***E.O. 12866 Review – Draft – Do Not Cite, Quote, or Release During Review ***

**E.O. 12866 NESHAP RICE Spark Ignition Engines 2060-AQ58 Proposal 20120315** 


### April 2012



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

Draft Report

Prepared for

Larry Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (AEG) (MD-C439-02) Research Triangle Park, NC 27711_________________________________ RTI International is a trade name of Research Triangle Institute. 

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

Draft Report

April 2012

Prepared for

Larry Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Benefit and Cost Group (ABCG) (MD-C439-02) Research Triangle Park, NC 27711

Prepared by

Paramita Sinha Fern Braun Brooks Depro RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709iii CONTENTS

Section Page

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

2 Introduction .................................................................................................................. . 2-1
2.1 Organization of this Report .................................................................................. 2-1

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

3.1 Electric Power Generation, Tran smission, and Distribution ............................... 3-1
3.1.1 Overview .................................................................................................. 3-1
3.1.2 Goods and Services Used ......................................................................... 3-3
3.1.3 Business Statistics .................................................................................... 3-4

3.2 Oil and Gas Extraction ....................................................................................... 3-11
3.2.1 Overview ................................................................................................ 3-11
3.2.2 Goods and Services Used ....................................................................... 3-11
3.2.3 Business Statistics .................................................................................. 3-13
3.2.4 Case Study: Marginal Wells .................................................................. 3-17
3.3 Pipeline Transportation of Natural Gas ............................................................. 3-18
3.3.1 Overview ................................................................................................ 3-18
3.3.2 Goods and Services Used ....................................................................... 3-18
3.3.3 Business Statistics .................................................................................. 3-20

4 Regulatory Alternatives, Costs, and Emission Impacts ................................................ 4-1
4.1 Background .......................................................................................................... 4-1
4.2 Proposed Amendments to SI RICE NESHAP ..................................................... 4-1
4.2.1 Total Hydrocarbon Compliance (THC ) Demonstration Option .............. 4-1
4.2.2 Proposed Amendment - Emergency Demand Response/Peak Shaving .................................................................................................... 4-5
4.2.3 Proposed Amendment - Non-Emergency Stationary SI RICE Greater than 500 HP Locate d at Area Sources...... ................................ 4-6iv 4.3 What Are the Pollutants Regulated by the Rule? ............................................... 4-11

4.4 Cost Impacts....................................................................................................... 4-14
4.4.1 Introduction ............................................................................................ 4-14
4.4.2 Control Cost Methodology .................................................................... 4-14
4.4.3 Control Cost Equations .......................................................................... 4-18
4.4.4 Summary ................................................................................................ 4-21
4.4.5 Caveats and Limitations for Cost Estimates .......................................... 4-35

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

5 Economic Impact Analysis, Energy Impacts, and Social Costs ................................... 5-1
5.1 Compliance Costs of the Propos ed Reconsidered Rule ....................................... 5-1

5.2 Social Cost Estimate ............................................................................................ 5-3
5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis .......... 5-4
5.2.1 Changes in Market Prices and Quantities ................................................ 5-4
5.2.2 Regulated Markets: The Electri c Power Generation, Transmission, and Distribution Sector ............................................................................ 5-6
5.2.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus ............................................................................... 5-7
5.4 Energy Impacts .................................................................................................... 5-9

5.5 Unfunded Mandates ........................................................................................... 5-10
5.5.1 Future and Disproportionate Costs ........................................................ 5-10
5.5.2 Effects on the National Economy .......................................................... 5-10

5.6 Environmental Justice ........................................................................................ 5-11
5.7 Employment Impact Analysis ............................................................................ 5-11
5.7.1 Employment Impacts from Polluti on Control Requirements ................ 5-13
5.7.2 Employment Impacts within the Regulated Industry............................. 5-17

6 Small Entity Screeni ng Analysis .................................................................................. 6-1v 6.1 Small Entity Data Set ........................................................................................... 6-1
6.2 Small Entity Economic Im pact Measures ............................................................ 6-2
6.2.1 Model Establishment Receipts and Annual Compliance Costs ............... 6-2

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

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

7.1 Calculation of PM 2.5 Human Health Co-Benefits ................................................ 7-1

7.2 Unquantified Benefits ........................................................................................ 7-13
7.2.1 HAP Benefits ......................................................................................... 7-13
7.2.2 Additional NO 2 Co-Benefits .................................................................. 7-14
7.2.3 Ozone Co- Benefits ................................................................................ 7-16
7.2.4 Carbon Monoxide Co-Benefits .............................................................. 7-16 7.2.5 Visibility Impairment Co-Benefits..................................7-23

7.3 Characterization of Uncertainty in the Monetized PM 2.5 Co-Benefits ............... 7-25

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

8 References for RIA ....................................................................................................... 8-1vi LIST OF FIGURES

Number Page

3-1 Industrial Production Index (NAICS 2211) ................................................................ 3-3 3-2 Internal Combustion Generato rs by State: 2006 ......................................................... 3-4 3-3 2002 Regional Distribution of Establis hments: Electric Power Generation, Transmission, and Distribution Industry (NAICS 2211) ............................................ 3-6 3-4 Industrial Production Index (NAICS 211) ................................................................ 3-12 3-5 2002 Regional Distribution of Establishm ents: Crude Petroleum and Natural Gas Extraction Industry (NAICS 211111) ................................................................ 3-15 3-6 2002 Regional Distribution of Establishm ents: Natural Gas Liquid Extraction Industry (NAICS 211112) ......................................................................................... 3-16 3-7 Distribution of Establishments within Pi peline Transportation (NAICS 486) .......... 3-19 3-8 Distribution of Revenue within Pipeli ne Transportation (NAICS 486) .................... 3-20 3-9 2002 Regional Distribution of Establishm ents: Pipeline Transportation (NAICS 486) .......................................................................................................................... .. 3-22 3-10 Share of Establishments by Legal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002 ................................ 3-22

5-1 Distribution of Engine Populat ion by Horsepower Group .......................................... 5-4 5-2 Market Demand and Supply Model: W ith and Without Regulation ........................... 5-6 5-3 Electricity Restructuring by State ................................................................................ 5-9

6-1 Distribution of Engine Population by Size for All Industries ..................................... 6-8 6-2 Distribution of Complian ce Costs by Engine Size fo r 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 SI RICE Reconsidered NESHAP in 2013 ...................................................................................................... 7-12 7-3. Breakdown of Monetized Co-Benefits for the Proposed SI RICE Reconsidered NESHAP by Engine Sizee ........................................................................................ 7-13 7-4. Estimated Chronic Census Tractl Carci nogenic Risk from HAP exposure from outdoor sources (2005 NATA) .................................................................................. 7-18 7-5. Estimated Chronic Census Tract Non cancer (Respiratory) Risk from HAP exposure from outdoor sources (2005 NATA) .......................................................... 7-18 7-6. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline .................................................................................................................... 7-28vii 7-7. Cumulative Distribution of Adu lt Population at Annual Mean PM 2.5 Exposure in the Baseline .......................................................................................................... 7-2 8 7-8. Net Benefits for the Proposed SI RICE Reconsidered NESHAP at 3% Discount Rate ............................................................................................................ 7-33 7-9. Net Benefits for the Proposed SI RICE Reconsidered NESHAP at 7% Discount Rate .......................................................................................................................... .. 7-34viii LIST OF TABLES

Number Page

1-1 Summary of the Monetized Co-Benefits, So cial Costs, and Net benefits for the Proposed SI RICE Reconsidered NES HAP in 2013 (millions of 2010$) ................... 1-2

3-1 Key Statistics: Electric Power Gene ration, Transmission, and Distribution (NAICS 2211) (2007) .................................................................................................. 3-2 3-2 Direct Requirements for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2002 ............................................................................... 3-5 3-3 Firm Concentration for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2002 ............................................................................... 3-7 3-4 United States Retail Electricity Sales Statistics: 2008 ................................................ 3-8 3-5 FY 2010 Financial Data for 70 U.S. Share holder-Owned Electric Utilities ............... 3-9 3-6 Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 2211 ....................... 3-9 3-7 Key Enterprise Statistics by Receipt Size for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2007 ............................................... 3-10 3-8 Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): (2007) ........................................................................................................................ 3-12 3-9 Key Statistics: Natural Gas Liquid Ex traction (NAICS 211112) (2007) .................. 3-13 3-10 Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002 ...................... 3-13 3-11 Key Enterprise Statistics by Employment Size for Crude Petroleum and Natural Gas Extraction ( NAICS 211111): 2007 ....................................................... 3-17 3-12 Key Enterprise Statistics by Employmen t Size for Crude Natural Gas Liquid Extraction (NAICS 211112): 2007 ............................................................................ 3-17 3-13 Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAICS 211 ....................... 3-18 3-14 Key Statistics: Pipeline Transportation of Natural Gas (NAICS 48621) (2007) ...... 3-19 3-15 Direct Requirements for Pipeline Transportation (NAICS 486): 2002 ..................... 3-21 3-16 Firm Concentration for Pipeline Tran sportation of Natural Gas (NAICS 48621): 2002 .............................................................................................................. 3-2 3 3-17 Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 486 ....................... 3-23 3-18 Key Enterprise Statistics by Receipt Size for Pipeline Transportation of Natural Gas (NAICS 48621): 2007 ........................................................................................ 3-24

4-1 Summary of Annual and Capital Costs E quations for Existing Stationary SI Engines ...................................................................................................................... 4-21 4-2 Summary of Major Source and Area Source Costs for the SI RICE NESHAP ........ 4-22 4-3 Summary of Major Source and Area S ource NAICS Costs for the SI RICE NESHAP ................................................................................................................... 4-23ix 4-4 Summary of Major Source and Area S ource NAICS Costs for the SI RICE NESHAP, by Size ...................................................................................................... 4-24 4-5 Summary of Major Source and Area S ource NAICS Costs for the SI RICE NESHAP, by Number of Engines ............................................................................. 4-28 4-6 Summary of Major Source and Area Source Baseline for the SI RICE NESHAP ................................................................................................................... 4-33 4-7 Emissions Factors ...................................................................................................... 4-33 4-8 Summary of Major Source and Area S ource Baseline Emissions for the SI RICE NESHAP by 2013 ........................................................................................... 4-34 4-9 Summary of Major Source and Area Sour ce Emissions Reductions for the SI RICE NESHAP by 2013 ........................................................................................... 4-34

5-1 Selected Industry-Level Annualized Co mpliance Costs as a Fraction of Total Industry Revenue: 2009 ............................................................................................... 5-3 5-2 Hypothetical Price Increases for a 1% Increase in Unit Costs .................................... 5-5 5-3 Hypothetical Consumption Decreases for a 1% Increase in Unit Costs ..................... 5-7 5-4 U.S. Electric Power a Sector Energy Consumption (Quadrillion BTUs): 2013 ........... 5-9 5-5 Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Control Equipment Requirements for Proposed Reconsideration SI RICE NESHAP........................................................5-16

6-1 Proposed NESHAP for Existing Stationary Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Busi ness Size Standards ............. 6-3 6-2 Average Receipts for Affected Industry by Enterprise: 2007 ($2009 Million/Establishment) ................................................................................................ 6-4 6-3 Average Receipts for Affected Industr y by Enterprise Receipt Range: 2007 ($2009/Establishment) ................................................................................................. 6-5 6-4 Representative Establishment Costs Used for Small Entity Analysis ($2009) ........... 6-7

7-1 Human Health Effects of PM 2.5 ................................................................................... 7-2 7-2. General Summary of Monetized PM 2.5 –Related Health Co-Benefits Estimates for the Proposed SI RICE Reconsidered NESHAP in 2013 (millions of 2010$) ...... 7-9 7-3. Summary of Reductions in H ealth Incidences from PM 2.5 Co-Benefits for the Proposed SI RICE Reconsidered NESHAP in 2013 ................................................ 7-10 7-4. All Monetized PM 2.5 Co-Benefits from PM 2.5 Benefits for the Proposed SI RICE Reconsidered NESHAP in 2013 ..................................................................... 7-11 7-5. Summary of the Annualized Monetized Benefits, Social Costs, and Net Benefits for the Proposed SI RICE Reconsidered NESHAP in 2013 (millions of 2010$) ................................................................................................................... 7 -311-1 Section 1
EXECUTIVE SUMMARY

This proposed action is a reconsideration of the promulgated NESHAP for existing stationary SI RICE with a site rating of less than or equal to 5 00 HP located at major sources, and existing stationary SI RICE of any site rating located at area sources.

EPA estimates that complying with the proposed reconsidered national emission standards for hazardous air pollutants (NESHAP) fo r stationary spark-ign ition (SI) reciprocating internal combustion engines (RICE) will have an annualized cost of approximately $115 million per year (2009 or 2010 dollars) in the year of fu ll implementation of the rule (2013). The total annualized costs of the proposed reconsidered rule are 55% less than those for the final SI RICE NESHAP promulgated in 2010. Using these cost s, EPA estimates in its economic impact analysis that the NESHAP will have limited impacts on the industries affected and their consumers. Using sales data obtained for affected small entities in an analysis of the impacts of this rule on small entities, EPA expects th at the NESHAP will not result in a SISNOSE (significant economic impacts for a substantial number of small entit ies), a result co nsistent with
the conclusion for the final SI RICE NESHAP issued in 2010. EPA also does not expect significant adverse energy impacts based on Executive Order 13211, an Executive Order that requires analysis of energy impacts for rules such as this one that are economically significant
under Executive Order 12866.

In the year of full implementation (2013), EPA estimates that the tota l monetized benefits of the proposed reconsidered NESHAP are $62 million to $150 million and $55 million to $140 million, at 3% and 7% discount rates, respectively (Table 1-1). All estimates are in 2010 dollars for the year 2013. These estimates reflect the co-benefits from 9,600 tons of NOx emission reductions associated with implementing the cont rols to reduce hazardous air pollutants (HAPs) required under this proposed reconsideration. Using altern ate 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 th ese estimates. The benefits from reducing other air pollutants have not been m onetized in this analysis, incl uding reducing 22,200 tons of carbon monoxide (CO) and 1,800 tons of hazardous air pollutants (HAPs) each year. In addition, ecosystem benefits and visibility benefits ha ve not been monetized in this analysis.

In the year of full implementation (2013), EPA estimates the net benefits of the proposed NESHAP are $-53 million to $35 million and $-60 million to $25 million at 3% and 7% discount1-2 rates, respectively (Table 1-1). These estimates are “snapshots” of benefits and costs at year 2013
and are in 2010 dollars

.1-3 Table 1-1. Summary of the Annualized Moneti zed Co-Benefits, Social Costs, and Net benefits for the Proposed Reconsiderati on SI RICE NESHAP in 2013 (millions of 2010$) 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 w ith 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 cobenefits 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 assu me that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality because there is no clear scientific evidence that would support the development of differential effects estimates by particle type. Because these estimates were generated using benefit-per-ton estimates, we do not break down the total monetized benefits into specific components here. See Figure 7-1 for an illustration of the breakdown, or th e RIA for the final Cross-States Air Pollution Rule (EPA, 2011) for more information.

3 The annual compliance costs serve as a pr oxy for the annual social costs of th is rule given the lack of difference

between the two. The annual compliance costs are calculated using a 7 percent discount rate.2-1 Section 2
INTRODUCTION

EPA is proposing NESHAP for existing stationary SI RICE that either are located at area sources of hazardous air pollutant emissions or that have a site rating of less than or equal to 500 horsepower and are located at major sources of hazardous air pollutant emissions. The proposed amendments to the SI RICE NESHAP are provide d in detail in Section 4 of this RIA.

The rule is economically significant accordi ng to Executive Order 12866. As part of the regulatory process of preparing th ese standards, EPA has prepared a regulatory impact analysis (RIA). This analysis includes an analysis of impacts to small enti ties as part of compliance with the Small Business Regulatory Enforcement Fair ness Act (SBREFA) and an analysis of impacts on energy consumption and production to comply with Executive Orde r 13211 (Statement of Energy Effects). An analysis of economic imp acts, along with an analysis of impacts on employment, is also included in th is RIA. Finally, an analysis of the benefits of the rule is
included in this RIA. It should be noted that the data that supports the analyses listed above have been updated where possible and ap propriate from the data used in the RIA for the SI RICE NESHAP promulgated in 2010.

2.1 Organization of this Report
The remainder of this report supports and details the methodology a nd the results of the
RIA:

 Section 3 presents a profile of the affected industries.

 Section 4 presents a summary of regulatory al ternatives considered in the final rule, and provides the compliance costs of the rule.

 Section 5 describes the estimated costs of the regulation and describes the economic impact analysis (EIA) methodology and re ports market, welfare, energy, and employment impacts.

 Section 6 presents estimated impacts on small entities.

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

This section provides an introduction to the i ndustries affected by the rule, i.e., industries in which the spark-ignition (SI) RICE being regu lated are found. SI RICE generate electric power, pump gas or other fluids, or compre ss air for machinery. The primary non-utility application of internal combus tion (IC) engines is in the na tural gas industry to power compressors used for pipeline transportation, field gathering (collecting gas from wells), underground storage tanks, and in-gas processing plants. RICEs are separated into three design classes: 2 cycle (stroke) lean burn, 4-stroke lean burn, and 4-stroke rich burn. Each of these have design differences that affect both baseline emi ssions as well as the potential for emissions
control.

These industries include the following:

 electric power generation, transm ission, and distribution (NAICS 2211),

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

 pipeline transportation of natural gas (NAICS 48621).

While this is not an exha ustive list of the i ndustries affected by this proposed reconsideration rule, these three industries incur about 83 percent of the an nualized costs of the rule. A full listing of all industries affected in this rulemaking can be found in Chapter 4. The purpose of this profile chapter is to give th e reader a general unders tanding of the economic aspects of the industry; their rela tive size, relationships with othe r sectors in the economy, trends for the industries, and financial statistics.

3.1 Electric Power Generation, Transmission, and Distribution

3.1.1 Overview
Electric power generation, transmission, and distribution (NAICS 2211) is an industry group within the utilities sector (NAICS 22). It includes establishments that produce electrical energy or facilitate its transm ission to the final consumer.

From 2002 to 2007, revenues from electric pow er generation grew about 18% to over $440 billion ($2007) (Table 3-1). 1 At the same time, payroll rose about 7% and the number of

1 We provide revenues from electric power generation for the years 2002 and 2007 for these are years of the Economic Census. We reference data from these Economic Censuses frequently in this industry profile and show revenues from this industry over this tim e frame due to availability of such data.3-2 employees decreased by around 4%. The number of establishments rose by about 3%. Industrial production within NAICS 2211 has increa sed 26% since 1997 (Figure 3-1).

Electric utility companies have traditionall y been tightly regula ted monopolies. Since 1978, several laws and orders have been passed to encourage competition w ithin the electricity market. In the late 1990s, many states began the process of restructuring their utility regulatory framework to support a competitive market. Follo wing market manipulation in the early 2000s, however, several states have susp ended their restructuring efforts. The majority (58%) of power generators controlled by combined heat and pow er (CHP) or independent power producers are located in states undergoing activ e restructuring (Figure 3-2).
Table 3-1. Key Statistics: Electric Power Ge neration, Transmission, and Distribution (NAICS 2211) ($2007)

2002 2007 Revenue ($10 6 ) 373,309 440,355 Payroll ($10 6 ) 40,842 43,792 Employees 535,675 515,335
Establishments 9,394 9,642

Source: U.S. Census Bureau; American FactFinder; “Sect or 22: EC0722I2: Utilities: In dustry Series: Preliminary

Comparative Statistics for the United States (2002 NAICS Basis): 2007 and 2002.” http://factfinder.census.gov3-3 Figure 3-1. Industrial Pro duction Index (NAICS 2211)

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

ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G2211.S <http://www.federalreserve.gov/datadownload/>. (January 27, 2010).

3.1.2 Goods and Services Used
In Table 3-2, we use the latest detailed be nchmark input-output data report by the Bureau of Economic Analysis (BEA) (2002) to identify the goods and serv ices used in electric power generation. As shown, labor and ta x requirements represent a signi ficant share of the value of power generation. Extraction, transportation, re fining, and equipment requirements potentially 80 85 90 95 100 105 110 1151997‐011997‐061997‐111998‐041998‐091999‐021999‐071999‐122000‐052000‐102001‐032001‐082002‐012002‐062002‐112003‐042003‐092004‐022004‐072004‐122005‐052005‐102006‐032006‐082007‐012007‐062007‐112008‐042008‐092009‐022009‐072009‐12IndexValue(Jan2002=100)3-4 Figure 3-2. Internal Combustion Generators by State: 2006
Source: U.S. Department of Energy, Energy Information Administration. 2007. “2006 EIA-906/920 Monthly Time

Series.”

associated with reciprocating internal combustion engines (o il and gas extraction, pipeline transportation, petroleum refineries, and turb ine manufacturing) repr esent around 10% of the
value of services.

3.1.3 Business Statistics

The U.S. Economic Census and Statistics of U.S. Businesses (SUSB) programs provide
national information on the dist ribution of economic variables by industry, location, and size of business. Throughout this section and re port, we use the following definitions:

 Establishmen t: An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed. Diesel and Natural Gas Internal Combustion Generators By State

No Restructuring Suspended Restructuring Active Restructuring
100

50

10
13-5 Table 3-2. Direct Requirements for Electri c Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Commodity Description Direct Requirements Coefficients a
V00100 Compensation of employees 20.52% V00200 Taxes on production and imports, less subsidies 13.71% 211000 Oil and gas extraction 6.16% 212100 Coal mining 5.86% 482000 Rail transportation 3.01% 230301 Nonresidential maintenance and repair 2.83% 486000 Pipeline transportation 1.70%

722000 Food services an d drinking places 1.40% 52A000 Monetary authorities and depository credit intermediation 1.39% 541100 Legal services 1.13%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table, Use Table and Direct Requirements Table. Tables 4 and 5.

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

 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 th e establishment are the same for singleestablishment firms. For each multiestablishment firm, establishments in the same industry within a state are counted as one firm; the firm employment and annual payroll are summed from the associated establishments.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise; the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size designations are determined by the su mmed employment of all associated establishments.3-6 In 2002, Texas had almost 1,000 power establis hments, 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 Interna tional; using American FactFinder; “Sector 22: Utilities:

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

As shown in Table 3-3, the four largest firms owned over 1,200 establishments and accounted for about 16% of total industry receip ts/revenue. The 50 largest firms accounted for almost 6,000 establishments and about 78% of total rece ipts/revenue.

Investor-owned energy providers accounted for only 2% of retail elect ricity sold in the United States in 2008 (Table 3-4). In 2008, invest or-owned energy provider companies with less than 50% of their assets regulated were unprof itable overall, while other companies in this category were profitable. (Table 3-5). In 2008, enterprises within NAICS 2211 had a pre-tax profit margin of 8.1% (Table 3-6).

In 2002, about 82% of firms generating, transm itting, or distributing electric power had receipts of under $50 million (Table 3-7). Ho wever, these firms accounted for only 11% of employment, with 89% of employees working fo r 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 Electri c Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Establishments Receipts/Revenue

Number of Employees Employees per Establishment Amount ($10 6 ) Percentage of Total
All firms 9,394 $325,028 100.0% 535,675 57
4 largest firms 1,260 $52,349 16.1% 68,432 54
8 largest firms 2,566 $95,223 29.3% 151,575 59
20 largest firms 3,942 $173,207 53.3% 271,393 69
50 largest firms 5,887 $253,015 77.8% 408,021 69

Source: U.S. Census Bureau; generated by RTI Interna tional; 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).3-8Table 3-4. United States Retail Electricity Sales Statistics: 2008Full-Service Providers Other ProvidersItem Investor-Owned Public Federal Cooperative Facility Energy Delivery TotalNumber of entities 3 62 1 25 1 NA NA 92Number of retail customers 46,985 2,160,220 36 940,697 1 NA NA 3,147,939Retail sales (103megawatthours) 2,257 70,303 9,625 21,868 117 NA NA 104,170Percentage of retail sales 2 67 9 21 0 — — 100Revenue from retail sales ($106) 113 5,934 473 1,994 6 NA NA 8,520Percentage of revenue 1.33 69.65 5.55 23.41 0.07 — — 100Average retail price (cents/kWh) 5.01 8.44 4.91 9.12 5.25 NA NA 8.18Source: U.S. Department of Energy, Energy Information Administration. 2009. “State Electricity Profiles 2008.” DOE/EIA-0348(01)/2. p. 260. <http://www.eia.doe.gov/cneaf/electricity/st_profiles/sep2008.pdf>.3-9 Table 3-5. FY 2010 Financial Data for 70 U. S. Shareholder-Owned Electric Utilities

Profit Margin Net Income Operating Revenues
Investor-Owned Utilities 4.81% $27,728 $371,545

Regulated a 7.25% $12,341 $158,657
Mostly regulated b 8.50% $17,815 $175,218

Diversified c -16.78% -$2,429 $37,671

a 80%+ of total assets are regulated.

b 50% to 80% of total assets are regulated.

c Less than 50% of total assets are regulated. Source: Edison Electric Institute. “Income Statement: Q4 2010 Financial Update. Quarterly Report of the U.S.

Shareholder-Owned Electric Utility Industry.” <http://www.eei.org>.
Table 3-6. Aggregate Tax Data for Accounting Period 2009: NAICS 2211

Number of enterprises a 1,187
Total receipts (10 3 ) $323,522,443
Net sales(10 3 ) $328,017,143
Profit margin before tax 3.1%
Profit margin after tax 2.0%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2000–

2009.” <http://www.irs.gov/taxs tats/article/0,,id=167415,00.html>; (May 2, 2010).3-10Table 3-7. Key Enterprise Statistics by Employee Size for Electric Power Generation, Transmission, and Distribution(NAICS 2211): 2007Variable All Enterprises<20Employees20–99Employees100–499Employees500+EmployeesFirms 1,687 630 670 251 136Establishments 9,611 687 1,110 999 6,815Employment 503,134 3,622 31,455 42,527 425,530Receipts ($103) $440,342,284 $8,364,773 $21,825,969 $41,370,375 $368,781,167Receipts/firm ($103) $261,021 $13,277 $32,576 $164,822 $2,711,626Receipts/establishment($103)$45,817 $12,176 $19,663 $41,412 $54,113Receipts/employment($) $875 $2,309 $694 $973 $867Source: U.S. Census Bureau. 2010. “Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size: 2007.”<http://www.census.gov/csd/susb/susb07.htm>.3-11 3.2 Oil and Gas Extraction

3.2.1 Overview
Oil and gas extraction (NAICS 211) is an industry group within the mining sector (NAICS 21). It includes establishments that ope rate or develop oil and gas field properties through such activities as exploring for oil a nd gas, drilling and e quipping wells, operating onsite equipment, and conducting ot her activities up to the point of shipment from the property.

Oil and gas extraction consists of two i ndustries: crude petroleum and natural gas extraction (NAICS 211111) and na tural gas liquid extraction ( NAICS 211112). Crude petroleum and natural gas extraction is the larger industry; in 2002, it account ed for 93% of establishments and 75% of oil and ga s extraction revenues.

Industrial production in this indus try is particularly sensitiv e to hurricanes in the Gulf Coast. In September of both 2005 and 2008, produc tion dropped 14% from the previous month. (Figure 3-4).

From 2002 to 2007, revenues from crude petrol eum and natural gas extraction (NAICS 211111) grew over 117% to almost $215 billion ($2007) (Table 3-8). At the same time, payroll grew 55% and the number of employees grew by 48%. The number of establishments dropped by over 17%; as a result, the average establishm ent revenue increased by 162%. Materials costs were approximately 18% of revenue over the period.

From 2002 to 2007, revenue from natural ga s liquid extraction ( NAICS 211112) grew over 26% to about $42 billion (T able 3-9). At the same time , payroll dropped 18% and the number of employees dropped by 24%. The number of establishments dropped by 43%, resulting in an increase of revenue pe r establishment of about 122%.

3.2.2 Goods and Services Used
The oil and gas extraction industry has similar labor and tax requirements as the electric power generation sector. Extrac tion, support, power, and equipm ent requirements potentially associated with RICE (oil and gas extracti on, support activities, elec tric power generation, machinery and equipment rental and leasing, and pipeline transportation) represent around 8% of the value of services (Table 3-10).3-12 Figure 3-4. Industrial Pro duction Index (NAICS 211)

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

ID: G17/IP_MINING_AND_UTILITY_D ETAIL/IP.G211.S <http://www.feder alreserve.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
Employees 94,886 140,160
Establishments 7,178 5,956

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

Industry Series: Historical Sta tistics 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 th e United States: 2007 ” <http://factfinder.census.gov>; (April 27, 2010). 75 80 85 90 95 100 105 1101997‐011997‐061997‐111998‐041998‐091999‐021999‐071999‐122000‐052000‐102001‐032001‐082002‐012002‐062002‐112003‐042003‐092004‐022004‐072004‐122005‐052005‐102006‐032006‐082007‐012007‐062007‐112008‐042008‐092009‐022009‐072009‐12IndexValue(Jan2002=100)3-13 Table 3-9. Key Statistics: Natural Gas Li quid Extraction (NAI CS 211112) ($2007)

2002 2007 Revenue ($10 6 ) $33,579 $42,363 Payroll ($10 6 ) $607 $501 Employees 9,693 7,343

Establishments 511 291

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

Industry Series: Historical Sta tistics 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 th e United States: 2007 ” <http://factfinder.census.gov>; (April 27, 2010).
Table 3-10. Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002

Commodity Commodity Description Direct Requirements Coefficients a
V00200 Taxes on production and imports, less subsidies 8.93% V00100 Compensation of employees 6.67% 230301 Nonresidential maintenance and repair 6.36% 211000 Oil and gas extraction 1.91% 213112 Support activities for oil and gas operations 1.51% 221100 Electric power generation, transmission, and distribution 1.47% 541300 Architectural, engineering, and related services 1.24% 532400 Commercial and industrial machinery and equipment rental and leasing 1.20% 33291A Valve and fittings other than plumbing 1.10% 541511 Custom computer programming services 0.99%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output 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 progr ams provide national information on the
distribution of economic variable s by industry, location, and size of business. Throughout this section and report, we use the following definitions:

 Establishment : An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed.3-14  Receipts : Receipts (net of taxes) are define d as the revenue for goods produced, distributed, or services provided, in cluding revenue earned from premiums, commissions and fees, rents, interest, divi dends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

 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 th e establishment are the same for singleestablishment firms. For each multiestablishment firm, establishments in the same industry within a state are counted as one firm; the firm employment and annual payroll are summed from the associated establishments.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise; the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size designations are determined by the su mmed employment of all associated establishments.

As of 2007, there were 6,563 firms within the NAICS 211111 code, of which 6427 (98 percent) were considered small businesses (Table 3-11). Within NAICS 211111, large firms compose about 2 percent of the firms, but accoun t for 59 percent of employment and generate about 80 percent of estimated receipts listed under the NAICS. Within NAICS 211112, there are 139 firms, of which 95 (71 percent) were co nsidered small businesses (Table 3-12). As shown in this table, large firms compose 29 per cent of the firms, but account for 78 percent of employment and generate about 95 per cent of estimated receipts.

Enterprises within this industry generated $193 billion in total receipts in 2008. Including those enterprises withou t 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 Es tablishments: Crude Petroleum and Natural Gas Extraction Industry (NAICS 211111)
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 21: Mining:

Geographic Area Series: Industry Statistics for the State or Offshore Areas: 2007.” <http://factfinder.census.gov>; (January 27, 2010). Establishments by State

Less than 100

100 - 249

250 - 499

500 - 1,000

More than 1,0003-16 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: 2007.” <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): 2007

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

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

NAICS Description SBA Size Standard Small Firms Large Firms Total Firms Number of Firms by Firm Size Natural Gas Liquid Extraction 500 98 41 139

Total Employment by Firm Size 1,875 6,648 8,523

Estimated Receipts by Firm Size ($1000) 2,164,328 37,813,413 39,977,741 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million re quired 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 a nd receipts could not be split between small and large businesses because of non-discl osure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the United States, Al l Industries: 2007.” <http://www.census.gov/econ/susb/>3-18 Table 3-13. Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAICS 211

Number of 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/ta xstats/article/0,,id=167415,00.html>; (May 2, 2010).

3.3 Pipeline Transportation of Natural Gas

3.3.1 Overview
Pipeline transportation of natu ral gas (NAICS 48621) is an industry group within the transportation and warehousing se ctor (NAICS 48-49), but more specifically in the pipeline transportation subsector (486). It includes the transmission of natural gas as well as the distribution of the gas through a local ne twork to participating businesses.

From 2002 to 2007, natural gas transportation revenues fell by 29% to just over $16 billion ($2007) (Table 3-14). At the same time , payroll decreased by 14%, while the number of paid employees decreased by nearly 25%. The numb er of establishments also fell by 8% from 1,701 establishments in 2002 to 1,560 in 2007.

3.3.2 Goods and Services Used
The BEA reports pipeline transportation of natural gas only for total pipeline transportation (3-digit NAICS 486). In addition to pipeline trans portation of natural gas (NAICS 4862), this industry includes pi peline transportation of crude oil (NAICS 4861) and other pipeline transportation (NAICS 4869). However, the BEA data are likely representative of the affected sector since pipeline transportati on of natural gas accounts for 60% of NAICS 486
establishments and 66% of re venues (Figures 3-8 and 3-9).3-19 Table 3-14. Key Statistics: Pipeline Transporta tion of Natural Gas (NAICS 48621) ($2007)

Year 2002 2007 Revenue ($10 6 ) 16,368 20,797 Payroll ($10 6 ) 2,086 2,064 Employees 24,519 24,683
Establishments 1,560 1,479
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48: EC0748I1:

Transportation and Warehousing: Industry Series: Prelim inary Summary Statistics for the United States: 2002 and 2007.” http://factfinder.census.gov (January 27, 2010).

Figure 3-8. Distribution of Establishments within Pipeline Transportation (NAICS 486)
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48:

Transportation and Warehousing: Industry Series : Summary Statistics for the United States: 2002 <http://factfinder.census.gov>; (January 27, 2010).

In Table 3-15, we use the latest detailed benchmark input-output da ta report by the BEA (2002) to identify the goods and services used by pipeline transportation (NAICS 486). As shown, labor, refineries, and maintenance requirem ents represent significant share of the cost associated with pipeline transportation. Power a nd equipment requirements potentially associated with reciprocating internal co mbustion engines (electric power generation and distribution) represent less than 2% of the value of services. 60%

25%

15%

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

4862 Pipeline Transportation of Natural Gas 4869 Other Pipeline Transportation 4861 Pipeline Transportation of Crude Oil3-20 Figure 3-9. Distribution of Revenue with in 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 cl early concentrated in the two states closest
to the refineries in the Gulf of Mexico. In 2002, Texas and Louisiana contributed to 31% of all pipeline transportation establishments in the Un ited States (Figure 3-10) and 41% of all U.S. revenues. Other larger co ntributors with over 50 establishments in their states include Oklahoma, Pennsylvania, Kansas, Mississi ppi, and West Virginia.

According to 2002 U.S. Census data, about 86% of transportation of natural gas establishments were owned by corporations and about 8% were owned by individual proprietorships. About 6% were owned by partne rships (Figure 3-11). As shown in Table 3-16, the four largest firms accounted for nearly half of the establishments, and just over half, 51%, of total revenue. The 50 largest firms accounted for over 1,354 establishments and about 99% of total revenue. The average number of employees per establishment was approximately 17 across all groups of firms.

Enterprises within pipeline transportation (NAICS 486) generated $11.1 billion in total receipts in 2008. Includi ng those enterprises without net income , the industry averaged an aftertax profit margin of 9.6% (Table 3-17). 66%

19% 15%

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

4862 Pipeline Transportation of Natural Gas 4869 Other Pipeline Transportation 4861 Pipeline Transportation of Crude Oil3-21 Table 3-15. Direct Requirements for Pipe line Transportation (NAICS 486): 2002

Commodity Commodity Description Direct Requirements Coefficients a
V00100 Compensation of employees 14.78%

324110 Petroleum refineries 13.55% 230301 Nonresidential maintenance and repair 6.07% 211000 Oil and gas extraction 4.94% 333415 Air conditioning, refrigeration, and warm air heating equipment manufacturing 4.40%

561300 Employment services 4.26% 5416A0 Environmental and other technical consulting services 3.04% 541300 Architectural, engineering, and related services 3.04%

420000 Wholesale trade 2.79% 332310 Plate work and fabricated structural product manufacturing 2.72% 5419A0 All other miscellaneous professional, scientific, and technical services 2.48%

524100 Insurance carriers 2.38%

531000 Real estate 2.33% 52A000 Monetary authorities and depository credit intermediation 1.76% V00200 Taxes on production and imports, less subsidies 1.41% 541100 Legal services 1.19% 221100 Electric power generation, transmission, and distribution 1.13%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table,

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

The 2007 SUSB shows that 47% of all firms in this industry made under $5 million in revenue. Enterprises with revenue over $100 million provided an overwhelming share of employment in this indust ry (98%) (Table 3-18).3-22 Figure 3-10. 2002 Regional Distribution of Establishments: Pipeline Transportation (NAICS 486)
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49:

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

Figure 3-11. Share of Establishments by Legal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49:

Transportation and Warehousing: Subject Series—Estab & Firm Size: Legal Form of Organization for the United States: 2002. <http://factfinder.c ensus.gov>; (December 12, 2008). Establishments by State

Less than 15

15 - 39

40 - 79

80 - 149

More than 150

86%

8% 6%

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

Corporations Individual Proprietorships Partnerships3-23 Table 3-16. Firm Concentration for Pipeline Transportation of Natural Gas (NAICS 48621): 2002

Commodity Establishments Receipts/Revenue

Number of Employees Employees per Establishment Amount ($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 3-17. Aggregate Tax Data for A ccounting Period 7/07–6/08: NAICS 486

Number of enterprises a 321

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

Net sales (10 3 ) $10,210,083

Profit margin before tax 13.2% Profit margin after tax 9.6%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2004-

2007.” <http://www.irs.gov/ta xstats/article/0,,id=167415,00.html>; (May 2, 2010).3-24Table 3-18. Key Enterprise Statistics by Employee Size for Pipeline Transportation of Natural Gas (NAICS 48621): 2007Variable All Enterprises<20Employees20–99Employees100–499Employees 500+ EmployeesFirms 126 63 12 9 42Establishments 1.479 66 26 70 1,317Employment 24,683 241 382 1,479 22,581Receipts ($103) $20,796,681 N/A $518,341 $1,448,020 $18,498,143Receipts/firm ($103) $165,053 N/A $43,195 $160,891 $440,432Receipts/establishment($103)$14,061 N/A $19,936 $20,686 $14,046Receipts/employment($)$843 N/A $1,357 $979 $819Source: U.S. Census Bureau. 2011. Firm Size Data from the Statistics of U.S. Businesses, U.S. All Industries Tabulated by Employee Size: 2007.http://www2.census.gov/csd/susb/2007/usalli_r07.xls.4-1 Section 4 REGULATORY ALTERNATIVES, CO STS, AND EMISSION IMPACTS

4.1 Background

This section of the RIA includes a discussion of the regulatory alternatives considered for the proposed reconsidered rule, th e costs associated w ith these regulatory alternatives, and the impacts on affected emissions (both HAP and non- HAP). All impacts presented are for the year of full implementation, 2013. Costs in this section are in 2009$. Costs in 2010$ presented
elsewhere in the RIA are escalated values base d on the 2009$ costs presen ted in this section. Although the estimates presented are annualized, they should be understood as a “snapshot” in analyzing costs.

This proposal was developed to address certain issues that ha ve been raised by different stakeholders through lawsuits, several petitions for reconsideration of the 2010 RICE NESHAP
amendments and other communications. Afte r promulgation of the 2010 RICE NESHAP amendments, the EPA received several petitions fo r reconsideration, legal challenges, and other communications raising issues of practical implem entability, and certain factual information that had not been brought to the EPA’s attention duri ng the rulemaking. The EPA has considered this
information and believes that amendments to th e rule to address certain of these issues are appropriate. Therefore, the EPA is proposing amendments to the national emission standards for hazardous air pollutants for stati onary reciprocating internal combustion engines under section 112 of the Clean Air Act. The proposed amendmen ts 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 sp arsely 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 fo r existing stationary emergency area source engines to be used for peak shaving and non-emergency demand response as part of the pre-existing allowance fo r such engines to be used for non-emergency use for 50 hours annually. In addition, the EPA is pr oposing, in both the NESHAP and in the new source performance standards for stationary inte rnal combustion engines to increase the hours that stationary emergency engines may be us ed for emergency demand response. The proposed
amendments also correct minor mistakes in th e pre-existing regulations . The full preamble for
the final SI RICE NESHAP and the rule itself can be reviewed at http://www.epa.gov/ttn/atw/rice/fr20au10.pdf

.4-2 4.2 Proposed Amendments to SI RICE NESHAP

4.2.1. Total Hydrocarbon Compliance (THC) Demonstration Option

4.2.1.1. Background

Currently, SI 4SRB non-emergency engines gr eater than 500 HP and located at major sources and existing SI 4SRB non-emergency engi nes greater than 500 HP located at area sources have the option of meeting either a formaldehyde percent reduc tion or a formaldehyde concentration standard. Formaldehyde was establis hed in the original 2004 RICE NESHAP as an appropriate surrogate for HAP emissions from 4SRB engines based on industry test data available at that time. Based on testing conduc ted at Colorado State University (CSU) of stationary lean burn engines, the EPA was able to establish CO as a surrogate for HAP for lean burn engines. Rich burn engines we re not tested at CSU and the data the EPA had available at
the time that were used to set the standard s for rich burn engines did not support the same relationship between CO and HAP reductions for rich burn engines. Therefore, the EPA was unable to establish CO as a surrogate for HAP emissions for rich burn engines and the emission standard for rich burn engines was specified in terms of formaldehyde, the hazardous air pollutant emitted in the largest quantity from stationary engines.

The EPA has previously acknowledged that it is significantly more expensive and difficult to test for formaldehyde versus CO, but ha s been unable in the past to support including the same flexibility for rich burn engines as is cu rrently in the rule for lean burn engines with the option to meet the standards in terms of eith er formaldehyde or CO. For these reasons and expecting that new data for rich burn engines may become available in the future for the EPA to review and reassess possible su rrogates 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 exis ting engines at area sources in 2009 (74 FR 9698). Specifically, the EPA
solicited comment on whether it would be appropriate to include an alternative standard in terms
of VOC and asked that commenters submit da ta supporting the relatio nship 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 wa s not appropriate to adopt an a lternative standard in terms of THC (or VOC) for rich burn engines and disc ussed the reasons why in the 2010 responses to4-3 comments. Compliance with the formaldehyde sta ndard in the rule is, therefore, currently demonstrated by initial and continuous performance testing for formaldehyde.

On October 19, 2010, engine manufacturer Dresser-Waukesha submitted a petition for reconsideration of the formaldehyde require ments. The EPA granted the petition for reconsideration on January 5, 2011. (In a ddition, on November 3, 2010, the Engine Manufacturers Association submitted a petition for j udicial review of these requirements.) In the petition for reconsideration, Dresser-Waukesha ar gued that formaldehyde is difficult and costly to measure. The petition requested that the HAP surrogate for 4SRB engines should be THC rather than formaldehyde. Dresser-Waukesha submitted data from testing it conducted illustrating that THC reduction across the catalyst is an appropriate surrogate for HAP reduction across the catalyst. According to the petitioner, testing for THC is easier and less costly and would substantially reduce the burden of the rule for owners and operators of these engines. Testing for formaldehyde emissions could cost more than double that of testing for THC
emissions and on a nationwide basis the EPA estimat es that replacing formaldehyde testing with THC testing would result in substantial comp liance cost savings annually while achieving the
same reduction in HAP emissions.

The EPA has reviewed the data submitted by Dresser-Waukesha. The data provided indicate that a strong relationshi p exists between per centage reductions of THC and percentage reductions of formaldehyde (the surrogate fo r HAP emissions in the NESHAP) on rich burn engines using non-selectiv e catalytic reduction (NSCR). Data analyzed by the EPA indicate that if the NSCR is reducing THC by at least 30 percent from 4SRB engines, formaldehyde emissions are guaranteed to be reduced by at least 76 perc ent, which is the percentage reduction required for the relevant engines. Ind eed, the percentage reduction of formaldehyde is invariably well above the 76 percent level, and is usually above 90 percent. Ther efore, the EPA agrees with the petitioner that for SI 4SRB engines using NSCR and meeting the NESHAP by showing a percentage reduction of HAP, it would be appr opriate to allow sources to demonstrate compliance with the NESHAP by showing a THC re duction of at least 30 percent. Including an optional THC compliance demonstration opti on would reduce the burden of compliance significantly while continuing to achieve the sa me level of HAP emission reduction because the
emission standards would remain the same. Cons equently, the EPA is proposing amendments to allow owners and operators of certain stationary 4SRB engines (i.e., the ones currently subject to a formaldehyde percent reduction requirement) to show compliance w ith an optional THC compliance demonstration option. The specific am endments 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 demonstrati ng 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 exis ting stationary 4SRB non-emergency engines greater than 500 HP that are locat ed at area sources of HAP emi ssions that choose to meet the formaldehyde percent reduction requir ement of 76 percent or more.

Based on the arguments and evidence presente d in the petition discussed above, the EPA is proposing to add a compliance demonstration option for stationary 4SRB engines meeting a 76 percent or more formaldehyde reduction. The co mpliance demonstration option would be an alternative to the existing met hod of demonstrating compliance with the formaldehyde percent reduction standard, which is to test engines for formaldehyde. The alternative for owners and operators of 4SRB engines meeting a 76 percent or more formaldehyde reduction would be to test their engines for THC showi ng that the engine is achieving at least a 30 percent reduction of
THC emissions.

Under the proposed amendments, existing and new stationary 4SRB e ngines greater than 500 HP and located at major sources would stil l be required to reduce formaldehyde emissions by 76 percent or more or limit the concentration of formaldehyde in the stationary RICE exhaust to 350 parts per billion by volume, dr y basis or less at 15 percent oxygen (O 2 ). However, owners and operators choosing to meet the formaldehyde concentration limit would not have the THC demonstration compliance option, because EPA c ould not verify a clear relationship between
concentrations of THC and concentrations of formaldehyde in exhaust from these SI 4SRB engines. The EPA is proposing that existing stationary 4SRB non-emer gency engines greater
than 500 HP located at area sources located in populated areas be subj ect to an equipment standard and required to insta ll a catalyst. These engines woul d be subject to testing to demonstrate initially and on an ongoing basis that the catalyst is reducing CO by 75 percent or more, or alternatively that THC emissions are being reduced by 30 percent or more.

Owners and operators of existing stationary 4SRB engines less than or equal to 500 HP who are required to limit the concentration of fo rmaldehyde 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 demonstrate compliance using THC and must continue to demonstrate compliance by testing for formaldehyde following the methods and procedures specified in the rule.4-5 Owners and operators opting to use the THC compliance demonstration method must demonstrate compliance by showing that the aver age reduction of THC is equal to or greater than 30 percent. Owners and operators of 4SRB st ationary RICE complying with the requirement to reduce formaldehyde emissions and demonstrating compliance by using the THC compliance demonstration option must conduct performance testing using Method 25A of 40 CFR part 60, appendix A – Determination of Total Gaseous Or ganic Concentration Using a Flame Ionization Analyzer. Measurements of THC at the inlet a nd the outlet of the NSCR must be on a dry basis and corrected to 15 percent O2 or equivalent ca rbon dioxide content. To correct to 15 percent O2, dry basis, owners and opera tors must measure oxygen using Me thod 3, 3A or 3B of 40 CFR part 60, appendix A, or ASTM Method D6522-00 (2005) and measure moisture using Method 4 of 40 CFR part 60, appendix A, or Test Met hod 320 of 40 CFR part 63, appendix A, or ASTM D6348-03. Because owners and operators are comp lying with a percent reduction requirement,
the method used must be suitable for the entire range of emis sions since pre and post-catalyst emissions must be measured. Method 25A is cap able 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 per cent by using Method 25A of 40 CFR part 60, appendix A to demonstrate compliance with the formaldehyde percent reduction in 40 CFR part 63, subpart
ZZZZ.
4.2.2. Proposed Amendment - Emergency Demand Response/Peak Shaving

The EPA is proposing to revise the current provisions for stationary engines used for emergency demand response operation. The provisi ons the EPA is proposing to amend are in §§63.6640(f) and 63.6675 of 40 CFR part 63, su bpart ZZZZ. Currentl y, §63.6640(f)(1)(iii) allows a maximum of 15 hours per year to be spent towards demand response operation under certain qualifying conditions. Al so, §63.6640(f)(1)(ii) currently includes an allowance of 100 hours per year for purposes of maintenance check s and readiness testing. The EPA is proposing that owners and operators of stationary emergenc y RICE be permitted to operate their engines as part of an emergency demand response program within the 100 hours per year that is permitted for maintenance and testing in §63.6640(f)(1)(ii). Owners and operato rs of stationary emergency engines can operate for emergency demand res ponse during periods in which the regional transmission authority or equiva lent balancing author ity and transmission operator has declared
an EEA Level 2 as defined in the North Ameri can Electric Reliability Corporation Reliability Standard EOP-002-3, Capacity and Energy Emer gency 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 to wards the 100 hours per y ear. If the total time spent for demand response operation and maintena nce and testing exceeds 100 hours per year the engine will not be considered an emergency engi ne under this subpart and will need to meet all requirements for non-emergency engines. The EP A is recognizing that these engines may be called to operate not only by the regional transm ission operator or equivalent to maintain the reliability of the bulk power system, but also by the local transmission and distribution system operators to support the local power systems.

For stationary emergency engines above 500 HP that were installed prior to June 12, 2006, there is currently no emergency demand res ponse allowance and there is no time limit on the use of emergency engines for routine test ing and maintenance in §63.6640(f)(2)(ii). Those engines were not the focus of the 2010 RICE NESHAP amendments; therefore, the EPA did not make any changes to the requirements for thos e 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 a nd SI engines in 40 CFR part 60, subparts IIII and JJJJ, respectively, to provide the sa me allowance for stationary emergency engines for emergency demand response operation as for engines subject to the RICE NESHAP. The NSPS regulations currently do not include such an allowance for emergency demand response operation. For the reasons discusse d as to why the EPA finds it appropriate to allow stationary emergency engi nes to participate in emergency demand response programs and remain being considered emergency units, and fo r consistency across engine regulations, the EPA is proposing to add an emergency demand response allowance under the NSPS regulations. Consequently, the EPA is proposing to revise the existing language in §§60.4211(f) and 60.4219 of 40 CFR part 60, subpart II II, and §§60.4243(d) and 60.4248 of 40 CFR part 60, subpart JJJJ, to specify that emergency engines may partic ipate in demand response programs for up to 100 hours per year, including hours spent towards mainte nance and testing of th e emergency engines.

In addition to the changes the EPA is proposing related to emergency demand response operation, the EPA is also including a further pr ovision for owners and operators of existing stationary emergency RICE located at area sources for the reasons discussed. Paragraph §63.6640(f) currently allows owners and operators of emergency stationary RICE to operate their engine for 50 hours per year in non-emergenc y situations. As curren tly written, the 50 hours4-7 per year for non-emergency situations cannot be used for peak shaving or to generate income for a facility to supply power to an electric grid or otherwise supply power as part of a financial arrangement with another entity; except that owners and operators of certain emergency engines may operate the engine for a maximum of 15 hours per year as part of an emergency demand response program. As discussed, the 15 hours pe r year allowance for emergency engines to participate in emergency demand response progra ms is being increased to 100 hours per year, but will also include hours spent towards main taining and conducting readiness testing of the emergency engines. However, additionally, the EP A is also proposing that stationary emergency engines located at area sources be permitted to apply the 50 hours per year that is currently allowed under §63.6640(f) for non-emergency operation towards any non-emergency operation, including operation as part of a financial agreement with another entity. The peak shaving allowance would expire in 2017. The EPA is specify ing that the power can only be used at the facility or towards the local system, and the engi ne can only be operated for peak shaving as part of a program with the local distribution system operator. The EPA is al so clarifying that an engine that exceeds the calendar year lim itations on non-emergency operation, including emergency demand response or peak shaving, wi ll be considered a non-emergency engine and subject to the requirements for non-emergency e ngines for the remaining life of the engine.

To estimate emissions from emergency engi nes the EPA has previously estimated that these types of engines would on average operate for 50 hours pe r year. The average hours of operation for emergency engines is not expected to change based on the proposed amendments and 50 hours per year is still believed to be representative of emergency engine operation. Therefore, the emissions previously calculated remain appropriate. In terms of any revenue generated from participation in demand response and peak shaving programs, the EPA expects owners and operators will benefi t financially, however, the EPA does not know to what extent. The EPA expects there will be savings and/or income generated through participation in emergency demand response programs and peak shaving operation, but the EPA has not accounted for any potential revenu e in estimating the costs and benefits of the proposed amendments. It is uncertain how frequently stat ionary emergency engines would operate if they are called upon. Other factors, such as the annual revenue from demand response programs (which varies), are also uncertain making it problem atic to estimate the economic benefit of such programs. As such, the EPA has not estimated any costs associated with the emergency engine
amendments.4-8 4.2.3 Proposed Amendment - Non-Emergency Statio nary SI RICE Greater than 500 HP Located
at Area Sources

4.2.3.1. Background

The EPA is also proposing to amend the requ irements that apply to existing stationary non-emergency 4 stroke SI RICE greater than 5 00 HP located at area sources of HAP emissions, which are generally natural gas fired engines. Currently, the RICE NESHAP requires owners and operators of such engines to 1) either meet a CO concentr ation limit of 47 parts ppmvd at 15 percent O2 or reduce emissions of CO by 93 percen t or more, if the engines are 4SLB; and 2) to meet a formaldehyde concentration limit of 2.7 ppmvd at 15 percent O2 or reduce formaldehyde emissions by 76 percent or more, if the engines are 4SRB. In both cases, the EPA expects that the standards would be met using aftertreatme nt; oxidation catalysts for 4SLB engines and NSCR for 4SRB engines. In addition to these em ission 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 fo r existing stationary SI engine s 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 Amer ican Petroleum Institute (EPA-HQ-OAR2008-0708-0582), the Interstate Natural Gas As sociation of America (EPA-HQ-OAR-2008- 0708-0584), and the Gas Processors Associ ation (EPA-HQ-OAR-2008-0708-0587) requesting
that the EPA reconsider the re quirements of the final rule. The petitioners expressed many
similar concerns. As relevant to this rulemaking, petitioners stated that the EPA did not take into account the difference in population density and subsequently did not consider the difference in health impacts in remote versus more heavil y populated locations. In petitioner’s opinion, there should be less concern about engine s that are located farther away from people; the petitioners
believed that the EPA has substantial latitude in requiring less stringent standards for owners and operators of stationary e ngines in remote areas.

While the EPA does not share all of the views of the petitioners re garding the difference between engines based on their location, the EPA does believe that it is reasonable to create a subcategory of existing stationa ry SI 4SLB and 4SRB engines above 500 HP located in areas remote from human activity. Engines located in re mote areas that are not close to significant human activity may be difficult to access, may no t have electricity or communications, and may
be unmanned most of the time. The costs of the emission controls, testing, and continuous monitoring requirements may be unreasonable when compared to the HAP emission reductions4-9 that would be achieved, consider ing that the engines are in sp arsely populated areas. The EPA believes that establishing a subcategory for SI engi nes at area sources of HAP located in sparsely populated areas accomplishes the agency’s goals a nd is adequate in protecting public health.

The EPA is proposing to subcategorize sp arsely populated engine s using the existing DOT pipeline classification system. This system classifies locations based on their distance to pipelines covered by the Pipeline and Hazardous Materials Safety Administration safety regulations. The DOT system de fines a class location unit as an onshore area that extends 220 yards or 200 meters on either si de of the centerline of any continuous 1-mile (1.6 kilometers) length of pipeline. The DOT approach further cl assifies pipeline locati ons into Class 1 through Class 4 locations based on the number of buildings intended for human occupancy. A Class 1 location is defined as an offshore area or any cl ass location unit that has 10 or fewer buildings intended for human occupancy. Stak eholders from the oil and gas industry have indicated to the EPA that the DOT system is well-established an d there would be substantial overlap between engines affected by the rule and covered by the DOT pipeline classification system. Incorporating this approach would also crea te harmonization between the EPA and DOT and would reduce the implementation and enforcement burden for states. Implementation for affected
sources would also be less burdensome because the system is already in place and used by industry and covers the majority of these engines. Stakeholders have indicated they are required
to review the class loca tion status of pipeline segments a nnually. The EPA believes this approach is reasonable for defining the subcategory of remo te engines for those engines that are associated with DOT-regulated 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 fe wer buildings intended for human occupancy.

The EPA is proposing management practices as generally available control technologies for existing stationary SI 4SLB and 4SRB area source non-emergency engines located in sparsely populated areas. Given the remote locat ion of the engines from human activity, the EPA believes that it is appropriate not to include re quirements that would neces sitate aftertreatment and extensive testing and monitoring. The EPA has previously estimated that the costs of oxidation catalyst for existing 4SLB and 4SRB engines above 500 HP at area sources are $310 and $150 million, for capital and annual costs, resp ectively. The capital and annual costs of the RICE NESHAP for existing 4SLB and 4SRB engi nes above 500 HP at area sources would be $30 million and $12 million, respectively, if these proposed amendments are incorporated into the rule. Creating a subcategory of these engines for the ones locat ed in sparsely populated areas4-10 and not mandating emission controls would signifi cantly 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 proposin g an equipment standard that requires the installation and operatio n of a catalyst that will have to be tested initially and annually to ensure that the catalyst is working pr operly and reducing emissions as required. In addition, these units will be required to have devices to shut down the engine if the catalyst is exposed to dangerous temperatures or have continuous monitoring eq uipment installed to record catalyst inlet temperatures. The EPA is proposing shorter te st duration and less rigorous methods than currently required while still ensuring that HAP reductions remain at expected levels for these engines located in populated areas. The specific amendments the EPA is proposing are discussed
below.

4.2.3.2. What are the Proposed Amendments?

Owners and operators of engines in sparse ly populated areas w ould have to conduct a
review of the surround ing area every 12 months to determ ine if the nearby population has changed. Stakeholders have indi cated that they visit these f acilities annually at a minimum. If the engine no longer meets the criteria for a sp arsely populated area the owner and operator must within 1 year comply with the emission standa rds specified below for populated areas. Owners and operators of existing stationary 4SLB and 4S RB greater than 500 HP at area sources that are in sparsely populated areas as described above would be requ ired to perform the following:

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

•Inspect spark plugs every 1,440 hours of opera tion or annually, whichever comes first, and replace as necessary; and

•Inspect all hoses and belts every 1,440 hours of operation or annually, whichever comes first, and replace as necessary.

Sources have the option to use an oil analys is program as described in §63.6625(i) of the rule in order to extend the specified oil change requirement. The oil analysis must be performed at the same frequency specified for changing th e oil in Table 2d of the rule. The analysis program must at a minimum analyze the follo wing three parameters: Total Acid Number, viscosity, and percent water content. The condemn ing limits for these parameters are as follows: Total Acid Number increases by more than 3.0 milligrams of potassium hydroxide per gram4-11 from Total Acid Number of the oil when new; viscosity of the oil has changed by more than 20 percent from the viscosity of the oil when new; or percent water content (by volume) is greater
than 0.5. If all of these condemn ing limits are not exceeded, the engine owner or operator is not required to change the oil. If any of the limits are exceeded, the engine owner or operator must change the oil within 2 days of receiving the resu lts of the analysis; if the engine is not in operation when the results of the analysis are rece ived, the engine owner or operator must change the oil within 2 days or before commencing oper ation, 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 analysis, and the oil changes fo r the engine. The analysis pr ogram must be part of the maintenance plan for the engine.

Owners and operators of existing stationary 4SLB and 4SRB area source engines above 500 HP in sparsely populated area s would also have to operate a nd maintain the stationary RICE and aftertreatment control device (if any) according to the manufacturer's emission-related written instructions or develop their own mainte nance plan which must provide to the extent practicable for the maintenance and operation of the engine in a manner consistent with good air pollution control practice for minimizing emissions.

For engines in populated areas, i.e., existi ng stationary 4SLB a nd 4SRB non-emergency engines greater than 500 HP at area sources that are located on DOT Class 2 through Class 4 pipeline segments or, for engines not associated with pipelines, that do not meet the 0.25 mile radius with 5 or less buildings criteria, the EPA is proposing to adopt an equipment standard requiring the installation of a catalyst to re duce HAP emissions. Owners and operators of existing area source 4SLB non-emergency engines greater than 500 HP in populated areas would be required to install an oxidation catalyst. Owners and operators of existing area source 4SRB non-emergency engines greater than 500 HP in populated areas would be required to install NSCR. Owners and operators must c onduct an initial test to demonstr ate that the engine achieves at least a 93 percent redu ction in CO emissions or a CO c oncentration 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 engi ne is a 4SRB engine. The initial test must
consist of three test runs. Each test run must be of at leas t 15 minute duration, except that each test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist of one measurement cycle as defined by the method and include at least 2 minutes of test data phase measurement. To measure CO, emission sources must use the CO methods already4-12 specified in subpart ZZZZ, or the proposed a ppendix 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 type s must also use a high temperature shutdown device that detects if the catalyst inlet temperat ure is too high, or, alte rnatively, the owner or operator can monitor the catalyst inlet temperature continuously and maintain the temperature within the range specified in the rule. For 4SLB engines the catalyst inlet temperature must
remain at or above 450°F and at or below 1,350°F. For 4SRB engines the temperature range must be greater than or equal to 750°F and less th an or equal to 1,250°F at the catalyst inlet.

Owners and operators must in addition to th e initial performance test conduct annual checks of the catalyst to ensure proper catalyst activity. The annua l check of the catalyst must at a minimum consist of one 15-minute run using th e methods discussed above, except that each test run conducted using the proposed appendix A to 40 CFR part 63, subpart ZZZZ must consist of one measurement cycle as defined by the method and include at least 2 minutes of test data phase measurement. Owners and operators of 4SLB engines must demonstrate during the catalyst activity test that the catalyst achieves at least a 93 percent reduction in CO emissions or that the engine exhaust CO emissions are no mo re than 47 ppmvd at 15 percent O2. Owners and operators of 4SRB engines must demonstrate that their catalyst is reducing CO emissions by 75 percent or more, or alternatively, that THC emi ssions are being reduced by at least 30 percent during the catalyst activity check.

If the emissions from the engine do not exceed the levels required for the initial test or annual checks of the catalyst, then the catalyst is considered to be working properly. If the emissions exceed the specified pollutant levels in the rule, the exceedance(s) is/are not considered a violation, but the owner or operator would be required to sh ut down the engine and take appropriate corrective action (e.g., repairs, cl ean or replace the cataly st, as appropriate). A follow-up test must be conducted within 7 days of the engine bei ng started up again to
demonstrate that the emission le vels are being met. If the retest shows that the emissions continue to exceed the specified levels, the stati onary RICE must again be shut down as soon as safely possible, and the engine may not operate, except for purposes of start-up and testing, until the owner/operator demonstrates through testin g that the emissions do not exceed the levels specified.4-13 4.2.3.3 Compliance Date

The EPA has received some questions re garding whether the compliance dates for engines impacted by the 2010 amendments and th is proposed reconsideration will be extended. Affected sources that may be impacted by th is action have expresse d concern about having sufficient time to comply with the rule by the compliance date, which is May 3, 2013, for existing stationary CI RICE and October 19, 201 3, for existing stationa ry SI RICE. Sources impacted by this reconsideration are particularly concerned with compliance in the event that the EPA does not finalize changes that are substantially similar to the changes being proposed in this
action. The EPA does not intend to extend the May 3, 2013, and October 19, 2013, compliance dates, because there are many e ngines that must meet those compliance dates that are not impacted by this reconsideration. However, we note that sources that are affected by the reconsideration and that may need additional ti me to install controls to comply with the applicable requirements can request up to an additio nal year to install controls, as specified in 40 CFR 63.6(i).

4.3 What Are the Pollutants Regulated by the Rule?
The proposed reconsideration rule regulates emissions of HAP. Available emissions data show that several HAP, which are formed during the combustion process or which are contained within the fuel burned, are emitted from stationary engines. The HAP which have been measured in emission tests conducted on SI stationary RICE include: formaldehyde, acetaldehyde, acrolein, methanol, benzene, toluene, 1,3-butad iene, 2,2,4-trimethylpentane, hexane, xylene, naphthalene, PAH, methylene chlo ride, and ethylbenzene. EPA desc ribed 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 contribu te significantly to air pollu tion, which may reasonably be anticipated to endanger pub lic health or welfare.

For the standards included in this action, EPA believes that previous determinations regarding the appropriateness of using fo rmaldehyde 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.4-14 In addition to reducing HAP, the emission cont rol technologies that will be installed on stationary RICE to reduce HAP will also redu ce CO and VOC, and for rich burn engines will
also reduce NOx.

4.4 Cost Impacts

4.4.1 Introduction
EPA has determined that oxidation catalysts for two-stroke lean burn (2SLB) and fourstroke lean burn (4SLB) engines, and non-sele ctive catalytic reduction (NSCR) for four-stroke rich burn (4SRB) engines are appl icable controls for HAP reduction from existing stationary SI RICE. To determine the capital and annual costs for these control technologies, equipment cost information was obtained from industry groups 2 and vendors and manufact urers 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 opti ons. Using this cost data, annualized cost and capital cost equations for oxidation catalysts and NSCR were developed.
4.4.2 Control Cost Methodology
The following sections describe the methodology us ed to derive the to tal capital and total annual costs for each of the control technology options. These methodologies were used to calculate total capital and total annual costs when only purchased equipment costs were available (e.g., vendor equipment costs). The methodologies were not used for cost data provided by industry groups because they included a breakdown of the actual total ca pital and total annual costs. A summary of the methodologies, equations, and assumptions used to estimate the total capital and total annual costs for some of the co st 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 purch asing and installing the control equipment. The direct cost incl udes the cost of purchas ing the equipment and instrumentation, cost of shipping, and the cost of installing the control e quipment. The indirect cost includes the costs for engineer ing, contractor fees, testing cost s, and also includes costs for contingencies, such as additional modifications, or delays in startup. The total capital cost equation can be summarized as follows:

Total Capital Cost (TCC) = Direct Costs (DC) + Indirect Costs (IC)

2 Reciprocating Internal Combustion Engine National Emission Standards for Hazardous Air Pollutants (RICE NESHAP) Proposed Revisions – Emission Control Costs Analysis Background for “Above the Floor” Emission Controls for Natural Gas-Fired RICE, Innovative Envi ronmental Solutions Inc., October 2009. (EPA-HQ-OAR2008-0708-0279).4-15 The direct costs include the costs of purchasing and installing the control equipment and can be summarized using the following equation;

DC = Purchased Equipment Cost (PEC) + Direct Installation Costs (DIC).

A summary of the cost assumptions for PEC includes the following:

 Control Device and Auxiliary Equipment (EC);

 Instrumentation (10% of EC);

 Sales Tax (3% of EC);

 Freight (5% of EC);

and can be summarized as:

PEC = 118% EC.

A summary of the cost assumptions for DIC includes the following:

 Foundations and Supports (8% of PEC);

 Handling and Erection (14% of PEC);

 Electrical (4% of PEC);

 Piping (2% of PEC);

 Insulation for Ductwork (1% of PEC);

 Painting (1% of PEC);

and can be summarized as:

DIC = 30% PEC = 0.3 PEC.

Therefore, the direct costs can be simplified using the following equation:

DC = PEC + 0.3 PEC = 1.3 PEC.

The indirect costs include the costs of engineerin g and contractor fees and contingencies and can be summarized using the following equation:

IC = Indirect Installation Co sts (ICC) + Contingencies (C).4-16 A summary of the cost assumptions for ICC includes the following:

 Engineering (10% of PEC);

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

 Contractor Fees (10% of PEC);

 Startup (2% of PEC);

 Performance Test (1% of PEC);

and can be summarized as:

IIC = 28% PEC = 0.28 PEC.

A summary of the cost assumpti ons for C includes the following:

 Equipment Redesign and Modifications;

 Cost Escalations;

 Delays in Startup;

and is assumed to be:

C = 3% PEC = 0.03 PEC.

Therefore, the IC can be summari zed using the following equation:

IC = 0.28 PEC + 0.03 PEC = 0.31 PEC,

and the simplified TCC equa tion 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 equipmen t. The direct annual cost incl udes 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 co ntrol equipment, administrative charges, and the capital recovery of the control technology. The total annual co st equation can be summarized as
follows:4-17 Total Annual Cost (TAC) = Direct Annual Co sts (DAC) + Indirect Annual Costs (IAC).

The DAC includes the following parameters:

 Utilities;

 Operating Labor;

 Maintenance;

 Annual Compliance Test;

 Catalyst Cleaning;

 Catalyst Replacement;

 Catalyst Disposal.

The IAC includes the following parameters:

 Overhead;

 Fuel Penalty;

 Property Tax;

 Insurance;

 Administrative Charges;

 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 mainte nance labor cost, and the cost for annual performance testing or downtime or allowance for catalyst washing. Actu al 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 cost s: administrative, fuel penalty, and capital recovery. Again, cost data from the industry groups was used to estimate these costs for each of the control technologies. No fuel penalty wa s estimated for the oxidation catalyst control technologies, because this control technology does not increase the fuel usage of the SI engine.4-18 4.4.3 Control Cost Equations
Control cost equations were developed fo r 2SLB oxidation catalyst, 4SLB oxidation catalyst, and a NSCR for 4SRB engines using the tota l capital cost and total annual cost data for each control technology. Control cost equations for 2SLB and 4SLB oxidation catalysts were developed separately because the 2SLB oxidatio n catalyst requires a premium catalyst to reduce the HAP compounds because of the low e xhaust temperature of 2SLB engines.
4.4.3.1 2SLB Oxidation Catalyst
The 2SLB oxidation catalyst is an effective control technology that reduces HAP emissions from a 2SLB SI engine by oxidi zing organic compounds using a catalyst. The oxidation catalyst unit contains a honeycomb-like structure or substrate with a large surface area that is coated with a premium active catalyst la yer such as platinum or palladium. The oxidation catalyst works by oxidizing car bon monoxide (CO) and gaseous hydrocarbons (HAP) in the exhaust gas to carbon dioxide (CO 2 ) and water. The reduction of CO and HAP varies depending on the type of catalyst used and the exhaus t temperature of the pollutant stream.

The cost of retrofitting an oxidation catalyst to an existing 2SLB engine was estimated using cost data obtained from vendors and industry groups covering engines ranging from 58 horsepower (HP) to 4,670 HP. An equipment life of 10 years and an interest rate of 7 percent were used to estimate the capital recovery of the c ontrol technology and the fuel penalty was assumed to be negligible. The cost equations are presented in 2009 dollars.

The total annualized cost equation for retrofit ting an oxidation catalyst on a 2SLB engine
was estimated to be:

2SLB Oxidation Catalyst Total Annual Cost = $11.4 x HP + $13,928

where

HP = engine size in HP.

The linear equation has a correlation coefficient of 0.8046, which shows the data fits the equation closely. Therefore, this equation was us ed to estimate annualized cost for an oxidation catalyst on a 2SLB engine.

The total capital cost equation for retrofitti ng an oxidation catalyst on a 2SLB engine was
estimated to be:4-19 2SLB Oxidation Catalyst Total Capital Cost = $47.1 x HP + $41,603

where

HP = engine size in HP.
4.4.3.2 4SLB Oxidation Catalyst
The 4SLB oxidation catalyst is an effective control technology that reduces HAP emissions from a 4SLB SI engine by oxidi zing organic compounds using a catalyst. The oxidation catalyst unit contains a honeycomb-like structure or substrate with a large surface area that is coated with a premium active catalyst la yer such as platinum or palladium. The oxidation catalyst works by oxidizing CO and gaseous hyd rocarbons (HAP) in the exhaust gas to CO 2 and water. The reductions of CO and HAP vary de pending on the type of catalyst used and the exhaust temperature of the pollutant stream.

The cost of retrofitting an oxidation catalyst to an existing 4SLB engine was estimated using cost data obtained from vendors and industry groups covering engines ranging from 400 HP to 8,000 HP. Again, an equipment life of 10 years and an interest rate of 7 percent were used to estimate the capital recovery of the control technology and the fuel penalty was assumed to be negligible. The cost equations are presented in 2009 dollars.

The total annualized cost equation for retrofit ting an oxidation catalyst on a 4SLB engine
was estimated to be:

4SLB Oxidation Catalyst Total Annual Cost = $1.81 x HP + $3,442

where

HP = engine size in HP.

The linear equation has a correlation coefficient of 0.9779, which shows the data fits the equation very closely. Therefore, this equation was used to estimate annualized cost for an oxidation catalyst on a 4SLB engine.

The total capital cost equation for retrofitting an oxidation catalyst on a 4SLB SI engine was
estimated to be:

4SLB Oxidation Catalyst Total Capital Cost = $12.8 x HP + $3,0694-20 where

HP = engine size in HP.

A summary of the cost calcula tions, regression analyses, and gr aphical representations of the annual and capital cost data are presented in Appe ndix A of the cost memo that is the basis for the cost data presented in this RIA. 3

4.4.3.3 Non-Selective Catalytic Reduction
The NSCR or three-way catalyst is used to control HAP emissions from 4SRB engines. In addition to HAP reductions, NSCR also reduces the emissions of nitrogen oxides (NOx), CO, and other hydrocarbons (HC). The reduction of HAP and CO takes place through an oxidation
reaction that converts HAP to CO 2 and water and converts CO to CO 2 . The conversion of NOx takes place through a reduction of the NOx to nitrogen gas and oxygen.

The cost of retrofitting an NSCR on an ex isting 4SRB engine was estimated based on cost data received from vendors and industry groups. A linear regressi on analysis was done on
the data set and the linear e quation for annualized cost was;

NSCR Annual Cost = $4.77 x HP + $5,679

where

HP = engine size in HP.

The linear equation has a co rrelation coefficient of 0.7987, which shows an acceptable representation of the cost data. Th erefore, this equation was used to estimate annualized cost for retrofitting the NSCR control t echnology on 4SRB engines.

The capital cost equation for re trofitting an air-to-fuel ratio (AFR) controller and NSCR on a 4SRB engine was estimated to be:

NSCR Capital Cost = $24.9 x HP + $13,118

where

HP = engine size in HP.

3 Memorandum from Bradley Nelson, EC/R to Melanie Ki ng, EPA. OAQPS/SPPD/ESG. Impacts Associated with NESHAP for Existing Stationary SI RICE. June 29, 2010.4-21 4.4.4 Summary
Table 4-1 presents a summary of the annual and capital control co sts as a function of engine size for the control technologies applicable to existing stationary SI engines, as discussed
in this memorandum.
Table 4-1. Summary of Annual and Capital Costs Equations for Existing Stationary SI Engines

HAP Control Device Annual Cost ($2009) Capital Cost ($2009) 2SLB Oxidation Catalyst $11.4 x HP + $13,928 $47.1 x HP + $41,603 4SLB Oxidation Catalyst $1.81 x HP + $3,442 $12.8 x HP + $3,069 NSCR $4.77 x HP + $5,679 $24.9 x HP + $13,118

A summary of the annual and capita l costs associated with the rule and obtained using the methodology described above are presen ted in Tables 4-2 to 4-5 below. 4 These costs are used as input to the economic impact as we ll as the small entity analysis.

4 Memorandum from Bradley Nelson, EC/R to Melanie Ki ng, EPA. OAQPS/SPPD/ESG. Impacts Associated with NESHAP for Existing Stationary SI RICE. June 29, 2010.Table 4-2. Summary of Major Source and Area Source Costs for the SI RICE NESHAPaSize Range (HP)CapitalControl CostAnnualControl CostInitial TestRecordkeepingReportingMonitoring—Capital CostMonitoring—AnnualCostTotal AnnualCostsTotal CapitalCostsMajor Sources25–50 $0 $0 $0 $4,060,795 $0 $0 $0 $4,060,795 $050–100 $0 $0 $0 $1,087,540 $0 $0 $0 $1,087,540 $0100–175 $48,502,361 $37,071,061 $15,971,384 $1,721,899 $5,725,314 $0 $0 $60,489,657 $48,502,361175–300 $13,225,919 $8,382,568 $3,442,648 $371,157 $1,234,097 $0 $0 $13,430,470 $13,225,919300–500 $10,934,795 $5,562,872 $2,123,326 $228,919 $761,155 $0 $0 $8,676,262 $10,934,795500–600 $0 $0 $0 $0 $0 $0 $0 $0 $0600–750 $0 $0 $0 $0 $0 $0 $0 $0 $0>750 $0 $0 $0 $0 $0 $0 $0 $0 $0Total $72,663,076 $51,016,500 $21,537,358 $7,470,310 $7,720,566 $0 $0 $87,744,734 $72,663,076Area Sources25–50 $0 $0 $0 $6,668,944 $0 $0 $0 $6,668,944 $050–100 $0 $0 $0 $2,868,511 $0 $0 $0 $2,868,511 $0100–175 $0 $0 $0 $3,529,711 $0 $0 $0 $3,529,711 $0175–300 $0 $0 $0 $1,264,799 $0 $0 $0 $1,264,799 $0300–500 $0 $0 $0 $908,913 $0 $0 $0 $908,913 $0500–600 $7,547,433 $2,662,805 $248,366 $454,493 $1,26,426 0 0 $3,492,090 $7,547,433600–750 $1,522,236 $505,221 $44,323 $77,882 $22,562 0 0 $649,988 $1,522,236>750 $21,075,418 $6,214,397 $472,244 $829,795 $240,387 0 0 $7,756,823 $21,075,418Total $30,145,088 $9,382,423 $764,933 $16,603,048 $389,375 0 0 $27,139,780 $30,145,088Grand TotalTotal $102.808,163 $60,398,923 $22,302,292 $24,073,358 $8,106,972 0 0 $114,884,514 $102,808.163aCosts are presented in 2009 dollars.4-23Table 4-3. Summary of Major Source and AreaSource NAICS Costs for the SI RICE NESHAPaMajor Source Area Source Total (Major + Area)NAICS Capital Cost Annual Cost Capital Cost Annual Cost Capital Cost Annual Cost2211 Electric Power Generation $52,905,258 $63,062,494 $11,698,144 $12,138,277 $64,603,403 $75,200,77248621 Natural Gas Transmission $1,484,494 $1,462,530 $13,718,381 $6,142,839 $15,202,876 $7,605,369211111 Crude Petroleum & NGProduction $4,561,236 $6,138,383$71,439 $951,462$4,632,675 $7,089,844211112 Natural Gas Liquid Producers $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,84492811 National Security $5,878,362 $7,006,944$1, 299,794 $1,348,697 $7,178,1566 $8,355,641335312 Hydro Power Units $0 $25,248 $0 $37,872 $0 $63,120335312 Irrigation Sets $3,025,050 $3,230,856 $3,285,990 $4,999,041 $6,310,940 $8,229,896333992 Welders $247,440 $679,896 $0 $570,130 $247,440 $1,250,027Total $72,663,076 $87,744,734 $30,145,088 $27,139,780$102,808,163$114,884,514aCosts are presented in 2009 dollars.4-24Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by SizeaMajor Source Area Source Total (Major + Area)NAICS Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostElectric Power Generation (2211)25–50 hp $0 $2,758,459 $0 $4,137,688 $0 $6,896,14750–100 hp $0 $606,144 $0 $909,215 $0 $1,515,359100–175 hp $33,868,173 $42,238,648 $0$1,803,548 $33,868,173 $44,042,196175–300 hp $10,603,849 $10,767,847 $0 $446,361 $10,603,849 $11,214,209300–500 hp $8,433,236 $6,691,397 $0 $264,820 $8,433,236 $6,956,217500–600 hp $0 $0 $2,543,944 $1,177,047 $2,543,944 $1,177,047600–750 hp $0 $0 $515,514 $220,122 $515,514 $220,122>750 hp $0 $0 $8,638,687 $3,179,475 $8,638,687 $3,179,475Total Electric Power Generation 2211 $52,905,258 $63,062,494 $11,698,144 $12,138,277 $64,603,403 $75,200,772Natural Gas Transmission (48621)25–50 hp $0 $102 $0 $1,934 $0 $2,03650–100 hp $0 $4,872 $0 $92,571 $0 $97,443100–175 hp $301,721 $376,291 $0 $203,518 $301,721 $579,809175–300 hp $643,157 $653,104 $0 $342,928 $643,157 $996,032300–500 hp $539,617 $428,162 $0 $214,637 $539,617 $642,799500–600 hp $0 $0 $1,925,560 $890,929 $1,925,560 $890,929600–750 hp $0 $0 $949,443 $405,408 $949,443 $405,408>750 hp $0 $0 $10,843,377 $3,990,913 $10,843,377 $3,990,913Total Natural Gas Transmission (48621) $1,484,494 $1,462,530 $13,781,381 $6,142,839 $15,202,876 $7,605,369Crude Petroleum & NG Production (211111)25–50 hp $0 $388,115 $0 $582,173 $0 $970,28850–100 hp $0 $66,698 $0 $100,047 $0 $166,744100–175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531(continued)4-25Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)Major Source Area Source Total (Major + Area)NAICS Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual Cost175–300 hp $1,037 $1,053 $0 $44 $1,037 $1,096300–500 hp $10,424 $8,271 $0 $327 $10,424 $8,598500–600 hp $0 $0 $3,102 $1,435 $3.102 $1,435600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $68,337 $25,151 $68,337 $25,151Total Crude Petroleum & NG Production(211111) $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,844Natural Gas Liquid Producers (211112)25–50 hp $0 $388,115 $0 $582,173 $0 $970,28850–100 hp $0 $66,698 $0 $100,047 $0 $166,744100–175 hp $4,549,775 $5,674,246 $0 $242,285 $4,549,775 $5,916,531175–300 hp $1,037 $1,053 $0 $44 $1,037 $1,096300–500 hp $10,424 $8,271 $0 $327 $10,424 $8,598500–600 hp $0 $0 $3,102 $1,435 $3,102 $1,435600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $68,337 $25,151 $68,337 $25,151Total Natural Gas Liquid Producers (211112) $4,561,236 $6,138,383 $71,439 $951,462 $4,632,675 $7,089,844National Security (92811)25–50 hp $0 $306,495 $0 $459,743 $0 $766,23950–100 hp $0 $67,349 $0 $101,024 $0 $168,373100–175 hp $3,763,130 $4,693,183 $0 $200,394 $3,763,130 $4,893,577175–300 hp $1,178,205 $1,196,427 $0 $49,596 $1,178,205 $1,246,023300–500 hp $937,026 $743,489 $0 $29,424 $937,026 $772,913500–600 hp $0 $0 $282,660 $130,783 $282,660 $130,783(continued)4-26Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)Major Source Area Source Total (Major + Area)NAICS Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual Cost600–750 hp $0 $0 $57,279 $24,458 $57,279 $24,458>750 hp $0 $0 $959,854 $353,275 $959,854 $353,275Total National Security (92811) $5,878,362 $7,006,944 $1,299,794, $1,348,697 $7,178,156 $8,355,641Hydro Power Units (335312)25–50 hp $0 $22,688 $0 $34,032 $0 $56,72150–100 hp $0 $2,560 $0 $3,840 $0 $6,399100–175 hp $0 $0 $0 $0 $0 $0175–300 hp $0 $0 $0 $0 $0 $0300–500 hp $0 $0 $0 $0 $0 $0500–600 hp $0 $0 $0 $0 $0 $0600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $0 $0 $0 $0Total Hydro Power Units (335312) $0 $25,248 $0 $37,872 $0 $63,120Irrigation Sets (335312)25–50 hp $0 $32,913 $0 $625,338 $0 $658,25150–100 hp $0 $65,825 $0 $1,250,677 $0 $1,316,502100–175 hp $1,222,348 $1,524,449 $0 $824,505 $1,222,348 $2,348,954175–300 hp $798,634 $810,986 $0 $425,827 $798,634 $1,236,813300–500 hp $1,004,068 $796,683 $0 $399,376 $1,004,068 $1,196,060500–600 hp $0 $0 $2,789,064 $1,290,460 $2,789,064 $1,290,460600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $496,827 $182,857 $496,827 $182,857Total Irrigation Sets (335312) $3,025,050 $3,230,856 $3,285,890 $4,999,041 $6,310,940 $8,229,896(continued)4-27Table 4-4. Summary of Major Source and Area Source NAICS Costs for the SI RICE NESHAP, by Sizea(continued)Major Source Area Source Total (Major + Area)NAICS Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostWelders (333992)25–50 hp $0 $163,908 $0 $245,862 $0 $409,77150–100 hp $0 $207,394 $0 $311,091 $0 $518,485100–175 hp $247,440 $308,594 $0 $13,177 $247,440 $321,771175–300 hp $0 $0 $0 $0 $0 $0300–500 hp $0 $0 $0 $0 $0 $0500–600 hp $0 $0 $0 $0 $0 $0600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $0 $0 $0 $0Total Welders (333992) $247,440 $679,896 $0 $570,130 $247,440 $1,250,027Total$72,663,076 $87,744,734 $30,145,088 $27,139,780 $102,808,163 $114,884,514aCosts are presented in 2009 dollars.4-28Table 4-5. Summary of Major Source and Area Source NAICSCosts for the SI RICE NESHAP, by Number of EnginesaNumber of Engines Total (Major + Area)NAICS Major Area Total Capital Cost Annual CostElectric Power Generation (2211)25–50 hp 37,933 56,900 94,833 $0 $6,896,14750–100 hp 8,336 12,503 20,839 $0 $1,515,359100–175 hp 16,534 24,802 41,336 $33,868,173 $44,042,196175–300 hp 4,092 6,138 10,230 $10,603,849 $11,214,209300–500 hp 2,428 3,642 6,070 $8,433,236 $6,956,217500–600 hp 0 2,107 2,107 $2,543,944 $1,177,047600–750 hp 0 363 363 $515,944 $220,122>750 hp 0 4,677 4,677 $8,638,687 $3,179,475Total Electric Power Generation (2211) 69,323 111,132 180,455 $64,603,403 $75,200,772Natural Gas Transmission (48621)25–50 hp 1 27 28 $0 $2,03650–100 hp 67 1,273 1,340 $0 $97,443100–175 hp 147 2,799 2,946 $301,721 $579,809175–300 hp 248 4,716 4,964 $643,157 $996,032300–500 hp 155 2,952 3,107 $539,617 $642,799500–600 hp 0 1,595 1,595 $1,925,560 $890,929600–750 hp 0 668 668 $949,443 $405,408>750 hp 0 5,871 5,871 $10,843,377 $3,990,913Total Natural Gas Transmission (48621)619 19,899 20,519 $15,202,876 $7,605,369Crude Petroleum & NG Production (211111)25–50 hp 5,337 8,006 13,343 $0 $970,28850–100 hp 917 1,376 2,293 $0 $166,744100–175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531(continued)4-29Table 4-5. Summary of Major Source and Area Source NAICSCosts for the SI RICE NESHAP, by Number of Enginesa(continued)Number of Engines Total (Major + Area)NAICS Major Area Total Capital Cost Annual Cost175–300 hp 0 1 1 $1,037 $1,096300–500 hp 3 5 8 $10,424 $8,598500–600 hp 0 3 3 $3,102 $1,435600–750 hp 0 0 0 $0 $0>750 hp 0 37 37 $68,337 $25,151Total Crude Petroleum & NG Production (211111) 8,479 12,758 21,237 $4,632,675 $7,089,844Natural Gas Liquid Producers (211112)25–50 hp 5,337 8,006 13,343 $0 $970,28850–100 hp 917 1,376 2,293 $0 $166,744100–175 hp 2,221 3,332 5,553 $4,549,775 $5,916,531175–300 hp 0 1 1 $1,037 $1,096300–500 hp 3 5 8 $10,424 $8,598500–600 hp 0 3 3 $3,102 $1,435600–750 hp 0 0 0 $0 $0>750 hp 0 37 37 $68,337 $25,151Total Natural Gas Liquid Producers (211112) 8,479 12,758 21,237 $4,632,675 $7,089,844National Security (92811)25–50 hp 4,215 6,322 10,537 $0 $766,23950–100 hp 926 1,389 2,315 $0 $168,373100–175 hp 1,837 2,756 4,593 $3,763,130 $4,893,577175–300 hp 455 682 1,137 $1,178,205 $1,246,023300–500 hp 270 404 674 $937,026 $772,913500–600 hp 0 234 234 $282,660 $130,783(continued)4-30Table 4-5. Summary of Major Source and Area Source NAICSCosts for the SI RICE NESHAP, by Number of Enginesa(continued)Number of Engines Total (Major + Area)NAICS Major Area Total Capital Cost Annual Cost600–750 hp 0 40 40 $57,279 $24,458>750 hp 0 520 520 $959.854 $353,275Total Natural Gas Liquid Producers (211112) 7,702 12,347 20,050 $7,178,156 $8,355,641Hydro Power Units (335312)25–50 hp 312 468 780 $0 $56,72150–100 hp 35 53 88 $0 $6,399100–175 hp 0 0 0 $0 $0175–300 hp 0 0 0 $0 $0300–500 hp 0 0 0 $0 $0500–600 hp 0 0 0 $0 $0600–750 hp 0 0 0 $0 $0>750 hp 0 0 0 $0 $0Total Hydro Power Units (335312) 347 521 868 $0 $63,120Irrigation Sets (335312)25–50 hp 453 8,599 9,052 $0 $658,25150–100 hp 905 17,199 18,104 $0 $1,316,502100–175 hp 597 11,338 11,935 $1,222,348 $2,348,954175–300 hp 308 5,856 6,164 $798,634 $1,236,813300–500 hp 289 5,492 5,781 $1,004,068 $1,196,060500–600 hp 0 2,310 2,310 $2,789,064 $1,290,460600–750 hp 0 0 0 $0 $0>750 hp 0 269 269 $496,827 $182857Total Irrigation Sets (335312) 2,552 51,063 53,615 $6,310,940 $8,229,896(continued)4-31Table 4-5. Summary of Major Source and Area Source NAICSCosts for the SI RICE NESHAP, by Number of Enginesa(continued)Number of Engines Total (Major + Area)NAICS Major Area Total Capital Cost Annual CostWelders (333992)25–50 hp 2,254 3,381 5,635 $0 $409,77150–100 hp 2,852 4,278 7,130 $0 $518,485100–175 hp 121 181 302 $247,440 $321,771175–300 hp 0 0 0 $0 $0300–500 hp 0 0 0 $0 $0500–600 hp 0 0 0 $0 $0600–750 hp 0 0 0 $0 $0>750 hp 0 0 0 $0 $0Total Welders (333992) 5,227 7,840 13,067 $247,440 $1,250,027Total102,729 228,319 331,047 $382,802,298 $253,374,9391Costs are presented in 2009 dollars.4.4.5 Caveats and Uncertainties in the Cost Estimates

* Current knowledge about NOx control tech niques and costs is applied in this study. Advances such as a lternative catalyst formula tions may occur between now and when sources comply with this rulemaking that may lower costs. Scale economies can also lower per unit producti on costs as the market for these NOx control techniques expands.

* The alternative control techniques and corresponding emission reductions and costs may not apply to every unit wi thin the source category. Many factors influence the performance and cost of any control technique. Because control technology references typically evaluate average retrofit si tuations, costs may
be underestimated for the fraction of th e source population with difficult to
retrofit conditions. Difficult to retrofit conditions may be less of an issue for RICEs than for other point sources, however.

* NOx control efficiency and cost estimate s associated with source category-control strategy combinations are represented as point estimates. In practice, control effectiveness and costs will vary by engine.4-33 4.5 Baseline Emissions and Emission Reductions
The baseline emissions, emissions factors and emissions reductions associated with the proposed reconsideration rule are pr ovided in the tables below. Em issions are in tons per year.
Table 4-6. Summary of Major Source and A rea Source Baseline Emissions for the SI RICE NESHAP in 2013

Baseline Emissions (TPY) Size Range (HP) HAP CO NOx VOC Major Sources

25–50 hp 1,107 28,557 41,751 5,696 50–100 hp 593 15,296 22,363 3,051 100–175 hp 1,721 44,399 64,913 8,855 175–300 hp 641 16,530 24,168 3,297 300–500 hp 666 17,171 25,105 3,425 500–600 hp 0 0 0 0 600–750 hp 0 0 0 0 >750 hp 0 0 0 0 Total 4,728 121,953 178,301 24,323
Area Sources

25–50 hp 1,818 46,898 68,566 9,354 50–100 hp 1,564 40,344 58,985 8,047 100–175 hp 3,529 91,013 133,065 18,153 175–300 hp 2,184 56,331 82,359 11,235 300–500 hp 2,643 68,178 99,679 13,598 500–600 hp 1,830 47,273 69,094 9,415 600–750 hp 383 9,876 14,438 1,969 >750 hp 6,041 155,890 227,890 31,076 Total 19,993 515,803 754,077 102,846 Major + Area Total 24,722 637,756 932,377 127,169

Table 4-7. Emissions Factors

Engine HAP (lb/hp-hr) CO (lb/hp-hr) NOx (lb/hp-hr) VOC (lb/hp-hr) Formaldehyde (lb/hp-hr)

2SLB 5.96  10 -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 1.75  10 -44-34 Table 4-8. Summary of Major Source and Area Source Emissions Reductions for the SI RICE NESHAP in 2013

Emission Reductions (TPY) Size Range (HP) HAP CO NOx VOC Major Sources

25–50 hp 0 0 0 0 50–100 hp 0 0 0 0 100–175 hp 744 7,124 0 3,826 175–300 hp 277 2,653 0 1,424 300–500 hp 288 2,755 0 1,480 500–600 hp N/A N/A N/A 0 600–750 hp N/A N/A N/A 0 >750 hp N/A N/A N/A 0 Total 1,308 12,532 0 6,730
Area Sources

25–50 hp 0 0 0 0 50–100 hp 0 0 0 0 100–175 hp 0 0 0 0 175–300 hp 0 0 0 0 300–500 hp 0 0 0 0 500–600 hp 101 2,070 2,,063 517 600–750 hp 22 453 452 113 >750 hp 347 7,156 7,133 1,787 Total 470 9,679 9,648 2,418 Major + Area Total 1,778 22,211 9,648 9,1475-1 Section 5 ECONOMIC IMPACT ANALYSIS, ENER GY IMPACTS, AND SOCIAL COSTS

The EIA provides decision makers with social cost estimates and enhances understanding of how the costs may be distributed acro ss stakeholders (EPA , 2010). Although several
economic frameworks can be used to estimate social costs for regulations of this size and sector scope, OAQPS has typically used partial equilibrium market models. However, the current data do not provide sufficient details to develop a market model; the data that are available have little or no sector/firm detail and are reported at the national level. In addi tion, some sectors have unique market characteristics that make developi ng 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 qual itative analysis of the proposed reconsidered rule’s impact on stakeholder decisions, a qualitati ve discussion on if unfunded manda tes occur as a result of this proposed reconsidered rule, and the potential distribution of soci al costs between consumers and producers.

5.1 Compliance Costs of the Proposed Reconsidered Rule
EPA’s engineering cost anal ysis estimates the total annua lized costs of the proposed reconsidered rule are $115 million (in 2010 dollars) (EC/R, 2012).

The majority of the costs are incurred by the electric power sector (65%). The remaining
industries each account for less than 8% of the total annualized co st. The industrial classification for each engine is taken from the Power System s Research (PSR) database, which is the major source of data for the engines affected by this ru le. The PSR database used as a basis for the analyses in this RIA contains information on both mobile and stationary engines, among other data, and does so not only for the U.S. but worl dwide. PSR has collected such data for more than 30 years. The Office of Transportation and Air Quality (OTAQ) uses this database frequently in the development of their mobile source rules.

The annualized compliance costs per engine vary by the engine size. For 500 hp engines or less, the annualized per-engine costs are below $371 per engine. Pe r-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 th e affected engines fall within the 25 to 50 hp category (45%). The next highest categories ar e 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 comp liance relative to the value of the goods and services for industries using affected engines, we collected Census data fo r selected industries. At the industry level, the annualized cost s represent a very small fraction of revenue (less than 1%), for
all affected industries. Results for affected industries can be found in Table 5-1. These industry level cost-to-sales ratios can be interpreted as an average impact on potentia lly affected firms in these industries. Based on the cost-to-sales ratios, we can conclude that the annualized cost of this rule should be no higher than 1% of the sales on average for a firm in each of these industries, excluding natural gas transmission and natural gas liquid producers, which face slightly higher costs to sales ratios. 45%

16% 22%

7% 5% 2% 0% 3%

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

25-50 hp 50-100 hp 100-175 hp 175-300 hp 300-500 hp 500-600 hp 600-750 hp >750 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 reas onable approximation of the social cost of this proposed
reconsidered rule. EPA believe s this approximation is better for industries whose markets are well characterized as perfectly competitive. This approximation is less well understood for
industries where the characterizat ion of markets is not always perfectly competitive such as electric power generation whose legal incidence of this rule is approximately 65 percent of the annualized compliance cost. However, given the data limitation noted ea rlier, EPA believes the accounting for compliance cost is a reasonable approximation to info rm policy discussion in this rulemaking. To shed more light on this issue, EPA ran hypothetical analyses and the results are
in Tables 5-2 and 5-3 later in this RIA.

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis
Markets are composed of people as consumer s 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 usi ng market supply and demand diagrams. The market supply curve describes how much of a good or service firms ar e willing and able to sell to people at a
Table 5-1. Selected Industry-Level Annualized Compliance Costs as a Fraction of Total Industry Revenue: 2009

Total Annualized Costs Sales, Shipments, Receipt, or Revenue ($Billion) Industry (NAICS) Industry Name ($ million) a ($2007) ($2009) Cost-toSales Ratio 2211 Electric Power Generation $128.4 $440.4 $453.7 0.004% 48621 Natural Gas Transmission $68.9 $16.4 $16.9 0.41% 211111 Crude Petroleum & NG Production $7.4 $214.2 $220.5 0.001% 211112 Natural Gas Liquid Producers $7.4 $42.4 $43.6 0.005% 92811 National Security $14.3 #N/A #N/A #N/A 333992 Welders $1.3 $5.2 $5.5 0.025%
111 and 112 Agriculture using irrigation systems a $25.7 $27.9 $28.8 0.09%5-4 a Irrigation engine costs assumed to be passed on to agricultural sectors that use irrigation systems. N/A: receipts are Not Available for National Security Sources: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 00: All sectors: Geographic Area Series: Economy-Wide Key Statistics: 2007” <http://factfinder.census.gov>; (July 7th , 2010). U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). 2009. “2008 Farm and Ranch Irrigation Survey.” Washington, DC: USDA-NASS. Costs from Existing SI RICE NESHAP Impacts received from EPA 1/26/12

particular price; we often draw this curve as upward sloping because some production resources are fixed. As a result, the cost of producing an additional unit typically rises as more units are
made. The market demand curve describes how much of a good or service consumers are willing and able to buy at some price. Holding other f actors constant, the quantity demand is assumed to fall when prices rise. In a perfectly competitive market, equilibrium price (P 0 ) and quantity (Q 0 ) is determined by the intersection of the supply and demand curves (see Figure 5-4).
5.3.1 Changes in Market Prices and Quantities
To qualitatively assess how the regulation may influence the equilibrium price and quantity in the affected markets, we assume d the market supply function shifts up by the additional cost of producing the good or service; the unit cost increase is typically calculated by dividing the annual compliance cost estimate by the baseline quantity (Q 0 ) (see Figure 5-4). As shown, this model makes two predic tions: the price of the affected goods and services are likely to rise and the consumption/product ion 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 Mo del: With and Without Regulation

The size of these changes depends on two f actors: the size of the unit cost increase (supply shift) and differences in how each side of the market (supply and demand) responds to changes in price. Economists measure response s using the concept of price elasticity, which represents the percentage change in quantity divided by the percentage change in price. This dependence has been expresse d 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 peopl e do not have good substitutes that they can switch to easily (demand is inelastic) and

5 For examples of similar mathematical models in the public finance literature, see Nicholson (1998), pages 444–447, or Fullerton and Metcalf (2002).5-6  suppliers have excess capacity and can eas ily adjust production levels at minimal costs, or the time period of analysis is long enough that suppli ers can change their fixed resources; supply is more elastic over longer periods.

Short-run demand elasticities for energy goods (e lectricity and natura l gas), agricultural products, and construction are ofte n inelastic. Specific estimates of short-run demand elasticities for these products can be obtained from existi ng literature. For the s hort-run demand of energy products, the National Energy Modeling System (N EMS) 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 agricultu re and approximately 1 for cons truction (U.S. EPA, 2004). As a result, a 1% increase in the prices of agricu lture products would lead to a 0.2% decrease in demand for those products, while a 1% increas e in construction prices would lead to approximately a 1% decrease in demand for construction. Given these demand elasticity scenarios (shaded in gray), approximately a 1% increase unit costs would result in a price increase of 0.1 to 1% (Table 5-2). As a result , 10 to 100% of the unit cost increase could be passed on to consumers in the form of higher goods/services prices. This price increase would correspond to a 0.1 to 0.8% decline in cons umption in these markets (Table 5-3).
Table 5-2. Hypothetical Price Increase s for a 1% Increase in Unit Costs

Market Demand Elasticity Market Supply Elasticity

0.1 0.3 0.5 0.7 1 1.5 3

− 0.1 0.5% 0.8% 0.8% 0.9% 0.9% 0.9% 1.0%

− 0.3 0.3% 0.5% 0.6% 0.7% 0.8% 0.8% 0.9%

− 0.5 0.2% 0.4% 0.5% 0.6% 0.7% 0.8% 0.9%

− 0.7 0.1% 0.3% 0.4% 0.5% 0.6% 0.7% 0.8%

− 1.0 0.1% 0.2% 0.3% 0.4% 0.5% 0.6% 0.8%

− 1.5 0.1% 0.2% 0.3% 0.3% 0.4% 0.5% 0.7%

− 3.0 0.0% 0.1% 0.1% 0.2% 0.3% 0.3% 0.5%

53.2 Regulated Markets: The Electric Power Ge neration, Transmission, and Distribution Sector
Given that the electric power sector bears ma jority of the estimated compliance costs and the industry is also among the la st major regulated energy industri es in the United States (EIA, 2010), the competitive model is not necessa rily applicable for this industry.5-7 Table 5-3. Hypothetical Consumption Decreases for a 1% Increase in Unit Costs

Market Demand Elasticity Market Supply Elasticity

0.1 0.3 0.5 0.7 1 1.5 3

− 0.1

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.3

− 0.1% − 0.2%

− 0.2%

− 0.2%

− 0.2%

− 0.3%

− 0.3%

− 0.5

− 0.1%

− 0.2% − 0.3%

− 0.3%

− 0.3%

− 0.4%

− 0.4%

− 0.7

− 0.1%

− 0.2%

− 0.3% − 0.4%

− 0.4%

− 0.5%

− 0.6%

− 1.0

− 0.1%

− 0.2%

− 0.3%

− 0.4% − 0.5%

− 0.6%

− 0.8%

− 1.5

− 0.1%

− 0.3%

− 0.4%

− 0.5%

− 0.6% − 0.8%

− 1.0%

− 3.0

− 0.1%

− 0.3%

− 0.4%

− 0.6%

− 0.8%

− 1.0% − 1.5%

Although the electricity i ndustry continues to go through a pro cess of restructuring, whereby the industry is moving toward a more competitive framework (see Figure 5-3 for the status of restructuring by state), 6 in many states, electricity prices con tinue to be fully regulated by Public Service Commissions. As a result, the rules a nd processes outlined by these agencies would ultimately determine how these additional regulatory costs would be recovered by affected
entities.
5.3.3 Partial Equilibrium Measures of Soci al Cost: Changes Consumer and Producer Surplus
In partial equilibrium analysis, the social co sts are estimated by measuring the changes in consumer and producer surplus, and these values can be determined using the market supply and demand model (Figure 5-2). The change in c onsumer surplus is measured as follows:



CS = – [  Q 1 ×  p ] + [0.5 ×  Q ×  p ]. (5.1)

Higher market prices and lower quantities lead to consumer welfare losses. Similarly, the change in producer surplus is measured as follows:



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

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_br ief/print_pages/electricity.pdf.5-8 Figure 5-3. Electricity Restructuring by State
Source. U.S. Energy Information Administration. 2010b.

<http://www.eia.doe.gov/cneaf/electricity/page/restructur ing/restructure_elect.html>. Last updated September 2010.

5.4 Energy Impacts
Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agencies will prepare
and submit to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, a Statement of Energy Effects for certain actions identified as “significant energy actions.” S ection 4(b) of Executive Order 13211 defines “significant energy actions” as any action by an ag ency (normally published in the Federal Register ) that promulgates or is expected to lead to the pr omulgation of a final rule or regulation, including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed rulemaking: (1) (i) that is a significant re gulatory action under Executive Order 12866 or any successor order, and (ii) is likely to have a significant adverse effect on the supply, distri bution, or use of energy;5-9 or (2) that is designated by the Administrator of the Office of In formation and Regulatory Affairs as a significant energy action.

This rule is not a signifi cant energy action as designated by the Administrator of the Office of Information and Regulatory Affairs because it is not likely to have a significant adverse impact on the supply, distribution, or use of ener gy. EPA has prepared an analysis of energy impacts that explains this conclusion as follows below.

With respect to energy supply and prices, th e analysis in Table 5-4 suggests at the industry level, the annualized cost s represent a very small fraction of revenue (all industries are impacted under 1%). As a result, we can conclu de supply and price imp acts should be small.

To enhance understanding regarding the regu lation’s influence on energy consumption, we examined publicly available data describing en ergy consumption for the electric power sector that will be affected by this rule. The A nnual Energy Outlook 2011 (EIA, 2011) provides energy consumption data. As shown in Table 5-4, this industry account for less than 0.3% of the U.S. total liquid fuels and less than 8.0% of natural gas. As a result, any energy consumption changes attributable to the regulatory program should not significantly influen ce 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 power plants whose primary business is

to sell electricity, or electricity an d heat, to the public. Includes small power producers and exempt wholesale generators.

b Includes conventional hydroelectric, geothermal, wood and wood waste, biogenic municipal solid waste, other

biomass, petroleum coke, wind, photovoltaic and solar thermal sources. Excludes net electricity imports.5-10 c Includes non-biogenic municipal waste not included above. Source: U.S. Energy Information Administration. 2011a. Supplemental Tables to the Annual Energy Outlook 2011.

Table 2. Available at: <http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.html>.

5.5 Unfunded Mandates
The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the rule and any disproportio nate budgetary effects. Our estimates of the future complian ce costs of the proposed rule are discussed previously in Section
4 of this RIA. We do not believe that there will be any dispropor tionate budgetary effects of the proposed rule on any particular areas of the country, State or local governments, types of communities (e.g., urban, rural), or particular industry segments.
5.5.1 Future and Disproportionate Costs
The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the rule and any disproportio nate budgetary effects. Our estimates of the future complian ce costs of the proposed rule are discussed previously in Chapter
4 of this RIA. We do not believe that there will be any dispropor tionate budgetary effects of the proposed rule on any particular areas of the country, State or local governments, types of communities (e.g., urban, rural), or particular industry segments.
5.5.2 Effects on the National Economy
The UMRA requires that we estimate the e ffect of the proposed rule on the national economy. To the extent feasible, we must estim ate the effect on producti vity, economic growth, full employment, creation of productive jobs, an d international competitiveness of the U.S. goods and services if we determine that accurate es timates are reasonably feasible and that such
effect is relevant and material. The nationw ide economic impact of the proposed rule is presented earlier in this RIA chapter. This an alysis provides estimates of the effect of the proposed rule on most of the categories menti oned above, and these estimates are presented earlier in this RIA chapter. In addition, we have determined that the proposed rule contains no regulatory requirements that might significantly or uniquely affect small governments. Therefore, today’s rule is not subject to the requirements of section 203 of the UMRA.

5.6 Environmental Justice

Executive Order (EO) 12898 (59 FR 7629 (Fe b. 16, 1994)) establishes federal executive policy on environmental justice. Its main provi sion 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 appropriate, disp roportionately high and adverse human health or environmental effects of their programs, policie s, and activities on minority populations and lowincome populations in the United States.

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 environm ental protection for all affected populations without having any disproportionately high and adve rse human health or environm ental effects on any population, including any minority or low-income population. This rule is a nationwide standard that reduces air toxics emissions from existing statio nary SI engines, thus decreasing the amount of
such emissions to which all a ffected populations are exposed.

5.7 Employment Impact Analysis

In addition to addressing the costs and benef its of the proposed reconsideration rule, EPA has analyzed the impacts of this rulemaking on em ployment, which are presented in this section. While a standalone analysis of employment impa cts is not included in a standard cost-benefit analysis, such an analysis is of particular co ncern in the current economic climate of sustained high unemployment. Executive Order 13563, states, “Our regulatory system must protect public health, welfare, safety, and our environment while promoting economic growth, innovation, competitiveness, and job creation” (emphasis added). Therefore, and consistent with recent efforts to characterize the employ ment effects of economically si gnificant rules, the Agency has provided this analysis to inform the discussi on of labor demand and em ployment impacts.

This analysis includes estimates of certa in short-term and on-going labor requirements (increase in labor demand) associated with reporting and recordkeepi ng, and the installation, operating and maintenance of control devices. EPA estimates that a bout 200 jobs will be created or supported in the short- term and about 400 jobs will be created or supported annually on a permanent basis. EPA also provides a quali tative discussion of othe r potential employment effects, including both increases and decreases. Because of the uncertain ties involved, these sets of estimates should not be added in an attemp t to characterize the ove rall employment effect.

We have not quantified the rule’s effects on a ll labor in other sector s not regulated by the proposed rule, or the effects i nduced by changes in workers’ in comes. What follows is an overview of the various ways that environmenta l regulation can affect employment, followed by a discussion of the estimated impacts of this rule. EPA continues to explore the relevant5-12 theoretical and empirical literatur e and to seek public comments in order to ensure that such estimates are as accurate, useful and informative as possible.

From an economic perspective, labor is an input into producing goods and services; if regulation requires that more la bor be used to produce a given amount of output, that additional
labor is reflected in an incr ease in the cost of production. 7 When an increase in employment occurs as a result of a regulat ion, it is a cost to firms. Moreover, when the economy is at full employment, we would not expect an environmen tal regulation to have an impact on overall employment because labor is being shifted from one sector to another. On the other hand, in periods of high unemployment, an increase in labor demand due to regulation may result in a short-term net increase in overall employment due to the potential hiring of previously unemployed workers by the regulated sector to he lp meet new requirements (e.g., to install new equipment) or by the environmental protection s ector to produce new abatement capital. When significant numbers of workers ar e unemployed, the opportunity cost s associated with displacing jobs in other sectors are likely to be smaller. And, in general, if a re gulation imposes high costs and does not increase the demand for labor, it may lead to a decrease in employment.

To provide a partial picture of the employmen t consequences of this rule, EPA takes two approaches. First, EPA uses information such as monitoring, record keeping, and reporting estimates derived from its cost analysis docum entation to generate estimates of employment impacts. Second, the analysis considers the re sults of Morgenstern, Pizer, and Shih (2002) in estimating the effects of the regulation on the regul ated industry. This appr oach has been used by EPA previously in recent Regulatory Impact Anal yses. EPA is interested in public comments on the merits of including inform ation derived in this fashion for assessing the employment consequences of regulations.

5.7.1 Employment Impacts from Pollution Control Requirements

Regulations set in motion new orders for po llution control equipmen t and services. New categories of employment have been created in the process of implementing regulations. When a new regulation is promulgated, one typical response of industry is to order pollution control equipment and services in order to comply with the regulation when it becomes effective, while closure of plants that choose not to comply occurs after th e compliance date. With such a

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 w ill cause a short-run aggregate supply curve to shift to the left, and businesses will produce less, all other things being equal.5-13 response by industry as a basis, th is section presents estimates for short term employment needed associated with the monitoring, re cordkeeping, and reporting requirements for this proposed rule. Environmental regulation may increase revenue and employment in the environmental technology industry. While these incr eases represent gains for that industry, they are costs to the regulated industries required to in stall the equipment. As with a ny pool of labor, the gross size of the labor pool does not reflect th e net impact on overall employment after adjusting for shifts in
other sectors.

Regulated firms hire workers to design and build pollution controls. Once the equipment is installed, regulated firms hire workers to ope rate and maintain the pollution control equipment – much like they hire workers to produce more output. Of course , these firms may also reassign existing employees to do these activities. Enviro nmental regulations also support employment in many basic industries. In addition to the in crease in employment in the pollution control industry (to fill increased orders for pollution co ntrol equipment placed by the regulated sector), environmental regulations also support employment in industries that provide intermediate goods to the pollution control industry. For example, an investment in capital expenditures to reduce air pollution involves the purchase of abatement equipment. The equipment manufacturers, in turn, order steel, tanks, vessels, blowers, pumps, and chemicals to manufacture and install the equipment. A study by Bezdek, Wendling, and Di Pernab (2008) found that “investments in environmental protection create jobs and displace jobs, but th e net effect on employment is positive.” 8 The majority of the jobs associated wi th added pollution controls (e.g., boilermakers, general construction workers, etc.) will provide domestic employment opportunities, but some goods and services demanded and/ or provided to the pollution control industry (e.g., steel, cement, etc.) are internationally traded goods.
Once the equipment is installed, regulated firms hire workers to operate and maintain the pollution control equipment – much like they hire workers to produce more output. Morgenstern et al. (2002) examined how regulated industrie s respond to regulation. The authors found that, on average for the industries they studied, employme nt increases in regulated firms. Of course, these firms may also reassign existing employees to perform these activities.
The focus of this part of the analysis is on labor requirements related to the compliance
actions of the affected entities within the a ffected sector. We do not estimate any potential

8 Environmental protection, the economy, and jobs: National and regional analyses

, Roger H. Bezdek, Robert M. Wendling and Paula DiPerna, Journal of Environmental Management Volume 86, Issue 1 , January 2008, Pages 63-79.5-14 changes in labor outside of the aff ected sector. It is important to highlight that unlike the typical case where to reduce a bad output (i.e., emissions) a firm often has to reduce production of the good output, many of the emission controls requir ed by the proposed rule will simultaneously increase production of the good output and reduce production of bad outputs. That is, these controls jointly pr oduce environmental improvements and incr ease output in the regulated sector. New labor associated with implementing these cont rols to comply with the new regulations can
also be viewed as additional labor increasi ng output while reduci ng undesirable emissions.

The employment analysis uses a bottom-up engineering-based met hodology to estimate employment impacts. The engineering cost anal ysis summarized in Section 4 of this RIA includes estimates of the labor requirements associated with implementing the proposed regulations. Each of these labor ch anges 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 continua l, annual labor requirements by estimating hours of labor required and converti ng this number to full-time equivalents (FTEs) by dividing by 2,080 (40 hours per week multiplied by 52 weeks). We note that this type of FTE estimate cannot be used to make assumptions about th e specific number of peopl e involved or whether new jobs are created for new employees.

The results of this employment estimate are presented in Table 5-5 for the proposed
NESHAP. The tables breaks down the installatio n, operation, and maintenance estimates by type of pollution control evaluated in the RIA and present both the es timated hours required and the
conversion of this estimate to FTE. For th e proposed NESHAP, repor ting and recordkeeping requirements were estimated requirements were es timated for the entire rule rather than by anticipated control requirements; the reporting and recordkeeping estimates are consistent with estimates EPA submitted as part of its Information Collection Request (ICR) that is in the Supporting Statement for the pr oposed reconsideration rule.

The up-front labor requirement is estima ted at 182 FTEs for the proposed NESHAP. These up-front FTE labor requirements can be view ed as short-term labor requirements required for affected entities to comply with the new regulation. Ongoing requirements are estimated at about 357 FTEs for the proposed NESHAP. Th ese ongoing FTE labor requirements can be viewed as sustained labor requi rements 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 f ound in the docket for the rulemaking. It is important to recognize that these seemingly precise estimates are not to be assumed to be exact measures of the5-15 employment impacts of this rulemaking. They represent a rough appr oximation of the small positive impacts that this rule may have on employment.5-16 Table 5-5. Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Cont rol Equipment Requirements for Proposed Reconsideration SI RICE NESHAP

Source Emission Control Measure Projected No. of Affected

Units Per-Unit One-Time

Labor Estimate (Hours) Total OneTime Labor

Estimate (Hours) Per-Unit Annual Labor Estimate (Hours) Total Annual Labor Estimate (Hours) One-Ti m Full-Ti m Equivale n

Major Sources

SI RICE <100 HP N/A 70,798 N/A N/A 1 70,798 N/A

-O&M/Recordkeeping

2SLB RICE 100-500 HP

N/A 7,398 N/A N/A N/A

92,480 N/A

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

Oxidation Catalyst 14,257 21 300,255 15
163,956 144 -Testing 8 -Reporting 3.5

Area Sources

All SI RICE N/A 228,318 N/A N/A 1 228,318 N/A

-O&M/Recordkeeping
Non-Emergency 4SLB SI RICE >500 HP in Populated Areas Oxidation Catalyst 768 37 28,117 15
15,734 14 -Testing 2 -Reporting 3.5 Non-Emergency 4SRB SI RICE >500 HP in Populated Areas NSCR 578 86 49,918 33
22,236 24 -Testing 2 -Reporting 3.5
Total 144 378,290 113 741,633 182

Note : Full-time equivalents (FTE) are estimated by first multip lying the projected number of affected units by the per unit labor requirements and then dividing by 2,080 (40 hours multiplied by 52 weeks). Totals may not sum due to independent rounding. HP = horsepower N/A = Not Applicable. O&M = Operating and Maintenance5-17 5.7.2 Employment Impacts within the Regulated Industry

In recent RIAs we have applied estimat es from a study by Morgenstern, Pizer and Shih (2002) 1 to derive the employment effects of new regulations w ithin the regulated industry. (See, for example, the Regulatory Impact Analyses for the recent final MATS and final CSAPR regulations). Determining th e direction of employment effects in the regulated industry is also challenging due to competing effects. Complying with the new or more stringent regulation re quires additional input s, 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 envi ronmental regulations can be understood as requiring regulated firms to a dd a new output (environmental quality) to their product mixes. Although legally compelled to satisfy this new demand, regulated firms have to finance this additional producti on with the proceeds of sales of their other (market) products. Satisfying this new dema nd requires additional i nputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms in their production processes.

More specifically, Morgenst ern, Pizer, and Shih (2002) decompose the effect of regulation on net employment in the regulated sector into the follo wing three subcomponents:

 The Demand Effect : higher production costs from comp lying with the regulation will raise market prices, reducing consum ption (and production), thereby reducing
demand for labor within the re gulated industry. The “extent of this effect depends on the cost increase passed on to consumers as well as the demand elasticity of industry output.” (p. 416)

 The Cost Effect : Assuming that the capital/labor ratio in the production process is held fixed, as “production costs rise, more inputs, including labor, are used to produce the same amount of output,” (p. 416). For example, to reduce pollutant emissions while holding output levels c onstant, regulated firms may re quire additional labor.

1 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 200 2. Jobs versus the Environment: An Industry-Level Perspective. ‖ Journal of Environmental Economics and Management 43(3):412-436.5-18  The Factor-Shift Effect : Regulated firms’ production technologies may be more or less labor intensive after complying with the regulation (i.e., more/less labor is required relative to capital pe r dollar of output). “Envir onmental activities may be
more labor intensive than conventional production,” meaning that “the amount of labor per dollar of output will rise.” Howeve r, activities may, instead, be less labor intensive because “cleaner operations coul d involve automation and less employment, for example.” (p. 416)

The demand effect is expected to have an unambiguously negative effect on employment, the cost effect to have an unambiguously posi tive effect on employment, and the factor-shift effect to have an ambiguous effect on employment . Without more information with respect to the magnitudes of these three competing eff ects, it is not possible to predict the net environmental employment eff ect in the regulated sector.

Using plant-level Census information be tween the years 1979 and 1991, Morgenstern et al. estimate the effects of pollution abatement expenditures on net employment in four highly polluting/regulated sectors (pulp and paper, plastics, steel, a nd petroleum refining). They
conclude that increased abatem ent expenditures generally have not caused a significant change in net employment in those sectors. More specifica lly, their results show th at, on average across the industries studied, each additional $1 million (in 1987$) spent on pollution abatement results in a (statistically insignifi cant) net increase of 1.55 (+/- 2.24) jobs. As a result, the authors conclude that increases in pollution abatement expenditures can have positive effects on employment and do not necessarily cause economically significan t employment changes. The conclusion is similar to Berman and Bui (2001), who found th at increased air quality regulation in Los Angeles did not cause larg e employment changes.

Ideally, the EPA would first apply the met hodology of Morgenstern et al. to current pollution expenditure and market da ta for the regulated firms to identify the relationship between abatement costs and employment, then use this relationship to extrapolate the effect of new projected abatement costs on these firms. Unfort unately, current firm-level abatement cost and
market characteristics are not ava ilable. In addition, there ar e important differences in the markets and regulatory settings analyzed in their study and the setting presented here that lead us to conclude that it is inappropriate to util ize their quantitative estimates to estimate the employment impacts from this reconsiderati on proposal. The differences between the underlying regulations motivating the abatement expenditures studied in Morgenstern et al. are potentially too many to allow for the direct transfer of their quantitative estimates for use in analysis of the proposed rule. There are also important differe nces between the industries affected by this5-19 proposed rule and the four manufacturing industr ies studied by Morgenstern et al. For these reasons, we conclude there are too many uncertain ties as to the comparability of the Morgenstern et al. study to apply their estimates to quantif y the employment impacts within the regulated sector for this proposed regulation.6-1 Section 6
SMALL ENTITY SCREENING ANALYSIS

The Regulatory Flexibility Act as am ended by the Small Business Regulatory Enforcement Fairness Act (SBREFA) generally re quires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the
Administrative Procedure Act or any other statute, unless the agen cy certifies that the rule will not have a significant economic impact on a substa ntial number of small entities. Small entities include small businesses, small governmental jurisdictions, and sm all not-for-prof it enterprises.

After considering the economic impact of the proposed rule on small entities, the screening analysis indicates that this proposed rule will not have a significant economic impact on a substantial number of small entities (or “S ISNOSE”). Under the analyses EPA considered,
sales and revenue tests for establishments owne d by model small entities are less than 1% except electric power generation (NAICS 2211 with receipts less than $100,000 per year) and crop and animal production (NAICS 111 and 112 with re ceipts less than $25,000 per year). These findings are similar to those for the final SI RICE rule promulgated in August 2010, though the impacts are lower due to the reduction in the cost estimates for these industries.

6.1 Small Entity Data Set
The industry sectors covered by the proposed ru le were identified during the development of the cost analysis (EC/R, 2012). The Statisti cs of United States Business (SUSB) provides
national information on the distri bution of economic variables by industry and enterprise size (U.S. Census, 2012a, b). 1 The Census Bureau and the Office of Advocacy of the SBA supported and developed these files for use in a broad range of economic analyses. 2 Statistics include the total number of establishments and receipts for all entities in an industry; however, many of these entities may not necessarily be covered by the pr oposed rule. SUSB also provides statistics by enterprise employment and receipt size.

The Census Bureau’s definitions used in the SUSB are as follows:

 Establishmen t: An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed.

1 The SUSB data do not provide establishment information fo r the national security NAICS code (92811) or irrigated farms. Since most national security installations are owne d by the federal government (e.g., military bases), EPA assumes these entities would not be considered small. For irrigated farms, we relied on receipt data provided in the 2008 Farm and Irrigation Survey (USDA, 2009).
2 See http://www.census.gov/csd/susb/ and http://www.sba .gov/advo/research/data.html for additional details.6-2  Receipts : Receipts (net of taxes) are define d as the revenue for goods produced, distributed, or services provided, in cluding revenue earned from premiums, commissions and fees, rents, interest, divi dends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise—the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size designations are determined by the su mmed employment of all associated establishments.

Because the SBA’s business size definitions (SBA, 2010) apply to an establishment’s “ultimate parent company,” we assumed in this an alysis that the “enterpri se” definition above is consistent with the concept of ultimate parent company that is typically used for SBREFA screening analyses and the terms are used interchangeably.

6.2 Small Entity Economic Impact Measures
The analysis generated a set of establishment sales tests (represented as cost-to-receipt ratios) 3 for NAICS codes associated with sectors li sted in Table 6-1. Although the appropriate SBA size definition should be applied at the pa rent company (enterpris e) level, we can only compute and compare ratios for a model establishm ent owned by an enterpri se within an SUSB size range (employment or receipts). Using th e SUSB size range helps us account for receipt differences between establishments owned by large and small enterprises and also allows us to
consider the variation in small business de finitions across affect ed industries. Using establishment receipts is also a conservative approach, because an establishment’s parent company (the “enterprise”) may have other economi c resources that could be used to cover the
costs of the final rule.
6.2.1 Model Establishment Receipt s and Annual Compliance Costs
The sales test compares a representative esta blishment’s total annual engine costs to the average establishment receipts for ente rprises in several size categories. 4 For industries with SBA

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

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

• small nonprofits (if applicable): “expenditure” test; annualized compliance cost as a percentage of annual operating expenses,
4 For the 1 to 20 employee categ ory, we excluded SUSB data for enterpri ses with zero employees. These enterprises did not operate the entire year.6-3 employment size standards, we calculated aver age establishment receipts for each enterprise employment range (Table 6-2). 5 For industries with SBA receipt size standards, we calculated
Table 6-1. SI NESHAP for Existing Statio nary Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Business Size Standards

Industry Description Corresponding NAICS SBA Size Standard for Businesses (November 5nd, 2010) Type of Small Entity
Electric Power Generation 2211 a Business and government Natural Gas Transmission 48621 $7.0 million in annual receipts Business Crude Petroleum & NG Production 211111 500 employees Business

Natural Gas Liquid Producers 211112 500 employees Business National Security 92811 NA Government Hydro Power Units See NAICS 2211 1,000 employees Business and government Irrigation Sets Affects NAICS 111 and 112 Generally $750,000 or less in annual receipts Business

Welders Affects industries that use heavy equipment such as construction,

mining, farming Varies by 6-digit NAICS code; Business Example industry:
NAICS 238 = $14 million in annual receipts

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 precedi ng fiscal year did not exceed 4 million megawatt hours. Source: U.S. Small Business Administration (SBA). 2010. “Table of Small Business Size Standards Matched to North American Industry Classification System Codes.” Effective November 5nd, 2010. Downloaded 2/16/12.

average establishment receipts fo r each enterprise r eceipt range (Table 6-3). We included the utility sector in the second gr oup, although the SBA size standard fo r this industry is defined in terms of physical units (megawatt hours) versus receipts. Crop and an imal production (NAICS 111 and 112) also have an SBA receipt size stan dard that defines a small business as receiving $750,000 or less in receipts per year. However, SUSB data were not available for these industries. Therefore, we conducted the sales te st using the following range of establishment receipts: farms with annual recei pts of $25,000 or less, farms with annual receipts of $100,000 or less, farms with annual receip ts of $500,000 or less, and farm s with annual receipts of $750,000
or less.

5 2007 Economic Census data are at http://www.census.gov/econ/census07/.6-4Table 6-2. Average Receipts for Affected Industryby Enterprise: 2009 ($2009 Million/Establishment)SBA SizeStandardfor Businesses(effectiveNovember 5,2010)Owned By Enterprises with Employee Range:NAICS NAICS DescriptionAllEnterprises1–20Employees20–99Employees100–499Employees500+Employees211111 Crude petroleum &natural gas extraction500 employees $30.22 $2.15 $33.02 $151,76 1,570211112 Natural gas liquidextraction500 employees $172.81 $0.30 NA $11.88 NA335312 Motor & generator mfg 1,000 employees $18.58 $1.37 $6.14 $15.96 $29.47333992 Welding & solderingequipment mfg500 employees $18.51 $1.56 $6.60 $33.25 NASource: U.S. Census Bureau. 2012a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.”<http://www.census.gov/csd/susb/ Downloaded 2/22/12.NA = Not available.6-5Table 6-3. Average Receipts for Affected Industry byEnterprise Receipt Range:2007 ($2008 /establishment)SBA Size Standardfor Businesses(effective November5, 2010)Owned By Enterprises with Receipt Range:NAICS NAICS DescriptionAllEnterprises0–99KReceipts100–499.9KReceipts500–999.9KReceipts1,000–4,999.9KReceipts5,000,000–9,999,999KReceipts<10,000KReceipts10,000–49,999KReceipts50,000–99,999KReceipts100,000K+Receipts2211Electric PowerGenerationa$261.0 $31.2 $272.5 $724.9$2,399.5 $7,330.5 $2,617.7$24,786.9$67,706.8$1,394,051.0622110 Hospitals$34.5 million in annualreceipts$202,058.7 NA $23.82 NA$3,255.0 $7,291.0 $4,692.1$23,481.9$67,545,6$508,705.8237310Highway , street, andbride construction$33.5 million inAnnual Receipts$7.74$0.06$0.32$0.84$2.74$8.11$2.00$22.62$56.48$56.81237110Water and sewer lineand related structures,construction$33.5 million inAnnual Receipts$3.89$0.06$0.32$0.85$2.73$8.17$1.84$20.62$45.05$47.27237130Powerandcommunicationline and relatedstructures construction$33.5 million inAnnual Receipts$3.39$0.06$0.31$0.83$2.52$7.75$1.32$16.84$34.50$23.86237990zOther heavy andcivil engineeringconstruction$33.5 million inAnnual Receipts$2.66$0.06$0.30$0.83$2.48$7.76$0.99$18.72$40.53$42.3592811 National Security NA NA NANA NA NA NANA NA NA NANotes: Note: Industries in green were included for consistency with the analysis done for finalrule. National Security is included in this table but does not havesize standards.aNAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm in these industries is defined as small by SBA if, including its affiliates, it isprimarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fiscal year did notexceed 4 million megawatt hours.NA = Not available. SUSB did not report this data for disclosure or other reasons.Source: U.S. Census Bureau. 2009a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.”<http://www.census.gov/csd/susb/6-6 Annual entity compliance costs vary depending on the size of the SI engines used at the affected establishment. Absent facility-specifi c information, we comput ed per-entity compliance
costs based for three different cases based on representative establishm ents—Cases 1, 2, and 3 (see Table 6-4). Each representative establishm ent differs based on the size and number of SI engines being used. Compliance costs are ca lculated by summing the total annualized compliance costs for the relevant engine cate gories, dividing the su m by the total existing population of those engines, and multiplying the average engine cost by the number of engines assumed to be at the establishment. Since NAICS 2211 and 48621 are fundamentally different than other industries considered in this analys is due to the number of engines affected and amount of cost incurred resulting from this propo sed rule, we used different assumptions about what constitutes the representative establishment and report these assumptions separately.

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

 Case 2: The representati ve establishment in NACIS 2211 and 48621 uses two 25 to 750+ hp engines with an average compliance cost of $412 per engine, resulting in a total annualized compliance cost of $824 for th is representative es tablishment. For all other industries, the repres entative establishment uses two 25 to 300 hp engines with an average compliance cost of $246 per engine , resulting in a total compliance cost of $492 for this representati ve establishment.

 Case 3: The representative establishment for all indus tries uses two 50 to 100 hp engines with an average co mpliance cost of $73 per engine, resulting in a total compliance cost of $145 for this representative establishment.

EPA believes that small entities are most likel y to face costs similar to Case 2 (columns shaded in gray in Table 6-4) because most of th e engines to be affected by this proposed rule in NAICS 335312, 333992, 211111, and 211112 are under 300 hp capacity, and most small entities in these industries will own engi nes of this size or smaller. This is corroborated by Figure 6-1
and 6-2 which shows the distribu tion of engine population and co mpliance costs by engine size for all industries. However, it is difficult to make a similar claim for NAICS 2211 and 48621 based on the existing distribution of engines in these industries. 6

6 This claim also cannot be made for NAICS 92811: National Security. However, since most national security installations are owned by the federal government (e.g., military bases), EPA assumes these entities would not be considered small.6-7 For the sales test, we divided the representative establishment compliance costs reported in Table 6-4 by the representative establishment r eceipts reported in Tables 6-2 and 6-3. This is known as the cost-to-receipt (i.e., sa les) ratio, or the “sales test.” The “sales test” is the impact
Table 6-4. Representative Establishment Cost s Used for Small Entity Analysis ($2009)

Case 1 Case 2 Case 3

NAICS 2211, 48621

(+750 hp

only) All Other NAICS (+750 hp

only) NAICS 2211,48621

(25-750+ hp) All Other NAICS (25–300

hp) NAICS 2211, 48621 (25–100 hp only) All Other NAICS (25–100 hp only) Total Annualized Costs ($) $7,710,388 $586,434 $82,806,141 $28,057,798 $8,510,985 $6,174,805 Engine Population 10,548 863 200,974 114,517 117,040 84,913 Average Engine Cost ($/engine) $731 $680 $412 $246 $73 $73 Assumed Engines Per Establishment 3 3 2 2 2 2 Total Annualized Costs per Establishment $2,193 $2,040 $824 $492 $145 $1456-8 Figure 6-1. Distribution of Engine Po pulation by Size for All Industries 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Electric Power Generation

(2211) Natural Gas Transmission

(48621) Crude Petroleum & NG Production (211111) Natural Gas Liquid Producers (211112) National Security (92811) Hydro Power Units (335312) Irrigation Sets (335312) Welders (333992) >750 hp

600

‐ 750 hp

500

‐ 600 hp

300

‐ 500 hp

175

‐ 300 hp

100

‐ 175 hp

50

‐ 100 hp

25

‐ 50 hp6-9 Figure 6-2. Distribution of Compliance Cost s by Engine Size for All Industries

methodology EPA employs in analyzing small entity impacts as opposed to a “profits test,” in which annualized compliance costs are calculated as a share of profits.

This is because revenues or sales data are commonly available data for entities normally impacted by EPA regulations and profits data no rmally made available are often not the true profit earned by firms because of accounting an d tax considerations. Revenues as typically published are usually correct figures and are more reliably reported when compared to profit data. The use of a “sales test” for estimating small business impacts for a rulemaking such as this one is consistent with guidance offe red by EPA on compliance with SBREFA 7 and is consistent with guidance published by the U.S. SBA’s Office of Advocacy that suggests that cost as a percentage of total revenues is a metric for ev aluating cost increases on small entities in relation to increases on large entities. 8

7 The SBREFA compliance guidance to EPA ru lewriters regarding the types of small business analysis that should be considered can be found at http://www.epa.gov/sbre fa/documents/rfafinalguidance06.pdf, pp. 24-25.
8 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. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Electric Power Generation

(2211) Natural Gas Transmission

(48621) Crude Petroleum & NG Production (211111) Natural Gas Liquid Producers (211112) National Security (92811) Hydro Power Units (335312) Irrigation Sets (335312) Welders (333992) >750 hp

600

‐ 750 hp

500

‐ 600 hp

300

‐ 500 hp

175

‐ 300 hp

100

‐ 175 hp

50

‐ 100 hp

25

‐ 50 hp6-10 If the cost-to-receipt ratio is less than 1%, th en we consider the propos ed rule to not have a significant impact on the establishment comp any in question. We summarize the industries with cost-to-receipt ra tios exceeding 1% below:

Primary Analysis:

 Case 2 : NAICS 2211 with receipts less than $100,000 per year and NAICS 111 and 112 with receipts less than $25,000 per year

 Case 3 : No industries

Sensitivity Analysis (unlikely):

 Case 1 : NAICS 2211 with receipts less than $100,000 per year

In the Case 2 primary analysis, only esta blishments in NAICS 2211 with receipts less than $100,000 per year (less than 5 percent of th e total), and establishments in NAICS 111 and 112 with receipts less than $25,000 per year (around 30 percent of the total) have cost-to-receipt ratios above 1%. However, establishments earning this level of receipts ar e likely to be using smaller engines than those assumed in Case 2, su ch as 25 to 300 hp engines. The results of our Case 3 analysis demonstrate that these establishments are not significantly impacted when taking this engine size into account.

After considering the economic im pacts of this proposed rule on small entities, we certify
that this action will not have a significant economic impact on a substantial number of small
entities. This certification is ba sed on the economic impact of this proposal action to all affected
small entities across all industries affected. The percentage of sm all entities impacted by this proposal having annualized costs greater than 1 pe rcent of sales is less than 2 percent according to this analysis. We thus conc lude that there is no significant economic impact on a substantial number of small entities (SISNOSE) for this proposed rule.

Although the proposed rule would not have a significant economic impact on a
substantial number of small en tities, EPA nonetheless tried to reduce the impact of the rule on small entities. When developing the revised standards, EPA took sp ecial steps to ensure that the burdens imposed on small entities were minimal. EPA conducted several meetings with industry trade associations to discuss regulatory opti ons and the corresponding burden on industry, such as recordkeeping and reporting. In addition, as mentioned earlier in this preamble, EPA proposes to reduce regulatory requirements for a variety of area sources affected under this RICE rule with amendments to the final RICE rules promulgated in 2010. We continue to be interested in the6-11 potential impacts of this proposed rule on small entities and welcome comments on issues related to such impacts.

6.3 Small Government Entities

The rule also covers sectors that include entities owned by small and large governments. However, given the uncertainty and data li mitations associated with identifying and appropriately classifying these entities, we computed a “revenue” test for a model small government, where the annualized compliance cost is a percentage of annual government revenues (U.S. Census, 2005a, b). The use of a “r evenue test” for estimating impacts to small governments for a rulemaking such as this one is consistent with gui dance offered by EPA on compliance with SBREFA, 9 and is consistent with guidan ce published by the US SBA’s Office of Advocacy. 10 For example, from the 2007 Census (in 2008 dollars), the average revenue for small governments (counties and municipalitie s) with populations fewer than 10,000 is $4 million per entity, and the average revenue for lo cal governments with populations fewer than 50,000 is $9 million per entity (U.S. Census Bu reau, 2009a; U.S. Census Bureau, 2009b). For the smallest group of local governments (<10,000 peopl e), the cost-to-revenu e ratio would be 0.2% or less under each case. For the larger gr oup of governments (<50,000 people), the cost-torevenue ratio is 0.1% or less under all cases.

9 The SBREFA compliance guidance to EPA rule writers regard ing the types of small business analysis that should be considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf , pp. 24-25.
10 U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Comply with the Regulatory Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003.7-1 Section 7
HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS

Synopsis

Implementation of emissions controls required by the proposed SI RICE NESHAP reconsideration is expected to reduce emissi ons of hazardous air pollutants (HAP) and have ancillary co-benefits that would lo wer ambient concentrations of NO 2 , PM 2.5 and ozone. In this section, we quantify the monetized co-benefits for this rule associ ated 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 milli on 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 cas es of morbidity and premature mortality among populations exposed to PM 2.5 reduced by this rule. These estimates reflect EPA’s most current interpretation of the scie ntific literature. Higher or lower estimates of benefits are possible using other assumptions; examples of this ar e provided in Figure 7-2. Data, resource, and methodological limitations preven ted 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 ecosystem ef fects and visibility impairment. In addition to reducing emissions of PM precursors such as NO x, 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

This proposed reconsideration NES HAP would reduce emissions of NO X , and VOCs. Because these emissions are precursors to PM 2.5, reducing these emissi ons would also reduce
PM 2.5 formation, human exposure and the incidence of PM 2.5 -related health effects. Due to analytical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 -related benefits or provide estimates of the health be nefits associated with exposure to HAP, CO, NO 2 or ozone. Instead, we used the “benefit-per-ton” approach to estimate these benefits. The methodology employed in this analys is is similar to the work de scribed in Fann, Fulcher, and Hubbell (2009), but represents an improvement th at EPA believes would provide more reliable
estimates of PM 2.5 -related health benefits for emissions re ductions 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 of premature mortality and premature morbidity)7-2 of reducing one ton of PM 2.5 from a specified source. EPA has us ed the benefit per-ton technique in several previous RIAs, including the recent SO 2 NAAQS RIA (U.S. EPA, 2010).

The Integrated Science Assessment (ISA) for Particulate Matter (U.S. EPA, 2009b)
identified the human health effects associated with ambient PM 2.5, which include premature morality and a variety of morbidity effects associ ated with acute and chronic exposures. Table 7- 1 shows the quantified and unquantified benefits cap tured in those benefit-per-ton estimates, but
this table does not include entr ies for the unquantified health eff ects associated with exposure to
ozone and NO 2 nor welfare effects such as ecosystem ef fects and visibility impairment that are
described in section 7.2. It is important to emphasize that th e list of unquantified benefit categories is not exhaustive, nor is qu antification of each effect complete.7-3 Table 7-1: Human Health Effects of PM 2.5

Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information

(refers to CSAPR RIA) Improved Human Health

Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30)   Section 5.4

Infant mortality (age <1)   Section 5.4

Reduced incidence of morbidity from exposure to PM 2.5 Non-fatal heart attacks (age > 18)   Section 5.4 Hospital admissions—respiratory (all ages)   Section 5.4 Hospital admissions—cardiovascular (age >20)   Section 5.4 Emergency room visits for asthma (all ages)   Section 5.4 Acute bronchitis (age 8-12)   Section 5.4 Lower respiratory symptoms (age 7-14)   Section 5.4 Upper respiratory symptoms (asthmatics age 9-11)   Section 5.4 Asthma exacerbation (asthmatics age 6- 18)   Section 5.4 Lost work days (age 18-65)   Section 5.4 Minor restricted-activity days (age 18-65)   Section 5.4 Chronic Bronchitis (age >26)   Section 5.4 Emergency room visits for cardiovascular effects (all ages) -- -- Section 5.4 Strokes and cerebrovascular disease (age 50-79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA 2
Other respiratory effects (e.g., pulmonaryfunction, non-asthma ER visits, nonbronchitis chronic diseases, other ages and populations) -- -- PM ISA 2

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

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

1 We assess these benefits qualitatively due to tim e and resource limitations for this analysis.

2 We assess these benefits qualitatively because we do not have sufficient co nfidence in available data or methods.
3 We assess these benefits qualitatively because current evid ence is only suggestive of ca usality or there are other significant concerns over the strength of the association.

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the benefits estimates
utilize the concentration -response functions as reported in the epidemiology literature, as well as the 12 functions obtained in EPA’s expert elic itation study as a sens itivity analysis.7-4  One estimate is based on the concentrati on-response (C-R) function developed from the extended analysis of American Cancer Society (ACS) cohort, as reported in Pope et al. (2002), a study that EPA has previously used to generate its primary benefits estimate. When calculating the estimate, EPA applied the effect coefficient as reported in the study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent (2006-2009) Office of Air and Radiation RIAs.

 One estimate is based on the C-R function developed from the extended analysis of the Harvard Six Cities cohort, as reported by Laden et al (2006). This study, published after the completion of the Staff Paper for the 2006 PM 2.5 NAAQS, has
been used as an alternative estimate in the PM 2.5 NAAQS RIA and PM 2.5 benefits estimates in RIAs completed since the PM 2.5 NAAQS. When calculating the estimate, EPA applied the effect coeffici ent as reported in the study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent (2006-2009) RIAs.

 Twelve estimates are based on the C-R func tions from EPA’s e xpert elicitation study (Roman et al., 2008) on the PM 2.5 -mortality relationship and interpreted for benefits analysis in EPA’s final RIA for the PM 2.5 NAAQS. For that study, twelve experts (labeled A through L) provided independent estimates of the PM 2.5 -mortality concentration-response function. EPA pract ice has been to develop independent
estimates of PM 2.5 -mortality estimates corresponding to the concentration-response function provided by each of the twelve expe rts, to better characterize the degree of variability in the expert responses.

The effect coefficients are drawn from epidemiology studies examining two large population cohorts: the American Cancer Society cohort (Pope et al., 2002) and the Harvard Six Cities cohort (Laden et al., 2006). 1 These are logical choices for anchor points in our presentation because, while both studies are well designed and peer reviewed, there are strengths and weaknesses inherent in each, which we beli eve argues for using both studies to generate benefits estimates. Previously, EPA had cal culated 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 relati onship between exposure to PM 2.5 and premature mortality (Roman

1 These two studies specify multi-pollutant models that control for SO 2 , among other co-pollutants.7-5 et al., 2008). 2 Within this assessment, we include the benefits estimates derived from the concentration-response function provided by each of the twelve experts to better characterize the uncertainty in the concentration-response functio n for mortality and the degree of variability in the expert responses. Because the experts used these cohor t studies to inform their concentration-response functions, be nefits estimates using these f unctions generally fall between results using these epidemiology studies (see Figu re 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 genera l methodology for creating the benefit-per-ton estimates used in this analys is should consult the draft Tech nical 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 analysis and the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality modeling data utilized. In this analysis, we apply these na tional benefit-per-ton estimates calculated for this category for NOx and multiply them by the corresponding emission
reductions.

These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premat ure mortality because the scientific evidence is not yet sufficient
to allow differentiation of effects estimat es by particle type. NOx is the primary PM 2.5 precursors affected by this rule. Even though we assume that all fine particles have equivalent health effects, the benefit-per-ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 levels, which drive population e xposure. The sector-specific modeling does not provide estimates of the PM 2.5 -related benefits associated with reducing VOC emissions, but these unquantif ied benefits are generally small compared to other PM 2.5 precursors (U.S. EPA, 2012).

The benefit-per-ton coefficients in this analys is were derived using modified versions of the health impact functions used in the PM NAAQS Regulatory Impact Analysis (U.S. EPA, 2006). Specifically, this analysis uses the met hod first applied in the Portland Cement NESHAP RIA (U.S. EPA, 2009a), which applied the functi ons directly from the epidemiology studies

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 poin t source category. If the affected stationary engines are more rural than the average of the non-EGU sources modeled, then it is possible that the benefits may be somewhat less than we have estimated here. The TSD provides the geographic distribution of the air quality changes associated with this sector. It is important to emphasize that this modeling represents the best available information on the air quality impact on a per ton basis for these sources.7-6 without an adjustment for an assumed threshol d. Removing the threshold assumption is a key difference between the method used in this analys is of PM benefits and the methods used in RIAs prior to Portland Cement proposal, and we now calculate incremental benefits down to the
lowest modeled PM 2.5 air quality levels. 4

Based on our review of the current body of sc ientific literature, EPA now estimates PMrelated mortality without applying an a ssumed concentration threshold. EPA’s Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was reviewed by EPA’s Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b),
concluded that the scientific literature consis tently finds that a no-th reshold log-linear model most adequately portrays the PM-mortality concentration-response relationship while recognizing potential uncertainty about the exact shape of the c oncentration-response function.

Consistent with this finding, we have c onformed the previous threshold sensitivity analysis to the current state of the PM scienc e by incorporating a “Lowest Measured Level” (LML) assessment, which is a method EPA has em ployed in several recent RIAs including the Cross-State Air Pollution Rule (U .S. EPA, 2011b). This information allows readers to determine the portion of population exposed to annual mean PM 2.5 levels at or above the LML of each study; in general, our co nfidence in the estimated PM mortal ity decreases as we consider air quality levels further below the LML in major cohort studies that estim ate PM-related mortality. While an LML assessment provides some insight into the level of uncertainty in the estimated PM mortality benefits, EPA does not view the LM L as a threshold and continues to quantify PMrelated mortality impacts using a full range of mode led air quality concentra tions. It is important to emphasize that we have high confidence in PM 2.5 -related effects down to the lowest LML of the major cohort studies, which is 5.8 μg/m 3 . Just because we have greater confidence in the benefits above the LML, this does not mean th at we have no confidence that benefits occur below the LML. For a summary of the scientif ic review statements regarding the lack of a
threshold in the PM 2.5 -mortality relationship, see the T echnical Support Document (TSD)
entitled Summary of Expert Opinions on the Existe nce of a Threshold in the ConcentrationResponse Function for PM 2.5 -related Mortality (U.S. EPA, 2010b).

For this analysis, policy-specific air quality data is not 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 ru le’s emission reductions at each PM 2.5 level. However, we believe that it is still important to characterize the distri bution of exposure to base line air quality levels.

4 Additional updates since the Cement RIA include a revised VSL and updated baseline incidence rates.7-7 As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionmen t modeling used to calculate the benefit-per-ton estimates for this sector. It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline inciden ce rates population, and change in air quality. In other words, the per centage of the population exposed to air pollution below the LML is not the same as the percenta ge of the population experiencing health impacts as a result of a specific emission reduction polic y. The most important aspect, which we are unable to quantify for rules without rule-specifi c air quality modeling, is the shift in exposure associated with this specific rule. Therefor e, caution is warranted when interpreting the LML
assessment for this rule. The results of this analysis are provided in Section 7.3.

As is the nature of RIAs, the assumptions and methods used to estimate air quality benefits evolve over time to reflect the Agency’s most current interpretation of the scientific and economic literature. For a period of time ( 2004-2008), the Office of Air and Radiation (OAR) valued mortality risk reductions using a value of statistical life (VSL) estimate derived from a limited analysis of some of the available studi es. OAR arrived at a VSL using a range of $1 million to $10 million (2000$) consistent with two meta-analyses of the wage-risk literature. The $1 million value represented the lower end of the interquartile range from the Mrozek and Taylor (2002) meta-analysis of 33 studies. Th e $10 million value represented the upper end of the interquartile range from the Viscusi and Aldy (2003) meta-ana lysis of 43 studies. The mean estimate of $5.5 million (2000$) 5 was also consistent with the mean VSL of $5.4 million estimated in the Kochi et al. (2006) meta-analysi s. However, the Agency neither changed its official guidance on the use of VSL in rulema kings nor subjected the interim estimate to a scientific peer-review process through the Scie nce Advisory Board (SAB ) or other peer-review

group.

During this time, the Agency continued work to update its guidance on valuing mortality risk reductions, including commissioning a repo rt from meta-analytic experts to evaluate methodological questions raised by EPA and the SAB on combining estimates from the various data sources. In addition, the Agency consulte d several times with the Science Advisory Board Environmental Economics Advisory Committee (SAB-EEAC) on the i ssue. With input from the meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, appropriate meta-analytic tech niques to combine estimates from unique data sources and

5 After adjusting the VSL for a different currency year (2010$) and to account for income growth to 2 015 of the $5.5 million value, the VSL is $8.0 million.7-8 different studies, including those using differe nt methodologies (i.e., wage-risk and stated preference) (U.S. EPA-SAB, 2007).

Until updated guidance is availabl e, the Agency determined that a single, peer-reviewed estimate applied consistently best reflects the SAB-EEAC advice it has re ceived. Therefore, the Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparing Economic Analyses (U.S. EPA, 2000) 6 while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates
derived from 26 labor market and contingent valuation st udies published between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$). 7 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made significant progre ss in responding to the SAB-EEAC’ s specific recommendations.

In implementing these rules, emission cont rols may lead to reductions in ambient PM 2.5 below the National Ambient Air Quality Standard s (NAAQS) for PM in some areas and assist other areas with attaining th e PM NAAQS. Because the PM NAAQS RIAs also calculate PM benefits, there are important differences worth no ting in the design and anal ytical objectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air quality standard nationwide based on an array of emission control st rategies for different sources. In short, NAAQS RIAs hypothesize, but do not pred ict, the control strate gies that States may choose to enact when implementing a NAAQS. The setting of a NAAQS doe s not directly result in costs or benefits, and as such, the NAAQS RI As are merely illustrative and are not intended to be added to the costs and benefits of other regula tions that result in speci fic costs of control and emission reductions. However, some costs and be nefits estimated in this RIA account for the same air quality improvements as estimated in the illustrative PM 2.5 NAAQS RIA.

By contrast, the emission reductions for impl ementation rules are from a specific class of well-characterized sources . In general, EPA is more confident in the ma gnitude and location of the emission reductions for implementation rule s rather than illustrative NAAQS analyses.
Emission reductions achieved unde r these and other promulgate d rules will ultimately be reflected in the baseline of future NAAQS an alyses, which would reduce the incremental costs

6 In revised Economic Guidelines (U.S. EPA, 2010c), EPA retained the VSL endorsed by the SAB with the understanding that further updates to the mortality risk va luation guidance would be forthcoming in the near future. Therefore, this report does not represent final agency policy.
7 This value is $4.8 in 1990$. In this analysis, we adjust the VSL to account for a different currency year ($2010) and to account for income growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is $9.2 million.7-9 and benefits associated with attaining th e NAAQS. EPA remains forward looking towards the next iteration of the 5-year re view cycle for the NAAQS, and as a result does not issue updated RIAs for existing NAAQS that retroactively update the baseline for NAAQS implementation. For more information on the relationship between the NAAQS and rules such as analyzed here, please see Section 1.2.4 of the SO 2 NAAQS RIA (U.S. EPA, 2010a).7-10 Figure 7.1 illustrates the relativ e breakdown of the monetized PM 2.5 health benefits.

Figure 7-1: Breakdown of Monetized PM 2.5 Health Benefits using Mortality Function from Pope et al. (2002)* *This pie chart breakdown is illustrative, using the results based on Pope et al. (2002) as an example. Using the Laden et al. (2006) function for premat ure mortality, the percentage of total monetized benefits due to adult mortality would be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be similar if a 7% discount rate was used.

Table 7-2 provides a general summary of th e monetized PM-related health benefits by precursor, including the emission re ductions and benefit-per-ton es timates at discount rates of
3% and 7%. 8 Table 7-3 provides a summary of the reducti ons in health incidences as a result of the pollution reductions. In Table 7-4, we provide the benefits using our anchor points of Pope
et al. and Laden et al. as well as the results fr om the expert elicitation on PM mortality. Figure 7-2 provides a visual repres entation 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 speci fic analysis year (i.e., 2013), and mo st of the PM benefits occur within that year with two excep tions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow-up medical co sts and lost wages. For premature mort ality, we assume that there is a “cessation” lag between PM exposures and the total reali zation of changes in health effects. Although the structure of the lag is uncertain, EPA follows the advice of the SAB-HES to assume a segmented lag structure characterized by 30% of mortality reductions in the first y ear, 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 la g 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 prematur e mortalities that occur after the analysis year. As such, the monetized benefits using a 7% discount rate are only approximately 10% less than the monetized benefits using a 3% discount rate. Adult Mortality ‐ Pope et al. 93% Chronic Bronchitis 4%

AMI 2% Acute Respiratory Symptoms 0.5%

Infant Mortality 0.4%

Work Loss Days 0.2%

Hospital Admissions, Cardio 0.2% Hospital Admissions, Resp 0.04% Asthma Exacerbation 0.01%
Acute Bronchitis 0.01% Upper Resp Symp 0.00% Lower Resp Symp 0.00%
ER Visits, Resp 0.00% Other 1%7-11 concentration-response functions supplied by ex perts. Figure 7-3 shows a breakdown of monetized benefits by engine size.

The benefit-per-ton estimates shown in this RIA are different than the benefit-per-ton
estimates cited in the 2010 final SI RICE RIA for two reasons. First, these estimates are based on updated air quality modeling, which results in s lightly higher benefits per ton for other nonEGU point sources than the previous modeling. Second, these estimates have been inflated to 2010$. Third, the new air quality modeling did not provide estimates associated with reducing
VOCs.

Table 7-2: General Summary of Monetized 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 (millions of 2010$ at 3%) Total Monetized Benefits (millions 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 im pairment. 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 th is 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-Benefits for Proposed SI RICE NESHAP Reconsideration*

Avoided Premature Mortality Pope et al. 7

Laden et al. 18 Avoided Morbidity

Chronic Bronchitis 5 Emergency Department Visits, Respiratory 5 Hospital Admissions, Respiratory 1 Hospital Admissions, Cardiovascular 3

Acute Bronchitis 11 Lower Respiratory 140 Upper Respiratory 110 Minor Restricted Activity Days 5,600 Work Loss Days 950

Asthma Exacerbation 230 Acute Myocardial Infarction 8 * All estimates are for the analysis year (2013) and are rounded to whole numbers with two significant figures. All fine particles are assumed to have equivalent health effect s because the scientific eviden ce is not yet sufficient to allow differentiation of effects estimate s by particle type. Confidence interval s 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 Deri ved from Epidemiology Literature Pope et al. $62 $55
Laden et al. $150 $140 Benefit-per-ton Coefficients D erived 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 signifi cant figures. The benefits estimates fr om the Expert Elicitation are provided as a reasonable characterization of the uncertainty in th e mortality estimates associated with the concentrationresponse function. Confidence interval s are unavailable for this analysis becau se of the benefit-per-ton methodology7-14 Figure 7-2: Total Monetized PM 2.5 Co-Benefits of Propos ed SI RICE NESHAP Reconsideration in 2013 *This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration-response function provided in those studies. $0 $50 $100 $150 $200 $250

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

PM 2.5 mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions 3% DR
7% DR7-15 Figure 7-3: Breakdown of Total Monetized PM 2.5 Co-Benefits of 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 as sociated with ambient fine part icles. Data, time, and resource limitations prevented EPA from quantifying the impacts to, or monetizing the benefits from several important benefit categories, including benefits from reducing exposure to HAP, CO,
NO 2 , and ozone exposure, as well as ecosystem eff ects, 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 Toxi cs Assessment (NATA) predicts that most Americans are exposed to ambient concentrations of air toxics at levels that have the potential to cause adverse health effects (U.S. EPA, 2011c). 9 The levels of air toxics to which people are exposed vary depending on where people live and wo rk and the kinds of activities in which they engage. In order to identify and prioritize air toxics, emission s ource types and locations that are

9 The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/. Area 500

‐ 600 HP 21%

Area 600

‐ 750 HP 5%

Area >750 HP 74%7-16 of greatest potential concern, U.S. EPA conducts the NATA. 10 The most recent NATA was conducted for calendar year 2005 and was released in March 2011. NATA includes four steps:

1) Compiling a national emissions inventory of air toxics emissions from outdoor sources

2) Estimating ambient and exposure concentratio ns of air toxics across the United States

3) Estimating population exposur es 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 a bout 5% of census tracts nationwide have increased cancer risks greater than 100 in a milli on. The average national cancer risk is about 50 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldehyde and benzene. 11 Secondary formation (e.g., formaldehyde forming from other emitted pollutants) was the largest contributor to cancer risks, while stationary, mobile and background sources contribute almost equal portions of the remaining cancer risk.

Noncancer health effects can result from chronic, 12 subchronic, 13 or acute 14 inhalation exposures to air toxics, and incl ude neurological, cardiovascular, liver, kidney, and respiratory
effects as well as effects on the immune and reproductive systems. According to the 2005 NATA, about three-fourths of the U.S. popul ation 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 acro lein is the primary driver for noncancer respiratory risk.

10 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertain ties 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 maki ng process. U.S. EPA.(2011). 2005 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/
11 Details about the overall confidence of certainty ranking of the individual pieces of NATA assessments including both quantitative (e.g., model-to-monitor ratios) and qua litative (e.g., quality of data, review of emission inventories) judgments can be found at h ttp://www.epa.gov/ttn/atw/nata/roy/page16.html.
12 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database (http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal species).
13 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species).
14 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.7-17 Figure 7-4 and Figure depict the estimate d census tract-level carcinogenic risk and noncancer respiratory hazard from the assessment. It is important to note that large reductions in HAP emissions may not necessarily translate into significant reductions in health risk because toxicity varies by pollutant, and exposures ma y or may not exceed levels of concern. For example, acetaldehyde mass emissions are more than double acrolein emissions on a national basis, according to EPA’s 2005 National Emissions Inventory (NEI). However, the Integrated Risk Information System (IRIS) reference concentr ation (RfC) for acrolein is considerably lower than that for acetaldehyde, suggesting that acro lein could be potential ly more toxic than acetaldehyde. Thus, it is important to account for the toxicity and exposure, as well as the mass of the targeted emissions.

Figure 7-4 Estimated Chronic Census Tract Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA)7-18 Figure 7-5 Estimated Chronic Census Trac t Noncancer (Respiratory) Risk from HAP exposure from outdoor sources (2005 NATA)

Due to methodology and time limitations under the court-ordered schedule, we were
unable to estimate the benefits associated with the hazardous air pollutants that would be reduced as a result of these rules. In a few previous anal yses of the benefits of reductions in HAP, EPA has quantified the benefits of poten tial reductions in the incidences of cancer and non-cancer risk (e.g., U.S. EPA, 1995). In those analyses, EPA relied on unit risk f actors (URF) developed through risk assessment procedures. 15 These URFs are designed to be conservative, and as such, are more likely to represent the hi gh end of the distribution of risk rather than a best or most likely estimate of risk. As the purpose of a benefit analysis is to describe the benefits most likely
to occur from a reduction in pollution, use of high-end, conser vative risk estimates would overestimate the benefits of the regulation. While we used high-end risk estimates in past analyses, advice from the EPA’s Science Adviso ry Board (SAB) recommended that we avoid

15 The unit risk factor is a quantitative estimate of the ca rcinogenic 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 analyses (U.S. EPA-SAB, 2002). Since this time, EPA has continued to develop better methods for an alyzing the benefits of reductions in HAP.

As part of the second prospective analysis of the benefits and costs of the Clean Air Act (U.S. EPA, 2011a), EPA conducted a case study analys is of the health eff ects associated with reducing exposure to benzene in Houston from implementation of the Clean Air Act (IEc, 2009). While reviewing the draft report, EPA’s Adviso ry Council on Clean Air Compliance Analysis concluded that “the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air polluta nts (HAPs) are daunting...due to a lack of exposure-response functions, uncertainties in em issions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods ” (U.S. EPA-SAB, 2008).

In 2009, EPA convened a workshop to address th e inherent complexities, limitations, and uncertainties in current methods to quantify the benefits of reducing HAP. Recommendations from this workshop included identifying rese arch priorities, focu sing on susceptible and vulnerable populations, and improving dose-respon se relationships (Gwinn et al., 2011).

In summary, monetization of the benefits of reductions in cancer incidences requires several important inputs, includi ng central estimates of cancer risk s, estimates of exposure to carcinogenic HAP, and estimates of the value of an avoided case of cance r (fatal and non-fatal). Due to methodology and time limitations under the cour t-ordered schedule, we did not attempt to
monetize the health benefits of reductions in HAP in this analysis. Instead, we provide a qualitative analysis of the heal th effects associated with the HAP anticipated to be reduced by these rules.EPA remains committed to improving methods for estimating HAP benefits by continuing to explore additional concepts of benefits, including changes in the distribution of
risk.

Although numerous HAPs may be emitted from SI RICE, a few HAPs account for over 90% of the total mass of HAPs emissions emitted. These HAPs are formaldehyde (72%), acetaldehyde (8%), acrolein (7%), methanol (3%), and benzene (3%). Although we do not have estimates of emission reductions for each HAP, this rule is anticipated to reduce 1,800 tons of HAPs each year. Below we describe the health effects associated with the top 5 HAPs by mass emitted from SI RICE.7-20 Formaldehyde

Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on evidence in humans and in rats, mice, hamsters, and monkeys. 16 Substantial additional research
since that time informs current scientific understanding of the health effect s associated with exposure to formaldehyde. These include recently published research conducted by the National Cancer Institute (NCI) which found an incr eased risk of nasopharyngeal cancer and lymphohematopoietic malignancies such as leukemia among workers exposed to formaldehyde. 17,18 In an analysis of the lymphohematopoi etic cancer mortality from an extended follow-up of these workers, NCI confirmed an a ssociation between lymph ohematopoietic cancer risk and peak formaldehyde exposures. 19 A recent NIOSH study of garment workers also found
increased risk of death due to leukem ia among workers exposed to formaldehyde. 20 Extended follow-up of a cohort of British chemical work ers did not find evidence of an increase in nasopharyngeal or lymphohematopoi etic cancers, but a continuing st atistically significant excess in lung cancers was reported. 21

In the past 15 years there has been substa ntial research on the inhalation dosimetry for formaldehyde in rodents and primates by the Ch emical Industry Institute of Toxicology (CIIT,
now renamed the Hamner Institutes for Health Scie nces), with a focus on use of rodent data for refinement of the quantitative can cer dose-response assessment. 22 , 23 , 24 CIIT’s risk assessment of

16 U.S. EPA. 1987. Assessment of Health Risks to Garment Workers and Certain Home Residents from Exposure to Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA-HQ-OAR-2010-0162.
17 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615- 1623. Docket EPA-HQ-OAR-2010-0162.
18 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 20 04. Mortality from solid cancers amongworkers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130. Docket EPA-HQOAR-2010-0162.
19 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Ha yes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National Cancer Institute cohort. J. National Cancer Inst . 101: 751-761. Docket EPA-HQ-OAR-2010-0162.
20 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers e xposed to formaldehyde: an update. Occup. Environ. Med. 61: 193-200. Docket EPA-HQ-OAR-2010-0162.
21 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. Docket EPA-HQ-OAR-2010-0162.
22 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller. 2003. Biologically motivated computational modeling of formaldehyde carcinogenicity in the F344 rat. Tox Sci 75: 432-447. Docket EPA-HQ-OAR-2010-0162.
23 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, an d FJ Miller. 2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose-response predictions derived from biologically-motivatedcomputational modeling of a combined rodent and human dataset. Tox Sci 82: 279-296. Docket EPA-HQ-OAR2010-0162.7-21 formaldehyde incorporated mechanistic and dosi metric information on formaldehyde. These data were modeled using a biologically-motivated two- stage clonal growth model for cancer and also a point of departure based on a Benchmark Dose approach. However, it should be noted that recent research published by EPA indicates that when two-stage modeling assumptions are varied, resulting dose-response estimates can vary by several orders of magnitude. 25 , 26 , 27 , 28 These findings are not supportive of inte rpreting the CIIT model results as providing a conservative (health protective) estimate of human risk. 29 EPA research also examined the contribution of the two-stage modeling for formaldehyde towards charac terizing the relative weights of key events in the mode-of-action of a carcinogen. For exampl e, the model-based inference in the published CIIT study that formaldehyde’s direct mutageni c action is not relevant to the compound’s tumorigenicity was found not to hold unde r variations of modeling assumptions. 30

Based on the developments of the last d ecade, in 2004, the working group of the IARC concluded that formaldehyde is carcinogenic to humans (Group 1), on the basis of sufficient evidence in humans and sufficient evidence in expe rimental animals - a higher classification than previous IARC evaluations. Afte r reviewing the currently available epidemiological evidence, the IARC (2006) characterized the human evid ence for formaldehyde carcinogenicity as “sufficient,” based upon the data on nasophar yngeal cancers; the epid emiologic evidence on leukemia was characterized as “strong.” 31

Formaldehyde exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of the eyes), nose and throat. Effects from repeated

24 Chemical Industry Institute of Toxicology (CIIT).1999 . Formaldehyde: Hazard characterization and dose-response assessment for carcinogenicity by the route of inhalation. CIIT, September 28, 1999. Research Triangle Park, NC. Docket EPA-HQ-OAR-2010-0162.
25 U.S. EPA. Analysis of the Sensitivity and Uncertainty in 2-Stage Clonal Growth Models for Formaldehyde with Relevance to Other Biologically-Based Dose Response (BBDR) Models. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-08/103, 2008. Docket EPA-HQ-OAR-2010-0162.
26 Subramaniam, R; Chen, C; Crump, K; .et .al. (2008) Uncertainties in biologically-based modeling of formaldehyde-induced cancer risk: identification of ke y issues. Risk Anal 28(4):907-923. Docket EPA-HQOAR-2010-0162.
27 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. Docket EPA-HQ-OAR-2010-0162.
28 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.
29 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.
30 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. Docket EPA-HQ-OAR-2010-0162.
31 International Agency for Research on Cancer (2006) Formaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2- ol. Monographs Volume 88. World Health Organization, Lyon, France. Docket EPA-HQ-OAR-2010-0162.7-22 exposure in humans include resp iratory tract irritation, chronic bronchitis and na sal epithelial lesions such as metaplasia and loss of cilia. Animal studies suggest that formaldehyde may also cause airway inflammation – including eosinophil infi ltration into the airways. There are several studies that suggest that formal dehyde may increase the risk of asthma – particularly in the

young. 32 , 33

The above-mentioned rodent and human studies , as well as mechanistic information and their analyses, were evaluated in EPA’s recent Draft Toxicological Review of Formaldehyde – Inhalation Assessment through the Integrated Risk Information System (IRIS) program. This
draft IRIS assessment was releas ed in June 2010 for public review and comment and external peer review by the National Research Council (NRC) . The NRC released their review report in April 2011 ( http://www.nap.edu/cata log.php?record_id=13142 ). The EPA is currently revising the draft assessment in response to this review.

Acetaldehyde

Acetaldehyde is classified in EPA’s IRIS da tabase as a probable human carcinogen, based on nasal tumors in rats, and is considered toxi c 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 Servi ces (DHHS) in the 11 th Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC. 35,36 The primary noncancer effects of exposure to acetaldehyde vapors include irrita tion of the eyes, skin, and respiratory tract. 37

32 Agency for Toxic Substances and Disease Registry (A TSDR). 1999. Toxicological profile for Formaldehyde. Atlanta, GA: U.S. Department of Health an d Human Services, Pub lic 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). 19 91. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.
35 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183.
36 International Agency for Research on Cancer (IARC). 1999. Re-evaluation of some organic chemicals, hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, Vol 71. Lyon, France.
37 U.S. Environmental Protection Agency (U.S. EPA). 19 91. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.7-23 Acrolein

EPA determined in 2003 that the human carci nogenic potential of acr olein could not be
determined because the available data were in adequate. No information was available on the carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of carcinogenicity. 38 The IARC determined in 1995 that acro lein was not classifiable as to its carcinogenicity in humans. 39

Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure resulting in upper respiratory tr act irritation, mucus hypersecreti on and congestion. The intense irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who suffer intolerable eye and nasal mucosal sens ory reactions within minutes of exposure. 40 These data and additional studies regarding acute effects of human exposure to acrolein are
summarized in EPA’s 2003 IRIS Huma n 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 symptoms. 42 Lesions to the lungs a nd upper respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein. 43 Acute exposure effects in animal studies report bronchial hyper-responsiveness. 44 In a recent study, the acute respiratory irrita nt effects of exposure to 1.1 ppm acrolein were more pronounced in mice with allergic airway disease by comparison to non-diseased mice wh ich 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 Environm ental Assessment, Washington, DC. This material is available at http://www.epa.g ov/iris/toxreviews/0364tr.pdf.
39 International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals, World Health Organization, Lyon, France.
40 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. EPA/635/R-03/003. p. 10. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
41 U.S. Environmental Protection Agency (U.S. EPA). 2003. In tegrated Risk Information System File of Acrolein. 2003. Research and Development, National Center for Environmental Assessm ent, Washington, DC. EPA/635/R-03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
42 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. p. 11. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
43 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/to xreviews/0364tr.pdf.
44 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/to xreviews/0364tr.pdf.7-24 respiratory rate. 45 Based on these animal data and demons tration of similar effects in humans (i.e., reduction in respiratory ra te), individuals with compro mised respiratory function (e.g., emphysema, asthma) are expected to be at incr eased risk of developi ng 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 exposur e is associated with additional health effects, including genetic changes in both humans and animals and increase d proliferation of bone marrow
cells in mice. 46,47,48 EPA states in its IRIS database that data indicate a causal relationship between benzene exposure and acute lymphocytic leukemia and suggest a relationship between benzene exposure and chronic non-lymphocytic leukemia a nd chronic lymphocytic leukemia. The IARC
has determined that benzene is a human carcin ogen and the DHHS has characterized benzene as a known human carcinogen. 49,50 A number of adverse noncancer health effects including blood disorders, such as preleukemia and aplastic anemia, have also been associated with long-term exposure to benzene. 51,52

45 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immedi ate sensory nerve-mediated respiratory responses to irritants in healthy and allergic airway-diseased mice. J Appl Physiol 94(4):1563-1571.
46 U.S. Environmental Protection Agency (U.S. EPA). 2000. Integrated Risk Information System File for Benzene. Research and Development, National Center for Environm ental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0276.htm.
47 International Agency for Research on Cancer, IARC monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agen cy for Research on Cancer, World Health Organization, Lyon, France, p. 345-389, 1982.
48 Irons, R.D.; Stillman, W.S.; Colagiova nni, D.B.; Henry, V.A. (1992) Synergis tic 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, So me industrial chemicals an d dyestuffs, World Health Organization, Lyon, France.
50 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183.
51 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197.
52 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554.7-25 Methanol

Exposure of humans to methanol by inhalation or ingestion may result in central nervous system depression and degenerative changes in the brain and visual system s. After inhaled or ingested, methanol is converted to formate, a hi ghly 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 de velopmental toxicity in rats and mice, and reproductive and developmental toxicity in monkeys. A number of studies have reported adverse effects in the offspring of rats and mice expos ed to methanol by inha lation including reduced weight of brain pituitary gla nd, thymus, thyroid, reduced overall fetal body weight and increased
incidence of extra ri bs and cleft palate. 54,55,56 Methanol inhalation studies using rhesus monkeys have reported a decrease in th e length of pregnancy, and limited evidence of impaired learning ability in offspring. 57,58,59,60 EPA has not classified methanol w ith 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 hea lth effects of those compounds can be found in
EPA’s IRIS database. 61

53 Rowe, VK and McCollister, SB. 1981. Alcohols. In: Patty's Industrial Hygiene and Toxicology, 3rd ed. Vol. 2C, GD Clayton, FE Clayton, Eds. John Wiley & Sons, New York, pp. 4528-4541.
54 New Energy Development Organization (NEDO). 1987. Toxico logical research of methan ol as a fuel for power station: summary report on tests with monkeys, rats and mice. Tokyo, Japan.
55 Nelson, BK; Brightwell, WS; MacKenzie, DR; Khan, A; Burg, JR; Weigel, WW; Goad, PT. 1985. Teratological assessment of methanol and ethanol at high inhalation levels in rats. Toxicol Sci, 5: 727-736.
56 Rogers, JM; Barbee, BD; Re hnberg, BF. 1993. Critical periods of sensitivity for the developmental toxicity of inhaled methanol. Teratology, 47: 395.
57 Burbacher, T; Grant, K; Shen, D; Damian, D; E llis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part II: developmental effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA.
58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part I: methanol disposition and reproductive toxicity in adu lt females. Health Effects Institute. Cambridge, MA.
59 Burbacher, TM; Grant, KS; Sh en, DD; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (Macaca fascic ularis): reproductive performance and birth outcome. Neurotoxicol Teratol, 26: 639-650.
60 Burbacher, TM; Shen, DD; Lalovic, B; Grant, KS; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (M acaca fascicularis): exposure and toxicokinetics prior to and during pregnancy. Neurotoxicol Teratol, 26: 201-221.
61 U.S. EPA Integrated Risk Information System (IR IS) database 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 emissions are also associated with a variety of respiratory health e ffects. Unfortunately, we were unable to estimate the health
benefits associated with reduced NO 2 or ozone exposure in this an alysis because we do not have air quality modeling data availabl e. Therefore, this analysis only quantifies and monetizes the
PM 2.5 benefits associated w ith the reductions in NO 2 emissions.

Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment (ISA) for Nitrogen Dioxide conc luded that there is a likely causal relationship between respiratory he alth effects and short-term exposure to NO 2 (U.S. EPA, 2008c). Persons with pr eexisting 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 ISA identified as a “likely causal relationship”: asthma exacerbation, respiratory -related emergency department visits, and respiratory-related hospitalizations. The differi ng evidence and associated strength of the
evidence for these different effects is described in detail in the NO 2 ISA. The NO 2 ISA also
concluded that the relations hip between short-term NO 2 exposure and premature mortality was “suggestive but not sufficient to infer a causal rela tionship” because it is difficult to attribute the mortality risk effects to NO 2 alone. Although the NO 2 ISA stated that studies consistently reported a relationship between NO 2 exposure and mortality, the e ffect was generally smaller than that for other pollutants such as PM.

NOx emissions also contribute to a variety of adverse we lfare effects, including acidic deposition, visibility impairment, nutrient enrichment. Deposition of nitrogen causes acidification, which can cause a loss of biodiversity of fi shes, zooplankton, and macro invertebrates in aquatic ecosystems, as well as a decline in sensitive tree species, such as red spruce ( Picea rubens ) and sugar maple ( Acer saccharum ) in terrestrial ecosystems. In the northeastern United States, the surface waters aff ected by acidification are a source of food for
some recreational and subsistence fishermen and for other consumers and support several cultural services, including aesthe tic and educational services and recreational fishing. Biological
effects of acidification in terres trial ecosystems are generally linke d 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, a nd disease leading to increased mortality of canopy trees. Terrestrial acidification affects several important ecological services, including declines in habitat for threatened and endange red species (cultural), declines in forest aesthetics (cultural),7-27 declines in forest productivity (p rovisioning), and increases in fore st soil erosion and reductions in water retention (cultural a nd regulating). (U.S. EPA, 2008d)

Deposition of nitrogen is also associated with aquatic and terrestrial nutrient enrichment. In estuarine waters, excess nutri ent enrichment can lead to eu trophication. Eutrophication of estuaries can disrupt an importa nt source of food production, part icularly fish and shellfish production, and a variety of cultural ecosystem se rvices, including water-based recreational and
aesthetic services. Terre strial nutrient enrichment is associ ated with changes in the types and number of species and biodiversit y in terrestrial systems. Exce ssive nitrogen deposition upsets the balance between native and nonnative plants, ch anging the ability of an area to support biodiversity. When the composition of species ch anges, then fire frequency and intensity can also change, as nonnative grasses fuel more fre quent and more intense wildfires. (U.S. EPA, 2008d)
7.2.3 Ozone Co-Benefits
In the presence of sunlight, NOx and VOC s can undergo a chemical reaction in the atmosphere to form ozone. Reducing ambien t ozone concentrations is associated with significant human health benefits, including mort ality and respiratory morbidity (U.S. EPA, 2008a). Epidemiological researchers have associat ed 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 fewe r asthma attacks, hospital and ER visits, school loss days, as well as premature mortality.
7.2.4 Carbon Monoxide Co-Benefits
Carbon monoxide in ambient air is formed primarily by the incomplete combustion of carbon-containing fuels and photochemical reactions in the atmosphere. The amount of CO emitted from these reactions, relative to carbon dioxide (CO 2 ), is sensitive to conditions in the combustion zone, such as fuel oxygen content, burn temper ature, or mixing time. Upon inhalation, CO diffuses through the respiratory system to the blood, which can cause hypoxia (reduced oxygen availability). Carbon monoxide can elicit a broad range of effects in multiple tissues and organ systems that are dependent upon concentration and duration of e xposure. The Integrated Science Assessment for Carbon Monoxide (U.S. EPA, 2010a) concluded that s hort-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 individua ls 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 morbid ity and mortality. The evidence is also suggestive of a causal relationship for birth outcomes and developmental effects following long-term exposure to CO, and for central nervous system effects linked to short- and long-term exposure to CO.

7.2.5 Visibility Impairment Co-Benefits

Reducing secondary formation of 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 pa rticles and gases degrade visibility by scattering and absorb ing light. Higher visibility impa irment levels in the East are due to generally higher concentrations of fine pa rticles, particularly su lfates, and higher average relative humidity levels. Visibility has direct significance to people’s enjoyment of daily
activities and their overall sense of wellbeing. Good visibility increases the quality of life where individuals live and work, and wh ere they engage in recreational activities. Previous analyses (U.S. EPA, 2006; U.S. EPA, 2011a; U.S. EPA, 2011b) show that visibility benefits are a significant welfare benefit cate gory. Without air quality modeling, we are unable to estimate visibility related benefits, nor are we able to determine whethe r VOC emission reductions would be likely to have a significant impact on vi sibility in urban ar eas or Class I areas.

7.3 Characterization of Uncertaint y in the Monetized Co-Benefits
In any complex analysis, there are likely to be many sources of uncertainty. Many inputs
are used to derive the final estimate of econo mic benefits, including emission inventories, air quality models (with their associated paramete rs and inputs), epidemio logical estimates of concentration-response (C-R) f unctions, estimates of values , population estimates, income estimates, and estimates of the future state of the world (i.e., regula tions, technology, and human behavior). For some parameters or inputs it may be possible to provide a statistical representation of the underlying unc ertainty distribution. For othe r parameters or inputs, the necessary information is not avai lable. As discussed in the PM 2.5 NAAQS RIA (Table 5.5) (U.S. EPA, 2006), there are a variety of uncertainties associated with th ese PM benefits. Therefore,
the estimates of annual benefits should be viewed as representative of the magnitude of benefits expected, rather than the actual bene fits that would o ccur every year.

It is important to note that the monetized benefit-per-ton estimates used here reflect specific geographic patterns of emissions redu ctions and specific air quality and benefits7-29 modeling assumptions. For example, these estimates do not reflect local va riability in population density, meteorology, exposure, baseline health inci dence 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 qua lity modeling. Great care should be taken in applying these estimates to emission reductions o ccurring in any specific location, as these are all based on national or broad regional emissi on reduction programs and therefore represent average benefits-per-ton over the entire Unit ed States. The benefits-per-ton for emission reductions in specific locations may be very differe nt than the estimates presented here. For more information, see the TSD describing the calcula tion of the new benefit-per-ton estimates (U.S. EPA, 2012).

PM 2.5 mortality benefits are the largest benef it category that we monetized in this analysis. To better characterize the uncertainty associated with mort ality impacts that are
estimated to occur in areas with low baseline levels of PM 2.5 , we included the LML assessment. For this analysis, policy-specifi c air quality data is not avai lable due to time or resource limitations, thus we are unable to estimate the per centage of premature mortality associated with this specific rule’s emission reductions at each PM 2.5 level. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionment modeling used to calculate the benefit-per-ton estimates for this sector. A very large proportion of the population is exposed at or above the lowest LML of the cohort studies (Figures 7-6 and 7-7), increasing our conf idence in the PM mortality analysis. Figure 7-6
shows a bar chart of the percentage of the population exposed to various air quality levels in the pre- and post-policy policy. Figure 7-7 shows a cumulative distribution function of the same data. Both figures identify the LML for each of the major cohort studies. As the policy shifts the distribution of air quality leve ls, fewer people are exposed to PM 2.5 levels at or above the LML. Using the Pope et al. (2002) study, the 77 % of the population is exposed to annual mean
PM 2.5 levels at or above the LML of 7.5 μg/m 3 . Using the Laden et al. (2006) study, 25% of the population is exposed above the LML of 10 μg/m 3

. As we model avoided premature deaths among populations exposed to levels of PM 2.5 , we have lower confidence in levels below the LML for each study. It is important to em phasize that we have high confidence in PM 2.5 -related effects down to the lowest LML of the major c ohort 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 baselin e exposure occurs below the level of the National Ambient Air Quality Standard (NAAQS) for annual PM 2.5 at 15 μg/m 3 ,which was set in 2006. It is7-30 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 consid eration 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 tota l benefits estimate.

Figure 7-6. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline7-31 Figure 7-7. Cumulative Distribution of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline

Above we present the estimates of the total benefits, based on our interpretation of the
best available scientific l iterature and methods and suppor ted by the SAB-HES and the NAS (NRC, 2002). The benefits estimates are subject to a number of assumptions and uncertainties. For example, for key assumptions underlying the estimates for premature mortality, which typically account for more than 90% of the total benefits, we we re able to quantify include the following:

1. PM 2.5 benefits were derived through benefit per-ton estimates, which do not reflect local variability in populati on density, meteorology, exposure, baseline health incidence rates, or other local factors that might lead to an over-estimate or underestimate of the actual benefits of controlling PM precursor s. We do not have data on the specific location of the air quality cha nges associated with this rulemaking; as such, it is not feasible to estimate the proportion of bene fits occurring in different locations, such as designat ed nonattainment areas. In addition, the benefit-per-ton estimates are based on emissions from existing sources. To the extent that the geographic distribution of the emissions reductions for this rule are different than the7-32 modeled emissions, the benefits may be undere stimated or overestimated. In general, there is inherently more uncertainty for new sources, which may not be included in the emissions inventory, than existing sources.

2. We assume that all fine particles, re gardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 produced via transported precursors emitted from EGUs may differ significantly from direct PM 2.5 released from diesel engines and other industrial sources, but no clear scien tific grounds exist for s upporting differential effects estimates by particle type.

3. We assume that the health impact functi on for fine particles is linear down to the lowest air quality levels modeled in this an alysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5, including both regions that are in attainment with fine particle standard and those that do not meet the standard down to th e lowest modeled concentrations.

4. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality (which typically accounts for 85% to 95% of total monetized benefits), we include a set of twelve estimates based on results of the expert elicitation study in addition to our core estimates. Even these multiple characterizations omit the uncertainty in air quality estimates, baseline incidence rates, populations exposed and transferability of the effect estimate to di verse locations. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the PM 2.5 estimates. This information should be interpreted within the context of the larger uncertainty surrounding the entire analysis. For more information on the uncertainties associated with PM 2.5 benefits, please consult the PM 2.5 NAAQS RIA (Table 5.5).

This RIA does not include the type of detail ed uncertainty assessment found in the PM NAAQS RIA because we lack the necessary air quality input and monitoring data to run the benefits model. In addition, we have not c onducted any air quality modeling for this rule. Moreover, it was not possible to develop benefit-per-ton metrics and associated estimates of uncertainty using the benefits estimates from th e PM RIA because of the significant differences
between the sources affected in that rule and th ose regulated here. Howe ver, the results of the Monte Carlo analyses of the health and welfare benefits presented in Chapter 5 of the PM RIA can provide some evidence of the uncertainty su rrounding the benefits results presented in this analysis.7-33 7.4 Comparison of Co-Benefits and Costs
Using a 3% discount rate, we estimate the to tal combined monetized co-benefits of the reconsidered SI RICE NESHAP proposal to be $62 million to $150 million in the implementation year (2013). Using a 7% discoun t rate, we estimate the total monetized cobenefits of the final rule to be $55 million to $140 million. The annualized social costs of the reconsidered SI RICE NESHAP proposal are $115 million at a 7% interest rate. 62 Thus, the net benefits are $-53 million to $35 million at a 3% discount rate and $-60 million to $ 25 million at
a 7% discount rate. All estimates are in 2010$ for the year 2013.

Table 7-5 shows a summary of the monetized co -benefits, social costs, and net benefits for the reconsidered SI RICE NESHAP proposal, respectively. Figures 7-8 and 7-9 show the full range of net benefits estimates (i.e., annual co-benefits minus a nnualized 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 1,800 t ons of HAPs each year from SI RICE have
not been included in these estimates.

Table 7-5. Summary of the Annualized Mone tized Benefits, Soci al Costs, and Net Benefits for the Proposed SI RICE NESHAP Reconsiderat ion in 2013 (millions of 2010$) 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 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 mo rtality because the scientific eviden ce is not yet sufficient to allow differentiation of effects estim ates by particle type. Because these esti mates were generated using benefit-per-ton estimates, we do not break down the total monetized benefits into specific components here. See Figure 7-1 for an illustration of the breakdown, or the RIA for the fina l Cross-States Air Pollution Rule (EPA, 2011) for more information.

62 For more information on the an nualized social costs, please re fer to Section 5 of this RIA.7-34 3 The annual compliance costs serve as a pr oxy for the annual social costs of th is rule given the lack of difference between the two. The engineering compliance costs are annualized using a 7 percent discount rate.7-35 Figure 7-8. Net Benefits for Proposed SI RICE NESHAP Reconsideration at 3% discount rate* *Net Benefits are quantified in terms of PM 2.5 at a 3% discount rate for 2013 and are in 2010$. This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. ‐ $100

‐ $80 ‐ $60 ‐ $40 ‐ $20

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

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

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions7-36 Figure 7-9. Net Benefits for Proposed SI RICE NESHAP Reconsideration at 7% discount rate* *Net Benefits are quantified in terms of PM 2.5 benefits at a 7% discount rate at a 3% discount rate for 2013 and are in 2010$. This graph shows 14 benefits estimates comb ined with the cost estimate. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. ‐ $100

‐ $80 ‐ $60 ‐ $40 ‐ $20

$0 $20 $40 $60 $80

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

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions7-37 7.5 References Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “The influence of location, source, and emission type in estimates of the human health be nefits 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 Bayes Approach to Combining Estimates of the Value of Statistical Life for Environmental Policy Analysis .” Environmental and Resource Economics. 34: 385-406.
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U.S. Environmental Protection Agency—Sci ence Advisory Board (U.S. EPA-SAB). 2009b. Consultation on EPA’s Particulate Matter National Ambient Air Quality Standards: Scope and Methods Plan for Health Risk and Exposure Assessment . EPA-COUNCIL-09- 009. May. Available at at <http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86 e/723FE644C5D758DF852575BD00763A32/$File/E PA-CASAC-09-009-unsigned.pdf>.
U.S. Small Business Administration (SBA). 2008. “Table of Small Business Size Standards Matched to North American Industry Classi fication System Codes.” Effective August 22, 2008. <http://www.sba.gov/idc/groups/public/ documents/sba_homepage/serv_sstd_ tablepdf.pdf>.
Viscusi, V.K., and J.E. Aldy. 2003. “The Value of a Statistical Life: A Critical Review of Market Estimates throughout the World.” Journal of Risk and Uncertainty 27(1):5-76.
Wade, S.H. 2003. “Price Responsiveness in th e AEO2003 NEMS Residential and Commercial Buildings Sector Models.” <http://www.eia.doe.gov/oiaf/analysispap er/elasticity/pdf/buildings.pdf>.B-9***E.O. 12866 Review – Draft – Do Not Cite, Quote, or Release During Review ***

**E.O. 12866 NESHAP RICE Compression Ignition Engines RIA 2060- AQ58 Proposal 20120315** 



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

Draft ReportThis page is intentionally blank.April 2012

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

By: Paramita Sinha, Brooks Depro, and Fern Braun RTI International Research Triangle Park, North Carolina

Prepared for: Larry Sorrels

Contract No. EP-D-06-003

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

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

Draft Report

April 2012

Prepared for

Larry Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (AEG) (MD-C439-02) Research Triangle Park, NC 27711

Prepared by

Paramita Sinha Brooks Depro Fern Braun RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709iii CONTENTS

Section Page

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

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

2.1 Organization of this Report .................................................................................. 2-1

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

3.2 Oil and Gas Extraction ......................................................................................... 3-7
3.2.1 Overview .................................................................................................. 3-7
3.2.2 Goods and Services Used ....................................................................... 3-10
3.2.3 Business Statistics .................................................................................. 3-11

3.3 Pipeline Transportation of Natural Gas ............................................................. 3-16
3.3.1 Overview ................................................................................................ 3-16
3.3.2 Goods and Services Used ....................................................................... 3-17

3.4 General Medical and Surg ical Hospitals ............................................................ 3-21
3.4.1 Overview ................................................................................................ 3-21
3.4.2 Goods and Services Used ....................................................................... 3-21
3.4.3 Business Statistics .................................................................................. 3-23

3.5 Irrigation Sets and Welding Equipment ............................................................. 3-25
3.5.1 Overview ................................................................................................ 3-25
3.5.2 Irrigation and Weldi ng Services ............................................................ 3-26
3.5.3 Business Statistics .................................................................................. 3-31

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

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

4.2 Summary of the Proposed Reconsideration Rule ................................................ 4-2iv 4.2.2 What Are the Pollutants Regulated by this Proposed Reconsideration Rule? ........................................................................... 4-15

4.3 Cost Impacts....................................................................................................... 4-16
4.3.1 Introduction ............................................................................................ 4-16
4.3.2 Major Sources ........................................................................................ 4-20
4.3.3 Area Sources .......................................................................................... 4-22

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

5.1 Compliance Costs of the Final Rule .................................................................... 5-1

5.2 Social Cost Estimate .............................................. Error! Bookmark not defined.

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis .......... 5-5
5.3.1 Changes in Market Prices and Quantities ................................................ 5-5
5.3.2 Regulated Markets: The Electri c Power Generation, Transmission, and Distribution Sector ............................................................................ 5-7
5.3.3 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus ............................................................................... 5-8

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

5.5 Unfunded Mandates ........................................................................................... 5-10
5.5.1 Future and Disproportionate Costs ........................................................ 5-11
5.5.2 Effects on the National Economy .......................................................... 5-11

5.6 Environmental Justice ........................................................................................ 5-12
5.7 Employment Impact Analysis ............................................................................ 5-11
5.7.1 Employment Impacts from Pollution Control Requirements5- 13 5.7.2Empl o

Section 6 Small Entity Screeni ng Analysis ............................................................. 6-1

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

6.2 Small Entity Economic Im pact Measures ............................................................ 6-2
6.2.1 Model Establishment Receipts and Annual Compliance Costs ............... 6-2

6.3 Small Government Entities ................................................................................ 6-12v Section 7 Human Health Benefits of Emissions Reductions ................................... 7-1

7.1 Calculation of PM 2.5 -Related Human Health Co-Benefits .................................. 7-1

7.2 Unquantified Benefits ........................................................................................ 7-15
7.2.1 HAP Benefits ............................................................................................ 7-15

7.2.2 Ozone Co-Benefits ................................................................................. 7-26
7.2.3 Carbon Monoxide Co-Benefits .............................................................. 7-26
7.2.4 Visibility Impairment Co-Benefits ........................................................ 7-26

7.3 Characterization of Uncertainty in the Monetized Co-Benefits ........................ 7-27

7.4 Comparison of Co-Benefits and Costs ............................................................... 7-32

7.5 References .......................................................................................................... 7-36

Section 8 References ................................................................................................ 8-1vi LIST OF FIGURES

Number Page

3-1. Industrial Production Index (NAICS 2211) ................................................................ 3-3 3-2. Internal Combustion Generato rs by State: 2006 ......................................................... 3-4 3-3. 2002 Regional Distribution of Establis hments: Electric Power Generation, Transmission, and Distribution Industry (NAICS 2211) ............................................ 3-5 3-4. Industrial Production Index (NAICS 211) .................................................................. 3-1 3-5. Distribution of Establishments within Pi peline Transportation (NAICS 486) .......... 3-17 3-6. Distribution of Revenue within Pipeli ne Transportation (NAICS 486) .................... 3-17 3-7. Share of Establishments by Legal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002 ................................ 3-19 3-8. Share of Establishments by Legal Form of Organization in the General Medical and Surgical Hospitals Industry (NAICS 6221): 2002 .............................................. 3-24 3-9. Industrial Production Index (NAICS 333111) .......................................................... 3-28

5-1. Distribution of Annualized Direct Co mpliance Costs by Industry: 2013 ................... 5-2 5-2. Distribution of Engine Population by Horsepower Group: 2013 ................................ 5-3 5-3. Average Annualized Cost per Engine by Horsepower Group: 2013 ($2007) ............. 5-3 5-4. Market Demand and Supply Model: W ith and Without Regulation ........................... 5-6 5-5. Electricity Restructuring by State ................................................................................ 5-9

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

7-4. Estimated Chronic Census Tract Carci nogenic Risk from HAP exposure from outdoor sources (2005 NATA) .................................................................................. 7-17 7-5. Estimated Chronic Census Tract Non cancer (Respiratory)Risk from HAP exposure from outdoor sources (2005 NATA).............. ....................................... 7-17 7-6. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline..............................................................................7-29 7-7 Cumulative Distribution of A dult Population by Annual Mean PM 2.5 Exposure in the Baseline........................................................................7-29 7-8. Net Benefits for Proposed CI RICE NESHAP Reconsideration at 3% discount rate..................................................................7-33vii 7-9. Net Benefits for Proposed CI RICE NESHAP Reconsideration at 7% discount rate..................................................................7-34viii LIST OF TABLES

Number Page

3-1. Key Statistics: Electric Power Gene ration, Transmission, and Distribution (NAICS 2211) ($2007) ................................................................................................ 3-2 3-2. Direct Requirements for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2007 ............................................................................... 3-5 3-3. Firm Concentration for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2002 ............................................................................... 3-7 3-4. United States Retail Electricity Sales Statistics: 2008 ................................................ 3-8 3-5. FY 2010 Financial Data for 70 U.S. Share holder-Owned Electric Utilities ............. 3-10 3-6. Aggregate Tax Data for Accounting Period 7/07–6/08: NAICS 2211 ..................... 3-10 3-7. Key Enterprise Statistics by Receipt Size for Electric Power Generation, Transmission, and Distribution (NAICS 2211): 2007 ............................................... 3-11 3-8. Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): ($2007) ...................................................................................................................... 3-11 3-9. Key Statistics: Natural Gas Liquid Ex traction (NAICS 211112) ($2007) ................ 3-12 3-10. Direct Requirements for Oil and Gas Extraction (NAICS 211): 2002 ...................... 3-12 3-11. Key Statistics for Crude Petroleum and Natural Gas Extraction (NAICS 211111): 2007 ............................................................................................................ 3-13 3-12. Key Statistics for Crude Natural Gas Liquid Extraction (NAICS 211112): 2007 .... 3-13 3-13. Aggregate Tax Data for Accounting Period 7/07

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

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

4-1. CI RICE Control Techno logies and Costs .................................................................. 4-9 4-2. Summary of Major Source and Area Source Costs for the CI RI CE NESHAP ....... 4-24 4-3. Summary of Major Source and Area S ource NAICS Costs for the CI RICE NESHAP ................................................................................................................... 4-25 4-4. Summary of Major Source and Area S ource NAICS Costs for the CI RICE NESHAP – by Size .................................................................................................... 4-26 4-5. Summary of Major Source and Area S ource NAICS Costs for the CI RICE NESHAP – by Number of Engines ........................................................................... 4-29 4-6. Summary of Major Source and Area Source Baseline Emissions for the CI RICE NESHAP – 2013 ...........................................................................4-36

4-7. Summary of Major Source and Area Sour ce Emission Reductions for the CI RICE NESHAP – by 2013 ...........................................................................4-36

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

6-1. Final NESHAP for Existing Stationary Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Busi ness Size Standards ............. 6-3 6-2. Average Receipts for Affected Industry by Enterprise: 2007 ($2008 Million/establishment) ................................................................................................. 6-5 6-3. Average Receipts for Affected Industr y by Enterprise Receipt Range: 2007 ($2008 /establishment) ................................................................................................ 6-6 6-4. Representative Establishment Costs Used for Small Entity Analysis ($2008) ........... 6-8

7-1. Human Health and Welfare Effects of PM 2.5 .............................................................. 7-1 7-2. Summary of Monetized Co-benefits Estimates for RICE NESHAP for Compression Ignition in 2013 (2008$) ..................................................................... 7-11 7-3. Summary of Reductions in H ealth Incidences from PM 2.5 Co-benefits for RICE NESHAP in 2013 ...................................................................................................... 7-12x 7-4 All PM 2.5 Co-benefits Estimates for the RICE NESHAP at discount rates of 3% and 7% in 2013 (in millions of 2008$) ...................................................................... 7-13 7-5. Summary of the Annualized Benefits, Soci al Costs, and Net Benefits for the Proposed Reconsidered CI RI CE NESHAP in 2013 ................................................. 7-321-1 SECTION 1
EXECUTIVE SUMMARY

The EPA estimates that complying with the proposed reconsiderati on of the stationary compression ignition (CI) reciprocating internal combustion engine (RICE) rule will have an annualized cost of approximately $372 million pe r year (2008 dollars) or $373 million per year (2010 dollars) in the year of full implementati on of the rule (2013). Using these costs, EPA estimates in its economic impact analysis that the NESHAP will have limited impacts on the industries affected and their consumers. Using sa les data obtained for aff ected small entities in an analysis of the impacts of this proposal on small entities, EPA expect s that the NESHAP will not result in a SISNOSE (significant economic impacts for a substantial number of small entities). EPA also does not expect significant adverse energy impacts based on Executive Order 13211, an Executive Order that requires analysis of energy impacts for rules such as this one that are economically significant unde r Executive Order 12866. All of these analysis results are practically identical to the results for the CI RICE NESHAP when it was promulgated in March
2010.

The RICE rule is also considered subj ect to the requirements of the Office of Management and Budget’s (OMB’s) Circular A-4 b ecause EPA expects that either the benefits or the costs are potentially $1 billion or higher. EPA estimates the total monetized co-benefits of the NESHAP to be $770 million to $1.9 billion (2010$) at a 3% discount rate and $690 million to $1.7 billion at a 7% discount rate in the year of full implementa tion of the rule (2013). The net benefits of the proposed CI RICE reconsider ation are therefore $400 m illion to $1.5 billion at a 3% discount rate and $320 million to $1.3 billio n at a 7% discount rate (in 2010$) in 2013.
These estimates are shown in Table 1-1. These co -benefit estimates are lo wer than those for the rule promulgated two years ago. The previ ous co-benefit estimates were $940 million to $2,300 million (2008 dollars) at a 3-percent disc ount rate and $850 million to $2,100 million (2008 dollars) at a 7-percent discount ra te. The previous estimates will be greater in a nominal (not inflation-adjusted) sense if shown in 2010 dollars, and thus the reduction in the benefits for the reconsidered rule compared to th e benefits for the 2010 final rule wi ll therefore be greater. EPA believes that the benefits are likely to exceed the annualized costs by a substantial margin under this rulemaking even when taking into account un certainties in the cost and benefit estimates

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

.1-2 Table 1-1. Summary of the Annualized Mone tized Benefits, Soci al Costs, and Net Benefits for the Proposed Reconsidered CI RICE NESHAP in 2013 (millions of 2010$) 1

3% Discount Rate 7% Discount Rate

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

Non-monetized Benefits Health effects from HAP exposure

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

1 All estimates are for the implementation year (2013) , and are rounded to two significant figures.
2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as directly emitted fine particles. Human health 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 prematur e mortality because the scien tific evidence is not yet sufficient to allow differentiation of effects estimates by particle type. Because these estimates were generated using benefit-per-ton estimates, we do not break down the total monetized benefits into specific components here. See Figure 7-1 for an illustration of the breakdown, or th e RIA for the final Cross-States Air Pollution Rule (EPA, 2011) for more information. 3 The annual compliance costs serve as a pr oxy for the annual social costs of th is rule given the lack of difference between the two. The engineering compliance costs are annualized using a 7 percent discount rate. These costs are $372 million in 2008 dollars.SECTION 2
INTRODUCTION

EPA is proposing reconsideration of nati onal emission standards for hazardous air pollutants (NESHAP) for existing stationary co mpression ignition (CI) r eciprocating internal combustion engines (RICE) that either are loca ted at area sources of hazardous air pollutant (HAP) emissions or that have a site rating of less than or equal to 500 brake horsepower (HP) and are located at major sources of HAP The proposed amendments to the CI RICE NESHAP are provided in detail in S ection 4 of this RIA.

The rule is economically significant accordi ng to Executive Order 12866. As part of the regulatory process of preparing th ese standards, EPA has prepared a regulatory impact analysis (RIA). This analysis includes an analysis of impacts to small enti ties as part of compliance with the Small Business Regulatory Enforcement Fair ness Act (SBREFA) and an analysis of impacts on energy consumption and production to comply with Executive Orde r 13211 (Statement of Energy Effects). An analysis of economic im pacts, along with an analysis of impacts on employment, is also included in th is RIA. Finally, an analysis of the benefits of the rule is
included in this RIA. It should be noted that the data that supports the analyses listed above have been updated where possible and ap propriate from the data used in the RIA for the CI RICE NESHAP promulgated in March 2010.

2.1 Organization of this Report
The remainder of this report supports and details the methodology a nd the results of the
RIA:

 Section 3 presents a profile of the affected industries.

 Section 4 presents a summary of the propos ed amendments to the proposed rule, and provides the compliance costs and emissi on reductions estimated for the rule.

 Section 5 describes the estimated costs of the regulation and describes the EIA methodology and reports market, welfare, energy, and employment impacts.

 Section 6 presents estimated impacts on small entities.

 Section 7 presents the benefits and net benefits (benefits – costs) estimates.SECTION 3
INDUSTRY PROFILE

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

 electric power generation, transm ission, and distribution (NAICS 2211),

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

 pipeline transportation of natural gas (NAICS 211112),

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

 irrigation sets and welding e quipment (NAICS 335312 and 333992).

This section provides an introduction to the industries affected by the proposed reconsidered rule. The purpose is to give the reader a general understanding of the economic aspects of the industry; their rela tive size, relationships with othe r sectors in the economy, trends for the industries, and financial statistics.

3.1 Electric Power Generation, Transmission, and Distribution

3.1.1 Overview
Electric power generation, transmission, and distribution (NAICS 2211) is an industry group within the utilities sector (NAICS 22). It includes establishments that produce electrical energy or facilitate its transm ission to the final consumer.

From 2002 to 2007, revenues from electric pow er grew about 18% to over $440 billion ($2007) (Table 3-1). At the same time, payroll rose about 7.6% and the number of employees decreased by over 6%. The number of establishments rose by a little more th an 2%, resulting in a increase in average establishment revenue of almost 24%. Industrial production within NAICS 2211 has increased 25% since 1997 (Figure 3-1).

Electric utility companies have traditionall y been tightly regula ted monopolies. Since 1978, several laws and orders have been passed to encourage competition w ithin the electricity market. In the late 1990s, many states began the process of restructuring their utility regulatory framework to support a competitive market. Follo wing market manipulation in the early 2000s,however, several states have susp ended their restructuring efforts. The majority (58%) of diesel power generators controlled by combined he at and power (CHP) or independent power producers are located in st ates undergoing active restructuring (Figure 3-2).
Table 3-1. Key Statistics: Electric Power Ge neration, Transmission, and Distribution (NAICS 2211) ($2007)

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

.Figure 3-1. Industrial Pro duction Index (NAICS 2211)

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

ID: G17/IP_MINING_AND_UTILITY_DETAIL/IP.G2211.S <http://www.federalreserve.gov/datadownload/>. (January 27, 2010).

3.1.2 Goods and Services Used
In Table 3-2, we use the latest detailed be nchmark input-output data report by the Bureau of Economic Analysis (BEA) (2002) to identify the goods and serv ices used in electric power generation. As shown, labor and ta x requirements represent a signi ficant share of the value of 80 85 90 95 100 105 110 1151997‐011997‐061997‐111998‐041998‐091999‐021999‐071999‐122000‐052000‐102001‐032001‐082002‐012002‐062002‐112003‐042003‐092004‐022004‐072004‐122005‐052005‐102006‐032006‐082007‐012007‐062007‐112008‐042008‐092009‐022009‐072009‐12IndexValue(Jan2002=100)Figure 3-2. Internal Combustion Generators by State: 2006
Source: U.S. Department of Energy, Energy Information Administration. 2007. “2006 EIA-906/920 Monthly Time

Series.”

power generation. Extraction, transportation, re fining, and equipment requirements potentially associated with reciprocating internal combustion engines (o il and gas extraction, pipeline transportation, petroleum refineries, and turb ine manufacturing) repr esent around 10% of the
value of services.

3.1.3 Business Statistics

The U.S. Economic Census and Statistics of U.S. Businesses (SUSB) programs provide
national information on the dist ribution of economic variables by industry, location, and size of business. Throughout this section and re port, we use the following definitions:

 Establishmen t: An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed. Diesel and Natural Gas Internal Combustion Generators By State

No Restructuring Suspended Restructuring Active Restructuring
100

50

10
1Table 3-2. Direct Requirements for Electri c Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Commodity Description Direct Requirements Coefficients a
V00100 Compensation of employees 20.52% V00200 Taxes on production and imports, less subsidies 13.71% 211000 Oil and gas extraction 6.16% 212100 Coal mining 5.86% 482000 Rail transportation 3.01% 230301 Nonresidential maintenance and repair 2.83% 486000 Pipeline transportation 1.70%

722000 Food services an d drinking places 1.40% 52A000 Monetary authorities and depository credit intermediation 1.39% 541100 Legal services 1.13%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table,

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

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

 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 th e establishment are the same for singleestablishment firms. For each multiestablishment firm, establishments in the same industry within a state are counted as one firm; the firm employment and annual payroll are summed from the associated establishments.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise; the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size designations are determined by the su mmed employment of all associated establishments.

In 2002, Texas had almost 1,000 power establis hments, 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 Es tablishments: Electric Power Generation, Transmission, and Distribution Industry (NAICS 2211)
Source: U.S. Census Bureau; generated by RTI Interna tional; using American FactFinder; “Sector 22: Utilities:

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

As shown in Table 3-3, the four largest firms owned over 1,200 establishments and accounted for about 16% of total industry receip ts/revenue. The 50 largest firms accounted for almost 6,000 establishments and about 78% of total rece ipts/revenue.

Investor-owned energy providers accounted fo r 67.5% of retail electricity sold in the United States in 2006 (Table 3-4). In 2010, less regulated investor-owned electric utility companies were on average more profitable than companies with greater regulation (Table 3-5). In 2006, enterprises within NAICS 2211 had a pre-ta x profit margin of only 0.9% (Table 3-6).

3.2 Oil and Gas Extraction

3.2.1 Overview
Oil and gas extraction (NAICS 211) is an industry group within the mining sector (NAICS 21). It includes establishm ents that operate or develop oil and gas field properties Establishments by State

Less than 100

100 - 199

200 - 349

350 - 500

More than 500Table 3-3. Firm Concentration for Electri c Power Generation, Transmission, and Distribution (NAICS 2211): 2002

Commodity Establishments Receipts/Revenue

Number of Employees Employees per Establishment Amount ($10 6 ) Percentage of Total
All firms 9,394 $325,028 100.0% 535,675 57
4 largest firms 1,260 $52,349 16.1% 68,432 54
8 largest firms 2,566 $95,223 29.3% 151,575 59
20 largest firms 3,942 $173,207 53.3% 271,393 69
50 largest firms 5,887 $253,015 77.8% 408,021 69

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

Subject Series—Estab & Firm Size: Concentration by Largest Firms for the United States: 2002.” <http://factfinder.census.gov>; (November 21, 2008).

through such activities as exploring for oil a nd gas, drilling and e quipping wells, operating onsite equipment, and conducting ot her activities up to the point of shipment from the property.

Oil and gas extraction consists of two i ndustries: crude petroleum and natural gas extraction (NAICS 211111) and na tural gas liquid extraction ( NAICS 211112). Crude petroleum and natural gas extraction is the larger industry; in 2007, it account ed for 93% of establishments and 75% of oil and ga s extraction revenues.

Industrial production in this indus try is particularly sensitiv e to hurricanes in the Gulf Coast. In September of both 2005 and 2008, produc tion dropped 14% from the previous month.

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

From 2002 to 2007, revenue from natural ga s liquid extraction ( NAICS 211112) grew over 19% to about $40 billion (Tab le 3-9). At the same time, payroll increased by only 1% and the number of employees dropped by almost 14%. The number of establishments dropped by over 59%, resulting in an increase of revenue per establishment of about 85%.3-9Table 3-4. United States Retail Electricity Sales Statistics: 2008Full-Service Providers Other ProvidersItem Investor-Owned Public Federal Cooperative Facility Energy Delivery TotalNumber of entities 3 62 1 25 1 NA NA 92Number of retail customers 46,985 2,160,220 36 940,697 1 NA NA 3,147,939Retail sales (103megawatthours) 2,257 70,303 9,625 21,868 117 NA NA 104,170Percentage of retail sales 2 67 9 21 0 — — 100Revenue from retail sales ($106) 113 5,934 473 1,994 6 NA NA 8,520Percentage of revenue 1.33 69.65 5.55 23.41 0.07 — — 100Average retail price (cents/kWh) 5.01 8.44 4.91 9.12 5.25 NA NA 8.18Source: U.S. Department of Energy, Energy Information Administration. 2009. “State Electricity Profiles 2008.” DOE/EIA-0348(01)/2. p. 260. <http://www.eia.doe.gov/cneaf/electricity/st_profiles/sep2008.pdf>.3-10 Table 3-5. FY 2010 Financial Data for 70 U. S. Shareholder-Owned Electric Utilities

Profit Margin Net Income Operating Revenues
Investor-Owned Utilities 4.81% $27,728 $371,545

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

Diversified c -16.78% -$2,429 $37,671

a 80%+ of total assets are regulated.

b 50% to 80% of total assets are regulated.

c Less than 50% of total assets are regulated. Source: Edison Electric Institute. “Income Statement: Q4 2010 Financial Update. Quarterly Report of the U.S.

Shareholder-Owned Electric Utility Industry.” <http://www.eei.org>.
Table 3-6. Aggregate Tax Data for Accounting Period 2009: NAICS 2211

Number of enterprises a 1,187
Total receipts (10 3 ) $323,522,443
Net sales(10 3 ) $328,017,143
Profit margin before tax 3.1%
Profit margin after tax 2.0%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2000–

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

3.2.2 Goods and Services Used
The oil and gas extraction industry has similar labor and tax requirements as the electric power generation sector. Extrac tion, support, power, and equipm ent requirements potentially associated with reciprocati ng internal combustion engines (oil and gas extraction, support activities, electric power genera tion, machinery and equipment rent al and leasing, and pipeline transportation) represent around 8% of the value of services (Table 3-10).3-11 3.2.3 Business Statistics
The U.S. Economic Census and SUSB progr ams provide national information on the
distribution of economic variable s by industry, location, and size of business. Throughout this section and report, we use the following definitions:

 Establishment : An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed.3-12Table 3-7. Key Enterprise Statistics by Employee Size for Electric Power Generation, Transmission, and Distribution (NAICS2211): 2007Variable All Enterprises<20Employees20–99Employee s100–499Employees500+EmployeesFirms 1,687 630 670 251 136Establishments 9,611 687 1,110 999 6,815Employment 503,134 3,622 31,455 42,527 425,530Receipts ($103) $440,342,284 $8,364,773 $21,825,969 $41,370,375 $368,781,167Receipts/firm ($103) $261,021 $13,277 $32,576 $164,822 $2,711,626Receipts/establishment($103)$45,817 $12,176 $19,663 $41,412 $54,113Receipts/employment($) $875 $2,309 $694 $973 $867Source: U.S. Census Bureau. 2010. “Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size: 2007.”<http://www.census.gov/csd/susb/susb07.htm>.3-13 Figure 3-4. Industrial Pro duction Index (NAICS 211)

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

ID: G17/IP_MINING_AND_UTILITY_D ETAIL/IP.G211.S <http://www.feder alreserve.gov/datadownload/>. (January 27, 2010).
Table 3-8. Key Statistics: Crude Petroleum and Natural Gas Extraction (NAICS 211111): ($2007)

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

Source: U.S. Census Bureau; Factfinder Series: “200 2 and 2007.” <http://factfinder.census.gov>; (February 23,

2012).

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

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

Establishments 511 321

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

Commodity Commodity Description Direct Requirements Coefficients a
V00200 Taxes on production and imports, less subsidies 8.93% V00100 Compensation of employees 6.67% 230301 Nonresidential maintenance and repair 6.36% 211000 Oil and gas extraction 1.91% 213112 Support activities for oil and gas operations 1.51% 221100 Electric power generation, transmission, and distribution 1.47% 541300 Architectural, engineering, and related services 1.24% 532400 Commercial and industrial machinery and equipment rental and leasing 1.20% 33291A Valve and fittings other than plumbing 1.10% 541511 Custom computer programming services 0.99%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table,

Use Table and Direct Requirements Table. Tables 4 and 5.
establishment firms. For each multiestablishment firm, establishments in the same industry within a state are counted as one firm; the firm employment and annual payroll are summed from the associated establishments.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise; the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size3-15 designations are determined by the su mmed employment of all associated establishments.

As of 2007, there were 6,563 firms within the NAICS 211111 code, of which 6427 (98 percent) were considered small businesses (Table 3-11). Within NAICS 211111, large firms compose about 2 percent of the firms, but accoun t for 59 percent of employment and generate about 80 percent of estimated receipts listed under the NAICS. Within NAICS 211112, there are 139 firms, of which 95 (71 percent) were co nsidered small businesses (Table 3-12). As shown in this table, large firms compose 29 per cent of the firms, but account for 78 percent of employment and generate about 95 per cent of estimated receipts.

Enterprises within NAICS 211111 generated $194 billion in total receipts in 2007. Enterprises within NAICS 211112 generated nearly $40 billion in total receipts in 2007. Including those enterprises without net income, NAICS 211 averaged an after-tax profit margin of 8.5% in 2008 (Table 3-13).
Table 3-11. Key Statistics for Crude Petroleum and Natural Gas Extraction (NAICS 211111): 2007

NAICS NAICS Description SBA Size Standard Small Firms Large Firms Total Firms Number of Firms by Firm Size Crude Petroleum and Natural Gas Extraction 500 6,329 95 6,424 Total Employment by Firm Size 55,622 77,664 133,286 Estimated Receipts by Firm Size ($1000) 44,965,936 149,141,316 194,107,252
Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million re quired 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 a nd receipts could not be split between small and large businesses because of non-discl osure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the United States, Al l Industries: 2007.” <http://www.census.gov/econ/susb/>3-16 Table 3-12. Key Statistics for Crude Natura l Gas Liquid Extraction (NAICS 211112): 2007

NAICS Description SBA Size Standard Small Firms Large Firms Total Firms Number of Firms by Firm Size Natural Gas Liquid Extraction 500 98 41 139

Total Employment by Firm Size 1,875 6,648 8,523

Estimated Receipts by Firm Size ($1000) 2,164,328 37,813,413 39,977,741 Note: *The counts of small and large firms in NAICS 486210 is based upon firms with less than $7.5 million in receipts, rather than the $7 million re quired 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 a nd receipts could not be split between small and large businesses because of non-discl osure requirements faced by the U.S. Census Bureau. Source: U.S. Census Bureau. 2010. “Number of Firms, Number of Establishments, Employment, Annual Payroll, and Estimated Receipts by Enterprise Receipt Size for the United States, Al l Industries: 2007.” <http://www.census.gov/econ/susb/>

Table 3-13. Aggregate Tax Data for Accounting Period 7/07

– 6/08: NAICS 211

Number of enterprises a 19,441
Total receipts (10 3 ) $193,230,241
Net sales(10 3 ) $166,989,539
Profit margin before tax 12.9%
Profit margin after tax 8.5%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2004-

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

3.3 Pipeline Transportation of Natural Gas

3.3.1 Overview
Pipeline transportation of natu ral gas (NAICS 48621) is an industry group within the transportation and warehousing se ctor (NAICS 48-49), but more specifically in the pipeline3-17 transportation subsector (486). It includes the transmission of natural gas as well as the distribution of the gas through a local ne twork to participating businesses.

From 2002 to 2007, natural gas transportation revenues fell by 10% to just under $21 billion ($2007) (Table 3-15). At the same time , payroll decreased by 18%, while the number of paid employees decreased by nearly 32%. The numb er of establishments decreased by 13% from 1,701 establishments in 2002 to 1,479 in 2007.

3.3.2 Goods and Services Used
The BEA reports pipeline transportation of natural gas only for total pipeline transportation (3-digit NAICS 486). In addition to pipeline trans portation of natural gas (NAICS 4862), this industry includes pi peline transportation of crude oil (NAICS 4861) and other pipeline transportation (NAICS 4869). However, the BEA data are likely representative of the affected sector since pipeline transportati on of natural gas accounts for 68% of NAICS 486
establishments and 72% of re venues (Figures 3-5 and 3-6).

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

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

Establishments 1,701 1,479

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

Transportation and Warehousing: Industry Series: Prelim inary Summary Statistics for the United States: 2002 and 2007.” http://factfinder.census.gov (January 27, 2010).

In Table 3-15, we use the latest detailed benchmark input-output da ta report by the BEA (2002) to identify the goods and services used by pipeline transportation (NAICS 486). As shown, labor, refineries, and maintenance requirem ents represent significant share of the cost associated with pipeline transportation. Power a nd equipment requirements potentially associated with reciprocating internal co mbustion engines (electric power generation and commercial and industrial machinery and equipment repair and maintenance) repres ent less than 2% of the value
of services.3-18 Figure 3-5. Distribution of Establishments within Pipeline Transportation (NAICS 486)
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48:

Transportation and Warehousing: Industry Series : Summary Statistics for the United States: 2002” <http://factfinder.census.gov >; (December 12, 2008).

Figure 3-6. Distribution of Revenue with in Pipeline Transportation (NAICS 486)
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48:

Transportation and Warehousing: Industry Series : Summary Statistics for the United States: 2002” <http://factfinder.census.gov >; (December 12, 2008). 68%

21%
11%

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

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

72%

16% 12%

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

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

Commodity Commodity Description Direct Requirements Coefficients a
V00100 Compensation of employees 14.78%

324110 Petroleum refineries 13.55% 230301 Nonresidential maintenance and repair 6.07% 211000 Oil and gas extraction 4.94% 333415 Air conditioning, refrigeration, and warm air heating equipment manufacturing 4.40%

561300 Employment services 4.26% 5416A0 Environmental and other technical consulting services 3.04% 541300 Architectural, engineering, and related services 3.04%

420000 Wholesale trade 2.79% 332310 Plate work and fabricated structural product manufacturing 2.72% 5419A0 All other miscellaneous professional, scientific, and technical services 2.48%

524100 Insurance carriers 2.38%

531000 Real estate 2.33% 52A000 Monetary authorities and depository credit intermediation 1.76% V00200 Taxes on production and imports, less subsidies 1.41% 541100 Legal services 1.19% 221100 Electric power generation, transmission, and distribution 1.13%

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table,

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

According to 2007 U.S. Census data, about 86% of transportation of natural gas establishments were owned by corporations and about 8% were owned by individual proprietorships. About 6% were owne d by partnerships (Figure 3-7).

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

The 2007 SUSB shows that abou t half of all firms have fewer than 20 employees, but only 1% of all employees in this industry. Firm s with more than 500 employees generate 89% of all receipts in this industry (Table 3-17).3-20 Figure 3-7. Share of Establishments by Legal Form of Organization in the Pipeline Transportation of Natural Gas Industry (NAICS 48621): 2002
Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 48-49:

Transportation and Warehousing: Subject Series—Estab & Firm Size: Legal Form of Organization for the United States: 2002” <http://f actfinder.census.gov>; (December 12, 2008).

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

Number of enterprises a 321

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

Net sales (10 3 ) $10,210,083

Profit margin before tax 13.2% Profit margin after tax 9.6%

a Includes corporations with and without net income. Source: Internal Revenue Service, U.S. Department of Treasury. 2010. “Corporation Source Book: Data Files 2004-

2007.” <http://www.irs.gov/ta xstats/article/0,id=167415, 00.html>; (May 2, 2010). 86%

8% 6%

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

Corporations Individual Proprietorships Partnerships3-21 Table 3-17. Key Enterprise Statistics by Em ployee Size for Pipeline Transportation of Natural Gas (NAICS 48621): 2007

Variable All Enterprises <20 Employees 20–99 Employees 100–499 Employees 500+ Employees

Firms 126 63 12 9 42 Establishments 1.479 66 26 70 1,317 Employment 24,683 241 382 1,479 22,581 Receipts ($10 3 ) $20,796,681 N/A $518,341 $1,448,020 $18,498,143 Receipts/firm ($10 3 ) $165,053 N/A $43,195 $160,891 $440,432 Receipts/establishment ($10 3 ) $14,061 N/A $19,936 $20,686 $14,046

Receipts/employment ($) $843 N/A $1,357 $979 $819

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

Tabulated by Employee Size: 2007. http://www2.census.gov/csd/susb/2007/usalli_r07.xls.

3.4 General Medical and Surgical Hospitals

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

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

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

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

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

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

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

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

Commodity Commodity Description Direct Requirements Coefficients a
V00100 Compensation of employees 51.90%

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

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

524100 Insurance carriers 1.66%

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

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

are expressed in percentage terms (coefficient ×100). Source: U.S. Bureau of Economic Analysis. 2002. 2002 Benchmark Input-Output Accounts: Detailed Make Table,

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

3.4.3 Business Statistics
In 2010, the United States had 5,754 hospitals (T able 3-20). As shown in Table 3-1, nongovernmental not-for-profit hospitals accounted for 2,904 (or 50%) of these hospitals, and State and local government hospitals account ed for 1,068 (or 19%) of these hospitals.3-24 General medical and surgical hospitals (NAICS 6221) generated $652 billion in total receipts in 2007. Includi ng those enterprises without net income , the industry averaged an aftertax profit margin of 3.1% (Table 3-22).

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

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

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

Commodity Establishments Amount ($10 6 ) Number of Employees Employees per Establishment
All firms 5,404 $651,639 5,041,848 933

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

19.5%

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

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

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

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

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

– 6/06: NAICS 622-4

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

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

3.5 Irrigation Sets and Welding Equipment

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

From 2002 to 2007, farm machinery and equipm ent manufacturing revenues increased by $8 billion from $15 billion to $23 billion (Table 3-23). At the same time, payroll increased by 21% and the number of paid employees increased by nearly 9%. The number of establishments dropped by 2% from 1,214 establishments in 2002 to 1,191 in 2007. Industrial production in the industry has been increasi ng since 1997 (Figure 3-9).3-26 The U.S. Economic Census classifies welding equipment under the welding and soldering equipment manufacturing industry group (NAICS 333992). This U.S. industry comprises establishments primarily engaged in manufacturing welding and soldering equipment and accessories (except transformers), such as welding electrodes, welding wire, and soldering equipment (except handheld).

From 2002 to 2007 welding and soldering equi pment manufacturing revenue increased by about 53% to nearly $6 billion (Table 3-24). At the same time, payroll increased by 12% and the number of paid employees increased by nearly 9%. The number of establishments increased by 31% from 250 establishments in 2002 to 303 in 2007.
3.5.2 Irrigation and Welding Services
The demand for equipment is derived from the demand for the services the equipment provides. We describe uses and indust rial consumers of this equipment.
3.5.2.1 Irrigation
Demand for irrigation equipment is driv en by farm operation decisions, optimal replacement considerations, and climate and weather conditions. The National Agriculture Statistics Service (NASS) 2008 Farm and Ranc h Irrigation Survey (USDA-NASS, 2010) showsPut page number here

3-27Table 3-23. Key Enterprise Statistics by Employee Size for General Medical and Surgical Hospitals (NAICS 6221): 2007($2007)VariableAllEnterprises <20 Employees20-99Employees100-499Employees 500+ EmployeesFirms 3,225 170 277 1,227 1,551Establishments 5,404 173 282 1,286 3,663Employment 5,041,848 606 18,718 294,247 4,728,277Receipts ($103) $651,639,328 346.216 1,553,004 $27,889,532 $621,850,576Receipts/firm ($103) $202,059 2,037 5,607 $22,730 $400,935Receipts/establishment($103)$120,585 2,001 5,508 $21,687 $169,766Receipts/employment($)$129 $571 $83 $95 $132Source: U.S. Small Business Administration (SBA). 2010. “Firm Size Data from the Statistics of U.S. Businesses: U.S. All Industries Tabulated by Receipt Size:2007.” <http://www.census.gov/csd/susb/susb07.htm>.3-28 Table 3-24. Key Statistics: Farm Machinery and Equipment Manufacturing (NAICS 333111) ($2007)

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

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

Figure 3-9. Industrial Pro duction Index (NAICS 333111) 40 50 60 70 80 90 100 110 120 130Index Values (Jan-97=100) Industrial Production Index (NAICS 333111)3-29 Table 3-25. Key Statistics: Welding and Soldering Equipment Manufacturing (NAICS 333992) ($2007)

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

Establishments 231 303

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

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

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

Per-acre operating costs for these irrigation sy stems vary by fuel type, and natural gas was the most expensive in 2008 ($93 per acre fo r well systems and $44 per acre for surface water systems) (Table 3-26). Systems using diesel fuel were operated at approximately half of these per-acre costs ($54 per acre for well systems and $42 per acre for surface water systems). Gasoline- and gasohol-powered systems offered the least expensive operating costs for well systems ($39 per acre) and electr icity-power systems offered the least expensive operating costs for surface water systems ($45 per acre). As show n in Table 3-27, the number of on-farm pumps increased to 546,308 from 489,434 (12%) betwee n 2003 and 2008. The use of electric- and diesel-powered pumps increased during this period (21% and 3%, respectively), while other fuel sources such as liquid petroleum (LP) gas, pr opane, and butane declined significantly (31%).3-30 Table 3-26. Expenses per Acre by Type of Energy: 2008

Fuel Type Irrigated by Water from Wells Irrigated by Surface Water Electricity $57.80 $35.07 Natural gas $93.03 $43.85 LP gas, propane, butane $38.72 $45.40
Diesel fuel $54.20 $41.94 Gasoline and gasohol $84.98 $39.24
Total $60.90 $36.13

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

Irrigation Survey.” Washington, DC: USDA-NASS. Table 20. Found on the Internet at http://www.agcensus.usda.g ov/Publications/2007/Onlin e_Highlights/Farm_and_Ranch _Irrigation_Survey/fris08_ 1_20.pdf

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

Fuel Type 2003 2008 Percentage Change Electricity 312,145 377,492 21% Natural gas 41,768 36,176 –13% LP gas, propane, butane 17,786 12,203 –31%
Diesel fuel 112,133 115,249 3% Gasoline and gasohol 5,602 5,188 –7%
Total 489,434 546,308 12%

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

Irrigation Survey.” Washington, DC: USDA-NASS. Table 20. Found on the Internet at http://www.agcensus.usda.g ov/Publications/2007/Onlin e_Highlights/Farm_and_Ranch _Irrigation_Survey/fris08_ 1_20.pdf

Although no information is available on the use a nd construction of on-fa rm pumps specifically, their use is tied to the amount of agricultural land in production. USDA repor ts that planted acres of the eight major crops hit a 5-year high of 252 million acres in 2008 but will fall and level off to around 244 million acres over the next 2 to 4 years (USDA, 2008).
3.5.2.2 Welding
Welding is used in a wide variety of app lications. One of the biggest manufacturers of welding products identifies the following key end-user segments:

 general metal fabrication;3-31  infrastructure including oil and gas pipelines and platform s, buildings, bridges, and power generation;

 transportation and defense industries (automo tive, trucks, rail, ships, and aerospace);

 equipment manufacturers in c onstruction, farming, and mining;

 retail resellers; and

 rental market (Lincoln Electric Holdings, 2006).

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

3.5.3 Business Statistics
Enterprises within agriculture, constr uction, and mining machinery manufacturing (NAICS 3331) generated $88 billion of total receipts in 2007, while those in other general purpose machinery manufacturing (NAICS 3339) ge nerated $85.7 billion. Th e average after-tax profit margin in these two industries wa s 6.9% and 4.7%, respectively (Table 3-28).
Table 3-28. Aggregate Tax Data for Acco unting Period 7/05–6/06: NAICS 3331 and 3339

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

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

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

As noted earlier, welding equipment is used in heavy fabrication such as earthmoving and construction equipment. We focus on the size dist ribution for a representa tive sector in this section (NAICS 237, Heavy and Civil Engineering Construction); other subs ections in Section 3 cover other sectors that poten tially use equipment powered by diesel engines (e.g., power generation and offshore gas distribution). As show n in Table 3-29, SUSB data suggest that more
than 80% of firms are below the Small Busi ness Administration (S BA) small business size3-32 standard for this industry. Howe ver, it is not clear what fracti on of these firms use stationary diesel engines.3-33Table 3-29. Key Enterprise Statistics byReceipt Size for Heavy Construction: 2007aVariable All Enterprises<20Employees20–99Employees100–499Employees 500+Firms 49,228 40,654 6,793 1,422 359Establishments 51,421 40,670 6,947 1,847 1,987Employment 1,016,407 183,487 273,867 238,342 320,711Receipts ($103) $263,941,774 $46,766,241 $68,078,765 $69,190,739 $79,906,029Receipts/firm ($103) $5,362 $1,150 $10,022 $48,657 $222,579Receipts/establishment($103)$5,133 $1,150 $9,800 $37,461 $40,214Receipts/employment($)$260 $255 $249 $290 $249a2007 SUSB. The most comparable 2007 NAICS code for this industry is 237.Source: U.S. Census Bureau. 2012b. Firm Size Data from the Statistics of U.S. Businesses, U.S. All Industries Tabulated by Receipt Size: 2007.http://www2.census.gov/csd/susb/2007/usalli_r07.xls.4-1 SECTION 4 REGULATORY ALTERNATIVES, CO STS, AND EMISSION IMPACTS

4.1 Background

This section of the RIA includes a discussion of the regulatory alternatives considered for the proposed reconsidered rule, th e costs associated w ith these regulatory alternatives, and the impacts on affected emissions (both HAP and non- HAP). All impacts presented are for the year of full implementation, 2013. Costs in the chap ter are in 2008$. Costs in 2010$ shown in other parts of the RIA are escalated values of th ese 2008$. Although the estimates presented are annualized, they should be understood as a “snapshot” in analyzing costs.

After promulgation of the 2010 RICE NESHAP amendments, the EPA received several petitions for reconsideration, le gal challenges, and other comm unications raising issues of practical implementability, and certain factual information that had not been brought to the EPA’s attention during the rulemaking. The EPA ha s considered this information and believes that amendments to the rule to address certain of these issues are appropriate. Therefore

, the EPA is proposing amendments to NESHAP for st ationary RICE signed in March 2010 for CI engines and August 2010 for SI engines under sec tion 112 of the Clean Air Act. This proposal was developed to address certain issues that ha ve been raised by different stakeholders through lawsuits, several petitions for reconsideration of the 2010 RICE NESHAP amendments and other
communications. The proposed amendments include alternat ive testing options for certain large spark ignition (generally natural gas-fueled) stationary reciprocati ng internal combustion engines, management practices for a subset of existing spark ignition stationary reciprocating internal combustion engines in sparsely populat ed areas, and alternat ive and less burdensome monitoring and compliance options for the same e ngines in populated areas. The EPA is also proposing to include a limited temporary allo wance for existing stationary emergency area source engines to be used for peak shaving a nd non-emergency demand response as part of the pre-existing allowance for such engines to be used for non-emergency use for 50 hours annually. In addition, the EPA is proposing, in both the NESHAP and in the new source performance standards for stationary internal combustion en gines 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-existi ng regulations.

EPA has taken several actions over the past several years to reduce exhaust pollutants from stationary diesel engines, but believe s that further reducing exhaust pollutants from stationary diesel engines, part icularly existing stationary dies el engines that have not been4-2 subject to federal standards, is justified. Therefore, EPA is issuing this rulemaking that reconsiders the 2010 final rule requiring emissions reductions from existin g stationary diesel engines. The full preamble for the final CI RICE NE SHAP and the rule itself can be reviewed at http://www.epa.gov/ttn/atw/rice/fr03mr10.pdf

.

4.2 Summary of the Proposed Reconsideration Rule

4.2.1 Proposed Amendment - Emergency Demand Response/Peak Shaving

4.2.1.1 Background

This action proposes to amend provisions in the RICE NESHAP th at currently allow owners and operators to operate stationary emer gency engines for up to 15 hours per year as part of a demand response program if the RTO or e quivalent balancing auth ority and transmission operator have determined there are emergency conditi ons that could lead to a potential electrical blackout, such as unusually low frequency, equi pment overload, capacity or energy deficiency, or unacceptable voltage level. The final rule did not allow emergency engines to be used for purposes of peak shaving or other non-emergenc y purposes as part of a financial arrangement. These provisions were included in the RICE NESHAP when require ments for existing stationary CI engines were finalized on March 3, 2010 ( 75 FR 9648). Following the completion of that portion of the rule, the EPA received three main petitions for reconsideration. One petition was from CPower, Inc., EnergyConnect, Inc., En erNOC, Inc., and Innoventive Power, LLC. (EnerNOC et al.)(EPA-HQ-OAR -2008-0708-0404). Another petiti on was received from the Delaware Department of Natural Resources and Environmental Control (DE DNREC) (EPAHQ-OAR-2008-0708-0400). The third pe tition was from the Nationa l Rural Electric Cooperative Association (NRECA) (OAR-2008-0708-0580). In a ddition to these main petitions the EPA
received a substantial number of letters from others in the electri c generation industry.

The petition from EnerNOC, et al., asked that EPA increase the period of time permitted for emergency demand response operation in the rule to 60 hours per year, or the minimum number of hours required by the emergency de mand response program. By contrast, the DE DNREC petition asked EPA to reconsider the em ergency demand response provision because of
the adverse effects that it believes would resu lt from increased emissions from these engines. The petition from NRECA requested that the EPA eliminate the restriction on the use of4-3 stationary emergency engines for demand res ponse purposes. The EPA granted the petitions from EnerNOC, et al., DE DNREC and NRECA, and issued a notice on December 7, 2010 (75 FR 75937), requesting comments on whether to amend the 15 hours per year limitation on the operation of stationary emergenc y RICE participating in emergency demand response programs.

The EPA received more than 120 comments from a number of different entities including various state agencies, utilities, electric c ooperatives and industry organizations. Many commenters expressed that 15 hours per year is not sufficient to meet current emergency demand response requirements for participation. For example, several emergency demand response programs have ISO tariff requirements greater than 15 hours per year, including the Electric Reliability Council of Texas emergency de mand response program, which has a tariff requirement of 24 hours per year; the Pennsylva nia Jersey Maryland (“PJM”) Interconnection, known as the Emergency Load Response Program , which has a tariff requirement of 60 hours per year; and the ISO New England (“ISO-NE”), wh ich forecasts that backup resources would be expected for 55 hours over a 12-month period. Tari ff requirements are developed to specify the mandatory time load resources (engines) must be willing and able to operate if the units are enrolled in the program. Conversely, some comm enters urged the EPA to allow stationary emergency engines to only operate during true em ergencies or when voltage or frequency varies beyond specified parameters.

Based on the EPA’s review of the petitions and comments that the EPA has received, the EPA has found it appropriate to propose to amend the current rule to increase the allowance for stationary emergency engine pa rticipation in emergency demand response programs to up to 100 hours per year, which would be included as part of the pre-existing al lowance of 100 hours for owners of emergency engines to test and main tain their emergency engines. The EPA believes that the emergency demand response programs th at exist across the country are important programs that protect the reliability and stability of the national electri c service grid. Allowing stationary emergency engines to operate as pa rt of emergency demand response programs can help prevent grid failure or blac kouts, by allowing these engines to be used in circumstances of grid instability prior to the occurrence of blackouts. Preven ting stationary emergency engines from being able to qualify and participate in emergency demand response programs without having to apply aftertreatment could force owners and operators to leav e their engines out of these programs, which will impair the ability of ISOs and RTOs to use these relatively small, quick-starting and reliable sources of energy to pr otect the reliability of their systems. The EPA does not wish to potentially jeopardiz e electrical reliability or crea te a disincentive for stationary emergency engines to participate in these pr ograms. The circumstances during which the EPA4-4 would allow stationary emergency engines to operate for emergency demand response purposes include periods during which the regional tran smission authority or equivalent balancing authority and transmission opera tor has declared an Energy Em ergency Alert Level 2 (EEA Level 2) as defined in the Nort h American Electric Reliability Corporation Reliability Standard EOP-002-3, Capacity and Energy Emergency, plus dur ing periods where there is a deviation of voltage or frequency of 5 percent or more belo w standard voltage or frequency. During EEA
Level 2 alerts there is insuffici ent energy supply and a true pote ntial for electrical blackouts. System operators must call on all available reso urces during EEA Level 2 alerts in order to stabilize the grid to prevent failure. Therefore, this situation is a good indicator of severe instability on the system. Consis tent normal voltage provided by the utility is ofte n called power quality and is an important factor in local elect ric system reliability. Re liability of the system requires electricity being provi ded at a normal expected vo ltage. The American National
Standards Institute standard C84.1-1989 defines the maximum allowable voltage sag at below 5 percent. On the local distribution level local voltage levels are ther efore important and a 5 percent or more change in the normal voltage or frequency is substantial and an indication that
additional resources are needed to ensure local distribution system reliability. This situation
would be indicative of severe instability on the system.

Emergency demand response programs rely on agreements under which owners of engine agree to make their engines avai lable to be called upon for a speci fic number of hours per year, as required by the relevant ISO or RTO tariff, under specified circumstances considered to indicate emergencies. In order to be enro lled in an emergency demand response program, participants must qualify their e ngines and must be able to use their emergency engines for the number of hours the program requires. Engine s are not generally called upon for the maximum hours required by the tariffs. However, even tho ugh the engine may not be called at all or may run for fewer hours than the program requires it to be available in a particular year, the engine
must still be available for t hose theoretical number of hours in order to join the program. Demand response contracts require more hours than th e 15 hours per year that is currently in the regulations, and the commenters state that the 15 hours per year is not a sufficient amount of time to ensure the reliability of the program; some programs require up to 60 hours per year, as discussed earlier. For these reasons, the EPA beli eves it is appropriate to allow additional hours for emergency demand response operation in orde r for such programs to be accessible to stationary emergency engines. Consequently, the EPA is proposi ng amendments to the rule to increase the limitation on emergency demand response operation to 100 hours per year for stationary emergency engines. It is expected that owners and ope rators of stationary emergency engines that seek to qualify th eir units as demand resources woul d with the propos ed increase to4-5 100 hours per year be able to meet the operational and qualification requirements of the different ISOs and RTOs in the country.

As stated, stationary emergency engines th at participate in demand response programs may not be called upon at all, but must nonethele ss be available to operate for the required amount stipulated by the specific program. Th e purpose of the limited allowance for demand response is to respond to emergencies, and the EPA is persuaded by the information that has been submitted that 15 hours per year is an insufficient amount of time to allow for emergency demand response needs, given past experience. The EPA believes 100 hours per year is sufficient to cover any potential demand respons e operation as well as th e required maintenance and testing that is also included within the 100 hours of operation.

The EPA has previously determined that sta tionary emergency engines typically operate well below 50 hours per year and more common ly about 1 to 2 hours per month. A survey conducted by the California Air Resources Boar d (CA ARB) indicated the average yearly operation for emergency diesel engines was 31 hour s over a period of 3 years. The majority of those hours were for the purpose of maintena nce and testing; less than 5 hours was for interruptible service contracts, and the remaining am ount for emergency/standby operation (EPA-HQ-OAR-2005-0029-0011). Data from demand response programs in ISO-NE and PJM
territories show that b ackup generation was dispatched for le ss than 30 hours during the summers of 2008, 2009 and 2010.

However, again, emergency units must be ava ilable to operate more than that in most cases to qualify for demand response programs. Fo r instance, PJM requires a minimum ISO tariff of 60 hours per year of engine availability for program participation. Consequently, in order to ensure that a sufficient amount of operating ti me is available for ma intenance and readiness testing, and for demand response operation, th e EPA is proposing 100 hours of operation. A number of commenters requested that an allowance of 100 hours per year be allowed in order to provide adequate hours consistent with mini mum required hours that customers must be available to operate and to a ddress local distribution system emergencies. For instance, in Hawaii, the emergency demand response program operated by the Hawaiian Electric Company requires that emergency engines be able to ope rate for 100 hours per year in the event of an emergency in order to participate in the program. In order to provide a sufficient amount of time to cover annual maintenance and testing, whic h is typically more than 20 hours per year according to the survey conducted by CA ARB (see EPA-HQ-OAR-2005-0029-0011), plus to cover hours necessary for qualifying for emer gency demand response programs or local distribution system emergencies, EPA believes an allowance of 100 hours per year would be4-6 appropriate for these activities. Taking into acco unt that there may be situations where annual maintenance and testing could exceed the typical 1 to 2 hours per month and accounting for other emergency demand response programs that require more than 60 hours per year for program participation (e.g., the Hawaiian Electric Compa ny), the EPA believes that 100 hours per year is appropriate for emergency demand respons e plus maintenance and testing.

The proposed amendment to the rule would mean that stationary emergency engines could operate for a total of 100 hours per year for emergency demand response operation as part of the 100 hours already permitted for maintenance and readiness testing while maintaining their status as emergency units, rather than non- emergency units, and continue to meet the requirements that apply to emergency engines.

On the issue of peak shaving and non-em ergency demand response, the EPA is proposing to include a temporary limited allowance for pe ak shaving and other t ypes of non-emergency use as part of a financial arrangement for existing st ationary emergency engines at area sources of HAP, if the peak shaving is done as part of a peak shaving (or load management) program with the local distribution system operator. The power generated under this allowance can only be used at the facility or towards the local system.

The EPA has determined that it is appropriate to include the option for existing stationary emergency engines at area sources to operate for a small number (50) of hours per year for any non-emergency reason to generate income locally and not be penalized or considered a nonemergency engine and subsequently required to inst all aftertreatment that could be prohibitively costly for these sources in the near term. The EPA is proposing that the 50-hour allowance for peak shaving for emergency engines at area sour ces be allowed for a limited period of time, but then removed after April 16, 2017. The peak shavi ng would also be limited to operation as part of a peak shaving (load management program) with the local distribut ion system operator. Owners would still have the pre-existing 50 hours per year allowance for non-emergency operation after April 16, 2017, but those 50 hours coul d no longer be used for peak shaving. The temporary allowance for peak shaving would give sources time to address reliability issues and develop solutions to reliability issues while facilities are coming into compliance with the
National Emission Standards for Hazardous Air Pollutants From Coal and Oil-Fired Electric Utility Steam Generating Units, which were pr omulgated on February 16, 2012 (77 FR 9304). ).
This limited allowance would allow the owners and operators of these engines more flexibility to run reliability critical units in order to minimize potential grid-re lated interruptions as coal- and oil-fired baseload power plants may be temporar ily shut down to install emission controls to comply with the NESHAP From Coal and Oil- Fired Electric Utility Steam Generating Units.4-7 Including this allowance is important for small electric cooperatives and other entities located at area sources that use these engines to maintain voltage and electric reliability. Many rural electric cooperatives enter agreements with owners of small emergency engines and rely on the engines to reduce demand on the centr al power supply during periods of high

, which reduces the cost of power duri ng periods of high demand for th e members of the cooperative. Commenters promoting the continued use of peak shaving programs said that maintaining the cost of power as low as possible is important across the country, but is partic ularly of significant importance to rural electric cooperatives that, according to the commenter, service customers in the most economically depressed areas of the co untry, where options are the most limited. The commenters argued that if small emergency engi nes would no longer be permitted to operate for peak shaving purposes without having to be reclassified as non- emergency engines and subsequently subject to costly emissions controls , owners could no longer afford to participate in such programs. Cooperatives argued that this woul d lead to increased costs that would ultimately be passed along to the customers. Commenters also maintained that keeping peak shaving programs would not lead to additional public health risks or emissions because the operation for peak shaving is minimal. If peak shaving is no t allowed under the rule, co mmenters said that this would lead to an increase in central power st ation capacity and possibl y more transmission and distribution line capacity to accommodate the in crease in demand resulting from eliminating small emergency engines from being used. This c ould lead to a larger im pact on the environment and public health than allowing a small numbe r of hours for peak shaving purposes. Certain small and remote facilities also rely on financia l programs to generate additional income in order to maintain their engines and stay in operati on. The additional funds can be essential for many smaller facilities and operations. Providing a limited allowance for peak shaving and nonemergency demand response could generate suffici ent income to prevent small facilities and owners from ceasing operation where these engines are in service. In orde r to further limit the operation of these engines to small, remote f acilities, the EPA is pr oposing that the power generated under this allowance can only be used at the facility or towards the local system. In addition, while the EPA is proposing this allo wance until the end of April 16, 2017, the EPA does not believe it is appropriate to continue the program beyond that time. Generators receive considerable compensation for th eir availability in peak shav ing programs and the EPA believes that it is not appropriate to a llow these engines to continue re ceiving compensation for this nonemergency use beyond 2017 without having to redu ce their emissions. The generators must by
that time decide whether to restrict their use to emergency or limited non-compensated nonemergency use or to reduce the emissions from th eir engines. The EPA also encourages engine4-8 owners and operators, as well as la rger system planners, to consider the use of alternative peak shaving options, such as load curtailments, lo wer emitting distributed generation, combined heat and power, and reduced line losses on the electricity grid.

The previous estimate of emissions from stati onary emergency engines is not expected to change due to this proposed limited allowance. To estimate emissions from stationary emergency engines, the EPA has previously estimated that emergency engines would on average operate for 50 hours per year. There is a wide range in how much these engines operate (some well below 50 hours per year), but on average and to be conservative, the EPA be lieves that 50 hours per year is still representative and consequently the environmental impact the EPA has calculated previously remains appropriate.In considerati on of all these issues, the EPA is proposing amendments to the rule to provide a limited a llowance for peak shaving for existing stationary emergency engines at area sour ces of HAP. The specific amendments the EPA is proposing are
discussed below.

4.2.1.2. What are the Proposed Amendments?

4.2.1.2.1 Emergency Demand Response.

The EPA is proposing to revise the current provisions for stationary engines used for emergency demand response operation. The provisi ons the EPA is proposing to amend are in §§63.6640(f) and 63.6675 of 40 CFR part 63, su bpart ZZZZ. Currentl y, §63.6640(f)(1)(iii) allows a maximum of 15 hours per year to be spent towards demand response operation under certain qualifying conditions. Al so, §63.6640(f)(1)(ii) currently includes an allowance of 100 hours per year for purposes of maintenance check s and readiness testing. The EPA is proposing that owners and operators of stationary emergenc y RICE be permitted to operate their engines as part of an emergency demand response program within the 100 hours per year that is permitted for maintenance and testing in §63.6640(f)(1)(ii). Owners and operato rs of stationary emergency engines can operate for emergency demand res ponse during periods in which the regional transmission authority or equiva lent balancing author ity and transmission operator has declared
an EEA Level 2 as defined in the North Ameri can Electric Reliability Corporation Reliability Standard EOP-002-3, Capacity and Energy Emer gency and during periods where there is a deviation of voltage or frequency of 5 percent or greater below standard voltage or frequency. The hours spent for emergency demand response operation are added to the hours spent for maintenance and testing purposes and counted to wards the 100 hours per y ear. If the total time spent for demand response operation and maintena nce and testing exceeds 100 hours per year the engine will not be considered an emergency engi ne under this subpart and will need to meet all4-9 requirements for non-emergency engines. The EP A is recognizing that these engines may be called to operate not only by the regional transm ission operator or equivalent to maintain the reliability of the bulk power system, but also by the local transmission and distribution system operators to support the local power systems.

For stationary emergency engines above 500 HP that were installed prior to June 12, 2006, there is currently no emergency demand res ponse allowance and there is no time limit on the use of emergency engines for routine test ing and maintenance in §63.6640(f)(2)(ii). Those engines were not the focus of the 2010 RICE NESHAP amendments; therefore, the EPA did not make any changes to the requirements for thos e 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 a nd SI engines in 40 CFR part 60, subparts IIII and JJJJ, respectively, to provide the sa me allowance for stationary emergency engines for emergency demand response operation as for engines subject to the RICE NESHAP. The NSPS regulations currently do not include such an allowance for emergency demand response operation. For the reasons discusse d as to why the EPA finds it appropriate to allow stationary emergency engi nes to participate in emergency demand response programs and remain being considered emergency units, and fo r consistency across engine regulations, the EPA is proposing to add an emergency demand response allowance under the NSPS regulations. Consequently, the EPA is proposing to revise the existing language in §§60.4211(f) and 60.4219 of 40 CFR part 60, subpart II II, and §§60.4243(d) and 60.4248 of 40 CFR part 60, subpart JJJJ, to specify that emergency engines may partic ipate in demand response programs for up to 100 hours per year, including hours spent towards mainte nance and testing of th e emergency engines.

4.2.1.3 Peak Shaving and other Non-emergency Use as Part of a Financial Arrangement.

In addition to the changes the EPA is proposing related to emergency demand response operation, the EPA is also including a further pr ovision for owners and operators of existing stationary emergency RICE lo cated at area sources. Paragr aph §63.6640(f) currently allows owners and operators of emergency stationary RI CE to operate their engine for 50 hours per year in non-emergency situations. As currently wr itten, the 50 hours per year for non-emergency situations cannot be used for peak shaving or to generate income for a f acility to supply power to an electric grid or otherwise s upply power as part of a financial arrangement with another entity;4-10 except that owners and operators of certain em ergency engines may operate the engine for a maximum of 15 hours per year as part of an emergency demand response program. As discussed, the 15 hours per year allowance for emergency engines to participate in emergency demand response programs is being increased to 100 hour s per year, but will also include hours spent towards maintaining and conducting readiness te sting of the emergency engines. However, additionally, the EPA is also proposing that stati onary emergency engines lo cated at area sources be permitted to apply the 50 hours per year th at is currently allowed under §63.6640(f) for nonemergency operation towards any non-emergency ope ration, including operation as part of a financial agreement with anothe r entity. The peak shaving allo wance would expire in 2017. The EPA is specifying that the power can only be used at the facility or towards the local system, and the engine can only be operated for peak shaving as part of a program with the local distribution system operator. The EPA is also clarifying that an engine that exceeds the calendar year limitations on non-emergency operation, including emergency demand response or peak shaving, will be considered a non-emergency engine a nd subject to the requirements for non-emergency engines for the remaining life of the engine.

4.2.1.4. Proposed Amendment - Stationary Agricultural RICE in San Joaquin Valley

In the 2010 amendments to the RICE NESHAP, the EPA required existing nonemergency CI engines above 300 HP to meet a st andard of either 70 pe rcent reduction of CO emissions or 49 ppmvd CO, for engines between 300 and 500 HP, or 23 ppmvd CO for engines above 500 HP. The requirements also included tes ting and monitoring provisions. As with all requirements for existing engines in that rule, owners and operato rs were required to meet the requirements within 3 years of the effectiv e date of the regulations (May 3, 2013).

Since the finalization of the rule for existing st ationary CI engines, stakeholders from the agricultural industry in the Sa n Joaquin Valley area of Califor nia have expressed concern regarding the effect of certain of these requirements on en gines in the San Joaquin Valley. The San Joaquin Valley Air Pollution Control Distri ct (APCD) has indica ted that there are 17 stationary CI engines at area sources in San Joaq uin Valley certified to th e Tier 3 standards in 40 CFR part 89 that were installed between Ja nuary 1 and June 12, 2006. Under the NESHAP, stationary CI engines at area sources are existing if construction of the engine commenced prior to June 12, 2006. These 17 Tier 3 engines in the San Joaquin Valley, which were built to meet stringent emission standards, would not be able to comply with the applicable RICE NESHAP emission standards for existing engines without further testing and monitoring, and possible retrofit with further controls, due to differences in the emission standards and testing protocols in
the RICE NESHAP versus the Tier 3 standards in 40 CFR part 89. However, an identical engine4-11 certified to the Tier 3 standard s (or Tier 2 standards for engine s above 560 kilowatts (kW)) in 40 CFR part 89 that was installed after June 12, 2006, would not have to be retrofit in order to comply with the NESHAP. Stationary CI engines installed after June 12, 2006, at area sources of HAP are required to comply with the NSPS for stationary CI engi nes, which requires engines to be certified to the standards in 40 CFR part s 89, 94, 1039, and 1042, as applicable. Thus, a 2006 model year stationary CI engine installed after June 12, 2006, that is certified to the applicable standards would meet the requirements of the NESHAP without further controls or testing.
While the EPA does not know if other certified Ti er 3 engines besides these 17 engines in the San Joaquin Valley were installed prior to June 12, 2006, EPA believes the same rationale should apply to any such engine.

The EPA believes that the Tier 3 standa rds (Tier 2 for engines above 560 kW) are technologically stringent regulations and believes it is unnecessary to re quire further regulation of engines meeting these standards. In order to address this concer n, the EPA is proposing changes to amend the requirements for any certif ied Tier 3 (Tier 2 for engines above 560 kW) stationary CI engine located at an area source and installed before June 12, 2006. The EPA is proposing amendments to specify that any existi ng certified Tier 3 (Tie r 2 for engines above 560 kW) CI engine that was installed before June 12, 2006, is in compliance with the NESHAP. This amendment would include any existing stationary Tier 3 (Tier 2 for engines above 560 kW) certified CI engine located at an area source of HAP emissions.

Another concern brought to the EPA’s atten tion by the San Joaqui n Valley agricultural industry is that due to state a nd local requirements in the San Jo aquin Valley, many of the Tier 1 and Tier 2 stationary CI engine s that are regulated as existing sources under the NESHAP must be replaced in the next few years, only a shor t time after the emission standards for existing engines must be met. Specifically, the San Joa quin Valley APCD rule for internal combustion engines (Rule 4702) requires Tier 1 and Tier 2 certified engines to meet Tier 4 standards by January 1, 2015, or 12 years afte r the installation date, but no later than June 1, 2018. The concern is that owners and opera tors of these engines would have to install aftertreatment by
2013 to meet the emission standards of the RICE NESHAP and then only a few years later be required to replace their engines per San Jo aquin Valley APCD Rule 4702. The San Joaquin Valley APCD has identified 49 Tier 1 engines and 360 Tier 2 engines that are scheduled to be replaced under the local rule. The EPA has not identified any engines outside the San Joaquin Valley APCD area that are in the same or simila r situation (i.e., required to be replaced shortly after the compliance date for exis ting engines), but the EPA does not preclude the possibility that4-12 there are such engines in othe r areas, and requests comment and information on other areas that may have similar concerns.

The EPA does not think it is appropriate to require emission controls on a stationary CI engine that is going to be retired only a short tim e after the rule goes into effect. Stationary CI engines would have to comply with this ru le by May 3, 2013, and owners of engines above 300 HP are expected to have to inst all aftertreatment on their engine s in order to meet the emission
standards. The EPA estimates that the one-time cost to equip a 500 HP stationary CI engine with the controls necessary to meet the emission st andards under this rule is close to $14,000 and more than $3,000 on a yearly basis, not accoun ting for additional costs associated with monitoring, testing, recordkeeping and reporting. These engines (e quipped with aftertreatment) could end up being in operation for less than 2 y ears or at most only 5 y ears before having to be replaced with a certified Tier 4 engine, as requ ired by San Joaquin Valley District Rule 4702. It would not be reasonable to requir e the engine owner to invest in costly controls and monitoring equipment for an engine that will be replaced shortly after the installation of the controls.

Consequently, the EPA is proposing amendmen ts to existing stationary CI engines
located at area sources of HAP emissions to address this concern. The EPA is proposing to amend the requirements for existing stationary Tier 1 and Tier 2 certified CI engines located at area sources that are greater than 300 HP that are subject to a state or local rule that requires the engine to be replaced. The EPA is proposing to allow these engines to meet management practices for a period of 2 years starting with the applicable May 3, 2013, compliance date. The EPA believes a period of 2 years is appropriate and provides owners enou gh time to replace their engines without mandating a possibly cost prohibitive requirement to change all of the engines in a short amount of time, while stil l requiring that replacement of th e engine or a retrofit of the engine occur relatively quickly after the owne r would have to comply with the NESHAP. The EPA is proposing that these engines be subjec t to management practices until May 3, 2015, after
which time the CO emission standards discussed above (and that are in Table 2d of the rule) apply. The management practices include requirements for when to inspect and replace the engine oil and filter, air cleaner, hoses and belt s. The complete details of which management practices are required are shown in Table 2d of the rule. Owners and operators of these existing stationary CI engines located at area sources of HAP emissions th at intend to meet management practices rather than the emission limits pr ior to May 3, 2015, must submit a notification by March 3, 2013, stating that they intend to use th is provision and identifying the state or local regulation that the e ngine is subject to.

4.2.1.5 Proposed Amendments – for Remote Areas of Alaska4-13 4.2.1.5.1 Background for Proposed Amendments

The RICE NESHAP currently specifies le ss stringent requirem ents for existing nonemergency CI engines at area sources located in remote areas of Alaska. Remote areas are defined as those not accessible by the FAHS. Th e FAHS includes areas with year-round ferry
service that are not on the con tiguous road system. Under the cu rrent regulation, stationary nonemergency CI engines at area sources in areas of Alaska that are not ac cessible by the FAHS are subject to management practices as oppos ed to numerical emission standards.

Following the publication of the final rule in 2010, the EPA received requests to expand
the definition of remote areas of Alaska. Stakeholde rs asserted that facili ties in areas that are accessible by the FAHS but are not connected to the Alaska Railbel t grid face the same challenges as those in areas not accessible by the FAHS. The Alaska Railbelt Grid refers to the service areas of the six regulated public utilitie s that extend from Fairbanks to Anchorage and the
Kenai Peninsula. These utilities are the Golden Valley Electric Association, Chugach Electric Association, Matanuska Electric Association, Homer Electric Asso ciation, Anchorage Municipal Light & Power, and the City of Seward Electr ic System. According to the stakeholders, one reason for broadening the definition of remote areas in Alaska is high energy costs, which provide a natural incentive to run CI engines as little as possible. The cost of energy is utilities’ greatest concern in Alaska. Also, the stakeholders indicated that extreme weather conditions in
certain areas of Alaska is anothe r reason for including a dditional areas in the de finition of remote areas of Alaska. The climate issue is unique to re mote areas of Alaska that experience some of the most extreme temperatures in the c ountry. Heavy snowfall and high winds are not
uncommon in several areas that are accessibl e by the FAHS. For instance, Copper Valley Electric Association (CVEA) is a utility accessi ble by the FAHS, but it includes areas that face the same challenges as other communities not accessible by the FAHS. The utility operates on an isolated grid and relies on dies el power generation. In one of CV EA’s territories, Valdez, Alaska, CVEA indicated that this area experiences brutal conditions and stated that Valdez is considered to have the greatest snowfall (326 inches per winte r) in any city of the United States. Also, winds at more than 100 miles per hour are not uncom mon for Valdez, Alaska, according to CVEA. Temperatures between 40 and 50 below zero ar e also not abnormal, which emphasizes the extreme reliance on power, CVEA asserted. Travel times and accessibility are issues on a regular basis, but can be additionally exacerbated due to severe weather, which in some cases may lead to avalanches and road closings. In particular, ev en if a site is on the FAHS, in the event of poor weather conditions and road closings, there are in many cases no alternat e roads to travel on. Further, access to specific isolated sites can also be problematic in par ticular remote areas of4-14 Alaska and the problems are unique to Alaska becau se of the infrastructure and environment. For example, communities made the case that sour ces along the AMHS that are only accessible by the AMHS should be treated the same way as communities not accessible by the FAHS. The AMHS primarily serves passenge rs and vehicles, and is not intended for transporting goods. Therefore, the same methods used to bring in goods to communities not on the FAHS are the same as those Alaskan villages served only by the AMHS. Goods are typically brought in to remote communities by barge and this is another exam ple of a scenario that is unique to Alaska. Other arguments for expanding the definition of remote areas of Alaska beyond those not accessible by the FAHS include very low popul ation density in many other remote areas although accessible by the FAHS, and the fact that many of these areas are not connected to the electric grid and rely on back up diesel gene ration to support fluctuating renewable energy systems. The energy supply system is another ar ea that is particularly different in Alaska compared to the rest of the country whose majo rity of customers are connected to the grid. Lastly, if sources were to comply with requ irements under the RICE NESHAP necessitating addon controls and associated monitoring, testi ng, and administrative re quirements, compliance costs would be high and funds needed for sustai nable renewable energy go als would be diverted. Therefore, for the reasons discussed, the EPA is proposing expansion of the remote area source category. This proposal is suppor ted by the Alaska Department of Environmental Conservation
and communities with whom the EPA has discussed this issue.

4.2.1.5.2 What are the Proposed Amendments?

The EPA is proposing to expand the current definition of remote areas of Alaska to extend beyond areas that are not accessible by the FAHS. Specifically, the EPA is proposing that areas of Alaska that are accessible by the FAHS and that meet all of the following criteria are also considered remote and subject to management practices under the rule:

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

•At least 10 percent of the power generated by th e engine per year is used for residential purposes, and

•The system capacity is less than 12 megawatts , or the engine is used exclusively for backup power for renewable energy and is used less than 500 hours pe r year on a 10-year rolling average.

The EPA is proposing limiting the remote classificati on to engines that are us ed at least partially for residential purposes, where the impact of hi gher energy costs is of greatest concern. The4-15 classification is further limited to sources that are used infre quently as backup for renewable power, or that are at smaller cap acity facilities, which are genera lly in more sparsely populated

areas.

4.2.1.6 Compliance Date

The EPA has received some questions re garding whether the compliance dates for engines impacted by the 2010 amendments and th is proposed reconsideration will be extended. Affected sources that may be impacted by th is action have expresse d concern about having sufficient time to comply with the rule by the compliance date, which is May 3, 2013, for existing stationary CI RICE and October 19, 201 3, for existing stationa ry SI RICE. Sources impacted by this reconsideration are particularly concerned with compliance in the event that the EPA does not finalize changes that are substantially similar to the changes being proposed in this
action. The EPA does not intend to extend the May 3, 2013, and October 19, 2013, compliance dates, because there are many e ngines that must meet those compliance dates that are not impacted by this reconsideration. However, we note that sources that are affected by the reconsideration and that may need additional ti me to install controls to comply with the applicable requirements can request up to an additio nal year to install controls, as specified in 40 CFR 63.6(i).

4.2.2 What Are the Pollutants Regulated by this Proposed Reconsideration Rule?
The proposed reconsideration ru le regulates emissions of HA P. Available emissions data show that several HAP, which are formed during the combustion process or which are contained within the fuel burned, are emitted from stationary engines. The HAP which have been measured
in emission tests conducted on di esel fired RICE include: 1,3- butadiene, acetaldehyde, acrolein, benzene, ethylbenzene, formaldehyde, n-hexane , naphthalene, polycycli c aromatic hydrocarbons, polycyclic organic matter, styrene, toluene, and xylene. Metallic HAP from diesel fired stationary RICE that have been measured ar e: cadmium, chromium, lead, manganese, mercury, nickel, and selenium.

EPA described the health effects of these HAP and other HAP emitted from the operation of stationary RICE in the preamble to 40 CFR part 63, subpart ZZZZ, published on June 15, 2004 (69 FR 33474). These HAP emissions are known to cause, or contribute significantly to air pollution, which may reasonably be anticipated to endanger public health or welfare. More4-16 details on the health effects of these HAP and other HAP emitted from operation of stationary
RICE can be found in Section 7 of this RIA.

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

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

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

4.3 Cost Impacts

4.3.1 Introduction
The cost impacts associated with this rule consist of different types of costs, which include the annual and capital co sts of controls, costs associat ed with keeping records of information necessary to demonstrate compliance, costs associated with reporting requirements under the General Provisions of 40 CFR part 63, s ubpart A, costs of purchasing and operating equipment associated with continuous parame tric monitoring, and the cost of conducting performance testing to demonstrate compliance with the emission standards. The capital and

1 In contrast, mobile source emission standards for diesel engines (both nonroad and on-highway) are promulgated on a mass basis rather than concentration.4-17 annual costs presented in this section are ca lculated based on the control cost methodology presented in the EPA (2002) Air Pollution C ontrol Cost Manual prepared by the U.S. Environmental Protection Agency. 2 This methodology sets out a procedure by which capital and annualized costs are defined and estimated, and this procedure is often used to estimate the costs of rulemakings such as this one. The capital cost s presented in this sect ion are annualized using a 7% interest rate, a rate that is consistent with the guidance provided in the Office of Management and Budget’s (OMB’s) (2003) Circular A-4. 3 The following sections describe how the various
cost elements were estimated. Note that the methodologies and procedures presented in the following sections are the same as those used for the 2010 final rule.

4.3.1.1 Control Costs
For engines that will need to add control t echnology to meet the em ission standards, the following equations were used to estimate capita l and annual control costs as shown in Table 4-
3:

Table 4-1 : CI RICE Control T echnologies and Costs
Technology Capital Cost ($2008) Annual Cost ($2008) Diesel oxidation ca talyst (DOC) $27.4 x hp

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

The control costs for DOC were calculated usi ng cost data obtained from a California Air Resources Board (CARB) study. 4 The study provided cost ranges fo r diesel engines ranging from 40 hp to 1400 hp. The average cost from the rang e was selected and was adjusted to 2008 dollars. The capital and annual co st were calculated using maintenance data from the CARB study and cost assumptions from the EPA Air Po llution Control Cost Manual. The control costs for the OCV system were calculated using 2008 cost data obtained fr om a diesel engine equipment vendor. An equipment life of 10 years was used to calculate the capital recovery factor (CRF) for developing the annual cost for each of the control devices. A linear regression equation was developed for the capital cost of th e DOC and OCV using the capital cost data and the engine size in hp. This approach was used to develop a linear regr ession equation for annual

cost.

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

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

. 4 Diesel PM Control Technologies, Appendix IX, California Air Resource Board, October 2000. http://www.arb.ca.gov/diesel/documents/rrpapp9.pdf4-18 4.3.1.2 Recordkeeping
Minimal recordkeeping costs were attribut ed to the requirement of following the
manufacturer’s emission-related operation and maintenance (O&M ) requirements or the owner or operator’s own maintenance plan. It is expected that the major ity of owners and operators are already following some type of O&M requirement s and a small additional burden is expected. The EPA expects that at most 1 hour will be necessary per year in order to keep track of maintenance. Owners and operator of stationary em ergency engines are required to keep track of the hours of operation and 1 hour per year was es timated to cover that recordkeeping activity. For emergency engines 1 hour is expected to co ver tracking hours of operation plus recording
maintenance activities. No cost is attributed to purchasing and installing an hour-meter since the majority of stationary engines already come equipped with such equipment. Labor costs associated with recording the hours of operation of emergency e ngines are based on a technical labor rate of $68 per hour which was obtained from the Department of Labor Statistics web site. 5 The final total wage rate was based on the 2005 compensation rates for professional staff and adjusted by an overhead and prof it rate of 167 percent. The year 2005 was used for consistency
in order to have the same basis for all costs. All costs were later converted to 2008 dollars for purposes of presenting costs associated w ith the rule in present day terms.
4.3.1.3 Reporting
Most engines affected by this rule will be subject to reporting requirements such as reading instructions, training personnel, submitting an initial no tification, submitting a notification of performance test(s), and submitti ng a compliance report. However, owners and operators of engines less than 100 HP, existing stationary emergency engines, and existing stationary engines less than 300 HP located at area sources are not subject to any specific reporting requirements. For stationary non-emer gency limited use CI engines that operate less than 100 hours per year, EPA is finalizing less burdensome reporting requirements by requiring these engines to submit compliance reports on an annual basis, as opposed to semiannually as is required for other engines subjec t to numerical emission limitati ons. The reporting requirements are based on $68 per hour for technical labor to comply with the reporting requirements. It is
estimated that a total of 14 hours will be needed, and 13 hours for limited use engines.
4.3.1.4 Monitoring
The cost of monitoring includes the purchas e of a continuous parametric monitoring system (CPMS). Non-emergency engines greate r than 500 hp that have add-on controls are

5 U.S. Department of Labor, Employer Costs for Employee Compensation, http://www.bls.gov/news .release/ecec.toc.htm4-19 required to use a CPMS to monitor the catalyst inlet temperature and pressure drop across the catalyst to ensure those parameters do not exceed the operating limita tions. The cost of purchasing and operating a CPMS was obtaine d from vendor quotes received for previous rulemaking and adjusted to 2008 dollars. 6 The capital cost of a CPMS for a large engine facility is $531. It is estimated that 30 hours per year is necessary to operate and maintain the CPMS and that 6 hours per year (or 0.5 hours per month) is n eeded to record information from the CPMS. It is assumed that all engines subject to continuous monitoring would be lo cated at large engine
facilities.
4.3.1.5 Performance Testing
Initial performance testing is required for non-emergency en gines greater than 100 hp at major sources and non-emergency engines greater th an 300 hp located at area sources. The cost of conducting a performance test on a CI engine is based on cost information gathered for previous rulemakings. 7 The performance testing cost is base d the use of a portable analyzer and was estimated to cost $1,000 per day of testing. Th is daily performance test cost was adjusted to 2008 dollars and was estimated to be $1,165. Because the regulation requires three-1 hour runs, EPA assumed that two engines could be tested at each facility in one day. Therefore, the estimated impacts performance testing cost will be assumed to be $583 per engine (or half of the $1,165 daily cost) using a portable analyzer.

4.3.1.6 Work Practices
The costs for performing work practices for CI engines less than 100 hp located at a major source was assumed to be negligible and we re not included in these impact calculations. The work practices are based on engine mainte nance procedures that the owner/operators perform regardless of the regulati on. These work practices include:

 Changing the oil and filter;

 Inspecting the air cleaner and replacing as necessary; and

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

EPA believes that these work practices w ill limit HAP emissions from these engines, because these work practices ensure that the e ngine is operating efficiently. Owner/operators of these engines regularly perform these work prac tices as part of the preventive maintenance

6 Part A of the Supporting Statement for Standard Form 83 Stationary Reciprocating Internal Combustion Engines, November 17, 2003.
7 Memorandum from Bradley Nelson, Alpha-Gamma Technologies, Inc. to Sims Roy, EPA/OAQPS/ESD/Combustion Group, Portable Emissions Analyzer Cost Information, August 31, 2005.4-20 schedule for the engine. Therefore, EPA believes that it is appropriate to not include these work practice costs in the impacts determination.
4.3.1.7 Management Practices
The costs for performing management practic es for non-emergency CI engines less than or equal to 300 hp located at ar ea sources and all emergency engines located at area sources was assumed to be negligible and were not included in these impact calcul ations. The management practices are based on engine maintenance pr ocedures that the owner/operators perform regardless of the regulation. Thes e management practices include:

 Changing the oil and filter;

 Inspecting the air cleaner, and re placing as necessary; and

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

EPA believes that these work practices w ill limit HAP emissions from these engines, because these work practices ensure that the e ngine is operating efficiently. Owner/operators of these engines regularly perform these work prac tices as part of the preventive maintenance schedule for the engine. Therefore, EPA believes that it is appropriate to not include these work practice costs in the impacts determination.
4.3.2 Major Sources
The cost impacts for stationary RICE vary depending on the engine type and size. The following sections describe the specific costs th at apply to each sub category of CI engines located at major sources.
4.3.2.1 All CI Engines hp < 100
The costs associated with CI engines less than 100 hp include mi nimal requirements. Owners and operators of engines less than 100 hp are required to follow the manufacturer’s emission-related O&M requirements or must deve lop their own maintenance plan to follow. Emergency engines must record the hours of opera tion, which is estimated at one hour per year at $72 per hour.

4.3.2.2 Non-emergency CI Engines 100 ≤ hp ≤ 300 hp
The costs associated with nonemergency CI engines greater than or equal to 100 hp and less than or equal to 300 hp include the cost of an initial test, recor dkeeping, and reporting. In addition, EPA assumes that some of these engines will be required to install a control device to4-21 meet the emissions standard. To estimate the num ber of CI engines that would be required to install control technology, EPA compared the emissi on rate of the test that was used to determine
the MACT floor with the CI nonroad emission factors. 8 EPA found that only the emission factors for Tier 0 CI engines were greater than the 1.2 g/hp-hr value that was used to set the MACT floor. Therefore, it was assumed that Tier 1 engi nes and greater would be able to meet the final emission standard. The model year for Tier 1 en gines begins in 1997 for 100 to 175 CI engines, and 1996 for 175 to 300 hp CI engines. Using the model year data in the population memorandum, EPA estimated that 35 percent of the existing CI engines grea ter than or equal to 100 hp and less than or equal to 300 hp are Tier 0 engines and would need to install control technology to meet the emission standard. The cost estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ultra-low sulfur diesel (ULSD). EPA estimated the cost of lubricity addi tives to ULSD would in crease the cost of the fuel by 0.2 cents per gallon, 9 which EPA believes is negligib le. In addition, there are no additional maintenance requirements for owner/opera tors using ULSD in existing diesel engines. Many owner/operators have found that time betw een oil changes can be extended for engines using ULSD fuel, which would decrease the overa ll cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not include any costs for switching to ULSD in the impacts
for this NESHAP.
4.3.2.3 Nonemergency CI Engines > 300 hp
The costs associated with non-emergency CI engines above 300 hp include the cost of installing and operating an oxidation catalyst for reducing HAP, as well as the cost of installing an open crankcase ventilation system. Non-emer gency CI engines greater than 500 hp are also subject to continuous monitoring requirements. In addition, owners and operators must conduct an initial performance test to demonstrate co mpliance with the emission limitation. Owners and operators of engines above 500 hp must conduc t subsequent performance testing every 8,760 hours or 3 years, whichever comes first to demonstrate compliance. The cost estimates for this subcategory of engines do not account for possibl e fuel price increases that may result from using ULSD. EPA estimated the cost of lubricity additives to ULSD would increase the cost of the fuel by 0.2 cents per gallon, 10 which EPA believes is neglig ible. In addition, there are no

8 Exhaust and Crankcase Emission Factors for Nonroad E ngine Modeling--Compression-Ignition, U.S. EPA, Office of Transportation and Air Quality, Assessment and Standa rds Division, EPA420-P-04-009, Revised April 2004. http://www.epa.gov/oms/models/nonrdmdl/nonrdmdl2004/420p04009.pdf
9 Memorandum from Melanie Taylor and Brad Nelson, AGTI to Sims Roy, EPA OAQPS ESD Combustion Group, Lubricity of Ultra Low Sulfur Diesel Fuel, June 2, 2004.
10 Memorandum from Melanie Taylor and Brad Nelson, AGTI to Sims Roy, EPA OAQPS ESD Combustion Group, Lubricity of Ultra Low Sulfur Diesel Fuel, June 2, 2004.4-22 additional maintenance requirements for owner/opera tors using ULSD in existing diesel engines. Many owner/operators have found that time betw een oil changes can be extended for engines using ULSD fuel, which would decrease the overa ll cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not include any costs for switching to ULSD in the impacts
for this NESHAP.
4.3.2.4 Emergency CI Engines
The costs associated with emergency CI e ngines greater than 300 hp and less than or equal to 500 hp (emergency CI engines above 500 hp were subject to an ear lier rule and are not subject to further regulation in this rule) in clude minimal recordkeeping requirements. The owners and operators must follow the manu facturer’s emission-related operating and maintenance (O&M) requirements or must develo p their own maintenance plan to follow and must also keep records of the hour s of operation. It is estimated th at one hour per year at $68 per
hour would be sufficient to record the hours of operation. No costs were included in the impacts for following the manufacturer’s emission-relate d O&M plan, because it is expected that owner/operators will follow this plan regardless of the regulation.

4.3.3 Area Sources
4.3.3.1 All Emergency CI Engines
The costs associated with emergency CI e ngines include recordk eeping requirements for tracking the hours of operation, but these engines are not subject to any performance testing. The owners and operators must follo w the manufacturer’s emission -related O&M requirements or must develop their own maintenance plan to follow . It is estimated that one hour per year at $68 per hour would be sufficient to record the hours of operation. Emergency CI engines at areas sources will be subject to management prac tices, rather numerical emission limits. The management practices do not requ ire aftertreatment controls. Ther efore, no control costs have been estimated for these engines. These engines will be subject to management practices which are not included in the costs, because it is assumed that these management practices are performed regardless of the regulation.
4.3.3.2 Non-emergency CI Engines ≤ 300 hp
The costs associated with nonemergency CI engines less than or equal to 300 hp are minimal and only include following the manufact urer’s emission-related O&M requirements or the owner or operator’s own maintenance plan. Th ese engines are not subject to any numerical emission limitations, therefore no control costs apply and no pe rformance testing is required.4-23 These engines will be subject to management pr actices which are not included in the costs, because it is assumed that these management prac tices are done regardless of the regulation.
4.3.3.3 Non-emergency CI Engines > 300 hp
The costs associated with nonemergency CI engines above 300 hp include the cost of installing and operating an oxidation catalyst for reducing HAP, as well as the cost of installing an open crankcase ventilation system. Nonemerg ency CI engines greater than 500 hp are also subject to continuous monitoring requirements. In addition, owners and operators must conduct an initial performance test to demonstrate comp liance with the emission limitation and engines above 500 hp must conduct subsequent perfor mance testing every 8,760 hours or 3 years, whichever comes first. The cost estimates for this subcategory of engines do not account for possible fuel price increases that may result from using ULSD. The cost estimates for this subcategory of engines do not account for possibl e fuel price increases that may result from using ULSD. EPA estimated the cost of lubricity additives to ULSD would increase the cost of the fuel by 0.2 cents per gallon, which EPA belie ves is negligible. In addition, there are no additional maintenance requirements for owner/opera tors using ULSD in existing diesel engines. Many owner/operators have found that time betw een oil changes can be extended for engines using ULSD fuel, which would decrease the overa ll cost of switching to ULSD fuel. Therefore, EPA believes that it is appropriate to not include any costs for switching to ULSD in the impacts
for this NESHAP.

A summary of the total costs associated w ith the rule by major source and area source categories is found in Table 4-2. A summary of the costs by NAICS codes is found in Table 4-3. Table 4-4 provides a summary of costs by engine size, and a pr esentation of the number of engines by engine size is in Table 4-5. All cost estimates are from “RICE NESHAP
Reconsideration Amendment – Cost and Enviro nmental Impacts RICE,” prepared by Tanya Parise, EC/R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards.4-24Table 4-2. Summary of Major Source and Area Source Costs for the CI RICE NESHAPaSizeRange(hp)Non-EmergencyCI CapitalControl CostNon-EmergencyCI AnnualControl Cost Initial Test Recordkeeping ReportingMonitoring –Capital CostMonitoring –Annual CostTotal AnnualCostsTotal CapitalCostsMajor Sources50–100 $0 $0 $0 $6,654,888 $0 $0 $0 $6,654,888 $0100–175 $24,057,778 $9,918,465 $14,150,269 $8,719,731 $5,973, 016 $0$0 $38,761,480 $24,057,778175–300 $35,917,270 $10,740,189 $10,730,759 $6,612,548 $4,529,595 $0 $0 $32,613,092 $35,917,270300–500 $107,841,136 $26,722,727 $5,645,923 $3,479,152 $2,383,219 $0 $0 $38,231,021 $107,841,136500–600 $13,126,952 $3,020,849 $500,530 $61,688 $211,280 $481,765 $2,220,755 $6,015,102 $13,608,716600–750 $8,240,540 $1,824,295 $256,204 $31,576 $108,147 $246,599 $1,136,729 $3,356,951 $8,487,139>750 $26,903,091 $5,618,803 $565,163 $69,653 $238,563 $543,975 $2,507,521 $8,999,703 $27,447,066Total $216,086,768 $57,845,329 $31,848,848 $25,629,236 $13,443,820 $1,272,338 $5,865,005 $134,632,238 $217,359,106Area Sources50–100 $0 $0 $0 $9,183,746 $0 $0 $0 $9,183,746 $0100–175 $0 $0 $0 $12,033,196 5,231,824 $0 $0 $17,265,000 $0175–300 $0 $0 $0 $9,125,316 $3,967,529 $0 $0 $13,092,845 $0300–600 269, 176, 789 $64,764,947 $12,533,931 $7,180,954$5,290,738 $4,021,343$18,536,893 $108,307,463$273,198,131600–750 67,576,980 $14,964,227$2,101,015 $1,203,716$886,866 $674,082 $9,321,806 $28,473,630,$68,251,062,>750 177,179,667 $37,004,585 $3,722,077 $2,132,457$1,571,138 $1,194,178$16,514,152 $60,944,409$178,373,845Total 513,933,435 $116,729,759 $18,357,024 $40,859,384$16,948, 096 $5,889,603 $44,372,851 $237,267,114$519,823,039Grand TotalTotal $730,020,203 $174,575,088 $50,205,872 $66,480,620 $30,391,916 $7,161,941$50,237,856 $371,899,352 $737,182,145aCosts are presented in 2008 dollars.4-25Table 4-3. Summary of Major Source and AreaSource NAICS Costs for the CI RICE NESHAPaNAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostElectric Power Generation(2211)$161,766,376 $90,982,105 $464,947,798 $202,463,116 $626,714,174 $293,445,222Hospitals (622110) $20,220,797 $11,372,763 $0 $0 $20,220,797 $11,372,763Crude Petroleum & NGProduction (211111)$2,374,401 $3,807,478 $1,590,115$2,597,836 $3,964,516 $6,405,314Natural Gas Liquid Producers(211112)$2,374,401 $3,807,478 $1,590,115$2,597,836 $3,964,516 $6,405,314National Security (92811) $20,220,797 $11,372,763 $51,660,866 $22,495,902 $71,881,663 $33,868,665Hydro Power Units (335312) $0 $16,637 $0 $22,959 $0 $39,597Irrigation Sets (335312) $10,294,073 $11,791,567 $34,145 $5,208,084 $10,328218 $16,999,651Welders (333992) $108,260 $1,481,447 $0 $1,881,380 $108,260 $3,362,827Total $217,359,106 $134,632,238 $519,823,039 $237,267,114 $737,182,145 $371,899,352aCosts are presented in 2008 dollars.4-26Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by SizeaNAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostElectric Power Generation (2211)50–100 hp $0 $3,396,123 $0 $5,272,480 $0 $8,668,603100–175 hp $13,406,919 $21,600,998 $0$10,824,132 $13,406,919 $32,425,129175–300 hp $23,012,914 $20,895,861 $0$9,437,454 $23,012,914 $30,333,314300–600 hp $96,907,266 $35,304,866 $245,239,035 $97,223,277 $342,146,301 $132,528,144600–750 hp $6,789,032 $2,685,292 $61,419,814 $25,623,705 $68,208,846 $28,308,997>750 hp $21,650,245 $7,098,966 $158,288,950 $54,082,069 $179,939,195 $61,181,035Total 2211 $161,766,376 $90,982,105 $464,947,798 $202,463,116 $626,717,174 $293,445,222Hospitals (622110)50–100 hp $0 $424,515 $0 $0 $0 $424,515100–175 hp $1,675,865 $2,700,125 $0 $0 $1,675,865 $2,700,125175–300 hp $2,876,614 $2,611,983 $0 $0 $2,876,614 $2,611,983300–600 hp $12,113,408 $4,413,108 $0 $0 $12,113,408 $4,413,108600–750 hp $848,629 $335,662 $0 $0 $848,629 $335,662>750 hp $2,706,281 $887,371 $0 $0 $2,706,281 $887,371Total 622110 $20,220,797 $11,372,763 $0 $0 $20,220,797 $11,372,763Crude Petroleum & NG Production (211111)50–100 hp $0 $420,256 $0 $579,954 $0 $1,000,210100–175 hp $2,026,868 $3,265,655 $0$1,454,578 $2,026,868 $4,720,233175–300 hp $3,592 $3,261 $0 $1,309 $3,592 $4,571300–600 hp $151,812 $55,308 $341,498 $135,384 $493,310 $190,692600–750 hp $0 $0 $0 0 $0 $0>750 hp $192,129 $62,998 $1,248,617 $426,611 $1,440,746 $489,609Total 211111 $2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314(continued)4-27Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by Sizea(continued)NAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostNatural Gas Liquid Producers (211112)50–100 hp $0 $420,256 $0 $579,954 $0 $1,000,210100–175 hp $2,026,868 $3,265,655 $0$1,454,578 $2,026,868 $4,720,233175–300 hp $3,592 $3,261 $0 $1,309 $3,592 $4,571300–600 hp $151,812 $55,308 $341,498 $135,384 $493,310 $190,692600–750 hp 0 0 0 0 $0 $0>750 hp $192,129 $62,998 $1,248,617 $426,611 $1,440,746 $489,609Total 211112 $2,374,401 $3,807,478 $1,590,115 $2,597,836 $3,964,516 $6,405,314National Security (92811)50–100 hp $0 $424,515 $0 $585,831 $0 $1,010,346100–175 hp $1,675,865 $2,700,125 $0$1,202,681 $1,675,865 $3,902,806175–300 hp $2,876,614 $2,611,983 $0$1,048,606 $2,876,614 $3,660,589300–600 hp $12,113,408 $4,413,108 $27,248,782 $10,802,586 $39,362,190 $15,215,695600–750 hp $848,629 $335,662 $6,824,424 $2,847,078 $7,673,053 $3,182,740>750 hp $2,706,281 $887,371 $17,587,661 $6,009,119 $20,293,942 $6,896,489Total 92811 $20,220,797 $11,372,763 $51,660,866 $22,495,902 $71,881,663 $33,86,665Hydro Power Units (335312)50–100 hp $0 $16,637 $0 $22,959 $0 $39,597100–175 hp $0 $0 $0 $0 $0 $0175–300 hp $0 $0 $0 $0 $0 $0300–600 hp $0 $0 $0 $0 $0 $0600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $0 $0 $0 $0Total 335312 $0 $16,637 $0 $22,959 $0 $39,597(continued)4-28Table 4-4. Summary of Major Source and Area SourceNAICS Costs for the CI RICE NESHAP – by Sizea(continued)NAICSMajor Source Area Source Total (Major + Area)Capital Cost Annual Cost Capital CostAnnual Cost Capital Cost Annual CostIrrigation Sets (335312)50–100 hp $0 $245,565 $0 $338,880 $0 $584,446100–175 hp $3,137,134 $5,054,497 $0$2,251,359 $3,137,134 $7,305,856175–300 hp $7,143,945 $6,486,744 $0$2,604,167 $7,143,945 $9,090,911300–600 hp $12,145 $4,425 $27,320 $10,831 $39,465 $15,255600–750 hp $849 $336 $6,825 $2,847 $7,674 $3,183>750 hp $0 $0 $0 $0 $0 $0Total 335312 $10,294,073 $11,791,567 $34,145 $5,208,984 $10,328,218 $16,999,651Welders (333992)50–100 hp $0 $1,307,020 $0 $1,803,688 $0 $3,110,708100–175 hp $108,260 $174,427 $0 $77,693 $108,260 $252,119175–300 hp $0 $0 $0 $0 $0 $0300–600 hp $0 $0 $0 $0 $0 $0600–750 hp $0 $0 $0 $0 $0 $0>750 hp $0 $0 $0 $0 $0 $0Total 333992 $108,260 $1,481,447 $0 $1,881,380 $108,260 $3,362,827Grand TotalTotal $217,359,106 $134,632,238 $519,823,039 $237, 267,114 $737,182,145 $371,899,352aCosts are presented in 2008 dollars.4-29Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of EnginesaNAICSNumber of Engines Total (Major + Area)Major Area Total Capital Cost Annual CostElectric Power Generation (2211)50–100 hp 47,324 79,859 127,183 $0 $8,668,603100–175 hp 67,713 114,266 181,980 $13,406,919 $32,425,129175–300 hp 59,039 99,627 158,666 $23,012,914 $30,333,314300–600 hp 42,113 97,919 140,032 $342,146,301 $132,528,144600–750 hp 1,760 16,455 18,215 $68,208,846 $28,308,997>750 hp 3,828 28,746 32,574 $179,939,195 $61,181,035Total 2211 221,777 436,872 658,649 $626,717,174 $293,445,222Hospitals (622110)50–100 hp 5,916 0 5,916 $0 $424,515100–175 hp 8,464 0 8,464 $1,675,865 $2,700,125175–300 hp 7,380 0 7,380 $2,876,614 $2,611,983300–600 hp 5,264 0 5,264 $12,113,408 $4,413,108600–750 hp 220 0 220 $848,629 $335,662>750 hp 479 0 479 $2,706,281 $887,371Total 622110 27,722 0 27,722 $20,220,797 $11,372,763Crude Petroleum & NG Production (211111)50–100 hp 5,856 8,784 14,640 $0 $1,000,210100–175 hp 10,237 15,355 25,592 $2,026,868 $4,720,233175–300 hp 9 14 23 $3,592 $4,571300–600 hp 66 136 202 $493,310 $190,692600–750 hp 0 0 0 $0 $0>750 hp 34 227 261 $1,440,746 $489,609Total 211111 16,202 24,517 40,719 $3,964,516 $6,405,314(continued)4-30Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of Enginesa(continued)NAICSNumber of Engines Total (Major + Area)Major Area Total Capital Cost Annual CostNatural Gas Liquid Producers (211112)50–100 hp 5,856 8,784 14,640 $0 $1,000,210100–175 hp 10,237 15,355 25,592 $2,026,868 $4,720,233175–300 hp 9 14 23 $3,592 $4,571300–600 hp 66 136 202 $493,310 $190,692600–750 hp 0 0 0 $0 $0>750 hp 34 227 261 $1,440,746 $489,609Total 211112 16,202 24,517 40,719 $3,964,516 $6,405,314National Security (92811)50–100 hp 5,916 8,873 14,789 $0 $1,010,346100–175 hp 8,464 12,696 21,160 $1,675,865 $3,902,806175–300 hp 7,380 11,070 18,450 $2,876,614 $3,660,589300–600 hp 5,264 10,880 16,144 $39,362,190 $15,215,695600–750 hp 220 1,828 2,048 $7,673,053 $3,182,740>750 hp 479 3,194 3,672 $20,293,942 $6,896,489Total 92811 27,722 48,541 76,263 $71,881,663 $33,868,665Hydro Power Units (335312)50–100 hp 232 348 580 $0 $39,597100–175 hp 0 0 0 $0 $0175–300 hp 0 0 0 $0 $0300–600 hp 0 0 0 $0 $0600–750 hp 0 0 0 $0 $0>750 hp 0 0 0 $0 $0Total 335312 232 348 580 $0 $39,597(continued)4-31Table 4-5. Summary of Major Source and Area Source NAICSCosts for the CI RICE NESHAP – by Number of Enginesa(continued)NAICSNumber of Engines Total (Major + Area)Major Area Total Capital Cost Annual CostIrrigation Sets (335312)50–100 hp 3,422 5,133 8,555 $0 $584,446100–175 hp 15,845 23,767 39,611 $3,137,134 $7,305,856175–300 hp 18,327 27,491 45,819 $7,143,945 $9,090,911300–600 hp 5 11 16 $39,465 $15,255600–750 hp 0 2 2 $7,674 $3,183>750 hp 0 0 0 $0 $0Total 335312 37,599 56,403 94,003 $10,328,218 $16,999,651Welders (333992)50–100 hp 18,213 27,319 45,532 $0 $3,110,708100–175 hp 547 820 1,367 $108,260 $252,119175–300 hp 0 0 0 $0 $0300–600 hp 0 0 0 $0 $0600–750 hp 0 0 0 $0 $0>750 hp 0 0 0 $0 $0Total 333992 18,760 28,140 46,899 $108,260 $3,362,827Grand TotalTotal 366,217 619,337 957,832 $737,182,145$371,899,352aCosts are presented in 2008 dollars.4-32 4.4 Baseline Emissions and Emission Reductions

The emissions reductions associated with the proposed reconsidered rule are based on requiring emission standards that are based on applying add-on controls to non-emergency CI engines greater than 500 HP. Baseline emissions from the current population of stationary RICE less than or equal to 500 HP at major sources an d existing stationary RICE at area sources were calculated based on non-emergency CI engines operating 1,000 hrs/yr, and emergency CI engines operating 50 hrs/yr. While the amendm ents the EPA is proposing for stationary emergency engines increases the time allowed fo r participation in emergency demand response programs and for certain engines to operate fo r peak shaving or other income-generating activities, the EPA believes that 50 hours per year is still repr esentative of emergency engine operation. There is a wide range in how much stationary emer gency engines operate. Some emergency units operate well below 50 hrs/yr, while some emergency engines are run above 50 hrs/yr. However, on average and to be conservative, the EPA be lieves that 50 hrs/yr is still representative and consequently to estimate emissions from stat ionary emergency engines, the EPA has retained the assumption that 50 hrs/ yr is appropriate. Th e following additional assumptions were used:

Emission Factors: Engine HAP (lb/hp-hr) CO (lb/hr) PM (lb/hp-hr) SO 2 (lb/hp-hr) CI 1.07x10 -4 6.96x10 -1 7.00x10 -4 0.00809xS 1 * *Obtained from AP-42, section 3.4 where S 1 is sulfur content.

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

Based on the above assumptions and the exis ting population of engine s shown earlier in this section, the HAP, CO, and PM baseline emissions and reductions were calculated

The estimated baseline emissions for each HAP and criteria pollutant in tons per year (tpy) for the final rule are shown in Table 4- 6. The estimated emission reductions for each HAP and criteria pollutant reductions in tons per year (tpy) as a resu lt of the final rule are shown in Table 4-7. In addition, it is e xpected that additional PM reduc tions will be achieved by the requirement to use ULSD for CI engines that install a DOC. The use of ULSD reduces the4-33 formation of sulfates in the exhaust gas, ther efore reducing the emissi on of these sulfate PM
emissions from the exhaust. EPA has estimated that the use of ULSD can reduce PM emissions by 5 to 30 percent depending on the sulfur concentrati on of the diesel fuel that is being replaced. Because EPA has no information on the type of fuel that CI engines are currently using, the PM reductions from switching to UL SD were not quantified and included in this summary.

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

The EPA is also proposing to specify that any existing certified Tier 3 CI engine that was installed before June 12, 2006, is in complian ce with the NESHAP. Th is amendment would include any existing stationary Ti er 3 certified CI engine locat ed at an area source of HAP emissions. There are 17 Tier 3 engines (2006 mode l year) located in San Joaquin Valley that were installed between January 1 and June 12, 2006. The EPA does not know if there are additional engines in other areas that in a si milar situation and the EPA has no information indicating how many such engines there could be in the rest of the country. Therefore, for purposes of calculating reductions, the EPA has in cluded 17 less engines from the control cost estimate. These 17 engines would under the pro posed amendments be subject to management practices.

The work practice requirement of using an open crankcase ventilation system to control metallic HAP emissions is expected to achieve additional HAP reductions from CI engines. However, the metallic HAP emission reduction cannot be quantified because of the difficulty of measuring metallic HAP from the crankcase exhaust. Therefore, the metallic HAP reductions
are not included in the total emission reductions. Also, all PM emissions are assumed to be in the fine particle emissions; t hus all emissions and PM emissi on reductions are assumed to be
PM 2.5
.4-34 Table 4-6. Summary of Major Source and Area Source Baseline Emissions for the CI RICE NESHAP in 2013

Summary of Major Source and Area Source Baseline Emissions for the RICE NESHAP
Size Range (HP) Baseline Emissions (tpy)
HAP CO NO x PM SO 2 VOC Major Sources 50-100 89 7,745 18,361 584 338 2,412 100-175 215 10,148 44,107 1,403 811 5,794 175-300 281 7,696 57,774 1,838 1,062 7,589 300-500 249 4,049 51,196 1,629 941 6,725 500-600 25 299 5,201 165 115 683 600-750 16 153 3,267 104 72 429

>750 52 338 10,677 340 236 1,402 Total 927 30,428 190,583 6,064 3,575 25,035 Area Sources 50-100 132 11,424 27,083 862 498 3,558 100-175 316 14,969 65,058 2,070 1,196 8,546 175-300 414 11,351 85,217 2,711 1,567 11,194 300-600 613 8,857 106,551 4,009 2,083 16,550 600-750 154 1,485 26,791 1,008 589 4,161

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

Grand Total 2,961 81,145 571,598 19,369 11,053 79,9654-35 Table 4-7. Summary of Major Source a nd Area Source Emissions Reductions for the CI RICE NESHAP in 2013

Summary of Major Source and Area Source Em ission Reductions for the CI RICE NESHAP

Size Range (HP) Emission Reductions (tpy)
HAP CO PM VOC Major Sources
50-100 0 0 0 0 100-175 44 2,072 123 1,183 175-300 57 1,571 161 1,549 300-500 145 2,362 407 3,923
500-600 18 209 50 478
600-750 11 107 31 300

>750 36 236 102 982 Total 312 6,558 874 8,416 Area Sources
50-100 0 0 0 0
100-175 0 0 0 0
175-300 0 0 0 0 300-600 363 5,244 1,017 9,798 600-750 91 879 256 2,463

>750 239 1,557 671 6,466 Total 693 7,680 1,944 18,727 Total 1,005 14,238 2,818 27,142 28 PM Estimate for 2010 Final CI Rule 1,014 14,342 2,844 27,395 Difference 9 104 26 253

Note: All emission reduction estimates are from “ RICE NESHAP Reconsideration Amendments- Cost and Environmental Impacts ,” prepared by Tanya Pari se, Ec/R, Inc. for Melanie King, U.S. EPA, Office of Air Quality Planning and Standards

.5-1 SECTION 5 ECONOMIC IMPACT ANALYSIS, ENER GY IMPACTS, AND SOCIAL COSTS

The EIA provides decision makers with social cost estimates and enhances understanding of how the costs may be distributed acro ss stakeholders (EPA , 2010). Although several
economic frameworks can be used to estimate social costs for regulations of this size and sector scope, OAQPS has typically used partial equilibrium market models. However, the current data do not provide sufficient details to develop a market model; the data that are available have little or no sector/firm detail and are reported at the national level. In addi tion, some sectors have unique market characteristics (e.g., hospitals) that make developing partial equilibrium models difficult. Given these constraints, we believe d the direct compliance costs as a reasonable approximation of total social cost s. In addition, we also provid e a qualitative an alysis of the proposed rule’s economic impact on stakeholde r decisions, a qualitati ve discussion on if unfunded mandates occur as a result of this propos ed rule, and a qualitative discussion of the potential distribution of social costs between consumers and producers.

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

As shown in Figure 5-1, the majority of the costs fall on the electric power sector (79%), followed by national security (9%). The remaining industries each account for 5% or less of the
total annualized cost. The industrial classificat ion for each engine is taken from the Power Systems Research (PSR) database, which is the ma jor source of data for the engines affected by
the final rule. The PSR database used as a basis for the analyses in this RIA contains information on both mobile and stationary onr oad and nonroad engines, among other data, and does so not only for the U.S. but worldwide. PSR has collected such data for more than 30 years. The Office of Transportation and Air Qualit y (OTAQ) uses this data base frequently in the development of their mobile source rules.

The annualized compliance costs per engine va ry by the engine size (see Figure 5-2). For 300 hp engines or less, the annualized per-engin e costs are below $215 per engine. Per-engine costs for higher horsepower (hp) engines range between $950 and $1,900.

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

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

3% 2% 2% 9%

0% 5%

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

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

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

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

24% 31%

23%

16%

2% 4%

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

50-100 hp 100-175 hp 175-300 hp 300-600 hp 600-750 hp >750 hp5-4 To assess the size of the comp liance cost relative to the va lue of the goods and services for industries using affected engi nes, we collected Census data for selected industries. At the industry level, the annualized costs represent a very small fraction of revenue (less than 0.07%) (Table 5-1). These industry level cost-to-sales ratios can be inte rpreted as an average impact on potentially affected firms in these industries. Ba sed on the cost-to-sales ratios, we can conclude
that the annualized cost of this rule should be no higher than 1% of th e sales on average for a
firm in each of these industries.

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

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

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

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

92811 National Security $33,9 #N/A #N/A #N/A
333992 Welders $3.4 $5.2 $5.3 0.06%

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

a Irrigation engine costs assumed to be passed on to agricultural sectors that use irrigation systems. N/A: receipts are Not Available for National Security Sources: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 00: All sectors:

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

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

Agency. Impacts Associated with NESH AP for Existing Stationary CI RICE.

5.2 Social Cost Estimate
As shown in Table 5-1, the compliance costs ar e 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 belie ves the national annualized compliance cost estimates provide a reasonable approximation of th e social cost of this proposed rule. EPA believes this approximation is better for indus tries whose markets are well characterized as5-5 perfectly competitive. This approximation is less well understood for industries where the characterization of markets is not always perfectly competitive such as electric power generation whose legal incidence of this rule is approximately 80 percent of the annualized compliance cost. However, given the data limitation noted earlie r, EPA believes the ac counting for compliance cost is a reasonable approximation to inform policy discussion in this rulemaking. To shed more light on this issue, EPA ran hypothe tical analyses and the results ar e later in the RIA in Tables 5-
2 and 5-3.

5.3 How Might People and Firms Respond? A Partial Equilibrium Analysis
Markets are composed of people as consum ers and producers trying to maximize utility (consumers) and maximize profits (producers) th ey can given their economic circumstances. One way economists illustrate behavi oral responses to pollution cont rol costs is by using market supply and demand diagrams. The market supply curve describes how much of a good or service firms are willing and able to sell to people at a pa rticular price; this curve is typically upward sloping because some production resources are fi xed. As a result, the cost of producing an additional unit typically rises as more units ar e made. The market demand curve describes how much of a good or service consumers are willing and able to buy at some price. Holding other factors constant, the quantity demand is assumed to fall when prices rise. In a perfectly competitive market, equilibrium price (P 0 ) and quantity (Q 0 ) is determined by the intersection of the supply and demand curves (see Figure 5-4).
5.3.1 Changes in Market Prices and Quantities
To qualitatively assess how the regulation may influence the equilibrium price and quantity in the affected markets, we assume d the market supply function shifts up by the additional cost of producing the good or service; the unit cost increase is typically calculated by dividing the annual compliance cost estimate by the baseline quantity (Q 0 ) (see Figure 5-4). As shown, this model makes two predic tions: the price of the affected goods and services are likely to rise and the consumption/product ion levels are likely to fall.5-6 consumer surplus = –[fghd + dhc] producer surplus = [fghd – aehb] – bdc total surplus = consumer surplus + producer surplus = –[aehb + dhc + bdc]
Figure 5-4. Market Demand and Supply Mo del: With and Without Regulation

The size of these changes depends on two f actors: the size of the unit production cost increase (supply shift) and differences in how each side of the mark et (supply and demand) responds to changes in price. Economists measure responses using the con cept of price elasticity, which represents the percentage change in quantity divided by th e percentage change in price. This dependence has been expressed in the following formula: 1



##   Demand) of Elasticity Price

- Supply of Elasticity Price Supply of Elasticity Price

 cost production 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 peopl e do not have good substitutes that they can switch to easily (demand is inelastic) and

1 For examples of similar mathematical models in the public finance literature, see Nicholson (1998), pages 444–447, or Fullerton and Metcalf (2002).5-7  suppliers have excess capacity and can eas ily adjust production levels at minimal costs, or the time period of analysis is long enough that suppli ers can change their fixed resources; supply is more elastic over longer periods.

Short-run demand elasticities for energy goods (e lectricity and natura l gas), agricultural products, and construction are ofte n inelastic. Specific estimates of short-run demand elasticities for these products can be obtained from existi ng literature. For the s hort-run demand of energy products, the National Energy Modeling System (N EMS) 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 agri culture and approximately 1 fo r construction (EPA, 2004). As a result, a 1% increase in the prices of agricu lture products would lead to a 0.2% decrease in demand for those products, while a 1% increas e in construction prices would lead to approximately a 1% decrease in demand for construction. Given these demand elasticity scenarios (shaded in gray), approximately a 1% increase unit costs would result in a price increase of 0.1 to 1% (Table 5-2). As a result , 10 to 100% of the unit cost increase could be passed on to consumers in the form of higher goods/services prices. This price increase would correspond to a 0.1 to 0.8% decline in cons umption in these markets (Table 5-3).
Table 5-2. Hypothetical Price Increase s 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 Ge neration, Transmission, and Distribution Sector
Given that the electric power sector bears majority of the estimated compliance costs (Figure 5-1) and the industry is also among the last major regu lated energy industries in the United States (EIA, 2000), the competitive model is not necessarily applicab le for this industry.5-8 Table 5-3. Hypothetical Consumption Decreases for a 1% Increase in Unit Costs

Market Demand Elasticity Market Supply Elasticity

0.1 0.3 0.5 0.7 1 1.5 3

− 0.1

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.1%

− 0.3

− 0.1% − 0.2%

− 0.2%

− 0.2%

− 0.2%

− 0.3%

− 0.3%

− 0.5

− 0.1%

− 0.2% − 0.3%

− 0.3%

− 0.3%

− 0.4%

− 0.4%

− 0.7

− 0.1%

− 0.2%

− 0.3% − 0.4%

− 0.4%

− 0.5%

− 0.6%

− 1.0

− 0.1%

− 0.2%

− 0.3%

− 0.4% − 0.5%

− 0.6%

− 0.8%

− 1.5

− 0.1%

− 0.3%

− 0.4%

− 0.5%

− 0.6% − 0.8%

− 1.0%

− 3.0

− 0.1%

− 0.3%

− 0.4%

− 0.6%

− 0.8%

− 1.0% − 1.5%

Although the electricity i ndustry continues to go through a pro cess of restructuring, whereby the industry is moving toward a more competitive framework (see Figure 5-5 for the status of restructuring by state), 2 in many states, electricity prices con tinue to be fully regulated by Public Service Commissions. As a result, the rules a nd processes outlined by these agencies would ultimately determine how these additional regulatory costs would be recovered by affected
entities.
5.3.3 Partial Equilibrium Measures of Soci al Cost: Changes Consumer and Producer Surplus
In partial equilibrium analysis, the social co sts are estimated by measuring the changes in consumer and producer surplus, and these values can be determined using the market supply and demand model (Figure 5-4). The change in c onsumer surplus is measured as follows:



CS = – [  Q 1 ×  p ] + [0.5 ×  Q ×  p ]. (5.1)

Higher market prices and lower quantities lead to consumer welfare losses. Similarly, the change in producer surplus is measured as follows:



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

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.

2 http://tonto.eia.doe.gov/energy_in_br ief/print_pages/electricity.pdf.5-9 Figure 5-5. Electricity Restructuring by State
Source. U.S. Energy Information Administration. 2010a.

<http://www.eia.doe.gov/cneaf/electricity/page/restructur ing/restructure_elect.html>. Last updated September 2010.

5.4 Energy Impacts
Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agencies will prepare
and submit to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, a Statement of Energy Effects for certain actions identified as “significant energy actions.” S ection 4(b) of Executive Order 13211 defines “significant energy actions” as any action by an ag ency (normally published in the Federal Register ) that promulgates or is expected to lead to the pr omulgation of a final rule or regulation, including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed rulemaking: (1) (i) that is a significant re gulatory action under Executive Order 12866 or any successor order, and (ii) is likely to have a significant adverse effect on the supply, distri bution, or use of energy; or (2) that is designated by the Administrator of the Office of In formation and Regulatory Affairs as a significant energy action.5-10 This rule is not a signifi cant energy action as designated by the Administrator of the Office of Information and Regulatory Affairs because it is not likely to have a significant adverse impact on the supply, distribution, or use of ener gy. EPA has prepared an analysis of energy impacts that explains this conclusion as follows below.

With respect to energy supply and prices, th e analysis in Table 5-1 suggests at the industry level, the annualized cost s represent a very small fracti on of revenue (less than 0.7%). As a result, we can conclude supply a nd price impacts should be small.

To enhance understanding regarding the regu lation’s influence on energy consumption, we examined publicly available data describing en ergy consumption for the electric power sector that will be affected by this rule. The A nnual Energy Outlook 2011 (EIA, 2011) provides energy consumption data. As shown in Table 5-4, this i ndustry account for about 0.3% of the U.S. total liquid fuels and less than 8% of natural gas. As a result, any energy consumption changes attributable to the regulatory program should not significantly influen ce the supply, distribution, or use of energy.

5.5 Unfunded Mandates

Title II of the Unfunded Mandates Refo rm Act of 1995 (UMRA), 2 U.S.C. 1531-1538, requires Federal agencies, unless otherwise prohibited by law, to assess the effects of their regulatory actions on State, local, and tribal governments and the privat e sector. This rule contains a Federal mandate that may result in expenditures of $100 million or more for State, local, and tribal governments, in the aggregat e, or the private sect or in any one year. Accordingly, EPA has prepared under section 20 2 of the UMRA a written statement which is
summarized below in this section.5-11 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 power plants whose primary business is

to sell electricity, or electricity an d heat, to the public. Includes small power producers and exempt wholesale generators.

b Includes conventional hydroelectric, geothermal, wood and wood waste, biogenic municipal solid waste, other

biomass, petroleum coke, wind, photovoltaic and solar thermal sources. Excludes net electricity imports.

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

projections for 2013. Available at: http://www.eia.gov /oiaf/aeo/tablebrowser/#rel ease=EARLY2012&subject=6- EARLY2012&table=2-EARLY2012®ion=1-0&cases=full2011-d020911a,early2012-d121011b
5.5.1 Future and Disproportionate Costs
The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the rule and any disproportio nate budgetary effects. Our estimates of the future compliance costs of the fina l rule are discussed prev iously in Section 4 of
this RIA. We do not believe that there will be any disproportionate budgetary effects of the final rule on any particular areas of the country, St ate or local governments, types of communities (e.g., urban, rural), or partic ular industry segments.
5.5.2 Effects on the National Economy
The UMRA requires that we estimate the e ffect of the proposed rule on the national economy. To the extent feasible, we must estim ate the effect on producti vity, economic growth, full employment, creation of productive jobs, an d international competitiveness of the U.S. goods and services if we determine that accurate es timates are reasonably feasible and that such
effect is relevant and material. The nationw ide economic impact of the proposed rule is presented earlier in this RIA chapter. This an alysis provides estimates of the effect of the5-12 proposal rule on most of the categories menti oned above, and these estimates are presented earlier in this RIA chapter. In addition, we have determined that the proposed rule contains no regulatory requirements that might significantly or uniquely affect small governments. Therefore, today’s rule is not subject to the requirements of section 203 of the UMRA.

5.6 Environmental Justice

Executive Order (EO) 12898 (59 FR 7629 (Fe b. 16, 1994)) establishes federal executive policy on environmental justice. Its main provi sion directs federal agencies, to the greatest extent practicable and permitted by law, to make environmental justice part of their mission by identifying and addressing, as appropriate, disp roportionately high and adverse human health or environmental effects of their programs, policie s, and activities on minority populations and lowincome populations in the United States.

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 environm ental protection for all affected populations without having any disproportionately high and adve rse human health or environm ental effects on any population, including any minority or low-income population. This rule is a nationwide standard that reduces air toxics emissions from existing statio nary CI engines, thus decreasing the amount of
such emissions to which all a ffected populations are exposed.

5.7 Employment Impact Analysis

In addition to addressing the costs and benef its of the proposed rule, EPA has analyzed the impacts of this rulemaking on employment, wh ich are presented in th is section. While a standalone analysis of employment impacts is no t included in a standard cost-benefit analysis, such an analysis is of particular concern in the current economic c limate of sustained high unemployment. Executive Order 13563, states, “Our regulatory system must protect public health, welfare, safety, and our environment while promoting economic growth, innovation, competitiveness, and job creation” (emphasis added). Therefore, and consistent with recent efforts to characterize the employ ment effects of economically si gnificant rules, the Agency has provided this analysis to inform the discussi on of labor demand and em ployment impacts.

The analysis includes estimates of certain short-term and on-going labor requirements (increase in labor demand) associated with reporting and recordkeepi ng, and the installation,5-13 operating and maintenance of control devices. EPA estimates that approximately 1,300 jobs will be created or supported in the short-term (the compliance period of the regulation) and approximately 2,000 jobs will be created or supporte d annually on a permanent basis. EPA also provides a qualitative discussion of other potential employment e ffects, including both increases
and decreases. Because of the uncertainties involv ed, these sets of estimates should not be added in an attempt to characteri ze the overall employment effect.

We have not quantified the rule’s effects on a ll labor in other sector s not regulated by the proposed rule, or the effects i nduced by changes in workers’ in comes. What follows is an overview of the various ways that environmenta l regulation can affect employment, followed by a discussion of the estimated impacts of this rule. EPA continues to explore the relevant theoretical and empirical literatur e and to seek public comments in order to ensure that such estimates are as accurate, useful and informative as possible.

From an economic perspective, labor is an input into producing goods and services; if regulation requires that more la bor be used to produce a given amount of output, that additional
labor is reflected in an incr ease in the cost of production. 3 When an increase in employment occurs as a result of a regulat ion, it is a cost to firms. Moreover, when the economy is at full employment, we would not expect an environmen tal regulation to have an impact on overall employment because labor is being shifted from one sector to another. On the other hand, in periods of high unemployment, an increase in labor demand due to regulation may result in a short-term net increase in overall employment due to the potential hiring of previously unemployed workers by the regulated sector to he lp meet new requirements (e.g., to install new equipment) or by the environmental protection s ector to produce new abatement capital. When significant numbers of workers ar e unemployed, the opportunity cost s associated with displacing jobs in other sectors are likely to be smaller. And, in general, if a re gulation imposes high costs and does not increase the demand for labor, it may lead to a decrease in employment.

To provide a partial picture of the employmen t consequences of this rule, EPA takes two approaches. First, EPA uses information such as monitoring, record keeping, and reporting estimates derived from its cost analysis docum entation to generate estimates of employment impacts. Second, the analysis considers the re sults of Morgenstern, Pizer, and Shih (2002) in estimating the effects of the regulation on the regul ated industry. This appr oach has been used by

3 It should be noted that if more labor must be used to produce a given amount of output, then this implies a decrease in labor productivity. A decrease in labor productivity w ill cause a short-run aggregate supply curve to shift to the left, and businesses will produce less, all other things being equal.5-14 EPA previously in recent Regulatory Impact Anal yses. EPA is interested in public comments on the merits of including inform ation derived in this fashion for assessing the employment consequences of regulations.

5.7.1 Employment Impacts from Pollution Control Requirements

Regulations set in motion new orders for po llution control equipmen t and services. New categories of employment have been created in the process of implementing regulations. When a new regulation is promulgated, one typical response of industry is to order pollution control equipment and services in order to comply with the regulation when it becomes effective, while closure of plants that choose not to comply occurs after th e compliance date. With such a response by industry as a basis, th is section presents estimates for short term employment needed associated with the monitoring, re cordkeeping, and reporting requirements for this proposed rule. Environmental regulation may increase revenue and employment in the environmental technology industry. While these incr eases represent gains for that industry, they are costs to the regulated industries required to in stall the equipment. As with a ny pool of labor, the gross size of the labor pool does not reflect th e net impact on overall employment after adjusting for shifts in
other sectors.

Regulated firms hire workers to design and build pollution controls. Once the equipment is installed, regulated firms hire workers to ope rate and maintain the pollution control equipment – much like they hire workers to produce more output. Of course , these firms may also reassign existing employees to do these activities. Enviro nmental regulations also support employment in many basic industries. In addition to the in crease in employment in the pollution control industry (to fill increased orders for pollution co ntrol equipment placed by the regulated sector), environmental regulations also support employment in industries that provide intermediate goods to the pollution control industry. For example, an investment in capital expenditures to reduce air pollution involves the purchase of abatement equipment. The equipment manufacturers, in turn, order steel, tanks, vessels, blowers, pumps, and chemicals to manufacture and install the equipment. A study by Bezdek, Wendling, and Di Pernab (2008) found that “investments in environmental protection create jobs and displace jobs, but th e net effect on employment is positive.” 4 The majority of the jobs associated wi th added pollution controls (e.g., boilermakers, general construction workers, etc.) will provide domestic employment opportunities, but some

4 Environmental protection, the economy, and jobs: National and regional analyses

, Roger H. Bezdek, Robert M. Wendling and Paula DiPerna, Journal of Environmental Management Volume 86, Issue 1 , January 2008, Pages 63-79.5-15 goods and services demanded and/ or provided to the pollution control industry (e.g., steel, cement, etc.) are internationally traded goods.
Once the equipment is installed, regulated firms hire workers to operate and maintain the pollution control equipment – much like they hire workers to produce more output. Morgenstern et al. (2002) examined how regulated industrie s respond to regulation. The authors found that, on average for the industries they studied, employme nt increases in regulated firms. Of course, these firms may also reassign existing employees to perform these activities.

The focus of this part of the analysis is on labor requirements related to the compliance
actions of the affected entities within the a ffected sector. We do not estimate any potential changes in labor outside of the aff ected sector. It is important to highlight that unlike the typical case where to reduce a bad output (i.e., emissions) a firm often has to reduce production of the good output, many of the emission controls requir ed by the proposed rule will simultaneously increase production of the good output and reduce production of bad outputs. That is, these controls jointly pr oduce environmental improvements and incr ease output in the regulated sector. New labor associated with implementing these cont rols to comply with the new regulations can
also be viewed as additional labor increasi ng output while reduci ng undesirable emissions.

The employment analysis uses a bottom-up engineering-based met hodology to estimate employment impacts. The engineering cost anal ysis summarized in Section 4 of this RIA includes estimates of the labor requirements associated with implementing the proposed regulations. Each of these labor ch anges 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 continua l, annual labor requirements by estimating hours of labor required and converti ng this number to full-time equivalents (FTEs) by dividing by 2,080 (40 hours per week multiplied by 52 weeks). We note that this type of FTE estimate cannot be used to make assumptions about th e specific number of peopl e involved or whether new jobs are created for new employees.

The results of this employment estimate are presented in Table 5-5 for the proposed
NESHAP. The tables breaks down the installatio n, operation, and maintenance estimates by type of pollution control evaluated in the RIA and present both the es timated hours required and the
conversion of this estimate to FTE. For th e proposed NESHAP, repor ting and recordkeeping requirements were estimated requirements were es timated for the entire rule rather than by anticipated control requirements; the reporting and recordkeeping estimates are consistent with5-16 estimates EPA submitted as part of its Information Collection Request (ICR) that is in the Supporting Statement for the pr oposed reconsideration rule.

The up-front labor requirement is estimated at 1,269 FTEs for the proposed reconsidered NESHAP. These up-front FTE labor requirement s can be viewed as short-term labor requirements required for affected entities to comply with the new regulation. Ongoing requirements are estimated at about 1,978 FTEs fo r the proposed reconsidered NESHAP. These ongoing FTE labor requirements can be viewed as sustained labor requirements required for affected entities to continuously co mply with the new regulation. A ll of this data is found in the cost memorandum for this proposed reconsidered rule, and can be found in the docket for the rulemaking. It is important to recognize that these seemingly precise estimates are not to be assumed to be exact measures of the employment impacts of this rulema king. They represent a rough approximation of the small positive impacts that this rule may have on employment.

Table 5-5. Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Cont rol Equipment Requirements for Proposed Reconsideration CI RICE NESHAP

Source

Emission Control Measure Projected No. of Affected Units Per-UnitOneTime Labor Estimate (Hours) TotalOneTime Labor Estimate (Hours) Per-Unit Annual Labor Estimate (Hours) Total Annual Labor Estimate (Hours) One-Time Full-Time Equivalent Annual Full-Time Equivalent

All CI RICE -O&M Recordkeeping N/A 366,217 N/A N/A 1 366,217 N/A 176 Non-Emergency CI RICE 100- 300 HP -Testing Oxidation Catalyst 54,697 11 593,496 2 738,404 285 355 -Reporting 8 Non-Emergency CI RICE > 300 HP 3.5

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

-Reporting 8 -CPMS Install 3.5 -CPMS O&M 1 -CPMS Recording 30
Area Sources 6 All CI RICE -O&M Recordkeeping Non-Emergency N/A 569,364 N/A N/A 1 569,364 N/A 2745-17 CI RICE 100- 300 HP -Testing N/A 64,095 N/A N/A 2 128,190 N/A 62 -Reporting Non-Emergency CI RICE > 300 HP Oxidation Catalyst + Crankcase Ventilation + CPMS 31,526 47 1,483,695 5 1,675,922 713 806

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

Total 105 2,640,361 124 4,114,232 1,269 1,978 Note : Full-time equivalents (FTE) are estimated by first multip lying the projected number of affected units by the per unit labor requirements and then dividing by 2,080 (40 hours multiplied by 52 weeks). Totals may not sum due to independent rounding. CPMS = Continuous Parameter Measurement System HP = horsepower N/A = Not Applicable. O&M = Operating and Maintenance

5.7.2 Employment Impacts within the Regulated Industry

In recent RIAs we have applied estimat es from a study by Morgenstern, Pizer and Shih (2002) 5 to derive the employment effects of new regulations w ithin the regulated industry. (See, for example, the Regulatory Impact Analyses for the recently released final MATS and final CSAPR regulations). Determining the direction of employment effects in the regulated industr y is also challenging due to competing effects. Complying with the new or more stringent regulation re quires 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 requiri ng regulated firms to add a new output (environmental quality) to their product mixes. Although legally compelled to satisfy this new demand, regulated firms have to finance this additional production with the proceeds of sales of their other (market) products. Satisfying this new demand requires additional

5 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 200 2. Jobs versus the Environment: An Industry-Level Perspective. ‖ Journal of Environmental Economics and Management 43(3):412-436.5-18 inputs, including labor, and ma y alter the relative proportions of labor and capital used by regulated firms in their production processes.

More specifically, Morgenst ern, Pizer, and Shih (2002) decompose the effect of regulation on net employment in the regulated sector into the follo wing three subcomponents:

 The Demand Effect : higher production costs from comp lying with the regulation will raise market prices, reducing consum ption (and production), thereby reducing
demand for labor within the re gulated industry. The “extent of this effect depends on the cost increase passed on to consumers as well as the demand elasticity of industry output.” (p. 416)

 The Cost Effect : Assuming that the capital/labor ratio in the production process is held fixed, as “production costs rise, more inputs, including labor, are used to produce the same amount of output,” (p. 416). For example, to reduce pollutant emissions while holding output levels c onstant, regulated firms may re quire additional labor.

 The Factor-Shift Effect : Regulated firms’ production technologies may be more or less labor intensive after complying with the regulation (i.e., more/less labor is required relative to capital pe r dollar of output). “Envir onmental activities may be
more labor intensive than conventional production,” meaning that “the amount of labor per dollar of output will rise.” Howeve r, activities may, instead, be less labor intensive because “cleaner operations coul d involve automation and less employment, for example.” (p. 416)

The demand effect is expected to have an unambiguously negative effect on employment, the cost effect to have an unambiguously posi tive effect on employment, and the factor-shift effect to have an ambiguous effect on employment . Without more information with respect to the magnitudes of these three competing eff ects, it is not possible to predict the net environmental employment eff ect in the regulated sector.

Using plant-level Census information be tween the years 1979 and 1991, Morgenstern et al. estimate the effects of pollution abatement expenditures on net employment in four highly polluting/regulated sectors (pulp and paper, plastics, steel, a nd petroleum refining). They
conclude that increased abatem ent expenditures generally have not caused a significant change in net employment in those sectors. More specifica lly, their results show th at, on average across the industries studied, each additional $1 million (in 1987$) spent on pollution abatement results in a5-19 (statistically insignifi cant) net increase of 1.55 (+/- 2.24) jobs. As a result, the authors conclude that increases in pollution abatement expenditures can have positive effects on employment and do not necessarily cause economically significan t employment changes. The conclusion is similar to Berman and Bui (2001), who found th at increased air quality regulation in Los Angeles did not cause larg e employment changes.

Ideally, the EPA would first apply the met hodology of Morgenstern et al. to current pollution expenditure and market da ta for the regulated firms to identify the relationship between abatement costs and employment, then use this relationship to extrapolate the effect of new projected abatement costs on these firms. Unfort unately, current firm-level abatement cost and
market characteristics are not av ailable. In addition, there ar e important differences in the markets and regulatory settings analyzed in their study and the setting presented here that lead us to conclude that it is inappropriate to util ize their quantitative estimates to estimate the employment impacts from this reconsiderati on proposal. The differences between the underlying regulations motivating the abatement expenditures studied in Morgenstern et al. are potentially too many to allow for the direct transfer of their quantitative estimates for use in analysis of the proposed rule. There are also important differe nces between the industries affected by this proposed rule and the four manufacturing industr ies studied by Morgenstern et al. For these reasons, we conclude there are too many uncertain ties as to the comparability of the Morgenstern et al. study to apply their estimates to quantif y the employment impacts within the regulated sector for this proposed regulation.6-1 SECTION 6
SMALL ENTITY SCREENING ANALYSIS

The Regulatory Flexibility Act as am ended by the Small Business Regulatory Enforcement Fairness Act (SBREFA) generally re quires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the
Administrative Procedure Act or any other statute, unless the agen cy certifies that the rule will not have a significant economic impact on a substa ntial number of small entities. Small entities as defined by the Small Business Administra tion (SBA) include small businesses, small governmental jurisdictions, and sm all not-for-prof it enterprises.

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

6.1 Small Entity Data Set
The industry sectors covered by the proposed ru le were identified during the development of the cost analysis (Nelson, 2012). The SUSB provides national informa tion on the distribution of economic variables by industry and enterprise si ze (U.S. Census, 2006a, b). 1 The Census Bureau and the Office of Advocacy of the SBA s upported and developed these files for use in a broad range of economic analyses. 2 Statistics include the total number of establishments and receipts for all entities in an industry; however, many of thes e entities may not necessarily be covered by the final rule. SUSB also provides statistics by ente rprise employment and receipt
size.

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

 Establishmen t: An establishment is a single phys ical location wh ere business is conducted or where services or i ndustrial operations are performed.

1 The SUSB data do not provide establishment information fo r the national security NAICS code (92811) or irrigated farms. Since most national security installations are owne d by the federal government (e.g., military bases), EPA assumes these entities would not be considered small. For irrigated farms, we relied on receipt data provided in the 2008 Farm and Irrigation Survey (USDA, 2009).
2 See http://www.census.gov/csd/susb/ and http://www.sba .gov/advo/research/data.html for additional details.6-2  Receipts : Receipts (net of taxes) are define d as the revenue for goods produced, distributed, or services provided, in cluding revenue earned from premiums, commissions and fees, rents, interest, divi dends, and royalties. Receipts exclude all revenue collected for local, state, and federal taxes.

 Enterprise : An enterprise is a business organi zation consisting of one or more domestic establishments that were specifi ed under common ownership or control. The enterprise and the establishment are the same for single-establishment firms. Each multiestablishment company forms one enterprise—the enterprise employment and annual payroll are summed from the asso ciated establishmen ts. Enterprise size designations are determined by the su mmed employment of all associated establishments.

Because the SBA’s business size definitions (SBA, 2010) apply to an establishment’s “ultimate parent company,” we assumed in this an alysis that the “enterpri se” definition above is consistent with the concept of ultimate parent company that is typically used for SBREFA screening analyses and the terms are used interchangeably.

6.2 Small Entity Economic Impact Measures
The analysis generated a set of establishment sales tests (represented as cost-to-receipt ratios) 3 for NAICS codes associated with sectors li sted in Table 6-1. Although the appropriate SBA size definition should be applied at the pa rent company (enterpris e) level, we can only compute and compare ratios for a model establishm ent owned by an enterpri se within an SUSB size range (employment or receipts). Using th e SUSB size range helps us account for receipt differences between establishments owned by large and small enterprises and also allows us to
consider the variation in small business de finitions across affect ed industries. Using establishment receipts is also a conservative approach, because an establishment’s parent company (the “enterprise”) may have other economi c resources that could be used to cover the
costs of the final rule.
6.2.1 Model Establishment Receipt s and Annual Compliance Costs
The sales test compares a representative esta blishment’s total annual engine costs to the average establishment receipts for ente rprises in several size categories. 4 For industries with SBA

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

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

• small nonprofits (if applicable): “expenditure” test; annualized compliance cost as a percentage of annual operating expenses,
4 For the 1 to 20 employee categ ory, we excluded SUSB data for enterpri ses with zero employees. These enterprises did not operate the entire year.6-3 employment size standards, we calculated aver age establishment receipts for each enterprise employment range (Table 6-2). 5 For industries with SBA receipt size standards, we calculated
Table 6-1. Final NESHAP for Existing Stationa ry CI Reciprocating Internal Combustion Engines (RICE): Affected Sectors and SBA Small Business Size Standards

Industry Description Corresponding NAICS SBA Size Standard for Businesses (effective November 5 , 2010) Type of Small Entity
Electric power generation 2211 a Business and government

Natural Gas Transmission 48621 $7.0 million in annual receipts Business

General medical & surgical hospitals 622110 $34.5 million in annual r eceipts Business and government

Crude petroleum and natural gas production 211111 500 employees Business

Natural gas liquid producers 211112 500 employees Business

National security 92811 NA Government
Hydro power units See NAICS 2211 a Business and government
Irrigation sets Affects NAICS 111 and 112 Generally $750,000 or less in annual receipts Business

Welders Affects industries that use heavy equipment such as construction,

mining, farming Varies by 6-digit NAICS code; Example industry: NAICS 238 = $14 million in annual receipts Business

a NAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm is small if, including its affiliates, it is

primarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fiscal year did not exceed 4 million megawatt hours.

Source: U.S. Small Business Administ ration (SBA). 2010. “Table of Small Business Size Standards Matched to North American Industry Classification System Codes.” Effective November 5nd, 2010. Downloaded 2/16/12.

average establishment receipts fo r each enterprise r eceipt range (Table 6-3). We included the utility sector in the second gr oup, although the SBA size standard fo r this industry is defined in terms of physical units (megawatt hours) versus receipts. Crop and an imal production (NAICS 111 and 112) also have an SBA receipt size stan dard that defines a small business as receiving $750,000 or less in receipts per year. However, SUSB data were not available for these industries. Therefore, we conducted the sales te st using the following range of establishment

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

.6-4 receipts: farms with annual recei pts of $25,000 or less, farms with annual receipts of $100,000 or less, farms with annual receip ts of $500,000 or less, and farm s with annual receipts of $750,000
or less.6-5Table 6-2. Average Receipts for Affected Industryby Enterprise: 2009 ($2008 Million/establishment)SBA SizeStandardfor Businesses(effectiveNovember 5,2010)Owned By Enterprises with Employee Range:NAICS NAICS DescriptionAllEnterprises1–20Employees20–99Employees100–499Employees500+Employees211111 Crude petroleum &natural gas extraction500 employees $30.22 $2.15 $33.02 $151,76 1,570211112 Natural gas liquidextraction500 employees $172.81 $0.30 NA $11.88 NA335312 Motor & generator mfg 1,000 employees $18.58 $1.37 $6.14 $15.96 $29.47333992 Welding & solderingequipment mfg500 employees $18.51 $1.56 $6.60 $33.25 NA .NA = Not available.Source: U.S. Census Bureau. 2012a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.”<http://www.census.gov/csd/susb/ Downloaded 2/22/12.6-6Table 6-3. Average Receipts for Affected Industry byEnterprise Receipt Range:2007 ($2008 /establishment)SBA Size Standardfor Businesses(effective November5, 2010)Owned By Enterprises with Receipt Range:NAICS NAICS DescriptionAllEnterprises0–99KReceipts100–499.9KReceipts500–999.9KReceipts1,000–4,999.9KReceipts5,000,000–9,999,999KReceipts<10,000KReceipts10,000–49,999KReceipts50,000–99,999KReceipts100,000K+Receipts2211Electric PowerGenerationa$261.0 $31.2 $272.5 $724.9$2,399.5 $7,330.5 $2,617.7$24,786.9$67,706.8$1,394,051.0622110 Hospitals$34.5 million in annualreceipts$202,058.7 NA $23.82 NA$3,255.0 $7,291.0 $4,692.1$23,481.9$67,545,6$508,705.8237310Highway , street, andbride construction$33.5 million inAnnual Receipts$7.74$0.06$0.32$0.84$2.74$8.11$2.00$22.62$56.48$56.81237110Water and sewer lineand related structures,construction$33.5 million inAnnual Receipts$3.89$0.06$0.32$0.85$2.73$8.17$1.84$20.62$45.05$47.27237130Powerandcommunicationline and relatedstructures construction$33.5 million inAnnual Receipts$3.39$0.06$0.31$0.83$2.52$7.75$1.32$16.84$34.50$23.86237990zOther heavy andcivil engineeringconstruction$33.5 million inAnnual Receipts$2.66$0.06$0.30$0.83$2.48$7.76$0.99$18.72$40.53$42.3592811 National Security NA NA NANA NA NA NANA NA NA NANotes: . National Security is included in this table but does not have size standards.aNAICS codes 221111, 221112, 221113, 221119, 221121, 221122: A firm in these industries is defined as small by SBA if, including its affiliates, it isprimarily engaged in the generation, transmission, and/or distribution of electric energy for sale and its total electric output for the preceding fiscal year did notexceed 4 million megawatt hours.NA = Not available. SUSB did not report this data for disclosure or other reasons.Source: U.S. Census Bureau. 2009a. “Firm Size Data from the Statistics of U.S. Businesses: U.S. Detail Employment Sizes: 2009.”<http://www.census.gov/csd/susb/6-7 Annual entity compliance costs vary depending on the size of the diesel engines used at the affected establishment. Absent facility -specific information, we computed per-entity compliance costs based for three different cases based on representative establishments—Cases 1, 2, and 3 (see Table 6-4). Each representative establishment differs based on the size and number of diesel engines being used. Complia nce costs are calculated by summing the total annualized compliance costs for the relevant engi ne categories, dividing the sum by the total existing population of those engines, and multiplying the average engine cost by the number of engines assumed to be at th e establishment. Since NAICS 2211 and 622110 are fundamentally
different than other industries c onsidered in this analysis, we used different assumptions about what constitutes the representative establishment and report these assumptions separately.

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

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

 Case 3: The representative establishment for all indus tries uses two 50 to 100 hp engines with an average co mpliance cost of $68 per engine, resulting in a total compliance cost of $137 for this representative establishment.

EPA believes that small entities are most likel y to face costs similar to Case 2 (columns shaded in gray in Table 6-4) because most of the engines to be affected by this proposal in NAICS 335312, 333992, 211111, and 211112 are under 300 hp capacity, and most small entities in these industries will own engi nes of this size or smaller. This is corroborated by Figure 6-1
and 6-2 which shows the distribu tion of engine population and co mpliance costs by engine size for all industries. However, it is difficult to make a similar claim for NAICS 2211 and 622110 based on the existing distribution of engines in these industries. 6 As noted earlier in the RIA, only 20 percent of the existing distribution of e ngines is expected to be classified as nonemergency.

6 This claim also cannot be made for NAICS 92811: National Security. However, since most national security installations are owned by the federal government (e.g., military bases), EPA assumes these entities would not be considered small.6-8 For the sales test, we divided the representative establishment compliance costs reported in Table 6-4 by the representative receipts reporte d in Tables 6-2 and 6-3. This is known as the cost-to-receipt (i.e., sales) ra tio, or the “sales test.” The “sales test” is the impact
Table 6-4. Representative Establishment Cost s Used for Small Entity Analysis ($2008)

Case 1 Case 2 Case 3
NAICS 2211, 622110 (+750 hp

only) All Other NAICS (+750 hp

only) NAICS 2211, 622110 (50–750+ hp) All Other NAICS (50–300 hp) NAICS 2211, 622110 (50–100 hp only) All Other NAICS (50–100 hp only)
Total Annualized Costs ($) $62,068,406 $7,875,707 $304,817,985 $40,407,406 $9,093,118 $6,745,516
Engine Population 33,052 4,194 727,090 276,374 133,099 98,736
Average Engine Cost ($/engine) $1,878 $1,878 $419 $146 $68 $68

Assumed Engines Per Establishment 3 3 2 2 2 2

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

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

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

Electric Power Generation

(2211) Hospitals (622110) Crude Petroleum & NG Production (211111) Natural Gas Liquid Producers

(211112) National Security (92811) Hydro Power Units (335312) Irrigation Sets (335312) Welders (333992) >750 hp

600

‐ 750 hp

300

‐ 600 hp

175

‐ 300 hp

100

‐ 175 hp

50

‐ 100 hp6-10 Figure 6-2. Distribution of Compliance Co sts by Engine Size for All Industries

methodology EPA employs in analyzing small entity impacts as opposed to a “profits test,” in which annualized compliance costs are calculated as a share of profits.

This is because revenues or sales data are commonly available data for entities normally impacted by EPA regulations and profits data no rmally made available are often not the true profit earned by firms because of accounting an d tax considerations. Revenues as typically published are usually correct figures and are more reliably reported when compared to profit data. The use of a “sales test” for estimating small business impacts for a rulemaking such as this one is consistent with guidance offe red by EPA on compliance with SBREFA 7 and is consistent with guidance published by the U.S. SBA’s Office of Advocacy that suggests that cost as a

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

Electric Power Generation

(2211) Hospitals (622110) Crude Petroleum & NG Production (211111) Natural Gas Liquid Producers

(211112) National Security (92811) Hydro Power Units (335312) Irrigation Sets (335312) Welders (333992) >750 hp

600

‐ 750 hp

300

‐ 600 hp

175

‐ 300 hp

100

‐ 175 hp

50

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

If the cost-to-receipt ratio is less than 1%, th en we consider the fina l rule to not have a significant impact on the establishment company in question. We summarize the industries with cost-to-receipt ratios exceeding 1% below:

Primary Analysis:

 Case 2 : NAICS 2211

 Case 3 : No industries

Sensitivity Analysis (unlikely):

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

In the Case 2 primary analysis, only esta blishments in NAICS 2211 with receipts less than $100,000 per year have cost-t o-receipt ratios above 1%. These establishments represent less than 5 percent of affected small establishments. However, establishments earning this level of receipts are likely to be using smaller engines than those assumed in Case 2, such as 50 to 100 hp engines. The results of our Case 3 analysis demonstrate that these establishments are not significantly impacted when taking this engine size into account.

After considering the economic im pacts of this proposed rule on small entities, we certify
that this action will not have a significant economic impact on a substantial number of small
entities. This certification is ba sed on the economic impact of this proposal action to all affected
small entities across all industries affected. The percentage of sm all entities impacted by this proposal having annualized costs greater than 1 pe rcent of sales is less than 2 percent according to this analysis. We thus conc lude that there is no significant economic impact on a substantial number of small entities (SISNOSE) for this proposed rule.

Although the proposed rule would not have a significant economic impact on a
substantial number of small en tities, EPA nonetheless tried to reduce the impact of the rule on small entities. When developing the revised standards, EPA took sp ecial steps to ensure that the burdens imposed on small entities were minimal. EPA conducted several meetings with industry

8 U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Comply with the Regulatory Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003.6-12 trade associations to discuss regulatory opti ons and the corresponding burden on industry, such as recordkeeping and reporting. In addition, as mentioned earlier in this preamble, EPA proposes to reduce regulatory requirements for a variety of area sources affected under this RICE rule with amendments to the final RICE rules promulgated in 2010. We continue to be interested in the potential impacts of this proposed rule on small entities and welcome comments on issues related to such impacts.

6.3 Small Government Entities

The rule also covers sectors that include entities owned by small and large governments. However, given the uncertainty and data li mitations associated with identifying and appropriately classifying these entities, we computed a “revenue” test for a model small government, where the annualized compliance cost is a percentage of annual government revenues (U.S. Census, 2005a,b). The use of a “rev enue test” for estimating impacts to small governments for a rulemaking such as this one is consistent with gui dance offered by EPA on compliance with SBREFA, 9 and is consistent with guidan ce published by the US SBA’s Office of Advocacy. 10 For example, from the 2002 Census (in 2008 dollars), the average revenue for small governments (counties and municipalitie s) with populations fewer than 10,000 are $3 million per entity, and the average revenue for lo cal governments with populations fewer than 50,000 is $8 million per entity. For the smalle st group of local governments (<10,000 people),
the cost-to-revenue ratio would be 0.2% or less under each case. Fo r 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 regard ing the types of small business analysis that should be considered can be found at http://www.epa.gov/sbrefa/documents/rfafinalguidance06.pdf , pp. 24-25.
10 U.S. SBA, Office of Advocacy. A Guide for Government Agencies, How to Comply with the Regulatory Flexibility Act, Implementing the President’s Small Business Agenda and Executive Order 13272, May 2003.7-1 SECTION 7
HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS
Synopsis

Implementation of emissions controls required by the proposed CI RICE NESHAP reconsideration is expected to reduce emissi ons of hazardous air pollutants (HAP) and have ancillary co-benefits that would lo wer ambient concentrations of PM 2.5 and ozone. In this section, we quantify the monetized co-benefits for this ru le associated with reduc ing exposure to ambient fine particulate matter (PM 2.5 ) by reducing emissions of precursors. We estimate the total monetized co-benefits to be $770 million to $1.9 b illion at a 3% discount rate and $690 million to $1.7 billion at a 7% discount rate in 2013. All estimates are in 2010$. These estimates reflect
the monetized human health benefits of reduci ng cases of morbidity a nd premature mortality among populations exposed to PM 2.5 reduced by this rule. These estimates reflect EPA’s most current interpretation of the scientific literatu re. Higher or lower estimates of benefits are possible using other assumptions; examples of th is are provided in Figure 7-2. Data, resource, and methodological limitations prevented EPA from monetizing the bene fits from several important benefit categories, including be nefits from reducing exposure to HAP, carbon monoxide, and ozone, as well as visibility impairment. In addition to reducing emissions of PM precursors, this rule would reduce 1,000 tons of HAP and 14,000 tons of carbon monoxide each year.

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

This proposed reconsideration would reduce em issions of directly emitted particles and VOCs. Because these emissions are precursors to PM 2.5, reducing these emissions would also
reduce PM 2.5 formation, human exposure and the incidence of PM 2.5 -related health effects. Due to analytical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 -related benefits or provide estimates of the health be nefits associated with exposure to HAP, CO, or ozone. Instead, we used the “benefit-per-ton” approach to estimate these benefits. The methodology employed in this analys is is similar to the work de scribed in Fann, Fulcher, and Hubbell (2009), but represents an improvement th at EPA believes would provide more reliable
estimates of PM 2.5 -related health benefits for emissions re ductions 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 of premature mortality and premature morbidity) of reducing one ton of PM 2.5 from a specified source. EPA has us ed the benefit per-ton technique in several previous RIAs, including the recent SO 2 NAAQS RIA (U.S. EPA, 2010).7-2 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 associ ated with acute and chronic exposures. Table 7- 1 shows the quantified and unquantified benefits cap tured in those benefit-per-ton estimates, but
this table does not include entr ies for the unquantified health eff ects associated with exposure to HAP, CO, or ozone nor welfare effects such visib ility impairment that are described in section 7.2. It is important to emphasize that the list of unquantified benef it categories is not exhaustive, nor is quantification of each effect complete.7-3 Table 7-1: Human Health Effects of PM 2.5

Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information

(refers to CSAPR RIA) Improved Human Health

Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30)   Section 5.4

Infant mortality (age <1)   Section 5.4

Reduced incidence of morbidity from exposure to PM 2.5 Non-fatal heart attacks (age > 18)   Section 5.4 Hospital admissions—respiratory (all ages)   Section 5.4 Hospital admissions—cardiovascular (age >20)   Section 5.4 Emergency room visits for asthma (all ages)   Section 5.4 Acute bronchitis (age 8-12)   Section 5.4 Lower respiratory symptoms (age 7-14)   Section 5.4 Upper respiratory symptoms (asthmatics age 9-11)   Section 5.4 Asthma exacerbation (asthmatics age 6- 18)   Section 5.4 Lost work days (age 18-65)   Section 5.4 Minor restricted-activity days (age 18-65)   Section 5.4 Chronic Bronchitis (age >26)   Section 5.4 Emergency room visits for cardiovascular effects (all ages) -- -- Section 5.4 Strokes and cerebrovascular disease (age 50-79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA 2
Other respiratory effects (e.g., pulmonaryfunction, non-asthma ER visits, nonbronchitis chronic diseases, other ages and populations) -- -- PM ISA 2

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

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

1 We assess these benefits qualitatively due to tim e and resource limitations for this analysis.

2 We assess these benefits qualitatively because we do not have sufficient co nfidence in available data or methods.
3 We assess these benefits qualitatively because current evid ence is only suggestive of ca usality or there are other significant concerns over the strength of the association.

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the benefits estimates
utilize the concentration -response functions as reported in the epidemiology literature, as well as the 12 functions obtained in EPA’s expert elic itation study as a sens itivity analysis.7-4  One estimate is based on the concentrati on-response (C-R) function developed from the extended analysis of American Cancer Society (ACS) cohort, as reported in Pope et al. (2002), a study that EPA has previously used to generate its primary benefits estimate. When calculating the estimate, EPA applied the effect coefficient as reported in the study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent (2006-2009) Office of Air and Radiation RIAs.

 One estimate is based on the C-R function developed from the extended analysis of the Harvard Six Cities cohort, as reported by Laden et al (2006). This study, published after the completion of the Staff Paper for the 2006 PM 2.5 NAAQS, has
been used as an alternative estimate in the PM 2.5 NAAQS RIA and PM 2.5 benefits estimates in RIAs completed since the PM 2.5 NAAQS. When calculating the estimate, EPA applied the effect coeffici ent as reported in the study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent (2006-2009) RIAs.

 Twelve estimates are based on the C-R func tions from EPA’s e xpert elicitation study (Roman et al., 2008) on the PM 2.5 -mortality relationship and interpreted for benefits analysis in EPA’s final RIA for the PM 2.5 NAAQS. For that study, twelve experts (labeled A through L) provided independent estimates of the PM 2.5 -mortality concentration-response function. EPA pract ice has been to develop independent
estimates of PM 2.5 -mortality estimates corresponding to the concentration-response function provided by each of the twelve expe rts, to better characterize the degree of variability in the expert responses.

The effect coefficients are drawn from epidemiology studies examining two large population cohorts: the American Cancer Society cohort (Pope et al., 2002) and the Harvard Six Cities cohort (Laden et al., 2006). 1 These are logical choices for anchor points in our presentation because, while both studies are well designed and peer reviewed, there are strengths and weaknesses inherent in each, which we beli eve argues for using both studies to generate benefits estimates. Previously, EPA had cal culated 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 relati onship between exposure to PM 2.5 and premature mortality (Roman

1 These two studies specify multi-pollutant models that control for SO 2 , among other co-pollutants.7-5 et al., 2008). 2 Within this assessment, we include the benefits estimates derived from the concentration-response function provided by each of the twelve experts to better characterize the uncertainty in the concentration-response functio n for mortality and the degree of variability in the expert responses. Because the experts used these cohor t studies to inform their concentration-response functions, be nefits estimates using these f unctions generally fall between results using these epidemiology studies (see Figu re 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 genera l methodology for creating the benefit-per-ton estimates used in this analys is should consult the draft Tech nical Support Document (TSD) on estimating the benefits per ton of reducing PM 2.5 and its precursors in the “Other Non-EGU Point” category (U.S. EPA, 2012). 3 The primary difference between the estimates used in this analysis and the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality modeling data utilized. In this analysis, we apply these na tional benefit-per-ton estimates calculated for this category for directly emitte d particles and multiply them by the corresponding
emission reductions.

These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premat ure mortality because the scientific evidence is not yet sufficient to allow differentiation of effects estimates by pa rticle type. Directly emitted particles are the primary PM 2.5 precursors affected by this rule. Even though we assume that all fine particles have equivalent health effects, the benefit-pe r-ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The sector-specific modeling does not provide estimates of the PM 2.5 -related benefits associated with reducing VOC emissions, but these unquantified benefits are generally small compared to
other PM 2.5 precursors (U.S. EPA, 2012).

The benefit-per-ton coefficients in this analys is were derived using modified versions of the health impact functions used in the PM NAAQS Regulatory Impact Analysis (U.S. EPA, 2006). Specifically, this analysis uses the met hod first applied in the Portland Cement NESHAP

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 poin t source category. If the affected stationary engines are more rural than the average of the non-EGU sources modeled, then it is possible that the benefits may be somewhat less than we have estimated here. The TSD provides the geographic distribution of the air quality changes associated with this sector. It is important to emphasize that this modeling represents the best available information on the air quality impact on a per ton basis for these sources.7-6 RIA (U.S. EPA, 2009a), which applied the functi ons directly from the epidemiology studies without an adjustment for an assumed threshol d. Removing the threshold assumption is a key difference between the method used in this analys is of PM benefits and the methods used in RIAs prior to Portland Cement proposal, and we now calculate incremental benefits down to the
lowest modeled PM 2.5 air quality levels. 4

Based on our review of the current body of sc ientific literature, EPA now estimates PMrelated mortality without applying an a ssumed concentration threshold. EPA’s Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was reviewed by EPA’s Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b),
concluded that the scientific literature consis tently finds that a no-th reshold log-linear model most adequately portrays the PM-mortality concentration-response relationship while recognizing potential uncertainty about the exact shape of the c oncentration-response function.

Consistent with this finding, we have c onformed the previous threshold sensitivity analysis to the current state of the PM scienc e by incorporating a “Lowest Measured Level” (LML) assessment, which is a method EPA has em ployed in several recent RIAs including the Cross-State Air Pollution Rule (U .S. EPA, 2011b). This information allows readers to determine the portion of population exposed to annual mean PM 2.5 levels at or above the LML of each study; in general, our co nfidence in the estimated PM mortal ity decreases as we consider air quality levels further below the LML in major cohort studies that estim ate PM-related mortality. While an LML assessment provides some insight into the level of uncertainty in the estimated PM mortality benefits, EPA does not view the LM L as a threshold and continues to quantify PMrelated mortality impacts using a full range of mode led air quality concentra tions. It is important to emphasize that we have high confidence in PM 2.5 -related effects down to the lowest LML of the major cohort studies, which is 5.8 μg/m 3 . Just because we have greater confidence in the benefits above the LML, this does not mean th at we have no confidence that benefits occur below the LML. For a summary of the scientif ic review statements regarding the lack of a
threshold in the PM 2.5 -mortality relationship, see the T echnical Support Document (TSD)
entitled Summary of Expert Opinions on the Existe nce of a Threshold in the ConcentrationResponse Function for PM 2.5 -related Mortality (U.S. EPA, 2010b).

For this analysis, policy-specific air quality data is not 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 ru le’s emission reductions at each PM 2.5 level. However, we believe

4 Additional updates since the Cement RIA include a revised VSL and updated baseline incidence rates.7-7 that it is still important to characterize the distri bution of exposure to base line air quality levels. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionmen t modeling used to calculate the benefit-per-ton estimates for this sector. It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline inciden ce rates population, and change in air quality. In other words, the per centage of the population exposed to air pollution below the LML is not the same as the percenta ge of the population experiencing health impacts as a result of a specific emission reduction polic y. The most important aspect, which we are unable to quantify for rules without rule-specifi c air quality modeling, is the shift in exposure associated with this specific rule. Therefor e, caution is warranted when interpreting the LML
assessment for this rule. The results of this analysis are provided in Section 7.3.

As is the nature of RIAs, the assumptions and methods used to estimate air quality benefits evolve over time to reflect the Agency’s most current interpretation of the scientific and economic literature. For a period of time ( 2004-2008), the Office of Air and Radiation (OAR) valued mortality risk reductions using a value of statistical life (VSL) estimate derived from a limited analysis of some of the available studi es. OAR arrived at a VSL using a range of $1 million to $10 million (2000$) consistent with two meta-analyses of the wage-risk literature. The $1 million value represented the lower end of the interquartile range from the Mrozek and Taylor (2002) meta-analysis of 33 studies. Th e $10 million value represented the upper end of the interquartile range from the Viscusi and Aldy (2003) meta-ana lysis of 43 studies. The mean estimate of $5.5 million (2000$) 5 was also consistent with the mean VSL of $5.4 million estimated in the Kochi et al. (2006) meta-analysi s. However, the Agency neither changed its official guidance on the use of VSL in rulema kings nor subjected the interim estimate to a scientific peer-review process through the Scie nce Advisory Board (SAB ) or other peer-review

group.

During this time, the Agency continued work to update its guidance on valuing mortality risk reductions, including commissioning a repo rt from meta-analytic experts to evaluate methodological questions raised by EPA and the SAB on combining estimates from the various data sources. In addition, the Agency consulte d several times with the Science Advisory Board Environmental Economics Advisory Committee (SAB-EEAC) on the i ssue. With input from the meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, appropriate meta-analytic tech niques to combine estimates from unique data sources and

5 After adjusting the VSL for a different currency year (2010$) and to account for income growth to 2 015 of the $5.5 million value, the VSL is $8.0 million.7-8 different studies, including those using differe nt methodologies (i.e., wage-risk and stated preference) (U.S. EPA-SAB, 2007).

Until updated guidance is availabl e, the Agency determined that a single, peer-reviewed estimate applied consistently best reflects the SAB-EEAC advice it has re ceived. Therefore, the Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparing Economic Analyses (U.S. EPA, 2000) 6 while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates
derived from 26 labor market and contingent valuation st udies published between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$). 7 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made significant progre ss in responding to the SAB-EEAC’ s specific recommendations.

In implementing these rules, emission cont rols may lead to reductions in ambient PM 2.5 below the National Ambient Air Quality Standard s (NAAQS) for PM in some areas and assist other areas with attaining th e PM NAAQS. Because the PM NAAQS RIAs also calculate PM benefits, there are important differences worth no ting in the design and anal ytical objectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air quality standard nationwide based on an array of emission control st rategies for different sources. In short, NAAQS RIAs hypothesize, but do not pred ict, the control strate gies that States may choose to enact when implementing a NAAQS. The setting of a NAAQS doe s not directly result in costs or benefits, and as such, the NAAQS RI As are merely illustrative and are not intended to be added to the costs and benefits of other regula tions that result in speci fic costs of control and emission reductions. However, some costs and be nefits estimated in this RIA account for the same air quality improvements as estimated in the illustrative PM 2.5 NAAQS RIA.

By contrast, the emission reductions for impl ementation rules are from a specific class of well-characterized sources. In general, EPA is more confident in the magnitude and location of the emission reductions for implementation rule s rather than illustrative NAAQS analyses.
Emission reductions achieved unde r these and other promulgate d rules will ultimately be reflected in the baseline of future NAAQS an alyses, which would reduce the incremental costs

6 In revised Economic Guidelines (U.S. EPA, 2010c), EPA retained the VSL endorsed by the SAB with the understanding that further updates to the mortality risk va luation guidance would be forthcoming in the near future. Therefore, this report does not represent final agency policy.
7 This value is $4.8 million in 1990$. In this analysis, we adjust the VSL to account for a different currency year ($2010) and to account for inco me growth to 2015. After applying these ad justments to the $6.3 million value, the VSL is $9.2 million.7-9 and benefits associated with attaining th e NAAQS. EPA remains forward looking towards the next iteration of the 5-year re view cycle for the NAAQS, and as a result does not issue updated RIAs for existing NAAQS that retroactively update the baseline for NAAQS implementation. For more information on the relationship between the NAAQS and rules such as analyzed here, please see Section 1.2.4 of the SO 2 NAAQS RIA (U.S. EPA, 2010a).7-10 Figure 7.1 illustrates the relativ e breakdown of the monetized PM 2.5 health benefits.

Figure 7-1: Breakdown of Monetized PM 2.5 Health Benefits using Mortality Function from Pope et al. (2002)* *This pie chart breakdown is illustrative, using the results based on Pope et al. (2002) as an example. Using the Laden et al. (2006) function for premat ure mortality, the percentage of total monetized benefits due to adult mortality would be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be similar if a 7% discount rate was used.

Table 7-2 provides a general summary of th e monetized PM-related health benefits by precursor, including the emission re ductions and benefit-per-ton es timates at discount rates of
3% and 7%. 8 Table 7-3 provides a summary of the reducti ons in health incidences as a result of the pollution reductions. In Table 7-4, we provide the benefits using our anchor points of Pope
et al. and Laden et al. as well as the results fr om the expert elicitation on PM mortality. Figure 7-2 provides a visual repres entation 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 speci fic analysis year (i.e., 2013), and mo st of the PM benefits occur within that year with two excep tions: acute myocardial infarctions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow-up medical co sts and lost wages. For premature mort ality, we assume that there is a “cessation” lag between PM exposures and the total reali zation of changes in health effects. Although the structure of the lag is uncertain, EPA follows the advice of the SAB-HES to assume a segmented lag structure characterized by 30% of mortality reductions in the first y ear, 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 la g 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 prematur e mortalities that occur after the analysis year. As such, the monetized benefits using a 7% discount rate are only approximately 10% less than the monetized benefits using a 3% discount rate. Adult Mortality ‐ Pope et al. 93% Chronic Bronchitis 4%

AMI 2% Acute Respiratory Symptoms 0.5%

Infant Mortality 0.4%

Work Loss Days 0.2%

Hospital Admissions, Cardio 0.2% Hospital Admissions, Resp 0.04% Asthma Exacerbation 0.01%
Acute Bronchitis 0.01% Upper Resp Symp 0.00% Lower Resp Symp 0.00%
ER Visits, Resp 0.00% Other 1%7-11 concentration-response functions supplied by ex perts. Figure 7-3 shows a breakdown of monetized benefits by engine size.

The benefit-per-ton estimates shown in this RIA are different than the benefit-per-ton
estimates cited in the 2010 final SI RICE RIA for two reasons. First, these estimates are based on updated air quality modeling, which results in s lightly higher benefits per ton for other nonEGU point sources than the previous modeling. Second, these estimates have been inflated to 2010$. Third, the new air quality modeling did not provide estimates associated with reducing
VOCs.

Table 7-2: General Summary of Monetized PM 2.5 -Related Health Co -Benefits Estimates for the Proposed CI RICE NESHAP Reconsideration (millions of 2010$) *

Pollutant Emissions Reductions (tons) Benefit per ton (Pope,

3%) Benefit per ton (Laden,

3%) Benefit per ton (Pope,

7%) Benefit per ton (Laden,

7%) Total Monetized Benefits (millions of 2010$ at 3%) Total Monetized Benefits (millions of 2010$ at 7%)

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

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

* All estimates are for the analysis year (2013), and are rounded to two significant figures so numbers may not sum across columns. It is important to note that the monetized benefits do not include reduced health effects from direct exposure to NO 2 , ozone exposure, ecosystem effects, or visibility im pairment. All fine 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 th is 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-Benefits for Proposed CI RICE NESHAP Reconsideration*

Avoided Premature Mortality Pope et al. 85

Laden et al. 220 Avoided Morbidity

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

Acute Bronchitis 130 Lower Respiratory 1,700 Upper Respiratory 1,300 Minor Restricted Activity Days 68,000 Work Loss Days 12,000 Asthma Exacerbation 2,800 Acute Myocardial Infarction 94 * All estimates are for the analysis year (2013) and are rounded to whole numbers with two significant figures. All fine particles are assumed to have equivalent health effect s because the scientific eviden ce is not yet sufficient to allow differentiation of effects estimate s by particle type. Confidence interval s are unavailable for this analysis because of the benefit-per-ton methodology.7-13 Table 7-4: All PM 2.5 Co-Benefits Estimates for the Proposed CI RICE NESHAP Reconsideration at discount rates of 3% and 7% in 2013 (in millions of 2010$)*

3% 7% Benefit-per-ton Coefficients Deri ved from Epidemiology Literature Pope et al. $770 $690 Laden et al. $1,900 $1,700 Benefit-per-ton Coefficients D erived from Expert Elicitation Expert A $2,000 $1,800 Expert B $1,500 $1,400 Expert C $1,500 $1,400 Expert D $1,100 $970 Expert E $2,500 $2,200 Expert F $1,400 $1,200 Expert G $920 $820 Expert H $1,200 $1,000 Expert I $1,500 $1,400 Expert J $1,200 $1,100 Expert K $290 $260 Expert L $1,000 $910

* All estimates are rounded to two signifi cant figures. The benefits estimates fr om the Expert Elicitation are provided as a reasonable characterization of the uncertainty in th e mortality estimates associated with the concentrationresponse function. Confidence interval s are unavailable for this analysis becau se of the benefit-per-ton methodology7-14 Figure 7-2: Total Monetized PM 2.5 Co-Benefits of Proposed CI RICE NESHAP Reconsideration in 2013 *This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA’s expert elicitation on PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration-response function provided in those studies. $0 $500 $1,000 $1,500 $2,000 $2,500

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

PM 2.5 mortality benefits estimates derived from 2 epidemiology functions and 12 expert functions 3% DR
7% DR7-15 Figure 7-3: Breakdown of Total Monetized PM 2.5 Co-Benefits of Proposed CI RICE NESHAP Reconsideration by Engine Size

7.2 Unquantified Benefits

The monetized benefits estimated in this RIA onl y reflect a subset of benefits attributable
to the health effect reductions as sociated with ambient fine part icles. Data, time, and resource limitations prevented EPA from quantifying the impacts to, or monetizing the benefits from several important benefit categorie s, including benefits from reducing exposure to HAP, CO, and ozone exposure, as well as ecosyst em effects, and visibility impa irment. 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 Toxi cs Assessment (NATA) predicts that most Americans are exposed to ambient concentrations of air toxics at levels that have the potential to cause adverse health effects (U.S. EPA, 2011c). 9 The levels of air toxics to which people are exposed vary depending on where people live and wo rk and the kinds of activities in which they engage. In order to identify and prioritize air toxics, emission s ource types and locations that are

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

Major >500 HP 6%

Area <600 HP 36% Area >600 HP 33%7-16 of greatest potential concern, U.S. EPA conducts the NATA. 10 The most recent NATA was conducted for calendar year 2005 and was released in March 2011. NATA includes four steps:

1) Compiling a national emissions inventory of air toxics emissions from outdoor sources

2) Estimating ambient and exposure concentratio ns of air toxics across the United States

3) Estimating population exposur es 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 a bout 5% of census tracts nationwide have increased cancer risks greater than 100 in a milli on. The average national cancer risk is about 50 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldehyde and benzene. 11 Secondary formation (e.g., formaldehyde forming from other emitted pollutants) was the largest contributor to cancer risks, while stationary, mobile and background sources contribute almost equal portions of the remaining cancer risk.

Noncancer health effects can result from chronic, 12 subchronic, 13 or acute 14 inhalation exposures to air toxics, and incl ude neurological, cardiovascular, liver, kidney, and respiratory
effects as well as effects on the immune and reproductive systems. According to the 2005 NATA, about three-fourths of the U.S. popul ation 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 acro lein is the primary driver for noncancer respiratory risk.

10 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertain ties 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 maki ng process. U.S. EPA. (2011) 2005 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/
11 Details about the overall confidence of certainty ranking of the individual pieces of NATA assessments including both quantitative (e.g., model-to-monitor ratios) and qua litative (e.g., quality of data, review of emission inventories) judgments can be found at h ttp://www.epa.gov/ttn/atw/nata/roy/page16.html.
12 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database (http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal species).
13 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species).
14 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.7-17 Figure 7-4 and Figure 7-5 depict the estimated census tract-level carcinogenic risk and noncancer respiratory hazard from the assessment. It is important to note that large reductions in HAP emissions may not necessarily translate into significant reductions in health risk because toxicity varies by pollutant, and exposures ma y or may not exceed levels of concern. For example, acetaldehyde mass emissions are more than double acrolein emissions on a national basis, according to EPA’s 2005 National Emissions Inventory (NEI). However, the Integrated Risk Information System (IRIS) reference concentr ation (RfC) for acrolein is considerably lower than that for acetaldehyde, suggesting that acro lein could be potential ly more toxic than acetaldehyde. Thus, it is important to account for the toxicity and exposure, as well as the mass of the targeted emissions.

Figure 7-4 Estimated Chronic Census Tract Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA)7-18 Figure 7-5 Estimated Chronic Census Trac t Noncancer (Respiratory) Risk from HAP exposure from outdoor sources (2005 NATA)

Due to methodology and time limitations under the court-ordered schedule, we were
unable to estimate the benefits associated with the hazardous air pollutants that would be reduced as a result of these rules. In a few previous anal yses of the benefits of reductions in HAP, EPA has quantified the benefits of poten tial reductions in the incidences of cancer and non-cancer risk (e.g., U.S. EPA, 1995). In those analyses, EPA relied on unit risk f actors (URF) developed through risk assessment procedures. 15 These URFs are designed to be conservative, and as such, are more likely to represent the hi gh end of the distribution of risk rather than a best or most likely estimate of risk. As the purpose of a benefit analysis is to describe the benefits most likely
to occur from a reduction in pollution, use of high-end, conser vative risk estimates would overestimate the benefits of the regulation. While we used high-end risk estimates in past analyses, advice from the EPA’s Science Adviso ry Board (SAB) recommended that we avoid

15 The unit risk factor is a quantitative estimate of the ca rcinogenic 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 analyses (U.S. EPA-SAB, 2002). Since this time, EPA has continued to develop better methods for an alyzing the benefits of reductions in HAP.

As part of the second prospective analysis of the benefits and costs of the Clean Air Act (U.S. EPA, 2011a), EPA conducted a case study analys is of the health eff ects associated with reducing exposure to benzene in Houston from implementation of the Clean Air Act (IEc, 2009). While reviewing the draft report, EPA’s Adviso ry Council on Clean Air Compliance Analysis concluded that “the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air polluta nts (HAPs) are daunting...due to a lack of exposure-response functions, uncertainties in em issions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods ” (U.S. EPA-SAB, 2008).

In 2009, EPA convened a workshop to address th e inherent complexities, limitations, and uncertainties in current methods to quantify the benefits of reducing HAP. Recommendations from this workshop included identifying rese arch priorities, focu sing on susceptible and vulnerable populations, and improving dose-respon se relationships (Gwinn et al., 2011).

In summary, monetization of the benefits of reductions in cancer incidences requires several important inputs, includi ng central estimates of cancer risk s, estimates of exposure to carcinogenic HAP, and estimates of the value of an avoided case of cance r (fatal and non-fatal). Due to methodology and time limitations under the cour t-ordered schedule, we did not attempt to
monetize the health benefits of reductions in HAP in this analysis. Instead, we provide a qualitative analysis of the heal th effects associated with the HAP anticipated to be reduced by these rules.EPA remains committed to improving methods for estimating HAP benefits by continuing to explore additional concepts of benefits, including changes in the distribution of
risk.

Although numerous HAP may be emitted from CI RICE, a few HAP account for over 90% of
the total mass of HAP emissions emitted. These HAP are formaldehyde (72%), acetaldehyde (8%), acrolein (7%), methanol (3%), and benzene (3%). Although we do not have estimates of emission reductions for each HAP, this rule for existing CI engines is anticipated to reduce 1,000 tons of HAP each year. Below we describe the health effects associated with the top 5 HAP by mass emitted from
CI RICE.7-20 Formaldehyde

Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on evidence in humans and in rats, mice, hamsters, and monkeys. 16 Substantial additional research
since that time informs current scientific understanding of the health effect s associated with exposure to formaldehyde. These include recently published research conducted by the National Cancer Institute (NCI) which found an incr eased risk of nasopharyngeal cancer and lymphohematopoietic malignancies such as leukemia among workers exposed to formaldehyde. 17,18 In an analysis of the lymphohematopoi etic cancer mortality from an extended follow-up of these workers, NCI confirmed an a ssociation between lymph ohematopoietic cancer risk and peak formaldehyde exposures. 19 A recent NIOSH study of garment workers also found
increased risk of death due to leukem ia among workers exposed to formaldehyde. 20 Extended follow-up of a cohort of British chemical work ers did not find evidence of an increase in nasopharyngeal or lymphohematopoi etic cancers, but a continuing st atistically significant excess in lung cancers was reported. 21

In the past 15 years there has been substa ntial research on the inhalation dosimetry for formaldehyde in rodents and primates by the Ch emical Industry Institute of Toxicology (CIIT,
now renamed the Hamner Institutes for Health Scie nces), with a focus on use of rodent data for refinement of the quantitative can cer dose-response assessment. 22 , 23 , 24 CIIT’s risk assessment of

16 U.S. EPA. 1987. Assessment of Health Risks to Garment Workers and Certain Home Residents from Exposure to Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA-HQ-OAR-2010-0162.
17 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615- 1623. Docket EPA-HQ-OAR-2010-0162.
18 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 20 04. Mortality from solid cancers amongworkers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130. Docket EPA-HQOAR-2010-0162.
19 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Ha yes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National Cancer Institute cohort. J. National Cancer Inst . 101: 751-761. Docket EPA-HQ-OAR-2010-0162.
20 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers e xposed to formaldehyde: an update. Occup. Environ. Med. 61: 193-200. Docket EPA-HQ-OAR-2010-0162.
21 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. Docket EPA-HQ-OAR-2010-0162.
22 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, and FJ Miller. 2003. Biologically motivated computational modeling of formaldehyde carcinogenicity in the F344 rat. Tox Sci 75: 432-447. Docket EPA-HQ-OAR-2010-0162.
23 Conolly, RB, JS Kimbell, D Janszen, PM Schlosser, D Kalisak, J Preston, an d FJ Miller. 2004. Human respiratory tract cancer risks of inhaled formaldehyde: Dose-response predictions derived from biologically-motivatedcomputational modeling of a combined rodent and human dataset. Tox Sci 82: 279-296. Docket EPA-HQ-OAR2010-0162.7-21 formaldehyde incorporated mechanistic and dosi metric information on formaldehyde. These data were modeled using a biologically-motivated two- stage clonal growth model for cancer and also a point of departure based on a Benchmark Dose approach. However, it should be noted that recent research published by EPA indicates that when two-stage modeling assumptions are varied, resulting dose-response estimates can vary by several orders of magnitude. 25 , 26 , 27 , 28 These findings are not supportive of inte rpreting the CIIT model results as providing a conservative (health protective) estimate of human risk. 29 EPA research also examined the contribution of the two-stage modeling for formaldehyde towards charac terizing the relative weights of key events in the mode-of-action of a carcinogen. For exampl e, the model-based inference in the published CIIT study that formaldehyde’s direct mutageni c action is not relevant to the compound’s tumorigenicity was found not to hold unde r variations of modeling assumptions. 30

Based on the developments of the last d ecade, in 2004, the working group of the IARC concluded that formaldehyde is carcinogenic to humans (Group 1), on the basis of sufficient evidence in humans and sufficient evidence in expe rimental animals - a higher classification than previous IARC evaluations. Afte r reviewing the currently available epidemiological evidence, the IARC (2006) characterized the human evid ence for formaldehyde carcinogenicity as “sufficient,” based upon the data on nasophar yngeal cancers; the epid emiologic evidence on leukemia was characterized as “strong.” 31

Formaldehyde exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of the eyes), nose and throat. Effects from repeated

24 Chemical Industry Institute of Toxicology (CIIT).1999 . Formaldehyde: Hazard characterization and dose-response assessment for carcinogenicity by the route of inhalation. CIIT, September 28, 1999. Research Triangle Park, NC. Docket EPA-HQ-OAR-2010-0162.
25 U.S. EPA. Analysis of the Sensitivity and Uncertainty in 2-Stage Clonal Growth Models for Formaldehyde with Relevance to Other Biologically-Based Dose Response (BBDR) Models. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-08/103, 2008. Docket EPA-HQ-OAR-2010-0162.
26 Subramaniam, R; Chen, C; Crump, K; .et .al. (2008) Uncertainties in biologically-based modeling of formaldehyde-induced cancer risk: identification of ke y issues. Risk Anal 28(4):907-923. Docket EPA-HQOAR-2010-0162.
27 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. Docket EPA-HQ-OAR-2010-0162.
28 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.
29 Crump, K; Chen, C; Fox, J; .et .al. (2008) Sensitivity analysis of biologically motivated model for formaldehydeinduced respiratory cancer in humans. Ann Occup Hyg 52:481-495. Docket EPA-HQ-OAR-2010-0162.
30 Subramaniam RP; Crump KS; Van Landingham C; et. al. (2007) Uncertainties in the CIIT model for formaldehyde-induced carcinogenicity in the rat: A limited sensitivity analysis–I. Risk Anal, 27: 1237–1254. Docket EPA-HQ-OAR-2010-0162.
31 International Agency for Research on Cancer (2006) Formaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2- ol. Monographs Volume 88. World Health Organization, Lyon, France. Docket EPA-HQ-OAR-2010-0162.7-22 exposure in humans include resp iratory tract irritation, chronic bronchitis and na sal epithelial lesions such as metaplasia and loss of cilia. Animal studies suggest that formaldehyde may also cause airway inflammation – including eosinophil infi ltration into the airways. There are several studies that suggest that formal dehyde may increase the risk of asthma – particularly in the

young. 32 , 33

The above-mentioned rodent and human studies , as well as mechanistic information and their analyses, were evaluated in EPA’s recent Draft Toxicological Review of Formaldehyde – Inhalation Assessment through the Integrated Risk Information System (IRIS) program. This
draft IRIS assessment was releas ed in June 2010 for public review and comment and external peer review by the National Research Council (NRC) . The NRC released their review report in April 2011 ( http://www.nap.edu/cata log.php?record_id=13142 ). The EPA is currently revising the draft assessment in response to this review.

Acetaldehyde

Acetaldehyde is classified in EPA’s IRIS da tabase as a probable human carcinogen, based on nasal tumors in rats, and is considered toxi c 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 Servi ces (DHHS) in the 11 th Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC. 35,36 The primary noncancer effects of exposure to acetaldehyde vapors include irrita tion of the eyes, skin, and respiratory tract. 37

32 Agency for Toxic Substances and Disease Registry (A TSDR). 1999. Toxicological profile for Formaldehyde. Atlanta, GA: U.S. Department of Health an d Human Services, Pub lic 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). 19 91. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.
35 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183.
36 International Agency for Research on Cancer (IARC). 1999. Re-evaluation of some organic chemicals, hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, Vol 71. Lyon, France.
37 U.S. Environmental Protection Agency (U.S. EPA). 19 91. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm.7-23 Acrolein

EPA determined in 2003 that the human carci nogenic potential of acr olein could not be
determined because the available data were in adequate. No information was available on the carcinogenic effects of acrolein in humans and th e animal data provided inadequate evidence of carcinogenicity. 38 The IARC determined in 1995 that acro lein was not classifiable as to its carcinogenicity in humans. 39

Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure resulting in upper respiratory tr act irritation, mucus hypersecreti on and congestion. The intense irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who suffer intolerable eye and nasal mucosal sens ory reactions within minutes of exposure. 40 These data and additional studies regarding acute effects of human exposure to acrolein are
summarized in EPA’s 2003 IRIS Huma n 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 symptoms. 42 Lesions to the lungs a nd upper respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein. 43 Acute exposure effects in animal studies report bronchial hyper-responsiveness. 44 In a recent study, the acute respiratory irrita nt effects of exposure to 1.1 ppm acrolein were more pronounced in mice with allergic airway disease by comparison to non-diseased mice wh ich 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 Environm ental Assessment, Washington, DC. This material is available at http://www.epa.g ov/iris/toxreviews/0364tr.pdf.
39 International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals, World Health Organization, Lyon, France.
40 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein. EPA/635/R-03/003. p. 10. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
41 U.S. Environmental Protection Agency (U.S. EPA). 2003. In tegrated Risk Information System File of Acrolein. 2003. Research and Development, National Center for Environmental Assessm ent, Washington, DC. EPA/635/R-03/003. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
42 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. p. 11. This material is available at http://www.epa.gov/iris/toxreviews/0364tr.pdf.
43 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/to xreviews/0364tr.pdf.
44 U.S. Environmental Protection Agency (U.S. EPA). 2003. Integrated Risk Information System File of Acrolein.Research and Development, National Center for Environmental Assessment, Washington, DC. EPA/635/R03/003. This material is available at http://www.epa.gov/iris/to xreviews/0364tr.pdf.7-24 respiratory rate. 45 Based on these animal data and demons tration of similar effects in humans (i.e., reduction in respiratory ra te), individuals with compro mised respiratory function (e.g., emphysema, asthma) are expected to be at incr eased risk of developi ng 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 exposur e is associated with additional health effects, including genetic changes in both humans and animals and increase d proliferation of bone marrow
cells in mice. 46,47,48 EPA states in its IRIS database that data indicate a causal relationship between benzene exposure and acute lymphocytic leukemia and suggest a relationship between benzene exposure and chronic non-lymphocytic leukemia a nd chronic lymphocytic leukemia. The IARC
has determined that benzene is a human carcin ogen and the DHHS has characterized benzene as a known human carcinogen. 49,50 A number of adverse noncancer health effects including blood disorders, such as preleukemia and aplastic anemia, have also been associated with long-term exposure to benzene. 51,52

45 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immedi ate sensory nerve-mediated respiratory responses to irritants in healthy and allergic airway-diseased mice. J Appl Physiol 94(4):1563-1571.
46 U.S. Environmental Protection Agency (U.S. EPA). 2000. Integrated Risk Information System File for Benzene. Research and Development, National Center for Environm ental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0276.htm.
47 International Agency for Research on Cancer, IARC monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, International Agen cy for Research on Cancer, World Health Organization, Lyon, France, p. 345-389, 1982.
48 Irons, R.D.; Stillman, W.S.; Colagiova nni, D.B.; Henry, V.A. (1992) Synergis tic 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, So me industrial chemicals an d dyestuffs, World Health Organization, Lyon, France.
50 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183.
51 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197.
52 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554.7-25 Methanol

Exposure of humans to methanol by inhalation or ingestion may result in central nervous system depression and degenerative changes in the brain and visual system s. After inhaled or ingested, methanol is converted to formate, a hi ghly 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 de velopmental toxicity in rats and mice, and reproductive and developmental toxicity in monkeys. A number of studies have reported adverse effects in the offspring of rats and mice expos ed to methanol by inha lation including reduced weight of brain pituitary gla nd, thymus, thyroid, reduced overall fetal body weight and increased
incidence of extra ri bs and cleft palate. 54,55,56 Methanol inhalation studies using rhesus monkeys have reported a decrease in th e length of pregnancy, and limited evidence of impaired learning ability in offspring. 57,58,59,60 EPA has not classified methanol w ith 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 hea lth effects of those compounds can be found in
EPA’s IRIS database. 61

53 Rowe, VK and McCollister, SB. 1981. Alcohols. In: Patty's Industrial Hygiene and Toxicology, 3rd ed. Vol. 2C, GD Clayton, FE Clayton, Eds. John Wiley & Sons, New York, pp. 4528-4541.
54 New Energy Development Organization (NEDO). 1987. Toxico logical research of methan ol as a fuel for power station: summary report on tests with monkeys, rats and mice. Tokyo, Japan.
55 Nelson, BK; Brightwell, WS; MacKenzie, DR; Khan, A; Burg, JR; Weigel, WW; Goad, PT. 1985. Teratological assessment of methanol and ethanol at high inhalation levels in rats. Toxicol Sci, 5: 727-736.
56 Rogers, JM; Barbee, BD; Re hnberg, BF. 1993. Critical periods of sensitivity for the developmental toxicity of inhaled methanol. Teratology, 47: 395.
57 Burbacher, T; Grant, K; Shen, D; Damian, D; E llis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part II: developmental effects in infants exposed prenatally to methanol. Health Effects Institute. Cambridge, MA.
58 Burbacher, T; Shen, D; Grant, K; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 1999. Reproductive and offspring developmental effects following maternal inhalation exposure to methanol in nonhuman primates Part I: methanol disposition and reproductive toxicity in adu lt females. Health Effects Institute. Cambridge, MA.
59 Burbacher, TM; Grant, KS; Sh en, DD; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (Macaca fascic ularis): reproductive performance and birth outcome. Neurotoxicol Teratol, 26: 639-650.
60 Burbacher, TM; Shen, DD; Lalovic, B; Grant, KS; Sheppard, L; Damian, D; Ellis, S; Liberato, N. 2004. Chronic maternal methanol inhalation in nonhuman primates (M acaca fascicularis): exposure and toxicokinetics prior to and during pregnancy. Neurotoxicol Teratol, 26: 201-221.
61 U.S. EPA Integrated Risk Information System (IR IS) database is available at: www.epa.gov/iris7-26 7.2.2 Ozone Co-Benefits
In the presence of sunlight, NOx and VOC s can undergo a chemical reaction in the atmosphere to form ozone. Reducing ambien t ozone concentrations is associated with significant human health benefits, including mort ality and respiratory morbidity (U.S. EPA, 2008a). Epidemiological researchers have associat ed 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 fewe r asthma attacks, hospital and ER visits, school loss days, as well as premature mortality.
7.2.3 Carbon Monoxide Co-Benefits
Carbon monoxide in ambient air is formed primarily by the incomplete combustion of carbon-containing fuels and photochemical reactions in the atmosphere. The amount of CO emitted from these reactions, relative to carbon dioxide (CO 2 ), is sensitive to conditions in the combustion zone, such as fuel oxygen content, burn temper ature, or mixing time. Upon inhalation, CO diffuses through the respiratory system to the blood, which can cause hypoxia (reduced oxygen availability). Carbon monoxide can elicit a broad range of effects in multiple tissues and organ systems that are dependent upon concentration and duration of e xposure. The Integrated Science Assessment for Carbon Monoxide (U.S. EPA, 2010a) concluded that s hort-term exposure to CO is “likely to have a causal relationship” with cardiovascular morbidity, particularly in individuals with coronary heart disease. Epidemiologic studies associate short-term CO exposure with increased risk of emergency department visits and hospital admissions. Coronary heart disease includes those who have angina pectoris (cardiac chest pain), as well as those who have experienced a heart attack. Other subpopulations potentially at risk include individua ls 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 morbid ity and mortality. The evidence is also suggestive of a causal relationship for birth outcomes and developmental effects following long-term exposure to CO, and for central nervous system effects linked to short- and long-term exposure to CO.

7.2.4 Visibility Impairment Co-Benefits

Reducing secondary formation of PM 2.5 would improve visibility throughout the U.S. Fine particles with significant light-extinction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil (Sisler, 1996). Suspended pa rticles and gases degrade visibility by scattering and absorb ing light. Higher visibility impa irment levels in the East are due to generally higher concentrations of fine pa rticles, particularly su lfates, and higher average7-27 relative humidity levels. Visibility has direct significance to people’s enjoyment of daily
activities and their overall sense of wellbeing. Good visibility increases the quality of life where individuals live and work, and wh ere they engage in recreational activities. Previous analyses (U.S. EPA, 2006; U.S. EPA, 2011a; U.S. EPA, 2011b) show that visibility benefits are a significant welfare benefit cate gory. Without air quality modeling, we are unable to estimate visibility related benefits, nor are we able to determine whethe r VOC emission reductions would be likely to have a significant impact on vi sibility in urban ar eas or Class I areas.

7.3 Characterization of Uncertaint y in the Monetized Co-Benefits
In any complex analysis, there are likely to be many sources of uncertainty. Many inputs
are used to derive the final estimate of econo mic benefits, including emission inventories, air quality models (with their associated paramete rs and inputs), epidemio logical estimates of concentration-response (C-R) f unctions, estimates of values , population estimates, income estimates, and estimates of the future state of the world (i.e., regula tions, technology, and human behavior). For some parameters or inputs it may be possible to provide a statistical representation of the underlying unc ertainty distribution. For othe r parameters or inputs, the necessary information is not avai lable. As discussed in the PM 2.5 NAAQS RIA (Table 5.5) (U.S. EPA, 2006), there are a variety of uncertainties associated with th ese PM benefits. Therefore,
the estimates of annual benefits should be viewed as representative of the magnitude of benefits expected, rather than the actual bene fits that would o ccur every year.

It is important to note that the monetized benefit-per-ton estimates used here reflect specific geographic patterns of emissions redu ctions and specific air quality and benefits modeling assumptions. For example, these estimates do not reflect local va riability in population density, meteorology, exposure, baseline health inci dence 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 qua lity modeling. Great care should be taken in applying these estimates to emission reductions o ccurring in any specific location, as these are all based on national or broad regional emissi on reduction programs and therefore represent average benefits-per-ton over the entire Unit ed States. The benefits-per-ton for emission reductions in specific locations may be very differe nt than the estimates presented here. For more information, see the TSD describing the calcula tion of the new benefit-per-ton estimates (U.S. EPA, 2012).7-28 PM 2.5 mortality benefits are the largest benef it category that we monetized in this analysis. To better characterize the uncertainty associated with mort ality impacts that are
estimated to occur in areas with low baseline levels of PM 2.5 , we included the LML assessment. For this analysis, policy-specifi c air quality data is not avai lable due to time or resource limitations, thus we are unable to estimate the per centage of premature mortality associated with this specific rule’s emission reductions at each PM 2.5 level. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the source apportionment modeling used to calculate the benefit-per-ton estimates for this sector. A very large proportion of the population is exposed at or above the lowest LML of the cohort studies (Figures 7-6 and 7-7), increasing our conf idence in the PM mortality analysis. Figure 7-6
shows a bar chart of the percentage of the population exposed to various air quality levels in the pre- and post-policy policy. Figure 7-7 shows a cumulative distribution function of the same data. Both figures identify the LML for each of the major cohort studies. As the policy shifts the distribution of air quality leve ls, fewer people are exposed to PM 2.5 levels at or above the LML. Using the Pope et al. (2002) study, the 77 % of the population is exposed to annual mean
PM 2.5 levels at or above the LML of 7.5 μg/m 3 . Using the Laden et al. (2006) study, 25% of the population is exposed above the LML of 10 μg/m 3

. As we model avoided premature deaths among populations exposed to levels of PM 2.5 , we have lower confidence in levels below the LML for each study. It is important to em phasize that we have high confidence in PM 2.5 -related effects down to the lowest LML of the major c ohort 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 baselin e exposure occurs below the level of the National Ambient Air Quality Standard (NAAQS) for annual PM 2.5 at 15 μg/m 3 , which was set in 2006. It is important to emphasize that NAAQS are not set at a level of zero risk. Instead, the NAAQS reflect the level determined by the Administrator to be protective of public health within an adequate margin of safety, taking into consid eration 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 tota l benefits estimate.7-29 Figure 7-6. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline7-30 Figure 7-7. Cumulative Distribution of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline

Above we present the estimates of the total benefits, based on our interpretation of the
best available scientific l iterature and methods and suppor ted by the SAB-HES and the NAS (NRC, 2002). The benefits estimates are subject to a number of assumptions and uncertainties. For example, for key assumptions underlying the estimates for premature mortality, which typically account for more than 90% of the total benefits, we we re able to quantify include the following:

1. PM 2.5 benefits were derived through benefit per-ton estimates, which do not reflect local variability in populati on density, meteorology, exposure, baseline health incidence rates, or other local factors that might lead to an over-estimate or underestimate of the actual benefits of controlling directly emitted fine particulates. We do not have data on the specific location of th e air quality changes associated with this rulemaking; as such, it is not feasible to estimate the proportion of benefits occurring in different locations, such as designat ed nonattainment areas. In addition, the benefit-per-ton estimates are based on emissi ons from existing sources. To the extent7-31 that the geographic distribution of the emissi ons reductions for this rule are different than the modeled emissions, the benefits ma y be underestimated or overestimated. In general, there is inherently more uncerta inty for new sources, which may not be included in the emissions inve ntory, than existing sources.

2. We assume that all fine particles, re gardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 produced via transported precursors emitted from EGUs may differ significantly from direct PM 2.5 released from diesel engines and other industrial sources, but no clear scien tific grounds exist for s upporting differential effects estimates by particle type.

3. We assume that the health impact functi on for fine particles is linear down to the lowest air quality levels modeled in this an alysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5, including both regions that are in attainment with fine particle standard and those that do not meet the standard down to th e lowest modeled concentrations.

4. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality (which typically accounts for 85% to 95% of total monetized benefits), we include a set of twelve estimates based on results of the expert elicitation study in addition to our core estimates. Even these multiple characterizations omit the uncertainty in air quality estimates, baseline incidence rates, populations exposed and transferability of the effect estimate to di verse locations. As a result, the reported confidence intervals and range of estimates give an incomplete picture about the overall uncertainty in the PM 2.5 estimates. This information should be interpreted within the context of the larger uncertainty surrounding the entire analysis. For more information on the uncertainties associated with PM 2.5 benefits, please consult the PM 2.5 NAAQS RIA (Table 5.5).

This RIA does not include the type of detail ed uncertainty assessment found in the PM NAAQS RIA because we lack the necessary air quality input and monitoring data to run the benefits model. In addition, we have not c onducted any air quality modeling for this rule. Moreover, it was not possible to develop benefit-per-ton metrics and associated estimates of uncertainty using the benefits estimates from th e PM RIA because of the significant differences
between the sources affected in that rule and th ose regulated here. Howe ver, the results of the Monte Carlo analyses of the health and welfare benefits presented in Chapter 5 of the PM RIA can provide some evidence of the uncertainty su rrounding the benefits results presented in this analysis.7-32 7.4 Comparison of Co-Benefits and Costs
Using a 3% discount rate, we estimate the to tal combined monetized co-benefits of the reconsidered CI RICE NESHAP proposal to be $770 million to $1.9 billion in the implementation year (2013). Using a 7% discoun t rate, we estimate the total monetized cobenefits of the reconsidered CI RICE NESH AP proposal to be $690 million to $1.7 billion. The annualized social costs of the proposed NESH AP are $373 million (2010$) at a 7% interest

rate. 62 The annualized social costs of the proposed NESHAP are $372 million in 2008$. Thus, the net benefits are $400 million to $1.5 billi on at a 3% discount rate and $320 million to $1.3
billion at a 7% discount rate. All es timates are in 2010$ for the year 2013.

Table 7-5 shows a summary of the monetized co -benefits, social costs, and net benefits for the CI RICE NESHAP, respectively. Figures 7- 8 and 7-9 show the full range of net benefits estimates (i.e., annual co-benefits minus annua lized costs) utilizi ng the 14 different PM 2.5 mortality functions at discount rates of 3% and 7%. In additi on, the benefits from reducing 109,000 tons of carbon monoxide and 6,000 tons of HA P each year from existing SI RICE have
not been included in these estimates. EPA believe s that the co-benefits are likely to exceed the costs under this rulemaking even when taking into account uncertainties in the cost and benefit
estimates.

Table 7-5. Summary of the Annualized Mone tized Benefits, Soci al Costs, and Net Benefits for the Proposed Reconsidered CI RICE NESHAP in 2013 (millions of 2010$) 1

3% Discount Rate 7% Discount Rate Final Major Source NESHAP

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

Non-monetized Benefits Health effects from HAP exposure

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

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

compliance costs are $372 million in 20 08$ as noted earlier in this RIA. Compliance costs are used as an approximation for social costs in this RIA.

62 For more information on the an nualized social costs, please re fer to Section 5 of this RIA.7-33 2 The total monetized benefits reflect the human health benefits associated with reducing exposure to PM 2.5 through reductions of PM 2.5 precursors such as directly emitted fine particles. Human health 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 prematur e mortality because the scien tific evidence is not yet sufficient to allow differentiation of effects estimates by particle type. Because these estimates were generated using benefit-per-ton estimates, we do not break down the total monetized benefits into specific components here. See Figure 7-1 for an illustration of the breakdown, or th e RIA for the final Cross-States Air Pollution Rule (EPA, 2011) for more information.

3 The engineering compliance costs are annualized using a 7 percent discount rate.7-34 Figure 7-8. Net Benefits for Proposed CI RICE NESHAP Reconsideration at 3% discount rate* *Net Benefits are quantified in terms of PM 2.5 at a 3% discount rate for 2013 and are in 2010$. This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton of precursor reduced has a diff erent propensity to become PM 2.5 . The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. ‐ $100

‐ $80 ‐ $60 ‐ $40 ‐ $20

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

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

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

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

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

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions7-35 Figure 7-9. Net Benefits for Proposed CI RICE NESHAP Reconsideration at 7% discount rate* *Net Benefits are quantified in terms of PM 2.5 benefits at a 7% discount rate at a 7% discount rate for 2013 and are in 2010$. This graph shows 14 benefits estimates combined with the cost estimate. All fine particles are assumed to have equivalent health effects. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. ‐ $500

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

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

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions7-36 7.5 References Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “The influence of location, source, and emission type in estimates of the human health be nefits of reducing a ton of air pollution.” Air Qual Atmos Health 2:169–176.
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Kochi, I., B. Hubbell, and R. Kramer. 2006. “An Empirical Bayes Approach to Combining Estimates of the Value of Statistical Life for Environmental Policy Analysis .” Environmental and Resource Economics. 34: 385-406.
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. Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 2002. “Lung Cancer, Cardiopulmonary Mortal ity, and Long-term Exposure to Fine Particulate Air Pollution.” Journal of the American Medical Association 287:1132-1141.
Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, and Patrick L. Kinney. 2008. “Expert Judgment Assessment of the Mortality Impact of Changes in Ambien t Fine Particulate Matter in the U.S.” Environ. Sci. Technol ., 42(7):2268-2274.7-37 Sisler, J.F. 1996. Spatial and seasonal patterns and long-term variability of the composition of the haze in the United States: an analy sis of data from the IMPROVE network . CIRA Report, ISSN 0737-5352-32, Colorado State University.
U.S. Environmental Protection Agency - Scie nce Advisory Board (U.S. EPA-SAB). 2007. SAB Advisory on EPA’s Issues in Valu ing Mortality Risk Reduction. EPA-SAB-08-001. October. Available on the Internet at

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United States Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impacts Division Research Triangle Park, NC