the same allowance for stationary emergency

engines for emergency

demand response operation as for engines subject to the RI CE NESHAP. The NSPS regulations currentl y do not include such an allowance for emergency demand response operation. For the reasons discussed as to wh y the EPA finds it appropriate to allow stationary

emergency

engines to participate in emergency demand response programs and remain being considered emergency units, and for consistency across engine regulations, the EPA is proposing to add an emergency demand response allowance under the NSPS regulations. Consequently , the EPA is proposing to revise the ex isting language in §§60.4211(f) and 60.4219 of 40 CFR part 60, subpart IIII, and §§60.4243(d) and 60.4248 of 40 CFR part 60, subpart JJJJ, to specify that emergency

engines may

participate in demand response programs for up to 100 hours per ye ar, including hours spent towards maintenance and testing of the emergency engines. 4.2.1.3 Peak Shaving and other Non - emergency U se as Part of a Financial Arrangement . In addition to the changes the EPA is proposing related to emergency demand response operation, the EPA is also including a further provision for owners and operators of existing stationary emergency

RICE located at area sources. Paragraph §63.6640(f) currentl y allows owners and operators of emergency stationary

RICE to operate their engine for 50 hours per y ear in non - emergency

situations. As currentl y written, the 50 hours per ye ar for non - emergency4 - 10

situations cannot be used for peak shaving or to generate income for a facility to supply power to an electric grid or otherwise supply power as part of a financial arrangement with another entity ; except that owners and operators of certain emergency engines may

operate the engine for a maximum of 15 hours per y ear as part of an emergency demand response program. As discussed, the 15 hours per ye ar allowanc e for emergency engines to participate in emergency demand response programs is being increased to 100 hours per y ear, but will also include hours spent towards maintaining and conducting readiness testing of the emergency engines. However, additionally , the EPA is also proposing that stationary emergency

engines located at area sources be permitted to appl y the 50 hours per ye ar that is currentl y allowed under §63.6640(f) for non emergency

operation towards an y non - emergency operation, including operation as part of a financial agreement with another entit y. The peak shaving allowance would expire in 2017. The EPA is specify ing that the power can onl y be used at the facilit y or towards the local system, and the engine can only

be operated for peak shaving a s part of a program with the local distribution sy stem operator. The EPA is also clarify ing that an engine that exceeds the calendar y ear limitations on non - emergency operation, including emergency demand response or peak shaving, will be considered a non - emergency engine and subject to the requirements for non - emergency engines for the remaining life of the engine. 4.2.1.4 . Proposed Amendment - Stationary Agricultural RI CE in San Joaquin Valley In the 2010 amendments to the RI CE NESHAP, the EPA required existing non emergency

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 abov e 500 HP. The requirements also included testing and monitoring provisions. As with all requirements for existing engines in that rule, owners and operators were required to meet the requirements within 3 ye ars of the effective date of the regulations (May 3, 2013). Since the finalization of the 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 engi nes in the San Joaquin Valley . The San Joaquin Valley

Air Pollution Control 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, would not be able to comply with the applicable RI CE NESHAP emission standards for existing engines without further testing and monitoring, and possible4 - 11

retrofit with further controls, due to differences in the emission standards and te sting protocols in the RI CE NESHAP versus the Tier 3 standards in 40 CFR part 89. However, an identical engine certified to the Tier 3 standards (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. Stationary 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 th e standards in 40 CFR parts 89, 94, 1039, and 1042, as applicable. Thus, a 2006 model y ear 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 an y such engine. The EPA believes that the T ier 3 standards (Tier 2 for engines above 560 kW) are technologicall y stringent regulations and believes it is unnecessary to require further regulation of engines meeting these standards. In order to address this concern, the EPA is proposing changes to amend the requirements for an y 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 proposing amendments to specify that an y existing certified Tier 3 (Tier 2 for en gines above 560 kW) CIengine that was installed before June 12, 2006, is in compliance with the NESHAP. This amendment would include an y existing stationary Tier 3 (Tier 2 for engines above 560 kW) certified CI engine located at an area source of HAP emis sions. 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 regulated as existing sources under the NESHAP must be replaced in the next few y ears, onl y a short time after the emission standards for existing engines must be met. Specificall y, the San Joaquin Valley APCD rule for internal combustion engines (Rule 4702) requires Tier 1 an d Tier 2 certified engines to meet Tier 4 standards by January 1, 2015, or 12 ye ars after the installation date, but no later than June 1, 2018. The concern is that owners and operators of these engines would have to install aftertreatment b y 2013 to meet the emission standards of the RICE NESHAP and then only a few ye ars 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 shortl y4 - 12

after the compliance date for existing engines), but 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 require emission controls on a stationary CI engi ne that is going to be retired onl y 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 i n 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 ye arly basis, n ot accounting for additional costs associated with monitoring, testing, recordkeeping and reporting. These engines (equipped with aftertreatment) could end up being in operation for less than 2 ye ars or at most only 5 y ears before having to be replaced with a certified Tier 4 engine, as required by San Joaquin Valley

District Rule 4702. It would not be reasonable to require the engine owner to invest in costly controls and monitoring equipment for an engine that will be replaced shortly after the installati on of the controls. Consequently , the EPA is proposing amendments to existing stationary CI engines located at area sources of HAP emissions to address this concern. The EPA is proposing to amend the requirements for existing stationary Tier 1 and Tier 2 c ertified CI engines located at area sources that are greater than 300 HP that are subject to a state or local rule that requires the engine to be replaced. The EPA is proposing to allow these engines to meet management practices for a period of 2 y ears starting with the applicable May 3, 2013, compliance date until January 1, 2015, or 12 ye ars after installation date (whichever is later), but not later than June 1, 2018. This proposed 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 relativel y quickl y after the owner would have to comply with th e NESHAP. The EPA is proposing that these engines be subject to management practices until until January 1 , 2015, , or 12 y ears after installation date (whichever is later), but not later than June 1, 2018, after which time the CO emission standards discuss ed above (and that are in Table 2d of the rule) apply . The management practices include requirements for when to inspect and replace the engine oil and filter, air cleaner, hoses and belts. The complete details of which management practices are required ar e 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 practices rather than the emission limits prior to May 3, 2015, must submit a notification by March 3,4 - 13

2013, stating that they

intend to use this provision and identify ing the state or local regulation that the engine is subject to. 4.2 . 1.5 Proposed Amendments

– for Remote Areas of Alaska 4.2.1.5.1 Background for Proposed Amendments The RI CE N ESHAP currently specifies less stringent requirements for existing non emergency

CI engines at area sources located in remote areas of Alaska. Remote areas are defined as those not accessible by the FAHS. The FAHS includes areas with y ear - round ferry servi ce that are not on the contiguous road s ys tem. Under the current regulation, stationary non emergency

CI engines at area sources in areas of Alaska that are not accessible by the FAHS are subject to management practices as opposed to numerical emission standards. Following the publication of the final rule in 2010, the EPA received requests to expand the definition of remote areas of Alaska. Stakeholders asserted that facilities in areas that are accessible by

the FAHS but are not connected to the Alaska R ailbelt grid face the same challenges as those in areas not accessible by the FAHS. The Alaska Railbelt Grid refers to the service areas of the six regulated public utilities that extend from Fairbanks to Anchorage and the Kenai Peninsula. These utilities are the Golden Valley Electric Association, Chugach Electric Association, Matanuska Electric Association, Homer Electric Association, Anchorage Municipal Li ght & Power, and the City of Seward Electric Sy stem. According to the stakeholders, one reason for b roadening the definition of remote areas in Alaska is high energy costs, which provide a natural incentive to run CI engines as little as possible. The cost of energy is utilities’ greatest concern in Alaska. Also, the stakeholders indicated that extreme w eather conditions in certain areas of Alaska is another reason for including additional areas in the definition of remote areas of Alaska. The climate issue is unique to remote areas of Alaska that experience some of the most extreme temperatures in the co untry . Heavy snowfall and high winds are not uncommon in several areas that are accessible b y t he FAHS. For instance, Copper Valley Electric Association (CVEA) is a utility accessible by

the FAHS, but it includes areas that face the same challenges as othe r communities not accessible by the FAHS. The utility

operates on an isolated grid and relies on diesel power generation. In one of CVEA’s territories, Valdez, Alaska, CVEA indicated that this area experiences brutal conditions and stated that Valdez is co nsidered to have the greatest snowfall (326 inches per winter) in an y cit y of the United States. Also, winds at more than 100 miles per hour are not uncommon for Valdez, Alaska, according to CVEA. Temperatures between 40 and 50 below zero are also not abno rmal, which emphasizes the extreme reliance on power, CVEA asserted. Travel times and accessibility are issues on a regular4 - 14

basis, but can be additionally exacerbated due to severe weather, which in some cases may lead to avalanches and road closings. In p articular, even if a site is on the FAHS, in the event of poor weather conditions and road closings, there are in many cases no alternate roads to travel on. Further, access to specific isolated sites can also be problematic in particular remote areas of A laska and the problems are unique to Alaska because of the infrastructure and environment. For example, communities made the case that sources along the AMHS that are only accessible b y the AMHS should be treated the same way as communities not accessible by the FAHS. The AMHS primarily

serves passengers and vehicles, and is not intended for transporting goods. Therefore, the same methods used to bring in goods to communities not on the FAHS are the same as those Alaskan villages served onl y b y the AMHS. Go ods are t ypically brought in to remote communities by

barge and this is another example of a scenario that is unique to Alaska. Other arguments for expanding the definition of remote areas of Alaska beyond those not accessible by

the FAHS include very

low population density

in many other remote areas although accessible by

the FAHS, and the fact that many of these areas are not connected to the electric grid and rel y on back up diesel generation to support fluctuating renewable energy sy stems. The energy

su pply s ys tem is another area that is particularl y different in Alaska compared to the rest of the country whose majority

of customers are connected to the grid. Lastl y, if sources were to comply with requirements under the RI CE NESHAP necessitating add on c ontrols and associated monitoring, testing, and administrative requirements, compliance costs would be high and funds needed for sustainable renewable energy goals would be diverted. Therefore, for the reasons discussed, the EPA is proposing expansion of the remote area source category . This proposal is supported by the Alaska Department of Environmental Conservation and communities with whom the EPA has discussed this issue. 4.2.1.5.2 What are the Proposed Amendments ? The EPA is proposing to expand the current definition of remote areas of Alaska to extend bey ond areas that are not accessible b y the FAHS. Specifically, the EPA is proposing that areas of Alaska that are accessible b y the FAHS and that meet all of the following criteria are also considered r emote and subject to management practices under the rule:

• The stationary

CI engine is located in an area not connected to the Alaska Railbelt Grid,

• At least 10 percent of the power generated b y the engine per ye ar is used for residential purposes, and4 - 15

• The sy stem capacity

is less than 12 megawatts, or the engine is used exclusively for backup power for renewable energy and is used less than 500 hours per y ear on a 10 - ye ar rolling average. The EPA is proposing limiting the remote classification to engines that are used at least partiall y for residential purposes, where the impact of higher energy costs is of greatest concern. The classification is further limited to sources that are used infrequently as backup for renewable power, or that are at smaller ca pacit y facilities, which are generally in more sparsel y populated areas. 4.2.1.6 Compliance Date The EPA has received some questions regarding whether the compliance dates for engines impacted b y the 2010 amendments and this proposed reconsideration will be extended. Affected sources that may be impacted by

this action have expressed concern about having sufficient time to comply with the rule by the compliance date, which is May 3, 2013, for existing stationary

CI RICE and October 19, 2013, for existing stationary SI RICE. Sources impacted b y this reconsideration are particularl y 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 b y this reconsideration. However, we note that sources that are affected b y the reconsideration and that may need additional time to install controls to comply with the applicable requirements can request up to an additional y ear to install controls, as specified in 40 CFR 63.6(i). **4.2.2 What Are the Pollutants Regulated by this Proposed**  **Reconsiderat ion**  **Rule?** The proposed reconsideration rule regulates emissions of HAP. Available emissions data show that several HAP, which are formed during the combustion process or which are contained within the fuel burned, are emitted from stationary engines. The H AP which have been measured in emission tests conducted on diesel fired RICE include: 1,3 - butadiene, acetaldeh yde, acrolein, benzene, eth yl benzene, formaldeh yde, n - hexane, naphthalene, pol yc yc lic aromatic hy drocarbons, poly cy clic organic matter, sty rene, t oluene, and xylene. Metallic HAP from diesel fired stationary RICE that have been measured are: cadmium, chromium, lead, manganese, mercury , nickel, and selenium.4 - 16

EPA described the health effects of these HAP and other HAP emitted from the operation of stationary

RI CE 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 w elfare. More details on the health effects of these HAP and other HAP emitted from operation of stationary RI CE can be found in Section 7 of this RIA. The proposed 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 CIengines. For the NESHAP promulgated in 2004, EPA found that there is a relations hip between CO emissions reductions and HAP emissions 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 reduction s 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 proposed amendments will result in the reduction of PM emissi ons from existing diesel engines. The aftertreatment technologies expected to be used to reduce HAP and CO emissions also reduce emissions of PM from diesel engines. Also, the proposed rule requires the use of UL SD for diesel - fueled stationary non emergenc y C I 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 b y reducing the sulfur content in the fuel. **4.3 Cost Impacts**  **4. 3**  **.1 Introduction**  The cost impacts associated with th is rule consist of different ty pes of costs, which include the annual and capital costs of controls, costs associated with keeping records of

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 - 17

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 parametric 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 Prote ction 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. 3 .1.1 Control Costs For engines that will need to add control technology to meet the emission standards, the following e quations were used to estimate capital and annual control 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 cataly st (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 dollars. The capital and annual cost were calculated using maintenance data from the CARB study and cost assumptions from the EPA Air Pollution Control Cost Manual. The control costs for the OCV s ys tem were calculated using 2008 cost data obtained from a diesel engine equipment vendor. An equipment life of 10 y ears was used to calculate the capital recovery f actor (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

2 Available on the Internet at http://epa.gov/ttn/catc/products.html#cccinfo . 3 Available on the Internet at http://www.whitehouse.gov/omb/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 - 18

the engine size in hp . This approach was used to develop a linear regression equation for annual cost. 4. 3 .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. Itis expected that the majority of owners and operators are alread y following some ty pe of O&M requirements and a small additional burden is expected. The EPA expects that at most 1 hour will be necessary per ye ar in order to keep track of maint enance. Owners and operator of stationary emergency

engines are required to keep track of the hours of operation and 1 hour per ye ar was estimated to cover that recordkeeping activity . For emergency

engines 1 hour is expected to cover tracking hours of ope ration plus recording maintenance activities. No cost is attributed to purchasing and installing an hour - meter since the majority of stationary

engines alread y come equipped with such equipment. Labor costs associated with recording the hours of operation 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 over head and profit rate of 167 percent. The ye ar 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. 3 . 1.3 Reporting Most engines affected b y this rule will be subject to reporting requirements such as reading instructions, training personnel, submitting an initial notification, submitting a notification of performance test(s), and submitting a compliance r eport. However, o wners and operators of engines less than 1 00 HP , existing stationary emergency

engines, and existing stationary engines less than 300 HP located at area sources are not subject to any specific reporting requirements . For stationary non - emergency limited use CIengines that operate less than 100 hours per ye ar, 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 f or 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 limit ed use engines .

5 U.S. Department of Labor, Emp loy er Costs for Employee Compensation , http://www.bls.gov/ne ws.release/ecec.toc.htm4 - 19

4. 3 .1.4 Monitoring The cost of monitoring includes the purchase of a continuous parametric monitoring sy stem (CPMS). Non - emergency engines greater than 500 hp that have add - on controls are required to use a CPMS to monitor the catal ys t inle t temperature and pressure drop across the catal ys t 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 dollar s. 6 The capital cost of a CPMS for a large engine facility is $531. Itis estimated that 30 hours per y ear is necessary to operate and maintain the CPMS and that 6 hours per ye ar (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. 3 .1.5 Performance Testing Initial performance testing is required for non - emergency engines greater than 100 hp at major sources and non - emergency en gines 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 anal yz er 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 anal yz er. 4. 3 .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 in clude:

 Changing the oil and filter;

 Inspecting the air cleaner and replacing as necessary ; and

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

6 Part A of the Supporting Statement for Standard Form 83 Stationary Reciprocating Internal Combustion Engines, November 17, 2003. 7 Mem orandum from Bradley Nelson , Alpha - Gamma T echnologies, Inc. to Sims Roy, EPA/OAQPS/ESD/Combustion Group , Portable Emissions Analyzer Cost Information , August 31 , 200 5.4 - 20

EPA believes that these work practices will limit HAP emissions from these engines, because these work practices ensure that the engine is operating efficientl y. Owner/operators of these engines regularl y perform these work practices as part of the preventive maintenance schedule for the engine. Therefore, EPA believes that it is appropriate to not includ e these work practice costs in the impacts determination. 4. 3 .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 procedures 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 pr actices ensure that the engine is operating efficientl y. Owner/operators of these engines regularl y perform these work practices as part of the preventive maintenance schedule for the engine. Therefore, EPA believes that it is appropriate to not include th ese work practice costs in the impacts determination. **4. 3**  **.2 Major Sources**  The cost impacts for stationary RI CE vary

depending on the engine ty pe and size. The following sections describe the specific costs that apply to each subcategory

of CI engines locat ed at major sources. 4. 3 .2.1 All CI Engines hp < 100 The costs associated with CIengines 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 require ments or must develop their own maintenance plan to follow. Emergency

engines must record the hours of operation, which is estimated at one hour per y ear at $72 per hour.4 - 21

4. 3 .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 in stall a control device to meet the emissions standard. To estimate the number 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 CInonroad emiss ion 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 y ear for Tier 1 engines begins in 1997 for 100 to 175 CIengines, and 1996 for 175 to 300 hp CIengines. Using the model y ear data in the population memorandum, EPA estimated that 35 percent of the existing CIengines greater than or eq ual 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 cost estimates for this subcategory of engines do not account for possible fuel price increases that may resul t from using ultra - low sulfur diesel (UL SD). EPA estimated the cost of lubricity additives to UL SD would increase the cost of the fuel by 0.2 cents per gallon, 9 which EPA believes is negligible. In addition, there are no additional maintenance requirements for owner/operators 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 include any costs for switching to UL SD in the impacts for this NESHAP. 4 . 3 . 2. 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 o xidation cataly st for reducing HAP, as well as the cost of installing an open crankcase ventilation sy stem. Non - emergency 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. 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 8 Exhaust and Crankcase Emission Factors for Nonroad Engine Modeling -- Com pression - Ignition, U.S. EPA, Office of Transportation and Air Quality, Assessment and Standards Division, EPA420 - P - 04 - 009, Revised April 2004. http://www.epa.gov/oms/models/nonrdmdl/nonrdmdl2004/420p04009.pdf 9 Mem orandum 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 - 22

using ULSD. EPA estimated the cost of lubricit y additives to UL SD would increase the cost of the fuel b y 0.2 cents per gallon, 10 which EPA b elieves is negligible. In addition, there are no additional maintenance requirements for owner/operators 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 include any costs for switching to UL SD in the impacts for this NESHAP. 4. 3 .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. Itis estimated that one hour per ye ar at $68 per hour would be sufficient to record the hours of operation. No costs were included in the impacts for following the manufacturer’s emission - related O&M plan, because it is expected that owner/operators will follow this plan reg ardless of the regulation. **4. 3**  **.3 Area Sources**  4. 3 .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 an y performance test ing. The owners and operators must follow the manufacturer’s emission - related O&M requirements or must develop their own maintenance plan to follow. Itis estimated that one hour per ye ar at $68 per hour would be sufficient to record the hours of operation . 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 eng ines 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.

10 Mem orandum from Melanie Taylor and Brad Nelson, AGTI to Sims Roy, EPA OAQPS ESD Combustion Group, Lubricity of Ultra Lo w Sulfur Diesel Fuel, June 2, 2004.4 - 23

4. 3 .3.2 Non - emergency CI Engines ≤ 300 hp The costs associated with nonemerg ency 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. 3 .3.3 Non - e mergency CI Engines > 300 hp The costs associated with non emergency CI engines above 300 hp include the cost of installing and operating an oxidation cataly st for reducing HAP, as well as the cost of installing an open crankcase ventilation sy stem. 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 50 0 hp must conduct subsequent performance testing every 8,760 hours or 3 y ears, 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 fo r this subcategory

of engines do not account for possible fuel price increases that may result from using ULSD. EPA estimated the cost of lubricit y additives to UL SD would increase the cost of the fuel b y 0.2 cents per gallon, which EPA believes is negligi ble. In addition, there are no additional maintenance requirements for owner/operators 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 include any costs for switching to UL SD 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 b y engine size is in Table 4 - 5 . All cost estimates are from “ RI CE NESHAP Reconsideration Amendment

– Cost and Environmental Impacts RI CE,” prepared by Tan ya Parise , E C /R, Inc. for Melanie King, U.S. EPA, Office of Air Qua lity Plannin g and Standards . These costs, presented in 2008 dollars, can be updated to 2010 dollars by apply ing 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 = 1.01.4-24 **Table 4**  **- 2**  **. Summary of**  **Major Source and Area Source Costs for the CI RICE NESHAP a** 

**Size Range**  **( hp**  **) Non**  **- Emergency** 

**CI Capital**  **Control Cost Non**  **- Emergency** 

**CI Annual**  **Control Cost Initial Test**  **Recordkeeping Reporting**  **Monitoring –**  **Capital Cost Monitoring**  **–**

**Annual Cost Total Annual** 

**Costs Total Capital** 

**Costs Major Sources**  50

– 100 $0 $0 $0 $6,654,888 $0 $0 $0 $6,654,888 $0 100

– 175 $24,057,778 $9,918,465 $14,150,269 $8,719,731 $ 5,973, 016 $0 $0 $38, 761,480 $24,057,778 175

– 300 $35,917,270 $10,740,189 $10,730,759 $6,612,548 $4, 529,595 $0 $0 $32, 613,092 $35,917,270 300

– 500 $107,841,136 $26,722,727 $5,645,923 $3,479,152 $2, 383,219 $0 $0 $38,2 31,021 $107,841,136 500

– 600 $13,126,952 $3,020,849 $500,530 $61,688 $21 1,280 $481,765 $2,220,755 $6,01 5,102 $13,608,716 600

– 750 $8,240,540 $1,824,295 $256,204 $31,576 $1 08,147 $246,599 $1,136,729 $3,35 6,951 $8,487,139 >750 $26,903,091 $5,618,803 $565,163 $69,653 $2 38,563 $543,975 $2,507,521 $ 8,999,703 $27,447,066 Total $216,086,768 $57,845,329 $31,848,848 $25,629,236 $13, 443,820 $1,272,338 $5,865,005 $134, 632,238 $217,359,106 **Area Sources** 50

– 100 $0 $0 $0 $9,183,746 $0 $0 $0 $9,183,746 $0 100

– 175 $0 $0 $0 $12,033,196 5,231,824 $0 $0 $ 17,265,000 $0 175

– 300 $0 $0 $0 $9,125,316 $ 3,967,529 $0 $0 $1 3,092,845 $0 300

– 600 269, 176, 789 $6 4,764,947 $12, 533,931 $7, 180,954 $5, 290,738 $4,0 21,343 $18, 536,893 $10 8,307,463 $27 3,198,131 600

– 750 67,576,980 $1 4,964,227 $2,1 01,015 $1,20 3,716 $8 86,866 $6 74,082 $ 9,321,806 $28, 473,630, $6 8,251,062, >750 177,179,667 $37, 004,585 $3,7 22,077 $2,13 2,457 $1,5 71,138 $1, 194,178 $1 6,514,152 $60, 944,409 $1 78,373,845 Total 513,933,435 $11 6,729,759 $18, 357,024 $40,8 59,384 $1 6,948, 096 $5, 889,603 $4 4,372,851 $23 7,267,114 $5 19,823,039 **Grand Total Total**  **$73 0,020,203**  **$17 4,575,088**  **$50, 205,872**  **$66, 480,620**  **$3 0,**  **391,916 $**  **7,161,941 $**  **50,237,856 $3**  **7 1,899,352**  **$ 737,182,145**  a Costs are presented in 2008 dollars.4-25 **Table 4**  **- 3**  **. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP**  **a**

**NAICS Major Source**  **Area Source Total (Major + Area)** 

**Capital Cost Annual Cost**  **Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost** Electric Pow er Generation (2211) $161,766,376 $9 0 ,9 82 , 10 5 $4 64,947,798 $20 2,463,116 $6 26,714,174 $29 3,445,222 Hospitals (622110) $20,220,797 $11,3 72,763 $0 $0 $20,220,797 $11,3 72 ,7 63 Crude Petroleum & NG Production (211111) $2,374,401 $3,8 07,478 $1, 590,115 $2, 59 7,836 $3,9 64,516 $6, 40 5,314 Natural Gas Liquid Producers (211112) $2,374,401 $3,8 07,478 $1, 590,115 $2 , 59 7,836 $3,9 64,516 $6, 40 5,314 National Security (92811) $20,220,797 $11,3 72,763 $5 1,660,866 $2 2, 495,902 $7 1,881,663 $3 3, 868,665 Hy dro Pow er Units (335312) $0 $16,637 $0 $22,959 $0 $39,597 Irrigation Sets (335312) $10,294,073 $11, 791,567 $34, 145 $ 5,208, 084 $10,328 218 $1 6,999, 651 Welders (333992) $108,260 $1,48 1,447 $0 $1, 881,380 $108,260 $ 3,362,827 **Total $217,359,106**  **$134, 632,238**  **$5 19,823,039**  **$2 3**  **7,267,114 $7**  **37,182,145 $3**  **7 1,899,352**  a Costs are presented in 2008 dollars.4-26 **Table 4**  **- 4**  **. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP**  **– by Size**  **a NAICS**  **Major Source Area**  **Source Total (Major + Area)**  **Capital Cost Annual Cost**  **Capital Cost Annual Cost**  **Capital Cost Annual Cost**  **Electric Power Generation (2211)** 50

– 100 hp $0 $3,396,123 $0 $5,272,480 $0 $8,668,603 100

– 175 hp $13,406,919 $21,600,998 $0 $ 10,824,132 $13,406,919 $32,425,129 175

– 300 hp $23,012,914 $20,895,861 $0 $ 9,437,454 $23,012,914 $30,333,314 300

– 600 hp $96,907,266 $35,304,866 $24 5,239,035 $9 7,223,277 $34 2,146,301 $13 2,528,144 600

– 750 hp $6,789,032 $2,685,292 $6 1,419,814 $25, 623,705 $6 8,208,846 $28, 308,997 >750 hp $21,650,245 $7,098,966 $1 58,288,950 $54,0 82,069 $1 79,939,195 $61,1 81,035 **Total 2211 $161,766,376**  **$90,982,105 $4**  **64,947,798 $20**  **2,463,116 $6**  **26,717,174 $29**  **3,445,222 Hospitals (622110)**  50

– 100 hp $0 $424,515 $0 $0 $0 $424,515 100

– 175 hp $1,675,865 $2,7 00,125 $0 $0 $1,675,865 $2,700,125 175

– 300 hp $2,876,614 $2,61 1,983 $0 $0 $2,876,614 $2,611,983 300

– 600 hp $12,113,408 $4,41 3,108 $0 $0 $12,113,408 $4,413,108 600

– 750 hp $848,629 $335, 662 $0 $0 $848,629 $335,662 >750 hp $2,706,281 $887, 371 $0 $0 $2,706,281 $887,371 **Total 622110 $20,220,797**  **$11,3 72,763**  **$0 $0**  **$20,220,797 $11,372,763**  **Crude Petroleum & NG Production (211111)** 50

– 100 hp $0 $420,256 $0 $579,954 $0 $1,000,210 100

– 175 hp $2,026,868 $3,265,655 $0 $1,454,578 $2,026,868 $4,720,233 175

– 300 hp $3,592 $3,261 $0 $1,309 $3,592 $4,571 300

– 600 hp $151,812 $55,308 $34 1,498 $13 5,384 $49 3,310 $19 0,692 600

– 750 hp $0 $0 $0 0 $0 $0 >750 hp $192,129 $62,998 $1,2 48,617 $426, 611 $1,4 40,746 $489, 609 **Total 211111 $2,374,401**  **$3,807,478 $1,**  **590,115 $2,59**  **7,836 $3,9**  **64,516 $6,40**  **5,314** (continued)4-27 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP –**  **by Size a**  **(continued) NAICS**  **Major Source Area Source**  **Total (Major + Area) Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost**  **Capital Cost Annual Cost**  **Natural Gas Liquid Producers (211112)** 50

– 100 hp $0 $420,256 $0 $579,954 $0 $1,000,210 100

– 175 hp $2,026,868 $3,265,655 $0 $1,454,578 $2,026,868 $4,720,233 175

– 300 hp $3,592 $3,261 $0 $1,309 $3,592 $4,571 300

– 600 hp $151,812 $55,308 $34 1,498 $13 5,384 $49 3,310 $19 0,692 600

– 750 hp 0 0 0 0 $0 $0 >750 hp $192,129 $62,998 $1,2 48,617 $426, 611 $1,4 40,746 $489, 609 **Total 211112 $2,374,401**  **$3,807,478 $1,**  **590,115 $2,59**  **7,836 $3,9**  **64,516 $6,40**  **5,314 National Security (92811)**  50

– 100 hp $0 $424,515 $0 $585,831 $0 $1,010,346 100

– 175 hp $1,675,865 $2,700,125 $0 $1,202,681 $1,675,865 $3,902,806 175

– 300 hp $2,876,614 $2,611,983 $0 $1,048,606 $2,876,614 $3,660,589 300

– 600 hp $12,113,408 $4,413,108 $27, 248,782 $10, 802,586 $39, 362,190 $15 ,215,695 600

– 750 hp $848,629 $335,662 $6, 824,424 $2,8 47,078 $7, 673,053 $3,1 82,740 >750 hp $2,706,281 $887,371 $17, 587,661 $6,00 9,119 $20, 293,942 $6,8 96,489 **Total 92811 $20,220,797**  **$11,372,763 $5**  **1,660,866 $22,**  **495,902 $7**  **1,881,663 $33,**  **86,665 Hydro Power Units (335312)**  50

– 100 hp $0 $16,637 $0 $22,959 $0 $39,597 100

– 175 hp $0 $0 $0 $0 $0 $0 175

– 300 hp $0 $0 $0 $0 $0 $0 300

– 600 hp $0 $0 $0 $0 $0 $0 600

– 750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $0 $0 $0 $0 **Total 335312 $0**  **$16,637 $0**  **$22,959 $0**  **$39,597** (continued)4-28 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP –**  **by Size a**  **(continued) NAICS**  **Major Source Area Source**  **Total (Major + Area) Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost**  **Irrigation Sets (335312)** 50

– 100 hp $0 $245,565 $0 $338,880 $0 $584,446 100

– 175 hp $3,137,134 $5,054,497 $0 $2,251,359 $3,137,134 $7,305,856 175

– 300 hp $7,143,945 $6,486,744 $0 $2,604,167 $7,143,945 $9,090,911 300

– 600 hp $12,145 $4,425 $27, 320 $10, 831 $39, 465 $15, 255 600

– 750 hp $849 $336 $6, 825 $2,8 47 $7, 674 $3,1 83 >750 hp $0 $0 $0 $0 $0 $0 **Total 335312 $10,294,073**  **$11,791,567 $34,**  **145 $5,208,**  **984 $10,328,**  **218 $16,999,**  **651 Welders (333992)**  50

– 100 hp $0 $1,307,020 $0 $1,803,688 $0 $3,110,708 100

– 175 hp $108,260 $174,427 $0 $77,693 $108,260 $252,119 175

– 300 hp $0 $0 $0 $0 $0 $0 300

– 600 hp $0 $0 $0 $0 $0 $0 600

– 750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $0 $0 $0 $0 **Total 333992 $108,260**  **$1,481,447 $0**  **$1,881,380 $108,260**  **$3,362,827 Grand Total**  **Total $217,359,106**  **$134,6 32,238**  **$5 19,823,039**  **$23 7, 267,114**  **$7 37,182,145**  **$37 1,899,352**  a Costs are presented in 2008 dollars.4-29 **Table 4**  **- 5**  **. Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP**  **– by Number of Engines**  **a**

**NAICS Number of**  **Engines Total (Major + Area)**  **Major Area**  **Total Capital Cost**  **Annual Cost Electric Power Generation (2211)**  50

– 100 hp 47,324 79,859 127,183 $0 $8,668,603 100

– 175 hp 67,713 114,266 181,980 $13,406,919 $3 2,4 25,129 175

– 300 hp 59,039 99,627 158,666 $23,012,914 $ 30,3 33,314 300

– 600 hp 42,113 97,919 140,032 $34 2,146,301 $13 2,528,144 600

– 750 hp 1,760 16,455 18,215 $6 8,208,846 $28, 308,997 >750 hp 3,828 28,746 32,574 $1 79,939,195 $61,1 81,035 **Total 2211 221,777**  **436,872 658,649**  **$6 26,717,174**  **$29 3,445,222**  **Hospitals (622110)** 50

– 100 hp 5,916 0 5,916 $0 $424,515 100

– 175 hp 8,464 0 8,464 $1,675,865 $2,70 0,125 175

– 300 hp 7,380 0 7,380 $2,876,614 $2,61 1,983 300

– 600 hp 5,264 0 5,264 $12,113,408 $4,41 3,108 600

– 750 hp 220 0 220 $848,629 $335, 662 >750 hp 479 0 479 $2,706,281 $887, 371 **Total 622110 27,722**  **0 27,722**  **$20,220,797 $11,3**  **72,763 Crude Petroleum & NG Production (211111)**  50

– 100 hp 5,856 8,784 14,640 $0 $1,000,210 100

– 175 hp 10,237 15,355 25,592 $2,026,868 $ 4,7 20,233 175

– 300 hp 9 14 23 $3,592 $4, 5 7 1 300

– 600 hp 66 136 202 $49 3,310 $19 0,692 600

– 750 hp 0 0 0 $0 $0 >750 hp 34 227 261 $1,4 40,746 $489, 609 **Total 211111 16,202**  **24,517 40,719**  **$3,9 64,516**  **$6, 4**  **05,314** (continued)4-30 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP**  **– by Number of Engines**  **a (continued)**  **NAICS Number of Engines**  **Total (Major + Area) Major**  **Area Total**  **Capital Cost Annual Cost**  **Natural Gas Liquid Producers (211112)** 50

– 100 hp 5,856 8,784 14,640 $0 $1,000,210 100

– 175 hp 10,237 15,355 25,592 $2,026,868 $4,720,233 175

– 300 hp 9 14 23 $3,592 $4,571 300

– 600 hp 66 136 202 $49 3,310 $19 0,692 600

– 750 hp 0 0 0 $0 $0 >750 hp 34 227 261 $1,4 40,746 $489, 609 **Total 211112 16,202**  **24,517 40,719**  **$3,9 64,516**  **$6,40 5,314**  **National Security (92811)** 50

– 100 hp 5,916 8,873 14,789 $0 $1,010,346 100

– 175 hp 8,464 12,696 21,160 $1,675,865 $3,902,806 175

– 300 hp 7,380 11,070 18,450 $2,876,614 $3,660,589 300

– 600 hp 5,264 10,880 16,144 $39, 362,190 $15, 215,695 600

– 750 hp 220 1,828 2,048 $7, 673,053 $3,1 82,740 >750 hp 479 3,194 3,672 $20, 293,942 $6,8 96,489 **Total 92811 27,722**  **48,541 76,263**  **$7 1,881,663**  **$33, 868,665**  **Hydro Power Units (335312)** 50

– 100 hp 232 348 580 $0 $39,597 100

– 175 hp 0 0 0 $0 $0 175

– 300 hp 0 0 0 $0 $0 300

– 600 hp 0 0 0 $0 $0 600

– 750 hp 0 0 0 $0 $0 >750 hp 0 0 0 $0 $0 **Total 335312 232**  **348 580**  **$0 $39,597**  (continued)4-31 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the CI RICE NESHAP –**  **by Number of Engines a**  **(continued) NAICS**  **Number of Engines Total (Major + Area)**  **Major Area**  **Total Capital Cost**  **Annual Cost Irrigation Sets (335312)**  50

– 100 hp 3,422 5,133 8,555 $0 $584,446 100

– 175 hp 15,845 23,767 39,611 $3,137,134 $7,305,856 175

– 300 hp 18,327 27,491 45,819 $7,143,945 $9,090,911 300

– 600 hp 5 11 16 $39, 465 $15, 255 600

– 750 hp 0 2 2 $7, 674 $3,1 83 >750 hp 0 0 0 $0 $0 **Total 335312 37,599**  **56,403 94,003**  **$10,328, 218**  **$16,999, 651**  **Welders (333992)** 50

– 100 hp 18,213 27,319 45,532 $0 $3,110,708 100

– 175 hp 547 820 1,367 $108,260 $252,119 175

– 300 hp 0 0 0 $0 $0 300

– 600 hp 0 0 0 $0 $0 600

– 750 hp 0 0 0 $0 $0 >750 hp 0 0 0 $0 $0 **Total 333992 18,760**  **28,140 46,899**  **$108,260 $3,362,827**  **Grand Total Total**  **366,217 619,337**  **957,832 $7**  **37,182,145 $**  **37 1,899,352**  a Costs are presented in 2008 dollars.4-32 **4. 4**  **Baseline Emissions and Emission Reductions** 

Baseline emissions are estimated for 2013 using the emissions dataset generated for the final CIRICE rule in 2010. The baseline emissions thus assume the final CI RICE rule has not been i mplemented. The emissions reductions in 2013 associated with the proposed reconsidered rule are based on requiring emission standards that are based on appl yi ng add - on controls to non emergency

CI engines greater than 5 00 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/y r, and emergency

CI engines operating 50 hrs/ yr. While the amendments the EPA is proposing for stationary emergency

engines increases the time allowed for participation in emergency demand response programs and for certain engines to operate for peak shaving or other income generating activities, the EPA belie ves that 50 hours per ye ar is still representative of emergency engine operation. There is a wide range in how much stationary emergency engines operate . S ome emergency

units operate well below 50 hrs /y r, 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 t o estimate emissions from stationary emergency

engines, the EPA has retained th e assumption that 50 hrs/y r 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 cataly st 7 0% 7 0% 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 y ear (tpy) as a result of the final rule are shown in4-33 Table 4 - 7 . In addition, it is expected that additional PM reductions will be achieved b y the

requirement to use UL SD for CI engines that install a DOC. The use of ULSD reduces the formation of sulfates in the exhaust gas, therefore 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 die sel fuel that is being replaced. Because EPA has no information on the ty pe of fuel that CIengines are currently using, the PM reductions from switching to ULSD were not quantified and included in this summary . T he EPA is proposing that existing station ary 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 RI CE NESHAP for a period of 2 y ears until May 3, 2015. T he 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 o r similar situation and although the EPA does not preclude the possibility that there are additional such engines, the EPA has no information on this. Therefore, for purposes of estimating reductions under the proposed amendments, the EPA has subtrac ted 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 proposing to specify that an y existing certified Tier 3 CI engine that was i nstalled before June 12, 2006, is in compliance with the NESHAP. This amendment would include an y existing stationary Tier 3 certified CI engine located at an area source of HAP emissions. There are 17 Tier 3 engines (2006 model y ear) located in San Joaqui n Valley that were installed between January 1 and June 12, 2006. The EPA does not know if there are additional engines in other areas that in a similar situation and the EPA has no information indicating how man y 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 proposed amendments be subject to management practices. The work practice requirement o f using an open crankcase ventilation sy stem to control metallic HAP emissions is expected to achieve additional HAP reductions from CIengines. However, the metallic HAP emission reduction cannot be quantified because of the difficult y of measuring metal lic 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 in4-34 the fine particle emissions; thus all emissions and PM emission reductions are assum ed to be

PM 2.5 . **Table 4**  **- 6**  **. Summary of Major Source and Area Source Baseline Emissions**  **for the CI**  **RICE NESHAP in 2013**  **Summary of Major Source and Area Source Baseline Emissions for the RICE NESHAP 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**  **79,965**4-35 **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 Emission 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 Estim ate**  **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 Qua lity Planning and Standards . January 26, 2012.5 - 1 **SECTION 5 ECONOMIC IMPACT ANAL**  **YSIS , ENERGY**  **I MPACTS**  **, AND**  **S OCIAL**  **C OSTS**  The EIA provides decision makers with social cost estimates and enhances understanding of how the costs may

be distributed across stakeholders (EPA, 20 1 0 ). Although several economic frameworks can be used to estimate social costs for regulations of this size and sector scope, OAQPS has t ypically used partial equilibrium market models. However, the current data do not provide sufficie nt details to develop a market model; the data that are available have little or no sector/firm detail and are reported at the national level. In addition, some sectors have unique market characteristics (e.g., hospitals) that make developing partial equil ibrium models difficult. Given these constraints, we believ ed the direct compliance costs as a reasonable approximation of total social costs. In addition, we also provide a qualitative anal ys is of the proposed rule’s economic impact on stakeholder decisio ns, a qualitative discussion on if unfunded mandates occur as a result of this proposed 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 ye ar 2013, EPA’s engineering cost anal ys is estimates the total annualized cost s of the final rule are $3 7 2 million (in 2008 dollars) ( E C /R , 201 2 ) . As shown in Figure 5 - 1, the majority of the costs fall on the electric power sector (79%), followed b y 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 Sy stems Research (PSR) database, which is the major source of data for the engines affected b y the final rule. The PSR database used as a basis for the anal ys es 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 ye ars. The Office of Transportation and Air Quality (OTAQ) uses this database frequentl y in the development of their mob ile 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 million 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%ElectricPowerGeneration(2211)Hospitals(622110)CrudePetroleum&NGProduction(211111)NaturalGasLiquidProducers(211112)NationalSecurity(92811)HydroPowerUnits(335312)IrrigationSets(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 >7 50 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 >7 50 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 C ensus 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

affec ted 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 Annualiz**  **ed Compliance Costs as a Fraction of Total Industry Revenue: 2008**  **Industry (NAICS)**  **Industry Nam e**  **Total Annualized Costs**  **($ m illion)**  **a Sales, Shipments, Receipt, or** 

**Revenue ($ Billion)**  **Cost -**  **to -**  **Sales Ratio**  **($2007) ($2008)**  2211 Electric Pow er Generation $29 3 . 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 $3 3,9 #N/A #N/A #N/A 333992 Welders $3.4 $5.2 $5.3 0.06% 111 and 112 Agriculture using irrigation

systems a $1 7 . 0 $27.9 $28.5 0.0 5 %

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 Source s : U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 00: All sectors: Geographic Area Series: Economy - Wide Key Statistics: 2007” <http://factfinder.census.gov>; (January 4th , 2010) . U.S. Department of Agriculture (USDA), Na tional Agricultural 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 NESHAP 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 annu alized compliance cost estimates provide a reasonable approximation of the social cost of this proposed rule. EPA believes this approximation is better for industries whose markets are well characterized as5 - 5

perfectly competitive. This approximation is le ss well understood for industries where the characterization of markets is not alway s perfectly 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 hy pothetical analy ses 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 consumers 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 suppl y 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 ty picall y upward sloping because some production resources are fixed. As a result, the cost of producing an additional unit ty

pically rises as more units are made. The market demand curve describe s how much of a good or service consumers are willing and able to buy at some price. Holding other factors constant, the quantity demand is assumed to fall when prices rise. In a perfectl y competitive market, equilibrium price (P 0 ) and quantity (Q 0 ) is det ermined 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 b y dividing the annual compliance cost estimate b y the baseline quantit y (Q 0 ) (see Figure 5 - 4). As shown, this model m akes two predictions: the price of the affected goods and services are likel y 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 + p roducer surplus =

– [aehb + dhc + bdc] **Figure 5 -**  **4. Market Demand and Supply Model: With and Without Regulation**  The size of these changes depends on two factors: the size of the unit production cost increase (suppl y shift) and differences in how each side of the market (supply and demand) responds to changes in price. Economists measure responses using the concept of price elasticity , which represents the percentage change in quantity divided by

the percentage change in price. This dependence has been expre ssed in the following formula: 1 

##   Demand) of Elasticity Price - Supply of Elasticity Price Supply of Elasticity Price  **cost** production unit er- 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

 goods and services are necessities and people do not have good substitutes that they can switch to easil y (demand is inelastic) and 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  suppliers have excess capacity and can easil y adjust production levels at minimal costs, or the time period of anal ys is is long enough that suppliers can change their fixed resources; suppl y is more elastic over longer periods. Short - run demand elasticities for energy goods (electricit y and natural gas), agricultural products, and construction are often inelastic. Specific estimates of short - run demand elasticities for these products can be obtained from existin g literature. For the short - run demand of energy products, the National Energy Modeling Sy stem (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 wou ld 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% decli ne 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.**  **3 .2**  **Regulated Markets: The Electric Power Generation, Transmission, and Distribution**  **Sector** Given that the electric power sector bears majorit y 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 necessaril y applicable for this industry .5 - 8

**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 electricit y i ndustry continues to go through a process of restructuring, whereby the industry is moving toward a more competitive framework (see Figure 5 - 5 for the status of restructuring b y state), 2 in many states, electricity

prices continue to be fully regulated by

Public Service Commissions. As a result, the rules and processes outlined b y these agencies would ultimately

determine how these additiona l 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 analy sis, the social costs are estimated by measuring the changes in consumer and p roducer surplus, and these values can be determined using the market suppl y and demand model (Figure 5 - 4). T he change in consumer surplus is measured as follows :  CS = – [ Q 1 × 

p ] + [ 0.5 × Q × 

p ] . (5.1 ) H igher 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 ) Higher unit costs and lower production level reduce producer surplus because the net price chan ge (  p – t ) is negative. However, these losses are mitigated because market prices tend to rise.

2 http://tonto.eia.doe.gov/energy_in_brief/print_pages/electricity.pdf .5 - 9

**Figure 5 -**  **5. Electricity Restructuring by State**  Source. U.S. Energy Information Administration. 20 10 a . <http://www.eia.doe.gov/cneaf/electricity/page/restructuring/restructure_elect.html>. Last updated September 20 10 . **5.4 Energy Impacts**  Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agenci es 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 Or der 13211 defines “ significant energy actions ” as an y action b y an agency (normall y published in the Federal Register) that promulgates or is expected to lead to the promulgation of a final rule or regulation, including notices of inquiry , advance notices of proposed rulemaking, and notices of proposed rulemaking: (1) (i) that is a significant regulatory action under Executive Order 12866 or any successor order, and (ii) is likely

to have a significant adverse effect on the supply , distribution, or use of e nergy ; or (2) that is designated by the Administrator of the Office of Information and Regulatory Affairs as a significant energy

action.5 - 10

This rule is not a significant energy action as designated by

the Administrator of the Office of Inf

ormation and Regul atory

Affairs because it is not likely to have a significant adverse impact on the supply , distribution, or use of energy . EPA has prepared an analy sis of energy impacts that explains this conclusion as follows below. With respect to energy

supply and pric es, the analy sis 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 r egulation’s influence on energy consumption, we examined publicly

available data describing energy consumption for the electric power sector that will be affected b y t his rule. The Annual Energy Outlook 201 1 (EIA, 20 11 ) provides energy consumption data. As shown in Table 5 - 4, this industry 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 si gnificantl y 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 prohibited by law, to assess the effects of the ir regulatory

actions on State, local, and tribal governments and the private sector. This rule contains a Federal mandate that may result in expenditures of $100 million or more for State, local, and tribal governments, in the aggregate, or the private se ctor in an y one y ear. Accordingl y, EPA has prepared under section 202 of the UMRA a written statement which is summarized below in this section .5 - 11

**Table 5 -**  **4 .**  **U.S. Electric Power a**  **Sector Ener gy Consumption (Quadrillion BTU**  **s) : 2013**  **Quantity Share of Total En**  **ergy 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 pow er 8.5 0 8. 8 % Renewable energy b 4 . 63 4 . 8 % Electricity Imports 0. 12 0.1% Total Electric Pow er Energy Consumption c 38 . 77 40. 1 % Delivered Energy Use 7 0 . 56 7 3 . 2 % Total Energy Use 96.66 100.0%

a Includes consumption of energy by electricity - only and combined heat and pow er plants whose primary business is to sell electricity, or electricity and heat, to the public. Includes small pow er producers and exempt wholesale generators. b Includes conventional hydroelectric, geothermal, w ood and wood w aste, biogenic municipal solid w aste, other biomass, petroleum coke, wind, photovoltaic and solar thermal sourc es. Excludes net electricity imports. c Includes non - biogenic municipal w aste not included above. Source: U.S. Energy Information Administration. 20 11 a . Supplemental Tables to the Annual Energy Outlook 20 1 1, projections for 2013 . Available at: http://www.eia.gov/oiaf/aeo/tablebrow ser/#release=EARLY2012&subject=6 - EARLY2012&table=2 - EA RLY2012®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 an y particular areas of the country, State or local governments, types of communities (e.g., urban, rural), or particular industry segments. **5.5. 2**  **E ffects on the National Economy**  The UMRA requires that we estimate the effect of the proposed rule on the national econom y. To the extent feasible, we must estimate the effect on productivity, economic growth, full employ

ment, creation of productive jobs, and international competitiveness of the U.S. goods and services if we determine that accurate estimates are reasonabl y feasible and that such effect is relevant and material. The nationwide economic impact of the proposed rule is presented earlier in this RIA chapter. This anal ys is provides estimates of the effect of the5 - 12

proposal rule on most of the categories mentioned above, and these estimates are presented earlier in this RIA chapter. In addition, we have determined that the proposed rule contains no re gulatory

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 appr opriate, disproportionately high and adverse human health or environmental effects of their programs, policies, and activities on minority populations and low income populations in the United States. Assuming that our baseline for this RIA does not inclu de implementation of the final 2010 CIRICE rule, as we state earlier in this document, EPA has determined that this proposed rule will not have disproportionately high and adverse human health or environmental effects on minority or low - income populations because it increases the level of environmental protection for all affected populations without having an y disproportionately high and adverse human health or environmental effects on an y population, including an y minorit y 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 cos ts and benefits of the proposed rule , EPA has anal yz ed the impacts of this rulemaking on employ ment , which are presented in this section . While a standalone anal ys is of employ ment impacts is not included in a standard cost - benefit anal ys is, such an anal ys is is of particular concern in the current economic climate of sustained high unemploy ment. Executive Order 13563, states, “Our regulatory s ys tem must protect public health, welfare, safet y, and our environment while promoting economic growth, inno vation, competitiveness, and job creation” (emphasis added). Therefore, and consistent with recent efforts to characterize the employ ment effects of economically significant rules, the Agency has provided this anal ys is to inform the discussion of labor dem and and employment impacts.5 - 13

Th is employ

ment impact anal ys is includes estimates of certain short - term and on - going labor requirements (increase in labor demand) a ssociated 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 annuall y on a per manent basis. EPA also provides a qualitative discussion of other potential employ

ment 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 o verall emplo ym ent effect. We have not quantified the rule’s net effects on the over all 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 ord er 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 employ ment occurs as a result of a regulation, it is a cost to firms. Moreover, when the econom y is at full employ ment, we would not expect an environmental re gulation to have an impact on overall employ ment 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 employ ment due to the potential hiring of previously unemploy ed workers by

the regulated sector to help meet new requirements (e.g., to install new equipment) or b y the environmental protection sector to produce new abatement capital. Wh en significant numbers of workers are unemploy ed, the opportunity costs associated with displacing jobs in other sectors are likely to be smaller. To provide a partial picture of the employ ment consequences of this rule, EPA takes two approaches. First, EPA uses informatio n such as monitoring, recordkeeping, and reporting estimates derived from its cost analy sis documentation to generate estimates of employ ment impacts. Second, the anal ys is 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 b y EPA previous ly in recent Regulatory

Impact Analy ses.

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 will cause a short - run aggregate supply curve to shift to the left, and businesses will produce less, all other things being equal.5 - 14

EPA is interested in public comments on the merits of including information derived in this fashion for assessing the employ ment consequences of regulations. **5.7.1 Employment Impacts from Pollution Control Requir em**  **ents** Regulations set in motion new orders for pollution control equipment and services. When a new regulation is promulgated, one t ypical response of industry is to order pollution control equipment and services in order to compl y with the regulation wh en it becomes effective, while closure of plants that choose not to comply is assumed to occur after the compliance date . With such a response b y industry as a basis, this section presents estimates for short term labor requirement needed associated with the monitoring, recordkeeping, and reporting requirements for this proposed rule . Environmental regulation may increase revenue and employ ment in the environmental technology industry . While these increases represent gains for that industry , they are cost s to the regulated industries required to install the equipment. As with any pool of labor, the gross size of the labor pool does not reflect the net impact on overall employ ment 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 r eassign existing employ ees to do these activities. A study including an anal ys is of environmental protection employ ment in six U.S. states in 2003 by Bezdek, Wendling, and DiPernab (2008) found that “investments in environmental protection create jobs and displace jobs, but the net effect on employ ment 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 anal ys is is on labor requirements related to the compliance actions of the affected entities within the affected sector The employ

ment anal ys is uses a bottom - up engineering - based methodology to estimate employ ment impacts. The engineering cost anal ys is summarized in Section 4 of this RIA 4 Environmental protection, the economy, and jobs: Nat ional 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 - 15

includes estimates of the labor requirements associated with implementing the proposed regulations. Each of these labor changes may either be required as part of an initial effort to comply with the new regulation or required as a continuous or annual effort to maintain compliance. We estimate up - front and continual, annual labor requirements by estimating hours of labor required and converting this number to full - time equivalents (FTEs) by dividing by 2,080 (40 hours per week multiplied by 52 weeks). We note that this ty pe of FTE estimate cannot be used to make assumptions about the specifi c number of people involved or whether new jobs are created for new emplo yees. The results of this employment estimate are presented in Table 5 - 5 for the proposed NESHAP. The tables breaks down the installation, operation, and maintenance estimates b y t ype of pollution control evaluated in the RIA and present both the estimated hours required and the conversion of this estimate to FTE. For the proposed NESHAP, reporting and recordkeeping requirements were estimated requirements were estimated for the entir e rule rather than b y anticipated control requirements; the reporting and recordkeeping estimates are consistent with estimates EPA submitted as part of its Information Collection Request (I CR) that is in the Supporting Statement for the proposed reconsid eration rule. The up - front labor requirement is estimated at 1, 300 FTEs for the proposed 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 regulat ion. Ongoing requirements are estimated at about 2,000 FTEs for the proposed reconsidered NESHAP. These ongoing FTE labor requirements can be viewed as sustained labor requirements required for affected entities to continuously compl y with the new regulati on. All of this data is found in the cost memorandum for this proposed reconsidered rule, and can be found in the docket for the rulemaking. It is important to recognize that these seemingl y precise estimates are not to be assumed to be exact measures of the emplo ym ent impacts of this rulemaking. They represent a rough approximation of the small positive impacts that this rule may have on employ

ment.5 - 16

**Table 5 -**  **5 . Labor**  **- based Employment Estimates for Reporting and Recordkeeping and**  **Installing, Opera ting, and Maintaining Control Equipment Requirements for Proposed**  **Reconsideration CI RICE NESHAP Source**  **Em ission** 

**Control Measure**  **Projected**

**No. of Affected**  **Units Per**  **- Unit** 

**One**   ** Tim** **e Labor**  **Estimate (Hours)**  **Total**

**One**   ** Tim** **e Labor**  **Estimate (Hours)**  **Per -**  **Unit**

**Annual Labor**  **Estimate (Hours)**  **Total**

**Annual Labor**  **Estimate (Hours)**  **One -**  **Ti me** 

**Full -**  **Tim e**  **Equivalent Annual** 

**Full -**  **Tim e**  **Equivalent** All CI RICE

- O&M Recordkeeping N/A 366,217 N/A N/A 1 366,217 N/A 176 Non - Emergency CI RICE 100 - 300 HP

- Testing Oxidation

Catalyst 54,697 11 593,496 2 738,404 285 355

- Reporting 8 Non - Emergency 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 Recordkeeping Non - Emergency 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 Non - Emergency 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 w eeks). Totals may not sum due to independent rounding. CPMS = Continuous Parameter Measurement System HP = horsepow er N/A = Not Applicable. O&M = Operating and Maintenance5 - 17 **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 employ ment effects of new regulations within the regulated industry . (See, for example, the Regulatory I mpact Anal ys es for the recently released final MATS and final CSAPR regulations). Determining the direction of employ ment effects in the regulated industry is also challenging due to competing effects. Complying with the new or more stringent regulation requires additional inputs, including labor, and may alter the relative proportions of labor and ca pital 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 qualit y) to their product mixes . Although legall y compelled to satisfy this new demand, regulated firms have to finance this additional production with the proceeds of sales of their other (market) products. Satisfying this new demand requires additional inputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms in their production processes. More specificall y, Morgenstern, Pizer, and Shih (2002) decompose the effect of regulation on net emplo yment in the regulated sector into the following three s ubcomponents:

 The Demand Effect : higher production costs from complying with the regulation will raise market prices, reducing consumption (and production), thereb y 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, a s “production costs rise, more inputs, inclu ding labor, are used to pr oduce the same amount of output, ” (p. 416). For example, to reduce pollutant emissions while holding output levels constant, regulated firms may require additional labor.

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 - 18  The Factor- Shift Effect : Regulated firms’ production tec hnologies 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). “ E nvironmental activities may be more labor intensive than conventional production,” meaning tha t “the amount of labor per dollar of output will rise.” However, activities may , instead, be less labor intensive because “cleaner operations could involve automation and less employ ment, for example.” (p. 416) The demand effect is expected to have a n unambiguously negative effect on employ ment, the cost effect to have an unambiguousl y positive effect on emplo ym ent, and the factor - shift effect to have an ambiguous effect on employ ment. Without more information with respect to the magnitudes of these three competing effects, it is not possible to predict the net environmental employ

ment effect in the regulated sector . Using plant - level Census information between the y ears 1979 and 1991, Morgenstern et al. estimate the effects of pollution abatement expenditures on net emplo yment in four highl y polluting/regulated sectors (pulp and paper, plastics, steel, and petroleum refining). They conclude that increased abatement expenditures generall y have not caused a significant change in net employ

ment in those secto rs. More specifically , their results show that, on average across the industries studied, each additional $1 million (in 1987$) spent on pollution abatement results in a (statistically

insignificant) net increase of 1.55 (+/ - 2.24) jobs. As a result, the a uthors conclude that increases in pollution abatement expenditures can have positive effects on employ ment and do not necessarily

cause economicall y significant employment changes. The conclusion is similar to Berman and Bui (2001), who found that increase d air qualit y regulation in L os Angeles did not cause large employ ment changes. Id eall y, the EPA would first apply the methodology of Morgenstern et al. to current pollution expenditure and market data for the regulated firms to identify the relationship between abatement costs and employ ment, then use this relationship to extrapolate the effect of new projected abatement costs on these firms. Unfortunately , current firm - level abatement cost and market characteristics are not available. In addition, ther e are important differences in the markets and regulatory

settings anal yz ed in their study and the setting presented here that lead us to conclude that it is inappropriate to utilize their quantitative estimates to estimate the employ ment impacts from this reconsideration proposal. The differences between the underl yi ng regulations motivating the abatement expenditures studied in Morgenstern et al. are potentiall y too many to allow for the direct transfer of their quantitative estimates for use in anal ys is of the proposed rule. There are also important differences between the industries affected b y this5 - 19

proposed rule and the four manufacturing industries studied by Morgenstern et al. For these reasons, we conclude there are too man y uncertainties as to the comparability of the Morgenstern et al. study

to appl y their estimates to quantify the employment impacts within the regulated sector for this proposed regulation.6 - 1 **SECTION 6 SMALL ENTITY SCREENI**  **NG ANALYSIS** The Regulatory

Flexibility

Act as amended b y the Small Business Regulatory Enforcement Fairness Act (SBREFA) generally requires an agency

to prepare a regulatory flexibility anal ys is of an y rule subject to notice and comment rulemaking requirements under the Administrative Procedure Act or an y 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 b y the Small Business Administration (SBA) incl ude small businesses, small governmental jurisdictions, and small not - for - profit enterprises. After considering the economic impact of the proposed reconsideration rule on small entities, the screening analy sis indicate s that this proposed rule will not ha ve a significant economic impact on a substantial number of small entities (or “SI SNOSE”) . Under the primary cost anal ys es EPA considered, sales and revenue tests for establishments owned b y model small entities are less than 3% and only one group of estab lishments (irrigated farms with receipts less than $ 25 ,000 ) has a ratio exceeding 1% . These results are identical to those from the small entity anal ys is done for the final CIRICE rule promulgated in March 2010. **6.1 Small Entity**  **Data Set** The industry

sector s covered b y the proposed rule were identified during the development of the cost anal ys is (Nelson, 20 12 ). The SUSB provide s national information on the distribution of economic variables b y industry and ente rprise size (U.S. Census, 2 006a, 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 anal ys es . 2 Statistics include the total number of establishments and receipts for all entities in an industry ; however, many of these entities may

not necessaril y be covered b y the final rule . SUSB also provides statistics by enterprise employ

ment and receipt size. The Census Bureau ’ s definitions used in the SUSB , which are stated in Section 3 and restated here for clari t y of presentation, are as follows:

 E stablishmen t: An establishment is a single ph ys ical location where business is conducted or where services or industrial operations are performed. 1 The SUSB data do not provide establishment information for the national security NAICS code (92811) or irrigated farms. Since most national security installations are owned by the federal government (e.g., military bases), EPA assumes these entities would not be considered small. For irrigated farms, we relied on receipt data provided in the 2008 Farm and Irrigation Survey (USDA, 2009 ). 2 Se e http://www.census.gov/csd/susb/ and http://www.sba.gov/advo/research/data.html for ad ditional details.6 - 2  R eceipts : Receipts (net of taxes) are defined as the revenue for goods produced, distributed, or services provided, including revenue earned from premiums, commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

 E nterprise : 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 mul ti establishment company forms one enterprise

—the enterprise employment and annual pay

roll are summed from the associated establishments. Enterprise size designations are determined by the summed employ

ment of all associated establishments. Because the SBA ’ s busin ess size definitions (SBA, 20 10 ) appl y to an establishment ’ s “ ultimate parent company , ” we assume d in this analy sis that the “ enterprise ” definition above is consistent with the concept of ultimate parent company that is ty picall y used for SBREFA screening anal ys es and the terms are used int erchangeabl y. **6.2 Small Entity Economic Impact Measures**  T he anal ys is generated a set of establishment sales tests (represented as cost - to - receipt ratios) 3 for NAI CS codes associated with sectors lis ted in Table 6 - 1 . Although the appropriate SBA size definition should be applied at the parent company (enterprise) level, we can only compute and compare ratios for a model establishment owned by an e nterprise within an SUSB size range (emplo ym ent or receipts). Using the SUSB size range helps us account for receipt differences between establishments owned by large and small enterprises and also allows us to consider the variation in small business definitions across affected indus tries. Using establishment receipts is also a conservative approach , because an establishment ’ s parent compan y (the “ enterprise ” ) may have other economic resources that could be used to c over 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 averag e establishment receipts for enterprises in several size categories . 4 For industries with SBA

3 The following metrics for other small entity economic impact measures (if applicable) w ould potentially include • sm all governments (if applicable): “revenue” test; annualized compliance cost as a percentage of annual government revenues and • sm all nonprofits (if applicable): “expenditure” test; annualized compliance cost as a percentage of annual operating expenses, 4 For the 1 to 20 employee category, we excluded SUSB data for enterprises with zero employees. These enterprises did not operate the entire year.6 - 3

employ ment size standards, we calculat ed average establishment receipts for each enterprise employ ment 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): Affecte d Sectors and SBA Small Business Size Standards**  **Industry Description Corresponding**  **NAICS SBA Size Standard for** 

**Businesses (effective Novem**  **ber 5 , 20**  **10 )**  **Type of Sm all Entity**  Electric pow er generation 2211 a Business and government Natural Gas Transmission 48621 $7.0 million in annual receipts Business General medical & surgical hospitals 622110 $34.5 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 Hy dro pow er 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 s ma ll 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. S ma ll Business Administration (SBA). 20 10 . “Table of Small Business Size Standards Matched to North American Industry Classification System Codes.” Effective November 5 nd, 20 10 . Downloaded 2/16/12. av erage establishment receipts for each enterprise receipt range (Table 6 - 3). We included the utility sector in the second group, although the SBA size standard for this industry is defined in terms of ph ys ical units (megawatt hours) versus receipts. Crop an d animal production (NAICS 111 and 112) also have an SBA receipt size standard that defines a small business as receiving $750,000 or less in receipts per y ear. However, SUSB data were not available for these industries. Therefore, we conducted the sales t est using the following range of establishment

5 We use 200 7 Economic Census data in estimating number of establishments by industry. The release schedules for different types of 2007 Economic C ensus data are at http://www.census.gov/econ/census07/pdf/EconCensusScheduleByDate.pdf .6 - 4

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.6-5 **Table 6**  **- 2.**  **Average Receipts for Affected Industry by E nterprise: 200**  **9 ($2008 Million/**  **establishment) SBA Size**  **Standard for Businesses**  **(effective Novem**  **ber 5 ,**  **20 10**  **) Owned By Enterprises with**  **Employee Range:**

**NAICS NAICS Description**  **All Enterprises**  **1 –**  **20**

**E mployees**  **20 –**  **99**

**E mployees**  **100 –** **499**

**E mployees**  **500 +** 

**E mployees**  211111 Crude petroleum &

natural gas extraction 500 employees $ 30.22 $ 2 . 15 $ 33.02 $ 151,76 1,570 211112 Natural gas liquid

extraction 500 employees $172.81 $0.30 NA $11.88 NA 335312 Motor & generator mfg 1,000 employees $18.58 $1.37 $6.14 $15.96 $29.47 333992 Welding & soldering

equipment mfg 500 employees $18.51 $1.56 $6.60 $33.25 NA . NA = Not available. Source: U.S. Census Bureau. 20 12 a . “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 200 9 .” <http://www.census.gov/csd/susb/ Downloaded 2 / 22 /1 2 .6-6 **Table 6 -**  **3. Average Receipts for Affected Industry by**  **Enterprise Receipt Range: 200 7**  **($2008 /establishment) SBA Size Standard**  **for Businesses (effective**  **November 5**  **, 20 10**  **) Ow**  **ned By Enterprises with Receipt Range: NAICS**  **NAICS Description All**  **Enterprises 0**  **– 99K** 

**Receipts 100**  **–**

**499.9K Receipts**  **500 –** 

**999.9K Receipts**  **1,000 –** 

**4,999.9K Receipts**  **5,000,000 –** 

**9,999,999K Receipts**  **<10,000K**

**Receipts 10,000**  **–**

**49,999K Receipts**  **50,000 –** 

**99,999K Receipts**  **100,000K+**

**Receipts** 2211 Electric Power Generation a $ 261.0 $ 31 . 2 $ 272 . 5 $ 724 . 9 $ 2,399 . 5 $ 7,330.5 $2 ,617.7 $ 24,786. 9 $ 67,706.

8 $ 1,394,051

.0 622110 Hospitals $34.5 million in annual receipts $ 202,058.7 NA $23.82 NA $3 ,255.0 $ 7,291.0 $ 4,692.1 $2 3,481. 9 $6 7,545,

6 $ 508,705.8 23 73 10 Highway , street , and bride construction $33.5 million in

Annual Receipts $7.74 $0.06 $0.32 $0.84 $2.74 $8.11 $2.00 $22.62 $56.48 $56.81 23 71 10 Water and sewer line

and related structures , construction $33.5 million in

Annual Receipts $3.89 $0.06 $0.32 $0.85 $2.73 $8.17 $1.84 $20.62 $45.05 $47.27 23 713 0 Power and communication line and related structures construction $33.5 million in

Annual Receipts $3.39 $0.06 $0.31 $0.83 $2.52 $7.75 $1.32 $16.84 $34.50 $23.86

23 7 990 O ther heavy and civil

engineering construction $33.5 million in

Annual Receipts $2.66 $0.06 $0.30 $0.83 $2.48 $7.76 $0.99 $18.72 $40.53 $42.35 92811 National Security NA NA NA NA NA NA NA NA NA NA NA Notes: . National Security is included in this table but does not have size standards. a NAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm in these industries i s defined as small by SBA if, including its affiliates, it is primarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric out put for the preceding fiscal year did not exceed 4 million megawatt hours. NA = Not available. SUSB did not report this data for disclosure or other reasons. Source: U.S. Census Bureau. 200 9 a . “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 200 9 .” <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 b y 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 NAI CS 2 211 and 622110 are fundamentall y different than other industries considered in this analy sis, we used different assumptions about what constitutes the representative establishment and report these assumptions separatel y.

 Case 1: The representative establi shment for all industries uses three 750+ hp engines with an average compliance cost of $1,87 8 per engine, resulting in a total annualized compliance cost of approximately $5,63 4 for this representative establishment.

 Case 2: The representative establishm ent in NACIS 2211 and 622110 uses two 50 to 750+ hp engines with an average compliance cost of $4 19 per engine, resulting in a total annualized compliance cost of $8 38 for this representative establishment. For all other industries, the representative esta blishment uses two 50 to 300 hp engines with an average compliance cost of $1 46 per engine, resulting in a total compliance cost of $ 292 for this representative establishment.

 Case 3: The representative establishment for all industries uses two 50 to 100 hp engines with an average compliance cost of $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 T able 6 - 4) because most of the engines to be affected b y t his proposal in NAI CS 335312, 333992, 211111 , and 211112 are under 300 hp capacit y, and most small entities in these industries will own engines of this size or smaller. This is corroborated b y Fi gur e 6 - 1 and 6 - 2 which shows the distribution of engine population and compliance costs by engine size for all industries. However, it is difficult to make a similar claim for NAI CS 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 non emergency .

6 This claim also cannot be made for NAICS 92811: National Security. How ever, since most national security installations are owned by the federal government (e.g., military bases), EPA assumes these entities w ould not be considered small.6 - 8

For the sales test, we divided the representative 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 Costs Used for Small**  **Entity Analysis ($200 8**  **) 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)** Tot al Annualized Costs ($) $62,0 68,406 $ 7,875,707 $3 04,817,985 $ 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) $1,87 8 $1,87 8 $4 19 $ 146 $68 $68 Assumed Engines Per Establishment 3 3 2 2 2 2 Total Annualized Costs per Establishment $5,63 4 $5,63 4 $8 38 $ 292 $137 $137 * Engine population estimates taken from “I mp acts Associated with NESHAP for Existing Stationary CI RICE,” prepared by Bradley Nelson, E C /R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards, February 19, 201 0 .6 - 9

**Figure 6 -**  **1 .**  **Distribution of Engine Population by Size for All Industries** 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Elec tr ic P owe r

Ge nera tion (2211) Hospitals

(622110) Crude Pet rol eum

& NG Product ion (211111) Natu ra l Gas

Liquid Producers (211112) National Securit y

(92811) Hydro Pow er

Un its (3 35312) Ir rigation Se ts

(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 employ s in anal yz ing 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 b y EPA regulations and profits data normally made available are often not the true profit earned b y firms because of accounting and tax considerations. Revenues as typicall y published are usuall y correct figures and are more reliably rep orted when compared to profit data. The use of a “sales test” for estimating small business impacts for a rulemaking such as this one is consistent with guidance offered b y 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 compli ance guidance to EPA rulewriters regarding the types of small business analysis that should be considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf , p p. 24 - 25. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Elec tr ic P owe r

Ge nera tion (2211) Hospitals

(622110) Crude Pet rol eum

& NG Product ion (211111) Natu ra l Gas

Liquid Producers (211112) National Securit y

(92811) Hydro Pow er

Un its (3 35312) Ir rigation Se ts

(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%, then we consider the final rule to not have a significant impact on the establishment compan y in question. We summarize the industries with cost - to - receipt ratios exceeding 1% below: Primary Analysis:

 Case 2 : NAI CS 2211

 Case 3 : No industries Sensitivity Analysis (unlikely):

 Case 1 : NAI CS 211111, 211112 , with less than 20 employ ees, NAICS 2211 with receipts less than $500,000 per year, NA IC S 234 with receipts less than $500,000 per ye ar, and irrigated farms with receipts of $500,000 or less per y ear In the Case 2 primary

analy sis, onl y establishments in NAI CS 2211 with receipts less than $100,000 per ye ar have cost - to - receipt ratios above 1%. These establishments represent less than 5 percent of affected small establishments. However, establishments earning this level of recei pts are likel y to be using smaller engines than those assumed in Case 2, such as 50 to 100 hp engines. The results of our Case 3 anal ys is demonstrate that these establishments are not significantl y impacted when taking this engine size into account. After considering the economic impacts of this proposed rule o n small entities, we certify that this action will not have a significant economic impact on a substantial number of small entities. This certification is based on the economic impact of this propos al action to all affected small entities across all industries affected. The percentage of small entities impacted by this proposal having annualized costs greater than 1 percent of sales is less than 2 percent according to this analy sis. We thus conclude that there is no significant economic impact on a substantial number of small entities (SI SNOSE) for this proposed rule. Although the proposed rule would not have a significant economic impact on a substantial number of small entities, EPA nonetheless tri ed to reduce the impact of the rule on small entities. When developing the revised standards, EPA took special steps to ensure that the burdens imposed on small entities were minimal. EPA conducted several meetings with industry 8 U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Com ply with the Regulatory Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003 .6 - 12

trade associations to dis cuss regulatory options and the corresponding burden on industry , such as recordkeeping and reporting. In addition, as mentioned earlier in this preamble, EPA proposes to reduce regulatory

requirements for a variet y of area so urces affected under this RI CE rule with amendments to the final RI CE rules promulgated in 2010. We continue to be interested in the potential impacts of this proposed rule on small entities and welcome comments on issues related to such impacts. **6.3 Small Government Entities**  The rule also covers sectors that include entities owned by small and large governments. However, given the uncertainty and data limitations associated with identify ingand appropriatel y classifying these entities, we computed a “ revenue ” test for a model small gov ernment, where the annualized compliance cost is a percent age of annual governme nt 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 b y t he US SBA’s Office of Advocacy . 10 For example, from the 2002 Census (in 200 8 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. F or the smallest group of local governments (<10,000 people), the c o st - 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 regarding the types of small business analysis that should be considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf , pp. 24 - 25. 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 Orde r 13272, May 2003 .7 - 1 **SECTION 7 HUMAN HEALTH BENEFIT**  **S OF EMISSIONS REDUCTIONS**  **Synopsis** Implementation of emissions controls required b y the proposed CIRICE NESHAP reconsideration is expected to reduce emissions of hazardous air pollutants (HAP) and have ancillary co - benefits that would lower ambient concentrations of PM 2.5 and ozone . Inthis 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 $ 77 0 mil lion to $ 1.9 b illion at a 3% discount rate and $ 69 0 million to $ 1.7 b illion at a 7% discount rate in 2013 . All estimates are in 2010$. These estimates reflect the monetized human health benefits of reducing cases of morbidit y and premature mortalit y among populations exposed to PM 2.5 reduced b y this rule . These estimates reflect EPA’s most current interpretation of the scientific literature. Higher or lower estimates of benefits are possible using other assumptions; examples of this are provided in Figure 7 - 2. Data, resource, and methodological limitations prevented EPA from monetizing the benefits from several important benefit categories, including benefits from reducing exposure to HAP, carbon monoxide, and ozone, as well as visibility impairment. In addition to reducing emissions of PM precur sors, this rule would reduce 1,0 00 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 CIRICE rule, as we state earlier in this document, this proposed reconsideration would reduce emissions of directly emitted particles and VOCs. Because these emissions are precursor s 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 analy tical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 - related benefits or provide estimates of the health benefits associat ed with exposure to HAP, CO, or ozone . Instead, we used the “benefit - per - ton” approach to estimate these benefits . The methodology employ ed in this anal ys is 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 - to n estimates provide the total monetized human health benefits (the sum of premature mortality and premature morbidity) of reducing one ton of PM 2.5 f rom a7 - 2

specified source. EPA has used the benefit per - ton technique in several previous RIAs, including the recent S O 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 unquantified health effects asso ciated with exposure to HAP, CO, or ozone nor welfare effects such visibility impairment that are described in section 7.2 . Itis important to emphasize that the list of unquantified benefit categories is not exhaustive, nor is quantification of each effe ct 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**

**Inform ation**  **(refers to CSAPR RIA)**  **Improved Human Health** Reduced incidence of premature mortality from exposure to PM 2.5 Ad ult 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 mo rbidity 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 Em ergency room visits for asthma (all ages) 

 

 Section 5.4 Ac ute bronchitis (age 8 - 12) 

 

 Section 5.4 Lo wer 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 Em ergency room visits for cardiovascular effects (all ages) -- -- Section 5.4 Strokes and cerebrovascular disease (age 50 - 79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA 2 Other respiratory effects (e.g., pulmonary function, non - asthma ER visits, non bronchitis 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 qualitative ly due to time and resource limitations for this analysis. 2 We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods. 3 We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other significant concerns ov er 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

anal ys is.7 - 4  One estimate is based on the concentration - response (C - R) function developed from the extended anal ys is of American Cancer Society (ACS) cohort, as reported in Pope et al. (2002) , a stud y that EPA has previously used to generate its primary benefits estimate. When calculating the estimate, EPA applied the effect coefficient as reported in the stud y without an adjustment for assumed concentration threshold of 10 μg/m 3 as was d one in recent ( 2006 - 2009 ) Office of Air and Radiation RIAs.

 One estimate is based on the C - R function developed from the extended analy sis of the Harvard Six Cities cohort, as reported b y 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 anal ys is in EPA’s final RIA for the PM 2.5 NAAQS. For that stud y, twelve experts (labeled A through L) provided independent estimates of the PM 2.5 - mortality concentration - response function. EPA practice has been to develop independent estimates of PM 2.5 - mortality estimates corresponding to the concentration - response function provided b y 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 Societ y cohort (Pope et al., 2002 ) and the Harvard Six Cities cohort (Laden et al., 2006 ). 1 These are logical c hoices for anchor points in our presentation because, while both studies are well designed and peer reviewed, there are strengths and weaknesses inherent in each, which we believe argues for using both studies to generate benefits estimates. Previously , EPA had calculated benefits based on these two empirical studies, but derived the range of benefits, including the minimum and maximum results, from an expert elicitation of the relationship between exposure to PM 2.5 and premature mortality (Roman

1 These tw o studies specify multi - pollutant models that control for SO 2 , am ong 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 uncertaint y in the concentration - response functio n for mortality and the degree of variability in the expert responses. Because the experts used these cohort studies to inform their concentration - response functions, benefits estimates using these functions generall y fall between results using these epid emiology 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 analy sis should consult 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, 2012). 3 The primary difference between the estimates used in this anal ys is and the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality modeling data utilized. The air qualit y modeling data used in this anal ys is use more narrow sector s. In addition, the updated air qualit y 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 est imates applied, and valuation techniques applied did not change. As noted below in the characterization of uncertaint y, these updated estimates still have similar limitations as all national - average benefit per - ton estimates in that they reflect the geogra

phic distribution of the modeled emissions , which may not exactl y match the emission reductions in this rulemaking, and they may not reflect local variability

in population density , meteorology , exposure, baseline health incidence rates, or other local fac tors for an y specific location. In this analysis, we apply the se national benefit - per - ton estimate s calculated for this category for directl y 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 y et sufficient to allow differentiation of effects estimates b y particle ty pe. Directl y emitted particles are the primary PM 2.5 precursors affected b y this rule. Even though we assume that all fine particles 2 Please see the Section 5.2 of the Portland Cement RIA in Appendix 5A for more informat ion 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 mo re rural than the average of the non - EGU sources modeled, then it is possible that the benefits may be som ewhat 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 availab le information on the air quality impact on a per ton basis for these sources.7 - 6

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 generall y small compared to other PM 2.5 precursors (U.S. EPA, 2012). The benefit - per - ton coefficients in this analy sis were derived using modified versions of the health impact functions used in the PM NAAQS Regulatory Impact Analy sis (U.S. EPA, 2006) . Specificall y, this anal ys is uses the method first applied in th e 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 analy s is 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 bod y of scientific literature, EPA now e stimates PM related mortalit y without applying an assumed concentration threshold. EPA’s Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was reviewed b y EPA’s Clean Air Scientific Advisory Committee (U.S. EPA - SAB, 2009a; U.S. EPA - SAB, 2009b), concluded that the scientific literature consistently finds that a no - threshold log - linear model most adequatel y portrays the PM - mortality concentration - response relationship while recognizing potential uncertainty about the exact shape o f the concentration - response function. Consistent with this finding, we have conformed the previous threshold sensitivity anal ys is to the current state of the PM science by incorporating a “Lowest Measured Level” (L ML ) assessment , which is a method EPA ha s employ ed in several recent RIAs including the Cross - State Air Pollution Rule (U.S. EPA, 2011 b ). This information allows readers to determine the portion of population exposed to annual mean PM 2.5 levels at or above the L MLof each study ; in general, our confidence in the estimated PM mortality decreases as we consider air quality levels further below the L MLin major cohort studies that estimate PM - related mortalit y. While an L MLassessment provides some insight into the level of uncertainty in the estimated PM mortality

benefits, EPA does not view the LMLas a threshold and continues to quantify PM related mortalit y impacts using a full range of modeled air qualit y concentrations. Itis important to emp hasize that we have high confidence in PM 2.5 - related effects down to the lowest L MLof the major cohort studies, which is 5.8 μg/m 3 . J ust because we have greater confidence in the 4 Additional updates since the Cement RIA include a revised VSL and updated baseline incidence rates.7 - 7

benefits above the LML, this does not mean that we have no confidence that benefits occur below the LML. F or a summary of the scientific review statements regarding the lack of a threshold in the PM 2.5 - mortality relationship, see the Technical Support Document (TSD) entitled Summary of Expert Opinions on the Existence of a Threshold in the Concentration Response Function for PM 2.5 - related Mortality (U.S. EPA, 2010 b ) . For this anal ys is, 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 mortalit y 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 distribution of exposure to baseline air qualit y levels. As a surrogate mea sure 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 . It is important to note that baseline exposure is o nly one parameter in the health impact function, along with baseline incidence rates population, and change in air quality . In other words, the percentage of the population exposed to air pollution below the LML is not the same as the percentage of the po pulation 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 specif ic rule. Therefore, caution is warranted when interpreting the LML assessment for this rule . The results of this anal ys is 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 analy sis of some of the available studies. OAR arrived at a VSL using a range of $1 million to $10 million (2000$) consistent with two meta - anal ys es of the wage - risk literature. The $1 million value represented the lower end of the interquartile range from the Mrozek and Tay lor (2002) meta - analy sis of 33 studies. The $10 million value represented the upper end of the interquartile range from the Viscusi and Aldy (2003) meta - anal ys is of 43 studies. The mean estimate of $5.5 million (2000$) 5 was also consistent with the mean VSLof $5.4 million estimated in the Kochi et al. (2006) meta - anal ys is. However, the Agency neither changed its official guidance on the use of VSL in rulemakings nor subjected the interim estimate to a

5 After adjusting the VSL for a different currency year ( 2010$ ) and to ac count for income grow th to 2015 of the $5.5 million value, the VSL is $ 8.0 million.7 - 8

scientif ic peer - review process through the Science Advisory Board (SAB) or other peer - review group. During this time, the Agency continued work to update its guidance on valuing mortalit y risk reductions, including commissioning a report from meta - anal yt ic experts to evaluate methodological questions raised b y 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 - anal yt ic experts, the SAB - EEAC advised the Agency to up date its guidance using specific, appropriate meta - anal yt ic techniques to combine estimates from unique data sources and different studies, including those using different methodologies (i.e., wage - risk and stated preference) (U.S. EPA - SAB, 2007). Unt il 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 b y the SA B in the Guidelines for Preparing Economic Analy ses (U.S. EPA, 2000) 6 while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates derived from 26 labor market and contingent valuation studies published between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$). 7 The Agency is committed to using scientifically

sound, appropriatel y 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 are as with attaining the PM NAAQS. Because the PM NAAQS RIAs also calculate PM benefits, there are important differences worth noting in the design and analy tical objectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air quality standard nationwide based on an array of emission control strategies for different sources. In short, NAAQS RIAs hypothesize, but do not predict, the control strategies that States may choose to enact when implementing a NAAQS. The settin g of a NAAQS does not directl y result

6 In revised Economic Guidelines (U.S. EPA, 2010c ), EPA retained the VSL endorsed by the SAB with the understanding that further updates to the mortality risk valuation gu idance would be forthcoming in the near future. Therefore, this report does not represent 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 ($20 10 ) and to account for income growth to 20 15 . After applying these adjustments to the $6.3 million value, the VSL is $ 9.2 million .7 - 9

in costs or benefits, and as such, the NAAQS RIAs are merel y 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 qualit y improvements as estimated in the illustrative PM 2.5 NAAQS RIA. By contrast, the emission reductions for implementation rule s are from a specific class of well - characterized sources. In general, EPA is more confident in the magnitude and location of the emission reductions for implementation rules rather than illustrative NAAQS anal ys es . Emission reductions achieved under these and other promulgated rules will ultimately be reflected in the baseline of future NAAQS anal ys es, which would reduce the incremental costs and benefits associated with attaining the NAAQS. EPA remains forward looking towards the next iteration of the 5 - ye ar review cy cle for the NAAQS, and as a result does not issue updated RIAs for existing NAAQS that retroactivel y update the baseline for NAAQS implementation. For more information on the relationship between the NAAQS and rules such as anal yz ed here, pleas e see Section 1.2.4 of the SO 2 NAAQS RIA (U.S. EPA, 2010 a ).7 - 10

Figure 7.1 illustrates the relative breakdown of the monetized PM 2.5 he alth benefits.

**Figure 7 -**  **1: Breakdown of Monetized PM**  **2.5 Health Benefits using Mortality F**  **uncti on** 

**from Pope et al. (2002)** ***** *T his 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 mo rtality wo uld be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be similar if a 7% discount rate was used. Table 7 - 2 provides a general summary of the monetized PM - related health benefits by precursor , including the emission reductions and benefit - per - ton estimates at discount rates of 3% and 7%. 8 Table 7 - 3 provides a summary of the reductions in health incidences as a result of the polluti on 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 P M mortality . Figure 7 - 2 provide s a visual representation of the range of PM 2.5 - related benefits estimates using 8 To comply with Circular A - 4, EPA provides monetized benefits using discount rates of 3% and 7% (OMB, 2003). These benefits are estimated fo r a specific analysis year (i.e., 2013 ), and most of the PM benefits occur within that year with two exceptions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow - up medical costs and lost wages. For premature m ortality, we assume that there is a “ cessation ” lag between PM exposures and the total realization of changes in health effects. Although the structure of the lag is uncertain, EPA follows the advice of the SAB - HES to assume a segmented lag structure c haracterized 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 valuation of premature mortalities that occur after the analysis year. As such, the monetized benefits using a 7% discount rate are only appr oximately 10% less than the monetized benefits using a 3% discount rate. **Adult Mo**  **rtality -**  **Po pe**  **e t**  **al. 93%**  **Chronic Bronchi**  **ti s**  **4% AMI**  **2%** Ac ute Respi ratory Symptom s 0. 5%

Infant Mortality 0. 4% Wo rk Los s Day s 0. 2% Hospi tal Admi ssi ons, Cardio

0. 2% Hospi tal Admi ssi ons, Re sp 0. 04% Asthma Ex ace rbation 0. 01% Acute B ronchitis 0. 01% UpperR es p Symp 0. 00% Lower Re sp Symp 0. 00% ER Vi si ts, Re sp 0. 00% Other 1%7 - 11

concentration - response functions supplied by experts . Figure 7 - 3 shows a breakdown of monetized benefits by

engine size. The benefit - per - ton estimates shown in this RIA are different than the benefit - per - ton estimates cited in the 2010 final SIRICE RIA for two reasons. First, these estimates are based on updated air qualit y m odeling, which results in slightly higher benefi ts per ton for other non EGU point sources than the previous modeling. Second, these estimates have been inflated to 2010$. Third, the new air quality modeling did not provide estimates associated with reducing VOCs.

**Table 7 -**  **2: General Summary of Mone**  **tized PM**  **2.5 -**  **Related Health Co -**  **Benefits Estimates**

**for the Proposed 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 (m illions**  **of 2010$ at 3%)**  **Total Monetized**

**Benefits (m illions**  **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 tw o 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 impairment. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton of precursor reduced has a different propensity t o 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.7 - 12

**Table 7 -**  **3: Summary of Reductions in**  **Health Incidences from PM 2.5**  **- Related**  **Co -**  **B enefits** 

**for Proposed CI RICE NESHAP**  **Reconsideration*** **Avoided Prem ature Mortality**  Pope et al. 85 Laden et al. 220 **Avoided Morbidity** Chronic Bronchitis 59 Em ergency Department Visits, Respiratory 66 Hospital Ad missions, Respiratory 16 Hospital Admissions, Cardiovascular 35 Ac ute Bronchitis 130 Lo wer Respiratory 1,700 Upper Respiratory 1,300 Minor Restricted Activity Days 68,000 Work Loss Days 12,000 Asthma Exacerbation 2,800 Ac ute 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 Proposed 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 Epide**  **miology 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 benefits estimates from the Expert Elicitation are provided as a reasonable characterization of the uncertainty in the mortality estimates associated with the concentration response function. Confi dence intervals are unavailable for this analysis because of the benefit - per - ton methodology7 - 14

**Figure 7 -**  **2: Total Monetized PM**  **2.5 Co**  **- Benefits of**  **Proposed 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 from EPA’s expert elicitation on PM mortality. The res ults shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration - response function provided in those studies.

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

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

PM 2.5 mortality be nefit s es tima te s derive d from 2 epide miology functions and 12 exp er t functions 

### 2013* 3% DR 7% DR7 - 15

**Figure 7 -**  **3: Breakdown of**  **Total Monetized PM 2.5**  **Co -**  **Benefits of Propos**  **ed CI RICE**

**NESHAP Reconsideration by Engine Size**  **7.2 Unquantified Benefits**  The monetized benefits estimated in this RIA onl y reflect a subset of benefits attributable to the health effect reductions associated with ambient fine particles. Data, time, and reso urce 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 ecos ys tem effects, and visibility imp airment . This does not imply that there are no benefits associated with these emission reductions. These benefits are described qualitatively

in this section. **7.2.1 HAP Benefits** Even though emissions of air toxics from all sources in the U.S. declined by approximately 42% since 1990, the 2005 National - Scale Air Toxics Assessment (NATA) predicts that most Americans are exposed to ambient concentrations of air toxics at levels that have the pot ential to cause adverse health effects (U.S. EPA, 2011 c ). 9 The levels of air toxics to which people are exposed vary

depending on where people live and work and the kinds of activities in which they engage. In order to identify and prioritize air toxics, emission source t ypes and locations that are

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

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 emission s 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 5 0 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldeh yde and benzene. 11 Secondary formation (e.g., formaldehy de forming from other emitted pollutants) was the largest contributor to cancer risks, whi le 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, cardiovascul ar, liver, kidney , and respiratory effects as well as effects on the immune and reproductive sy stems. 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 potenti al for adverse noncancer respiratory health effects. Results from the 2005 NATA indicate that acrolein is the primary driver for noncancer respiratory

risk.

10 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertainties are discussed on the 2005 NATA w ebsite. Even so, this modeling framework is very useful in identifying air toxic pollutants and sources of greatest concern, setting regulatory priorit ies, 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 inc luding both quantitative (e.g., model - to - mo nitor ratios) and qualitative (e.g., quality of data, review of emission inventories) judgments can be found at http://www.epa.gov/ttn/atw/nata/roy/page16.html. 12 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database (http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal species). 13 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species). 14 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.7 - 17

Figure 7 - 4 and Figure 7 - 5 depict the estimated census tract - level carcinogenic risk and noncan cer respiratory

hazard from the assessment. It is important to note that l arge reductions in HAP emissions may

not necessarily

translate into significant reductions in health risk because toxicity varies b y pollutant, and exposures may or may not exceed l evels of concern. For example, acetaldeh yd e mass emissions are more than double acrolein emissions on a national basis, according to EPA’s 2005 National Emissions Inventory (NE I). However, the Integrated Risk Information Sy stem (I RI S) reference concentration (RfC) for acrolein is considerabl y lower than that for acetaldeh yd e, suggesting that acrolein could be potentially more toxic than acetaldeh yde. Thus, it is important to account for the toxicity and exposure, as well as the mass of the targeted emiss ions.

**Figure 7**  **- 4**  **Estimated Chronic Census Tract Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA)** 7 - 18

**Figure 7**  **- 5**  **Estimated Chronic Census Tract Noncancer (Respiratory) Risk from HAP exposure from outdoor sources (2005 NATA)**  Due to meth odology

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 anal ys es of the benefits of reductions i n 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 anal ys es, EPA relied on unit risk factors (URF) developed through risk assessment procedures. 15 These URFs are designed to be conservative, and as such, are more likely

to represent the high end of the distribution of risk rather than a best or most likely estimate of risk. As the purpose of a benefit anal ys is 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 anal ys es, advice from the EPA’s Science Advisory Board (SAB) recommended that we avoid

15 The unit risk factor is a quantitative estimate of the carcinogenic potency of a pollutant, often expressed as the p robability of contracting cancer from a 70 - year lifetime continuous exposure to a concentration of one μg/m 3 of a pollutant.7 - 19

using high - end estimates in benefit anal ys es (U.S. EPA - SAB, 2002 ). Since this time, EPA has continued to develop better methods for anal yz ing the benefits of reductions in HAP . As part of the second prospect ive anal ys is of the benefits and costs of the Clean Air Act (U.S. EPA, 2011 a ), EPA conducted a case stud y analy sis 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 Anal ys is concluded that “the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air pollutants ( HAPs ) are daunting...due to a lack of exposure - response functions, uncertainties in emissions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods” (U.S. EPA - SAB, 2008 ). In 2009, EPA convened a workshop to address the inherent complexities, limitations, and uncertainties in current methods to quantify the benefits of reducing HAP . Recommendations from this workshop included identifying research priorities, focusing on susceptible and vulnerable populations, and improving dose - response relationships (Gwinn et al., 2011 ). In summary , monetization of the benefits of reduct ions in cancer incidences requires several important inputs, including central estimates of cancer risks, estimates of exposure to carcinogenic HAP , and estimates of the value of an avoided case of cancer (fatal and non - fatal). Due to methodology

and time limitations under the court - ordered schedule, we did not attempt to monetize the health benefits of reductions in HAP in this analy sis. Instead, we provide a qualitative anal ys is of the health effects associated with the HAP anticipated to be reduced b y th ese 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 e ngines is anticipated to reduce 1 ,000 tons of HAP each y ear. 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 formaldeh yde as a probable human carcinogen based on evidence in humans and in rats, mice, hamsters, and monkey s. 16 Substantial additional research since that time informs current scientific understanding of the health effects associated with exposure to formaldeh yd e. These include recentl y published researc h conducted by the National Cancer Institute (NCI) which found an increased risk of nasophary ngeal cancer and ly mphohematopoietic malignancies such as leukemia among workers exposed to formaldeh yde. 17 , 18 Inan analy sis of the l ymphohematopoietic cancer mort alit y from an extended follow - up of these workers, NCIconfirmed an association between l ymphohematopoietic cancer risk and peak formaldeh yde exposure s. 19 A recent NIOSH stud y of garment workers also found increased risk of death due to leukemia among worke rs exposed to formaldehy de. 20 Extended follow - up of a cohort of British chemical workers did not find evidence of an increase in nasophary

ngeal or l ymphohematopoietic 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 formaldeh yde in rodents and primates b y the Chemical Industry I nstitute of Toxicology

(CIIT, now renamed the Hamner Institutes for Health Sciences), with a focus on u se of rodent data for refinement of the quantitative cancer dose - response assessment. 22 , 23 , 24 CI IT’s risk assessment of

16 U.S. EPA. 1987. Assessment of Health Risks to Garment Workers and Certain Home Residents from Exposure to Form aldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA - HQ - OAR - 2010 - 0162 . 17 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hay es, 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.; Haye s, R. B.; Blair, A. 2004. Mortality from solid cancers among workers in formaldehyde industries. American Journal of Epidemiology 159: 1117 - 1130. Docket EPA - HQ OAR - 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 w orkers exposed to formaldehyde: an update. Occup. Environ. Med. 61: 193 - 200. Docket EPA - HQ - OAR - 2010 - 0162 . 21 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow - up of a cohort of British chemical w orkers 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 Kal isak, J Preston, and FJ Miller. 2003. Biologically mo tivated computational modeling of formaldehyde carcinogenicity in the F344 rat. Tox Sci 75: 432 - 447. Docket EPA - HQ - OAR - 2010 - 0162 . 23 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Presto n, and FJ Miller. 2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose - response predictions derived from biologically - mo tivated computational modeling of a combined rodent and human dataset. Tox Sci 82: 279 - 296. Docket EPA - HQ - OAR 2010 - 0162 .7 - 21

formaldeh yde incorporated mechanistic and dosimetric information on formaldehyde. These data were modeled using a biologicall y - 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 suppo rtive of interpreting the CIIT model results as providing a conservative (health protective) estimate o f human risk. 29 EPA research also examined the contribution of the two - stage modeling for formaldeh yde 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 CI IT stud y that formaldehy de’s direct mutagenic action is not relevant to the compound’s tumorigenicit y was found not to hold under variations of modeli ng assumptions. 30 Based on the developments of the last decade, i n 2004, the working group of the IARC concluded that formaldehy de is carcinogenic to humans (Group 1), on the basis of sufficient evidence in humans and sufficient evidence in experimental ani mals - a higher classification than previous IARC evaluations. After reviewing the currentl y available epidemiological evidence, the IARC (2006) characterized the human evidence for formaldeh yd e carcinogenicit y as “sufficient,” based upon the data on naso phary ngeal cancers; the epidemiologic evidence on leukemia was characterized as “strong.” 31 Formaldeh yd e exposure also causes a range of noncancer health effects, including irritation of the ey es (burning and watering of the ey es), nose and throat. Effec ts from repeated

24 Chemical Industry Institute of Toxicology (CIIT).1999. Formaldehyde: Hazard characterization and dose - response assessment for carcinogenicity by the route of inhalation. CIIT, September 28, 1999. Research Triangle Park, NC. Docket EPA - HQ - OAR - 2010 - 0162 . 25 U.S. EPA. Analysis of the Sensitivity and Uncertainty in 2 - Stage Clonal Growth Models for Formaldehyde with Relevance to Other Biologically - Based Dose Response (BBDR) Models. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R - 08/103, 2008. Docket EPA - HQ - OAR - 2010 - 0162 . 26 Subramaniam, R; Chen, C; Crump, K; .et .al. (2008) Uncertainties in biologically - based modeling of formaldehyde - induced cancer risk: identification of key issues. Risk Anal 28(4):907 - 923. Docket EPA - HQ OAR - 2010 - 0162 . 27 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde - induced carcinogenicity in the rat: A limited sensitivity analysis

– I. Risk Anal, 27: 1237

– 1254. Docket EPA - HQ - OAR - 2010 - 0162 . 28 Crump, K; Chen, C; F ox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehyde induced 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 b iologically motivated model for formaldehyde induced respiratory cancer in humans. Ann Occup Hyg 52:481 - 495. Docket EPA - HQ - OAR - 2010 - 0162 . 30 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde - induced carcinogenicity in the rat: A limited sensitivity analysis

– I. Risk Anal, 27: 1237

– 1254. Docket EPA - HQ - OAR - 2010 - 0162 . 31 International Agency for Research on Cancer (2006) Formaldehyde, 2 - Butoxyethanol and 1 - tert - Butoxypropan - 2 - ol. Monographs Volume 88. Wor ld Health Organization, Lyon, France. Docket EPA - HQ - OAR - 2010 - 0162 .7 - 22

exposure in humans include respiratory tract irritation, chronic bronchitis and nasal epithelial lesions such as metaplasia and loss of cilia. Animal studies suggest that formaldehy de may also cause airway

inflammation

– including eosinop hil infiltration into the airway s. There are several studies that suggest that formaldeh yde ma y increase the risk of asthma

– particularl y in the yo ung. 32 , 33 The above - mentioned rodent and human studies, as well as mechanistic information and their anal ys es , were evaluated in EPA’s recent Draft Toxicological Review of Formaldehy de

– Inhalation Assessment through the Integrated Risk Information Sy stem (I RI S) program. This draft IRIS assessment was released in June 2010 for public review and comment and exter nal peer review b y 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 currentl y revising the dr aft 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 possibl y carcinogenic to humans (Group 2B) by the IARC. 35 , 36 The primary nonc ancer effects of exposure to acetaldehyde vapors include irritation of the eyes, skin, and respiratory tract. 37

32 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological profile for Formaldehyde. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. http://www.atsdr.cdc.gov/toxprofiles/tp111.html . Docket EPA - HQ - OAR - 2010 - 0162 . 33 WHO (2002) Concise International Chemical Assessment Document 40: Formaldehyde. Published under the joint sponsorship of the United Nations Environment Programme, the International Labour Organization, and the World Health Organization, and produced w ithin the framework of the Inter - Organization Programme for the Sound Management of Chemicals. Geneva. Docket EPA - HQ - OAR - 2010 - 0162 . 34 U.S. Environmental Protection Agency (U.S. EPA). 1991. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available ele ctronically at http://www.epa.gov/iris/subst/0290.htm. 35 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183. 36 International Agency for Research on Cancer (IARC). 1999. Re - evaluation of some organic chemicals, hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, Vol 71. Lyon, France. 37 U.S. Environmental Protection Agency (U.S. EPA). 1991 . Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.7 - 23

Acrolein EPA determined in 2003 that the human carcinogenic potential of acrolein could not be determined because the available data were ina dequate. 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 hy persecretion and congestion. The intense irritancy of this carbonyl has been demonstrated during controlle d tests in human subjects, who suffer intolerable ey e 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 I RI S Human Health A ssessment 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 ey e irritation with increasing concentrations leading to more extensive ey e, nose and respiratory s ymptoms. 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 hy per - responsiveness. 44 In a r ecent study , the acute respiratory

irritant effects of exposure to 1.1 ppm acrolein were more pronounced in mice with allergic airway

disease by

comparison to non - diseased mice which also showed decreases in

38 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf. 39 International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals, World Health Organization, Lyon, France. 40 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. EPA/635/R - 03/003. p. 10. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/toxrevie ws/0364tr.pdf. 41 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. 2003. Research and Development, National Center for Environmental Assessment, Washington, DC. E PA/635/R - 03/003. This material is available at http://www.epa.gov/iris/toxrevie ws/0364tr.pdf. 42 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center for Env ironmental Assessment, Washington, DC. EPA/635/R 03/003. 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. R esearch 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. 44 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Ris k Information System File of Acrolein. 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

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., emphy sema, asthma) are expected to be at increased risk of developing adverse responses to strong respiratory

irri tants 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 huma ns and animals and increased proliferation of bone marrow cells in mice. 46 , 47 , 48 EPA states in its IR IS database that data indicate a causal relationship between benzene exposure and acute l ym phocy tic leukemia and suggest a relationship between benzene expos ure and chronic non - ly mphocy tic leukemia and chronic l ym phocy tic 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 inclu ding blood disorders, such as preleukemia and aplastic anemia, have also been associated with long - term exposure to benzene. 51 , 52

45 Morris JB, Symanowicz PT, Ols en JE, et al. 2003. Immediate sensory nerve - mediated respiratory responses to irritants in healthy and allergic airw ay - diseased mice. J Appl Physiol 94(4):1563 - 1571. 46 U.S. Environmental Protection Agency (U.S. EPA). 2000. Integrated Risk Information System File for Benzene. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0276.htm. 47 International Agency for Research on Cancer, IARC mo nographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agency for Research on Cancer, World Health Organization, Lyon, France, p. 345 - 389, 1982. 48 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. (1992) Synergistic action of the benzene metabolite hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony - stimulating factor in vitro, Proc. Natl. Acad. Sci. 89:3691 - 3695. 49 International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health Organization, Lyon, France. 50 U.S. Department of Health a nd Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183. 51 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193 - 197. 52 Goldstein, B.D. (19 88). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541 - 554.7 - 25

Methanol Exposure of humans to methanol by inhalation or ingestion may result in central nervous sy stem depression and degenerative changes in the brain and visual s ys tems. After inhaled or ingested, methanol is converted to formate, a highly toxic metabolite that within the course of a few hours can cause narcosis, metabolic acidosis, headaches, severe abdominal and leg pain and visual degeneration that can lead to blindness. 53 Methanol has been demonstrated to cause developmental toxicity in rats and mice, and reproductive and developmental toxicity in monkey s. A number of studies have reported adverse effects in the off

spring of rats and mice exposed to methanol by inhalation including reduced weight of brain pituitary

gland, thy

mus, thy roid, reduced overall fetal body weight and increased incidence of extra ribs and cleft palate. 54 , 55 , 56 Methanol inhalation studies using rhesus monkey s 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 carcinogenicit y. 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 I RI S database. 61

53 Row e, 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 pow er station: summary report on tests with monkeys, rats and mice. Tokyo, Japan. 55 Nelson, BK; Brightwell, WS; MacKenzie, DR; Khan, A; Bu rg, JR; Weigel, WW; Goad, PT. 1985. Teratological assessment of methanol and ethanol at high inhalation levels in rats. Toxicol Sci, 5: 727 - 736. 56 Rogers, JM; Barbee, BD; Rehnberg, BF. 1993. Critical periods of sensitivity for the developmental toxicity of inhaled methanol. Teratology, 47: 395. 57 Burbacher, T; Grant, K; Shen, D; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part II: development al effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA. 58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhal ation exposure to methanol in nonhuman primates Part I: methanol disposition and reproductive toxicity in adult females. Health Effects Institute. Cambridge, MA. 59 Burbacher, TM; Grant, KS; Shen, DD; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chr onic maternal methanol inhalation in nonhuman primates (Macaca fascicularis): reproductive performance and birth outcome. Neurotoxicol Teratol, 26: 639 - 650. 60 Burbacher, TM; Shen, DD; Lalovic, B; Grant, KS; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 20 04. Chronic maternal methanol inhalation in nonhuman primates (Macaca fascicularis): exposure and toxicokinetics prior to and during pregnancy. Neurotoxicol Teratol, 26: 201 - 221. 61 U.S. EPA Integrated Risk Information System (IRIS) database is available at : www.epa.gov/iris7 - 26

**7.2. 2**  **Ozone Co**  **-**

**Benefits** In the presence of sunlight, NOx and VOCs can undergo a chem ical reaction in the atmosphere to form ozone. Reducing ambient o zone concentrations is associated with significant human health benefits, including mortality and respiratory

morbidity

(U.S. EPA, 2008 a ). Epidemiological researchers have associated ozone exposure with adverse health effects in numerous toxicological, clinical and epidemio logical studies (U.S. EPA, 2006c ). These health effects include respiratory morbidity such as fewer asthma attacks, hospital and ER visits, school loss day s, as well as p remature 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, r elative 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) conclude d 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 depar tment 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 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 an d respiratory morbidity

and mortality . The evidence is also suggestive of a causal relationship for birth outcomes and developmental effects following long - term exposure to CO, and for central nervous system effects linked to short - and long - term exposure to CO. **7.2. 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 sulfates, nitrates, organic carbon, elemental carbon, and soil (Sisler, 1996). Suspended particles and gases degrade visibility by scattering and absorbing light. Higher visibility impairment levels in the East are due to generally

higher concentrations of fine particles, particularl y sulfates, and higher ave rage7 - 27

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 anal ys es (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 w e 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 an y complex anal ys is, there are likel y to be many sources of uncertainty . Many inputs are used to derive the final estimate of economic benefits, including emission inventories, air quality models (with their associated parameters and inputs), epidemiological estimates of concentration - response (C - R) functions, estimates of values, population estimates, income estimates, and estimates of the future state of the world (i.e., regulations, technology , and human behavior). For some parameters or inputs it may be possible to provide a statistical repres entation 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 variet y of uncertainties associated with these P M 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 y ear. It is important to note that the monetized benefit - per - ton esti mates used here reflect specific geographic patterns of emissions reductions and specific air quality and benefits modeling assumptions. For example, these estimates do not reflect local variability in population density , meteorology , exposure, baseline he alth incidence rates, or other local factors. Use of these $/ton values to estimate benefits may lead to higher or lower benefit estimates than if benefits were calculated based on direct air quality modeling. Great care should be taken in applying these e stimates to emission reductions occurring in any specific location, as these are all based on national or broad regional emission reduction programs and therefore represent average benefits - per - ton over the entire United States. The benefits - per - ton for em ission reductions in specific locations may be very different than the estimates presented here. For more information, see the TSD describing the calculation of the new benefit - per - ton estimates (U.S. EPA, 2012).7 - 28

PM 2.5 mortality

benefits are the largest b enefit category that we monetized in this anal ys is. 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 L MLassessment. For this anal ys is, policy - specific air quality data is not available due to time or resource limitations , thus we are unable to estimate the percentage of premature mortality associated with this specific rule’s emission reductions at each 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 LMLof the cohort studies (Figures 7 - 6 and 7 - 7 ), increasing our confidence in the PM mortality anal ys is. Figure 7 - 6 shows a bar chart of the p ercentage of the population exposed to various air quality levels in the pre - and post - policy

po licy . Figure 7 - 7 shows a cumulative distribution function of the same data. Both figures identify the LM L 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 a bove the LM L. 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 L MLof 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 LM L for each stud y. It is important to emphasize that we have high confidence in PM 2.5 - related effects down to the lowest L MLof the major cohort studies. Just because we have greater confidence in the benefits above the LML, this does not mean that we have no confidence that benefits occur below the LML. A large fraction of the baseline exposure occur s below the level of the Nati onal 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 protecti ve of public health within an adequate margin of safety , taking into consideration effects on susceptible populations. While benefits occurring below the standard may be less certain than those occurring above the standard, EPA considers them to be legitim ate components of the total benefits estimate.**Figure 7 -**  **6. Percentage of Adult Population by Annual Mean PM**  **Baseline**

7 - 29 **2.5 Exposure**  **in the Figure 7**  **- 7.**  **Cumulative Distribution of Adult Population Exposure**  **in the Baseline** Above we present the estimates of the total benefits, based on our interpretation of the best available scientific literature and methods and supported by the SAB (NRC, 2002 ). The benefits estimates are subject to a number of assump For example, for key

assumptions underlying the estimates for premature mortality, which ty picall y account for more than 90% of the total benefits, we were able to quantify include the following: 1. PM 2.5 benefits were derived thr local variability

in population density , meteorology , exposure, baseline health incidence rates, or other local factors that might lead to an over estimate of the actual benefits of con not have data on the specific location of the air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different locations, such benefit - per - ton estimates are based on emissions from existing sources. To the extent 7 - 30 **Cumulative Distribution of Adult Population by**  **Annual Mean PM**

**in the Baseline** present the estimates of the total benefits, based on our interpretation of the best available scientific literature and methods and supported by the SAB - HES and the NAS

). The benefits estimates are subject to a number of assump tions and uncertainties. For example, for key

assumptions underlying the estimates for premature mortality, which

90% of the total benefits, we were able to quantify include the

benefits were derived thr ough benefit per - ton estimates, which do not reflect local variability

in population density , meteorology , exposure, baseline health incidence rates, or other local factors that might lead to an over - estimate or under estimate of the actual benefits of con trolling directly emitted fine particulates. not have data on the specific location of the air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different locations, such as designated nonattainment areas. In addition, the

ton estimates are based on emissions from existing sources. To the extent **Annual Mean PM 2.5**  present the estimates of the total benefits, based on our interpretation of the HES and the NAS tions and uncertainties. For example, for key

assumptions underlying the estimates for premature mortality, which

90% of the total benefits, we were able to quantify include the ton estimates, which do not reflect local variability

in population density , meteorology , exposure, baseline health estimate or under trolling directly

emitted 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 estimate the proportion of benefits occurring as designated nonattainment areas. In addition, the ton estimates are based on emissions from existing sources. To the extent7 - 31 that the geographic distribution of the emissions reductions for this rule are different than the modeled emissions , the benefits may be underestimated or overestimated. In general, there is inherently more uncertainty for new sources, which may not be included in the emissions inventory , than existing sources. 2. We assume that all fine particles, regardless of their che mical 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 significantl y from direct PM 2.5 released from diesel engines and other in dustrial sources, but no clear scientific grounds exist for supporting differential effects estimates by

particle t ype. 3. We assume that the health impact function for fine particles is linear down to the lowest air quality

levels modeled in this analy sis. 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 mod eled concentrations. 4. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality (which t ypically accounts for 85% to 95% of total monetized benefits), we include a set of twelve estimates based on results of the expert elici tation study in addition to our core estimates. Even these multiple characterizations omit the uncertaint y in air quality estimates, baseline incidence rates, populations exposed and transferability

of the effect estimate to diverse locations. As a resul t, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertaint y in the PM 2.5 estimates. This information should be interpreted within the context of the larger uncertaint y surrounding the entire anal ys is. 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 ty pe of detailed uncertainty assessment found in the PM NAAQS RIA because we lack the necess ar y air quality input and monitoring data to run the benefits model. In addition, we have not conducted any air qualit y modeling for this rule. Moreover, it was not possible to develop benefit - per - ton metrics and associated estimates of uncertaint y 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 anal ys es 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 anal ys is.7 - 32

**7.4 Comparison of Co**  **- Benefits and Costs**  Using a 3% discount rate, we estimate the total combined mo netized co - benefits of the reconsidered C I RI CE NESHAP proposal to be $ 77 0 million to $1. 9 billion in the implementation y ear (2013). Using a 7% discount rate, we estimate the total monetiz ed co benefits of the reconsidered CIRICE NESHAP proposal to be $ 6 9 0 million to $1. 7 billion. The annu ali zed social costs of the proposed NESHAP are $ 37 3 million (2010$) at a 7% interest rate. 62 The annualized social costs of the proposed NESHAP are $372 million in 2008$. As stated in Section 4 of this RIA, the costs in 2008 dollars can be updat ed to 2010 d ollars 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. Thus, the net benefits are $ 40 0 million to $ 1.5 b illion at a 3% discount rate and $ 32 0 million to $ 1.3 b illion at a 7% discount rate. All of these estimates are in 2010 $ for the ye ar 2013. Table 7 - 5 shows a summary of the monetized co - benefits, social costs, and net benefits for the C I RI CE NESHAP, respectivel y. Figures 7 - 8 and 7 - 9 show the full range of net benefits estimates (i.e., annual co - benefits minus annualized costs) utilizing the 14 different PM 2.5 mortality functions at discount rates of 3% and 7%. In addition, the benefits from reducing 1 4 ,000 tons of carbon monoxide and 1 ,0 00 tons of HAP each year from existing SI RI CE have not been included in these estimates. EPA believes that the co - benefits are likely to exceed the costs under this rulemaking even when taking into account uncertainties in the cost and benefit estimat es. **Table 7 -**  **5 .**  **Summary of the Monetized Benefits, Compliance Costs and Net benefits for the 2010 Rule with the Proposed 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

62 For more information on the annualized social costs, please refer to Section 5 of this RIA.7 - 33 Visibility impairment 1 All estimates are for the implementation year ( 2013 ), and are rounded to tw o significant figures. The annual ized compliance costs are $37 3 million in 20 10 $ as noted earlier in this RIA. These costs, presented in 2008 dollars, can be updat ed 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 approxim ation for social costs in this RIA. 2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as directly emitted fine particles . Human health b enefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing prem ature mortality because the scientific evidence is not yet sufficient to allow

differentiation of effects estimates by particle type. Because these estimates were generated using benefit - per - ton estimates, w e do not break down the total monetized benefits into specific components here. See Figure 7 - 1 for an illustration of th e breakdown, or the RIA for the final Cross - States Air Pollution Rule (EPA, 2011) for more information. 3 The engineering compliance costs are annualized using a 7 percent discount rate.**Figure 7 -**  **8. Net Benefits for**  **Proposed CI RICE discount rate**  ***** *Net Benefits are quantified in terms of PM benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent 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.**M i** **l l** **i o** **n s** **( 2** **0 1** **0 $** **)**

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 eta l.**M i** **l l** **i o** **n s** **( 2** **0 1** **0 $** **)**

Cost es ti ma te co mbi ned wi th total mone tize d be nefi ts es ti mate s der iv ed f rom 2 ep id em iology fu nctions and 12 e xpert

7 - 34 **Proposed CI RICE NESHAP**  **Recons ideration at 3%**  *Net Benefits are quantified in terms of PM2.5 at a 3% discount rate for 2013 and are in 2010$ . This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent but the benefit per ton estimates vary because each ton of precursor reduced has a different propensity to become . The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2

epidemiology functions and 12 expert functions La den eta l.

Cost es ti ma te co mbi ned wi th total mone tize d be nefi ts es ti mate s der iv ed f rom 2 ep id em iology fu nctions and 12 e xpert functions **ideration at 3%** . 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 . The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2 La den eta l.

Cost es ti ma te co mbi ned wi th total mone tize d be nefi ts es ti mate s der iv ed f rom 2 ep id em iology fu nctions and 12 e xpert7 - 35

**Figure 7 -**  **9. Net Benefits for**  **Proposed CI RICE NESHAP 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 w ith the cost estimate. All fine particles are assumed to have equivalent health effects. The monetized benefits incorporate the conversion from precursor emissions to am bient fine particles. - $500 $0 $500 $1, 000 $1, 500 $2, 000 $2, 500

Pope eta l. La den eta l.**M i** **l l** **i o** **n s** **( 2** **0 1** **0 $** **)**

Cost es ti ma te co mbi ned wi th total mone tize d be nefi ts es ti mate s der iv ed f rom 2 ep id em iology fu nctions and 12 e xpert functions7 - 36

**7.5 References**  Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “The influence of location, source, and emission ty pe in estimates of the human health benefits 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

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A., Katherine D. Walker, Ty ra L. Walsh, L isa Conner, Harvey M. Richmond, Br yan J. Hubbell, and Patrick L . Kinney . 2008. “Expert Judgment Assessment of the Mortality I mpact of Changes in Ambient Fine Particulate Matter in the U.S.” Environ. Sci. Technol ., 42(7):2268 - 2274.7 - 37

Sisler, J.F. 1996. Spatial and seasonal patterns and long- term variability of the composition of the haze in the United States: an analysis of data from the IMPROVE network . CI RA Report, ISSN 0737 - 5352 - 32, Colorado State Universit y. 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/$File/ sab - 08 - 001.pdf >. U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA - SAB). 2009a. Review of EPA’s Integrated Science Assessment for Particulate Matter (First External Review Draft, December 2008). EPA - COUNCIL - 09 - 008. May . Available on the Internet at < http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/73 ACCA834AB44A10852575BD0064346B/$File/EPA - CASAC - 09 - 008 - unsigned.pdf >. U.S. E nvironmental 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 . A vailable on the Internet at < http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead0 06be86e/72 3FE644C5D758DF852575BD00763A32/$File/EPA - CASAC - 09 - 009 - unsigned.pdf >. U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA - SAB). 2010. Review of EPA’s DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clea n Air Act. EPA - COUNCIL - 10 - 001 . June. Available on the Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/0/72D4EFA39E48CDB28525774500738776/$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 W orkshop 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%5CSABPRODUCT.NSF/34355712EC011A358525719A0 05BF6F6/$File/ecwkshp02001%2Bappa - g.pdf>. U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA - SAB). 2008. Benefits of Reducing Benzene Emissions in Ho uston, 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>.7 - 38

U.S. Environmental Pr otection 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 In novation. Washington, DC. September. Available on the Internet at < http://y osemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/cover.pdf >. U.S. Environmental Protection Agency (U.S. EPA) . 2006. Regulatory Impact Analysis, 2 006 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). 2008a. 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 >. 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, Rese arch Triangle Park, NC. July . Available at at <http://cfpub.epa.gov/ncea/cfm/recordisplay .cfm?deid=194645>. U.S. Environmental Protection Agency (U.S. EPA) . 2008d. Integrated Science Assessment for Oxides of Nitrogen and Sulfur

– Ecological Criteria Nation al (Final Report). National Center for Environmental Assessment, Research Triangle 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 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. Integrated Science Assessment for Particulate Ma tter (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 . Rese arch 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 In novation. 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 >.7 - 39

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 Qualit y Planning and Standards, Research Triangl e Park, NC. June. Available at <http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2011 c . 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). 2012. Technical Support Document: Estimating the Benefit per ton of Reducing PM 2.5 Precursors from Other Point Sources . Off ice of Air Quality

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United States Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impacts

Division Research Triangle Park, NC