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



### Ma **y 201**  **2** 

# Regulatory

**Impact Analysis (RIA) for Proposed**  **Reconsideration Existing**  **Stationary Spark**  **Ignition RICE**  **NESHAP** Final Report Prepared for Larry Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (A E G)

(MD - C439 - 02) Research Triangle Park, NC 2771 1_________________________________ RTI International is a trade name of Research Triangle Institute . 

# Regulatory Impact Analysis (RIA) for Existing Stationary Spark Ignition RICE NESHAP

Final Report

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

Air Benefit and Cost Group (ABCG)

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

of Impacts for SIRICE NESHAP Reconsideration Proposal............1 - 1 ES.2 Comparison with Results from 2010 Final SIRICE NESHAP......................1 - 2 2 Introduction ................................ ................................ ................................ ................. 2 - 11 2.1 Organization of this Report ................................ ................................ ................ 2 - 11 3 Industry

Profile ................................ ................................ ................................ ............. 3 - 1 3.1 Electric Power Generation, Transmission, and Distribution ............................... 3 - 1 3.1.1 Overview ................................ ................................ ................................ .. 3 - 1 3.1.2 Goods and Services Used ................................ ................................ ......... 3 - 3 3.1.3 Business Statis tics ................................ ................................ .................... 3 - 4 3.2 Oil and Gas Extraction ................................ ................................ ....................... 3 - 11 3.2.1 Overview ................................ ................................ ................................ 3 - 11 3.2.2 Goods and Services Used ................................ ................................ ....... 3 - 11 3.2.3 Business Statistics ................................ ................................ .................. 3 - 13 3 .2.4 Case Study : Marginal Wells ................................ ................................ .. 3 - 17 3.3 Pipeline Transportation of Natural Gas ................................ ............................. 3 - 18 3.3.1 Overview ................................ ................................ ................................ 3 - 18 3.3.2 Goods and Services Used ................................ ................................ ....... 3 - 18 3.3.3 Business Statistics ................................ ................................ .................. 3 - 20 4 Regulatory

Alternatives, Costs, and Emission Impacts ................................ ................ 4 - 1 4.1 Background ................................ ................................ ................................ .......... 4 - 1 4.2 Proposed Amendments to SIRICE NESHAP ................................ ..................... 4 - 1 4.2.1 Total Hydrocarbon Compliance (THC) Demonstration Option .............. 4 - 1 4.2.2 Proposed Amendment - Emergency Demand Response/Peak Shaving ................................ ................................ ................................ .... 4 - 5iv 4.2.3 Proposed Amendment - Non - Emergency Stationary

SI RICE Greater than 500 HP Located at Area Sources ...... ................................ 4 - 6 4. 3 What Are the Pollutants Regulated b y the Rule? ................................ ............... 4 - 11 4. 4 Cost Impacts ................................ ................................ ................................ ....... 4 - 14 4. 4 .1 Introduction ................................ ................................ ............................ 4 - 14 4. 4 .2 Control Cost Methodology ................................ ................................ .... 4 - 14 4. 4 .3 Control Cost Equations ................................ ................................ .......... 4 - 1 8 4. 4 .4 Summary ................................ ................................ ................................ 4 - 21 4. 4 .5 Caveats and Limitations for Cost Estimates ................................ .......... 4 - 35 4. 5 Baseline Emissions and Emission Reductions ................................ ................... 4 - 36 5 Economic Impact Anal ys is, Energy Impacts, and Social Costs ................................ ... 5 - 1 5.1 Compliance Costs of the Proposed Reconsidered Rule ................................ ....... 5 - 1 5. 2 Social Cost Estimate ................................ ................................ ............................ 5 - 3 5. 3 How Might People and Firms Respond? A Partial Equilibrium Analy sis ........... 5 - 4 5.2.1 Changes in Market Prices and Quantities ................................ ................ 5 - 4 5.2.2 Regulated Markets: The Electric Power Generation, Transmission, and Distribution Sector ................................ ................................ ............ 5 - 6 5.2.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus ................................ ................................ ............... 5 - 7 5.4 Energy

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

ment Impact Analy sis ................................ ................................ ............ 5 - 11 5.7.1 Employ

ment Impacts from Pollution Control Requirements ................ 5 - 13 5.7.2 Employ

ment Impacts within the Regulated Industry ............................. 5 - 17v

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 - 2 6.3 Small Government Entities ................................ ................................ ................ 6 - 11 7 Benefits of Emissions Reductions ................................ ................................ ................ 7 - 1 7 . 1 Calculation of PM 2.5 Human Health Co - Benefits ................................ ................ 7 - 1 7 . 2 Unquantified Benefits ................................ ................................ ........................ 7 - 1 3 7 . 2 . 1 HAP Benefits ................................ ................................ ......................... 7 - 13 7 . 2 . 2 Additional NO 2 Co - Benefits ................................ ................................ .. 7 - 1 4 7 . 2 . 3 Ozone Co - Benefits ................................ ................................ ................ 7 - 1 6 7. 2 . 4 Carbon Monoxide Co - Benefits ................................ .............................. 7 - 1 6 7.2.5 Visibility

Impairment Co - Benefits..................................7 - 23 7 . 3 Characterization of Uncertainty in the Monetized PM 2.5 Co - Benefits ............... 7 - 2 5 7 . 4 Comparison of Co - Benefits and Costs ................................ ............................... 7 - 30 8 References for RIA ................................ ................................ ................................ ....... 8 - 1vi **LIST OF FIGURES Number**  **Page** 1 - 1. Breakdown of Total Monetized PM 2.5 Co - Benefits of Proposed S I RI CE Reconsideration b y Engine Size ............................................................1 **-** 8 1 - 2. Total Monetized PM 2.5 Co - Benefits Estimates for the S I RI CE Reconsideration Proposal in 2013 ...............................................................................1 - 9 3 - 1 Industrial Production Index (NAI CS 2211) ................................ ................................ 3 - 3 3 - 2 Internal Combustion Generators b y State: 2006 ................................ ......................... 3 - 4 3 - 3 2002 Regional Distribution of Establishments: Electric Power Generation, Transmission, and Distribution In dustry (NAICS 2211) ................................ ............ 3 - 6 3 - 4 Industrial Production Index (NAI CS 211) ................................ ................................ 3 - 12 3 - 5 2002 Regional Distribution of Establishments: Crude Petroleum and Natural Gas Extraction Industry

(NAI CS 211111) ................................ ................................ 3 - 15 3 - 6 2002 Regional Distribution of Establishments: Natural Gas Liquid Extraction Industry (NAICS 211112) ................................ ................................ ......................... 3 - 16 3 - 7 Distribution of Establishments within Pipeline Transportation (NAICS 486) .......... 3 - 19 3 - 8 Distribution of Revenue within Pipeline Transportation (NAICS 486) .................... 3 - 20 3 - 9 2002 Regional Distribution of Establishments: Pip eline Transportation (NAI CS 486) ................................ ................................ ................................ ............................ 3 - 22 3 - 10 Share of Establishments by L egal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002 ................................ 3 - 22 5 - 1 Distribution of Engine Population by Horsepower Group ................................ .......... 5 - 4 5 - 2 Market Demand and Supply Model: With and Without Regulation ........................... 5 - 6 5 - 3 Electricity R estructuring by State ................................ ................................ ................ 5 - 9 6 - 1 Distribution of Engine Population by Size for All Industries ................................ ..... 6 - 8 6 - 2 Distribution of Compliance Costs by Engine Size for All Industries ......................... 6 - 9 7 - 1 . Breakdown of Monetized PM 2.5 Health Co - Benefits using Mortality Function from Pope et al. (2002) ................................ ................................ ................................ 7 - 7 7 - 2 . Total Monetized PM 2.5 Co - Benefits for the Proposed SIRICE Reconsidered NESHAP in 2013 ................................ ................................ ................................ ...... 7 - 1 2 7 - 3 . Breakdown of Monetized Co - Benefits for the Proposed SIRICE Reco nsidered NESHAP by Engine Size e ................................ ................................ ........................ 7 - 1 3 7 - 4 . Estimated Chronic C ensus Tract l Carcinogenic Risk from HAP exposure from outdoor sources ( 2005 NATA) ................................ ................................ .................. 7 - 1 8vii

7 - 5 . Estimated C hronic Census Tract Noncancer (Respiratory) Risk from HAP exposure from outdoor sources ( 20 05 NATA) ................................ .......................... 7 - 1 8 7 - 6 . Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline ................................ ................................ ................................ .................... 7 - 2 8 7 - 7. Cumulative Distribution of Adult Population at Annual Mean PM 2.5 Exposure in the Baseline ................................ ................................ ................................ .......... 7 - 2 8 7 - 8 . Net Benefits for the Proposed SIRICE Reconsidered NESHAP at 3% Discount Rate ................................ ................................ ................................ ............ 7 - 3 3 7 - 9 . Net Benefits for the Proposed SIRICE Reconsidered NESHAP at 7% Discount Rate ................................ ................................ ................................ ............................ 7 - 3 4viii **LIST OF TABLES Number**  **Page** 1 - 1 Summary

of the Monetized Co - Benefits, Social Costs, and Net benefits for the Proposed SIRI CE Reconsidered NESHAP in 2013 (millions of 20 10 $) ................... 1 - 3 1 - 2. Summary

of th e Monetized Co - Benefits, Compliance Costs, and Net benefits for the 2010 Rule with the Proposed Amendments to the Stationary SI RICE Engine NESHAP in 2013 (millions of 20 10 $) ............................................................... ...................................... 1 - 4 1 - 3. Summary

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

of Estimated Reductions in Health Incidences from PM 2.5 for th e SIRICE Reconsideration Proposal in 2013...........................................................1 - 7 1 - 5. Summary

of Estimated Social Costs and Benefits for the 2010 Final SIRICE Rule and the Proposed Reconsideration (millions of 2010 dollars)........................1 - 10 3 - 1 Key

Stati stics: 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): 2002 ................................ ................................ ............... 3 - 5 3 - 3 Firm Concentration for Electric Power Generation, Transmission, and Distribution (NAI CS 2211): 2002 ................................ ................................ ............... 3 - 7 3 - 4 United States Retail Electricity Sales Statistics: 2008 ................................ ................ 3 - 8 3 - 5 FY 20 10 Financial Data for 70 U.S. Shareholder - Owned Electric Utilities ............... 3 - 9 3 - 6 Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAI CS 2211 ....................... 3 - 9 3 - 7 Key

Enterprise Statistics by

Receipt Size for Electric Power Generation, Transmission, and Distribution (NAI CS 2211): 200 7 ................................ ............... 3 - 10 3 - 8 Key

Statistics: Crude Petroleum and Natural Gas Extraction (NAI CS 211111): (2007) ................................ ................................ ................................ ........................ 3 - 12 3 - 9 Key

Statistics: Natural Gas Li quid Extraction (NAICS 211112) (2007) .................. 3 - 13 3 - 10 Direct Requirements for Oil and Gas Extraction (NAI CS 211): 2002 ...................... 3 - 13 3 - 11 Key

Enterprise Statistics by

Employ ment Size for Crude Petroleum and Natural Gas Extraction (NAI CS 211111): 200 7 ................................ ....................... 3 - 17 3 - 12 Key

Enterprise Statistics by

Employ ment Size for Crude Natural Gas Liquid Extraction (NAI CS 211112): 200 7 ................................ ................................ ............ 3 - 1 7 3 - 13 Aggregate Tax Data for Accounting Period 7/07 – 6/08: NAI CS 211 ....................... 3 - 18 3 - 1 4 Key

Statistics: Pipeline Transportation of Natural Gas (NAI CS 48621) (2007) ...... 3 - 19 3 - 1 5 Direct Requirements for Pipeline Transportation (NAI CS 486): 2002 ..................... 3 - 21 3 - 1 6 Firm Concentration for Pipeline Transportation of Natural Gas (NAI CS 48621): 2002 ................................ ................................ ................................ .............. 3 - 23ix

3 - 1 7 Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAI CS 486 ....................... 3 - 23 3 - 1 8 Key

Enterprise Statistics by

Receipt Size for Pipeline Transportation of Natural Gas (NAI CS 48621): 200 7 ................................ ................................ ........................ 3 - 24 4 - 1 Summary

of Annual and Capital Costs Equations for Existing Stationary SI Engines ................................ ................................ ................................ ...................... 4 - 21 4 - 2 Summary

of Major Source and Area Source Costs for the SI RI CE NESHAP ........ 4 - 22 4 - 3 Summary

of Major Source and Area Source NAICS Costs for the SIRICE NESHAP ................................ ................................ ................................ ................... 4 - 23 4 - 4 Summary

of Major Source and Area Source NAICS Costs for the SIRICE NESHAP, by

Size ................................ ................................ ................................ ...... 4 - 24 4 - 5 Summary

of Major Source and Area Source NAICS Costs for the SIRICE NESHAP, by

Number of Engines ................................ ................................ ............. 4 - 28 4 - 6 Summary

of Major Source and Area Source Baseline for the SI RI CE NESHAP ................................ ................................ ................................ ................... 4 - 33 4 - 7 Emissions Factors ................................ ................................ ................................ ...... 4 - 34 4 - 8 Summary

of Major Source and Area Source Basel ine Emissions for the SI RI CE NESHAP by

2013 ................................ ................................ ........................... 4 - 34 4 - 9 Summary

of Major Source and Area Source Emissions Reductions for the SI RI CE NESHAP by

2013 ................................ ................................ ........................... 4 - 34 5 - 1 Selected Industry - Level Annualized Compliance Costs as a Fraction of Total Industry Revenue: 2009 ................................ ................................ ............................... 5 - 3 5 - 2 Hy pothetical Price Increases for a 1% Increase in Unit Costs ................................ .... 5 - 5 5 - 3 Hy pothetical Consumption Decreases for a 1% Increase in Unit Costs ..................... 5 - 7 5 - 4 U.S. Electric Powera Sector Energy Consumption (Quadrillion BTUs): 2013 ........... 5 - 9 5 - 5 Labor - based Employ ment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Control Equipment Requirements for Proposed Reconsideration SI RI CE NESHAP...................................................... .. 5 - 1 6

6 - 1 Proposed 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 ($2009 Million/Establishment) ................................ ................................ ................................ 6 - 4 6 - 3 Average Receipts for Affected Industry by Enterprise Receipt Range: 200 7 ($2009/Establishment) ................................ ................................ ................................ . 6 - 5 6 - 4 Representative Establishment Costs Used for Small Entity Analy sis ($2009) ........... 6 - 7 7 - 1 Human Health Effects of PM 2.5 ................................ ................................ ................... 7 - 2 7 - 2. General Summary

of Monetized PM 2. 5 –Related Health Co - Benefits Estimates for the Proposed SIRICE Reconsidered NESHAP in 2013 (millions of 20 1 0 $) ...... 7 - 9x

7 - 3. Summary

of Reductions in Health Incidences from PM 2.5 Co - Benefits for the Proposed SIRICE Reconsidered NESHAP in 2013 ................................ ................ 7 - 10 7 - 4 . All Monetized PM 2.5 Co - Benefits from PM 2.5 Benefits for the Proposed SI RI CE Reconsidered NESHAP in 2013 ................................ ................................ ..... 7 - 1 1 7 - 5 . Summary

of the Annualized Monetized Benefits, Social Costs, and Net Benefits for the Proposed SIRICE Reconsidered NESHAP in 2013 (millions of 20 10 $) ................................ ................................ ................................ ................... 7 - 311 - 1 **Section 1 EXECUTIVE SUMMARY**  ES.1 Summary

of Impacts for the Proposed Reconsideration This proposed action is a reconsideration of the promulgate d NESHAP for existing stationary SI RICE with a site rating of less than or equal to 500 HP located at major sources, and existing stationary

SI RI CE of any

site rating located at area sources. EPA estimates that complying with the proposed reconsidered n ational emission standards for hazardous air pollutants (NESHA P ) for stationary spark - ignition (SI) reciprocating internal combustion engines ( RI CE ) will have an annualized cost of approximately $ 115 million per year ( 200 9 or 2010 dollars) in the y ear of f ull implementation of the rule (2013). The total annualized costs of the proposed reconsidered rule are 55% less than those for the final SI RI CE NESHAP promulgated in 2010. 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 analysi s of the impacts of this rule on small entities , EPA e xpects that the NESHAP will not result in a SI SNOSE ( signifi cant economic impacts for a subs tantial number of small entities ) , a result consistent with the conclusion for the final SIRICE NESHAP issued in 2010 . EPA also does not expect significant adverse energy impacts based on Executive Order 13211, an Executive Order that requires anal ys is of energy impacts for rules such as this one that are economically significant under Executive Order 12866. In the ye ar of full implementation (2013), EPA estimates that the total monetized benefits of the proposed reconsider ed NESHAP are $ 62 million to $ 150 m illion and $ 55 million to $ 140 m illion, at 3% and 7% discount rates, respectivel y (Table 1 - 1). All estimates are in 20 10 dollars for the ye ar 2013. These estimates reflect the co - benefits from 9,600 tons of NOx emission reductions associated with implementing the controls to reduce hazardous air pollutants (HAPs) required under this proposed reconsideration. Using alternate relationships between PM 2.5 and premature mortality

supplied by

experts, higher and lower benefits estimates are plausible, but most of the expert - based estimates fall between these estimates. The benefits from reducing other air pollutants have not been monetized in this analy sis, including reducing 22 , 2 00 tons of carbon monoxide (CO) and 1 , 8 00 tons of hazardous air pollutants ( HAPs ) each ye ar. In addition, ecos ys tem benefits and visibility benefits have not been monetized in this analy sis.1 - 2

In the ye ar of full implementation (2013), EPA estimates the net benefits of the proposed NESHAP are $ - 53 m illion to $ 35 m illion and $ - 60 m illion to $ 25 m illion at 3% and 7% discount rates, respectivel y (Table 1 - 1) . These estimates are “snapshots” of benefits and costs at y ear 2013 and are in 2010 dollars .1 - 3

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

**benefits for the Proposed Reconsideration**  **SI RICE NESHAP in 2013 (millions**  **of 20 10**  **$) 1**  **3% Discount Rate 7% Discount Rate**  Total Monetized Benefits 2 $62 to $150 $55 to $140 Total Compliance Costs 3 $115 $115 Net Benefits $ - 53 to $35 $ - 60 to $25 Non - monetized Benefits Health effects from HAP exposure Health effects from CO , NO 2 , and ozone exposure Ecosystem effects Visibility impairment

1 All estimates are for the implementation year (2013), and are rounded to two significant figures. 2 The total monetized co - benefits reflect the human health co - benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as NOx and VOC. It is important to note that the monetized co benefits include many but not all health effects associated with PM 2.5 exposure. It is important to note that the monetized benefits include many but not all health effects associated with PM 2. 5 exposure. Benefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of their chemical composition, are equally

potent in causing premature mortality because there is no clear scientific evidence that would support the development of differential effects estimates by particle ty

pe. Because these estimates were generated using benefit - per - ton estimates, we do not break down the total monetized benefits into specific components h ere. See Figure 7 - 1 for an illustration of the breakdown, or the RIA for the final Cross - States Air Pollution Rule (EPA, 2011) for more information. 3 The annual compliance costs serve as a proxy for the annual social costs of this rule given the lack of difference between the two. The annual compliance costs are calculated using a 7 percent discount rate. ES.2 Comparison of Impacts for Final 2010 SI RICE Final Rule and SIRICE NESHAP Proposed Reconsideration The EPA anal yz ed the costs, economic impacts and benefits of this proposed rule using the identical methodology as the RIA for the SIRICE final rule promulgated in October, 2010 . Therefore, all changes to the costs, benefits, and economic impacts for this proposed rule are due to changes (or proposed amendments) to this proposed rule for SI RICE, which are fully described later in this RIA and the preamble for the proposed rule . Our baseline does not assume compliance with the 2010 SI RICE final rule. This assumption is based on the fact that full implementation of the final rule has not taken place as of yet (it will take p lace by October , 2013). In addition, this assumption is consistent with the baseline definition applied in the recentl y 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.1 - 4

The following table shows an approximation of the changes in monetized benefits and engineering costs due to changes to the SI RICE rule included in the SIRICE reconsideration proposal, and includes values that show a comparison based on the final rule emissions inventory . All values in this table are in 2010 dollars. **Table 1 -**  **2. Summary of the Monetized Benefits**  **and Compliance Costs for the 2010 Rule**  **with the Proposed Amendments to the Stationary S**  **I Engine NESHAP in 2013 (millions of 2010 dollars)**  **a Monetized Benefits**  **in 2013 Annual Engineering Costs**  **in 2013**  SIRICE Final Rule (May 2010) $ 510 to $ 1,200 million $253 million Changes due to the proposed amendments to the final SI RICE rule - $ 448 to $ 1,050 million - $138 million Proposed SI RICE rule (2012) +$ 62 to $ 150 million $115 million * Monetized benefits are shown at a 3% discount rate and are from reductions in PM 2.5 emissions. These benefits do not include benefits associated with reduced exposure to HAP, visibility impairment, or ecosystem effects. Monetary estimates are in 2010 dollars. The results for the economic impacts fall by more than half from those for the SIfinal rule. This outcome is due to the significant reduction in compliance costs associated with the proposed amendments in this proposal. All of the results for this proposed rule are found in Section 5 in this RIA. The results for sales tests (i.e. annual cost/sales analy sis) for small businesses also fall from those calculated for the final SIRICE rule . This outcome is also due to the overall large reductions in compliance costs. All of the results for this proposed rule are found in Section 6 in this RIA. We estimate change s in employ ment for this SI 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 200 full - time equivalents (FTEs) will be required as one - time labor for installation of e quipment, and 400 FTEs will be required as ongoing labor for compliance with the proposed rule. The results are presented and explained in detail in Section 5 of this RIA. We did not estimate changes in employ ment for the 2010 final SIRICE rule.1 - 5

The b enefits estimates decreas ed significantl y for the proposal. The range for the 2010 final SIRICE R IA was $510 m illion (200 9 $) to $1,200 m illion (200 9 $) at 3 percent discount rate. The range for this proposal is $62 million (2010$) to $150 million (2010 $) at 3 percent discount rat e. The range for the 2010 final SI RICE RIA was $460 million (2009$) to $1,100 million (2009 $) at 7 percent discount rate. Th e range for the proposal was $55 million (2010$) to $ 1 40 million (2010 $) at 7 percent discount rate. The health ben efits were calculated using a methodolo gy described in the 2010 final SI 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 estimate the benefits from reducing exposure to HAPs, ecos ys tem impairment, and visibility impairment , including reducing 22 ,000 tons of carbon monoxide, 9,000 tons of VOC and 1,800 tons of HAPs. Please refer to the full description lat er in this RIA of the unquantified benefits as well as technical details of the anal ys is and its limitations and uncertainties. These monetized ben efits are approximately 90% lower than the 2010 final SIRICE rule due to the estimated de crease in NOx emiss ion reductions. These benefit - per - ton esti mates were calculated for a 2013 anal ys is y ear (i.e., using popul ation and income growth for 2013 ) . See Tables 1 - 2 and 1 - 3 for the updated benefits results.

**Table 1**  **- 3**  **: Summary of Monetized**  **PM 2.5**  **- Related Co**  **- Be**  **nefits Estimates for SI RICE Reconsideration Proposal in**  **2013 Pollutant**  **Emissions**

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

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

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

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

**per ton (Laden,**  **7%) Total** 

**M onetized**  **Benefits (m** **illions 2010 $**  **at 3%)**  **Total M onetized** 

**Benefits (m** **illions 2010 $**  **at 7%)** NO x 9,648 $6 , 4 00 $16 ,000 $5 , 7 00 $14 ,000 $ 62 to $150 $55 to $140 **Total $62**  **to $**  **150 $**  **55 to**  **$ 1**  **40** * All estimates are f

or the implementation year (2013 ), and are rounded to two significant figures so numbers may not sum across columns. It is important to note that the monetized benefits do not include reduced health effects from direct exposure to 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 - 61 - 7

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

**SI RICE Reconsideration Proposal in 2013 Proposed Option**  **Avoided Prem ature Mortality**  Pope et al. 7

Laden et al. 18 **Avoided Morbidity** Chronic Bronchitis 5 Emergency Room Visits, Respiratory 5 Hospital Admissions, Respiratory 1 Hospital Admissions, Cardiovascular 3 Ac ute Bronchitis 11 Lo wer Respiratory 14 0 Upper Respiratory 11 0 Minor Restricted Activity Days 5 , 6 00 Work Loss Days 95 0 Asthma Exacerbation 23 0 Ac ute Myocardial Infarction 8 * All estimates are for the analysis year ( 2013 ) and are rounded to whole numbers with two significant figures. All fine particles are assumed to have equivalent health effects because the scientific evidence is not yet sufficient to1 - 8

allow differentiation of effects estimates by particle type . Co nfidence 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 : Breakdown of**  **Total Monetized**  **PM 2.5**  **Co -**  **Benefits of Proposed SI RICE**  **Reconsideration by**  **Engine Size**

**Area 500 -**  **600 HP**  **21% Area 600**  **- 750**  **HP**

**5% Area >750 HP**  **74%**1 - 9

**Figure 1**  **- 2: Total Monetized PM**  **2.5 Co**  **- Benefits Estimates for the**  **SI 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 $50 $100 $150 $200 $250

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 - 10

Table 1 - 5 shows the estimated costs and benefits for the 2010 final S I RICE Rule and the reconsideration proposal. T he estimated net benefits for the reconsideration proposal are considerabl y smaller than the range for the 2010 final SIRICE rule RIA, which was $ 210 million to $ 860 million at a 7 percent discount rate and w as $ 250 million to $ 980 billion at 3 percent. **Table 1**  **- 5**  . **Summary of Estimated Social Costs and Benefits for the 2010 final SI RICE rule** 

**and the Reconsideration Proposal (millions of 2010 dollars) 1**  **3% Discount Rate 7% Discount Rate**  **2010 Final SI RICE NESHAP**  Total Monetized Benefits $510 to $1,200 $460 to $1,100 Total Social Costs $253 $253 Net Benefits $250 to $980 $210 to $860 **Proposed Reconsideration SI RICE NESHAP**  Total Monetized Benefits $62 to $150 $55 to $140 Total Social Costs $115 $115 Net Benefits $ - 53 to $35 $ - 60 to $25 1 All estimates are for the implementation year ( 2013 ), and are rounded to two significant figures. All monetized benefits are from reductions of PM 2.5 emissions, a co - benefit of this proposal. The annual ized compliance costs are $115 million in 2010$ as noted earlier in this RIA, and are annualized using a 7% interest rate. Compliance costs are used as an approximation for social costs in this RIA.2 - 11 **Section 2 INTRODUCTION**  EPA is pro posing NESHAP for existing stationary SIRICE that either are located at area sources of hazardous air pollutant emissions or that have a site rating of less than or equal to 500 horsepower and are located at major sources of hazardous air pollutant emissions. The prop osed amendments to the SIRICE 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 benefits of the rule is included in this RIA. It should be no ted 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 SI RI CE NESHAP promulgated in 2010. **2.1 Organization of this Report**  The remainder of this report supports and det ails the meth odology and the results of the R IA :

 Section 3 presents a profile of the affected industries.

 Section 4 presents a summary of regulatory

alternatives considered in the final rule, and provides the compliance costs of the rule.

 Section 5 describes the estimated costs of the regulation and describes the economic impact anal ys is ( EIA ) methodology and reports market , welfare , energy , and employ ment impacts.

 Section 6 presents estimated impacts on small entities.

 Section 7 presents the benef its and net benefits (benefits - costs) estimates.3 - 1 **Section 3 INDUSTRY PROFILE**  This section provides an introduction to the industries affected b y the rule , i.e., industries in which the spark - ignition ( SI ) RI CE being regulated are found . SIRICE generate electric power, pump gas or other fluids, or compress air for machinery . The primary non - utility application of internal combustion (I C) engines is in the natural gas industry to power compressors used for pipel ine transportation, field gathering (collecting gas from wells), underground storage tanks, and in - gas processing plants. RI CEs are separated into three design classes: 2 cycle (stroke) lean burn, 4 - stroke lean burn, and 4 - stroke rich burn. Each of these have design differences that affect both baseline emissions as well as the potential for emissions control.The se industries include the following:

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

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

 pipeline transportation of natural gas (NAICS 48621) . While this is not an exhaustive list of the industries affected by this proposed reconsideration rule, these three industries incur about 8 3 percent of the annualized cost s of the rule. A full listing of all industries affected in this rulemaking can be found in Chapter 4. The purpose of this profile chapter is to give the reader a general understanding of the economic aspects of the industry ; their relative size, relations hips 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 t o 2007 , revenues from electric power generation grew about 18 % to over $ 440 billion ($2007) ( Table 3 - 1). 1 At the same time, pay roll rose about 7 % and the number of 1 We provide revenues from electric power generation for the years 2002 and 2007 for these are years of the Economic Census. We reference data from these Economic Censuses frequently in this industry profile and show revenues from this industry over this t ime frame due to availability of such data.3 - 2

employees decreased by around 4 %. The number of establishments rose by about 3 % . Industrial production within NAI CS 2211 has increased 2 6 % 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 m arket. 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 effort s. The majority (58%) of power generators controlled b y combined heat and power (CHP) or independent power producers are located in states undergoing active restructuring ( Figure 3 - 2). **Table 3 -**  **1. Key Statistics: Electric Power Generation, Transmission, and**  **Distribution**

**(NAICS 2211) ($2007) 2002**  **2007** Revenue ($10 6 ) 373,309 440,355 Payroll ($10 6 ) 40,842 43,792 Em ploy ees 535,675 515,335 Establishments 9,394 9,642 Source: U.S. Census Bureau; American FactFinder; “ Sector 22: EC0722I2: Utilities: Industry Series: Preliminary Com parative Statistics for the United States (2002 NAICS Basis): 2007 and 2002. ” http://factfinder.census.gov3 - 3

**Figure 3 -**  **1. Industrial**  **Production Index (NAICS 2211)** Source: The Federal Reserve Board. “ Industrial Production and Capacity Utilization: Industrial Production ” Series ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G2211.S <http://www.federalreserve.gov/datadownload/>. ( January 27, 2010 ). **3 .1.2**  **Goods and Ser vices Used**  In Table 3 - 2, we use the latest detailed benchmark input - output data report by the Bureau of Economic Anal ys is (BEA) (2002) to identify the goods and services used in electric power generation. As shown, labor and tax requirements represent a significant share of the value of power generation. Extraction, transportation, refining, and equipment requirements potentially

80 85 90 95 100 105 110 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** **)**3 - 4

**Figure 3 -**  **2. Internal Combustion Generators by State: 2006**  Source: U.S. Departm ent of Energy, Energy Information Administration. 2007. “ 2006 EIA - 906/920 Monthly Time Series. ” 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 13 - 5

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

**Distribution (NAICS 2211): 2002 Comm**  **odity Comm**  **odity Description Direct Requirements**  **Coefficients 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 Requirement s 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 busine ss organization consisting of one or more domestic establishments in the same state and industry that were specified under common ownership or control. The firm and the establishment are the same for single 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 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 s ummed from the associated establishments. Enterprise size designations are determined by the summed employ

ment of all associated establishments.3 - 6

In 2002, Texas had almost 1,000 power establishments, while California, Georgia, and Ohio all had between 400 and 500 ( Figure 3 - 3). Hawaii, Nebraska, and Rhode Island all had fewer than 20 establishments in their states.

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

**Transmission, and Distribution Industry (NAICS 2211)**  Source : U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 22: Utilities: Geographic Area Series: Summary Statistics: 2002. ” <http://factfinder.census.gov>; (November 10, 2008) . . As shown in Table 3 - 3, the fo ur largest firms owned over 1,200 establishments and accounted for about 16% of total industry receipts/revenue. The 50 largest firms accounted for almost 6,000 establishments and about 78% of total receipts/revenue. Investor - owned energy

providers accounted for only 2 % of retail electricity

sold in the United States in 200 8 ( Table 3 - 4). In 200 8 , investor - owned energy provider companies with less than 50% of their assets regulated were unprofitable overall , while other companies in this category were profi table . ( Table 3 - 5). In 200 8 , enterprises within NAICS 2211 had a pre - tax profit margin of 8.1 % ( Table 3 - 6 ). In 2002, about 82% of firms generating, transmitting, or distributing electric power had receipts of under $50 million ( Table 3 - 7). However, these firms accounted for only 11% of employ ment, with 89% of employ ees working for firms with revenues in excess of $100 million. **Establishments by State**

Less than 100 100 - 199 200 - 349 350 - 500 More than 5003 - 7

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

**Distribution (NAICS 2211): 2002**

**Comm odity**  **Establishm ents**  **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).3-8 **Table 3 -**  **4. United States Retail 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 Numbe r of retail customers 46,985 2,160,220 36 940,697 1 NA NA 3,147,939 Retail s ales (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 from retail sales ($10 6 ) 113 5,934 473 1,994 6 NA NA 8,520 Percentage of revenue 1.33 69.65 5.55 23.41 0.07

— — 100 Average retail price (cents/kWh) 5.01 8.44 4.91 9.12 5.25 NA NA 8.18 Sourc e: U.S. Department of Energy, Energy Information Administration. 2009. “State Electricity Profiles 2008.” DOE/EIA - 0348(01)/2. p. 260. < http://www.eia.doe.gov/cneaf/electricity/st_profiles/sep2008.pdf>.3 - 9

**Table 3 -**  **5. FY 20**  **10 Financial Data for 70 U.S. Sha**  **reholder -**  **Owned Electric Utilities Profit Margin**  **Net Income Operating Revenues**  Investor - Owned Utilities 4.81% $27,728 $371,545 Regulated a 7.25% $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. “ Income Statement: Q4 20 10 Financial Update. Quarterly Report of the U.S. Shareholder - Owned Electr ic Utility Industry. ” <http://www.eei.org>. **Table 3 -**  **6. Aggregate Tax Data**  **for Accounting Period 2009**  **: NAICS 2211** Number of enterprises a 1,187 Total receipts (10 3 ) $3 23,522,443 Net sales(10 3 ) $328,017,143 Profit margin before tax 3.1% Profit margin after tax 2.0%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “ Corporation Source Book: Data Files 200 0

– 200 9 . ” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2 , 2010).3-10 **Table 3 -**  **7. Key Enterprise Statistics by**  **Employee Size for Electric Power Generation, Transmission, and Distribution**  **(NAICS 2211): 200 7** 

**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 - 11

**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 develo p oil and gas field properties 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 property. Oil and gas extraction consists of two industries: crude petroleum and natural gas extraction (NAICS 211111) and natural gas liquid extraction (NAICS 211112). Crude petroleum and natural gas extraction is the larger industry ; in 2002, it accounted for 93% of establishments and 75% of oil and gas extraction revenues. Industrial production in this industry is particularly

sensitive to hurricanes in the Gulf Coast. In September of both 2005 and 2008, production dropped 14% from the previous month. ( Figure 3 - 4). From 2002 to 200 7 , revenues fr om crude petroleum and natural gas extraction (NAICS 211111) grew over 117 % to almost $ 215 billion ($2007) ( Table 3 - 8). At the same time, pay roll grew 55 % and the number of employ ees grew by 48 %. The number of establishments dropped by over 17 %; as a result, the average establishment revenue increased by 162 %. Materials costs were approximately 18 % of revenue over the period. From 2002 to 200 7 , revenue from natural gas liquid extraction (NAI CS 211112) grew over 26 % to about $ 42 billion ( Table 3 - 9). At the same time, pay roll dropped 1 8 % and the number of emplo ye es dropped by 24 %. The number of establishments dropped by 43 %, resulting in an increase of revenue per establishment of about 122 %. **3 .2.2**  **Goods and Services Used** The oil and gas extractio n industry has similar labor and tax requirements as the electric power generation sector. Extraction, support, power, and equipment requirements potentially associated with RI CE (oil and gas extraction, support activities, electric power generation, machi nery

and equipment rental and leasing, and pipeline transportation) represent around 8% of the value of services ( Table 3 - 10).3 - 12

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

**($2007) 2002**  **2007** Revenue ($10 6 ) $98,667 $214,198 Payroll ($10 6 ) $5,785 $8,980 Em ploy ees 94,886 140,160 Establishments 7,178 5,956 Source s : U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: Mining: Industry Series: Historical Statistics for the Industry: 2002 and 1997. ” <http://factfinder.census.gov>; (November 26, 2008) . U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: EC0721I1: Mining: Industry Series: Detailed Statistics by Industry for the United States: 2007 ” <http://factfinder.census.gov>; (April 27, 2010). 75 80 85 90 95 100 105 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 - 13

**Table 3**  **- 9.**  **Key Statistics: Natural Gas Liquid Extraction (NAICS 211112) ($2007) 2002**  **2007** Revenue ($10 6 ) $33,579 $42,363 Payroll ($10 6 ) $607 $501 Em ploy ees 9,693 7,343 Establishments 511 291 Source s : U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: Mining: Industry Series: Historical Statistics for the Industry: 2002 and 1997. ” <http://factfinder.census.gov>; (November 26, 2008) . U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: EC0721I1: Mining: Industry Series: Detailed Statistics by Industry for the United States: 2007 ” <http://factfinder.census.gov>; (April 27, 2010). **Table 3**  **- 10.**  **Dire ct 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 power generation, transmission, and distribution 1.47% 541300 Architectural, engineering, and related services 1.24% 532400 Commercial and industrial machinery and equipment rental and leasing 1.20% 33291A Valve and fittings other than plumbing 1.10% 541511 Custom computer programming services 0.99%

a These values show

the amount of the commodity required to produce $1.00 of the industry ’ s output. The values are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input - Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. **3 .2.**  **3 Business Statistics**  The U.S. Economic Census and SUSB programs provide national information on the distribution of economic variables 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 - 14  Receipts : Receipts (net of taxes) are defined a s the revenue for goods produced, distributed, or services provided, including revenue earned from premiums, commissions and fees, rents, interest, dividends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

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

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

roll are summed from the associated establishments. Enterprise size designations are determined by the summ ed 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 211 112, there are 139 firms, of which 95 (71 percent) were considered small businesses (Table 3 - 12). As shown in this table, large firms compose 29 percent of the firms, but account for 78 percent of employ ment and generate about 95 percent of estimated rece ipts. Enterprises within this industry generated $1 93 billion in total receipts in 200 8 . Including those enterprises without net income, the industry averaged an after - tax profit margin of 8.5 % ( Table 3 - 13).3 - 15

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

**Gas Extraction Industry (NAICS 211111)**  Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: Mining: Geographic Area Series: Industry Statistics for the State or Offsh ore Areas: 200 7 . ” <http://factfinder.census.gov>; ( January 27, 2010). **Establishments by State**

Less than 100 100 - 249 250 - 499 500 - 1,000 More than 1,0003 - 16

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

**Extraction Industry (NAICS 211112)**  Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 21: Mining: Geographic Area Series: Industry Statistics for the State or Offshore Areas: 200 7 . ” <http://factfinder.census.gov>; ( January 27, 2010). **Establishments by State**

Less than 5 5 - 9 10 - 19 20 - 40 More than 403 - 17

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

**211111): 200 7**  NAICS NAICS Description SBA Size Standard Small

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

Crude Petroleum and Natural Gas Extraction 500 6,329 95 6,424 **Total Employment by Firm Size** 55,622 77,664 133,286 **Estimated Receipts by Firm Size ($1000)** 44,965,936 149,141,316 194,107,252 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census reports firm counts for firms with receipts less than $7.5 million. **Employment and receipts could not be split between small and large businesses because of non - disclosure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the United States, All Industries: 2007.” <http://www.census.gov/econ/susb/>

**Table 3 -**  **12. Key Statistics for Crude Natural Gas Liquid Extraction (NAICS 211112): 200**  **7**

NAICS Description SBA Size Standard Small

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

Natural Gas Liquid Extraction 500 98 41 139 **Total Employment by Firm Size** 1,875 6,648 8,523 **Estimated Receipts by Firm Size ($1000)** 2,164,328 37,813,413 39,977,741 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million required by the SBA Size Standard. We used this value because U.S. Census reports firm counts for firms with receipts less than $7.5 millio n. **Employment and receipts could not be split between small and large businesses because of non - disclosure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Pay roll, and Estimated Receipts by Enterprise Receipt Size for the United States, All Industries: 2007.” <http://www.census.gov/econ/susb/>3 - 18

**Table 3**  **- 13.**  **Aggregate Tax Data for Accounting Period 7/0 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 without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “ Corporation Source Book: Data Files 2004 - 2007. ” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2 , 2010). **3.3 Pipeline Transportation of Natural Gas**  **3 .3.1**  **Overview** Pipeline transportation of natural gas (NAICS 48621) is an industry group within the transportation and warehousing sector (NAI CS 48 - 49), but more sp ecifically in the pipeline transportation subsector (486). It includes the transmission of natural gas as well as the distribution of the gas through a local network to participating businesses. From 2002 to 200 7 , natural gas transportation revenues fell by 29 % to just over $ 16 billion ($2007) ( Table 3 - 1 4 ). At the same time, payroll decreased b y 14 %, while the number of paid employees decreased by nearl y 25 %. T he number of establishments also fell by 8 % from 1,701 establishments in 2002 to 1, 560 in 200 7 . **3 .3.2**  **Goods and Services Used** The BEA 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 transportati on of crude oil (NAICS 4861) and other 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 60 % of NAICS 486 establishments and 66 % of revenue s (Figures 3 - 8 and 3 - 9).3 - 19

**Table 3**  **- 1**  **4 .**  **Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) ($2007) Year**  **2002 200**  **7** Revenue ($10 6 ) 16,368 20,797 Payroll ($10 6 ) 2,086 2,064 Em ploy ees 24,519 24,683 Establishments 1,560 1,479 Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48: EC0748I1: Transportation and Warehousing: Industry Series: Preliminary Summary Statistics for the United States: 2002 and 2007 .” http://factfinder.census.go v (January 27, 2010).

**Figure 3**  **- 8.**  **Distribution of Establishments within Pipeline Transportation (NAICS 486)** Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48: Transportation and Warehousing: Industry Series: Summary Statistics for the United States: 2002 <http://factfinder.census.gov>; ( January 27, 2010 ). In Table 3 - 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 equipme nt requirements potentially associated with reciprocating internal combustion engines (electric power generation and distribution ) represent less than 2% of the value of services. 60%

25% 15% 0% 10% 20% 30% 40% 50% 60% 70%

4862 Pipe line

Tr ansp or tati on of Natu ra l Gas 4869 Ot her Pipe line

Tr an sp or tati on 4861 Pi pe line

Tr an spor tati on of Cr ude

Oi l3 - 20

**Figure 3**  **- 9.**  **Distribution of Revenue within Pipeline Transportation (NAICS 486)**  Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48: Transportation and Warehousing: Industry Series: Summary Statistics for the United States: 2002 ” <http://factfinder.census.gov>; ( January 27, 2010) . **3 .3.3**  **Business Statistics** The pipeline transportation of natural gas is clearly concentrated in the two states closest to the refineries in the Gulf of Mexico. In 2002, Texas and L ouisiana contributed to 31% of all pipeline transportation establishments in the United States ( Figure 3 - 10) and 41% of all U.S. revenues. Other larger contributors with over 50 establishments in their states include Oklahoma, Pennsylvania, Kansas, Mississippi, and West Virginia. According to 2002 U.S. Census data, about 86% of tr ansportation 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 - 11). As shown in Table 3 - 1 6 , the four largest firms accounted for nearl y half of the establishments, and just over half, 51%, of total revenue. The 50 largest firms accounted for over 1,354 establishments and about 99% of total revenue. The average number of employees per establishment was approximately 17 across all groups of firms. Ente rprises within pipeline transportation (NAICS 486) generated $ 11.1 billion in total receipts in 200 8 . Including those enterprises without net income, the industry averaged an after tax profit margin of 9.6 % ( Table 3 - 1 7 ). 66%

19% 15% 0% 10% 20% 30% 40% 50% 60% 70%

4862 Pipe line

Tr ansp or tati on of Natu ra l Gas 4869 Ot her Pipe line

Tr an sp or tati on 4861 Pi pe line

Tr an spor tati on of Cr ude

Oi l3 - 21

**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 warm 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 work and fabricated structural product manufacturing 2.72% 5419A0 All other miscellaneous professional, scientific, and technical services 2.48% 524100 Insurance carriers 2.38% 531000 Real estate 2.33% 52A000 Monetary authorities and depository credit intermediation 1.76% V00200 Taxes on production and imports, less subsidies 1.41% 541100 Legal services 1.19% 221100 Electric power generation, transmission, and distribution 1.13%

a These values show

the amount of the commodity required to produce $1.00 of the industry ’ s output. The values are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input - Output Accounts: Detaile d Make Table, Use Table and Direct Requirements Table. Tables 4 and 5. The 200 7 SUSB shows that 47% of all firms in this industry made under $5 million in revenue. Enterprises with revenue over $100 million provided an overwhelming share of employ ment in this industry

(98%) ( Table 3 - 1 8 ).3 - 22

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

**(NAICS 486)** Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48 - 49: Geographic Distribution

—Pipeline transportation of natural gas: 2002 . <http://factfinder.census.gov>; (November 10, 2008).

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

**Transportation of Natural Gas Industry (NAICS 48621): 2002** Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48 - 49: Transportati on and Warehousing: Subject Series

—Estab & Firm Size: Legal Form of Organization for the United States: 2002 . <http://factfinder.census.gov>; (December 12, 2008). **Establishments by State**

Less than 15 15 - 39 40 - 79 80 - 149 More than 150

86%

8% 6% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Co rp or at io ns In di vi du al Pr opr iet or sh ip s Pa rt ners hip s3 - 23

**Table 3**  **- 1**  **6 .**  **Firm Concentration for Pipeline Transportation of Natural Gas (NAICS** 

**48621): 2002**

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

**Establishment Am**  **ount ($10 6**  **) Percentage of** 

**Total** All firms 1,431 $14,797 100% 23,677 16.5 4 largest firms 698 $7,551 51% 11,814 16.9 8 largest firms 912 $10,059 68% 15,296 16.8 20 largest firms 1,283 $13,730 93% 21,792 17.0 50 largest firms 1,354 $14,718 99% 23,346 17.2 Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “ Sector 48: Transportation and Warehousing: Subject Series

—Estab & Firm Size: Concentration by Largest Firms for the United States: 2002 ” <http://factfinder.census.gov>; (December 12, 2008). **Table 3**  **- 1**  **7 .**  **Aggregate Tax Data for Accounting Period 7/07 –**  **6/08: NAICS 486** Number of enterprises a 321 Total receipts (10 3 ) $11,062,608 Net sales (10 3 ) $10,210,083 Profit margin before tax 13.2% Profit margin after tax 9.6% a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “ Corporation Source Book: Data Files 2004 - 2007. ” <http://www.irs.gov/taxstats/article/0,,id=167415,00.html>; (May 2 , 2010).3-24 **Table 3**  **- 1**  **8 .**  **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 Employ ee Size: 200 7 . http://www2.census.gov/csd/susb/200 7 /usalli_r0 7 .xls.4 - 1 **Section 4 REGULATORY ALTERNATI**  **VES, COSTS, AND EMIS SION IMPACTS**  **4.1 Background**  This section of the RIA includes a discussion of the regulatory alternatives considered for the proposed reconsidered rule, the costs associated with these regulatory alternatives, and the impacts on affected emissions (both HAP and non - HAP). All impacts p resented are for the year of full implementation, 2013. Costs in this section are in 2009$. Costs in 2010$ presented elsewhere in the RIA are updat ed values based on the 2009$ costs presented in this section. Although the estimates presented are annual ized, they should be understood as a “snapshot” in anal yz ing costs. Annualized costs are estimated as equal for each year that control equipment is operated. This proposal was developed to address certain issues that have been raised by different stakehol ders through lawsuits, several petitions for reconsideration of the 2010 RI CE NESHAP amendments and other communications. After promulgation of the 2010 RI CE NESHAP amendments, the EPA received several petitions for reconsideration, legal challenges, and o ther communications raising issues of practical implementability , and certain factual information that had not been brought to the EPA’s attention during the rulemaking. The EPA has considered this information and believes that amendments to the rule to ad dress certain of these issues are appropriate. Therefore, the EPA is proposing amendments to the national emission standards for hazardous air pollutants for stationary reciprocating internal combustion engines under section 112 of the Clean Air Act. The proposed amendments include alternative testing options for certain large spark ignition (generally natural gas - fueled) stationary reciprocating internal combustion engines, management practices for a subset of existing spark ignition stationary reciprocating internal combustion engines in sparsely populated areas, and alternative and less burdensome monitoring and compliance options for the same engines in populated areas. The EPA is also proposing to include a limited temporary allowance for existing stationary emergency

area source engines to be used for peak shaving and non - emergency demand response as part of the pre - existing allowance for such engines to be used for non - emergency use for 50 hours annually . In addition, the EPA is proposing, in both the NESHAP and in the new source performance standards for stat ionary internal combustion engines to increase the hours that stationary

emergency

engines may

be used for emergency

demand response. The proposed amendments also correct minor mistakes in the pre - existing regulations. The full preamble for the final SIRI CE NESHAP and the rule itself can be reviewed at http://www.epa.gov/ttn/atw/rice/fr20au10.pdf .4 - 2

**4.2 Proposed Amendments to SI RICE NESHAP** 4.2.1 . Total Hydrocarbon Compliance (THC) Demonstratio n Option 4.2.1. 1. Background Currently , SI 4SRB non - emergency engines greater than 500 HP and located at major sources and existing SI4SRB non - emergency engines greater than 500 HP located at area sources have the option of meeting either a formaldehyde percent reduction or a formald eh yde concentration standard. Formaldeh yde was established in the original 2004 RI CE NESHAP as an appropriate surrogate for HAP emissions from 4SRB engines based on industry test data available at that time. Based on testing conducted at Colorado State Uni versity (CSU) of stationary lean burn engines, the EPA was able to establish CO as a surrogate for HAP for lean burn engines. Rich burn engines were not tested at CSU and the data the EPA had available at the time that were used to set the standards for ri ch burn engines did not support the same relationship between CO and HAP reductions for rich burn engines. Therefore, the EPA was unable to establish CO as a surrogate for HAP emissions for rich burn engines and the emission standard for rich burn engines was specified in terms of formaldehyde, the hazardous air pollutant emitted in the largest quantity from stationary engines. The EPA has previousl y acknowledged that it is significantly more expensive and difficult to test for formaldehyde than for CO, b ut has been unable in the past to support including the same flexibility for rich burn engines as is currentl y in the rule for lean burn engines with the option to meet the standards in terms of either formaldeh yde or CO. For these reasons , and expecting that new data for rich burn engines may become available in the future for the EPA to review and reassess possible surrogates for HAP, the EPA requested comment on this issue when proposing NESHAP for stationary existing engines less than or equal to 500 HP at major sources and all stationary existing engines at area sources in 2009 (74 FR 9698). Specificall y, the EPA solicited comment on whether it would be appropriate to include an alternative standard in terms of VOC and asked that commenters submit data supporting the relationship between HAP and VOC. Comments the EPA received back on the proposed rule asked that the formaldehyde standards for rich burn engines be replaced with emission standards for THC. The EPA determined at the time that it was not app ropriate to adopt an alternative standard in terms of THC (or VOC) for rich burn engines and discussed the reasons wh y in the 2010 responses to comments. Compliance with the formaldeh yd e standard in the rule is,4 - 3

therefore, currentl y demonstrated b y initia l and continuous performance testing for formaldeh yde. On October 19, 2010, engine manufacturer Dresser - Waukesha submitted a petition for reconsideration of the formaldehyde requirements. The EPA granted the petition for reconsideration on January 5, 201 1. (In addition, on November 3, 2010, the Engine Manufacturers Association submitted a petition for judicial review of these requirements.) In the petition for reconsideration, Dresser - Waukesha argued that formaldeh yd e is difficult and costly to measure. T he petition requested that the HAP surrogate for 4SRB engines should be THC rather than formaldeh yd e. Dresser - Waukesha submitted data from testing it conducted illustrating that THC reduction across the catal ys t is an appropriate surrogate for HAP reductio n across the catal ys t. According to the petitioner, testing for THC is easier and less costly and would substantially

reduce the burden of the rule for owners and operators of these engines. Testing for formaldeh yde emissions could cost more than double th at of testing for THC emissions and on a nationwide basis the EPA estimates that replacing formaldehyde testing with THC testing would result in substantial compliance cost savings annuall y while achieving the same reduction in HAP emissions. The EPA has reviewed the data submitted by Dresser - Waukesha. The data provided indicate that a strong relationship exists between percentage reductions of THC and percentage reductions of formaldeh yde (the surrogate for HAP emissions in the NESHAP) on rich burn engine s using non - selective catal yt ic reduction (NSCR). Data anal yz ed b y the EPA indicate that if the NSCR is reducing THC by at least 30 percent from 4SRB engines, formaldehyde emissions are guaranteed to be reduced b y at least 76 percent, which is the percenta ge reduction required for the relevant engines. Indeed, the percentage reduction of formaldeh yd e is invariably well above the 76 percent level, and is usually above 90 percent. Therefore, the EPA agrees with the petitioner that for SI 4SRB engines using NS CR and meeting the NESHAP by showing a percentage reduction of HAP, it would be appropriate to allow sources to demonstrate compliance with the NESHAP by showing a THC reduction of at least 30 percent. Including an optional THC compliance demonstration opt ion would reduce the burden of compliance significantl y while continuing to achieve the same level of HAP emission reduction because the emission standards would remain the same. Consequently , the EPA is proposing amendments to allow owners and operators o f certain stationary 4SRB engines (i.e., the ones currently subject to a formaldeh yd e percent reduction requirement) to show compliance with an optional THC compliance demonstration option. The specific amendments the EPA is proposing are presented below.4 - 4

4.2.1. 2. Proposed Amendments The EPA is proposing to add an alternative method of demonstrating compliance with the NESHAP for stationary

4SRB non - emergency

engines greater than 500 HP that are located at major sources of HAP emissions and for existing st ationary 4SRB non - emergency

engines greater than 500 HP that are located at area sources of HAP emissions that choose to meet the formaldeh yde percent reduction requirement of 76 percent or more. Based on the arguments and evidence presented in the peti tion discussed above, the EPA is proposing to add a compliance demonstration option for stationary 4SRB engines meeting a 76 percent or more formaldehyde reduction. The compliance demonstration option would be an alternative to the existing method of demon strating compliance with the formaldeh yde percent reduction standard, which is to test engines for formaldehyde. The alternative for owners and operators of 4SRB engines meeting a 76 percent or more formaldeh yde reduction would be to test their engines for THC showing that the engine is achieving at least a 30 percent reduction of THC emissions. Under the proposed amendments, e xisting and new stationary 4SRB engines greater than 500 HP and located at major sources would still be required to reduce formald eh yde emissions by 76 percent or more or limit the concentration of formaldehyde in the stationary RI CE exhaust to 350 parts per billion by volume, dry basis or less at 15 percent oxygen (O 2 ). However, owners and operators choosing to meet the formaldeh yde concentration limit would not have the THC demonstration compliance option, because EPA could not verify a clear relationship between concentrations of THC and concentrations of formaldehyd e in exhaust from these SI4SRB engines. The EPA is proposing that existing stationary 4SRB non - emergency

engines greater than 500 HP located at area sources located in populated areas be subject to an equipment standard and required to install a catal ys t. These engines would be subject to testing to demonstrate initially

and on an ongoing basis that the catal ys t is reducing CO by 75 percent or more, or alternativel y that THC emissions are being reduced b y 30 percent or more. Owners and operators of exist ing stationary 4SRB engines less than or equal to 500 HP who are required to limit the concentration of formaldeh yde in the stationary RICE exhaust to 10.3 parts per million by

volume, dry

basis (ppmvd) or less at 15 percent O 2 do not have the option to de monstrate compliance using THC and must continue to demonstrate compliance by testing for formaldeh yd e following the methods and procedures specified in the rule.4 - 5

Owners and operators opting to use the THC compliance demonstration method must demonstrate compliance by showing that the average reduction of THC is equal to or greater than 30 percent. Owners and operators of 4SRB stationary RI CE complying with the requirement to reduce formaldeh yd e emissions and demonstrating compliance b y using the THC compl iance demonstration option must conduct performance testing using Method 25A of 40 CFR part 60, appendix A

– Determination of Total Gaseous Organic Concentration Using a Flame Ionization Analyzer. Measurements of THC at the inlet and the outlet of the NSCR must be on a dry basis and corrected to 15 percent O2 or equivalent carbon dioxide content. To correct to 15 percent O2, dry basis, owners and operators must measure oxygen using Method 3, 3A or 3B of 40 CFR part 60, appendix A, or ASTM Method D6522 - 00 (2 005) and measure moisture using Method 4 of 40 CFR part 60, appendix A, or Test Method 320 of 40 CFR part 63, appendix A, or ASTM D6348 - 03. Because owners and operators are complying with a percent reduction requirement, the method used must be suitable fo r the entire range of emissions since pre and post - catal ys t emissions must be measured. Method 25A is capable of measuring emissions down to 5 ppmv and is, therefore, an appropriate method for measuring THC emissions for compliance demonstration purposes. The EPA is allowing sources the option to meet a minimum THC percent reduction of 30 percent b y using Method 25A of 40 CFR part 60, appendix A to demonstrate compliance with the formaldeh yde percent reduction in 40 CFR part 63, subpart ZZZZ. 4.2.2. Propos ed Amendment - Emergency Demand Response/Peak Shaving The EPA is proposing to revise the current provisions for stationary engines used for emergency

demand response operation. The provisions the EPA is proposing to amend are in §§63.6640(f) and 63.6675 of 40 CFR part 63, subpart ZZZZ. Currently , §63.6640(f)(1)(iii) allows a maximum of 15 hours per 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 p er 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 operator has declared an EEA Level 2 as defined in the North American Electric Reliability Corporation Reliability Standard EOP - 002 - 3, Capacity and Energy

Emergency

and during periods where there is a deviation of voltage or frequency of 5 percent or greater below standard voltage or frequency .4 - 6

The hours spent for emergency demand response operation are added to the hours spent for maintenance and testing purposes and counted towards the 100 hours per year. If the total time spent for d emand 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 eng ines may be called to operate 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 s tationary

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 respo nse 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 existin g 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 hour s spent towards maintenance and testing of the emergency engines. In addition to the changes the EPA is proposing related to emergency demand response operation, the EPA is also including a further provision for owners and operators of existing stationary emergency

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

RI CE to operate their engine for 50 hours per year in non - emergency situations. As currently

written, the 50 hours4 - 7

per year for non - emergency situations cannot be used for peak shaving or to generate income for a facilit y to supply power to an electric grid or otherwise suppl y power as part of a financial arrangement with another entity ; except that owners an d 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 y ear allowance for emergency engines to participate in emergency

demand respo nse programs is being increased to 100 hours per year, but will also include hours spent towards maintaining and conducting readiness testing of the emergency

engines. However, additionall y, the EPA is also proposing that stationary emergency engines locat ed at area sources be permitted to apply the 50 hours per ye ar that is currentl y allowed under §63.6640(f) for non - emergency operation towards any

non - emergency

operation, including operation as part of a financial agreement with another entity . The peak s having allowance would expire in 2017. The EPA is specifying that the power can only be used at the facility or towards the local sy stem, and the engine can onl y be operated for peak shaving as part of a program with the local distribution sy stem operator. The EPA is also clarifying that an engine that exceeds the calendar ye ar 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 - emergen cy engines for the remaining life of the engine. To estimate emissions from emergency engines the EPA has previousl y estimated that these ty pes of engines would on average operate for 50 hours per ye ar. The average hours of operation for emergency

engines is not expected to change based on the proposed amendments and 50 hours per ye ar is still believed to be representative of emergency engine operation. Therefore, the emissions previously calculated remain appropriate. In terms of an y revenue generated fro m participation in demand response and peak shaving programs, the EPA expects owners and operators will benefit financiall y, however, the EPA does not know to what extent. The EPA expects there will be savings and/or income generated thr ough participation in emergency

demand response programs and peak shaving operation, but the EPA has not accounted for an y potential revenue in estimating the costs and benefits of the proposed amendments. It is uncertain how frequently stationary

emergency

engines would ope rate if they are called upon. Other factors , such as the annual revenue from demand response programs (which varies), are also uncertain making it problematic to estimate the economic benefit of such programs. As such, the EPA has not estimated an y costs a ssociated with the emergency engine amendments.4 - 8

4.2.3 Proposed Amendment - Non - Emergency Stationary

SI RICE Greater than 500 HP L ocated at Area Sources 4.2.3. 1. Background The EPA is also proposing to amend the requirements that apply to existing stati onary non - emergency

4 stroke SIRICE greater than 500 HP located at area sources of HAP emissions, which are generall y natural gas fired engines. Currently, the RICE NESHAP requires owners and operators of such engines to 1) either meet a CO concentration limit of 47 parts ppmvd at 15 percent O2 or reduce emissions of CO by 93 percent or more, if the engines are 4SLB; and 2) to meet a formaldeh yde concentration limit of 2.7 ppmvd at 15 percent O2 or reduce formaldeh yd e emissions by

76 percent or more, if th e engines are 4SRB. In both cases, the EPA expects that the standards would be met using aftertreatment; oxidation cataly sts for 4SLB engines and NSCR for 4SRB engines. In addition to these emission requirements, owners and operators of existing stationary 4 - stroke engines greater than 500 HP at area sources are also subject to monitoring, testing, recordkeeping and reporting requirements. After the final requirements for existing stationary SIengines greater than 500 HP at area sources were published on August 20, 2010 (75 FR 51570), the EPA received petitions from Exterran (EPA - HQ - OAR - 2008 - 0708 - 0581), the American Petroleum Institute (EPA - HQ - OAR 2008 - 0708 - 0582), the Interstate Natural Gas Association of America (EPA - HQ - OAR - 2008 - 0708 - 0584), and the Gas Pr ocessors Association (EPA - HQ - OAR - 2008 - 0708 - 0587) requesting that the EPA reconsider the requirements of the final rule. The petitioners expressed man y similar concerns. As relevant to this rulemaking, petitioners stated that the EPA did not take into account the difference in population density and subsequently

did not consider the difference in health impacts in remote versus more heavily populated locations. In the petitioner ’s opinion, there should be less concern about engines that are located farther a way from people; the petitioners believed that the EPA has substantial latitude in requiring less stringent standards for owners and operators of stationary engines in remote areas. While the EPA does not share all of the views of the petitioners regard ing the difference between engines based on their location, the EPA does believe that it is reasonable to create a subcategory

of existing stationary

SI 4SLB and 4SRB engines above 500 HP located in areas remote from human activity . Engines located in remo te areas that are not close to significant human activity

may be difficult to access, may not have electricit y or communications, and may be unmanned most of the time. The costs of the emission controls, testing, and continuous monitoring requirements may be unreasonable when compared to the HAP emission reductions4 - 9

that would be achieved, considering that the engines are in sparsel y populated areas. The EPA believes that establishing a subcategory for SI engines at area sources of HAP located in sparsel y po pulated areas accomplishes the agency ’s goals and is adequate in protecting public health. The EPA is proposing to subcategorize sparsely populated engines using the existing DOT pipeline classification sy stem . This s ys tem classif ies locations based on their distance to pipelines covered b y the Pipeline and Hazardous Materials Safet y Administration safet y regulations. The DOT s ystem defines a class location unit as an onshore area that extends 220 yards or 200 meters on either side of the centerline of any continuous 1 - mile (1.6 kilometers) length of pipeline. The DOT approach further classifies pipeline locations into Class 1 through Class 4 locations based on the number of buildings intended for human occupancy . A Class 1 location is defined as an offsh ore area or an y class location unit that has 10 or fewer buildings intended for human occupancy . The DOT classification sy stem also has special provisions for locations that lie within 100 yards (91 meters) of either a building or a small, well - defined out side area (such as a playground, recreation area, outdoor theater, or other place of public assembly) that is occupied by 20 or more persons on at least 5 day s a week for 10 weeks in any 12 - month period, and for class location units where buildings with fo ur or more stories above ground are prevalent. To be considered remote, a source could not fall under one of these special provisions. Stakeholders from the oil and gas industry have indicated to the EPA that the DOT sy stem is well - established and there w ould be substantial overlap between engines affected b y the rule and covered b y the DOT pipeline classification system. Incorporating this approach would also create harmonization between the EPA and DOT and would reduce the implementation and enforcement burden for states. Implementation for affected sources would also be less burdensome because the s ys tem is already in place and used by

industry and covers the majority

of these engines. Stakeholders have indicated they are required to review the class loc ation status of pipeline segments annuall y. The EPA believes this approach is reasonable for defining the subcategory

of remote engines for those engines that are associated with natural gas pipelines. For those engines not associated with pipelines, the EPA is using similar criteria. An engine would be considered to be in sparsely populated areas if within 0.25 mile radius of the engine there are 5 or fewer buildings intended for human occupancy . EPA requests comment on whether the use of these DOT classi fications are appropriate for airborne emissions and whether, to be considered remote, an engine not associated with a natural gas pipeline should also need to be farther than 100 yards (91 meters) of either a building or a small, well - defined outside area4 - 10

(such as a playground, recreation area, outdoor theater, or other place of public assembly) that is occupied b y 20 or more persons on at least 5 days a week for 10 weeks in any 12 - month period. The EPA is proposing management practices as generall y availa ble control technologies for existing stationary

SI 4SLB and 4SRB area source non - emergency engines located in sparsel y populated areas. Given the remote location of the engines from human activity, the EPA believes that it is appropriate not to include re quirements that would necessitate aftertreatment and extensive testing and monitoring. The EPA has previously estimated that the costs of oxidation cataly st for existing 4SLB and 4SRB engines above 500 HP at area sources are $310 and $150 million, for capi tal and annual costs, respectivel y. The capital and annual costs of the RI CE NESHAP for existing 4SLB and 4SRB engines above 500 HP at area sources would be $30 million and $12 million, respectivel y, if these proposed amendments are incorporated into the r ule. Creating a subcategory of these engines for the ones located in sparsely populated areas and not mandating emission controls would significantly reduce the cost of the rule for such engines. For existing stationary

SI 4SLB and 4SRB area source non - emergency engines that are located in populated areas, the EPA is proposing an equipment standard that requires the installation and operation of a cataly st that will have to be tested initially and annually

to ensure that the catal ys t is working properl y and reducing emissions as required. In addition, these units will be required to have devices to shut down the engine if the catal ys t is exposed to dangerous temperatures or have continuous monitoring equipment installed to record cataly st inlet temperatur es. The EPA is proposing shorter test duration and less rigorous methods than currentl y required while still ensuring that HAP reductions remain at expected levels for these engines located in populated areas. The specific amendments the EPA is proposing are discussed below. 4.2.3. 2. What are the Proposed Amendments ? Owners and operators of engines in sparsel y populated areas would have to conduct a review of the surrounding area every 12 months to determine if the nearb y population has changedIf the engine no longer meets the criteria for a sparsely populated area the owner and operator must within 1 year compl y with the emission standards specified below for populated areas . The EPA requests comment on whether engines that are not associated with pipelines should be required to conduct the review less frequently than every 12 months.4 - 11

Owners and operators of existing stationary 4SLB and 4SRB greater than 500 HP at area sources that are in sparsely populated areas as described above would be requir ed to perform the following:

• Change oil and filter every 1,440 hours of operation or annually , whichever comes first;

• In spect spark plugs every 1,440 hours of operation or annuall y, whichever comes first, and replace as necessary ; and

• In spect all hoses and belts every 1,440 hours of operation or annually , whichever comes first, and replace as necessary . Sources have the option to use an oil anal ys is program as described in §63.6625(i) of the rule in order to extend the specified oil change requirement. T he oil anal ys is must be performed at the same frequency

specified for changing the oil in Table 2d of the rule. The anal ys is program must at a minimum analyze the following three parameters: Total Acid Number, viscosity , and percent water content. The cond emning limits for these parameters are as follows: Total Acid Number increases b y more than 3.0 milligrams of potassium h ydroxide per gram from Total Acid Number of the oil when new; viscosity of the oil has changed b y more than 20 percent from the viscosi ty of the oil when new; or percent water content (by volume) is greater than 0.5. If all of these condemning limits are not exceeded, the engine owner or operator is not required to change the oil. If an y of the limits are exceeded, the engine owner or ope rator must change the oil within 2 day s of receiving the results of the anal ys is; if the engine is not in operation when the results of the anal ys is are received, the engine owner or operator must change the oil within 2 day s or before commencing operation , whichever is later. The owner or operator must keep records of the parameters that are anal yzed as part of the program, the results of the anal ys is, and the oil changes for the engine. The analy sis program must be part of the maintenance plan for the eng ine. Owners and operators of existing stationary 4SLB and 4SRB area source engines above 500 HP in sparsely

populated areas would also have to operate and maintain the stationary RI CE and aftertreatment control device (if any) according to the manufacture r's emission - related written instructions or develop their own maintenance plan which must provide to the extent practicable for the maintenance and operation of the engine in a manner consistent with good air pollution control practice for minimizing emis sions. For engines in populated areas, i.e., existing stationary 4SLB and 4SRB non - emergency engines greater than 500 HP at area sources that are located on DOT Class 2 through Class 44 - 12

pipeline segments or, for engines not associated with pipelines, that do not meet the 0.25 mile radius with 5 or less buildings criteria, the EPA is proposing to adopt an equipment standard requiring the installation of a cataly st to reduce HAP emissions. Owners and operators of existing area source 4SLB non - emergency engin es greater than 500 HP in populated areas would be required to install an oxidation cataly st. Owners and operators of existing area source 4SRB non - emergency

engines greater than 500 HP in populated areas would be required to install NSCR. Owners and operators must conduct an initial test to demonstrate that the engine achieves at least a 93 percent reduction in CO emissions or a CO concentration level of 47 ppmvd at 15 percent O2, if the engine is a 4SLB engine. Similarly , owners and operators must conduct an initial performance test to demonstrate that the engine achieves at least a 75 percent CO reduction or a 30 percent THC reduction, if the engine is a 4SRB engine. The initial test must consist of three test runs. Each test run must be of at least 15 mi nute duration, except that each test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist of one measurement cycle as defined by the method and include at least 2 minutes of test data phase measurement. To measure CO, em ission sources must use the CO methods already specified in subpart ZZZZ, or the proposed appendix A to 40 CFR part 63, subpart ZZZZ. The THC testing must be conducted using EPA Method 25A. The owner or operator of both engine t yp es must also use a high t emperature shutdown device that detects if the catal ys t inlet temperature is too high, or, alternatively , the owner or operator can monitor the catal ys t inlet temperature continuously and maintain the temperature within the range specified in the rule. For 4SLB engines the catal ys t inlet temperature must remain at or above 450°F and at or below 1,350°F. For 4SRB engines the temperature range must be greater than or equal to 750°F and less than or equal to 1,250°F at the catal ys t inlet. Owners and operators must in addition to the initial performance test conduct annual checks of the cataly st to ensure proper catal ys t activity . The annual check of the catal ys t must at a minimum consist of one 15 - minute run using the methods discussed above, except that each test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist of one measurement cycle as defined by the method and include at least 2 minutes of test data phase measurement. Owners and operators of 4SLB engines must demonstrate during the catal ys t activity

test that the catal ys t achieves at least a 93 percent reduction in CO emissions or that the engine exhaust CO emissions are no more than 47 ppmvd at 15 percent O2. Owners and operators of 4SRB engines must demonstrate that their catal ys t is reducing CO emissions by 75 percent or more, or alternatively , that THC emissions are being reduced by at least 30 percent during the catal ys t activity check.4 - 13

If the emissions from the engine do not exceed the levels required for the in itial test or annual checks of the cataly st, then the catal ys t is considered to be working properl y. If the emissions exceed the specified pollutant levels in the rule, the exceedance(s) is/are not considered a violation, but the owner or operator would be required to shut down the engine and take appropriate corrective action (e.g., repairs, clean or replace the catal ys t, as appropriate). A follow - up test must be conducted within 7 day s of the engine being started up again to demonstrate that the emission levels are being met. I f the retest shows that the emissions continue to exceed the specified levels, the stationary RI CE must again be shut down as soon as safel y possible, and the engine may not operate, except for purposes of start - up and testing, until the owner/operator demonstrates through testing that the emissions do not exceed the levels specified.

4.2.3.3 Compliance Date The EPA has received some questions regarding whether the compliance dates for engines impacted 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 O ctober 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 a ction. 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 aff ected by the reconsideration and that may need additional time to install controls to comply with the applicable requirements can request up to an additional year to install controls, as specified in 40 CFR 63.6(i). **4. 3**  **What Are the Pollu tants Regulated b**  **y the**  **Rule?** The proposed reconsideration ru le 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 em itted from stationary engines. Th e HAP which have been measured in emission tests conducted on SIstationary RI CE include: formaldehyde, acetaldehyde,4 - 14

acrolein, methanol, benzene, toluene, 1,3 - butadiene, 2,2,4 - trimethylpentane, hexane, xylene, naphthalene, PAH, methylene chloride, and ethylbenzene . EPA described the health effects of these HAP and other HAP emitted from the operation of stationary RICE in the preamble to 40 CFR part 63, subpart ZZZZ, published on June 15, 2004 (69 FR 33474) . These HAP emissions are known to cause, or contribute significantl y to air pollution, which may reasonabl y be anticipated to endanger public health or welfare. For the standards included in this action, EPA believes that previous determinations regarding the appropriateness of using formaldeh yde and carbon monoxide (CO) both in concentration (parts per million (ppm)) levels as surrogates for HAP for stationary RICE are still valid . Consequently , EPA is promulgating CO or formaldehyde standards in order to regulate HAP emissions . In addition to reducing HAP, the emission control technologies that will be installed on stationary RICE to reduce HAP will also reduce CO and VOC, and for rich burn engines will also reduce NOx. **4.4 Cost Impacts**  **4.4.1 Introduction**  EPA has determined that oxidation cataly sts for two - stroke lean burn (2SLB) and four stroke lean burn (4SLB) engines, and non - selective catal yt ic reduction (NSCR) for four - stroke rich burn (4SRB) engines are applicable controls for HAP reduction from existing stationary SI RI CE. To determine the ca pital and annual costs for these control technologies, e quipment cost information was obtained from industry groups 2 and vendors and manufacturers of SI engine control technology . In some cases, the industry groups provided a breakdown of the capital and annual cost components for each of the retrofit options. Using this cost data, annualized cost and capital cost equations for oxidation cataly sts and NSCR were developed. **4.4.2 Control Cost**  **M**

**ethodology** The following section s describe the methodology used to derive the total capital and total annual costs for each of the control technolog y options . These methodologies were used to calculate total capital and total annual costs when only purchased equipment costs were available (e.g., vendor equipment costs) . The methodologies were not used for cost data provided b y 2 Reciprocating Internal Combustion Engine National Emission Standards for Hazardous Air Pollutants (RICE NESHAP) Proposed Revisions

– Emission Control Costs Analysis Background for “Above the Floor” Emission C ontrols for Natural Gas - Fired RICE, Innovative Environmental Solutions Inc., October 2009. (EPA - HQ - OAR 2008 - 0708 - 0279).4 - 15

industry groups because they

included a breakdown of the actual total capital and total annual costs. A summary

of the m ethodolog ies, equations, and assumptions used to estimate the total capital and total annual costs for some of the cost data are described in the following sections. 4.4.2.1 Total Capital Costs The total capital cost includes the direct and indirect costs of purchasing and installing the control equipment. The direct cost includes the cost of purchasing the equipment and instrumentation, cost of shipping, and the cost of installing the control equipment. The indirect cost includes the costs for engineering, contractor fees, testing costs, and also includes costs for contingencies, such as additional modifications, or delay s in startup. The total capital cost equation can be summarized as follows:

Total Capital Cost (TCC) = Direct Costs (DC) + Indirect Costs (I C) The direct costs include the costs of purchasing and installing the control equipment and can be summarized using the following equation;

DC = Purchased E quipment C ost (PEC) + Direct Installation Costs ( DI C ). A summary

of the cost assumptions for PEC includes the following :

 Control Device and Auxiliary Equipment (EC) ;

 Instrumentation (10% of EC) ;

 Sales Tax (3% of EC) ;

 Freight (5% of EC) ; and can be summarized as: PEC = 118% EC . A summary

of the cost assumptions for DI C includes the following:

 Foundations and Supports (8% of PEC) ;

 Handling and Erection (14% of PEC) ;

 Ele ctrical (4% of PEC) ;

 Piping (2% of PEC) ;4 - 16  Insulation for Ductwork (1% of PEC) ;

 Painting (1% of PEC) ; and can be summarized as: DI C = 30% PEC = 0.3 PEC. Therefore, the direct costs can be simplified using the following equation: DC = PEC + 0.3 PEC = 1.3 PEC . The indirect costs include the costs of engineering and contractor fees and contingencies and can be summarized using the following equation:

IC = Indirect Installation Costs ( IC C ) + Contingencies ( C ). A summary

of the cost assumptions for I CC includes th e following :

 Engineering (10% of PEC) ;

 Construction and Field Expenses (5% of PEC) ;

 Contractor Fees (10% of PEC) ;

 Startup (2% of PEC) ;

 Performance Test (1% of PEC) ; and can be summarized as: IIC = 28% PEC = 0.28 PEC . A summary

of the cost assumptions for C includes the following :

 Equipment Redesign and Modifications ;

 Cost Escalations ;

 Delay s in Startup ; and is assumed to be: C = 3% PEC = 0.03 PEC .4 - 17

Therefore, the IC can be summarized using the following equation: IC = 0.28 PEC + 0.03 PEC = 0.31 PEC , and the simplified TCC equation can be expressed as:

TCC = 1.3 PEC + 0.31 PEC = 1.61 PEC = 1.61 (1.18 EC) = 1.9 EC 4.4.2.2 Total Annual Costs The total annual cost includes the direct and indirect annual costs of operating and maintaining the control equipment. The direct annual cost includes the cost of the utilities, operating labor, and control device cleaning and maintenance. The indirect annual cost includes the overhead costs such as spare parts for the control equipment, administrative charges, and the cap ital recovery

of the control technology . The total annual cost equation can be summarized as follows: Total Annual Cost (TAC) = Direct Annual Costs (D A C) + Indirect Annual Costs (IA C) . The DAC includes the following parameters :

 Utilities ;

 Operating Labor ;

 Maintenance ;

 Annual Compliance Test ;

 Cataly st Cleaning ;

 Cataly st Replacement ;

 Cataly st Disposal . The IAC includes the following parameters :

 Overhead ;

 Fuel Penalt y ;

 Property

Tax ;

 Insurance ;

 Administrative Charges ;4 - 18  Capital Recovery

= { I(1+I) n/((1+I) n - 1)*TCC} where I is the interest rate, and n is the equipment life. To calculate DAC, the costs were broken up into three separate costs: operation and maintenance materials cost, operation and maintenance labor cost, and the cost for annual performance te sting or downtime or allowance for catal ys t washing. Actual annual cost data from the industry

groups were used to estimate the DAC for each of the control technologies. The IAC was broken up into three separate costs: administrative, fuel penalty , and cap ital recovery . Again, cost data from the industry groups was used to estimate these costs for each of the control technologies. No fuel penalt y was estimated for the oxidation catalyst control technologies, because this control technology does not increase the fuel usage of the SI engine. **4.4.3 Control Cost Equations**  Control cost equations were developed for 2SLB oxidation cataly st, 4SLB oxidation catal ys t, and a NSCR for 4SRB engines using the total capital cost and total annual cost data for each control technology . Control cost equations for 2SLB and 4SLB oxidation catal ys ts were developed separately

because the 2SLB oxidation catal ys t requires a premium catal ys t to reduce the HAP compounds because of the low exhaust temperature of 2SLB engines. 4.4.3.1 2 SLB Oxidation Catalys t The 2SLB oxidation cataly st is an effective control technology that reduces HAP emissions from a 2SLB SI engine b y oxidizing organic compounds using a catal ys t. The oxidation cataly st unit contains a honeycomb - like structure or substrate with a large surface area that is coated with a premium active catal y st layer such as platinum or palladium. The oxidation catal ys t works b y oxidizing carbon monoxide ( CO ) and gaseous h ydrocarbons (HAP) in the exhaust gas to carbon dioxide (CO 2 ) and water . The reduction of CO and HAP varies depending on the ty pe of cataly st used and the exhaust temperature of the pollutant stream. The cost of retrofitting an oxidation cataly st to an existing 2SLB engine was estimated using cost data obtained from ven dors and industry groups covering engines ranging from 58 horsepower (HP) to 4,670 HP. An equipment life of 1 0 y ears and an interest rate of 7 percent were used to estimate the capital recovery of the control technology and the fuel penalty

was assumed to be negligible. The cost equations are presented in 20 09 dollars. The total annualized cost equation for retrofitting an oxidation cataly st on a 2SLB engine was estimated to be :

2SLB Oxidation Cataly st Total Annual Cost = $11.4 x HP + $13,9284 - 19

where HP = eng ine size in HP. The linear equation has a correlation coefficient of 0. 8046 , which shows the data fit s the equation closel y. Therefore, this equation was used to estimate annualized cost for an oxidation catal ys t on a 2SLB engine . The total capital cost e quation for retrofitting an oxidation cataly st on a 2SLB engine was estimated to be:

2SLB Oxidation Cataly st Total Capital Cost = $47.1 x HP + $41,603 where HP = engine size in HP. 4.4.3.2 4SLB Oxidation Catalyst The 4SLB oxidation cataly st is an effective control technology that reduces HAP emissions from a 4SLB SI engine b y oxidizing organic compounds using a catal ys t. The oxidation cataly st unit contains a honeycomb - like structure or substrate with a large surface area that is coated with a prem ium active catal ys t layer such as platinum or palladi um. The oxidation catal ys t works b y oxidizing CO and gaseous h ydrocarbons (HAP) in the exhaust gas to CO 2 and water . The reduction s of CO and HAP vary depending on the ty pe of catal yst used and the exhau st temperature of the pollutant stream. The cost of retrofitting an oxidation cataly st to an existing 4SLB engine was estimated using cost data obtained from vendors and industry groups covering engines ranging from 400 HP to 8,000 HP. Again, an equipment life of 1 0 y ears and an interest rate of 7 percent were used to estimate the capital recovery of the control technology and the fuel penalty

was assumed to be negligible. The cost equations are presented in 2009 dollars. The total annualized cost equation for retrofitting an oxidation cataly st on a 4SLB engine was estimated to be :

4SLB Oxidation Cataly st Total Annual Cost = $1.81 x HP + $3,442 where4 - 20

HP = engine size in HP. The linear equation has a correlation coefficient of 0. 9779 , which shows the data fit s the equation very closely . Therefore, this equation was used to estimate annualized cost for an oxidation cataly st on a 4SLB engine . The total capital cost equation for retrofitting an oxidation cataly st on a 4SLB SI engine was estimated to be:

4SLB Oxidation Cataly st Total Capital Cost = $12.8 x HP + $3,069 where HP = engine size in HP. A summary

of the cost calculations, regression analy ses, and graphical representations of the annual and capital cost data are presented in Appendix A of the cos t memo that is the basis for the cost data presented in this RIA . 3 4.4.3.3 Non - Selective Catalytic Reduction The NSCR or three - way

catal ys t is used to control HAP emissions from 4SRB engines. In addition to HAP reductions, NSCR also reduces the emissions o f nitrogen oxides (NO x ), CO , and other hydrocarbons (HC) . The reduction of HAP and CO takes place through an oxidation reaction that converts HAP to CO 2 and water and converts CO to CO 2 . The conversion of NO x takes place through a reduction of the NO x to n itrogen gas and ox ygen. The cost of retrofitting an NSCR on an existing 4SRB engine was estimated based on cost data received from vendors and industry groups. A linear regression analy sis was done on the data set and the linear equation for annualized cos t was; NSCR Annual Cost = $4.77 x HP + $5,679 where HP = engine size in HP.

3 Memorandum from Bradley Nelson, EC/R to Melanie Kin g, EPA. OAQPS/SPPD/ESG. Im pacts Associated with NESHAP for Existing Stationary SI RICE . June 29, 2010 .4 - 21

The linear equation has a correlation coefficient of 0. 7987 , which shows an acceptable representation of the cost data . Therefore, this equation was used to estimate annualized cost for retrofitting the NSCR control technology on 4SRB engines . The capital cost equation for retrofitting an air - to - fuel ratio (AFR) controller and NSCR on a 4SRB engine was estimated to be: NS CR Capital Cost = $24.9 x HP + $13,118 where HP = engine size in HP. **4.4.4 S** **ummary** Table 4 - 1 presents a summary of the annual and capital control costs as a function of engine size for the control technologies applicable to existing stationary SI engines, as discussed in this memorandum. **Table 4**  **- 1**  **. Summary of Annual and Capital Costs Equations for Existing Stationary SI** 

**Engines HAP Control Device**  **Annual Cost ($20 09**  **) Capital Cost ($20**  **09 )**  2SLB Oxidation Catalyst $11.4 x HP + $13,928 $47.1 x HP + $41,603 4SLB Oxidation Catalyst $1.81 x HP + $3,442 $12.8 x HP + $3,069 NSCR $4.77 x HP + $5,679 $24.9 x HP + $13,118 A summary

of the annual and capital costs associated with the rule and obtained using the methodology

described above are presented in T ables 4 - 2 t o 4 - 5 below . **4** These costs are used as input to the economic impact as well as the small entity analy sis.

4 Memorandum from Bradley Nelson, EC/R to Melanie King, EPA. OAQPS/SPPD/ESG. Im pacts Associated with NESHAP for Existing Stationary SI RICE . June 29, 2010 .**Table 4 -**  **2 .**  **Summary of Major Source and Area Source Costs for the SI RICE NESHAP a** 

**Size Range (HP) Capital** 

**Control Cost Annual** 

**Control Cost Initial Test**  **Record**   ** keeping** **Reporting Monitoring** **— Capital Cost**  **Monitoring**

**— Annual**  **Cost Total Annual** 

**Costs Total Capital** 

**Costs Major Sources**  25

– 50 $0 $0 $0 $4,060,795 $0 $0 $0 $4,060,795 $0 50

– 100 $0 $0 $0 $1,087,540 $0 $0 $0 $1,087,540 $0 100

– 175 $48,502,361 $37,071,061 $15,971,384 $1,721,899 $5,725,314 $0 $0 $60,489,657 $48,502,361 175

– 300 $13,225,919 $8,382,568 $3,442,648 $371,157 $1,234,097 $0 $0 $13,430,470 $13,225,919 300

– 500 $ 10 , 93 4, 795 $ 5 , 562 , 872 $2,123,326 $228,919 $761,155 $0 $0 $ 8,676,262 $ 10 , 934 , 795 500

– 600 $0 $0 $0 $0 $0 $0 $0 $0 $0 600

–750 $0 $0 $0 $0 $0 $0 $0 $0 $0 >750 $0 $0 $0 $0 $0 $0 $0 $0 $0 **Total $**  **72 ,**  **663 ,**  **076 $5**  **1 ,0**  **16 ,**  **500 $21,537,358**  **$7,470,310 $7,720,566**  **$0 $0**  **$87,744,734 $72**  **, 663**  **, 076**  **Area Sources** 25

– 50 $0 $0 $0 $6,668,944 $0 $0 $0 $6,668,944 $0 50

– 100 $0 $0 $0 $2,868,511 $0 $0 $0 $2,868,511 $0 100

– 175 $0 $0 $0 $3,529,711 $0 $0 $0 $3,529,711 $0 175

– 300 $0 $0 $0 $1,264,799 $0 $0 $0 $1,264,799 $0 300

– 500 $0 $0 $0 $908,913 $0 $0 $0 $908,913 $0 500

– 600 $ 7,547,433 $2 ,662,805 $ 248,366 $454,493 $1,26 , 426 0 0 $ 3,492,090 $7 ,547,433 600

–750 $ 1,522,236 $5 05,221 $ 44,323 $77,882 $22 , 562 0 0 $ 649,988 $1 , 5 22,236 >750 $ 21,075,418 $6 ,214,397 $ 472,244 $829,795 $240 , 387 0 0 $ 7,756,823 $21 ,075,418 **Total $**  **30,145,088 $9**  **,382,423 $**  **764,933 $16,603,048**  **$389 ,**  **375 0**  **0 $**  **27,139,780 $30,**  **145,088** Grand Total **Total $**  **102.808,163 $**  **60,398,923 $**  **2 2**  **,302,292 $24,073,358**  **$ 8,106,972**  **0 0**  **$ 114,884,514**  **$ 102,808.163** 

a Costs are presented in 2009 dollars.4-23 **Table 4 -**  **3 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP a**  **Major Source Area Source**  **Total (Major + Area) NAICS**  **Capital Cost Annual Cost**  **Capital Cost Annual Cost**  **Capital Cost Annual Cost**  2211 Electric Power Generation $52,905,258 $63,062,494 $1 1,698,144 $ 12,138,277 $ 64,603,403 $ 75,200,772 48621 Natural Gas Transmission $1,484,494 $1,462,530 $1 3,718,381 $ 6,142,839 $1 5,202,876 $ 7,605,369 211111 Crude Petroleum & NG

Production $4,561,236 $6,138,383 $7 1,439 $ 951,46 2 $ 4,632,675 $7, 089,844 211112 Natural Gas Liquid Producers $4,561,236 $6,138,383 $7 1,439 $ 951,46 2 $ 4,632,675 $7, 089,844 92811 National Security $5,878,362 $7,006,944 $1 , 299,79 4 $ 1,348,697 $ 7,178,156 6 $ 8,355,641 335312 Hydro Pow er Units $0 $25,248 $0 $37,872 $0 $63,120 335312 Irrigation Sets $3,025,050 $3,230,856 $3 ,285,990 $ 4,999,04 1 $ 6,310,940 $ 8,229,896 333992 Welders $247,440 $679,896 $0 $570,130 $247,440 $1,250,027 Total $72,663,076 $87,744,734 $3 0,145,088 $ 27,139,780 **$ 102,808,163**  **$ 114,884,514** 

a Costs are presented in 2009 dollars.4-24 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Size a**  **Major Source**  **Area Source Total (Major + Area)**  **NAICS Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Electric Power Generation (2211)**  25

– 50 hp $0 $2,758,459 $0 $4,137,688 $0 $6,896,147 50

– 100 hp $0 $606,144 $0 $909,215 $0 $1,515,359 100

– 175 hp $33,868,173 $42,238,648 $0 $1,803,548 $33,868,173 $44,042,196 175

– 300 hp $10,603,849 $10,767,847 $0 $446,361 $10,603,849 $11,214,209 300

– 500 hp $8,433,236 $6,691,397 $0 $264,820 $8,433,236 $6,956,217 500

– 600 hp $0 $0 $2 ,543,944 $1 ,177,047 $2 ,543,944 $1 ,177,047 600

–750 hp $0 $0 $ 515,514 $2 20,122 $5 15,514 $2 20,122 >750 hp $0 $0 $8 ,638,687 $3 ,179,475 $8 ,638,687 $ 3,179,475 Total Electric Power Generation 2211 $52,905,258 $63,062,494 $1 1,698,144 $ 12,138,277 $ 64,603,403 $ 75,200,772 **Natural Gas Transmission (48621)** 25

– 50 hp $0 $102 $0 $1,934 $0 $2,036 50

– 100 hp $0 $4,872 $0 $92,571 $0 $97,443 100

– 175 hp $301,721 $376,291 $0 $203,518 $301,721 $579,809 175

– 300 hp $643,157 $653,104 $0 $342,928 $643,157 $996,032 300

– 500 hp $539,617 $428,162 $0 $214,637 $539,617 $642,799 500

– 600 hp $0 $0 $1 ,925,560 $ 890,929 $1 ,925,560 $ 890,929 600

–750 hp $0 $0 $9 49,443 $ 405,408 $9 49,443 $ 405,408 >750 hp $0 $0 $1 0,843,377 $ 3 ,9 90,913 $1 0,843,377 $ 3 , 990,913 Total Natural Gas Transmission (48621) $1,484,494 $1,462,530 $1 3,781,381 $6 ,142,839 $1 5,202,876 $ 7,605,369 **Crude Petroleum & NG Production (211111)** 25

– 50 hp $0 $388,115 $0 $582,173 $0 $970,288 50

– 100 hp $0 $66,698 $0 $100,047 $0 $166,744 100

– 175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531 (continued)4-25 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Size a**  **(continued) Major Source**  **Area Source Total (Major + Area)**  **NAICS Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost** 175

– 300 hp $1,037 $1,053 $0 $44 $1,037 $1,096 300

– 500 hp $10,424 $8,271 $0 $327 $10,424 $8,598 500

– 600 hp $0 $0 $3 ,102 $1 ,435 $3 .102 $1 ,435 600

–750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $ 68,337 $ 25,151 $ 68,337 $ 25,151 Total Crude Petroleum & NG Production (211111) $4,561,236 $6,138,383 $7 1,439 $ 951,462 $ 4,632,675 $7, 089,844 **Natural Gas Liquid Producers (211112)** 25

– 50 hp $0 $388,115 $0 $582,173 $0 $970,288 50

– 100 hp $0 $66,698 $0 $100,047 $0 $166,744 100

– 175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531 175

– 300 hp $1,037 $1,053 $0 $44 $1,037 $1,096 300

– 500 hp $10,424 $8,271 $0 $327 $10,424 $8,598 500

– 600 hp $0 $0 $3 ,102 $1 ,435 $3,1 02 $1, 43 5 600

–750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $ 68,337 $ 25,151 $ 68,337 $ 25,151 Total Natural Gas Liquid Producers (211112) $4,561,236 $6,138,383 $7 1,439 $ 951,462 $ 4,632,675 $7, 089,844 **National Security (92811)** 25

– 50 hp $0 $306,495 $0 $459,743 $0 $766,239 50

– 100 hp $0 $67,349 $0 $101,024 $0 $168,373 100

– 175 hp $3,763,130 $4,693,183 $0 $200,394 $3,763,130 $4,893,577 175

– 300 hp $1,178,205 $1,196,427 $0 $49,596 $1,178,205 $1,246,023 300

– 500 hp $937,026 $743,489 $0 $29,424 $937,026 $772,913 500

– 600 hp $0 $0 $2 82,660 $1 30,783 $2 82,660 $1 30,783 (continued)4-26 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Size a**  **(continued) Major Source**  **Area Source Total (Major + Area)**  **NAICS Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost** 600

–750 hp $0 $0 $ 57,279 $ 24,458 $5 7,279 $ 24,45 8 >750 hp $0 $0 $9 59,854 $ 353,275 $9 59,854 $ 353,275 Total Nat ional Security ( 92811 ) $5,878,362 $7,006,944 $1 ,299,794, $ 1 , 348,697 $ 7,178,156 $ 8,355,641 **Hydro Power Units (335312)** 25

– 50 hp $0 $22,688 $0 $34,032 $0 $56,721 50

– 100 hp $0 $2,560 $0 $3,840 $0 $6,399 100

– 175 hp $0 $0 $0 $0 $0 $0 175

– 300 hp $0 $0 $0 $0 $0 $0 300

– 500 hp $0 $0 $0 $0 $0 $0 500

– 600 hp $0 $0 $0 $0 $0 $0 600

–750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $0 $0 $0 $0 Total Hydro Pow er Units (335312) $0 $25,248 $0 $37,872 $0 $63,120 **Irrigation Sets (335312)** 25

– 50 hp $0 $32,913 $0 $625,338 $0 $658,251 50

– 100 hp $0 $65,825 $0 $1,250,677 $0 $1,316,502 100

– 175 hp $1,222,348 $1,524,449 $0 $824,505 $1,222,348 $2,348,954 175

– 300 hp $798,634 $810,986 $0 $425,827 $798,634 $1,236,813 300

– 500 hp $1,004,068 $796,683 $0 $399,376 $1,004,068 $1,196,060 500

– 600 hp $0 $0 $2 ,789,064 $1 ,290,460 $2 ,789,064 $1 ,290,460 600

–750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $ 496,827 $ 182,857 $ 496,827 $ 182,857 Total Irrigation Sets (335312) $3,025,050 $3,230,856 $ 3,285,890 $ 4,999,041 $ 6,310,940 $ 8,229,896 (continued)4-27 **Table 4 -**  **4 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Size a**  **(continued) Major Source**  **Area Source Total (Major + Area)**  **NAICS Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Capital Cost**  **Annual Cost Welders (333992)**  25

– 50 hp $0 $163,908 $0 $245,862 $0 $409,771 50

– 100 hp $0 $207,394 $0 $311,091 $0 $518,485 100

– 175 hp $247,440 $308,594 $0 $13,177 $247,440 $321,771 175

– 300 hp $0 $0 $0 $0 $0 $0 300

– 500 hp $0 $0 $0 $0 $0 $0 500

– 600 hp $0 $0 $0 $0 $0 $0 600

–750 hp $0 $0 $0 $0 $0 $0 >750 hp $0 $0 $0 $0 $0 $0 Total Welders (333992) $247,440 $679,896 $0 $570,130 $247,440 $1,250,027 **Total** $72,663,076 $87,744,734 $3 0,145,088 $ 27,139,780 $ 102,808,163 $ 114,884,514 a Costs are presented in 2009 dollars.4-28 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Number of Engines a**  **Number of Engines Total (Major**  **+ Area) NAICS**  **Major Area**  **Total Capital Cost**  **Annual Cost Electric Power Generation (2211)**  25

– 50 hp 37,933 56,900 94,833 $0 $6,896,147 50

– 100 hp 8,336 12,503 20,839 $0 $1,515,359 100

– 175 hp 16,534 24,802 41,336 $33,868,173 $44,042,196 175

– 300 hp 4,092 6,138 10,230 $10,603,849 $11,214,209 300

– 500 hp 2,428 3,642 6,070 $8,433,236 $6,956,217 500

– 600 hp 0 2,107 2,107 $ 2,543,944 $1 ,177,047 600

–750 hp 0 363 363 $ 515,944 $2 20,122 >750 hp 0 4,677 4,677 $8 ,638,687 $3 ,179,475 Total Electric Power Generation ( 2211 ) 69,323 111,132 180,455 $ 64,603,403 $ 75,200,772 **Natural Gas Transmission (48621)** 25

– 50 hp 1 27 28 $0 $2,036 50

– 100 hp 67 1,273 1,340 $0 $97,443 100

– 175 hp 147 2,799 2,946 $301,721 $579,809 175

– 300 hp 248 4,716 4,964 $643,157 $996,032 300

– 500 hp 155 2,952 3,107 $539,617 $642,799 500

– 600 hp 0 1,595 1,595 $1 ,925,560 $ 890,929 600

–750 hp 0 668 668 $9 49,443 $ 405,408 >750 hp 0 5,871 5,871 $1 0,843,377 $ 3,990,913 Total Natural Gas Transmission (48621) 619 19,899 20,519 $1 5,202,876 $ 7,605,369 **Crude Petroleum & NG Production (211111)** 25

– 50 hp 5,337 8,006 13,343 $0 $970,288 50

– 100 hp 917 1,376 2,293 $0 $166,744 100

– 175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531 (continued)4-29 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP**  **, by Number of Engines**  **a (continued)**  **Number of Engines Total (Major + Area)**  **NAICS Major**  **Area Total**  **Capital Cost Annual Cost**  175

– 300 hp 0 1 1 $1,037 $1,096 300

– 500 hp 3 5 8 $10,424 $8,598 500

– 600 hp 0 3 3 $3 ,102 $1 ,435 600

–750 hp 0 0 0 $0 $0 >750 hp 0 37 37 $ 68,337 $ 25,151 Total Crude Petroleum & NG Production (211111) 8,479 12,758 21,237 $ 4,632,675 $ 7,089,844 **Natural Gas Liquid Producers (211112)** 25

– 50 hp 5,337 8,006 13,343 $0 $970,288 50

– 100 hp 917 1,376 2,293 $0 $166,744 100

– 175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531 175

– 300 hp 0 1 1 $1,037 $1,096 300

– 500 hp 3 5 8 $10,424 $8,598 500

– 600 hp 0 3 3 $3 ,102 $1 ,435 600

–750 hp 0 0 0 $0 $0 >750 hp 0 37 37 $ 68,337 $ 25,151 Total Natural Gas Liquid Producers (211112) 8,479 12,758 21,237 $ 4,632,675 $7, 089,844 **National Security (92811)** 25

– 50 hp 4,215 6,322 10,537 $0 $766,239 50

– 100 hp 926 1,389 2,315 $0 $168,373 100

– 175 hp 1,837 2,756 4,593 $3,763,130 $4,893,577 175

– 300 hp 455 682 1,137 $1,178,205 $1,246,023 300

– 500 hp 270 404 674 $937,026 $772,913 500

– 600 hp 0 234 234 $2 82,660 $1 30,783 (continued)4-30 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Number of Engines a**  **(continued) Number of Engines**  **Total (Major + Area) NAICS**  **Major Area**  **Total Capital Cost**  **Annual Cost** 600

–750 hp 0 40 40 $5 7,279 $ 24,458 >750 hp 0 520 520 $9 59.854 $ 353,275 Total Natural Gas Liquid Producers (211112) 7,702 12,347 20,050 $ 7,178,156 $ 8,355,641 **Hydro Power Units (335312)** 25

– 50 hp 312 468 780 $0 $56,721 50

– 100 hp 35 53 88 $0 $6,399 100

– 175 hp 0 0 0 $0 $0 175

– 300 hp 0 0 0 $0 $0 300

– 500 hp 0 0 0 $0 $0 500

– 600 hp 0 0 0 $0 $0 600

–750 hp 0 0 0 $0 $0 >750 hp 0 0 0 $0 $0 Total Hydro Pow er Units (335312) 347 521 868 $0 $63,120 **Irrigation Sets (335312)** 25

– 50 hp 453 8,599 9,052 $0 $658,251 50

– 100 hp 905 17,199 18,104 $0 $1,316,502 100

– 175 hp 597 11,338 11,935 $1,222,348 $2,348,954 175

– 300 hp 308 5,856 6,164 $798,634 $1,236,813 300

– 500 hp 289 5,492 5,781 $1,004,068 $1,196,060 500

– 600 hp 0 2,310 2,310 $2 ,789,064 $1 ,290,460 600

–750 hp 0 0 0 $0 $0 >750 hp 0 269 269 $ 496,827 $ 182857 Total Irrigation Sets (335312) 2,552 51,063 53,615 $ 6,310,940 $ 8,229,896 (continued)4-31 **Table 4 -**  **5 .**  **Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP ,**  **by Number of Engines a**  **(continued) Number of Engines**  **Total (Major + Area) NAICS**  **Major Area**  **Total Capital Cost**  **Annual Cost Welders (333992)**  25

– 50 hp 2,254 3,381 5,635 $0 $409,771 50

– 100 hp 2,852 4,278 7,130 $0 $518,485 100

– 175 hp 121 181 302 $247,440 $321,771 175

– 300 hp 0 0 0 $0 $0 300

– 500 hp 0 0 0 $0 $0 500

– 600 hp 0 0 0 $0 $0 600

–750 hp 0 0 0 $0 $0 >750 hp 0 0 0 $0 $0 Total Welders (333992) 5,227 7,840 13,067 $247,440 $1,250,027 **Total** 102,729 228,319 331,047 $382,802,298 $253,374,939 1 Costs are presented in 2009 dollars.**4.4.5 Caveats and Uncerta**  **i nties in the Cost Estimates** 

* Current knowledge about NOx control techniques and costs is applied in this study . Advances such as alternative catal ys t formulations may occur between now and when sources comply with this rulemaking that may lower costs. Scale economies can also lower per unit p roduction costs as the market for these NOx control techniques expands. * The alternative control techniques and corresponding emission reductions and costs may not appl y to every

unit within the source category . Many factors influence the performance and cost of an y control technique. Because control technology

references t ypically evaluate average retrofit situations, costs may be underestimated for the fraction of the source population with difficult to retrofit conditions. Difficult to retrofit cond itions may be less of an issue for RI CEs than for other point sources, however. * NOx control efficiency and cost estimates associated with source category - control strategy combinations are represented as point estimates. In practice, control e ffectiveness and costs will vary by engine .4 - 33

**4.5 Baseline**  **Emissions and Emission Reductions** The baseline emissions, emissions factors and emissions reductions associated with the proposed reconsideration rule are provided in the tables below. Baseline emissions are estimated for 2013 using the emissions dataset generated for the final SI RICE rule in 2010. The baseline emissions thus assume the final SIRICE rule has not been implemented. Emissions are in tons per y ear. **Table 4 -**  **6 .**  **Summary o f Major Source and Area Source Baseline**  **Emissions for the SI** 

**RICE NESHAP in**  **2013 Baseline**  **Emissions (TPY)**  **Size Range (HP) HAP**  **CO NOx**  **VOC Major Sources**  25

– 50 hp 1, 107 28,557 41,751 5 , 696 50

– 100 hp 593 15,296 22,363 3 , 0 5 1 100

– 175 hp 1,721 44,399 64,913 8 , 855 175

– 300 hp 641 16,530 24,168 3 , 297 300

– 500 hp 666 17,171 25,105 3 , 4 2 5 500

– 600 hp 0 0 0 0 600

–750 hp 0 0 0 0 >750 hp 0 0 0 0 **Total 4**  **,728 121,953**  **178,301 24**  **, 3**  **2 3**  **Area Sources** 25

– 50 hp 1 ,8 1 8 46,898 68,566 9 , 3 54 50

– 100 hp 1 , 564 40,344 58,985 8 , 0 4 7 100

– 175 hp 3 , 529 91,013 133,065 1 8 , 1 53 175

– 300 hp 2 , 184 56,331 82,359 1 1 , 2 3 5 300

– 500 hp 2 , 643 68,178 99,679 1 3 , 59 8 500

– 600 hp 1 ,8 30 47,273 69,094 9 , 415 600

–750 hp 383 9,876 14,438 1 , 969 >750 hp 6 ,0 4 1 155,890 227,890 31 , 076 **Total 1**  **9 ,**  **993 515,803**  **754,077 1**  **02,846 Major + Area**  **Total 24,72**  **2 637,756**  **932,37 7**  **127,1 69** 4 - 34

**Table 4 -**  **7 .**  **Emissions Factors Engine**  **HAP**

**(lb/hp -**  **hr) CO** 

**(lb/hp -**  **hr) NOx** 

**(lb/hp -**  **hr) V**  **O C** 

**(lb/hp -**  **hr) Form**  **aldehyde**

**(lb/hp -**  **hr)** 2SLB 5.96  10 - 4 1.06  10 - 2 4.18  10 - 2 3.07  10 - 3 4 . 29  10 - 4 4SLB 5 . 41  10 - 4 3.92  10 - 3 1.15  10 - 2 2. 78  10 - 3 3 . 96  10 - 4 4SRB 2 . 43  10 - 4 1.93  10 - 2 1.47  10 - 2 1.25  10 - 3 1 .7 5  10 - 4 **Table 4 -**  **8 .**  **Summary of Major Source and Area Source Emissions Reductions for the SI**

**RICE NESHAP in 2013**  **Emission Reductions (TPY) Size**  **Range (HP) HAP**  **CO NOx**  **VOC Major Sources**  25

– 50 hp 0 0 0 0 50

– 100 hp 0 0 0 0 100

– 175 hp 744 7,124 0 3 , 8 26 175

– 300 hp 277 2,653 0 1 , 424 300

– 500 hp 288 2,755 0 1,480 500

– 600 hp N/A N/A N/A 0 600

–750 hp N/A N/A N/A 0 >750 hp N/A N/A N/A 0 **Total 1**  **, 3**  **0 8**  **1 2**  **, 532**  **0 6**  **, 730**  **Area Sources** 25

– 50 hp 0 0 0 0 50

– 100 hp 0 0 0 0 100

– 175 hp 0 0 0 0 175

– 300 hp 0 0 0 0 300

– 500 hp 0 0 0 0 500

– 600 hp 1 01 2, 070 2 , , 0 63 517 600

–750 hp 22 453 45 2 113 >750 hp 347 7 , 15 6 7 , 13 3 1 , 787 **Total 470**  **9 ,**  **679 9**  **, 64**  **8 2**  **, 41**  **8 Major + Area**  **Total 1,77**  **8 22**  **,2 1**  **1 9**  **, 64**  **8 9**  **,14 7** 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 sufficient details to develop a market model; the data that are available have little or no sector/firm detail and are reported at the national level. In addition, some sectors have unique market characteristics th at make developing partial equilibrium models difficult. Given these constraints, we used the direct compliance costs as a measure of total social costs. In addition, we also provide a qualitative anal ys is of the proposed reconsidered rule’s impact on stak eholder decisions, a qualitative discussion on if unfunded mandates occur as a result of this proposed reconsidered rule, and the potential distribution of social costs between consumers and producers. **5.1 Compliance Costs of the**  **Proposed Reconsidered Rule**  E PA’s engineering cost anal ys is estimates the total annualized cost s of the proposed reconsidered rule are $ 115 million (in 20 10 dollars) ( EC/R , 201 2 ) . T he majority

of the costs are incurred b y the electric power sector ( 65 %). The remaining industries each account for less than 8 % of the total annualized cost. The industrial classification for each engine is taken from the Power Sy stems Research (PSR) database, which is the major source of data for the engines affected b y th is rule. The PSR database used as a basis for the anal ys es in this RIA contains information on both mobile and stationary engines, among other data, and does so not only for the U.S. but worldwide. PSR has collected such data for more than 30 y ears. The Office of Transportation and Air Quality (OTAQ) uses this database frequentl y in the development of their mobile source rules. The annualized compliance costs per engine vary by the engine size . For 500 hp engines or less, the annualized per - engine costs are below $ 371 per engine. Per - engine annualized compliance costs for higher horsepower (hp) engines range up to $ 2,800 . The proposed reconsidered rule will affect approximately 331,000 existing stationary SI engines. As shown in Figure 5 - 1 , most of the a ffected engines fall within the 25 to 50 hp category ( 45 %). The next highest categories are 100 to 175 hp ( 22 %) and 50 to 100 hp ( 16 %).5 - 2

**Figure 5 -**  **1 .**  **Distribution of Engine Population by Horsepower Group** To assess the size of the compliance relative to the value of the goods and services for industries using affected engines, we collected C ensus data for selected industries. At the industry level, the annualized costs represent a very small fraction of revenue (less than 1 % ) , for all affected industri es. Results for affected industries can be found in Table 5 - 1 . These industry level cost - to - sales ratios can be interpreted as an average impact on potentially affected firms in these industries. Based on the cost - to - sales ratios, we can conclude that the annualized cost of this rule should be no higher than 1% of the sales on average for a firm in each of these industries , excluding natural gas transmission and natural gas liquid producers, which face slightly higher costs to sales ratios . 45%

16% 22%

7% 5% 2% 0% 3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

25 - 50 hp 50 - 100 hp 100 - 175 hp 175 - 300 hp 300 - 500 hp 500 - 600 hp 600 - 750 hp >7 50 hp5 - 3

**5.2 Social Cost**  **Estimate** As shown in Table 5 - 1 , the compliance costs are only a small fraction of the affected product value; this suggests that shift of the supply curve may

also be small and result in small changes in market prices and consumption. EPA believes the national annualized compliance cost estimates provide a reasonable approximation of the social cost of this proposed reconsidered rule. EPA believes this approximation is better for industries whose markets are well characterized as perf ectl y competitive. This approximation is less well understood for industries where the characterization of markets is not alway s perfectl y competitive such as electric power generation whose legal incidence of this rule is approximately 65 percent of the annualized compliance cost. However, given the data limitation noted earlier, EPA believes the accounting for compliance cost is a reasonable approximation to inform policy discussion in this rulemaking. To shed more light on this issue, EPA ran h ypothe tical anal yses and the results are in Tables 5 - 2 and 5 - 3 later in this RIA . **5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis**  Markets are composed of people as consumers and producers trying to do the best they can given their economic circumstances. One way economists illustrate behavioral responses to pollution control costs is by using market supply

and demand diagrams. The market suppl y curve describes how much of a good or service firms are willing and able to sell to people at a **Table 5 -**  **1. Selected Industry**  **- Level Annualized Compliance Costs as a Fract**  **ion of Total**

**Industry Revenue: 200**  **9 Total**  **Annualized Costs**  **Sales, Shipments, Receipt,**

**or Revenue ($Billion) Industry**  **(NAICS) Industry Nam**  **e ($ m** **illion) a**  **($2007) ($2009)**  **Cost -**  **to**   ** Sales Ratio** 2211 Electric Power Generation $1 28 . 4 $440.4 $453.7 0.004 % 48621 Natural Gas Transmission $6 8 . 9 $16.4 $16.9 0.41 % 211111 Crude Petroleum & NG Production $7.4 $214.2 $220.5 0.001 % 211112 Natural Gas Liquid Producers $7.4 $42.4 $43.6 0.005 % 92811 National Security $14. 3 #N/A #N/A #N/A 333992 Welders $1. 3 $5.2 $5. 5 0.0 2 5% 111 and 112 Agriculture using irrigation systems a $2 5 . 7 $27.9 $28.8 0.09%5 - 4 a Irrigation engine costs assumed to be passed on to agricultural sectors that use irrigation systems. N/A: receipts are Not Available for National Security So urce 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>; (July 7th , 2010). U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). 2009. “2008 Farm and Ranch Irrigation Survey.” Washington, DC: USDA -NASS. Costs from Existing SI RICE NESHAP Impacts received from EPA 1/26/12 particular price; we often draw this curve as upward sloping because some production resources are fixed. As a result, the cost of producing an additional unit ty picall y rises as more units are made. The market demand curve describes how much of a good or service consumers are willing and able to bu y at some price. Holding other factors constant, the quantity demand is assumed to fall when prices rise. In a perfectly competitive market, equilibrium price (P 0 ) and quantity (Q 0 ) is determined b y 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 mode l makes 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 - 5 consumer surplus =

– [fghd + dhc] producer surplus = [fghd

– aehb]

– bdc total surplus = consumer surplus + producer surplus =

– [aehb + dhc + bdc] **Figure 5 -**  **2 .**  **Market Demand and Supply Model: With and Without Regulation** The size of these changes depends on two factors: the size of the unit cost increase (supply shift) and differences in how each side of the m arket (suppl y and demand) responds to changes in price. Economists measure responses using the concept of price elasticity , which represents the percentage change in quantit y divided by the percentage change in price. This dependence has been expressed in the following formula: 5



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

5 For examples of similar mathematical model s in the public finance literature, see Nicholson (1998) , pages 444

–447, or Fullerton and Metcalf (2002) .5 - 6  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 elasticiti es 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 existing literature. For the short - run demand of ene rgy 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 ( U.S. EPA, 2004 ). As a result, a 1% increase in the prices of agriculture products would lead to a 0.2% decrease in demand for those products, while a 1% increase in construction prices would lead to approximately

a 1% decrease in demand for construction. Given these demand elasticity scenarios (shaded in gray), approximately a 1% increase unit costs would result in a price incre ase of 0.1 to 1% (Table 5 - 2). As a result, 10 to 100% of the unit cost increase could be passed on to consumers in the form of higher goods/services prices. This price increase would correspond to a 0.1 to 0.8% decline in consumption in these markets (Tabl e 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 and the industry

is also among the last major regulated energy industries in the United States (EIA, 20 1 0 ), the competitive model is not necessaril y applicable for this industry .5 - 7

**Table 5 -**  **3. Hypothetical Consumption Decreases for a 1% Increase in Unit Costs**  **Market Demand Elasticity**  **Market Supply Elasticity** 

**0.1 0.3**  **0.5 0.7**  **1 1.5**  **3** −0.1

− **0.1%** −0.1% − 0.1% − 0.1% − 0.1% − 0.1% − 0.1% −0.3 −0.1% **− 0.2%**  − 0.2% − 0.2% − 0.2% − 0.3% − 0.3% −0.5 −0.1% − 0.2% **− 0.3%**  − 0.3% − 0.3% − 0.4% − 0.4% −0.7 −0.1% − 0.2% − 0.3% **− 0.4%**  − 0.4% − 0.5% − 0.6% −1.0 −0.1% − 0.2% − 0.3% − 0.4% **− 0.5%**  − 0.6% − 0.8% −1.5 −0.1% − 0.3% − 0.4% − 0.5% − 0.6% **− 0.8%**  − 1.0% −3.0 −0.1% − 0.3% − 0.4% − 0.6% − 0.8% − 1.0% **− 1.5%**  Although the 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 - 3 for the status of restructuring b y state), 6 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 additional re gulatory 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 produ cer surplus, and these values can be determined using the market suppl y and demand model (Figure 5 - 2 ). 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 change ( p – t ) is negative. However, these losses are mitigated because market prices tend to rise.

6 http://tonto.eia.doe.gov/energy_in_brief/print_pages/electricity.pdf .5 - 8

**Figure 5 -**  **3 .**  **Electricity Restructuring by State** Source. U.S. Energy Information Administration. 20 10b . <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 agencies will prepare and submit to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, a Statement of Energy Effects for certain actions identified as “ significant energy

actions. ” Section 4(b) of Executive Order 1321 1 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 propo sed rulemaking, and notices of proposed rulemaking: (1) (i) that is a significant regulatory action under Executive Order 12866 or any successor order, and (ii) is likely

to have a significant adverse effect on the supply , distribution, or use of energy ;5 - 9

o r (2) that is designated by the Administrator of the Office of Information and Regulatory Affairs as a significant energy

action. This rule is not a significant energy action as designated by

the Administrator of the Office of Inf

ormation and Regulatory

Af fairs 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 prices, the analy sis in Table 5 - 4 suggests at the industry level, the annualized costs represent a very small fraction of revenue (all industries are impacted under 1% ). As a result, we can conclude supply and price impacts should be small. To enhance understanding r egarding the regulation’s influence on energy consumption, we examined publicly

available data describing energy consumption for the electric power sector that will be affected b y this rule. The Annual Energy Outlook 201 1 (EIA, 20 11 ) provides energy consumption data. As shown in Table 5 - 4, this industry account for less than 0. 3 % of the U.S. total liquid fuels and less than 8 . 0 % of natural gas. As a result, an y energy consumption changes attributable to the regulatory program should n ot significantl y influence the supply , distribution, or use of energy . **Table 5 -**  **4. U.S. Electric Power**  **a Sector Energy Consumption (Quadrillion BTUs): 2013**  **Quantity Share of Total Energy Use**  Distillate fuel oil 0.09 0.1% Residual fuel oil 0.22 0.2% Liquid fuels subtotal 0.31 0.3% Natural gas 7.63 7.9% Steam coal 17.37 18.0% Nuclear power 8.50 8.8% Renewable energy b 4.63 4.8% Electricity Imports 0.12 0.1% Total Electric Power Energy Consumption c 38.77 40.1% Delivered Energy Use 70.56 73.2% Total Energy Use 96.66 100.0%

a Includes consumption of energy by electricity - only and 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, wood and wood waste, biogenic municipal solid waste, other biomass, petroleum coke, wind, photovoltaic and solar thermal sources. Excludes net electricity imports.5 - 1 0 c Includes non - biogenic munici pal waste not included above. Source: U.S. Energy Information Administration. 20 11 a . Supplemental Tables to the Annual Energy Outlook 20 1 1 . Table 2 . Available at: < http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.htm l > . **5.5 Unfunded Mandates**  The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the rule and any

disproportionate budgetary effects. Our estimates of the future compliance costs of the proposed rule are discussed previously in Section 4 of this RIA. We do not believe that there will be any disproportionate budgetary effects of the proposed rule on any

particular areas of the country , State or local g overnments, ty pes of communities (e.g., urban, rural), or particular industry segments. **5.5. 1**  **Future and Disproportionate Costs** The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the ru le and any

disproportionate budgetary effects. Our estimates of the future compliance costs of the proposed rule are discussed previously in Chapter 4 of this RIA. We do not believe that there will be any disproportionate budgetary effects of the proposed rule on any

particular areas of the country , State or local governments, ty pes of communities (e.g., urban, rural), or particular industry segments. **5.5. 2**  **Effects on the National Economy** The UMRA requires that we estimate the effect of the proposed rule o n 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 estim ates 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 the proposed rule on most of the cat egories mentioned above, and these estimates are presented earlier in this RIA chapter. In addition, we have determined that the proposed rule contains no regulatory

requirements that might significantly or uniquely

affect small governments. Therefore, tod ay ’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 by5 - 11

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 SIRICE 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 emis sions from existing stationary S I 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 reconsideration rule , EPA has anal yz ed the impacts of this rulemaking on employ ment , which are presented in this section . While a standalone anal ysis of employ ment impacts is not included in a standard cost - benefit an al ys is, such an analy sis is of particular concern in the current economic climate of sustained high unemplo ym ent. Executive Order 13563, states, “Our regulatory s ys tem must protect public health, welfare, safet y, and our environment while promoting economic growth, innovation, 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 demand and employment impacts. This 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 ins tallation, operating and maintenance of control devices. EPA estimates that about 200 full - time equivalents (FTE) will be created or supported in the short - term and about 400 FTE s will be created or supported annuall y on a permanent basis. EPA also pr ovides 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 overall employ ment effect. W e have not quantified the rule’s net effects on the overall labor market , or the potential changes to workers’ incomes. EPA continues to explore the relevant theoretical and empirical5 - 12

literature and to seek public comments in order to ensure that such est imates 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 refl ected in an increase in the cost of production. 7 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 regulation 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 emplo ym ent due to the pot ential 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 unempl oy 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 information such as monitoring, reco rdkeeping, 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 previously in recent Regulatory

Impact Analy ses. 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 Requirements** 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 when it becomes effective, while closure of plants that choose not to comply is assumed to occur after the compliance date . Wi th 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 reve nue and employ ment in the environmental technology industry . While these increases represent gains for that industry , they 7 It should be noted that if more labor must be used to produce a given amount of output, then this implies a decrease in labor productivity. A decrease in labor productivity will cause a short - run aggregate supply curve to shift to the left, and businesses will produce less, all other things being equal.5 - 13

are costs to the regulated industries required to install the equipment. As with any pool of labor, the gross size of the labor pool does not reflect the net impact on overall 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 m aintain the pollution control equipment

– much like they may hire workers to produce more output. Of course, these firms may

also reassign 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.” 8 Once the equipment is installed, regulated firms may hire workers to operate and maintain the pollution control equipment

– much like they may hire workers to produce more output. The focus of this part of the 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 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, annua l labor requirements b y estimating hours of labor required and converting this number to full - time equivalents (FTEs) b y dividing b y 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 specific number of people involved or whether new jobs are created for new emplo ye es. The results of this employment estimate are presented in Table 5 - 5 for the proposed NESHAP. The tables breaks down the installation, operation, and maintenanc e 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 esti mated for the entire rule rather than b y

8 Environmental protection, the economy, and jobs: National and regional analyses , Roger H. Bezdek, Robert M. Wendling and Paula DiP erna, Journal of Environmental Management Volume 86, Issue 1 **,** January 2008, Pages 63 - 79.5 - 14

anticipated control requirements; the reporting and recordkeeping estimates are consistent with estimates EPA submitted as part of its Information Collection Request (I CR) that is in the Supporting Statement for th e proposed reconsideration rule. The up - front labor requirement is estimated at 200 FTEs for the proposed NESHAP. These up - front FTE labor requirements can be viewed as short - term labor requirements required for affected entities to comply with the new regulation. Ongoing requirements are estimated at about 400 FTEs for the proposed NESHAP. These ongoing FTE labor requirements can be viewed as sustained labor requirements required for affected entities to continuously comply with the new regulation. All of this data is found in the cost memorandum for this proposed reconsidered rule, and can be found in the docket for the rulemaking. Itis important to recognize that these seemingl y precise estimates are not to be assumed to be exact measures of the employ ment impacts of this rulemaking. They represent a rough approximation of the small positive impacts that this rule may have on employment.5 - 15

**Table 5 -**  **5. Labor -**  **based Employment Estimates for Reporting and R ecordkeeping and**  **Installing, Operating, and Maintaining Control Equipment Requirements for Proposed Reconsideration SI RICE NESHAP** 

**Source Emission**  **Control Measure**  **Projected No. of**

**Affected Units Per**  **- Unit** 

**On e**  **- Time**  **Labor Estimate**  **(Hours) Total One**  ****

**Time Labor**  **Estimate (Hours)**  **Per -**  **Unit**

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

**Annual Labor**  **Estimate (Hours)**  **On e**  **- Time Full**  **- Time** 

**Equivalent Annual** 

**Full**   ** Tim** **e Equival**  **ent Major Sources**  SI RICE <100 HP N/A 70,798 N/A N/A 1 70,798 N/A 34

- O&M/Recordkeeping 2SLB RICE 100 - 500 HP N/A 7,398 N/A N/A N/A 92,480 N/A 34 - O&M/Recordkeeping 1

- Testing 8

- Reporting 3.5 Emergency 4SRB SI RICE 100 - 500 HP N/A 1,597 N/A N/A 1 1,597 N/A 0.77 Non - Emergency 4SRB SI RICE 100 - 500 HP N/A 12,740 N/A N/A N/A 146,515 N/A 70 - Testing 8

- Reporting 3.5 4SLB SI RICE 100 - 500 HP Oxidation Catalyst 14,257 21 300,255 15 163,956 144 34 - Testing 8

- Reporting 3.5 **Area Sources** All SI RICE N/A 228,318 N/A N/A 1 228,318 N/A 110

- O&M/Recordkeeping Non - Emergency 4SLB SI RICE >500 HP in Populated Areas Oxidation Catalyst 768 37 28,117 15 15,734 14 7.56

- Testing 2

- Reporting 3.5 Non - Emergency 4SRB SI RICE >500 HP in Populated Areas NSCR 578 86 49,918 33 22,236 24 10.69

- Testing 2

- Reporting 3.5 **Total** 144 378,290 113 741,633 182 357

Note : Full - time equivalents (FTE) are estimated by first multiplying the projected number of affected units by the per unit labor requirements and then dividing by 2,080 (40 hours multiplied by 52 w eeks). Totals may not sum due to independent rounding. HP = ho rsepower N/A = Not Applicable. O&M = Operating and Maintenance5 - 16 **5.7.2 Employment Impacts within the Regulated Industry**  In recent RIAs we have applied estimates from a study by Morgenstern , Pizer and Shih (2002) 1 to derive the employ ment effects of new regulation s within the regulated industry . (See, for example, the Regulatory Impact Anal ys es for the recent final MATS and final CSAPR regulations). Determining the direction of emplo ym ent effects in the regulated industry

is also challenging due to competing effects. Complying with the new or more stringent regulation requires additional inputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms in their production processes. Morgenstern, et al. (2002) demonstrate that environmental regulations can be understood as requiring regulated firms to add a new output (environmental quality) to their product m ixes . Although legally compelled to satisfy

this new demand, regulated firms have to finance this additional production with the proceeds of sales of their other (market) products. Satisfyingthis new demand requires additional inputs, including labor, and may alter the relative proportions of labor and capital used b y 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 fo llowing three subcomponents:

 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 thi s 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, including 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.

1 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 2002. Jobs versus the Environment: An Industry - Le vel Perspective. ‖ Journal of Environmental Economics and Management 43(3):412 - 436.5 - 17  The Factor- Shift Effect : Regulated firms’ produ ction technologies may be more or less labor intensive after complying with the regulation (i.e., more/less labor is required relative to capital per dollar of output). “ E nvironmental activities may be more labor intensive than conventional production,” me aning that “the amount of labor per dollar of output will rise.” However, activities may , instead, be less labor intensive because “cleaner operations could involve automation and less employ ment, for example.” (p. 416) The demand effect is expected to hav e an 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 the se 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 years 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 sectors. More specifically , their results show that, on average across the industries studied, each additional $1 million (in 1987$) spent on pollution abatement results in a (statistically

insignificant) net increase of 1.55 (+/ - 2.24) jobs. As a re sult, the authors 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 th at increased 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 re lationship 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 ad dition, there 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 impac ts 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 - 18

proposed rule and the four manufacturing industries studied by Morgenstern et al. For these reasons, we conclude there are too man y uncertainti es 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 include small businesses, small governmental jurisdictions , and small not - for - profit enterprises. After considering the economic impact of the proposed rule on small entities, the screening anal ys is indicate s that this proposed rule will not have a significant economic impact on a substantial number of small enti ties (or “SI SNOSE”) . Under the analy ses EPA considered, sales and revenue tests for establishments owned by model small entities are less than 1 % except electric power generation (NAICS 2211 with receipts less than $100,000 per year) and crop and animal pr oduction (NAICS 111 and 112 with receipts less than $25,000 per year) . The se findings are similar to those for the final SIRICE rule promulgated in August 2010, though the impacts are lower due to the reduction in the cost estimates for these industries. **6.1 Small Entity**  **Data Set** The industry

sectors covered b y the proposed rule were identified during the development of the cost anal ys is ( EC/R, 20 1 2 ). The Statistics of United States Business ( SUSB ) provide s national information on the distribution of economic variables b y industry and ente rprise size (U.S. Census, 20 12 a, 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, man y of these entities may

not n ecessarily

be covered b y the proposed rule . SUSB also provides statistics by enterprise employ

ment and receipt size. The Census Bureau ’ s definitions used in the SUSB are as follows:

 E stablishmen t: An establishment is a single ph ys ical location where busin ess 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 owne d by the federal government (e.g., military bases), EPA assumes these entities would not be considered small. For irrigated farms, we relied on receipt data provided in the 2008 Farm and Irrigation Survey (USDA, 2009 ). 2 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, re nts, 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 multi establishment company forms one enterprise

—the enterprise employment and annual pay

roll are summed from the associated establishments. Enterpris e 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 y sis generated a set of establishment sales tests (represented as cost - to - receipt ratios) 3 for NAI CS codes associated with sectors listed in Table 6 - 1 . Although the appropriate SBA size definition should be applied at the parent company (enterprise) level, we can only compute and compare ratios for a model establishment owned by an 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 e nterprises and also allows us to consider the variation in small business definitions across affected industries. Using establishment receipts is also a conservative approach , because an establishment ’ s parent compan y (the “ enterprise ” ) may have other econ omic 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 econom ic impact measures (if applicable) would potentially include • small governments (if applicable): “revenue” test; annualized compliance cost as a percentage of annual government revenues and • small nonprofits (if applicable): “expenditure” test; annualized compliance cost as a percentage of annual operating expenses, 4 For the 1 to 20 employee category, we excluded SUSB data for enterprises with zero employees. These enterprises did not operate the entire year.6 - 3

employ ment size standards, we calculated 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. SI**  **NESHAP for Existing Stationary Reciprocating Internal Combustion**

**Engines (RICE): Affected Sectors and SBA Small Business Size Standards Industry Description**  **Corresponding NAICS**  **SBA Size Standard for**

**Businesses ( November**  **5 nd,** 

**20 10**  **) Type of**  **Sm all**  **Entity** Electric Power Generation 2211 a Business and government Natural Gas Transmission 48621 $7.0 million in annual receipts Business Crude Petroleum & NG Production 211111 500 employees Business Natural Gas Liquid Producers 211112 500 employees Business National Security 92811 NA Government Hydro Pow er Units See NAICS 2211 1,000 employees Business and government Irrigation Sets Affects NAICS 111 and 112 Generally $750,000 or less in annual receipts Business Welders Affects industries that use heavy equipment such as construction, mining, farming Varies by 6 - digit NAICS code; Business Example industry: NAICS 238 = $14 million in annual receipts a NAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm is small if, including its affiliates, it is primarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fi scal year did not exceed 4 million megawatt hours. Source: U. S. Small Business Administration (SBA). 20 10 . “Table of Small Business Size Standards Matched to North American Industry Classification Sy stem Codes.” Effective Novem ber 5 nd, 20 10 . Downloaded 2/16/12. average establishment receipts for each enterprise receipt range (Table 6 - 3). We included the utility sector in the second group, although the SBA size standard for this industry is defined i n terms of ph ys ical units (megawatt hours) versus receipts. Crop and animal production (NAICS 111 and 112) also have an SBA receipt size standard that defines a small business as receiving $750,000 or less in receipts per y ear. However, SUSB data were not available for these industries. Therefore, we conducted the sales test using the following range of establishment receipts : farms with annual receipts of $25,000 or less, farms with annual receipts of $100,000 or less, farms with annual receipts of $500,00 0 or less, and farms with annual receipts of $750,000 or less.

5 2007 Economic Census data are at http://www.ce nsus.gov/econ/census07/ .6-4 **Table 6**  **- 2.**  **Average Receipts for Affected Industry by E nterprise: 200**  **9 ($2009 Million/E**  **stablishment) 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 Source: U.S. Census Bureau. 2012a . “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. NA = Not available.6-5 **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 zO 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: Note: Industries in green were included for consistency with the analysis done for final rule . 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 output for the preceding fis cal year did not exceed 4 million megawatt hours. NA = Not available. SUSB did not report this data for disclosure or other reasons . Source: U.S. Census Bureau. 2009a . “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 200 9 .” <http://www.census.gov/csd/susb/6 - 6

Annual entity compliance costs vary depending on the size of the SI engines used at the affected establishment. Absent facility - specific information, we computed per - entit y compliance costs based for three different cases based on representative establishments

— Cases 1, 2, and 3 (see Tab le 6 - 4). Each representative establishment differs based on the size and number of SI engines being used. Compliance costs are calculated by summing the total annualized compliance costs for the relevant engine categories, dividing the sum by the total exi sting population of those engines, and multiplying the average engine cost by the number of engines assumed to be at the establishment. Since NAI CS 2211 and 48621 are fundamentally different than other industries considered in this anal ys is due to the numb er of engines affected and amount of cost incurred resulting from this proposed rule , we used different assumptions about what constitutes the representative establishment and report these assumptions separatel y.

 Case 1: The representative establishment for all industries uses three 750+ hp engines with an average compliance cost of $ 680 to $ 730 per engine, resulting in a total annualized compliance cost of approximately $ 2,040 to $ 2,200 for this representative establishment.

 Case 2: The representative e stablishment in NACIS 2211 and 48621 uses two 25 to 750+ hp engines with an average compliance cost of $ 412 per engine, resulting in a total annualized compliance cost of $ 824 for this representative establishment. For all other industries, the representat ive establishment uses two 25 to 300 hp engines with an average compliance cost of $ 24 6 per engine, resulting in a total compliance cost of $ 49 2 for this representative establishment.

 Case 3: The representative establishment for all industries uses two 50 to 100 hp engines with an average compliance cost of $ 73 per engine, resulting in a total compliance cost of $ 145 for this representative establishment. EPA believes that small entities are most likely to face costs similar to Case 2 (columns shaded in gray

in Table 6 - 4) because most of the engines to be affected b y this proposed rule 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 gure 6 - 1 and 6 - 2 which shows the distribution of engine population and compliance costs by engine size for all industries. However, it is difficu lt to make a similar claim for NAI CS 2211 and 48621 based on the existing distribution of engines in these industries. 6

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 would not be considered small.6 - 7

For the sales test, we divided the representative establishment compliance costs reported in Table 6 - 4 by

the representative establishment receipts reported in Tables 6 - 2 and 6 - 3. This is known as the cost - to - receipt (i.e., sales) ratio, or the “sales test.” The “sales test” is the impact **Table 6 -**  **4. Representative Establishment Costs**  **Used for Small Entity Analysis ($200 9**  **) Case 1**  **Case 2 Case 3**  **NAICS 2211, 48621**  **(+750 hp only)**  **All Other**

**NAICS (+750 hp**  **only) NAICS** 

**2211,48621 (25**  **- 750+**  **hp) All Other** 

**NAICS (25**  **– 300**  **hp) NAICS** 

**2211, 48621**  **(25 –**  **100 hp only)**  **All Other**

**NAICS (25**  **– 100**  **hp only)**  Total Annualized Costs ($) $ 7,710,388 $ 586,434 $ 82,806,141 $28,057, 798 $8,510,985 $6,174,805 Engine Population 10,548 863 200,974 114,517 117,040 84,913 Average Engine Cost ($/engine) $ 731 $ 680 $ 412 $24 6 $73 $73 Assumed Engines Per Establishment 3 3 2 2 2 2 Total Annualized Costs per Establishment $2 ,193 $2 ,040 $ 824 $49 2 $145 $1456 - 8

**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) Natur al Gas

Tr an smission (48621) Crude Pet roleum

& NG Product ion (211111) Natu ra l Gas

Li quid Producers (211112) National Se curity

(92811) Hydro Pow er

Un its (3 35312) Ir ri gation Se ts

(335312) Welders

(333992) >750 hp

600 - 750 hp 500 - 600 hp 300 - 500 hp 175 - 300 hp 100 - 175 hp 50 - 100 hp 25 - 50 hp6 - 9

**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 percentage of total revenues is a metric for evaluating cost increases on small entities in relation to increases on large entities. 8

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

Elec tr ic P owe r

Ge nera tion (2211) Natur al Gas

Tr an smission (48621) Crude Pet roleum

& NG Product ion (211111) Natu ra l Gas

Li quid Producers (211112) National Se curity

(92811) Hydro Pow er

Un its (3 35312) Ir ri gation Se ts

(335312) Welders

(333992) >750 hp

600 - 750 hp 500 - 600 hp 300 - 500 hp 175 - 300 hp 100 - 175 hp 50 - 100 hp 25 - 50 hp6 - 10

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

 Case 2 : NAI CS 2211 with receipts less than $100,000 per y ear and NAICS 1 11 and 112 with receipt s less than $25,000 per y ear

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

 Case 1 : NAI CS 2211 with receipts less than $ 1 00,000 per y ear In the Case 2 primary

analy sis, onl y establishments in NAI CS 2211 with recei pts less than $100,000 per ye ar (less than 5 percent of the total) , and establishments in NAI CS 111 and 112 with receipts less than $25 ,000 per ye ar (around 30 percent of the total) have cost - to - receipt ratios above 1%. However, establishments earning this level of receipts are likely to be using smaller engines than those assumed in Case 2, such as 25 to 3 00 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 proposal action to all affected small entities across all industries affected. The percentage of small entities impacted by this proposal having annualized costs greater than 1 percent of sales is less than 2 percent according to this analy sis. We thus co nclude that there is no significant economic impact on a substantial number of small entities (SI SNOSE) for this proposed rule. Although the propos ed rule would not have a significant economic impact on a substantial number of small entities, EPA nonetheless tried to reduce the impact of the rule on small entities. When developing the revised standards, EPA took special steps to ensure that the burdens imposed on small entities were minimal. EPA conducted several meetings with industry trade associations to discuss regulatory options and the corresponding burden on industry , such as recordkeeping and reporting. In addition, as mentioned earlier in this preamble, EPA proposes to reduce regulatory

requirements for a 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 the6 - 11

potential impacts of this proposed rule o n 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 b y small and large governments. However, given the uncertainty and data limitations associated with identifyingand appropriatel y classifying these entities, we computed a “ revenue ” test for a model small government, 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 b y EPA on compliance with SBREFA, 9 and is consistent with guidance published b y the US SBA’s Office of Advocacy . 10 For example, from the 200 7 Census (in 200 8 dollars ), the average revenue for small governments (counties and municipalities) with populations fewer than 10,000 is $ 4 mill ion per entity , and the average revenue for local governments with populations fewer than 50,000 is $ 9 million per entity (U.S. Census Bureau, 200 9 a; U.S. Census Bureau, 200 9 b) . F or the smallest group of local governments (<10,000 people), the co st - to - reve nue 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.e pa.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 Order 13272, May 2003 .7 - 1 **Section 7 HUMAN HEALTH BENEFIT**  **S OF EMISSIONS REDUC TIONS**  **Synopsis** Implementation of emissions controls required b y the proposed SI RICE NESHAP reconsideration is expected to reduce emissions of hazardous air pollutants (HAP) and have ancillary co - benefits that would lower ambient concentrations of NO 2 , PM 2.5 an d ozone . In this section, we quantify the monetized co - benefits for this rule associated with reducing exposure to ambient fine particulate matter (PM 2.5 ) by reducing emissions of precursors. We estimate the total monetized co - benefits to be $62 million to $ 150 million at a 3% discount rate and $ 55 million to $ 140 million at a 7% discount rate in 2013 . All estimates are in 2010$. These estimates reflect the monetized human health benefits of reducing cases of morbidity and premature mortality

among populat ions exposed to PM 2.5 reduced by this rule . These estimates reflect EPA’s most current interpretation of the scientific literature. Higher or lower estimates of benefits are possible using other assumptions; examples of this are provided in Figure 7 - 2. D ata, resource, and methodological limitations prevented EPA from monetizing the benefits from several important benefit categories, including benefits from reducing exposure to HAP, carbon monoxide, NO 2 and ozone, as well as ecos ys tem effects and visibility impairment. In addition to reducing emissions of PM precursors such as NOx , this rule would reduce 1,800 tons of HAP and 22,000 tons of carbon monoxide each year. **7.1 Calculation of**  **PM 2.5**  **- Related**  **Human Health Co**  **- Benefits**  Assuming that our basel ine does not include implementation of the 2010 final SI RICE rule, as we state earlier in this RIA, this proposed reconsideration NESHAP would reduce emissions of NO X , and VOCs. Because these emissions are precursor s to PM 2.5, reducing these emissions wo uld also reduce PM 2.5 formation, human exposure and the incidence of PM 2.5 - related health effects. Due to anal yt ical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 - related benefits or provide estimates of the health benefits associated with exposure to HAP, CO, NO 2 or ozone . Instead, we used the “benefit - per - ton” approach to estimate these benefits . The methodology employ ed in this analy sis is similar to the work described in Fann, Fulcher, and Hubbell (2009) , but represents an improvement that EPA believes would provide more reliable estimates of PM 2.5 - related health benefits for emissions reductions in specific sectors. The key assumptions are described in detail below. These PM 2.5 benefit - per - ton estimates provide the total monetized human health benefits (the sum of7 - 2

premature mortality

and premature morbidit y) of reducing one ton of PM 2.5 f rom a 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 heal th effects associated with exposure to ozone and NO 2 nor welfare effects such as ecos ys tem effects and visibility impairment that are described in section 7.2 . It is important to emphasize that the list of unquantified benefit categories is not exhaustive , nor is quantification of each effect complete.7 - 3

**Table 7 -**  **1: Human Health Effects of**  **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 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30) 

 

 Section 5.4 Infant mortality (age <1) 

 

 Section 5.4

Reduced incidence of 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 Emergency 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 Emergency room visits for cardiovascular effects (all ages) -- -- Section 5.4 Strokes and cerebrovascular disease (age 50 - 79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA2 Other respiratory effects (e.g., pulmonary function, non - asthma ER visits, non bronchitis chronic diseases, other ages and populations) -- -- PM ISA2 Reproductive and developmental effects (e.g., low birth weight, pre - term births, etc) -- -- PM ISA2,3 Cancer, mutagenicity, and genotoxicity effects -- -- PM ISA2,3 1 We assess these benefits 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 study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent ( 2006 - 2009 ) Office of Air and Radiation RIAs.

 One estimate is based on the C - R function developed from the extended 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 report ed 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 Society 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 two studies specify multi - pollutant models that control for SO 2 , among other co - pollutants.7 - 5

et al., 2008 ). 2 Within this assessment, we include the benefits estimates derived from the concentration - response function provided by each of the twelve experts to better characterize the uncertaint y in the concentration - response function for mortality and the degree of variability in the expert responses. Because the experts used these cohort studies to inform their concentration - response functions, benefits estimates using these functions generall y fall between results using these epidemiology studies (see Figure 7 - 2 ). In general, the expert elicitation results support the conclusion that the benefits of PM 2.5 control are very likely to be substantial. Readers interested in reviewing the general methodology for creating the benefit - per - ton estimates used in this analy sis should consult the draft Technical Support Document (TSD) on estimating the benefits per ton of reducing PM 2.5 and its precursors from in the “ Other Non - EGU Point” sector (U.S. EPA, 2012). 3 The primary difference between the estimates used in this anal y sis 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 sectors. In addition, the updated air qualit y modeling data reflects more rec ent emissions data (2005 rather than 2001) and has a higher spatial resolution (12km rather than 36 km grid cells). The benefits methodology , such as health endpoints assessed, risk estimates applied, and valuation techniques applied did not change. As not ed 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 geographic 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 factors for an y specific location. In this analysis, we apply the se natio nal benefit - per - ton estimate s calculated for this category for NOx and multiply them by the corresponding emission reductions . These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature m ortality because the scientific evidence is not y et sufficient to allow differentiation of effects estimates b y particle ty pe. NOx is the primary

PM 2.5 precursors affected b y this rule. Even though we assume that all fine particles have equivalent health

2 Please see the Section 5.2 of the Portland Cement RIA in Appendix 5A for more information regarding the change in the presentation of benefits estimates. 3 Stationary engines are included in the other non - EGU point source category. If the affected stat ionary 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 available information on the air quality impact on a per ton basis for these sources.7 - 6

effects, the benefit - per - ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure . The sector - specific modeling does not provide estimates of the PM 2.5 - related benefits a ssociated 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 func tions 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 the Portland Cement NESHAP RIA (U.S. EPA, 2009a), which applied the functions directly from the epidemiology

studies witho ut an adjustment for an assumed threshold. Removing the threshold assumption is a key difference between the method used in this analy sis of PM benefits and the methods used in RIAs prior to Portland Cement proposal, and we now calculate incremental benef its down to the lowest modeled PM 2.5 air quality levels. 4 Based on our review of the current body of scientific literature, EPA now estimates PM related mortalit y without applying an assumed concentration threshold. EPA’s Integrated Science Assessment f

or 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 of the concentration - response function. Consistent with this finding, we have conformed the previous threshold sensitivity anal ys is to the curr ent state of the PM science by incorporating a “Lowest Measured Level” (LML ) assessment , which is a method EPA has employed in several recent RIAs including the Cross - State Air Pollution Rule (U.S. EPA, 2011 b ). This information all ows readers to determine the portion of population exposed to annual mean PM 2.5 levels at or above the LMLof each study ; in general, our confidence in the estimated PM mortality decreases as we consider air quality levels further below the LMLin major co hort studies that estimate PM - related mortalit y. While an LMLassessment 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 imp acts using a full range of modeled air quality concentrations. Itis important to emphasize that we have high confidence in PM 2.5 - related effects down to the lowest LMLof the major cohort studies, which is 5.8 μg/m 3 . Just because we have greater confide nce in the 4 Additional updates since the Cement RIA include a revised VSL and updated baseline incid ence 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 availa

ble due to time or resource limitations. For these rules, we are unable to estimate the percentage of premature mortality associated with this specific rule’s emission reductions at each PM 2.5 level. However, we believe that it is still important to char acterize the distribution of exposure to baseline air quality levels. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionment modeling used to calculate the benefi t - per - ton estimates for this sector . It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline incidence rates population, and change in air quality . In other words, the percentage of the popu lation exposed to air pollution below the LML is not the same as the percentage of the population experiencing health impacts as a result of a specific emission reduction policy . The most important aspect, which we are unable to quantify

for rules without rule - specific air quality modeling, is the shift in exposure associated with this specific rule. Therefore, caution is warranted when interpreting the LML assessment for this rule . The results of this 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 - ana ly ses of the wage - risk literature. The $1 million value represented the lower end of the interquartile range from the Mrozek and Taylor (2002) meta - analy sis of 33 studies. The $10 million value represented the upper end of the interquartile range from th e 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 account for income grow th to 2015 of the $5.5 million value, the VSL is $ 8.0 million.7 - 8

scientific peer - review process through the Science Advisory Board (SAB) or other peer - review group. During this time, the Agency continued work to update its guidance on valuing 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). Until updated guidance is available, the Agency determined that a single, peer - reviewed estimate applied consistently best reflects the SAB - EEAC advice it has received. Therefore, the Agency has decided to apply

the VSL that was vetted and endorsed b y the SAB 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 va luation 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 signific ant progress in responding to the SAB - EEAC’s specific recommendations. In implementing these rules, emission controls may lead to reductions in ambient PM 2.5 below the National Ambient Air Quality Standards (NAAQS) for PM in some areas and assist other areas with attaining the PM NAAQS. 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 attaini ng a new air quality standard nationwide based on an array of emission control strategies for different sources. In short, NAAQS RIAs hypothesize, but do not predict, the control strategies that States may choose to enact when implementing a NAAQS. The setting of a NAAQS does not directl y result

6 In revised Economic Guidelines (U.S. EPA, 2010c ), EPA retained the VSL endorsed b y the SAB with the understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future. Therefore, this report does not represent final agency policy. 7 This value is $4.8 in 1990$. In this analysis, we a djust 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 reducti ons. 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 redu ctions for implementation rule s are from a specific class of well - ch aracterized 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 ulti mately 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 cycle 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, please 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**  **unction**

**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 c hart 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 ben efit - 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 for a specific analysis year (i.e., 2013 ), and most of the PM benefits occur within that year with two exceptions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow - up medical costs and lost wages. For premature mortality, we assume that there is a “ cessation ” lag between PM exposures and the total realization of changes in health effects. Although the structure of the lag is uncertai n, EPA follows the advice of the SAB - HES to assume a segmented lag structure characterized by 30% of mortality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 20 after the reduction in 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 analysi s year. As such, the monetized benefits using a 7% discount rate are only approximately 10% less than the monetized benefits using a 3% discount rate. **Adult 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 odeli ng, which results in slightly higher benefits 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 V OCs. **Table 7 -**  **2: General Summary of Monetized**  **PM 2.5**  **- Related Health Co**  **- Benefits Estimates** 

**for the Proposed SI RICE NESHAP**  **Reconsideration (millions of 2010$**  **)** *****

**Pollutant Emissions** 

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

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

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

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

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

**Benefits (m illions**  **of 2010$ at 7%)**  **PM 2.5**  **Precursors** NO X 9,648 $6,400 $16,000 $5,700 $14,000 $62 to $150 $55 to $140 **Total $62**  **to $150**  **$55 to**  **$140** * All estimates are for the analysis year ( 2013 ), and are rounded to two significant figures so numbers may not sum across columns. It is important to note that the monetized benefits do not include reduced health effects from direct exposure to 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 . 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 SI RICE NESHAP**  **Reconsideration*** **Avoided Prem ature Mortality**  Pope et al. 7 Laden et al. 18 **Avoided Morbidity** Chronic Bronchitis 5 Emergency Department Visits, Respiratory 5 Hospital Admissions, Respiratory 1 Hospital Admissions, Cardiovascular 3 Ac ute Bronchitis 11 Lo wer Respiratory 140 Upper Respiratory 110 Minor Restricted Activity Days 5,600 Work Loss Days 950 Asthma Exacerbation 230 Ac ute Myocardial Infarction 8 * All estimates are for the analysis year ( 2013 ) and are rounded to whole numbers with two significant figures. All fine particles are assumed to have equivalent health effects because the scientific evidence is not yet sufficient to allow differentiatio n 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 SI RICE NESHAP** 

**Reconsideration at discount rates of 3 % and 7%**  **in 2013 (in millions of**  **2010$ )** * 3% 7% **Benefit -**  **per -**  **ton Coefficients Derived from Epide**  **miology Literature** Pope et al. $62 $55 Laden et al. $150 $140 **Benefit -**  **per -**  **ton Coefficients Derived from Expert Elicitation**  Expert A $160 $150 Expert B $120 $110 Expert C $120 $110 Expert D $87 $78 Expert E $200 $180 Expert F $110 $100 Expert G $74 $66 Expert H $93 $83 Expert I $120 $110 Expert J $100 $89 Expert K $24 $21 Expert L $82 $73 * All estimates are rounded to two significant figures. The benefits estimates from the Expert Elicitation are provided as a reasonable characterization of the uncertainty in the mortality estimates associated with the 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 SI RICE NESHAP**

**Reconsideration in**  **2013** * This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on PM mortality. The results shown are not the direct results from the studies or exp ert elicitation; rather, the estimates are based in part on the concentration - response function provided in those studies.

$0 $50 $100 $150 $200 $250

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

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 Proposed SI 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 resource limitations prevented EPA from quantifying the impacts t o, or monetizing the benefits from several important benefit categories, including benefits from reducing exposure to HAP, CO, NO 2 , and ozone exposure, as well as ecos ys tem effects, and visibility impairment . This does not imply that there are no benefits associated with these emission reductions. These benefits are described qualitatively

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

d epending 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/. **Area 500 -**  **600 HP**  **21% Area 600**  **- 750**  **HP**

**5% Area >750 HP**  **74%**7 - 16

of greatest potential concern, U.S. EPA conducts the NATA. 10 The most rec ent NATA was conducted for calendar year 2005 and was released in March 2011. NATA includes four steps: 1) Compiling a national emissions inventory of air toxics emissions from outdoor sources 2) Estimating ambient and exposure concentrations of air toxic s 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 abo ut 5% of census tracts nationwide have increased cancer risks greater than 100 in a million. The average national cancer risk is about 50 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldeh yde and b enzene. 11 Secondary formation (e.g., formaldehyde forming from other emitted pollutants) was the largest contributor to cancer risks, while stationary , mobile and background sources contribute almost equal portions of the remaining cancer risk. Noncancer h ealth effects can result from chronic, 12 subchronic, 13 or acute 14 inhalation exposures to air toxics, and include neurological, cardiovascular, liver, kidney, and respiratory effects as well as effects on the immune and reproductive 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 potential for adverse noncancer respiratory health effects. Results from the 2005 NATA indicate that acrolein is the primary driver for noncancer respiratory

risk.

10 The NATA modelin g framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertainties are discussed on the 2005 NATA website. Even so, this modeling framework is very useful in identifying ai r toxic pollutants and sources of greatest concern, setting regulatory priorities, and informing the decision making process. U.S. EPA.(2011) . 2005 National - Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/ 11 Details about the overall co nfidence of certainty ranking of the individual pieces of NATA assessments including 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 s pan in humans (more than approximately 90 days to 2 years in typically used laboratory animal species). 13 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species). 14 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.7 - 17

Figure 7 - 4 and Figure depict the estimated census tract - level carcinogenic risk and noncancer respiratory

hazard from the assessment. It is important to note that 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 levels of concern. For example, acetaldeh yd e mass emissions are more than d ouble acrolein emissions on a national basis, according to EPA’s 2005 National Emissions Inventory (NE I). However, the Integrated Risk Information Sy stem (IRI S) reference concentration (RfC) for acrolein is considerabl y lower than that for acetaldeh yd e, s uggesting 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 emissions.

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

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

and time limitations under the court - ordered schedule, we were unab le 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 in HAP , EPA has quantified the benefits of potential reductions in the incid ences 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 lik ely

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 probability 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 - S AB, 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 prospective anal ys is of the benefits and costs of the Clean Air Act (U.S. EPA, 2011 a), EPA conducted a case study 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 i nventories 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 2 009, 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 suscepti ble and vulnerable populations, and improving dose - response relationships (Gwinn et al., 2011 ). In summary , monetization of the benefits of reductions in cancer incidences requires several important inputs, including central est imates 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 these rules.EPA remains committed to improving methods for estimating HAP benefits by continuing to explore additional concepts of benefits, includin g changes in the distribution of risk. Although numerous HAPs may be emitted from SI RICE, a few HAPs account for over 90% of the total mass of HAPs emissions emitted. These HAPs are formaldehyde (72%), acetaldehyde (8%), acrolein (7%), methanol (3%), and benzene (3%). Although we do not have estimates of emission reductions for each HAP, this rule is anticipated to reduce 1,800 tons of HAPs each year. Below we describe the health effects associated with the top 5 HAPs by mass emitted from SI RICE.7 - 20

Formaldehyde Since 1987, EPA has classified 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 research conducted b y the National Cancer Institute (NCI) which found an increased risk of nasophary ngeal cancer and ly mphohematopoietic malignancies such as leukemi a among workers exposed to formaldeh yde. 17 , 18 Inan analy sis of the l ymphohematopoietic cancer mortalit 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 re cent NIOSH stud y of garment workers also found increased risk of death due to leukemia among workers exposed to formaldehyde. 20 Extended follow - up of a cohort of British chemical workers did not find evidence of an increase in nasophary

ngeal or l ymphohemat opoietic 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 Institute of Toxicology

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

16 U.S. EPA. 1987. Assessment of Health Risks to Garme nt Workers and Certain Home Residents from Exposure to Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA - HQ - OAR - 2010 - 0162 . 17 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615 - 1623. Docket EPA - HQ - OAR - 2010 - 0162 . 18 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from s olid 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 worke rs exposed to formaldehyde: an update. Occup. Environ. Med. 61: 193 - 200. Docket EPA - HQ - OAR - 2010 - 0162 . 21 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow - up of a cohort of British chemical workers exposed to formaldehyde. J National Cancer I nst. 95:1608 - 1615. Docket EPA - HQ - OAR - 2010 - 0162 . 22 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller. 2003. Biologically 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 Preston, and FJ Miller. 2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose - response predictions derived from biologically - mo tivated com putational 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 an d 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 pu

blished by

EPA indicates that when two - stage modeling assumptions are varied, resulting dose - response estimates can vary by several orders of magnitude. 25 , 26 , 27 , 28 These findings are not supportive of interpreting the CIIT model results as providing a conserv ative (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 mo del - based inference in the published CI IT stud y that formaldehyde’s direct mutagenic action is not relevant to the compound’s tumorigenicit y was found not to hold under variations of modeling assumptions. 30 Based on the developments of the last decade, i n 2 004, the working group of the IARC concluded that formaldehyde is carcinogenic to humans (Group 1), on the basis of sufficient evidence in humans and sufficient evidence in experimental animals - a higher classification than previous IARC evaluations. Aft er 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 nasophary ngeal cancers; the epidemiologic evidence on leukemia was char acterized as “strong.” 31 Formaldeh yd e exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of the ey es), nose and throat. Effects from repeated

24 Chemical Industry Institute of Toxicology (CIIT).1999. Formaldehyde: Hazard characterization and dose - response assessment for carcinogenicity by the route of inhalation. CIIT, September 28, 1999. Research Triangle Park, NC. Docket EPA - HQ - OAR - 2010 - 0162 . 25 U.S. EPA. Analysis of the Sensitivity and Uncertainty in 2 - Stage Clonal Growth Models for Formaldehyde with Relevance to Other Biologically - Based Dose Response (BBDR) Models. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R - 08/103, 2008. D ocket 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; Fox, 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 biologica lly 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 carcinog enicity in the rat: A limited sensitivity analysis

– I. Risk Anal, 27: 1237

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

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

inflammation

– including eosinophil infiltration into the 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 Formaldeh yde

– Inhalation Assessment through the Integrated Risk Information Sy stem (IRI S) program. This draft IRIS assessment was released in June 2010 for public review and comment and external 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 draft assessment in response to this review. Acetaldehyde Acetaldehyde is classified in EPA’s IRIS database as a probable human carcinogen, based on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous routes. 34 Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. Department of Health and Human Services (DHHS) in the 11 th Report on Carcinogens and is classified as possibl y carcinogenic to humans (Group 2B) by the IARC. 35 , 36 The primary noncancer effects of exposure to ac etaldehyde vapors include irritation of the eyes, skin, and respiratory tract. 37

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

Acrolein EPA determined in 2003 that the human carcinogenic potential of acrolein could not be determined because the available data were inadequate. No information was av ailable 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

acri d 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 controlled 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 IRI S Human Health Assessment for acrolein. 41 Evidence available from studies in humans indicate that levels as low as 0.09 ppm (0.21 mg/m 3 ) for five minutes may elicit subjective complaints of eye irritation with increasing concentrations leading to more extensive eye, 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 recent study, the acute r espiratory

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 Ag ency (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. EPA/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 Environmental 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. 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. 44 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrol ein. 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 simi lar 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

irritants such as acrolein. Benzene The EPA’s IRIS database lists benzene as a known human carcinogen (causing leukemia) by all routes of exposure, and concludes that exposure is associated with additional health effects, including genetic changes in both humans and animals and incre ased 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 exposure and chronic non - ly mp hocy 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 including blood disorders, su ch as preleukemia and aplastic anemia, have also been associated with long - term exposure to benzene. 51 , 52

45 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immediate sens ory nerve - mediated respiratory responses to irritants in healthy and allergic airway - diseased mice. J Appl Physiol 94(4):1563 - 1571. 46 U.S. Environmental Protection Agency (U.S. EPA). 2000. Integrated Risk Information System File for Benzene. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0276.htm. 47 International Agency for Research on Cancer, IARC monographs on the evaluation of carcinog enic risk of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agency for Research on Cancer, World Health Organization, Lyon, France, p. 345 - 389, 1982. 48 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. ( 1992) Synergistic action of the benzene metabolite hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony - stimulating factor in vitro, Proc. Natl. Acad. Sci. 89:3691 - 3695. 49 International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health Organization, Lyon, France. 50 U.S. Department of Health and Human Services National Toxicology P rogram 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183. 51 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193 - 197. 52 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541 - 554.7 - 25

Methanol E xposure 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 carcinogenicity. Other Air Toxics In addition to the compounds described above, other toxic compounds might be affected by these rules. Information regarding the health effects of those compounds can be found in EPA’s IRI S database. 61

53 Rowe, VK and McCollister, SB. 1981. Alcohols. In: Patty's Industrial Hygiene and Toxicology, 3rd ed. Vol. 2C, GD Clayton, FE Clayton, Eds. John W iley & 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; MacKe nzie, DR; Khan, A; Burg, JR; Weigel, WW; Goad, PT. 1985. Teratological assessment of methanol and ethanol at high inhalation levels in rats. Toxicol Sci, 5: 727 - 736. 56 Rogers, JM; Barbee, BD; Rehnberg, BF. 1993. Critical periods of sensitivity for the deve lopm ental toxicity of inhaled methanol. Teratology, 47: 395. 57 Burbacher, T; Grant, K; Shen, D; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part II: developmental effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA. 58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects fol lowing maternal inhalation exposure to methanol in nonhuman primates Part I: methanol disposition and reproductive toxicity in adult females. Health Effects Institute. Cambridge, MA. 59 Burbacher, TM; Grant, KS; Shen, DD; Sheppard, L; Damian, D; Ellis, S; L iberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (Macaca fascicularis): reproductive performance and birth outcome. Neurotoxicol Teratol, 26: 639 - 650. 60 Burbacher, TM; Shen, DD; Lalovic, B; Grant, KS; Sheppard, L; Damian, D; Elli s, S; Liberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (Macaca fascicularis): exposure and toxicokinetics prior to and during pregnancy. Neurotoxicol Teratol, 26: 201 - 221. 61 U.S. EPA Integrated Risk Information System (IRIS) dat abase is available at: www.epa.gov/iris7 - 26

**7.2 .**  **2 Additional NO** **2 Co**  **- Benefits**  In addition to being a precursor to PM 2.5 , NO x emis sions are also associated with a variet y of respiratory health effects. Unfortunately, we were unable to estimate the health benefits associated with reduced NO 2 or ozone exposure in this analy sis because we do not have air quality

modeling data available . Therefore, this analy sis onl y quantifies and monetizes the PM 2.5 benefits associated with the reductions in NO 2 emissions. Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment (I SA) for Nitrogen Dioxide concluded that there is a likely causal relationship between respiratory health effects and short - term exposure to NO 2 (U.S. EPA, 2008c ). Persons with preexisting respiratory disease, children, and older adults may be more susceptible to the effects of NO 2 exposure. Based on our review of this information, we identified four short - term morbidity endpoints that the NO 2 IS A identified as a “likely causal relationship”: asthma exacerbation, respiratory - related emergency department visits, and respiratory - related hospitalizations. The differing evidence and associated strength of the evidence for these different effects is described in detail in the NO 2 IS A. The NO 2 IS A also concluded that the relationship between short - term NO 2 exposure and premature mortalit y was “suggestive but not sufficient to infer a causal relationship” because it is difficult to attribute the mortality risk effects to NO 2 alone. Although the NO 2 IS A stated that studies consistently reported a relation ship between NO 2 exposure and mortality , the effect was generall y smaller than that for other pollutants such as PM. NOx emissions also contribute to a variet y of adverse welfare effects , including acidic deposition, visibility

impairment, nutrient enrichment . Deposition of nitrogen causes acidification, which can cause a loss of biodiversity of fishes, zooplankton, and macro invertebrates in aquatic ecosy stems, as well as a decline in sensitive tree species, such as red spruce ( Picea rubens ) and sugar map le ( Acer saccharum ) in terrestrial ecosy stems . In the northeastern United States, the surface waters affected b y acidification are a source of food for some recreational and subsistence fishermen and for other consumers and support several cultural service s, including aesthetic and educational services and recreational fishing. B iological effects of acidification in terrestrial ecos ys tems are generally linked to aluminum toxicity , which can cause reduced root growth, which restricts the ability of the plant to take up water and nutrients. These direct effects can, in turn, increase the sensitivity of these plants to stresses, such as droughts, cold temperatures, insect pests, and disease leading to increased mortality of canop y trees. Terrestrial acidificati on affects several important ecological services, including declines in habitat for threatened and endangered species (cultural), declines in forest aesthetics (cultural),7 - 27

declines in forest productivity (provisioning), and increases in forest soil erosion and reductions in water retention (cultural and regulating). (U.S. EPA, 2008d) Deposition of nitrogen is also associated with aquatic and terrestrial nutrient enrichment. In estuarine waters, excess nutrient enrichment can lead to eutrophication. Eutro phication of estuaries can disrupt an important source of food production, particularl y fish and shellfish production, and a variet y of cultural ecosystem services, including water - based recreational and aesthetic services. Terrestrial nutrient enrichment is associated with changes in the ty pes and number of species and biodiversity in terrestrial sy stems. Excessive nitrogen deposition upsets the balance between native and nonnative plants, changing the ability of an area to support biodiversity . When the composition of species changes, then fire frequency and intensit y can also change, as nonnative grasses fuel more frequent and more intense wildfires. (U.S. EPA, 2008d) **7.2.3 Ozone**  **Co -** 

**Benefits** In the presence of sunlight, NOx and VOCs can undergo a chemic al 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 . **7.2.4 Carbon Monoxide Co**  **- Benefits**  Carbon monoxide in ambient air is formed primarily by the incomplete combustion of carbon - containing fuels and photochemical reactions in the atmosphere. The amount of CO emitted from these reactions, relative to carbon dioxide (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 o xygen availability). Carbon monoxide can elicit a broad range of effects in multiple tissues and organ systems that are dependent upon concentration and duration of exposure. The Integrated Science Assessment for Carbon Monoxide (U.S. EPA, 2010a) concluded that short - term exposure to CO is “likely to have a causal relationship” with cardiovascular morbidity, particularly in individuals with coronary heart disease. Epidemiologic studies associate short - term CO exposure with increased risk of emergency department visits and hospital admissions. Coronary heart disease includes those who have angina pectoris (cardiac chest pain), as well as those who have experienced a heart attack. Other7 - 28

subpopulations potentially at risk include individuals with diseases such as chronic obstructive pulmonary

disease (COPD), anemia, or diabetes, and individuals in very early or late life stages, such as older adults or the developing young. The evidence is suggestive of a causal relationship between short - term exposure to CO and respiratory morbidity

and mortality . The evidence is also suggestive of a causal relationship for birth outcomes and developmental effects following long - term exposure to CO, and for central nervous system effects linked to short - and long - term exposure t o CO. **7.2.5 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 averag e 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 recreatio nal 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 we a ble 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 represent ation 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 PM b enefits. 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 estimat es used here reflect specific geographic patterns of emissions reductions and specific air quality and benefits7 - 29

modeling assumptions. For example, these estimates do not reflect local variability in population density , meteorology , exposure, baseline health incidence rates, or other local factors. Use of these $/ton values to estimate benefits may lead to higher or lower benefit estimates than if benefits were calculated based on direct air quality modeling. Great care should be taken in applying these esti mates to emission reductions occurring in an y 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 emiss ion 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). PM 2.5 mortality

benefits are the largest benef it 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 LMLassessment. 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 - polic y policy . 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 above 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 LMLof 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 study. It is important to emphasize that we have high confidence in PM 2.5 - related effects down to the lowest LMLof 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 National Ambient Air Quality

Standard (NAAQS) for annual PM 2.5 at 15 μg/m 3 , which was set in 2006. It isimportant to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS

reflect the level determined by the adequate margin of safety, taking into consideration effects on susceptible populations. While benefits occurring below the standard may be less certain than those occurring above the standard, EPA considers them to be legitimate components of the total benefits estimate.

**Figure 7 -**  **6. Percentage of Adult Population by Annual Mean PM** 

**Baseline**

7 - 30 important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS reflect the level determined by the Administrator to be protective of public health within an adequate margin of safety, taking into consideration effects on susceptible populations. While benefits occurring below the standard may be less certain than those occurring above the considers them to be legitimate components of the total benefits estimate.

**Percentage of Adult Population by Annual Mean PM 2.5**  **Exposure** important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS Administrator to be protective of public health within an adequate margin of safety, taking into consideration effects on susceptible populations. While benefits occurring below the standard may be less certain than those occurring above the considers them to be legitimate components of the total benefits estimate.

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

assumptions underlying the estimates for premature mortality, which 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 through benefit per local variability

in population density , meteorology , exposure, baseline health incidence rates, or other local factors that might lead to an over estimate of the actual benefits of controlling the specific location of the air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different locatio ns, such as designated nonattainment areas. I n addition, the benefit estimates are based on emissions from existing sources. To the extent that the geographic distribution of the emissions reductions for this rule are different than the 7 - 31 **Cumulative Distribution of Adult Population by**  **Annual Mean PM**

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

). The benefits estimates are s ubject to a number of assumptions and uncertainties. For example, for key

assumptions underlying the estimates for premature mortality, which

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

in population density , meteorology , exposure, baseline health incidence rates, or other local factors that might lead to an over - estimate or under of the actual benefits of controlling PM precursors . We do not have data on the specific location of the air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different ns, such as designated nonattainment areas. I n addition, the benefit estimates are based on emissions from existing sources. To the extent that the geographic distribution of the emissions reductions for this rule are different than the **Annual Mean PM 2.5**  Above we present the estimates of the total benefits, based on our interpretation of the HES and the NAS ubject to a number of assumptions and uncertainties. For example, for key

assumptions underlying the estimates for premature mortality, which

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

in population density , meteorology , exposure, baseline health estimate or under We do not have data on the specific location of the air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different ns, such as designated nonattainment areas. I n addition, the benefit - per - ton estimates are based on emissions from existing sources. To the extent that the geographic distribution of the emissions reductions for this rule are different than the7 - 32 modeled e missions, the benefits may be underestimated or overestimated. In general, there is inherentl y more uncertaint y for new sources, which may not be included in the emissions inventory , than existing sources. 2. We assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality . This is an important assumption, because 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 industrial 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 an aly 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 lo west modeled 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 expe rt elicitation 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 result, 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 neces sary 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 o f the PM RIA can provide some evidence of the uncertainty surrounding the benefits results presented in this anal ys is.7 - 33

**7.4 Comparison of Co**  **- Benefits and Costs**  Using a 3% discount rate, we estimate the total combined mon etized co - benefits of the reconsidered SI RI CE NESHAP proposal to be $ 62 million to $150 m illion in the implementation year (2013). Using a 7% discount rate, we estimate the total monetized co benefits of the final rule to be $ 55 million to $140 m illion. The annualized social costs of the reconsidered SI RICE NESHAP proposal are $ 115 million at a 7% interest rate. 62 Thus, the net benefits are $ - 53 million to $ 35 m illion at a 3% discount rate and $ - 60 million to $ 25 m illion at a 7% discount rate. All estimates are in 2010 $ for the y ear 2013. Table 7 - 5 shows a summary of the monetized co - benefits, social costs, and net benefits for the reconsidered SI RICE NESHAP proposal , respectivel y. Figures 7 - 8 and 7 - 9 show the full range of net benefits estimates (i.e., annual co - bene fits 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 22 ,000 tons of carbon monoxide and 1,8 00 tons of HAPs each ye ar from SI RI CE have not been included in these estimates. **Table 7**  **- 5**  **. Summary of the**  **Annualized Monetized Benefits, Social Costs, and Net**  **Benefits for the Proposed SI RICE NESHAP Reconsideration**  **in 201 3**  **(millions of 20 10**  **$) 1**  **3% Discount Rate 7% Discount Rate**  Total Monetized Benefits 2 $62 to $150 $55 to $140 Total Compliance Costs 3 $115 $115 Net Benefits $ - 53 to $35 $ - 60 to $25 Non - monetized Benefits Health effects from HAP exposure Health effects from CO , NO 2 , and ozone exposure Ecosystem effects Visibility impairment 1 All estimates are for the implementation year ( 2013 ), and are rounded to two significant figures. 2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as NOx. 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 premature mortality because the scientific evide nce is not yet sufficient to allow differentiation of effects estimates by particle type. Because these estimates were generated using benefit - per - ton estimates, we do not break down the total monetized benefits into specific components here. See Figur e 7 - 1 for an illustration of the breakdown, or the RIA for the final Cross - States Air Pollution Rule (EPA, 2011) for more information.

62 For more information on the annualized social costs, please refer to Section 5 of this RIA.7 - 34

3 The annual compliance costs serve as a proxy for the annual social costs of this rule given the lack of difference betwe en the two . The engineering compliance costs are annualized using a 7 percent discount rate.**Figure 7 -**  **8. Net Benefits for**  **Proposed SI RICE discount rate**  ***** *Net Benefits are quantified in terms of PM benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. The monetized benefits incorporate the conversion from precursor emissions to - $100 - $80 - $60 - $40 - $20 $0 $20 $40 $60 $80 $100

Pope et al.**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

7 - 35 **Proposed SI RICE NESHAP**  **Reconsideration at 3%** *Net Benefits are quantified in terms of PM2.5 at a 3% discoun t rate for 2013 and are in 2010$ . This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. The monetized benefits incorporate the conversion from precursor emissions to am bient fine particles. Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2

epidemiology functions and 12 expert functions **Reconsideration at 3%**

. This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. am bient fine particles. Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2**Figure 7 -**  **9. Net Benefits for**  **Proposed SI RICE discount rate**  ***** *Net Benefits are quantified in terms of PM in 2010$ . This graph shows 14 benefits estimates combined w ith the cost estimate. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. - $100 - $80 - $60 - $40 - $20 $0 $20 $40 $60 $80

Pope et al.**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

7 - 36 **Proposed SI RICE NESHAP**  **Reconsideration** *Net Benefits are quantified in terms of PM2.5 benefits at a 7 % discount rate at a 3% discount rate

graph shows 14 benefits estimates combined w ith the cost estimate. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 2

epidemiology functions and 12 expert functions **Reconsideration at 7%**  at a 3% discount rate for 2013 and are graph shows 14 benefits estimates combined w ith the cost estimate. The monetized benefits Laden et al.

Cost estimate combined with total monetized benefits estimates derived from 27 - 37

**7.5 References**  Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “The influe nce 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

of 2009 workshop and future considerations.” Environ Health Perspect . Jan; 119(1): p. 125 - 30. Kochi, I., B. Hubbell, and R. Kramer. 2006. “An Empirical Bay es Approach to Combining Estimates of the Value of Statistical L ife for Environmental Policy Anal ys is .” Environmental and Resource Economics. 34: 385 - 406. Krewski D, Jerrett M, Burnett RT, Ma R, Hughes E, Shi, Y, et al. 2009. Extended follow - up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. HEIResearch Report, 140, Health Effects Institute, Boston, MA. Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery . 2006. Reduction in Fine Particulate Air Pollution and Mortality . American Journal of Respiratory and Critical Care Medicine. 173: 667 - 672. Mrozek, J.R., and L .O. Taylor. 2002. “What Determines the Value of Life? A Meta - Analy sis.” Journal of Policy

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