# Revised Economic Impact Analysis of the Industrial Boilers and Process Heaters NESHAP_________________________________ RTI International is a trade name of Research Triangle Institute. June 2007

Revised Economic Impact Analysis of the I ndustrial Boilers and Process Heaters NESHAP

By:

RTI International Health, Social, and Economics Research Research Triangle Park, NC 27709

Prepared for:

John L. Sorrels U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Benefits and Costs Group C439-02 Research Triangle Park, NC 27711

Contract No. EP-D-06-003iii CONTENTS

Section Page
1 Introduction................................................................................................................. .. 1-1 1.1 Agency Requirements for an EIA........................................................................ 1-1 1.2 Scope and Purpose............................................................................................... 1-2 1.3 Organization of the Report .................................................................................. 1-2 2 Boiler and Process Heater Technologies ...................................................................... 2-1

2.1 Characteristics of Steam ...................................................................................... 2-1

2.2 Fossil-Fuel Boiler Characterization..................................................................... 2-4 2.2.1 Industrial, Commercial, a nd Institutional Boilers.................................... 2-4 2.2.2 Heat Transfer Configurations .................................................................. 2-5 2.2.3 Major Design Types................................................................................. 2-5 2.2.3.1 Stoker-Fired Boilers (Coal) ...................................................... 2-5 2.2.3.2 Pulverized Coal Boilers (Coal)................................................. 2-6 2.2.3.3 Fluidized Bed Combustion (FBC) Boilers (Coal) .................... 2-6 2.2.3.4 Tangentially Fired Boilers (C oal, Oil, Natural Gas)................. 2-7 2.2.3.5 Wall-fired Boilers (Coal, Oil, Natural Gas).............................. 2-7

2.3 Process Heater Characterization.......................................................................... 2-8 2.3.1 Classes of Process Heaters....................................................................... 2-8 2.3.2 Major Design Types................................................................................. 2-9 2.3.2.1 Combustion Chamber Set-Ups ................................................. 2-9 2.3.2.2 Combustion Air Supply ............................................................ 2-9 2.3.2.3 Tube Configurations ............................................................... 2-11 2.3.2.4 Burners.................................................................................... 2-11

3 Profile of Affected Units and F acilities, and Compliance Costs .................................. 3-1 3.1 Regulatory Alternatives....................................................................................... 3-1 3.1.1 Regulatory Background ........................................................................... 3-2 3.1.2 Regulatory Authority ............................................................................... 3-2 3.1.3 Regulatory Alternatives a nd Control Technologies................................. 3-6 3.1.3.1 MACT Floor Development....................................................... 3-6 3.1.3.2 Consideration of Options Beyond the Floor for Existing Units........................................................................................ 3-13 3.1.3.3 EPA Response to Recent Court Decisions in Developing the Emission Limitations ........................................................ 3-17 3.1.3.4 How did EPA Determine the Emission Limitations for New Units? ............................................................................. 3-19iv 3.1.4 Considerations of Possible Risk -Based Alternatives to Reduce Impacts to Sources ................................................................................. 3-29 3.1.4.1 Applicability Cutoffs for Threshold Pollutants Under Section 112(d)(4) of the CAA ................................................ 3-30 3.1.4.2 Applicability Cutoffs for Hydrogen Chloride Controls Under Section 112(d)(4) of the CAA ..................................... 3-31 3.1.4.3 Applicability Cutoffs for Tota l Selected Metals Controls Under Section 112(d)(4) of the CAA ..................................... 3-32 3.2 Profile of Existing Boiler and Process Heaters Units........................................ 3-34 3.2.1 Development of the Unit Inventory Database ....................................... 3-34 3.2.2 Distribution of Existing Boilers and Facilities by Industry ................... 3-35 3.2.3 Technical Characteristics of Existing Boilers........................................ 3-35 3.2.3.1 Final Rule................................................................................ 3-35 3.3 Methodology for Estimating Cost Impacts........................................................ 3-38 3.4 Projection of New Boilers and Process Heaters ................................................ 3-46 3.5 National Engineering Population, Cost Estimates, and Cost-Effectiveness Estimates............................................................................................................ 3-47

4 Profiles of Affected Industries...................................................................................... 4-1 4.1 Textile Mill Products (SIC 22/NAICS 313) ........................................................ 4-1

4.2 Lumber and Wood Product s (SIC 24/NAICS 321) ............................................. 4-1 4.2.1 Supply Side of the Industry...................................................................... 4-3 4.2.1.1 Production Processes ................................................................ 4-3 4.2.1.2 Types of Output ........................................................................ 4-3 4.2.1.3 Major By-Products and Co-Products........................................ 4-4 4.2.1.4 Costs of Production................................................................... 4-4 4.2.1.5 Capacity Utilization .................................................................. 4-4 4.2.2 Demand Side of the Industry ................................................................... 4-5 4.2.3 Product Characteristics ............................................................................ 4-5 4.2.4 Uses and Consumers of Outputs.............................................................. 4-6 4.2.5 Organization of the Industry .................................................................... 4-6 4.2.6 Markets and Trends.................................................................................. 4-7

4.3 Furniture and Related Product Manu facturing (SIC 25/NAICS 337) ................. 4-8 4.4 Paper and Allied Products (SIC 26/NAICS 322) ................................................ 4-9 4.4.1 Supply Side of the Industry.................................................................... 4-10 4.4.1.1 Production Process.................................................................. 4-10 4.4.1.2 Types of Output ...................................................................... 4-11 4.4.1.3 Major By-Products and Co-Products...................................... 4-11 4.4.1.4 Costs of Production................................................................. 4-12 4.4.1.5 Capacity Utilization ................................................................ 4-12v 4.4.2 Demand Side of the Industry ................................................................. 4-13 4.4.2.1 Product Characteristics ........................................................... 4-13 4.4.2.2 Uses and Consumers of Products............................................ 4-13 4.4.3 Organization of the Industry .................................................................. 4-13 4.4.4 Markets and Trends................................................................................ 4-14

4.5 Medicinal Chemicals and Botanical Products and Pharmaceutical Preparations (SICs 2833, 2834/NAICS 32451)................................................. 4-15 4.5.1 Supply Side of the Industry.................................................................... 4-15 4.5.1.1 Production Processes .............................................................. 4-15 4.5.1.2 Types of Output ...................................................................... 4-17 4.5.1.3 Major By-Products and Co-Products...................................... 4-17 4.5.1.4 Costs of Production................................................................. 4-17 4.5.1.5 Capacity Utilization ................................................................ 4-19 4.5.2 Demand Side of the Industry ................................................................. 4-19 4.5.3 Organization of the Industry .................................................................. 4-19 4.5.4 Markets and Trends................................................................................ 4-21 4.6 Industrial Organic Chemicals I ndustry (SIC 2869/NAICS 3251)..................... 4-22 4.6.1 Supply Side of the Industry.................................................................... 4-22 4.6.1.1 Production Processes .............................................................. 4-22 4.6.1.2 Types of Output ...................................................................... 4-23 4.6.1.3 Major By-Products and Co-Products...................................... 4-24 4.6.1.4 Costs of Production................................................................. 4-24 4.6.1.5 Capacity Utilization ................................................................ 4-24 4.6.2 Demand Side of the Industry ................................................................. 4-25 4.6.3 Organization of the Industry .................................................................. 4-25 4.6.4 Markets and Trends................................................................................ 4-26 4.7 Electric Services (SIC 4911/NAICS 22111) ..................................................... 4-27 4.7.1 Electricity Production ............................................................................ 4-27 4.7.1.1 Generation............................................................................... 4-27 4.7.1.2 Transmission........................................................................... 4-28 4.7.1.3 Distribution ............................................................................. 4-29 4.7.2 Cost of Production ................................................................................. 4-30 4.7.3 Organization of the Industry .................................................................. 4-30 4.7.3.1 Utilities.................................................................................... 4-31 4.7.3.2 Nonutilities.............................................................................. 4-33 4.7.4 Demand Side of the Industry ................................................................. 4-33 4.7.4.1 Electricity Consumption ......................................................... 4-33 4.7.4.2 Trends in the Electricity Market ............................................. 4-35 5 Economic Analysis Methodology................................................................................. 5-1 5.1 Background on Economic Modeling Approaches............................................... 5-1 5.1.1 Modeling Dimension 1: Scope of Economic Decisionmaking................ 5-1 5.1.2 Modeling Dimension 2: Interacti on Between Economic Sectors............ 5-3vi 5.2 Selected Modeling Approach for Boile rs and Process Heaters Analysis............ 5-4 5.2.1 Directly Affected Markets ....................................................................... 5-6 5.2.1.1 Electricity Market ..................................................................... 5-6 5.2.1.2 Petroleum Market ..................................................................... 5-7 5.2.1.3 Goods and Services Markets: Agriculture, Manufacturing, Mining, Commercial , and Transportation....... 5-8 5.2.2 Indirectly Affected Markets................................................................... 5-10 5.2.2.1 Market for Coal....................................................................... 5-10 5.2.2.2 Natural Gas Market................................................................. 5-11 5.2.2.3 Goods and Services Markets................................................... 5-11 5.2.2.4 Impact on Residential Sector .................................................. 5-11 5.3 Operationalizing the Economic Impact Model.................................................. 5-11 5.3.1 Computer Model .................................................................................... 5-13 5.3.2 Calculating Changes in Social Welfare ................................................. 5-16 6 Economic Impact Analysis Results .............................................................................. 6-1

6.1 Social Cost Estimates .......................................................................................... 6-1 6.2 National Market-Level Impacts........................................................................... 6-3 6.3 Executive Order 13211 (Energy Effects) ............................................................ 6-5

6.4 Conclusions ......................................................................................................... 6-6 7 Small Entity Impacts..................................................................................................... 7-1 7.1 Background on Small Entity Screenings ............................................................. 7-1 7.2 Identifying Small Entities with A ffected Sources in the Inventory Database............................................................................................................... 7-2 7.3 Analysis of Facility-Level and Parent-Level Data .............................................. 7-4 7.4 Small Entity Impacts ........................................................................................... 7-9 7.5 Affected Government Entities: Supplemental Analysis.................................... 7-10 7.6 Small Utility and Nonutility Entities: Data and Screening Analysis Results.... 7-13 7.7 Assessment of SBREFA Screening................................................................... 7-14

References..................................................................................................................... .........R-1vii Appendixes A Estimating Economic Impacts in Markets Affected by the Boilers and Process Heaters MACT ...................................................................................... A-1 B Assumptions and Sensitivity Analysis ................................................................B-1 C Economic Analysis of Regulatory Alternative: Option 1A.................................C-1 D Impacts from Application of Risk-Based Alternatives....................................... D-1viii LIST OF FIGURES

Number Page 2-1 Generating Electricity: Steam Turbines........................................................................ 2-3

3-1 Characteristics of Units Affected................................................................................ 3-38

4-1 Traditional Electric Powe r Industry Structure ............................................................ 4-28 4-2 Utility and Nonutility Generation and Shares by Class, 1988 and 1998 .................... 4-32 4-3 Annual Electricity Sales by Sector ............................................................................. 4-35
5-1 Links Between Energy and Goods and Services Markets ............................................ 5-5 5-2 Market Effects of Regulation-Induced Costs................................................................ 5-7 5-3 Fuel Market Interactions with Facility-Level Production Decisions............................ 5-9 5-4 Operationalizing the Estimation of Economic Impact................................................ 5-12 5-5 Changes in Economic Welf are with Regulation......................................................... 5-17
7-1 Parent Size by Employment Range............................................................................... 7-6 7-2 Number of Parent s by Sales Range............................................................................... 7-7ix LIST OF TABLES

Number Page 3-1 Emission Limits for Boilers and Process Heaters (lb/MMBtu).................................... 3-5 3-2 Units and Facilities Affected by the Final Rule by Industry ...................................... 3-36 3-3 Testing and Monitoring Co sts for Units Covered....................................................... 3-43 3-4 Cost Effectiveness (C/E) of Industr ial Boiler and Process Heater MACT on Existing Units and Subcategories ............................................................................... 3-46 3-5 New Unit Projections by Industry, MACT Floor ....................................................... 3-48 3-6 Unit Cost and Population Estimates fo r the Final Rule by Industry, 2005................. 3-50

4-1 Lumber and Wood Products Ma rkets Likely to Be Affected by the Regulation.......... 4-2 4-2 Value of Shipments for the Lumber and Wood Products Industry (SIC 24/NAICS 321), 1987–1996................................................................................. 4-2 4-3 Inputs for the Lumber and Wood Pr oducts Industry (SIC 24/NAICS 321), 1987–1996..................................................................................................................... 4 -5 4-4 Capacity Utilization Ratios for Lumber and Wood Products Industry, 1991– 1996........................................................................................................................... .... 4-5 4-5 Size of Establishments and Value of Shipments for the Lumber and Wood Products Industry (SIC 24/NAICS 321) ....................................................................... 4-7 4-6 Measures of Market Concentration fo r Lumber and Wood Products Markets............. 4-8 4-7 Paper and Allied Products Industry Markets Likely to Be Affected by Regulation..................................................................................................................... 4-9 4-8 Value of Shipments for the Paper and Allied Products Industry (SIC 26/NAICS 322), 1987–1996............................................................................... 4-10 4-9 Inputs for the Paper and Allied Pr oducts Industry (SIC 26/NAICS 322), 1987– 1996........................................................................................................................... .. 4-12 4-10 Capacity Utilization Ratios for th e Paper and Allied Products Industry, 1991– 1996........................................................................................................................... .. 4-13 4-11 Size of Establishments and Value of Shipments for the Paper and Allied Products Industry (SIC 26/NAICS 322) ..................................................................... 4-14 4-12 Measurements of Market Concentration for Paper and Allied Products Markets...... 4-15 4-13 Value of Shipments for the Medicinals and Botanicals and Pharmaceutical Preparations Industries, 1987–1996............................................................................ 4-16 4-14 Inputs for Medicinal Chemical s and Botanical Products Industry (SIC 2833/NAICS 32451), 1987–1996....................................................................... 4-18 4-15 Inputs for the Pharmaceutical Prepar ations Industry (SIC 2834/NAICS 32451), 1987–1996................................................................................................................... 4-1 8 4-16 Capacity Utilization Ratios for the Me dicinal Chemicals and Botanical Products (SIC 2833/NAICS 32451) and Ph armaceutical Preparations (SIC 2834/NAICS 32451) Industries, 1991–1996...................................................... 4-19x 4-17 Size of Establishments and Value of Shipments for the Medicinal Chemicals and Botanical Products (SIC 2833/ NAICS 32451) and Pharmaceutical Preparations (SIC 2834/NAICS 32451) Industries..................................................... 4-20 4-18 Measures of Market Concentration fo r the Medicinal Chemicals and Botanical Products (SIC 2833/NAICS 32451) and Phar maceutical Preparations (SIC 2834/NAICS 32451) Industries .................................................................................. 4-21 4-19 Value of Shipments for the Industrial Organic Chemicals, N.E.C. Industry (SIC 2869/NAICS 3251), 1987–1996 ................................................................................. 4-23 4-20 Inputs for the Industrial Organic Ch emicals Industry (SIC 2869/NAICS 3251), 1987–1996................................................................................................................... 4-2 5 4-21 Capacity Utilization Ratios for the In dustrial Organic Chemicals Industry (SIC 2869/NAICS 3251), 1991–1996 ................................................................................. 4-25 4-22 Size of Establishments and Value of Shipments for the Industrial Organic Chemicals Industry (SIC 2869/NAICS 3251) ............................................................ 4-26 4-23 Net Generation by Energy Source, 1995 .................................................................... 4-29 4-24 Total Expenditures in 1996 ($10 3 ).............................................................................. 4-30 4-25 Number of Electricity Suppliers in 1999 .................................................................... 4-31 4-26 U.S. Electric Utility Retail Sales of Electricity by Sector, 1989 Through 1998 (10 6 kWh).................................................................................................................... 4-34 4-27 Key Parameters in the Cases....................................................................................... 4-36
5-1 Comparison of Modeling Approaches.......................................................................... 5-2 5-2 Supply and Demand Elasticities ................................................................................. 5-14 5-3 Fuel Price Elasticities.................................................................................................. 5- 16
6-1 Social Cost Estimates ($1998 10 6 ): Final Rule............................................................. 6-1 6-2 Distribution of Social Costs by Sector/Market: Final Rule ($1998 10 6 ) ...................... 6-2 6-3 Market-Level Impacts: Final Rule................................................................................ 6-4
7-1 Summary of Small Entity Impacts................................................................................ 7-1 7-2 Facility-Level and Parent -Level Data by Industry........................................................ 7-5 7-3 Small Parent Enti ties by Industry ................................................................................. 7-8 7-4 Summary Statistics for SBREFA Screening Analysis................................................ 7-10 7-5 Regional Distribution of Municipal Systems.............................................................. 7-11 7-6 Selected Municipal Utilities’ Capaci ty, Usage, and Consumer Types ....................... 7-12 7-7 Comparison of Screening Analysis Results for Small Governmental Jurisdictions ................................................................................................................ 7- 13 7-8 Industry Distribution of Small Commer cial Electric Utility and Nonutility Entities ....................................................................................................................... . 7-14 7-9 Supplemental Screening Analysis for Small Governmental Jurisdictions ................. 7-14 7-10 Profit Margins for Industry Sectors with Affected Small Businesses ........................ 7-151-1 SECTION 1 INTRODUCTION
The U.S. Environmental Protection Agency (referred to as EPA or the Agency) is developing regulations under Section 112 of the Cl ean Air Act (CAA) or the Act for industrial, commercial, and institutional (ICI) boilers and process heaters. These combustion devices are used in the production processes of numerous indu stries in the U.S. The hazardous air pollutants (HAPs) are generated by the combustion of fo ssil fuels and biomass in boilers and process heaters. The primary HAPs emitted by ICI boilers and process heaters include arsenic, beryllium, cadmium, lead, hydrochloric acid, mercury, and ot her HAPs. In addition, ICI boilers and process heaters also emit non-HAP pollutants such as sulf ur dioxide and particulate matter. To inform this rulemaking, the Air Benefits and Costs Group (ABCG) of EPA’s Office of Air Quality Planning and Standards (OAQPS) has developed an economic impact analysis (EIA) to estimate the potential social cost s of the regulation.
This report presents the results of this anal ysis in which a market model was used to analyze the impacts of the air pollution rule on societ y. It is a corrected vers ion of a final report prepared in February 2004 in support of the pr omulgation of this final rule. Corrections and revisions to the small entity analysis were made in response to data and statements provided as part of a lawsuit filed by several Ohio municipa lities against EPA’s promulgation of this MACT standard. The effect of these co rrections and revisions are found in Section 7 of this report.

1.1 Agency Requirements for an EIA Congress and the Executive Office have imposed statutory and administrative requirements for conducting economic analyses to accompany regulatory actions. Section 317 of the CAA specifically requires estimation of th e cost and economic impacts for specific regulations and standards under the authority of the Act. In addition, Executive Order (EO) 12866 requires a more comprehensive analysis of benefits and costs fo r significant regulatory actions. 1 Other statutory and administ rative requirements include ex amination of the composition and distribution of benefits and costs. For exam ple, the Regulatory Flexibility Act (RFA), as amended by the Small Business Regulatory En forcement and Fairness Act of 1996 (SBREFA), requires EPA to consider the economic impacts of regulatory actions on small entities. The Agency’s OAQPS Economic Analysis Resource Document provides detailed instructions and expectations for economic analyses that support rulemaking (EPA, 1999).

1 Current Office of Management and Budget (OMB) guidance under EO 12866 stipulates that a full benefit-cost analysis is required only when the regulatory action has an annual effect (benefits + costs) on the economy of $100 million or more.1-2 1.2 Scope and Purpose The CAA’s purpose is to protec t and enhance the quality of the nation’s air resources (Section 101(b)). Section 112 of the CAA Amendments of 1990 esta blishes the auth ority to set national emissions standards for HAPs. This repo rt evaluates the economic impacts of pollution control requirements placed on ICI boilers and process heater s under these amendments. These control requirements are designed to redu ce releases of HAPs into the atmosphere.
To reduce emissions of HAPs, the Agency establishes maximum achievable control technology (MACT) standards. The term “MAC T floor” refers to the minimum control technology on which MACT standards can be based. For existing major sources, 2 the MACT floor is the average emissions limitation achieve d by the best performing 12 percent of sources (if there are 30 or more sources in the categor y or subcategory). For new sources, the MACT floor must be no less stringent than the emi ssions control achieved in practice by the best controlled similar source. The MACT can also be chosen to be more stringent than the floor, considering the costs and the hea lth and environmental impacts.
The MACT floor will affect approximately 5,600 existing and new units. EPA developed annual compliance costs for model units in each of 83 different model unit types. EPA then linked the annualized compliance co sts from the model units to the estimated existing population of boilers and process heaters to obtain nati onal impact estimates. In addition, the Agency projected entrance of new boilers and proce ss heaters through the ye ar 2005, and linked the annualized compliance costs to these projected new units.
The economic impacts of national complian ce costs, including both existing and new units, on affected markets was then estimated us ing a computerized market model. EPA used changes in prices and quantitie s in energy markets and final product markets to estimate the firm-, industry-, market-, and societal-lev el impacts associated with the regulation.

1.3 Organization of the Report The remainder of this report is divided in to six sections that describe the methodology and presents the analysis results:

 Section 2 provides background informati on on ICI boiler and process heater technologies.

2 A major source is defined as a stationary source or group of stationary sources located within a contiguous area and under common control that emits, or has the potential to emit considering control, 10 tons or more of any one HAP or 25 tons or more of any combination of HAPs.1-3  Section 3 profiles existing ICI boilers and pr ocess heaters by capaci ty, fuel type, and industry and presents projecti ons of the future population of units in 2005. National compliance cost estimates are al so presented in this section.

 Section 4 profiles the industries with the largest number of affected facilities. Included are profiles of the lumber and wood products (SIC 24/NAICS 321), paper and allied products (SIC 26/ NAICS 322), and electrical services (SIC 49/NAICS 221) industries.

 Section 5 describes the methodology for assessing the economic impacts of the National Emission Standard for H azardous Air Pollutants (NESHAP).

 Section 6 presents the results of the ec onomic analysis, including market, industry, and social cost impacts.

 Section 7 provides the Agency’s analysis of the regulation’s impact on small entities. In addition to these sections, Appendix A deta ils the economic model used to predict the economic impacts of the NESHAP, Appendix B pres ents the results of sensitivity analyses on key model assumptions, Appendix C presents resu lts of analyses for regulatory alternative Option 1A., and Appendix D provides results of a se nsitivity analysis based on considering riskbased compliance alternatives includ ed in the final MACT standard.2-1 SECTION 2 BOILER AND PROCESS HEATER TECHNOLOGIES
The three categories of combus tion devices affected under the regulations are industrial, commercial, and institutional (ICI) boilers and process heaters. Although their primary function is to transfer heat generated from fuel combus tion to materials used in the production process, the applications for boilers and process heaters are somewhat different. As a result, the primary industries using boilers may not be the same as t hose using process heaters. It is important to note that throughout this report the terms “boilers and proces s heaters,” and “units” are synonymous with “ICI boilers and process heat ers.” Utility boilers primarily engaged in generating electricity are not c overed by the NESHAP under analysis and are therefore excluded from this analysis.
Boilers are combustion devices used to produ ce steam or heat water. Steam is produced in boilers by heating water until it vaporizes. The steam is then channeled to applications within a facility or group of f acilities via pipes. Steam is an impor tant power and heating source for the U.S. economy. It is used in the preparation or manufacturing of many key products, such as paper, petroleum products, furniture, and chemicals. Steam is also used to heat buildings and to generate the majority of the elec tricity consumed in this country. There are literally thousands of boilers currently being used in the United St ates throughout a wide va riety of industries.
Process heaters are primarily used as heat transfer units in which heat from fuel combustion is transferred to proces s fluids, although they may also be used to transfer heat to other nonfluid materials or to heat transfer ma terials for use in a process unit (not including generation of steam). Process heaters are generall y used in heat transfer applications where boilers are inadequate. Often these are uses in which heat must be transferred at temperatures in excess of 90° to 204°C (200° to 400°F). Process h eaters are used in the petroleum refining and petrochemical industries, with minor applications in the asphalt concrete, gypsum, iron and steel, and wood and forest products industries.

Since one of the main uses of boilers is to generate steam, some of the characteristics of steam are discussed in this secti on. This section also provides an overview of the various types of boiler and process heater ch aracteristics and designs.

2.1 Characteristics of Steam Steam, an odorless, invisible gas of vaporized water, may be interspersed with water droplets, which gives it a cloudy a ppearance. It is produced natura lly when underground water is2-2 heated by volcanic processes and mechanically us ing boilers and other he ating processes. When water is heated at atmospheric pressure, it re mains in liquid form until its temperature exceeds 212°F, the boiling point of water. Additional he at does not raise the water’s temperature but rather vaporizes the water, conve rting it into steam. However, if water is heated under pressure, such as in a boiler, the boiling point is higher than 212°F and more heat is required to generate steam. Once all the water has been vaporized into steam, the addition of heat causes the temperature and volume to increase. Steam’s hea ting and work capabilities increase as it is produced under greater pressure coupled with hi gher temperatures. As steam escapes from the boiler, it can be direct ed through pipes to drive mechanical processes or to provide heat.
The steam used in most utility, industrial, a nd commercial applications is referred to as “clean steam.” Clean steam encompasses steam purit ies ranging from pure, solid-free steam used in critical processes to filtered steam for less de manding applications. The various types of clean steam differ in steam purity and steam quality. Steam purity is a quantitative measure of contamination of steam caused by dissolved partic les in the vapor or by tiny droplets of water that may remain in the steam. Steam quality is a measure of how much liquid water is mixed in with the dry steam (Fleming, 1992). Firms select the levels of steam quality and steam purity for their applications based on the sensitivity of th eir equipment to impurities, water droplet size, and condensation as well as the requirements fo r their production proces s. Using clean steam minimizes the risk of product contamination and prolongs equipment life. Although there are infinite possible levels of water purity and qual ity, the term “clean steam” generally refers to three basic types of steam:

 filtered steam—produced by filtering plant steam using high-efficiency filters. Filtered steam is generally of high steam quality because most large water droplets and other contaminants will be filtered out.

 clean steam—steam that is frequently produ ced from deionized and distilled water. Deionized and distilled water is free of dissolved solids and ions, which may corrode pipework.

 pure steam—similar to clean steam except that it is always produ ced from deionized and distilled water. Steam applications can be categorized by the amount of pressure required: hot water, low pressure, and high pressure. Low pressure is 0 to 15 pounds per square inch (psi) and high pressure steam is above 15 psi ( Plant Engineering , 1991). Hot water systems, which generate little steam, are primarily used for comfort appl ications, such as hot water for a building. Low pressure applications include process heat a nd space heating. High pressure steam applications are more frequently used in industrial and utility applications. Some high pressure applications2-3 require that the steam be superheated, a process which ensures that the steam is free of water droplets, to avoid damaging sensitive equipment.
Electric cogenerators, such as large factories and processing f acilities, use steam to drive turbines to generate electricity. A conventiona l steam electric power plant burns fossil fuels (coal, gas, or oil) in a boiler, releasing heat that boils water and converts it into high-pressure steam (see Figure 2-1). The steam enters a turbine where it expands and pushes against blades to turn the generator shaft and create electric cu rrent. In this way, the thermal energy of steam becomes mechanical energy, which is converted in to electricity. Steam us ed to drive turbines generates most of the electric power in the United States (TXU, 2000).

Figure 2-1. Generating Elect ricity: Steam Turbines
Source: Texas Utilities (TXU). 2000. “Generating Electricity: Steam Turbines.” As obtained in September 2000. <http://www.txu.com/knowledge/energy_lib/generating01.html>.
Industrial operations use steam to perform work such as powering complex machinery operations, in the same way that electric utilities use steam to rotate turbines. Textile mills, pulp and paper mills, and other manufacturing outfits are examples of facilities that use steam to run machinery. Steam also provides heat and pre ssure for manufacturing processes. Industrial establishments use steam to provide heat for dr ying or to heat and separate materials. For example, the paper industry uses steam to heat roll ers that dry paper during the final stages of the2-4 production process. Petroleum refi neries and chemical producers us e steam to heat petroleum, raw materials, and other inputs to separate inputs into their constitu ent components or to facilitate chemical interactions. In addition to these applications, steam is employed in many other industrial processes, in cluding textile production, wood working, furniture making, metal working, food preparation, and the manufacture of chemicals. Substitutes for using steam as process heat include electrical heating equipment, infrared, and other radiant drying techniques. Electricity may be used to power machinery, as well. However, switching from steam-powered to electricity-powered machiner y would require significant equipm ent retrofits or replacement.
Other steam applications include heating, sanitation, food processing and preparation, and cleaning. In addition to us ing boilers to heat water, fa ctories, hospitals, government buildings, schools and other large buildings use bo iler-generated steam to provide space heating. Substitutes for boilers in heating air and wate r include electrical water and space heaters; furnaces; and other heating, ventilati on, and air conditioning equipment.

2.2 Fossil-Fuel Boiler Characterization
Section 2.2 discusses the different classes of fossil-fuel boilers, the most common heat transfer configurations, and the major design type s. The discussion indicate s the type(s) of fuel that each design can use to operate.

2.2.1 Industrial, Commercial, and Institutional Boilers Industrial, commercial, and in stitutional boilers ar e primarily used for process heating, electrical or mechanical power generation, and/or space heating. Industrial boi lers are used in all major industrial sectors but primarily by the paper products, chemical, food, and petroleum industries. It is estimated that the heat input capacity for these bo ilers is typically between 10 and 250 MMBtu/hr; however, larger indust rial boilers do exist and are similar to utility boilers (EPA, 1997b). Commercial/institutional boilers are generally smaller than the industr ial units, with heat input capacities generally below 10 MMBtu/hr. These units norma lly supply the steam and hot water for space heating in a wide range of locatio ns, including wholesale and retail trade, office buildings, hotels, restaurants, hospitals, schools, museums, government buildings, and airports.
A boiler system includes the boiler itself, a ssociated piping and valves, operation and safety controls, water treatment system, and peripheral equipment such as pollution control devices, economizers, or superheaters ( Plant Engineering , 1991). Most boilers are made of steel, cast iron, or copper. The primary fu els used by boilers are coal, oil, and natural gas, but some use electricity, waste gases, or biomass.2-5 Boilers may either be erected onsite (field- erected boilers) or a ssembled at a factory (packaged boilers). Packaged boilers are typically lower in initial co st and more simple to install. However, field-erected boilers may have lower operating costs, less main tenance, and greater flexibility because the furnace or convection patt ern chosen to meet required steam pressure, capacity, and fuel specifications is ta ilored to the boiler’s potential use ( Plant Engineering , 1991). Applications requiring more than 100,000 pounds of steam per hour are usually equipped with a field-erected boiler.

2.2.2 Heat Transfer Configurations The heat transfer configuration of a boile r refers to the method by which heat is transferred to the water. The four primary boile r configurations are wate rtube, firetube, cast iron, and tubeless. Most industrial users tend to rely on either watertube or fi retube configurations.
In a watertube boiler, combus tion heat is transferred to water flowing through tubes lining the furnace walls and boiler passes. The furnace watertubes absorb primarily radiative heat, while the watertubes in the boiler passes ga in heat by convective heat transfer. These units have a wide range of heat i nput capacities (ICI units range from 0.4 to 1,500 MMBtu/hr) and can be either field erected or packaged. 3 Watertube boilers with heat input capacities greater than 200 MMBtu/hr are typically field erected.
Because firetube, cast iron, and tubeless heat tr ansfer configurations typically have heat input capacities below 10 MMBtu/hr, they will not generally be covered by the NESHAP. Therefore, this profile focuses on those boile r types that use watertube heat transfer configurations.

2.2.3 Major Design Types This section summarizes the five major design types for fossil fuel i ndustrial boile rs that will be covered by the NESHAP. It also discusses, where possible, the fuels used, capacity, and assembly method of each of these types of boilers.

2.2.3.1 Stoker-Fired Boilers (Coal)
These units use underfeed air to combust the coal char on a stationary grate, combined with one or more levels of overf ire air introduced above the grate. There are three types of stoker units:

3 Office of Management and Budget (OMB) guidance under EO 12866 stipulates that a full benefit-cost analysis is required only when the regulatory action has an annual effect on the economy of $100 million or more.2-6  spreader stokers,

 underfeed stokers, and

 overfeed stokers. Stokers generally burn all types of coal, w ith the exception of overfeed stokers, which do not burn coking bituminous coals. Stokers can also burn other types of solid fuel, such as wood, wood waste, and bagasse. Spreader stokers are th e most common of these boiler types and have heat input capacities that t ypically range from 5 to 550 MMBtu/hr. However, some of these boilers have capacities as high as 1,500 MMBtu/hr. Smaller stoker units (i.e., those with heat input capacities less than 100 MMBtu/hr) are generally packaged, while larger units are usually field erected.

2.2.3.2 Pulverized Coal Boilers (Coal) Combustion in pulverized coal-fired units take s place almost entirely while the coal is suspended, unlike in stoker units in which the coal burns on a grate. Finely ground coal is typically mixed with primary combustion air and fed to the burner or burners, where it is ignited and mixed with secondary combustion air. De pending on the location of the burners and the direction of coal injection into the furnace, pulver ized coal-fired boilers can be classified into three different firing types:

 single and opposed wall,

 tangential, and

 cyclone. Of these types, wall and ta ngential configurations are the most common. These firing methods are described furt her in Sections 2.2.3.4 and 2.2.3.5.

2.2.3.3 Fluidized Bed Combustion (FBC) Boilers (Coal) FBC is an integrated technology for reducing sulfur dioxide (SO 2 ) and NO x emissions during the combustion of coal. In a typical FBC boiler, crushed coal and inert material (sand, silica, alumina, or ash) and/ or a sorbent (limestone) are maintained in a highly turbulent suspended state by the upward flow of primary air from the windbox located directly below the combustion floor. This fluidized state provides a large amount of surface contact between the air and solid particles, which promotes uniform and efficient combustion at lower furnace temperatures than conventional coal-fired boi lers. Once the hot gases leave the combustion chamber, they pass through the convective sections of the boiler, which are si milar or identical to components used in conventional boilers.2-7 For the FBCs currently in use in all sectors, coal is the primary fuel source, followed in descending order by biomass, coal waste, and municipal waste. Th e heat input capacities of all ICI FBC units generally range from 1.4 to 1,075 MMBtu/hr.

2.2.3.4 Tangentially Fired Boilers (Coal, Oil, Natural Gas) The tangentially fired boiler is based on the concept of a single flame zone within the furnace. The fuel-air mixture projects from the four corners of the furn ace along a line tangential to an imaginary cylinder located along the furnac e centerline. As fuel and air are fed to the burners and the fuel is combuste d, a rotating “fireball” is form ed. Primarily because of their tangential firing pattern, which leads to larger flame volumes and flame interaction, uncontrolled tangentially fired boilers gene rally emit relatively lower NO x than other uncontrolled boiler designs.
Utilities primarily use this type of boiler. Coal is the most common fuel used by these units. Tangentially fired boilers operated by utilities are typica lly larger than 400 MW, while industrial ones almost always have heat inpu t capacities over 100 MMBtu/hr. In general, most units with heat inpu t capacities over 100 MMBtu /hr are field erected.

2.2.3.5 Wall-fired Boilers (Coal, Oil, Natural Gas) Wall-fired boilers are characterized by multip le individual burners located on a single wall or on opposing walls of the furnace. In contra st to tangentially fire d boilers, each of the burners in a wall-fired boiler has a relatively distinct flame zone , and the burners in wall-fired boilers do not tilt. Superheated steam temperatur es are instead controlle d by excess air levels, heat input, flue gas recircul ation, and/or steam attemperati on (water spray). Depending on the design and location of the burners, wall-fired boile rs are referred to as single wall or opposed wall.
Wall-fired boilers are used to burn coal, oil, or natural gas, and some designs feature multifuel capability. Almost all industrial wall-fi red boilers have heat input capacities greater than 100 MMBtu/hr. Opposed-wall boilers in pa rticular are usually much larger than 250 MMBtu/hr heat input capacity and are much more common in utility rather than in industrial operations. Because of their size, most wall-fired units are field erected. Field-erected watertube boilers strictly designed for oil fi ring are more compact than coal-fired boilers with the same heat input, because of the more rapid combustion charact eristics of fuel oil. Field-erected watertube boilers fired by natural gas are ev en more compact because of the rapid combustion rate of the gaseous fuel, the low flame luminosity, and the ash-free content of natural gas.2-8 2.3 Process Heater Characterization
Process heaters are heat transfer units in wh ich heat from fuel combustion is transferred to materials used in a production process. The pro cess fluid stream is heated primarily for one of two reasons: to raise the temperature for additional processing or to make chemical reactions occur. This section describes th e different classes of process heaters and major design types.

2.3.1 Classes of Process Heaters The universe of process heaters is divided into two categories:

 indirect-fired process heater—any process heater in which the combustion gases do not mix with or exhaust to the atmosphere from the same stack(s) or vent(s) with any gases emanating from the proce ss or material being processed.

 direct-fired process heater —any process heater in whic h the combustion gases mix with and exhaust to the atmosphere from the same stack(s) or vent(s) with gases originating from the process or material being processed.
Indirect-fired units are used in situations where direct flame contact with the material being processed is undesirable because of probl ems with contamination and ignition of the process material. Direct-fired units are used wh ere such problems are not an important factor. Emissions of indirect-fired units consist solely of the products of combustion (including those of incomplete combustion). On the other hand, direct -fired units will generate emissions consisting not only of the products of com bustion, but also the process mate rial(s). This means that the emissions from indirect-fired proc ess heaters will be generic to the fuel in use and are common across industries while emissions fr om direct-fired process heaters are unique to a given process and may vary widely depending on the process mate rial. Only indirect-fir ed process heaters are considered under this regulation. Many direct-f ired process heaters are being considered under separate MACT-development projects.

In addition to the distinction between direct- and indirect-fir ed heaters, process heaters may also be considered either heated feed or r eaction feed. Heated feed process heaters are used to heat a process fluid stream before additional processing. Thes e types of process heaters are used as preheaters for various operations in the petroleum refining industr y such as distillation, catalytic cracking, hydroprocessi ng, and hydroconversion. In addi tion, heated feed process heaters are used widely in the chemical manuf acturing industry as fire d reactors (e.g., steamhydrocarbon reformers and olefins pyrolysis furn aces), feed preheaters for nonfired reactors, reboilers for distillation operations , and heaters for heating transf er oils. Reaction feed process heaters are used to provide enough heat to cause chemical reactions to occur inside the tubes being heated. Many chemical reactions do not occur at room temperature and require the2-9 application of heat to the reac tants to cause the reaction to ta ke place. Applications include steam-hydrocarbon reformers used in ammonia a nd methanol manufacturing, pyrolysis furnaces used in ethylene manufacturing, and thermal cr acking units used in refining operations.

2.3.2 Major Design Types Process heaters may be designed and construc ted in a number of ways, but most process heaters include burner(s), combustion chamber(s ), and tubes that c ontain process fluids. Sections 2.3.2.1 through 2.3.2.4 describe combusti on chambers setups, combustion air supply, tube configurations, a nd burners, respectively.

2.3.2.1 Combustion Chamber Set-Ups
Process heaters contain a radiant heat transfer area in the combustion chamber. This area heats the process fluid stream in the tubes by flame radiation. Equipment found in this area includes the burner(s) and the co mbustion chamber(s). Most heat transfer to the process fluid stream occurs here, but these tubes do not necessarily constitute a majority of the tubes in which the process fluid flows.
Most process heaters also use a convective heat transfer section to recover residual heat from the hot combustion gases by convective heat transfer to the process fluid stream. This section is located after the radiant heat transfer section and also contains tubes filled with process fluid. The first few rows of tubes in this secti on are called shield tubes and are subject to some radiant heat transfer. Typically, the process fluid flows th rough the convective section prior to entering the radiant section to preheat the proces s fluid stream. The temperature of the flue gas upon entering the convective section usually ranges from 800°C to 1,000°C (1,500°F to 2,000°F). Preheating in the convective section impr oves the efficiency of the process heater, particularly if the tube design includes fins or other extended surface areas. An extended tube surface area can improve efficiency by 10 percent. Extended tubes can reduce flue gas temperatures from 800°C to 1,000°C to (1,500°F to 2,000°F) to 120°C to 260°C (250°F to 500°F).

2.3.2.2 Combustion Air Supply Air for combustion is supplied to the burners vi a either natural draft (ND) or mechanical draft (MD) systems. Natural draft heaters use duct work systems to route air, usually at ambient conditions, to the burners. MD heaters use fans in the ductwork system to supply air, usually preheated, to the burners. The combustion air suppl y must have sufficient pressure to overcome the burner system pressure drops caused by ducting, burner registers, and dampers. The pressure inside the firebox is generally a slightly negati ve draft of approximately 49.8 to 125 Pascals (Pa)2-10 at the radiant-to-convective s ection transition point. The nega tive draft is achieved in ND systems via the stack effect and in MD systems via fans or blowers.
ND combustion air supply uses the stack effect to induce the flow of combustion air in the heater. The stack effect, or thermal buoyancy, is caused by th e density difference between the hot flue gas in the stack and the significan tly cooler ambient air surrounding the stack. Approximately 90 percent of all gas-fired heater s and 76 percent of all oil-fired heaters use ND combustion air supply (EPA, 1993).
There are three types of MD combustion air supply: forced draft, induced draft, and balanced draft. The draft types are named accord ing to the position, relative to the combustion chamber, of the fans used to create the pressure difference in the process heater. All three types of MD heaters rely on the fans to supply combus tion air and remove flue gas. In forced draft combustion air supply systems, the fan is lo cated upstream from the combustion chamber, supplying combustion air to the burne rs. The air pressure supplied to the burners in a forced draft heater is typically in the range of 0.747 to 2.49 kilopascals (kPa). Though combustion air is supplied to the burners under pos itive pressure, the remainder of the process heater operates under negative pressure caused by the stack effect. In induced draft combustion air systems, the fan is located downstream of th e combustion chamber, creating negative pressure inside the combustion chamber.
This negative pressure draws, or induces , combustion air into the burner registers. Balanced draft combustion air systems use fans placed both upstream and downstream (forced and induced draft) of the combustion chamber.
There are advantages and disadvantages for both ND and MD combustion air supply. One advantage to natural draft heaters is that they do not require the fans and equipment associated with MD combustion air supply. Howeve r, control over combustion air flow is not as precise in ND heaters as in MD heaters. MD heaters, unlike ND heaters, provide the option of using alternate sources of combustion oxygen, such as gas turbine exhaust. They also allow the use of combustion air preheat. Combustion air preh eat has limited application in ND heaters due to the pressure drops associated with combustion air preheaters.
Combustion air preheaters are often used to increase the efficiency of MD process heaters. The maximum thermal efficiency obtaina ble with current air preheat equipment is 92 percent. Preheaters allow heat to be transferre d to the combustion air from flue gas, steam, condensate, hydrocarbon, or other hot streams. The preheater incr eases the efficiency of the2-11 process heater because some of the thermal ener gy is reclaimed that would have been exhausted from the hot streams via cooling to wers. If the thermal energy is from a hot stream other than the flue gas, the entire plant’s efficiency is increased . The benefit of higher thermal efficiency is that less fuel is required to operate the heater.

2.3.2.3 Tube Configurations The orientation of the tubes through which a pro cess fluid stream flows is also taken into consideration when designing a pr ocess heater. The tubes in the convective section are oriented horizontally in most process heaters to allow cr oss-flow convection. However, the tubes in the radiant area may be oriented either horizontally or vertically. The orientat ion is chosen on a caseby-case basis according to the design specificatio ns of the individual process heater. For example, the arbor, or wicket, type of heater is a specialty design to minimize the pressure drop across the tubes.

2.3.2.4 Burners Many different types of burners are used in process heaters. Burner selection depends on several factors including process heat flux requirements, fuel t ype, and draft type. The burner chosen must provide a radiant heat distribution that is consistent with the configuration of the tubes carrying process fluid. Also, the numbe r and location of the burner(s) depend on the process heater application.
Many burner flame shapes are possible, but the most common types are flat and conical. Flat flames are generally used in applications that require high temperatures such as ethylene pyrolysis furnaces, although some ethylene furnaces use conical flames to achieve uniform heat distribution. Long conical flames are used in cases where a uniform heat distribution is needed in the radiant section.
Fuel compatibility is also important in burner selection. Burners may be designed for combustion of oil, gas, or a gas/oil mixture. Gas-fired burners are simpler in operation and design than oil-fired burners and are classified as either premix or raw gas burners. In premix burners, 50 to 60 percent of the air necessary fo r combustion is mixed with the gas prior to combustion at the burner tip. This air is induced into the gas stream as the gas expands through orifices in the burner. The re mainder of the air necessary fo r combustion is provided at the burner tip. Raw gas burners receive fuel gas without any premixed combustion air. Mixing occurs in the combustion zone at the burner tip.2-12 Oil-fired burners are classified according to the method of fuel atomization used. Atomization is needed to increase the mixing of fuel and combustion air. Three types of fuel atomization commonly used are mechanical, air, and steam. Steam is the most widely used method because it is the most economical, provide s the best flame control, and can handle the largest turndown ratios. Typical steam require ments are 0.07 to 0.16 kilogram (kg) steam/kg of oil.
Combination burners can burn 100 percent oil, 1 00 percent gas, or any combination of oil and gas. A burner with this capab ility generally has a si ngle oil nozzle in th e center of a group of gas nozzles. The air needed for combustion can be controlled separately in this type of burner. Another option is to base load the burners with one fuel and to add the other fuel to meet increases in load demand. Combina tion burners add flexibility to the process heater, especially when the composition of the fuel is variable.

The location and number of burners needed fo r a process heater are also determined on an individual basis. Burners can be located on the ceiling, walls, or floor of the combustion chamber. Floor- and wall-fired units are the most common burner types found in process heaters because they are both efficient and flexible. In particular, floor-mounted burners integrate well with the use of combustion air preheat, liquid fuels, and alternate sources of combustion oxygen such as turbine exhaust.
The number of burners in a heater can range from 1 to over 100. In the refinery industry, the average number of burners is estimated at 24 in ND heaters with an average design heat release of 69.4 million Btu per hour (MMBtu/hr). The average number of burners is estimated at 20 in MD heaters with ambient combustion ai r and an average design heat release of 103.6 MMBtu/hr. The average number of burners is estim ated at 14 in MD heaters with combustion air preheat and an average design heat release of 135.4 MMBtu/hr. In general, the smaller the number of burners, the simpler the heater will be. However, multiple burners provide a more uniform temperature distribution.3-1 SECTION 3 PROFILE OF AFFECTED UNITS AND FACILITIES, AND COMPLIANCE COSTS
The floor-level MACT for the regulation will affect existing and new ICI boilers and process heaters that have input capacity greater than 10 million Btus and are fueled by fossil and nonfossil fuel solids and liquids. The economic im pact estimates presented in Section 6 and the small entity screening analysis presented in Section 7 are based on the estimated stock of existing units and the projection of new units through the year 2005. They are also based on the compliance costs associated with applying the final rule to these units. This section begins with a review of the industry distributi on and technical charac teristics of existing boilers and process heaters contained in the Agency’s Inventory Da tabase. It also presents projected growth estimates for boilers and process heaters through the year 2005, a description of how costs are estimated, and the national engineering cost estim ates and cost-effectiveness (cost/ton) estimates by pollutant controlled.

3.1 Regulatory Alternatives Section 112 of the CAA requires EPA to promul gate regulations for the control of HAP emissions from each source category listed under section 112(c). The statute requires the regulations to reflect the maximu m degree of reductions in emissi ons of HAP that is achievable taking into consideration the cost of achieving emissions reducti ons, any nonair quality health and environmental impacts, and energy requirements. This level of control is commonly referred to as MACT. The MACT regulation can be ba sed on the emissions reductions achievable through application of measures, processes, met hods, systems, or techniques including, but not limited to: (1) reducing the volume of, or elim inating emissions of, such pollutants through process changes, substitutions of materials, or other modifications; (2 ) enclosing systems or processes to eliminate emissions; (3) collecti ng, capturing, or treating such pollutants when released from a process, stack, storage or f ugitive emission point; (4) design, equipment, work practices, or operational standards as provided in subsection 112(h) ; or (5) a combination of the above.
For new sources, MACT standards cannot be less stringent than the emission control achieved in practice by the best-controlled sim ilar source. The MACT standards for existing sources can be less stringent than standards for new sources, but they cannot be less stringent than the average emission limitation achieved by the best-performing 12 percent of existing sources for categories and subcategories with 30 or more sources, or the best-performing 5 sources for categories or subcateg ories with fewer than 30 sources.3-2 In essence, these MACT standards would en sure that all major sources of air toxic emissions achieve the level of control already being achieved by the better-controlled and loweremitting sources in each category. This approach provides assurance to citizens that each major source of toxic air pollution will be required to effectively control its emissions. A major source of HAP emissions is any stati onary source or group of statio nary sources located within a contiguous area and under common c ontrol that emits or has the potential to emit any single HAP at a rate of 9.07 Mg (10 tons) or more per y ear or any combination of HAPs at a rate of 22.68 Mg (25 tons) or more a year. At the same time, this approach provides a level economic playing field, ensuring that faci lities that employ cleaner proc esses and good emission controls are not disadvantaged relative to competitors with poorer controls.

3.1.1 Regulatory Background In September 1996, EPA chartered the Indus trial Combustion Coordinated Rulemaking (ICCR) advisory committee under the Federa l Advisory Committee Act (FACA). The committee’s objective was to develop recommenda tions for regulations for several combustion source categories under sections 112 and 129 of the CAA. The ICCR advisory committee, known as the Coordinating Committee, formed S ource Work Groups for the various combustion types covered under the ICCR. One of the work groups was formed to research issues related to boilers. Another was formed to research issues re lated to process heaters. The Boiler and Process Heater Work Groups submitted recommendations, information, and data analysis results to the Coordinating Committee, which in turn considered them and submitted recommendations and information to EPA. The Committee’s recommenda tions were considered by EPA in developing these proposed standards for boilers and process heaters. The Committee’s 2-year charter expired in September 1998.
Following the expiration of the ICCR FACA ch arter, EPA decided to combine boilers with units in the proce ss heater source category covering indirect fired un its, and to regulate both under this NESHAP. This was done because indirect fired process heaters and boilers are similar devices, burn similar fuel, have similar emission ch aracteristics, and emissions from each can be controlled using similar cont rol devices or techniques.

3.1.2 Regulatory Authority Section 112 of the CAA requires that EPA promulgate regulat ions requiring the control of HAP emissions from major sources and certain area sources. The control of HAP is achieved through promulgation of emission standards under sections 112(d) and (f) and, in appropriate circumstances, work practice standa rds under section 112(h) of the CAA.3-3 An initial list of categories of major and ar ea sources of HAP select ed for regulation in accordance with section 112(c) of the CAA was published in the Federal Register on July 16, 1992 (57 FR 31576). Industrial boilers, commercial and institutional boilers, and process heaters are three of the listed 174 categories of sour ces. The listing was based on the Administrator’s determination that they may reasonably be antici pated to emit several of the 188 listed HAP in quantities sufficient to designate them as major sources.
This rule affects industrial boilers, ins titutional and commercial boilers, and process heaters. In this rule process heaters are defi ned as units in which the combustion gases do not directly come into contact with process gases in the combustion chamber (e.g., indirect fired). Boiler means an enclosed device using contro lled flame combustion and having the primary purpose of recovering thermal energy in the form of steam or hot water. A waste heat boiler (or heat recovery steam generator) is a device that recovers normally unused energy and converts it to usable heat. Waste heat boilers are excluded fr om this rule. A hot water heater is a closed vessel in which water is heated by combustion of gaseous fuel and is withdrawn for use external to the vessel at pressures not exceeding 160 psig. Hot water heaters are excluded from this rule.
Boilers and process heaters emit particul ate matter, volatile organic compounds, and hazardous air pollutants, depending on the material burned. Solid and liquid fuel-fired units emit metals, halogenated compounds and organic compounds. Gas fuel-fired units emit mostly organic compounds.

The affected source is each individual industr ial, commercial, or institutional boiler or process heater located at a major facility. The affected source does not include units that are municipal waste combustors (40 CFR part 60, subparts AAAA, BBBB or Cb), medical waste incinerators (40 CFR part 60, subpart Ce and Ec ), fossil fuel fired electric utility steam generating units, commercial and industrial so lid waste incineration units (40 CFR part 60 subparts CCCC or DDDD), recovery boilers or furnaces (40 CFR part 63, subpart MM), or hazardous waste combustion units required to have a permit under section 3005 of the Solid Waste Disposal Act or are subject to 40 CF R part 63, subpart EEE.
The rule applies to an owner or operate a boiler or process heater at a major source meeting the requirements in section II.C. A majo r source of HAP emissions is any stationary source or group of stationary sources locat ed within a contiguous area and under common control that emits or has the pot ential to emit any single HAP at a rate of 9.07 Mg (10 tons) or more per year or any combination of HAP at a rate of 22.68 Mg (25 tons) or more a year.3-4 An affected operator must meet the emission limits for the subcategories in Table 3-1 of this preamble for each of the pollutants liste d. Emission limits were developed for new and existing sources; and for large, small, and limited use solid, liquid, and gas fuel fired units. Large units are those with heat input capacities greate r than 10 MMBtu/hr. Sma ll units are those with heat input capacities less than or equal to 10 MMBtu/hr. Limited use units are those with capacity utilizations less than or equal to 10 percent as required in a federally enforceable permit.
If your new or existing boiler or process heat er is permitted to burn a solid fuel, or any combination of solid fuel with liquid or gaseous fu el, the unit is in one of the solid subcategories. If your new or reconstructed boiler or process he ater burns a liquid fuel , or a liquid fuel in combination with a gaseous fuel, the unit is in one of the liquid subcategories. If your new or existing boiler or process heater burns a gaseous fuel only, the unit is in the gas subcategory and is not required to meet any emission limit.
For solid fuel-fired boilers or process heater s, we are allowing s ources to choose one of two emission limit options: (1) ex isting and new affected sources may choose to limit PM emissions to the level listed in Table 3-1 or (2 ) existing and new affected sources may choose to limit total selected metals emissions to the level listed in Table 3-1 of this preamble.
If you do not use an add-on control or use an add-on control other than a wet scrubber, you must maintain opacity level to less than or equal to the level established during the compliance test for mercury and PM or total selected metals, and maintain the fuel chlorine content to less than or equal to the operating level established during the HCl compliance test.
If you use a wet scrubber, you must maintain the minimum pH, pressure drop and liquid flowrate above the operating levels es tablished during the performance tests.
If you use a dry scrubber, you must maintain opacity level and the minimum sorbent injection rate established during the performance test.
If you use an ESP in combination with a wet scrubber and cannot monitor the opacity, you must maintain the average s econdary current and voltage or total power input established during the performance test.3-5 Table 3-1. Emission Limits for Boil ers and Process Heaters (lb/MMBtu)

Source Subcategory PM or Total Selected Metals HC1 Mercury (Hg) Carbon Monoxide (CO-ppm @ 3% oxygen) Solid Fuel, Large Unit 0.04 or 0.00007 0.016 0.0000026 200 Solid Fuel, Small Unit 0.04 or 0.00007 0.032 0.0000026 — Solid Fuel, Limited Use 0.04 or 0.00007 0.032 0.0000026 200 Liquid Fuel, Large Unit 0.068 — 0.00045 200 Liquid Fuel, Small Unit 0.068 — 0.0009 — — Liquid Fuel, Limited Use 0.068 — 0.0009 — 200 New Boiler or Process Heater

Gaseous Fuel, Large Unit — — — — 200 Gaseous Fuel, Small Unit — — — — Gaseous Fuel, Limited Use — — — — 200 Solid Fuel, Large Unit 0.062 or 0.001 0.048 0.000004 — Solid Fuel, Small Unit — — — — —
Solid Fuel, Limited Use 0.21 or 0.001 — — — Liquid Fuel, Large Unit

— — — — — Liquid Fuel, Small Unit — — — — — Liquid Fuel, Limited Use — — — — — Existing Boiler or Process Heater

Gaseous Fuel — — — — —

There is an alternative compliance procedur e and operating limit for meeting the total selected metals emission limit option. If you have no control or do not want to take credit of metals reductions with your exis ting control device, and can show that total metals in the fuel would be less than the metals emission level, th en you can monitor the metals fuel analysis to meet the metals emissions limitations. Similarly, if you have no control or do not want to take credit of mercury reduction with your existing control device, and can show that mercury in the fuel would be less than the mercury emission level, then you can monitor the mercury fuel analysis to meet the mercury emission limitations.3-6 3.1.3 Regulatory Alternatives and Control Technologies

3.1.3.1 MACT Floor Development We considered several approaches to iden tifying MACT floor for existing industrial, commercial, and institutional boilers and process heaters. First, we considered using emissions data on boilers and process heaters to set the MA CT floor. However, after review of the data available, we determined that emissions inform ation was inadequate to set MACT floors. We then considered using State regulations and perm its to set the MACT floors. However, we found no State regulations or State permits which specifi cally limit HAP emissions from these sources.
Consequently, we concluded that the only r easonable approach for determining MACT floors is to base it on control technology. Info rmation was available on the control technologies employed by the population of bo ilers identified by the EPA. We considered several possible control technologies (i.e., factors that influence emissions), including fuel substitution, process changes and work practices, and add-on control technologies.
We first considered whether fuel switching would be an appropriate control option for sources in each subcategory. Both fuel switching to other fuels us ed in the subcategory and fuels from other subcategories were considered. Th is consideration included determining whether switching fuels would achieve lo wer HAP emissions. A second cons ideration was whether fuel switching could be technically done on boilers and process heaters in the subcategory considering the existing design of boilers and process heaters. We also considered the availability of the alternative fuel.
After considering these factors, we determined that fuel switching was not an appropriate control technology to be include d in determining the MACT fl oor level of control for any subcategory. This decision was based on the ove rall effect of fuel sw itching on HAP emissions, technical and design considerations discussed in section III.A of this preamble, and concerns about fuel availability.

Based on the data available in the emissions database, we determined that while fuel switching from solid fuels to gaseous or liqui d fuels would decrease PM and some metals emissions, emissions of some organic HAP would al so increase, resulting in uncertain benefits. We determined that it would be inappropriate in a MACT rulemaking, that is technology based, to consider a technology that pote ntially will result in an incr ease in a HAP regardless of its potential to reduce other HAP wit hout determining the overall benefit. Determining the benefits of fuel switching would require an assessment of the risk associated which each HAP emitted3-7 and a determination of which fuel results in the overall lower risk taking into account the available control technology for each fuel. This assessment will be performed in a future rulemaking.

A similar determination was made when cons idering fuel switching to “cleaner” fuels within a subcategory. For example, the term “clean coal” refers to coal that is lower in sulfur content and not necessarily lowe r in HAP content. Data gather ed by EPA also indicates that within specific coal types HAP content can va ry significantly. Switching to a “clean coal” may increase emissions of some HAP. Therefore, fuel switching to a “c leaner” coal would not be an appropriate option. Fuel switching from coal to biomass would result in similar impacts on HAP emissions. While metallic HAP emissions would be reduced, emissions of organics would increase based on information in the emissions database.
Another factor considered was the availability of alternative fuels. Natural gas pipelines are not available in all regions of the U.S., and natural gas is simp ly not available as a fuel for many industrial, commercial, and institutional boil ers and process heaters. Moreover, even where pipelines provide access to natural gas, suppl ies of natural gas may not be adequate. For example, it is common practice in cities during wi nter months (or periods of peak demand) to prioritize natural gas usage for residential areas before industrial usage. Requiring EPA regulated combustion units to switch to natural gas woul d place an even greater strain on natural gas resources. Consequently, even where pipelines ex ist some units would not be able to run at normal of full capacity du ring these times if shortages were to occur. Therefore, under any circumstances, there would be some units that co uld not comply with a re quirement to switch to natural gas.
Similar problems for fuel switching to bi omass could arise. Existing sources burning biomass generally are combusting a recovered mate rial from the manufacturing or agriculture process. Industrial, commercial, and institutional facilities that are not associated with the wood products industry or agriculture may not have access to a suffici ent supply of biomass materials to replace their fossil fuel.
There are many concerns with switching fuels on sources designed and operated to burn specific fuels. Changes to the fuel type (solid, liquid, or gas) will require extensive changes to the fuel handling and feeding system (e.g., a st oker using wood as fuel would need to be redesigned to handle fuel oil or gaseous fuel ). Additionally, burners and combustion chamber designs are generally not capable of handling different fuel types, and generally cannot accommodate increases or decreases in the fuel volume and shape. Design changes to allow3-8 different fuel use, in some cases, may reduce the capacity and efficiency of the boiler or process heater. Reduced efficiency may result in a greater degree of incomplete combustion and, thus, an increase in organic HAP emissions. For the r easons discussed above, we decided that fuel switching to “cleaner” solid fuels or to liquid or gaseous fuels would not be appropriate or available as a MACT floor level.
We also determined that using process change s or work practices were not appropriate in developing MACT floors. HAP emissions from boilers and process heaters are primarily dependent upon the composition of the fuel. Fuel dependent HAP are meta ls, including mercury, and acid gases. Fuel dependent HAP are typicall y controlled by removing them from the flue gas after combustion. Therefore, they are not aff ected by the operation of the boiler or process heater. Consequently, process changes would be ineffective in reducing these fuel-related HAP emissions.
On the other hand, organic HAP can be formed from incomplete combustion of the fuel. Data are not available that de finitively show that organic HAP emissions are related to the operation of the boiler or process heater. Some studies indicate that organic HAP are greatly influence by time, turbulence and temperature. Other studies indica te that organic HAP emissions are not affected by the operation of the unit. The measurement of CO is generally an indicator of incomplete combustion since CO w ill burn to carbon dioxide if adequate oxygen is available. Correcting incomplete combusti on may be accomplished through providing more combustion air. Therefore, we consider monitori ng and maintaining CO emission levels to be associated with minimizing organic HAP emissi on levels and, thus, CO monitoring would be a good indicator of combustion effici ency and organic HAP emissions.
In summary, we determined that consideri ng process changes and work practices would not be appropriate in developing MACT floors for existing units. We are requesting comment, and information on emission reductions, on whether there are other GCP pract ices that would be appropriate for minimizing organi c HAP emissions from industrial, commercial, and institutional boilers and process heaters.
Consequently, we concluded that add-on c ontrol technology is the only factor that significantly controls HAP emissions.

In order to determine the MACT floor base d on add-on control technologies, we first examined the population database of existing sour ces. Units not meeting the definition of an industrial, commercial, or institu tional boiler or process heater, a nd units located at area sources3-9 were removed from the database. The remaining un its were divided first into three subcategories based on fuel state: gaseous fuel-f ired, liquid fuel-fired, and solid fuel-fired units. Each of these three subcategories was then fu rther divided into subcategorie s based on capacity: (1) large boilers and process heaters (un its with heat inputs greater th an 10 MMBtu/hr); (2) small units (with a maximum rated heat input capacity of 10 MMBtu/hr or less); and (3) limited use units with capacity utilizati on less than 10 percent.
We identified the types of air pollution cont rol techniques currently used by existing boilers and process heaters in each subcategory. We ranked those controls according to their effectiveness in removing the different categories of pollutants; including metallic HAP and PM, inorganic HAP such as acid gases, mercury, a nd organic HAP. The EPA ranked these existing control technologies by incorpor ating recommendations made by the ICCR, and by reviewing emissions test data, previous EPA studies, and ot her literature, as well as by using engineering judgment.
Based upon the emissions reduction potential of existing air pollution control techniques, we listed all the boilers and pr ocess heaters in the population da tabase in order of decreasing control device effectiveness for each subcateg ory. Then the technology basis of the existingsource MACT floor was determined for each pollutant category by identifying the bestperforming 12 percent of units. We then selected the technology us ed by the median unit in the best performing 12 percent of units (i.e., the boi ler or process heater unit representing the 94th percentile) as the technology associated with the MACT floor level of control for each subcategory. As previously described, emissions da ta for this category is insufficient to identify the best-performing units. The most appropriate way to identify the average emission limitation achieved by the best-performing 12 percent of exis ting sources is to identify the technology used by the unit in the middle of the range of the best performing 12 percent of units, i.e., the median unit).
After establishing the technology basis for the existing source MACT floor for each subcategory and each type of pollutant, the EP A examined the emissions data available for boilers and process heaters controlled by thes e technologies to determine achievable emission levels. The resulting emission levels associated with the existing source MACT floors for each pollutant are based on the average of the lowest th ree run average test data from units using the technology associated with the MACT floor leve l of control, and by incorporating operational variability using results from multiple tests on these best performing units. This approach reasonably ensures that the emission limit selected as the MACT floor represents a level of control that can be consiste ntly achieved by a uni t in the subcategor y using the control3-10 technology associated with the MACT floor. This approach is reasonable because the most informative way to predict the worst reasonably foreseeable performance of the best-controlled units, with available data, is to examine the available long-term perf ormance of the best performing units that had multiple test results. In other words, the EPA considers all units with the same control technology that is properly designed and operated to be equally well controlled, even if the emission test results fr om such units vary considerably.
The level of control “achieved” by the averag e of the top performing 12 percent of units is best represented by the aver age emissions observed from all units using the same technology as that employed by the unit representi ng the median of the top 12 percent.

The EPA’s review of emissions data indica tes that some boilers and process heaters within each subcategory may be able to meet the floor emission levels without using the air pollution control technology that is associated with the MACT fl oor. This is to be expected, given the variety of fuel types, fuel input rates, and boiler designs included within each subcategory and the resulting vari ability in emission rates. Thus, for instance, boilers or process heaters within the large unit solid fuel subcateg ory that burn lower percentages of solid fuels may be able to achieve the emission levels for the large unit solid fuel subcategory without the need for additional control devices.
Furthermore, solid fuels, especially coal , are very heterogeneous and can vary in composition by location. Coal analysis data obtaine d from the electric utility industry in another rulemaking contained information on the mercury, ch lorine, and ash content of various coals. A preliminary review of this data indicate that the composition can vary gr eatly from location to location, and also within locati on. Based on the range of variati on of mercury, chlorine, and ash content in coal, it is possible for a unit with a lower performing control system to have emission levels lower than a unit considered to be included in the best performing 12 percent of the units.

This situation is reflected in the emissions information used to set the MACT floor emission limits. In some instances there are boile rs with ESP’s or other controls that achieve similar, or lower, outlet emission levels of non- mercury metallic HAP, PM, or mercury to fabric filters. In most cases, this is due to concentrations entering these other control devices being lower, even though the percent reduction ach ieved is lower than fabric filters.
Additionally, the design of some control devices may have a substantial effect on the their emission reduction capability. For example, fabric filters are largely insensitive to the physical characteristics of the inlet gas stream. Thus, their de sign does not vary widely, and3-11 emissions reductions are expected to be similar (e.g., 99 percen t reduction of PM). However, ESP design can vary significantly.
Consequently, since fuel substitution has b een determined not to be an appropriate MACT floor control technology, EPA still considers th e fabric filter to be the best-performing control for non-mercury metallic HAPs, PM, and mercury and only emissions information for fabric filters was used to develop emission lim its. A detailed discussi on of the MACT floor methodology is presented in the memorandum “MACT Floor Analysis for New and Existing Sources in the Industrial, Comm ercial, and Institutional Boiler s and Process Heaters Source Categories” in the docket.
Existing Solid Fuel Boilers and Process Heat ers Large Units-Heat Inputs Greater than 10 MMBtu/hr . The most effective cont rol technologies identifie d for removing non-mercury metallic HAP and PM are fabric filters. About 14 percent of solid fuel-fired boilers and process heater use fabric filters. Because this is the technology used by the 94th percentile (the median of the best-performing 12 percent), the EPA considers a fabric filter to be the technology basis for the MACT floor for non-mercury metallic HAP c ontrol for existing boiler s and process heaters in this subcategory.
The most effective control technologies id entified for removing inorganic HAP that are acid gases, such as hydrogen chloride, are we t scrubbers and packed bed scrubbers. These technologies are used by about 12 percent of the boilers and process heat ers in the solid fuel subcategory. About 10 percent of solid-fired boilers and process heaters use wet scrubbers, and approximately 1 percent use packed bed scr ubbers. Because wet scr ubbers are the technology used by the 94th percentile (media n of the best-performing 12 pe rcent), the EPA considers a wet scrubber to be the technology basis for the MACT floor for acid gas control for existing boilers and process heaters in the solid fuel subcateg ory. The MACT floor emission level based on wet scrubbers and incorporating operationa l variability is 0.048 lb HCl/MMBtu.
Based on test information on utility boilers, we have concluded that fabric filters are most effective in controlling mercury, and units having them would constitute the best controlled mercury sources. As discussed previously, more than 6 percent of sour ces in the subcategory have fabric filters. The MACT floor emission le vel based on fabric f ilters and incorporating operational variability is 0.000004 lb mercury/MMBtu.
For organic HAP, we assessed whether mainta ining and monitoring CO levels would be part of the MACT floor, and determ ined that less than 6 percent of the units in this subcategory3-12 do so. Therefore, we concluded the MACT floor for existing sources in this subcategory is no emissions reductions for organic HAP.
Therefore, the EPA determined that the combination of fabric filter and wet scrubber control technologies forms the basis for the MACT floor level of control for existing solid fuel boilers or process heaters in this subcategor y. We recognize that some boilers and process heaters that use technologies ot her than those used as the basis of the MACT floor can achieve the MACT floor emission levels. For example, em ission test data show that many boilers with well-designed and operated ESP can meet the MACT floor emission levels for non-mercury metallic HAP and PM, even though the floor emission level for these pollutants is based on a fabric filter (however, we would not expect that all units using ESP would be able to meet the proposed rule).
Small Units—Heat Inputs Less than or Equal to 10 MMBtu/hr . Less than 6 percent of the units in this subcategory used control techniques that woul d reduce non-mercury metallic HAP and PM, mercury, and inorganic HAP, such as HCl. Also, maintaining and monitoring CO levels was used by less than 6 percent of the units in the subcategory.
Therefore, we determined that the MACT fl oor emission level for existing units for any of the pollutant categories in this subcategory is no emissions reductions.
Limited Use Units—Capacity Utilizations Less than or Equal to 10 Percent . The most effective control techno logies identified for removing non-mercury metallic HAP and PM are ESP and fabric filters. Less than 2 percent of soli d fuel-fired boilers and process heater in this subcategory use fabric filters, and 14 percent us e ESP. Because ESP are the technology used by the 94th percentile (the median of the best-performing 12 percent) , the EPA considers an ESP to be the technology basis for the MACT floor for non-mercury metallic HAP control for existing boilers and process heaters in th e solid fuel subcategory. A PM level is set as a surrogate for nonmercury metallic HAP control. The MACT floor emission level based on ESPs, considering operational variability, is 0.021 lb PM/MMBtu. We are also providi ng an alternativ e metals limit of 0.001 lb metals/MMBtu which can be used to show compliance in cases where metal HAP emissions are low in proportion to PM emissions.
Similar control technology analyses were done for the boilers and process heaters in this subcategory for the other pollutant groups of interest, including inor ganic HAP, organic HAP and mercury. Less than 6 percent of the units in th is subcategory have cont rols that would reduce emissions of organic HAP, mercur y, and inorganic HAP, so the existing source MACT floor for3-13 those pollutants is no emissions reductions. Th erefore, we determined that ESP control technology, which achieves non-mercury metallic HAP and PM control forms the basis for the MACT floor level of control for existing solid fuel boilers and process heaters in this subcategory.
Existing Liquid Fuel Boilers and Process Heaters . Emissions data for liquid subcategories was inadequate to identify the be st-performing sources for reasons described in section D of the preamble. We also found no State regulations or permits which specifically limit HAP emissions from these sources. Therefore, we examined control tec hnology data to identify a MACT floor. We found that less than 6 percent of the units in each of the liquid subcategories used control techniques that would reduce non- mercury metallic HAP and PM, mercury, organic HAP, or inorganic HAP (such as HCl). Therefore, we determined that the control technique associated with the 94th percentil e (the median of the best-perfo rming 12 percent) could not be identified.
Therefore, we are unable to identify the be st performing 12 percent of units in the subcategories. In light of this analysis, we concluded the MACT floor for existing sources in these liquid subcategory is no emissions reduc tions for non-mercury metallic HAP, mercury, inorganic HAP, and organic HAP.
Existing Gaseous Fuel Boilers and Process Heaters . Emissions data for gas subcategories was inadequate to identify the best-performing so urces for reasons described in section D of the preamble. We also found no State regulations or permits which specifically limit HAP emissions from these sources. Therefore, we examined c ontrol technology data to identify a MACT floor. We found that no existing units in the gaseous fuel-fired subcategories were using control technologies that achieve consistently lower emi ssion rates than uncontroll ed sources for any of the pollutant groups of interest. Therefore, we are unable to identify the best performing 12 percent of units in the subcateg ories. Consequently, the EPA dete rmined that no existing source MACT floor based on control tec hnologies could be identified for gaseous fuel-fired units. Therefore, we concluded the MACT floor for existing sources in this subcategory is no emissions reductions for non-mercury metallic HAP, mercury, inorganic HAP, and organic HAP.

3.1.3.2 Consideration of Options Beyond the Floor for Existing Units Once the MACT floor determinations were done for each subcategory, the EPA considered various regulatory optio ns more stringent than the MACT floor level of control (i.e., technologies or other work prac tices that could result in lowe r emissions) for the different subcategories.3-14 Maintaining and monitoring CO levels was id entified as a possible control for organic HAPs. However, less than 6 percent of the source s in the existing source subcategories used this control method and it was not cons idered the MACT floor control technology. We then looked at it as an above-the-floor option. However, info rmation was not available to estimate the HAP emissions reductions that would be associated with CO monitoring and emission limits. This option would also require a high co st to install and operate CO m onitors. Given the cost and the uncertain emissions reductions th at might be achieved, we chose to not require CO monitoring and emission limits as MACT.
The following sections discuss the above-the-floor options an alyzed to control emissions of metallic HAP, mercury, and inorganic HAP. Based on the analysis described in these sections, the EPA decided to not go beyond the MACT floor level of control for the proposed rule for any of the subcategories of existing sources.
Existing Solid Fuel Units . Large Units—Heat Inputs Greater than 10 MMBtu/hr . Besides fuel switching (see section III.D of this preamble) , we identified a better designed and operated fabric filter (the MACT floor for new units) as a control technology that could achieve greater emissions reductions of metallic HAP and PM emi ssions than the MACT floor level of control (i.e., a typical existing fabric filter). Conseque ntly, the EPA analyzed the emissions reductions and additional cost of adopting an emission limit representative of the pe rformance of a unit with a better designed and operated fabric filter. The additional annualized cost to comply with this emission limit was estimated to be approxima tely $500 million with an additional emission reduction of approximately 100 tons of metallic HAP . The results indicated that while additional emissions reductions would be realized, the cost s would be too high to consider it a feasible above the floor option. Non-air qua lity health, environmental imp acts, and energy effects were not significant factors, because th ere would be little difference in the non-air quality health and environmental impacts of replacing existing fabric filters with improved performance fabric filters. Therefore, we did not select these cont rols as MACT. Fuel switching was not considered a feasible beyond-the-floor option for the same r easons described in section III.E of the proposal preamble.
We identified packed bed scrubbers as a c ontrol technology that could achieve greater emissions reductions of inorganic HAP, like HCl, than the MACT floor level of control (i.e., a wet scrubber). Consequently, the EPA analyzed th e emissions reductions a nd additional cost of adopting an emission limit representative of the performance of a unit with a packed bed scrubber. The additional annualized cost to comply with this emission limit (using a packed bed scrubber) was estimated to be approximately $900 million with an additional emission reduction3-15 of approximately 20,000 tons of HCl. The resu lts indicated that while additional emissions reductions would be realized, the costs would be t oo high to consider it a f easible above the floor option. Non-air quality h ealth, environmental impacts, and en ergy effects were not significant factors, because there would be little differen ce in the non-air quality h ealth and environmental impacts between packed bed scrubbers and wet sc rubbers. Therefore, we did not select these controls as MACT.
In reviewing potential regul atory options for existing sources, the EPA identified one existing industrial boiler that was using a techno logy, carbon injection, used in other industries to achieve greater control of mercury emissions than the MACT floor level of control. However, emission data indicated that this unit was not achieving merc ury emission reductions. The EPA does not have information that would show carbo n injection is effective for reducing mercury emissions from industrial, commercial, and institu tional boilers and process heaters. Therefore, carbon injection was not evalua ted as a regulatory option.
However, the EPA requests comments on whet her carbon injection shou ld be considered as a beyond-the-floor option and whether existing industrial, commercial, or institutional boilers and process heaters could use carbon injecti on technology, or other co ntrol techniques to consistently achieve mercury emissi on levels that are lower than levels from similar sources with the MACT floor level of control. The EPA is aw are that research continues on ways to improve mercury capture by PM controls, sorbent inject ion, and the development of novel techniques. The EPA requests comment and information on the e ffectiveness of such c ontrol technologies in reducing mercury emissions.
Small Units—Heat Inputs Less than or Equal to 10 MMBtu/hr . The EPA could not identify a technology-based level of control for the MACT floor for this subcategory. To control non-mercury metallic HAP and mercury, we analyzed the above the floor opti on of a fabric filter which was identified as the most effective c ontrol device for non-mercury metallic HAP and mercury. To control inorganic HAP such as hydrog en chloride, we analyzed the above the floor option of a wet scrubber si nce it was identified as the least cost option.
The total annualized cost of complying with the fabric filter option was estimated to be $10 million, with an estimated emission reduction of 1.9 tons per year of non-mercury metallic HAP and 0.003 tons of mercury. The annualized cost of complying with the wet scrubber option was estimated to be $11 million, with an emission reduction of 48 per year of HCl. The results of this analysis indicated that while additional em issions reductions could be realized, the costs would be too high to consider them feasible options. Therefore, we did not select these controls3-16 as MACT. Non-air quality healt h, environmental impacts, and en ergy effects were not significant factors.
Limited Use Units—Capacity Utilizations Less than or Equal to 10 Percent . The MACT floor level of control for this subcategory fo r non-mercury metallic HAP control is an ESP. Although fabric filters were identified as being more effective, many ESP can achieve similar levels. Any additional emission reduction from usi ng a fabric filter would be minimal and costly considering retrofit costs for exis ting units that already have ESP. Therefore, an above-the-floor option for metallic HAP was not analyzed in detail , and we did not select fabric filters as MACT. However, an above the floor option of a fabric f ilter was analyzed for me rcury control. The total annualized costs of the fabric filter option was es timated to be an additional $21 million, with an estimated emission reduction of 0.04 tons of mercury.
The EPA could not identify a technology-based level of control for the MACT floor for inorganic HAP in this subcategor y. To control inorganic HAP, we analyzed the above-the-floor option of a wet scrubber si nce it was identified as the least cost option. The total annualized costs of the wet scrubber option was estimated to be $49 million, with an estimated emission reduction of 463 tons per year of HCl.
The results of the above the floor options analyses indicated that while additional emissions reductions could be real ized, the costs would be too hi gh to consider them feasible options. Therefore, we did not select these controls as MACT. Non-air quality health, environmental impacts, and energy effects were not significant factors.
Existing Liquid Fuel Units . For the liquid fuel subcategorie s, the EPA could not identify a technology-based level of control for the MA CT floor. For beyond-the-floor options for the liquid subcategory, the EPA identified several PM controls (e.g., fabric filters, electrostatic precipitators, and venturi scrubbers) that w ould reduce non-mercury metallic HAP emissions. For the above-the-floor analysis, we analyzed the cost and emission reduction of applying a high efficiency PM control device, such as a fabric filter, since these would be more likely to be installed for units firing liqui d fuel. We identified wet scr ubbers as a technology option beyond the floor for reduction of inorganic HAP, such as HCl. We identified fabric filters as a technology option beyond the floor for reduction of mercury. Consequently, the EPA analyzed the emissions reductions and addi tional cost of applying high e fficiency PM controls and wet scrubbers on liquid fuel-fired units. The additiona l total annualized cost of a high efficiency PM control device (such as a fabric filter) was es timated to be $460 million, with an additional estimated emission reduction of 1,500 tons per y ear for non-mercury metallic HAP and 3 tons3-17 per year for mercury. The annualized cost of a we t scrubbers was estimated to be an additional $480 million, with an additional HCl reduction of 30 tons per year. The results indicated that while additional emissions reductions would be real ized, the costs would be too high to consider them feasible options. Non-air quality health, environmental impacts, and energy effects were not significant factors. Therefore, the EPA chos e to not select these controls as MACT for existing liquid units.
Existing Gas-fired Units . For the gaseous fuel subcategories, the EPA could not identify a technology-based level of control for the MACT floor. The great majority, if not all, of the emissions from gas-fired units are organic HAP. As discussed in section III.E of the preamble, CO monitoring and emission limits were consider ed as an above the floor option but was not selected as MACT given the costs and uncertain reductions achieved. Therefore, no above the floor control technique was anal yzed for organic HAPs, and MA CT is no emission reduction of non-mercury metallic HAP and mercur y, inorganic HAP, and organic HAP.
Fuel Switching as a Beyond-the-floor Option . For the solid fuel and liquid fuel subcategories, fuel switching to natural gas is a regulatory option more stringent than the MACT floor level of control that would reduce mercury, metallic HAP, and inorganic HAP emissions. We determined that fuel switching was not an ap propriate above-the-floor option for the reasons discussed in sections III.A a nd III.D of this proposal preamble. In some cases, organic HAP would be increased by fuel sw itching. Additionally, the estimat ed emissions reductions that would be achieved if solid and liquid fuel units switched to natural gas were compared with the estimated cost of converting exis ting solid fuel and liquid fuel un its to fire natural gas. The annualized cost of fuel switching was estimated to be $12 billion. The additional emission reduction associated with it was estimated to be 1,500 tons per year for metallic HAP, 11 tons per year for mercury, and 13,000 tons per year for inorganic HAP. Additional detail on the calculation procedures is provided in the me morandum “Development of Fuel Switching Costs and Emissions reductions for Industrial, Comm ercial, and Institutional Boilers and Process Heaters” in the docket.

3.1.3.3 EPA Response to Recent Court Decisions in Developing the Emission Limitations In developing the emission limitations, we tr ied to be responsive to the recent court decisions from National Lime Association v. EPA and Cement Kiln Recycling Coalition v. EPA , regarding the methodology used for determining th e MACT floor. In response, we determined that the most acceptable and appropriate approach for determining the MACT floor appears to be using only emission data. As disc ussed and explained in section II.E of the proposal preamble,3-18 we determined that for these source categories and the subcategories esta blished the use of only the available emission data would be inappropria te for determining the MACT floor for existing and new units. If only the available emission data (from a population of units that is deemed unrepresentative) is used, the resulting MACT floor emission levels would be, in most many cases, unachievable. This is because the concen tration of HAP (metals, HCl, mercury) vary greatly within each fuel type. Some even have fuel analysis levels be low the detection limit. Therefore, some units without a ny add-on controls have emission levels below those with add-on controls. Section III.E of the proposal preamble e xplains in more detail the approach used to develop the MACT floors for each subcategory a nd why the approach is appropriate for the subcategories regulated by this rule and w hy the mandating of fuel choice (using low HAPcontaining fuel) is also inappropriate.
In terms of subcategorizing, the main difficulty of establishing a separate subcategory for each specific fuel type is that many industrial boilers burn a combination of fuels. Determining which subcategory applies if the mixture varies would be problematic. Would the applicable emission limits change each time the fuel mixture changes? How would compliance be determine and how would continuous compliance be monitored? Because of these concerns, EPA chose not to further subcategori ze sources by each specific fuel type.
However, if we were to further subcategorize solid-fuel units into separate fossil and nonfossil subcategories, we would first determine if the MACT floor could be developed, for either subcategory, based on emissions information. If not, then we would look at developing MACT floors based on control technologi es. First we would determine if fuel switching or work practices could be used. Based on the MACT floor analysis for solid-fuel fired boilers, it is expected that emissions information and fuel sw itching would not be appropriate to develop the MACT floors for a solid fossil or solid non-foss il subcategory. Similarly, there would be an insufficient number of boilers or process heaters that would be meeting CO limits to set a level for existing units. However, new units would like ly be subject to a CO limit and monitoring.

In order to determine the MACT floor base d on add-on control technologies, we would follow similar procedures described in section III.E of the preamble. We would examine the population database of existing sources and subc ategorize solid fossil and non-fossil fuel fired boilers into each of the following three subcateg ories based on capacity: (1) large boilers and process heaters (units with h eat inputs greater than 10 MMBtu /hr); (2) small units (with a maximum rated heat input capacity of 10 MMBtu/h r or less); and (3) li mited use units with capacity utilization less than 10 percent.3-19 We would identify the types of air pollution c ontrol techniques curr ently used by existing boilers and process heaters in e ach subcategory. Then we would ra nk those controls according to their effectiveness in removing th e different categories of polluta nts; including metallic HAP and PM, inorganic HAP such as acid gases, mercury, and organic HAP.
Based upon the emissions reduction potential of existing air pollution control techniques, we would list all the boilers and process heaters in the population da tabase in order of decreasing control device effectiveness for each subcateg ory. Then the technology basis of the existing source MACT floor would be determined for ea ch pollutant category by identifying the bestperforming 12 percent of units. We would then selected the technology used by the median unit in the best performing 12 percent of units (i.e., the boiler or process heat er unit representing the 94th percentile) as the technology associated wi th the MACT floor level of control for each subcategory.
After establishing the technology basis for the existing source MACT floor for each subcategory and each type of pollutant, we w ould examine the emissions data available for boilers and process heaters controlled by thes e technologies to determine achievable emission levels. The resulting emission levels associated with the existing source MACT floors for each pollutant would be based on the average of the lo west three run average test data from units using the technology associated w ith the MACT floor level of control, and by incorporating operational variability using results from multiple tests on these best performing units.
The preliminary MACT floor control technology for solid fossil-fuel fired units would be a combination of a fabric filter and a scrubber. The preliminary MACT floor control technology for solid non-fossil-fuel fired units would be a combination of an ESP and a scrubber.

3.1.3.4 How did EPA Determine the Emission Limitations for New Units? All standards established pursuant to sect ion 112 of the CAA must reflect MACT, the maximum degree of reduction in emissions of air pollutants that the Administrator, taking into consideration the cost of achieving such emissions reductions, and any non- air quality health and environmental impacts and energy requirements, determines is achievable for each category. The CAA specifies that the degree of reduction in emissions that is deemed achievable for new boilers and process heaters must be at least as stringent as the emissions control that is achieved in practice by the best-controlled similar unit. Ho wever, the EPA may not c onsider costs or other impacts in determining the MACT floor. The EP A may require a control option that is more stringent than the floor (beyond-the-floor) if the Administrator considers the cost, environmental, and energy impacts to be reasonable.3-20 Determining the MACT floor for New Units . Similar to the MACT floor process used for existing units, we considered several approaches to identifying MACT floors for new industrial, commercial, and institutional boilers and process heaters. First, we considered using emissions data on boilers and process heaters to set the MA CT floor. However, after review of the data available, we determined that emissions inform ation was inadequate to set MACT floors. We also reviewed State regulations and permits for these sources, but found no State regulations or State permits which specifical ly limit HAP emissions from industrial, commercial, and institutional boilers and process heaters.
Consequently, we concluded that the only r easonable approach for determining MACT floors is to base it on control technology. Data were available on the control technologies employed by the population of bo ilers identified by the EPA. We considered several possible control technologies (i.e., factors that influence emissions), including fuel substitution, process changes and work practices, and add-on control technologies.
We first considered whether fuel switching would be an appropriate control option for sources in each subcategory. Both fuel switching to other fuels us ed in the subcategory and fuels from other subcategories were considered. Th is consideration included determining whether switching fuels would achieve lo wer HAP emissions. A second cons ideration was whether fuel switching could be technically done on boilers and process heaters in the subcategory considering the existing design of boilers and process heaters. We also considered the availability of the alternative fuel.
As discussed in section III.D of the proposal preamble, based on the data available in the emissions database, we determined that while fuel switching would decrease some HAPs, emissions of some organic HAPs would increase, re sulting in uncertain benefits. We determined that it would be inappropriate in a MACT rule making, that is technology based, to consider a technology that potentially will result in an increase in a HAP regardless of its potential to reduce other HAP without determining the overall benefit. A detailed disc ussion of the consideration of fuel switching is discussed in proposal preamble section III.D.
We also determined that using process change s or work practices were not appropriate in most cases for developing MACT floors. HAP em issions from boilers and process heaters are primarily dependent upon the comp osition of the fuel. Fuel depende nt HAP are metals, including mercury, and acid gases. Fuel dependent HAP ar e typically controlled by removing them from the flue gas after combustion. Therefore, they ar e not affected by the ope ration of the boiler or process heater. Consequently, process changes w ould be ineffective in reducing their emissions.3-21 The exception to this conclusion is monitoring and maintaining CO levels. The measurement of CO is generally an indicator of incomplete co mbustion since CO will burn to carbon dioxide if adequate oxygen is available. Correcting incomplete combustion may be accomplished through providing more combustion air. Therefore, we consider monitoring and maintaining CO emission levels to be associated with minimi zing organic HAP emission levels and, thus, CO monitoring would be a good indica tor of combustion efficiency and organic HAP emissions. As discussed in the final preamble, CO is considered a surrogate fo r organic HAP emissions in this rule.
To determine if CO monitoring would be th e basis of the new source MACT floor for organic emissions control, we examined availa ble information. The population databases did not contain information on existing units monitoring CO emissions. We review ed State regulations applicable to boilers and proce ss heaters that required the use of CO monitoring to maintain a specific CO limit. The analysis of the State regula tions indicated that at least one of the boilers and process heaters in the large and limited us e subcategories for solid fuel, liquid fuel, and gaseous fuel were required to monitor CO emissions and meet a CO limit of 200 parts per million. Therefore, the new source MACT floor leve l of control includes a CO emission limit of 200 parts per million for large and limited use units.
We concluded that, except for CO m onitoring for organic HAP, add-on control technology is the only factor that significantly controls emissions . To determine the MACT floor for new sources, the EPA reviewed the populat ion database of existing major sources.
Based upon the emission reduction potential of existing air pollution control devices, the EPA listed all the boilers and process heaters in the population database in order of decreasing control device effectiveness for each subcategory and each type of pollutant. Once the ranking of all existing boilers and proce ss heaters was completed for eac h subcategory and type of pollutant, the EPA determined the technol ogy basis of the new source MACT floor by identifying the best-controlled source using the air polluti on control rankings.
After establishing the technology basis fo r the new source MACT floor for each subcategory and each type of pollutant, the EP A examined the emissions data available for boilers and process heaters controlled by thes e technologies to determine achievable emission levels for PM (as a surrogate for non-merc ury metallic HAP), total selected non-mercury metallic HAP, mercury, HCl (as a surrogate for inorganic HAP), and CO (as a surrogate for organic HAP). This approach is reasonable because the most informative way to predict the worst reasonably foreseeable performance of the best-controlled unit, with available data, is to3-22 examine the performance of other units that us e the same technology. In other words, the EPA considers all units with the same control techno logy to be equally well controlled, and each unit with the best control technology is a “best controlled simila r unit” even if the emission test results from such units vary considerably.
Accordingly, we selected as the floor for ne w units the level of control that was being achieved in practice by the best-controlled simila r source, that is, the source with emissions representing the performance of the most effective cont rol technology under the worst reasonably foreseeable circumstances. A detailed description of the MACT floor determination is in the memorandum “MACT Floor Analysis for New and Existing Sources in the Industrial, Commercial, and Institutional Boilers and Proces s Heaters Source Categories” in the docket.
New Solid Fuel-fired Units . Large Units—Heat Inputs Greater than 10 MMBtu/hr . The most effective control technology id entified for removing PM from boilers in this subcategory is fabric filters. Therefore, the EP A considers a fabric filter to be the technology basis for the new source MACT floor for non-mercury metallic HAP emissions. The MACT floor emission level based on fabric filters is 0.04 lb PM/MMBtu. This PM emission level was selected from a subset of fabric filters contained in th e database. This subset includes fabric filters assumed to be subject or achieving the N SPS for industrial boilers. The NSPS (40 CFR 60.40b), which represent best demonstrated tec hnology for criteria pollutants, is based on the use of a fabric filter for PM and requires the use of a scrubber for sulfur dioxid e. Therefore, fabric filters subjected to the NSPS are assumed to be better designed, and operated than those built prior to the NSPS.
We are also providing an a lternative metals limit of 0.00007 lb metals/MMBtu which can be used to show compliance in cases where me tal HAP emissions are low in proportion to PM emissions. The emissions database indicates that some biomass units have low metals content but high PM emissions. The emission level for metals wa s selected from metals test data associated with PM emission tests from fabric filters that met the MACT floor PM emission level. The most effective control technologies identified for re moving inorganic HAP including acid gases, such as HCl, are wet scrubbers and pack ed bed scrubbers. Wet scrubbers is a generic term that is most often used to describe venturi scrubbers, but can include packed bed scrubbers, impingement scrubbers, etc. One percent of boilers and proce ss heaters in this subc ategory reported using a packed bed scrubber. Emission test data from ot her industries sugge sts that packed bed scrubbers achieve consistently lower emission levels than wet scrubbers. Therefore, the EPA considers a packed bed scrubber to be the technology basi s for the new source MACT floor for acid gas3-23 control for boilers and process heaters in the solid fuel subcategory. The MACT floor emission level based on packed scrubbe rs is 0.016 lb HCl/MMBtu.
For mercury control, one technology, carbon in jection, that has demonstrated mercury reductions in other source categories (i.e., municipa l waste combustors), was identified as being used on one existing industrial boiler. Howeve r, test data on this carbon injection system indicated that this uni t was not achieving mercury emissions reductions. Therefore, we did not consider carbon injection to be a MACT floor control technology for industrial, commercial, and institutional boilers and process heaters. Data from electric utili ty boilers indicate that fabric filters can achieve mercury emissions reductions. Th erefore, the EPA considers a fabric filter to be the control technology basis for controlli ng mercury in this subcategory. The MACT floor emission level based on fabric filters is 0.0000026 lb mercury/MMBtu.
Similar control technology analysis was done fo r the boilers and proc ess heaters in this subcategory for organic HAP. One control technique, controlling inlet temperature to the PM control device, that has demonstrated controlling downstream formation of dioxins in other source categories (e.g., municipal waste combustors ) was analyzed for indus trial boilers. Inlet and outlet dioxins test data were available on four boilers controlled with PM control devices. In all cases, no increase in dioxins emissions were indicated across the PM control device even at high inlet temperatures. However, we are requesting comment on controls that would achieve reductions of organic HAP, including any additiona l data that might be available. The EPA did find that CO monitoring can reduce organic HAP emissions, and has included it in the new source MACT floors as described unde r section III.F. of this preamble.
In light of this analysis, the EPA determined that the combination of a fabric filter, a packed bed scrubber, and CO monitoring forms the control technology basis for the new source MACT floor for boilers and proce ss heaters in this subcategory.
Small Units—Heat Inputs Less th an or Equal to 10 MMBtu/hr . The most effective control technologies identified for removing non-mercury metallic HAP used by units in this subcategory are fabric filters. Therefore, the EPA considers fabric filters to be the technology basis for the new source MACT floor for non-merc ury metallic HAP control in this subcategory. The most effective control technology identified for units in this subcategory for removing acid gases, such as HCl, are wet scrubbers. The most effective control tec hnologies identified for removing mercury used by units in this subcategory are fabric filters.3-24 The EPA identified no control technology being used in the existing population of boilers and process heaters that consistently achieve d lower emission rates than uncontrolled levels, such that a best-controlled similar source for or ganic HAP could be identi fied. We concluded the MACT floor for new sources in this subcateg ory is no emissions reductions for organic HAP. Furthermore, CO monitoring is not required for small boilers and process heaters by any State rules.
Thus, the EPA determined that the combination of a fabric filter and a wet scrubber forms the control technology basis for the new source MA CT floor for boilers and process heaters in this subcategory.

The emissions test database did not contain te st data for boilers and process heaters less than 10 MMBtu/hr heat input. In order to deve lop emission levels for this subcategory, we decided to use information from units in the large solid subcategory. We considered this to be an appropriate methodology because although the units in this subcategory are different enough to warrant their own subcategory (i .e., different designs and emissi ons), emissions of the specific HAP for which limits are being proposed (HCl, PM and metals) are expected to be related more to the type of fuel burned and the type of cont rol used than to the unit design. Consequently, we determined that emissions information from units greater than 10 MMBtu/h r heat input could be used to establish the MACT floor levels for this subcategory for HCl, non-mercury metallic HAP (using PM as a surrogate), and mercury becau se the fuels and controls are similar.

The MACT floor emission level based on emissi ons data for fabric filters on solid fuelfired boilers is 0.04 lb PM/MMBtu or 0.00007 lb selected non-mercury metals/MMBtu, and 0.0000026 mercury/MMBtu. The MACT floor emission level based on wet scrubbers is 0.032 lb HCl/MMBtu. We are requesting comment on using em ission data from another subcategory to develop emission levels for this subcategory. We are also requesting any available emissions information for this subcategory.
Limited Use Units—Capacity Utilizations Less than or Equal to 10 Percent . The most effective control techno logies identified for removing non-mercury metallic HAP and mercury used by units in this subcategory are fabric filters. Therefore, the EPA considers fabric filters to be the technology basis for the new source MACT floor for non-mercury metallic HAP and mercury control in this subcategor y. The most effective control technology identified for units in this subcategory for removing acid gases, su ch as hydrogen chloride, are wet scrubbers.3-25 The EPA did find that monitoring CO is used by at least one unit and can reduce organic HAP emissions, and has included it in the new source MACT floor for this subcategory as described under section I II.F of this preamble.
Therefore, based on this analysis, the EPA de termined that the combination of a fabric filter, a wet scrubber, and CO monitoring form s the control technology basis for the new source MACT floor for boilers and proce ss heaters in this subcategory.
Consequently, we determined that emissions information from units greater than 10 MMBtu/hr heat input could be used to establish MACT floor levels for this subcategory because the fuels and controls are similar. The MACT fl oor emission level based on fabric filters is 0.04 lb PM/MMBtu or 0.00007 lb metals/MMBtu, and 0.0000026 mercury/MMBtu. The MACT floor emission level based on wet scrubbers is 0.032 lb HCl/MMBtu. We are requesting comment on using emission data from another subcategory to develop emission levels for this subcategory. We are also requesting any available emi ssions information for this subcategory.
New Liquid Fuel-fired Units . Large Units—Heat Inputs Greater than 10 MMBtu/hr . The most effective control technologies identifie d for removing non-mercury metallic HAP and PM from units in this subcategory are fabric filters. Therefore, the EPA considers a fabric filter to be the technology basis for the new source MACT fl oor for non-mercury metallic HAP. A PM level is set as a surrogate for non-mercury metallic HAP control. The MACT floor emission level based on emission data for fabric filters on li quid fuel fired boilers is 0.068 lb PM/MMBtu. Unlike for solid fuel subcategories, we are not aw are of any liquid fuels that are low in metals but would have high PM emissions. Therefore, we are not proposing an alternative metals standard for the liquid subcategories.
The most effective control technologies id entified for removing inorganic HAP that are acid gases, such as HCl, are packed bed scrubbe rs. Therefore, the EPA considers a packed bed scrubber to be the technology basis for the ne w source MACT floor for acid gas control for boilers and process heaters in the liquid fuel subcategory. The MACT floor emission level based on packed scrubbers is 0.00045 lb HCl/MMBtu.
Similar control technology analyses were done for the boilers and process heaters in this subcategory for mercury and organic HAP.

Information in the emissions database or from other source categorie s does not show that control technologies, such as fabric filters or wet scrubbers, achieve reductions in mercury emissions from liquid fuel-fired industrial, co mmercial, and institutional boilers and process3-26 heaters. Therefore, EPA identified no control technology being used in th e existing population of boilers and process heaters in th ese subcategories that consistent ly achieved lower emission rates than uncontrolled levels, such that a best-contr olled similar source for organic HAP could be identified. However, we did find that monito ring CO is a good combusti on practice that can reduce organic HAP emissions, and has included it in the new sour ce MACT floor as described under section III.D of this preamble. We concluded the MACT floor for new sources in this subcategory is no emissions reductions for mercury.
In light of this analysis, the EPA determined that the combination of a fabric filter, a packed bed scrubber, and CO monitoring forms the control technology basis for the new source MACT floor for boilers and proce ss heaters in this subcategory.
Small Units—Heat Inputs Less th an or Equal to 10 MMBtu/hr . The most effective control technologies identified for removing non-mercury metallic HAP used by units in this subcategory are fabric filters. Therefore, the EPA considers fabric filters to be the technology basis for the new source MACT floor for non-merc ury metallic HAP control in this subcategory. The most effective control technology identified for units in this subcategory for removing acid gases, such as hydrogen ch loride, are wet scrubbers.

Information in the emissions database or from other source categorie s does not show that other control technologies, such as fabric filters or wet scrubber s, achieve reductions in mercury emissions from liquid fuel-fired industrial, co mmercial, and institutional boilers and process heaters. Therefore, EPA could not identify a control technology being used in the existing population of boilers and process heaters that consistently achie ved lower emission rates than uncontrolled levels, such that a best-controlled si milar source for mercury or organic HAP could be identified. We concluded the MACT floor for ne w sources in this subcategory is no emissions reductions for mercury or organic HAP.
Thus, the EPA determined that the combination of a fabric filter and a wet scrubber forms the control technology basis for the new source MA CT floor for boilers and process heaters in this subcategory.

The emissions test database did not contain te st data for boilers and process heaters less than 10 MMBtu/hr heat input. In order to deve lop emission levels for this subcategory, we decided to use information from units in the larg e liquid subcategory. We considered this to be an appropriate methodology because although the un its in this subcategory are different enough to warrant their own subcategory (i.e., different designs and emi ssions), emissions of the specific3-27 types of HAP for which limits are being proposed (HCl and metals) are expected to be more related to the type of fuel burned and the type of control than to unit design. Consequently, we determined that emissions information from units greater than 10 MMBtu/h r heat input could be used to establish MACT floor levels for this subcategory because the fuels and controls are similar. The MACT floor emission level based on fabric filters is 0.068 lb PM/MMBtu. The MACT floor emission level based on wet scrubbers is 0.0009 lb HCl/MMBtu.
Limited Use Units—Capacity Utilizations Less than or Equal to 10 Percent . The most effective control techno logies identified for removing non-mercury metallic HAP used by units in this subcategory are fabric filters. Therefor e, the EPA considers fabric filters to be the technology basis for the new sour ce MACT floor for non-mercury metallic HAP control in this subcategory. The most effective control technology identified for units in this subcategory for removing acid gases, such as hydrogen chloride, are wet scrubbers.

Information in the emissions database or from other source categorie s does not show that other control technologies, such as fabric filters or wet scrubber s, achieve reductions in mercury emissions from liquid fuel-fired industrial, co mmercial, and institutional boilers and process heaters. The EPA identified no control technolo gy being used in th e existing population of boilers and process heaters that consistently achieved lower emission rates than uncontrolled levels, such that a best-controlled similar sour ce for mercury could be identified. We concluded the MACT floor for new sources in this subcat egory is no emissions reductions for mercury.
We did find that monitoring CO can reduce organic HAP emissions and is used by at least one unit in this subcate gory, and have included it in the new source MACT floor as described under section III.D of this preamble. Therefore, ba sed on this analysis, the EPA determined that the combination of a fabric f ilter, a wet scrubber, and CO monitoring forms the control technology basis for the new source MACT fl oor for boilers and process heaters in this subcategory.

The emissions test database did not contain te st data for limited use liquid-fired boilers and process heaters. In order to develop emission levels for this subcategory, we decided to use information from units in the large liquid s ubcategory. Consequently, we determined that emissions information from units greater than 10 MMBtu/hr heat input could be used to establish MACT floor levels for this subcategory because the fuels and controls are similar. The MACT floor emission level based on fabric filters is 0.068 lb PM/MMBtu. The MACT floor emission level based on wet scrubbers is 0.0009 lb HCl/M MBtu. We are requesting comment on using3-28 emission data from another subcategory to develo p emission levels for this subcategory. We are also requesting any available emissions information for this subcategory.
Gaseous Fuel Subcategories . No existing units were usi ng control technologies that achieve consistently lower emission rates than uncontrolled sources for any of the pollutant groups of interest, except organic HAP. At least one unit in the population database in the large and limited use gaseous fuel subcategories is re quired to monitor CO. Therefore, the MACT floor for gaseous fuel-fired units includes a CO monitoring requirement and emission limit, as described in section III.D of this preamble, but it does not include any emission limits for PM, metallic HAP, mercury, or inorganic HAP based on the utilization of add-on control technology.
How EPA Considered Beyond the Floor Options for New Units . The MACT floor level of control for new units is based on the emission c ontrol that is achieved in practice by the best controlled similar source within ea ch of the subcategories. No te chnologies were identified that would achieve non-mercury metals reduction grea ter than the new source floors (i.e., fabric filters) for the liquid and solid subcategories or CO monitoring for the solid, liquid, and gaseous subcategories. For inorganic HAP control, we determined that packed bed scrubbers achieve higher emissions reductions than MACT floors consisting of a wet scrubber. Packed bed scrubbers are the technology basis of the MACT floor for the large unit subcategory, but wet scrubbers were the technology basis of th e floors for the small unit and limited unit subcategories. Therefore, we examined the co st and emission reductions of applying a packed bed scrubber as a beyond the floor option for ne w solid and liquid units within the small and limited use subcategories. We determined that costs were excessive for the limited emission reduction that would be achieve d. Non-air quality h ealth, environmental impacts, and energy effects were not significant factor s, because there would be little difference in the non-air quality health and environmental impacts between packed bed scrubbers and wet scrubbers. Therefore, the EPA did not select this be yond-the-floor option, and the proposed new source MACT level of control for PM, metallic HAP, and inorganic HAP (HCl) is the same as the MACT floor level of control for all of the subcategories.
In reviewing potential regul atory options beyond the new s ource MACT floor level of control, the EPA identified one existing solid fuel-fired industr ial boiler that was using carbon injection technology for mercury control. Howe ver, emission data obtained from this unit indicated that it was not ach ieving mercury emission reductions from the uncontrolled levels. Moreover, we do not have information to otherwis e show that carbon injection is effective for reducing mercury emissions from industrial, comme rcial, and institutional boilers and process heaters. Information in the emissions database or from other source categories does not show that3-29 other control technologies, such as fabric filters or wet scrubber s, achieve reductions in mercury emissions from liquid fuel-fired industrial, co mmercial, and institutional boilers and process heaters. Therefore, carbon injection, for solid fu el units, and other control techniques, for liquid fuel units, were not evaluated as regulatory options.
For the solid fuel and liquid fuel subcategories, fuel switching to natural gas is a potential regulatory option beyond the new source floor level of control that would reduce mercury and metallic HAP emissions. However, based on current trends within the industry, the EPA projects that the majority of new boilers and process heaters will be built to fire natural gas as opposed to solid and liquid fuels such that the overall emissi ons reductions associated with this option would be minimal. Furthermore, organic HAP may be increased by fuel switching. Limited emissions reductions in combination with the high cost of fuel switching and considerations about the availability and technical feas ibility of fuel switching makes this an unreasonable regulatory option that was not considered further. Non-ai r quality health, environmental impacts, and energy effects were not significan t factors. No beyond-the-floor options for gas-fired boilers were identified.
Based on the analysis discussed above, th e EPA decided to not go beyond the MACT floor level of control for new sources for MACT in the rule.

3.1.4 Considerations of Possible Risk-Based A lternatives to Reduce Impacts to Sources The Agency has made every effort in developi ng this rule to minimize the cost to the regulated community and allow maximum flexibility in compliance options consistent with our statutory obligations. However, we recognize that the rule may still require some facilities to take costly steps to further control emissions even though their emissions may not result in exposures which could pose an excess individual lifetime cancer risk greater than one in one million or which exceed thresholds determined to provide an ample margin of safety for protecting public health and the environment from the effects of hazardous air pollutants. We therefore solicited comment on whether there are further ways to stru cture the rule to focus on the facilities which pose significant risks and avoid th e imposition of high costs on fac ilities that pose little risk to public health and the environment.
Representatives of the plywood and com posite wood products industry provided EPA with descriptions of three mechanisms that they believed could be used to implement more costeffective reductions in risk. The docket for toda y’s rule contains “white papers” prepared by industry that outline their proposed approaches (see docket number A-98-44, Item # II-D-525). These approaches could be effective in focusi ng regulatory controls on facilities that pose3-30 significant risks and avoiding the im position of high costs on faciliti es that pose little risk to public health or the environment, and we sought public comment on the utility of each of these approaches with respect to this rule.
One of the approaches, an applicability cutoff for threshold pollutants, would be implemented under the authority of CAA section 112(d)(4); the second approach, subcategorization and delisting, would be impl emented under the authority of CAA sections 112(c)(1) and 112(c)(9); a nd, the third approach, would involve the use of a concentration-based applicability threshold. We sought comments on wh ether these approaches are legally justified and asked for information that could be used to support such approaches.
The approach the Agency has chosen to include in the final rule is the first approach—an applicability cutoff for threshold pollutants. The threshold pollutants for which an applicability cutoff is applied are hydrochloric acid (HCl) a nd a series of eight me tals known as the total selected metals (TSM).

3.1.4.1 Applicability Cutoffs for Threshold Pollu tants Under Section 112(d)(4) of the CAA This approach is an “applicability cutoff” fo r threshold pollutants that is based on EPA’s authority under CAA section 112(d)(4). A “thres hold pollutant” is one for which there is a concentration or dose below which adverse effect s are not expected to occur over a lifetime of exposure. For such pollutants, section 112(d)(4) allo ws EPA to consider the threshold level, with an ample margin of safety, when establishi ng emissions standards. Specifically, section 112(d)(4) allows EPA to establish emission st andards that are not based upon the maximum achievable control technology (MACT) specifi ed under section 112(d)(2) for pollutants for which a health threshold has been established. Su ch standards may be less stringent than MACT. Historically, EPA has interpreted 112(d)(4) to allo w us to avoid further regulation of categories of sources that emit only threshold pollutants, if those emissions re sult in ambient levels that do not exceed the threshold, with an ample margin of safety. 4
In the past, EPA routinely treated carci nogens as non-threshold pollutants. The EPA recognizes that advances in risk assessmen t science and policy may affect the way EPA differentiates between thres hold and non-threshold HAP. The EPA’s draft Guidelines for Carcinogen Risk Assessment (E PA, 1999) suggest that carcinoge ns be assigned non-linear doseresponse relationships where data warrant. Moreover, it is possibl e that dose-response curves for some pollutants may reach zero risk at a dose greater than zero, creating a threshold for

4 See 63 FR 18754, 18765-66 (April 15, 1998) (Pulp and Paper Combustion Sources Proposed NESHAP).3-31 carcinogenic effects. It is possi ble that future evaluations of the carcinogens emitted by this source category would determine that one or mo re of the carcinogens in the category is a threshold carcinogen or is a carcinogen that e xhibits a non-linear dose -response relationship but does not have a threshold.
The dose-response assessments for formal dehyde and acetaldehyde are currently undergoing revision by the EPA. As part of this revision effort, EPA is evaluating formaldehyde and acetaldehyde as potential non-linear carcinog ens. The revised dose-response assessments will be subject to review by the EPA Scien ce Advisory Board, followed by full consensus review, before adoption into the EPA Integrated Risk Information System (IRIS). At this time, EPA estimates that the consensus review will be completed sometime in 2004. The revision of the dose-response assessments could affect the po tency factors of these HAP, as well as their status as threshold or non-thre shold pollutants. At this time , the outcome is not known. In addition to the current reassessment by EPA, th ere have been several reassessments of the toxicity of and carcinogenicity of formaldehyde in recent years, including work by the World Health Organization and the Ca nadian Ministry of Health.

3.1.4.2 Applicability Cutoffs for Hydrogen Chloride Controls Under Secti on 112(d)(4) of the CAA HCl Compliance Alternative . As an alternative to the re quirement for each large solid fuel-fired boiler to demonstrate compliance w ith the HCl emission limit in the final rule, you may demonstrate compliance with a health-bas ed facility-wide HCl equivalent allowable emission limit.
The procedures for demonstrating eligibil ity for the HCl compliance alternative (as outlined in appendix A of the final rule) are: (1) You must include in your demonstration ev ery emission point within the facility that emits a respiratory toxicant included on EPA’s list of hazardo us air pollutants. (2) You must conduct HCl and chlorine emissi ons tests for every emission point covered under subpart DDDDD. (3) You must obtain either through emissi on testing or through the development and documentation of best engineering estimates of maximum emissions of respiratory toxicants from all emission points at the facility not covered under subpart DDDDD of part 63 from which a respiratory toxicant might reasonably be emitted. (4) You must determine the total maximum hour ly mass HCl-equivalent emission rate for your facility by summing the maximum hourly toxicity-weighted emission rates of all appropriate respiratory toxican ts (calculated using the maximum rated capacities of the units) for each of the units at your facility.3-32 (5) Use the look-up table in the appendix A of subpart DDDDD to determine if your facility is in complian ce with health-based HCl-equivalent emission limit. (6) Select the maximum allowable HCl-equiva lent emission rate from the look-up table in appendix A of subpart DDDDD of part 63 for your facility usi ng the average stack height of your subpart DDDD D emission units as your stack height and the minimum distance between any respiratory toxicant emi ssion point at the facility and the closest boundary of the nearest reside ntial (or residentially zone d) area as your fenceline distance. (7) Your facility is in compliance if your maximum HCl-equivalent emission rate does not exceed the value specified in the look- up table in appendix A of subpart DDDDD. (8) As an alternative to using the look -up table, you may conduct a site-specific compliance demonstration (as outlined in a ppendix A of subpart DDDDD of part 63) which demonstrate that your facility cannot cause an i ndividual chronic inhalation exposure from respiratory toxicants which can exceed a Hazard Index (HI) value of 1.0.

3.1.4.3 Applicability Cutoffs for Total Selected Meta ls Controls Under Section 112(d)(4) of the CAA In lieu of complying with the emission st andard for TSM in subpart DDDDD of part 63 based on the sum of emissions for the selected metals (arsenic, cadmium, chromium, mercury, manganese, nickel, and lead) you may demonstrat e eligibility for comp lying with the TSM standard based on excluding manganese emission s from the summation of TSM emissions for the affected source unit.
The procedures for demonstrating eligibility for the TSM compliance alternative (as outlined in appendix A of the subpart DDDDD) are: (1) You must include in your demonstration ev ery emission point within the facility that emits a CNS toxicant included on EPA’ s list of hazardous air pollutants. (2) You must conduct manganese emissions te sts for every emission point covered under subpart DDDDD that emits manganese. (3) You must obtain either through emissi on testing or through the development and documentation of best engineering estim ates of maximum emissions of CNS toxicants from all emission points at the facility not covered under subpart DDDDD from which a CNS toxicant might reasonably be emitted. (4) You must determine the total maximum hourly manganese equivalent emission rate from your facility by summing the maximum hourly toxicity-wei ghted emission rates of all appropriate CNS toxicants (calcula ted using the maximum rated heat input capacities) for each of the units at your facility.3-33 (5) Use the look-up table in appendix A of subpart DDDDD to determine if your facility is eligible for complying with the TSM limit based on the sum of emissions for seven metals (excluding manganese) for the affected source units. (6) Select the maximum allowable manganese- equivalent emission ra te from the look-up table in appendix A of subpart DDDDD for your facility using the average stack height of your subpart DDDD D emission units as your stack height and the minimum distance between any CNS toxicant emission point at the facility and the closest boundary of the nearest reside ntial (or residentially zone d) area as your fenceline distance. (7) Your facility is eligible if your maxi mum manganese-equivalent emission rate does not exceed the value specified in the look- up table in appendix A of subpart DDDDD. (8) As an alternative to using look-up table to determine if your facility is eligible for the TSM compliance alternative, you may conduct a site-specific compliance demonstration (as outlined in appendix A of subpart DDDDD) which demonstrates that your facility ca nnot cause an individua l chronic inhalation exposure from CNS toxicants which can exce ed a HI value of 1.0. If you elect to demonstrate eligibility for either of the health-based compliance alternatives, you must subm it certified documentation suppo rting compliance with the procedures at least 1 year before the compliance date.
You must submit supporting documentation in cluding documentation of all maximum capacities, existing control devices used to re duce emissions, stack parameters, and property boundary distances to each on-si te source of HCl-equivalent and/or manganese-equivalent emissions.
You must keep records of the informa tion used in devel oping the eligibility demonstration for your affected source.
To be eligible for either health-based complia nce alternative, the parameters that defined your affected source as eligible for the health-b ased compliance alternatives (including, but not limited to, fuel type, type of control devices, process parameters documented as worst-case conditions during the emissions testing used for your eligibility demonstration) must be incorporated as Federally enforceable limits into your title V permit. If you do not meet these criteria, then your affected sour ce is subject to the applicable emission limits, operating limits, and work practice standards in Subpart DDDDD.
If you intend to change key parameters (i ncluding distance of stack to the property boundary) that may result in lower allowable heal th-based emission limits, you must recalculate3-34 the limits under the provisions of this secti on, and submit documentation supporting the revised limits prior to initiating the change to the key parameter.
If you intend to install a new solid fuel-fir ed boiler or process heater or change any existing emissions controls that may result in increasing HCl-equivale nt and/or manganeseequivalent emissions, you must recalculate the total maximum hourly HCl-equivalent and/or manganese-equivalent emission rate from your affected source, and submit certified documentation supporting continued e ligibility under the revised information prior to initiating the new installation or change to the emissions controls.

Facilities that could no t demonstrate that they are eligible to be included in the low-risk subcategory would be subject to MACT and possible future residual risk standards.

3.2 Profile of Existing Boiler and Process Heaters Units This section profiles existing boilers and process heaters, collectively referred to as “units,” with respect to business applications, indu stry of parent company, and fuel use. The unit population database in combination with the model units that helped in preparing that database were used to determine which types of boilers, fu el, and control devices we re in the existing unit population so that corresponding em ission factors could be deve loped for all combinations.

3.2.1 Development of the Unit Inventory Database The development of the population database and the model units are discussed in the memoranda, “Development of the Population Data base for the Industria l, Commercial, and Institutional Boiler and Process Heater Nationa l Emission Standard for Hazardous Air Pollutants (NESHAP)” and “Development of the Model Units for the Industrial, Commercial, and Institutional Boiler and Process Heater Nationa l Emission Standard for Hazardous Air Pollutants (NESHAP).” The units contained in the Inventory Database are based on information from the Aerometric Information Retrieval System (AIRS) and Ozone Transport Assessment Group (OTAG) databases, state and local permit r ecords, and the combus tion source Information Collection Request (ICR) conducted by the Agency in 1997. The list of units contained in the Inventory Database was reviewed and updated by industry and e nvironmental stakeholders as part of the Industrial Combus tion Coordinated Rulemaking (I CCR), chartered under the Federal Advisory Committee Act (FACA).
The entire Inventory Database contains more than 58,000 ICI boilers and process heaters; however only 3,730 units in the database are estimated to be affected by the final rule. Of these existing units, a little over half had sufficient in formation on operating parameters to be included3-35 in the floor-level EIA. The number of potentially affected units included in the profile for the final rule was 2,186.

3.2.2 Distribution of Existing Boile rs and Facilities by Industry Table 3-2 presents the number of existing boi lers and process heaters and the number of facilities owning units by two-digi t SIC code and three- digit NAICS code that may be affected by the final rule. For the final rule, the industrie s with the largest number of potentially affected units are the furniture, paper, lumber, and electr ical services industries. These four industries alone account for nearly 60 percen t of affected units. Almost all the process heaters are in the lumber industry. (Section 4 presents industr y profiles for the lumber and wood products, electrical services, and paper industries, am ong others.) The remaining units are primarily distributed across the manufacturing sector and service industries.

3.2.3 Technical Characteristics of Existing Boilers Figure 3-1 characterizes the population of 2,186 units identified in the Inventory Database by capacity range, fuel type , and level of preexisting control.

3.2.3.1 Final Rule

 Capacity Range: Unit input capacities in the population are expresse d in four ranges: 0–10, 10–100, 100–250, and >250 MMBtu/hr. About 52 percent of the units affected for this alternative have capacities betw een 10 and 100 MMBtu/hr. The two largest capacity ranges each contain approximately one quarter of the population. Only 1 percent of units have input capacities less than 10 MMBtu/hr.

 Fuel Type: About half of these units consum e coal as their primary fuel (1,074 units). After coal, the next most common fuel type is wood (479 units).

 Control Level: About 83 percent of units ha ve some type of control device already installed. Only 289 units do not. Typical cont rol devices include fabric filters, wet scrubbers, and electrostatic precipitators.3-36 Table 3-2. Units and Facilities Affect ed by the Final Rule by Industry a

SIC Code NAICS Code Description Boilers Heaters Total Units Facilities 01 111 Agriculture—Crops 3 0 3 3 02 112 Agriculture—Livestock 0 0 0 0 07 115 Agricultural Services 0 0 0 0 10 212 Metal Mining 9 0 9 4 12 212 Coal Mining 2 0 2 1
13 211 Oil and Gas Extraction 0 0 0 0 14 212 Mining/Quarrying—Nonmetallic Minerals 8 0 8 4 17 235 Construction—Special Trade Contractors 0 0 0 0
20 311 Food and Kindred Products 138 0 138 60
21 312 Tobacco Products 11 0 11 7
22 313 Textile Mill Products 135 0 135 71 23 315 Apparel and Other Products from Fabrics 2 0 2 2
24 321 Lumber and Wood Products 335 25 360 262
25 337 Furniture and Fixtures 234 0 234 154 26 322 Paper and Allied Products 321 0 321 194 27 511 Printing, Publishing, and Related Industries 0 0 0 0
28 325 Chemicals and Allied Products 171 3 174 70 29 324 Petroleum Refining and Related Industries 11 0 11 8
30 326 Rubber and Miscellaneous Plastics Products 17 0 17 13
31 316 Leather and Leather Products 1 0 1 1 32 327 Stone, Clay, Glass, and Concrete Products 9 0 9 7 33 331 Primary Metal Industries 41 0 41 16
34 332 Fabricated Metal Products 16 0 16 10 35 333 Industrial Machinery and Computer Equipment 23 0 23 12 36 335 Electronic and Electrical Equipment 5 0 5 5 37 336 Transportation Equipment 102 0 102 41 38 334 Scientific, Optical, and Photographic Equip. 8 0 8 4 39 339 Miscellaneous Manufacturing Industries 2 0 2 2 40 482 Railroad Transportation 4 0 4 1 (continued)3-37 Table 3-2. Units and Facilities Affect ed by the Final Rule by Industry a (continued)

SIC Code NAICS Code Description Boilers Heaters Total Units Facilities 42 484 Motor Freight and Warehousing 5 0 5 1 46 486 Pipelines, Except Natural Gas 0 0 0 0 49 221 Electric, Gas, and Sanitary Services 318 0 318 160
50 421 Wholesale Trade—Durable Goods 3 0 3 2
51 422 Wholesale Trade—Nondurable Goods 2 0 2 1
55 441 Automotive Dealers and Gasoline Service Stations 0 0 0 0 58 722 Eating and Drinking Places 0 0 0 0 60 522 Depository Institutions 0 0 0 0
59 445–454 Miscellaneous Retail 0 0 0 0 70 721 Hotels and Other Lodging Places 1 0 1 1
72 812 Personal Services 0 0 0 0 76 811 Miscellaneous Repair Services 2 0 2 1
80 621 Health Services 37 0 37 18 81 541 Legal Services 0 0 0 0
82 611 Educational Services 105 0 105 45
83 624 Social Services 2 0 2 1 86 813 Membership Organizations 0 0 0 0 87 541 Engineering, Accounting, Research, Management and Related Services 2 0 2 2

89 711/514 Services, N.E.C. 2 0 2 1 91 921 Executive, Legislative, and General Administration 1 0 1 1 92 922 Justice, Public Order, and Safety 29 0 29 9
94 923 Administration of Human Resources 1 0 1 1 96 926 Administration of Economic Programs 4 0 4 3 97 928 National Security and International Affairs 29 0 29 11
NA SIC Information Not Available 7 0 7 4
2,158 28 2,186 1,214

a Based on the Inventory Database.3-38 >250 23% 10 to 100 52%

100 to 250 25%

Input Capacity (million Btu) Preexisting Control Technology Fuel Type Cyclone

36% No Control 13% Wet Scrubber

12% Fabric Filter 16% ESP 23% Coal 49%

Coal and

Wood

7% Wood 22% Other

4% Other Biomass

14% Bagasse 4% 0 to 10

1% Floor Alternative (n=2,186)

Figure 3-1. Characteristic s of Units Affected

3.3 Methodology for Estimating Cost Impacts The predominant type of control measure that is considered in the analysis of emission reductions needed for sources to achieve the MA CT floor is add-on control technologies. Add-on control techniques are those technologies that are applied to the vent gas stream of the boiler or process heater to reduce emissions. The boiler an d process heaters populati on database includes information on all control techniques that are ap plied to industrial, co mmercial, institutional boilers and process heaters. Gene rally, they can be grouped into PM control or acid gas control. The most common technologies, and the ones analyzed for the impacts analysis, include fabric filters, ESP’s, packed scrubbers, venturi scrubbe rs, and spray dryers. In addition, when add-on technologies are used, the cost of ductwork and associated equipment also needed to be considered.
Components of capital cost include

 purchased equipment cost of the prim ary device and auxiliary equipment,

 instrumentation,

 sales tax and freight, and

 installation costs. Installa tion costs include foundations and support, handling and erection, electrical, piping, insulation, a nd painting, engineering, construction and field expenses, contractor fees, start-up, performance te sts, and contingencies.3-39 Components of annual cost include

 raw materials,

 utilities (electricity, fu el, steam, air, water),

 waste treatment and disposal,

 labor (operating, supervisory, maintenance),

 maintenance materials,

 replacement parts,

 overhead,

 property taxes,

 insurance,

 administration charges, and

 capital recovery costs. For this analysis, costs were estimated in 1999 dollars. Capital recovery was calculated assuming 7 percent interest rate over the life of the equipment. The use of this interest rate is based on Office of Management and Budget (OMB) gui dance (Circular A-94, October 29, 1992).
The algorithms used to estimate these costs were obtained from pr evious EPA studies. These cost algorithms are included as appendi ces to the cost methodology memorandum in the public docket. Inputs for the algorithms used in th e impacts analysis are also presented in this memorandum.

Fabric Filter The algorithms used to estimate capital and a nnual costs of fabric filters were obtained from EPA’s EPA Air Pollution Control Cost Manu al. Algorithms were provided for 4 types of fabric filters: shaker, reversed air, pulse-jet modular, and puls e-jet common. The cost algorithms for estimating capital costs reduced to basic equa tions for each are provided in Appendix A-1 of the cost methodology memorandum (henceforth calle d the “cost memo”). Capital costs are based on the gross cloth area of the fabric filter, wh ich is a function of th e gas inlet flow rate. Algorithms for calculating annual costs are provide d in Appendix A-2 of the cost memo. Annual costs include dust disposal, electricity, maintenan ce, labor, bag replacement, maintenance labor, compressed air, overhead, administrative, property taxes, and insurance. Capital recovery is annualized over 20 years at 7 percent interest. Appendix A-3 of the cost memo presents the values for the inputs used in this an alysis and the reasons for their use.3-40 Electrostatic Precipitator The algorithms used to estimate capital and annual costs of ESPs were obtained from EPA’s Air Pollution Control Cost Manual. Capita l costs are based on the total collection plate area, which is calculated from the gas inlet fl ow rate and the required removal efficiency. The cost algorithms for estimating capi tal costs of ESPs reduced to basic equations are provided in Appendix B-1 of the cost memo. Algorithms fo r calculating annual cost s are provided in Appendix B-2 of the cost memo. Annual costs in clude dust disposal, electricity, maintenance, labor, maintenance labor, overhead, administrativ e, property taxes, and insurance. Capital recovery is annualized at 7 percen t interest. Appendix B-3 of the cost memo presents the values for the inputs used in this analys is and the reasons for their use.

Venturi Scrubber The algorithms used to estimate capital and annual costs of venturi scrubbers were obtained from EPA cost algorithms on EPA’ s Web site (http://www.epa.gov/ttn/catc/ products.html#cccinfo.) Capital costs include not onl y the cost of the vent uri scrubber but also a pump to provide motive force for the solvent. Ca pital costs are based on the gas flow rate and saturation temperature of the gas-solvent. The cost algorithms for estimating capital costs of each piece of equipment were reduced to basic equations in Appendix C-1 of the cost memo. The cost algorithms for estimating annual costs were reduced to basic equations in Appendix C-2 of the same memorandum. Annual costs incl ude wastewater disposal, solven t, electricity, maintenance, labor, maintenance labor overhead, administrativ e, property taxes, and insurance. Capital recovery is an annualized cost estimated using a 7 percent interest rate. Appendix C-3 of the cost memo presents the values for the inputs used in this analysis and the reasons for their use.

Packed Bed Scrubber The algorithms used to estimate capital and a nnual costs of packed bed scrubbers were obtained from EPA’s Air Pollution Control Cost Ma nual. The capital costs are comprised of the scrubber tower, packing, pumps, and fans. Capital costs are based primarily on gas flow rate and removal efficiency. The cost algorithms for estimating capital costs of packed scrubber equipment reduced to their basic equations for each are provided in Appendix D-1 of the cost memo. The cost algorithms for estimating annual costs of packed scrubbers are provided in Appendix D-2 of the cost memo. Annual costs in clude caustic, wastewater disposal, water, electricity, maintenance, labor, overhead, administra tive, property taxes, and insurance. Capital recovery is an annualized cost estimated using a 7 percent interest rate. Appendix D-3 of the cost memo presents the values for the inputs used in this analysis and the reasons for their use.3-41 Spray Dryer The algorithms used to estimate capital and a nnual costs of spray dryers were obtained from previous EPA studies. Capita l costs include the cost of th e spray dryer and pumps. Capital costs are based on the gas flow rate. The cost al gorithms for estimating capital costs of spray dryer equipment reduced to basic equations are provided in Appendix E-1 of the cost memo. The cost algorithms for estimating annual costs for sp ray dryers are provided in Appendix E-2 of the cost memo. Annual costs include li me, water, electricity, maintena nce, labor, maintenance labor, overhead, administrative, pr operty taxes, and insurance. Capita l recovery is an annualized cost estimated using a 7 percent intere st rate. Appendix E-3 of the cost memo presents the values for the inputs used in this analysis and the reasons for their use.

Ductwork The algorithms used to estimate capital and a nnual costs of ductwork were obtained from EPA’s Air Pollution Control Cost Manual. Capita l costs include 500 feet of ductwork, elbows, and fans. The 500 feet of ductwork was based on engineering judgment and previous experience on the distance between emission points and contro l devices in chemical facilities and the availability of space for retrof itting controls. Costs are based on ductwork diameter, which is calculated from the gas flow rate. The cost al gorithms for estimating capital costs and annual costs reduced to basic equations are provided in Appendix F-1 of the cost memo. Annual costs include electricity, maintenance, maintenance la bor, overhead, administrative, property taxes, and insurance. Capital recovery is an annualized cost estimated using a 7 percent interest rate. Required inputs to the ductwork algorithms ar e provided in the inputtables provided in Appendices A-3, B-3, C-3, D-3, a nd E-3 of the cost memo.

Good Combustion Practices Few sources in the population database specifically reported using good combustion practices. Boilers and process heaters within each subcategory might use any of a wide variety of different work practices, depending on the ch aracteristics of the individual unit.
Consequently, any uniform requirements or set of work practices that would meaningfully reflect the use of good combustion practices, or that could be meaningfully implemented across any subcategory of boilers a nd process heaters could not be identified.
Additionally, few of the GCP’s have been documented to reduce organic HAP emissions, and they could not be considered in the MACT analysis. One GCP that may effect organic HAP emissions is maintaining CO emission levels. CO is generally an indicator of incomplete combustion because CO will burn to carbon dioxide if adequate oxygen is available. Controlling3-42 CO emissions is a mechanism for ensuring combus tion efficiency, and therefore may be viewed as a kind of GCP.
Capital and annual costs for CO monitoring is presented in Appendix G of the cost memo. The costing information was obtained fr om a previous EPA study. Capital costs are comprised of the initial cost of the equipment. Annual costs include operating and maintenance costs, annual and quarterly checks, recordk eeping and reporting, taxes, insurance, and administrative costs. Annualized costs such as ca pital recovery costs are calculated assuming an equipment life of 20 years and an interest rate of 7 percent. Testing and Monitoring Costs The final rule includes emission limits for HCl, PM, metallic HAP, and mercury. Additionally, as mentioned in Sect ion 1 of this EIA and the preambl e, the rule allows sources to meet requirements by monitoring fuel content in stead of emissions. Consequently, testing and monitoring costs of meeting the st andards were incorporated into the cost estimates. Capital costs for testing include initial stack tests for PM, HCl, and metals for fossil fuels, and materials and fuel analysis for biomass. Capital cost compone nts include operation and maintenance costs and capital recovery assuming the initi al capital investment is annua lized over a 5 year period at 7 percent interest. Monitoring costs are include d for opacity monitoring, HCl monitoring, and scrubber parametric monitoring. 5 Monitoring costs include the capital cost of monitoring equipment, and the annual costs of capital recove ry assuming the initial capital investment is annualized over a 20 year period at 7 percent interest. Annual monitoring costs also include operation and maintenance as well as other additi onal costs. The testing and monitoring costs are shown in Table 3-3. Appendix G of the cost memo includes further details on these costs. Information used to estimate testing and mon itoring costs were obtained from previous EPA studies.

5 The monitoring costs reported for existing units are not the cost of continuous emission monitors (CEM), but the costs associated with monitoring the process parameters of the control device. Installation of these process monitors are integral to the control device and would be installed with or without the monitoring requirements of the MACT. Therefore, even though we pr esent these monitoring costs separately, they are included in the overall reported control costs and should not be considered as an additional cost for emission monitoring.3-43Table 3-3. Testing and Monitoring Costs for Units CoveredMaterial or FuelNo. ofIndustrialBoilersNo. ofProcessHeatersTotal CapitalInvestment ofTesting andMonitoring ($)Total AnnualCosts ofTesting ($)Total AnnualCosts ofMonitoring ($)Annual CapitalRecovery—Testingand Monitoring(1999$)Total AnnualCosts of Testingand Monitoring(1999$)Regular Use UnitsCoal2,328 0 123,759,254 63,608,65559,828,340 8,265,169 123,436,995Coal/Wood/NFFaLiquid/NFF Solid169 0 8,847,579 2,444,4561,302,784 280,698 3,747,240Gas30,473 13,481 0 0 0 0 0Gas/Wood/OtherBiomass/Liquid FF201 0 9,831,749 2,909,9942,327,840 447,120 5,237,834Distillate Liquid FF2,921 353 0 0 0 0 0NFF Liquid/NFF Solid/Gas115 11 7,452,131 3,074,9182,930,348 404,077 6,005,266Wood663 42 5,545,669 5,268,614 6,392,240 1,411,706 11,660,854Wood/Other Biomass/NFFLiquid/NFF Solid147 0 8,180,852 3,003,1462,001,492 299,112 5,004,638Residual Liquid FF2,036 674 0 0 0 0 0Bagasse/Other132 0 5,821,106 490,000 2,891,728 412,546 3,381,728Total for Regular Use Units39,185 14,561 169,438,340 80,799,78377,674,772 11,520,428 158,114,555(continued)3-44Table 3-3. Testing and Monitoring Costs for Units Covered (continued)Material or FuelNo. ofIndustrialBoilersNo. ofProcessHeatersTotal CapitalInvestment ofTesting andMonitoring ($)Total AnnualCosts ofTesting ($)Total AnnualCosts ofMonitoring ($)Annual CapitalRecovery—Testingand Monitoring(1999$)Total AnnualCosts of Testingand Monitoring(1999$)Limited Use UnitsCoal198 0 6,427,715 1,584,000 1,716,416 457,169 3,330,416Coal/Wood/NFFLiquid/NFF Solid4 0 119,600 32,000 29,772 8,268 61,772Gas2,314 624 0 0 0 0 0Gas/Wood/OtherBiomass/Liquid FF8 0 290,366 64,000 105,020 21,366 169,020Distillate Liquid FF672 31 0 0 0 0 0NFF Liquid/NFF Solid/Gas4 1 156,800 40,000 39,696 11,024 79,696Wood28 0 1,074,549 224,000 331,200 80,279 555,200Wood/Other Biomass/NFFLiquid/NFF Solid6 0 194,000 48,000 49,620 13,780 97,620Residual Liquid FF533 31 0 0 0 0 0Total for Limited Use Units3,767 687 8,263,030 1,992,0002,271,724 591,886 4,263,724Grand Total42,952 15,248 177,701,370 82,791,78379,946,496 12,112,314 162,738,279aNFF = costs for units that are not fossilfueled; FF = units that are fossil fueled.3-45 Costs to Control Non-Air Effects Related to Rule Implementation The Agency estimated the additional water us age that would result from the MACT floor level of control to be 110 million gallons per ye ar for existing sources and 0.6 million gallons per year for new sources. In addition to the increased water usage, an additional 3.7 million gallons per year of wastewater would be produced for existing sources and 0.6 million gallons per year for new sources. The Agency estimated the add itional solid waste that would result from the MACT floor level of control to be 102,000 tons pe r year for existing sources and 1 ton per year for new sources

. The costs ($900,000) of handling the addi tional solid waste generated from applying MACT floor technology are accounted for in the control cost estimates for ESP and fabric filter applications. The costs ($20,000) of treating wastewater from venturi and packed bed scrubber are also accounted for in the control cost estimates. Cost Effectiveness To provide additional information on the magnitude of the cost estimates, Table 3-4 shows the cost-effectiveness (c ost/ton reduced estimates) for the HAP and non-HAP pollutants whose emissions are reduced by this rule.

Cost Uncertainties The primary limitation to the cost estimates de veloped for the rule is that costs were calculated for model units rather than each indivi dual boiler or process heater. Consequently, the costs do not characterize any “real” unit. This wa s done for practical reas ons. Because there are over 60,000 units in the U.S., it woul d not be possible to gather unit-specific information for each unit necessary for estimating costs, such as flue gas temperatures and flow rates. Additionally, emission information was only availa ble for less than 1 percent of the units. In order to estimate costs and emission reductions of the rule, model units were developed to represent the population of boilers and process heaters in th e U.S. While sufficient information was not available for characterizing each unit, su fficient emissions and process information were available to develop model units. Each unit in the U.S. was then assigned to a model based on their size and fuel burned. It also should be noted that the costing methodology is the cost algorithms for the control devices provide a cost range of +/- 30 percent. This aspect of the costing methodology reflects the degree of vari ability typically found in study-level cost estimates. This is also the de gree of variability found in the cost methodology employed in the EPA Air Pollution Control Cost Manual, which is an important reference for the cost estimates supplied in the RIA. Cost information available to owners and operators of boilers and process heaters will be more specific a nd accurate. Consequently, the cost estimates may overestimate or underestimate costs.3-46 Table 3-4. Cost Effectiveness (C/E) of Indus trial Boiler and Process Heater MACT on Existing Units and Subcategories

Total Annualized Costs Large Solid Fuel Subcategory Large Solid Fuel Subcategory—

Coal Only Large Solid Fuel Subcategory—

Wood Only Limited Use Solid Fuel Subcategory Control Costs ($) 720,577,200 b 697,619,328 585,932,309 111,687,020 22,957,871 PM Emissions Reduction (Tons/Year) 565,900 563,060 359,920 203,140 2,840

C/E ($/ton PM) 1,273 a 1,239 1,628 550 8,084 Metals Emissions Reduction (Tons/Year) 1,093 1,087 591 496 6

C/E ($/ton metals) 659,266 a 641,784 a 991,425 a 225,175 a 3,826,312 a HCl Emissions Reduction (Tons/Year) 46,515 46,515 45,136 1,379 —

C/E ($/ton HCl) 15,491 a 14,998 a 12,981 a 80,991 a — HAP Emissions Reduction (Tons/Year) 47,608 47,602 45,727 1,875 6

C/E ($/ton HAP) 15,136 14,655 12,814 59,566 3,826,312

a The cost-effectiveness value is based on the total annualized cost of the rule and not on the cost for controlling the

specific pollutant, and, thus, overstates the cost/ton for the specific HAP or other pollutant.
b Costs are in 1999 dollars. Emission reductions are calculated for 2005.
3.4 Projection of New Boilers and Process Heaters Energy Information Administration fuel consum ption forecasts were used in conjunction with existing model boile r population data to project the numbe r and type of new boilers to be installed by 2005. EPA used the following steps to calculate new boile r population estimates:

1. Calculate the percentage change in industrial fuel consumption . Energy Information Administration data were used to obtai n industrial and commercial fuel use projections. The percentage change in consumption (1998 to 2005) in the industrial and commercial sectors was calculated for the following fu el categories using 1998 as the base year (the same year that the model boiler algorithms are based on): steam coal (2.6 percent), natural gas (6.3 percent), residual fuel oil (–7.4 percent), distillate fuel oil (12.0 percent), and biomass (11.5 pe rcent). It should be noted that 1998 was a year of below average energy prices, and that current and potential future energy prices are higher than the historical average. If real fuel prices increase faster than the EIA’s projections, then conservation measur es may lead to fewer projected boilers and process heaters. This trend would lead to an overestimate (upward bias) of the impact estimates presented in this report.3-47 2. Estimate the number of new boilers by model number-fuel type . To predict the number of new boilers in operation by 2005, EPA applied the percentage difference for each fuel category to the 1998 fuel c onsumption of boilers represented by the boiler models to calculate total energy consumed by boilers in 2005 for each model number. The number of new boilers per m odel was calculated by dividing the model fuel forecasts by the annual fuel consumption of one unit and then subtracting the number of units present in 1998, as follows:

Number of New Units = ⎝ ⎜ ⎛ ⎠ ⎟ ⎞ Total energy consumed (2005) [MMBtu/yr]

Avg capacity [MMBtu/hr] x 8,760 [hr/yr] – Number of Units (1998)

Following these steps, EPA projects that 1,458 boilers and 374 process heaters to be installed between 1998 and 2005 will be affected by the new source MACT floor. The only new ICI boilers and process heaters that will be unaffected are those natural gas and distillate fuel units that have input capaciti es less than 10 MMBtu/hr. These projections were developed by model unit type, not by industry.

To assess the distributio n of the boilers and process heat ers estimated to be operating in 2005 across industries, EPA attached unit-level we ights by model number to each unit in the Inventory Database. These weights allow each un it in the Inventory Database to represent a number (or fraction) of units th at are predicted to be in use by the end of 2005. The weights were then summed by two-digit SIC code to es timate the distribution of units by industry.
Table 3-5 presents the projected number of new boilers and process heaters for the MACT floor. Industries with the estimated gr eatest concentrations of new units include chemicals and allied products ( 295), petroleum refining (198), electric services (134), and paper and allied products (96).

3.5 National Engineering Population, Cost Es timates, and Cost-Effectiveness Estimates The Agency estimates that in 2005, 5,562 units (exi sting units and new units) may be affected by the final rule. This population wa s used to estimate national engi neering costs. As discussed previously, the distribution of units by industry shown in Tables 3-5 and 3-6 was determined by weighting 2,186 units with SIC code informati on to represent all 5.562 existing and new units, and then tallying weighted units by SIC code. Th e weights assigned to e ach existing unit in the Inventory Database were derived by comparing the existing unit’s config uration (e.g., fuel type, control type, size) with the 2005 estimated populati on of units with the same configuration. The average cost of control by unit configuration wa s multiplied by the weighted number of units to determine industry-level control cost estimates.3-48 Table 3-5. New Unit Projections by Industry, MACT Floor

SIC Code NAICS Code Description New Units Cost 01 111 Agriculture—Crops — — 02 112 Agriculture—Livestock — — 07 115 Agricultural Services — — 10 212 Metal Mining 6 $47,040 12 212 Coal Mining 1 $7,840 13 211 Oil and Gas Extraction 89 $697,760 14 212 Mining/Quarrying—Nonmetallic Minerals 6 $87,740 17 235 Construction—Special Trade Contractors — — 20 311 Food and Kindred Products 63 $801,836 21 312 Tobacco Prod ucts 7 $54,880 22 313 Textile Mill Products 73 $1,329,391 23 315 Apparel and Other Products from Fabrics — — 24 321 Lumber and Wood Products 61 $1,748,655 25 337 Furniture and Fixtures 47 $1,354,701 26 322 Paper and Allied Products 96 $1,526,704 27 511 Printing, Publishing, and Related Industries 19 $148,960 28 325 Chemicals and Allied Products 295 $3,793,738 29 324 Petroleum Refining and Related Industries 198 $1,552,320 30 326 Rubber and Miscellaneous Plastics Products 44 $385,660 31 316 Leather and Leather Products 5 $39,200 32 327 Stone, Clay, Glass, and Concrete Products 37 $549,975 33 331 Primary Metal Industries 80 $2,873,492 34 332 Fabricated Metal Products 53 $496,920 35 333 Industrial Machinery and Computer Equipment 35 $396,500 36 335 Electronic and Electrical Equipment 40 $313,600 37 336 Transportation Equipment 80 $1,133,423 38 334 Scientific, Optical, and Photographic Equipment 11 $86,240 39 339 Miscellaneous Manufacturing Industries 9 $162,323 40 482 Railroad Transportation — — 42 484 Motor Freight and Warehousing 1 $48,540 46 486 Pipelines, Except Natural Gas 1 $7,840 49 221 Electric, Gas, and Sanitary Services 134 $2,094,546 50 421 Wholesale Trade—Durable Goods — — 51 422 Wholesale Trade—Nondurable Goods — — (continued)3-49 Table 3-5. New Unit Projections by Industry, MACT Floor (continued)

SIC Code NAICS Code Description New Units Cost

55 441 Automotive Dealers and Gasoline Service Stations — — 58 722 Eating and Drinking Places — — 59 445–454 Miscellaneous Retail — — 60 522 Depository Institutions — — 70 721 Hotels and Other Lodging Places — — 72 812 Personal Services 1 $7,840 76 811 Miscellaneous Repair Services — — 80 621 Health Services 6 $209,840 81 541 Legal Services — — 82 611 Educational Services 19 $815,855 83 624 Social Services — — 86 813 Membership Organizations — — 87 541 Engineering, Accounting, Research, Management and Related Services 2 $388,350

89 711/514 Services, N.E.C. — — 91 921 Executive, Legislative, and General Administration — — 92 922 Justice, Public Order, and Safety 4 $153,460 94 923 Administration of Human Resources — — 96 926 Administration of Economic Programs — — 97 928 National Security and International Affairs 2 $97,080 NA SIC Information Not Available 307 $2,497,327 State Parent is a State Government — — 1,832 $25,909,574

Table 3-6 presents industry-le vel population and cost estimat es for boilers and process heaters. The distribution of we ighted units across industries mi rrors that of the analysis population even though it was determined by weigh ting units by configurati on, not industry-level growth estimates. The floor cost of control for the estimated 5,562 boilers and process heaters is $746.5 million, with an average per-un it additional control cost of $134,212.3-50 Table 3-6. Unit Cost and Population Estimates for the Final Rule by Industry, 2005

Total Units Total Cost SIC Code NAICS Code Description Floor Units Percent Floor Costs (by Unit) Percent 01 111 Agriculture—Crops 5 0.08 $628,943 0.08 02 112 Agriculture—Livestock — 0.00 — 0.00 07 115 Agricultural Services — 0.00 — 0.00 10 212 Metal Mining 27 0.48 $6,651,678 0.89 12 212 Coal Mining 6 0.10 $235,107 0.03 13 211 Oil and Gas Extraction 89 1.60 $697,760 0.09 14 212 Mining/Quarrying—Nonmetalli c Minerals 25 0.46 $8,253,479 1.11 17 235 Construction—Special Trade Contractors — 0.00 — 0.00 20 311 Food and Kindred Products 312 5.60 $28,641,029 3.84 21 312 Tobacco Products 28 0.51 $5,460,065 0.73 22 313 Textile Mill Produc ts 360 6.47 $67,982,598 9.11 23 315 Apparel and Other Products from Fabrics 4 0.08 $472,691 0.06 24 321 Lumber and Wood Products 483 8.68 $31,368,106 4.20 25 337 Furniture and Fixtures 311 5.59 $17,723,831 2.37 26 322 Paper and Allied Pr oducts 565 10.15 $118,213,485 15.84 27 511 Printing, Publishing, and Re lated Industries 19 0.34 $148,960 0.02 28 325 Chemicals and Allied Products 644 11.58 $101,104,523 13.54 29 324 Petroleum Refining and Rela ted Industries 217 3.91 $3,806,027 0.51 30 326 Rubber and Miscellaneous Plas tics Products 73 1.32 $5,972,514 0.80 31 316 Leather and Leather Products 7 0.13 $607,530 0.08 32 327 Stone, Clay, Glass, and Conc rete Products 57 1.02 $4,772,789 0.64 33 331 Primary Metal Industries 159 2.85 $23,403,883 3.14 34 332 Fabricated Metal Pr oducts 87 1.56 $7,405,792 0.99 35 333 Industrial Machinery and Computer Equipment 84 1.51 $9,655,328 1.29 36 335 Electronic and Electrical Equipment 52 0.93 $3,744,828 0.50 37 336 Transportation Equipment 300 5.39 $44,905,003 6.02 38 334 Scientific, Optical, and Photographic Equipment 26 0.46 $3,277,844 0.44 39 339 Miscellaneous Manufacturi ng Industries 12 0.22 $826,346 0.11 40 482 Railroad Transportation 9 0.16 $1,251,062 0.17 42 484 Motor Freight and Warehousing 12 0.22 $1,507,689 0.20 46 486 Pipelines, Except Natural Gas 1 0.02 $7,840 0.00 49 221 Electric, Gas, an d Sanitary Services 718 12.91 $134,204,401 17.98 50 421 Wholesale Trade—Durable Goods 6 0.12 $2,154,760 0.29 51 422 Wholesale Trade—Nondurable Goods 4 0.07 $1,673,511 0.22 55 441 Automotive Dealers and Gasoline Service Stations — 0.00 — 0.00
(continued)3-51 Table 3-6. Unit Cost and Population Estimates for the Final Rule by Industry, 2005 (continued)

Total Units Total Cost

SIC Code NAICS Code Description Floor Units Percent Floor Costs (by Unit) Percent 58 722 Eating and Drinking Places — 0.00 — 0.00 59 445–454 Miscellaneous Retail — 0.00 — 0.00 60 522 Depository Institutions — 0.00 — 0.00 70 721 Hotels and Other Lodging Places 2 0.04 $567,811 0.08 72 812 Personal Services 1 0.02 $7,840 0.00 76 811 Miscellaneous Repair Services 4 0.08 $625,531 0.08 80 621 Health Services 86 1.55 $13,015,265 1.74 81 541 Legal Services — 0.00 — 0.00 82 611 Educational Services 251 4.52 $54,837,468 7.35 83 624 Social Services 5 0.08 $820,191 0.11 86 813 Membership Organizations — 0.00 — 0.00 87 541 Engineering, Accounting, Research, Management and Re lated Services 38 0.68 $2,240,544 0.30 89 711/514 Services, N.E.C. 2 0.04 $918,360 0.12 91 921 Executive, Legislative, and General Administration 2 0.04 $312,765 0.04 92 922 Justice, Public Order, and Safety 69 1.23 $13,087,190 1.75 94 923 Administration of Human Resources 2 0.04 $107,496 0.01 96 926 Administration of Economic Programs 8 0.15 $1,746,157 0.23 97 928 National Security and International Affairs 64 1.16 $16,355,556 2.19 NA SIC Information Not Available 326 5.86 $5,085,199 0.68 State Parent is a state government — 0.00 — 0.00 5,562 $746,486,7744-1 SECTION 4 PROFILES OF AFFECTED INDUSTRIES
This section contains profiles of the major industries affected by the MACT for boilers and process heaters. Included are pr ofiles of the following industries:

 Textile Mill Products (SIC 22/NAICS 313)

 Lumber and Wood Products (SIC 24/NAICS 321)

 Furniture and Related Product Ma nufacturing (SIC 25/NAICS 337)

 Paper and Allied Products (SIC 26/NAICS 322)

 Medicinal Chemicals and Botanical Products and Pharmaceutical Preparations (SICs 2833, 2834/NAICS 32451)

 Industrial Organic Chemicals (SIC 2869/NAICS 3251)

 Electric Services (SIC 4911/NAICS 22111)

4.1 Textile Mill Products (SIC 22/NAICS 313) The textile industry is one of the few i ndustries found throughout the world, from the most industrialized countries to the poorest. This industry includes fi rms producing the following products: broadwoven fabric; weft, lace, and warp knit fabrics; carpets and rugs; spun yarn products; and man-made fibers. The United States ha s typically run a trade deficit in the textiles sector in recent years, im porting about $1.3 billion more th an was exported in 1995. Although trade has become an increasingly important part of this industry, trade in this segment is relatively small compared with trade in the dow nstream apparel segment. In 1996, the total value of shipments for the text ile industry was $80,242 million.

4.2 Lumber and Wood Products (SIC 24/NAICS 321) The lumber and wood products industry compri ses a large number of establishments engaged in logging; operating sawmills and pl aning mills; and manufact uring structural wood panels, wooden containers, and other wood pr oducts. Table 4-1 lists the lumber and wood products markets that are likely to be affected by the regulation on boilers. Most products are produced for the domestic market, but exports in creasingly account for a larger proportion of sales (Haltmaier, 1998). The largest consumers of lumber and wood produc ts are the remodeling and construction industries.4-2 Table 4-1. Lumber and Wood Products Markets Li kely to Be Affected by the Regulation

SIC NAICS Description 2421 321113 Sawmills and Planing Mills, General 2434 33711 Wood Kitchen Cabinets 2449 32192 Wood Containers, N.E.C. 2491 32114 Wood Preserving 2493 321219 Reconstituted Wood Products 2499 321999 Wood Products, N.E.C. Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.
In 1996, the lumber and wood products indus try’s total value of shipments was $85,724.0 million. As seen in Table 4-2, shipment values increased steadily through the late 1980s before declining slightly through the early 1990s as new construction starts and furniture purchases declined (Haltmaier, 1998). Shipment values recovered, however, as the economy expanded in the mid-1990s. Table 4-2. Value of Shipments for th e Lumber and Wood Products Industry (SIC 24/NAICS 321), 1987–1996

Year Value of Shipments (1992 $10 6 ) 1987 85,383.4 1988 85,381.2 1989 85,656.8 1990 86,203.0 1991 81,666.0 1992 81,564.8 1993 74,379.6 1994 79,602.0 1995 87,574.6 1996 85,724.0
Sources: U.S. Department of Commer ce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures [Multiple Years] . Washington, DC: Government Printing Office.4-3 4.2.1 Supply Side of the Industry This section describes the lumber industry’ s production processes, output, costs of production, and capacity utilization.

4.2.1.1 Production Processes
Sawn lumber . Sawn lumber is softwood or hardwood trimmed at a sawmill for future uses in construction, flooring, furn iture, or other markets. Soft woods, such as Douglas fir and spruce, are used for framing in residential or light-commercial construction. Hardwoods, such as maple and oak, are used in flooring, furn iture, crating, and ot her applications.
Lumber is prepared at mills using a four-step process. First, logs are debarked and trimmed into cants, or partially finished lumber. The cants are then cut to specific lengths. Logs are generally kept wet during storage to preven t cracking and to keep them supple. However, after being cut, the boards undergo a drying process, either in open air or in a kiln, to reduce the moisture content. The drying process may take several months and varies according to the plant’s climate and the process us ed. Finally, the lumber may be tr eated with a surface protectant to prevent sap stains and pr epare it for export (EPA, 1995a).
Reconstituted wood products . Reconstituted wood products, such as particleboard, medium density fiberboard, hardboard, and orie nted strandboard, are made from raw wood that is combined with resins and other additives and processed into boards. The size of the wood particles used varies from sawdust to stra nds of wood. Once combined, the ingredients are formed into a mat and then, at high temperatures , pressed into a board. A final finishing process prepares the boards for delivery.
Wood preserving . Wood is treated with preservati ve to protect it from mechanical, physical, and chemical influences (EPA, 1995a). Treatment agents are either water-based inorganics, such as copper arsenate (78 percen t), or oil-borne organi cs, such as creosote (21 percent) (EPA, 1995a). Wood preservatives ar e usually applied using a pressure treatment process or a dipping tank. Producers achieve the best results when the lumber’s moisture content is reduced to a point where the preservative can be easily soaked into the wood. Treated wood is then placed in a kiln or stacked in a low-humidity climate to dry.

4.2.1.2 Types of Output The lumber and wood products industry produces essential inputs in to the construction, remodeling, and furniture sectors. Lumber and re constituted wood products are produced in an array of sizes and can be trea ted to enhance their value and shelf-life. These products are4-4 intermediate goods; they are purch ased by other industries and inco rporated into higher valueadded products. In addition to sawmills, the lu mber and wood products in dustry includes kitchen cabinets, wood containers, and other wooden produc ts used for fabricating finished goods for immediate consumption.

4.2.1.3 Major By-Products and Co-Products Shavings, sawdust, and wood chips are the pr incipal co-products of sawn lumber. Paper mills and makers of reconstituted wood products fr equently purchase this material as an input. By-products are limited to emissions from the drying process and from use of preservatives.
Very little solid waste is generated by reconstituted wood products manufacturing. Because the production process incor porates all parts of the sawn l og, little is left over as waste. However, air emissions from dryers are a source of emissions.
Wood preserving results in two types of by- products: air emissions and process debris. As preservatives dry, either in a kiln or outside, they emit vari ous chemicals into the air. At plants with dipping processes, w ood chips, stones, and other debris build up in the dipping tank. The debris is routinely co llected and disposed of.

4.2.1.4 Costs of Production The costs of production for the wood products industry fluctuate with the demand for the industry’s products. Most notably, the costs of production steadily dec lined during the early 1990s as recession stifled furniture purchases and new housing starts (see Table 4-3). Overall, employment in the lumber and wood products in dustry increased approximately 6 percent from 1987 to 1996. During this same period, payroll costs decreased 12 percent, indicating a decrease in average annual income per employee. New capita l investment and costs of materials generally moved in tandem over the 10-year period, in creasing from 1987 to 1990 and 1994 to 1996 and decreasing from 1991 to 1993.

4.2.1.5 Capacity Utilization Full production capacity is broadly defined as the maximum level of production an establishment can obtain under nor mal operating conditions. The capaci ty utilization ratio is the ratio of the actual production leve l to the full production level. Ta ble 4-4 presents the historical trends in capacity utilization for the lumber and wood products industry. The varying capacity utilization ratios reflect adjus ting production levels and new pr oduction facilities going on- or off-line. The capacity utilization ratio for the indu stry in 1996 was 78; the average over the last 6 years was 79 percent.4-5 Table 4-3. Inputs for the Lumber and Wood Products Industry (SIC 24/NAICS 321), 1987– 1996

Labor

Year Quantity (10 3 ) Payroll (1992 $10 6 ) Materials (1992 $10 6 ) New Capital Investment (1992 $10 6 ) 1987 698.4 15,555.5 50,509.2 2,234.3 1988 702.4 15,800.0 51,341.0 2,099.4 1989 684.2 15,381.3 51,742.2 2,329.9 1990 677.7 15,612.9 53,369.0 2,315.3 1991 623.6 14,675.8 50,416.3 2,006.5 1992 655.8 13,881.8 48,570.0 1,760.1 1993 685.4 11,798.9 45,300.3 1,538.1 1994 718.5 12,212.5 48,535.6 1,956.8 1995 740.2 13,915.4 53,732.9 2,553.1 1996 738.7 13,933.7 52,450.1 2,659.9

Sources: U.S. Department of Commer ce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures [Multiple Years] . Washington, DC: Government Printing Office. Table 4-4. Capacity Utilization Ratios for Lumber and Wood Products Industry, 1991– 1996

1991 1992 1993 1994 1995 1996
78 80 81 80 77 78 Note: All values are percentages. Source: U.S. Department of Commer ce, Bureau of the Census. 1998. Survey of Plant Capacity: 1996. Washington, DC: Government Printing Office.
4.2.2 Demand Side of the Industry
This section describes the demand side of th e market, including pr oduct characteristics, the uses and consumers of the final products, organization of the industry, and markets and trends.

4.2.3 Product Characteristics Lumber and wood products are valued both for their physical attribut es and their relative low cost. Wood is available in varying degrees of durability, shades, and sizes and can be easily shaped. Lumber and wood products have long been the principal raw materials for the residential and light commercial construction industries, the remodeling indus try, and the furniture industry.4-6 Wood is readily available because over one-third of the United States is forested. The ready supply of wood reduces its costs.

4.2.4 Uses and Consumers of Outputs Lumber and wood products are used in a wide range of applications, including residential and nonresidential construction; repair/r emodeling and home improvement projects; manufactured housing; millwork and wood products; pulp, paper, and paperboard mills; toys and sporting goods; kitchen cabinets; crates and other wooden containers ; office and household furniture; and motor homes and recrea tional vehicles (Haltmaier, 1998).

4.2.5 Organization of the Industry In 1992, 33,878 companies produced lumber and wood products and operated 35,807 facilities, as shown in Table 4-5. By way of comparison, in 1987, 32,014 companies controlled 33,987 facilities. About two-thirds of all establishments have nine or fewer employees. Between 1987 and 1992, the number of facilities with nine or fewer employees increased more than 10 percent to 23,590. These fac ilities’ share of the value of ship ments increased about 18.3 percent. Although the number of es tablishments employing 100 to 249 people decreased during that time, that category’s shipment value jumped nearly 40 percent. The remaining facility categories lost both facilities and value of shipment.

Market structure can affect th e size and distribution of regul atory impacts. Concentration ratios are often used to evaluate the degree of competition in a market, with low concentration indicating the presence of a competitive mark et, and higher concentration suggesting lesscompetitive markets. Firms in less-concentrated industries are more likely to be price takers, while firms in more-concentrated industries are mo re likely to influence market prices. Typical measures include four- and eight-firm concentr ation ratios (CR4 and CR8) and HerfindahlHirschmann indices (HHI). The CR4 for lumber and wood products subsectors represented in the boilers inventory database range s between 13 and 50, meaning that, in each subsector, the top firms’ combined sales ranged from 13 to 50 percen t of that respective subsector’s total sales. The CR8 ranges from 47 to 66 (U.S. Department of Commerce, 1995d).
Although there is no obj ective criterion for determining market structure based on the values of concentration ratios, the 1992 Department of Justic e’s (DOJ’s) Horizontal Merger Guidelines provide criteria for doing so based on HHIs. According to these criteria, industries with HHIs below 1,000 are considered unconcentrated (i.e., more competitive), those with HHIs between 1,000 and 1,800 are considered moderately concentrated (i.e., moderately competitive), and those with HHIs above 1,800 are considered hi ghly concentrated (i.e., less competitive)4-7 Table 4-5. Size of Establishments and Va lue of Shipments for the Lumber and Wood Products Industry (SIC 24/NAICS 321)

1987 1992

Average Number of Employees in Establishment Number of Facilities Value of Shipments (1992 $10 6 ) Number of Facilities Value of Shipments (1992 $10 6 ) 1 to 4 employees 14,562 2,769.7 15,921 3,288.9 5 to 9 employees 6,702 4,264.4 7,669 5,030.4 10 to 19 employees 5,353 6,982.3 5,331 6,902.8 20 to 49 employees 4,160 28,551.3 3,924 26,964.9 50 to 99 employees 1,702 (D) 1,615 (D) 100 to 249 employees 1,190 24,583.3 1,082 34,051.4 250 to 499 employees 260 12,093.4 219 (D) 500 to 999 employees 47 3,907.9 39 3,331.4 1,000 to 2,499 employees 4 2,231.3 4 598.6 2,500 or more employees 2 (D) 3 1,396.4 Total 33,987 85,383.4 35,807 81,564.8
(D) = undisclosed Sources: U.S. Department of Commer ce, Bureau of the Census. 1991. 1987 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office.
(DOJ, 1992). Firms in less-concentrat ed industries are more likely to be price takers, while firms in more-concentrated industries are more likely to be able to influence market prices. The unconcentrated nature of the markets is al so indicated by HHIs of 1,000 or less (DOJ, 1992). Table 4-6 presents various measures of market concentration for sectors within the lumber and wood products industry. All lumber and wood produc ts industries are consid ered unconcentrated and competitive.

4.2.6 Markets and Trends The U.S. market for lumber and wood pr oducts is maturing, and manufacturers are looking to enter other markets. Although 91 percen t of the industry’s products are consumed by the U.S. domestic market, the share of exports in creases each year. Exports more than doubled in value from $3 billion in 1986 to $7.3 billion in 1996 (Haltmaier, 1998). The U.S. market grew only 2 percent between 1986 and 1996. Ameri can manufacturers are focusing on growing construction markets in Canada, Mexico, and the Pacific Rim, with products such as durable hardwood veneer products and reconstituted wood boards (EPA, 1995a).4-8 Table 4-6. Measures of Market Concentrat ion for Lumber and Wood Products Markets

SIC Description Comparable NAICS CR4 CR8 HHI Number of Companies Number of Facilities 2421 Saw Mills and Planing Mills 321912, 321113, 321918, 321999 14 20 78 5,302 6004

2434 Wood Kitchen Cabinets 33711 19 25 156 4,303 4323 2449 Wood Containers, N.E.C. 32192 34 47 414 217 225 2491 Wood Preserving 321114 17 28 152 408 486 2493 Reconstituted Wood Products 321219 50 66 765 193 288

2499 Wood Products, N.E.C. 339999, 333414, 32192, 321999 13 19 70 2,656 2754

Sources: U.S. Department of Commer ce, Bureau of the Census. 1995d. 1992 Concentration Ratios in Manufacturing . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary. Washington, DC: Government Printing Office.
4.3 Furniture and Related Product Manufacturing (SIC 25/NAICS 337) More than 20,000 establishments in the Unite d States produce furn iture and furniturerelated products. These establishments are locate d across the United States but are traditionally most concentrated in southern states, such as North Carolina, Mississippi, Alabama, and Tennessee. According to the “1997 Economic Cens us,” these establishments employed more than 600,000 people and paid annual wages of n early $15 billion. The overall industry-wide value of shipments was $63.9 billion that ye ar (U.S. Department of Commerce, 2001).
This industry is in a state of change: rapid U.S. economic growth translated into vigorous sales of household and office furnitu re, but this trend is unlikely to continue as the U.S. economy cools after its record r un. Adding to industry fluctuation is th e merger of two large firms, Lay-ZBoy and LADD Furniture. Although the industry include s a multitude of niche market players, it is really dominated by a few large companies that operate several subsidiaries, each with its own brand identity. It is unclear whether the merg er between two key players in the market will compel other large manufacturers to pursue mergers and acquisitions.
What is clear, however, is that large U.S. manu facturers will seek to leverage their brand identities into wider profit margins by operati ng direct sales establis hments and co-branding. Manufacturers that are moving into retail and di stribution include Bassett Furniture, Thomasville Furniture, Ethan Allen Interiors, and Drexel. Co -branding efforts are aimed at capitalizing on the combined power of two identities, such as th e Thomas Kinkade Collection from Lay-Z-Boy and4-9 popular artist Thomas Kinkade and the Ernest Hemingway Collection from Thomasville. The overarching goal is to enhance margins and wa rd off invigorated competition from foreign companies that have used this strategy to cap ture U.S. market share, such as the Swedish manufacturer Ikea (Lemm, 2000).
U.S. imports of household furniture totale d nearly $7 billion in 1998. Between 1992 and 1998, furniture imports grew at an annualized rate of nearly 15 pe rcent. Jamie Lemm, an analyst with the U.S. Department of Commerce’s Office of Consumer Goods attributes this growth to changes in U.S. manuf acturing and markets:
A portion of [the] increase can be attribut ed to the labor-intensive furniture parts imported by U.S. manufacturers to enhance produ ct lines, but the increase also signifies the growing importance of the U.S. market to foreign firms. While some U.S. manufacturers operate showroom s, galleries, and retail outlets in foreign markets, few sell internationally on a large scale. In 1998, U.S. furniture exports totaled $1.6 billion, accounting for only 6 percent of all U.S. product shipments.

4.4 Paper and Allied Products (SIC 26/NAICS 322) The paper and allied products industry is one of the largest manufacturing industries in the United States. In 1996, the industry shipped nearly $150 billion in paper commodities. The industry produces a wide range of wood pulp, pr imary paper products, and paperboard products such as printing and writing papers, industria l papers, tissues, container board, and boxboard. The industry also includes manu facturers that “convert” primar y paper and paperboard into finished products like envelopes, packaging, and shipping containers ( EPA, 1995b). Paper and allied products industry subsectors that are likely to be affected by the regulation are listed in Table 4-7. Table 4-7. Paper and Allied Products Industr y Markets Likely to Be Affected by Regulation

SIC NAICS Industry Description 2611 32211 Pulp Mills 2621 32212 Paper Mills 2676 322291 Sanitary Paper Products Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.4-10 Table 4-8 lists the paper and allied products industry’s value of shipments from 1987 to 1996. The industry’s performance is tied to raw ma terial prices, labor conditions, and worldwide inventories and demand (EPA, 1995b). Performance over the 10-year period was typical of most manufacturing industries. The i ndustry expanded in the late 1980s , then contracted as demand tapered off as the industry suffered recessiona ry effects. In the two years after 1994, the industry’s value of shipments incr eased 9.3 percent to $149.5 billion. Table 4-8. Value of Shipments for the Paper and Allied Products Industry (SIC 26/NAICS 322), 1987–1996

Year Value of Shipments (1992 $10 6 ) 1987 129,927.8 1988 136,829.4 1989 138,978.3 1990 136,175.7 1991 132,225.0 1992 133,200.7 1993 131,362.2 1994 136,879.9 1995 135,470.3 1996 149,517.1

Sources: U.S. Department of Commer ce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures, [Multiple Years] . Washington, DC: Government Printing Office.
4.4.1 Supply Side of the Industry

4.4.1.1 Production Process The manufacturing paper and allied products in dustry is capital- a nd resource-intensive, consuming large amounts of pulp wood and water in the manufacturing process. Approximately half of all paper and allied produc ts establishments are integrated facilities, meaning that they produce both pulp and paper on-site. The rema ining half produce only paper products; few facilities produce only pulp (EPA, 1995b).4-11 The paper and paperboard manufacturing proces s can be divided into three general steps: pulp making, pulp processing, and paper/paperb oard production. Paper and paperboard are manufactured using what is essentially the same process. The principal difference between the two products is that paperboard is thicker than paper’s 0.3 mm.
Producers manufacture pulp mixtures by using chemicals, machines, or both to reduce raw material into small fibers. In the case of wood, the most common pulping material, chemical pulping actions release cellulose fibers by selectively destroying the chemical bonds that bind the fibers together (EPA, 1995b). Impurities are re moved from the pulp, which then may be bleached to improve brightness. Only about 20 percent of pulp and paper mills practice bleaching (EPA, 1995b). The pulp may also be furt her processed to aid in the paper-making
process. During the paper-making stage, the pulp is st rengthened and then converted into paper. Pulp can be combined with dyes, resins, filler materials, or other additives to better fulfill specifications for the final product. Next, the wa ter is removed from the pulp, leaving the pulp on a wire or wire mesh conveyor. The fibers bond together as they are carried through heated presses and rollers. The paper is stored on larg e rolls before being shipped for conversion into another product, such as envelopes and boxes, or cut into paper sheets for immediate consumption.

4.4.1.2 Types of Output The paper and allied products industry’s outpu t ranges from writing papers to containers and packaging. Paper products include printing and writing papers; paperboard boxes; corrugated and solid fiber boxes; fiber cans, drums, and simi lar products; sanitary food containers; building paper; packaging; bags; sanitary paper napkins ; envelopes; stationary products; and other converted paper products.

4.4.1.3 Major By-Products and Co-Products The paper and allied products industry is the la rgest user of industrial process water in the United States. In 1988, a typical mill used betw een 16,000 and 17,000 gallons of water per ton of paper produced. The equivalent amount of waste water discharged each day is about 16 million cubic meters (EPA, 1995b). Most fa cilities operate waste water trea tment facilities on site to remove biological oxygen demand (BOD), total suspended solids (TSS), and other pollutants before discharging the wate r into a nearby waterway.4-12 4.4.1.4 Costs of Production
Historical statistics for the co sts of production for the paper and allied products industry are listed in Table 4-9. From 1987 to 1996, industry payroll generally ranged from approximately $19 to 20 billion. Employment peaked at 633,200 people in 1989 and declined slightly to 630,600 people by 1996. Materials costs averaged $74.4 billion a year and new capital investment averaged $8.3 billion a year. Table 4-9. Inputs for the Paper and Allied Products Industry (SIC 26/NAICS 322), 1987– 1996

Labor
Year Quantity (10 3 ) Payroll (1992 $10 6 ) Materials (1992 $10 6 ) New Capital Investment (1992 $10 6 ) 1987 611.1 20,098.6 70,040.6 6,857.5 1988 619.8 19,659.0 73,447.4 8,083.8 1989 633.2 19,493.1 75,132.5 10,092.9 1990 631.2 19,605.2 74,568.8 11,267.2 1991 624.7 19,856.3 72,602.5 9,353.9 1992 626.3 20,491.9 73,188.0 7,962.4 1993 626.3 20,602.6 73,062.6 7,265.2 1994 621.4 20,429.7 76,461.6 6,961.7 1995 629.2 18,784.3 79,968.6 7,056.8 1996 630.6 19,750.0 75,805.9 8,005.9
Sources: U.S. Department of Commer ce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summery . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures [Multiple Years] . Washington, DC: Government Printing Office.
4.4.1.5 Capacity Utilization Table 4-10 presents the trend in capacity ut ilization for the pape r and allied products industry. The varying capacities reflect adjusting production leve ls and new production facilities going on- or off-line. The average capacity uti lization ratio for the paper and allied products industry between 1991 and 1996 was approximately 80, w ith capacity declining slightly in recent
years.4-13 Table 4-10. Capacity Utilization Ratios for the Paper and Allied Products Industry, 1991– 1996

1991 1992 1993 1994 1995 1996 78 80 81 80 77 78 Note: All values are percentages. Source: U.S. Department of Commer ce, Bureau of the Census. 1998. Survey of Plant Capacity: 1996. Washington, DC: Government Printing Office.
4.4.2 Demand Side of the Industry

4.4.2.1 Product Characteristics Paper is valued for its diversity in product t ypes, applications, and low cost due to ready access to raw materials. Manufact urers produce papers of varyi ng durabilities, textures, and colors. Consumers purchasing large quantities of papers may have papers tailored to their specification. Papers may be simple writing pape rs or newsprint for personal consumption and for the printing and publishing industry or durable for conversion into shipping cartons, drums, or sanitary boxes. Inputs in the paper producti on process are readily available in the United States because one-third of the country is forest ed, and facilities generally have ready access to waterways.

4.4.2.2 Uses and Consumers of Products The paper and allied products industry is an integral part of the U.S. economy; nearly every industry and service sector relies on pa per products for its pe rsonal, education, and business needs. Among a myriad of uses, pape rs are used for correspondence, printing and publishing, packing and storage, and sanitary pur poses. Common applications are all manners of reading material, correspondence, sanitary c ontainers, shipping cartons and drums, and miscellaneous packing materials.

4.4.3 Organization of the Industry In 1992, 4,264 companies produced paper and allied products and operated 6,416 facilities. By way of comparison, 4,215 compan ies controlled 1,732 faci lities in 1987. Although the number of small firms and faci lities increased during those 5 y ears, the industry is dominated by high-volume, low-cost producers (Haltmai er, 1998). Even though they account for only 45 percent of all facilities, those w ith 50 or more employees contri bute more than 93 percent of the industry’s total value of shipments (see Tabl e 4-11). (According to the Small Business Administration, those companies employing fewer than 500 employees are “small.”)4-14 Table 4-11. Size of Establishments and Value of Shipments for the Paper and Allied Products Industry (SIC 26/NAICS 322)

1987 1992 Number of Employees in Establishment Number of Facilities Value of Shipments ($10 6 ) Number of Facilities Value of Shipments ($10 6 ) 1 to 4 employees 729 640.6 786 216 4 to 9 employees 531 (D) 565 483 10 to 19 employees 888 1,563.4 816 1,456.5 20 to 49 employees 1,433 18,328.6 1,389 6,366.6 50 to 99 employees 1,018 (D) 1,088 12,811.5 100 to 249 employees 1,176 32,141.7 1,253 35,114.0 250 to 499 employees 308 24,221.1 298 22,281.2 500 to 999 employees 145 28,129.1 159 31,356.5 1,000 to 2,499 employees 63 24,903.1 62 23,115.4 2,500 or more employees 1 (D) Total 1,732 129,927.8 6,416 133,200.7 (D) = undisclosed Sources: U.S. Department of Commer ce, Bureau of the Census. 1990c. 1987 Census of Manufactures, Industry Series: Pulp, Paper, and Board Mills . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995c. 1992 Census of Manufactures, Industry Series: Pulp, Paper, and Board Mills . Washington, DC: Government Printing Office.
For paper and allied products markets likely to be affected by the boilers regulation, the CR4 ranged between 29 and 68 in 1992 (see Table 4-12) . This means that, in each subsector, the top firms’ combined sales ranged from 29 to 68 per cent of their respective industry’s total sales. For example, in the sanitary paper products indus try, the CR4 ratios indicate that a few firms control 68 percent of the market. Th is sector’s moderately concentrated nature is also indicated by its HHI of 1,451 (DOJ, 1992). The remaining two s ectors’ HHIs indicate that their respective markets are unconcentrated (i.e., competitive).

4.4.4 Markets and Trends The Department of Commerce proj ects that shipments of paper a nd allied products will increase through 2002 by an annual average of 2.5 percent (Haltmaier, 1998). Because nearly all of the industry’s products are consumer related, shipment s will be most affected by the health of the U.S. and global economy. The United States is a ke y competitor in the international market for paper products and, after Canada , is the largest exporter of paper products. According to Haltmaier (1998), the largest paper and allied pro ducts exporters in the world are Canada (with 23 percent of the market), the United States (10 to 15 percent), Finland (8 percent), and Sweden (7 percent).4-15 Table 4-12. Measurements of Market Concen tration for Paper and Allied Products Markets

SIC Description CR4 CR8 HHI Number of Companies Number of Facilities 2611 Pulp Mills 48 75 858 29 45 2621 Paper Mills 29 49 392 127 280 2676 Sanitary Paper Products 68 82 1,451 80 150
Sources: U.S. Department of Commer ce, Bureau of the Census. 1995d. 1992 Concentration Ratios in Manufacturing . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995c. 1992 Census of Manufactures, Industry Series: Pulp, Paper, and Board Mills . Washington, DC: Government Printing Office.
4.5 Medicinal Chemicals and Botanical Pro ducts and Pharmaceutical Preparations (SICs 2833, 2834/NAICS 32451) The pharmaceutical preparations industr y (SIC 2834/NAICS 32451) and the medicinal chemicals and botanical produc ts industry (SIC 2833/NAICS 32451) are both primarily engaged in the research, development, manufacture, a nd/or processing of medicinal chemicals and pharmaceutical products. Apart from manuf acturing drugs for human and veterinary consumption, the industries grind, grade, and m ill botanical products that are inputs for other industries. Typically, most facilities cross over into both industries (EPA, 1997a). Products include drugs, vitamins, herbal remedies, and production inputs, such as alkaloids and other active medicinal principals.
Table 4-13 presents both industries’ value of shipments from 1987 to 1996. Medicinals and botanicals’ performance during the late 1980s and early 1990s was mixed. However, shipments increased steadily from 1994 to 1996, incr easing 37.7 percent as na tural products such as herbs and vitamins became more popular (EPA, 1997a). Pharmaceutical preparations’ shipments increased steadily over the 10-y ear period. From 1987 to 1996, the industry’s shipments increased 24.3 per cent to $55.1 billion in 1996.

4.5.1 Supply Side of the Industry

4.5.1.1 Production Processes The medicinals and botanical products i ndustry and the pharmaceutical preparations industry share similar production pr ocesses. Many products of the former are inputs in the latter’s production process. There are three ma nufacturing stages: research and development, preparation of bulk ingredients, a nd formulation of the final product.4-16 Table 4-13. Value of Shipments for the Medic inals and Botanicals and Pharmaceutical Preparations Industries, 1987–1996

Year SIC 2833 a Medicinals & Botanicals ($10 6 ) SIC 2834 a Pharmaceutical Preparations ($10 6 ) 1987 4,629.1 44,345.7 1988 5,375.4 46,399.1 1989 5,708.9 48,083.6 1990 5,535.8 49,718.0 1991 6,637.7 49,866.3 1992 6,438.5 50,417.9 1993 5,669.2 50,973.5 1994 5,774.7 53,144.7 1995 6,404.1 53,225.9 1996 7,952.8 55,103.6

a Comparable NAICS: 325411, 325412. Sources: U.S. Department of Commer ce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures [Multiple Years] . Washington, DC: Government Printing Office.
The research and development stage is a l ong process both to ensu re the validity and benefit of the end product and to satisfy the requirements of stringent federal regulatory committees. (The pharmaceutical industry operate s under strict oversight of the Food and Drug Administration [FDA].) Therefore, every stage in the developm ent of new drugs is thoroughly documented and studied. After a new compound is discovered, it is subjected to numerous laboratory and animal tests. Results are presente d to the FDA via applica tions that present and fully disclose all findings to date. As research and development proceeds, studies are gradually expanded to involve human trials of the new compound. Should FDA approve the compound, the new product is readied for mass production.
To ensure a uniform product, all ingredients are prepared in bulk using batch processes. Companies produce enough of each ingredient to satisfy projected sales demand (EPA, 1997a). Prior to production, all equipment is thoroughly cl eaned, prepared, and validated to prevent any contaminants from entering the production cycle. Most ingredients are prepared by chemical synthesis, a method whereby primary ingredie nts undergo a complex series of processes, including many intermediate stages and chemical reactions in a step-by-step fashion (EPA, 1997a).4-17 After the bulk materials are prepared, they are converted into a final usable form. Common forms include tablets, pi lls, liquids, creams, and ointments. Equipment used in this final stage is prepared in the sa me manner as that involved in th e bulk preparation process. Clean and validated machinery is used to process a nd package the pharmaceuticals for shipment and consumption.

4.5.1.2 Types of Output Both industries produce pharmaceutical and bo tanical products for end consumption and intermediate products for the industries’ own a pplications. Products in clude vitamins, herbal remedies, and alkaloids. Prescription and over-th e-counter drugs are produ ced in liquid, tablet, cream, and other forms.

4.5.1.3 Major By-Products and Co-Products Both industries produce many by-products because of the large number of primary inputs and the extensive chemical pr ocesses involved. Wastes and em issions vary by the process employed, raw materials consumed, and equipment used. In genera l, emissions originate during drying and heating stages and during process wate r discharge. Emissions controls are in place pursuant to environmental regulations. Other wastes include used filters, spent raw materials, rejected product, and reac tion residues (EPA, 1997a).

4.5.1.4 Costs of Production Table 4-14 presents SIC 2833 industry’s costs of production and employment statistics from 1987 to 1996. Employment was stable during th e late 1980s before steadily growing in the 1990s. In 1987, medicinals a nd botanicals employed 11,600 people. By 1996, the industry employed 16,800, an increase of n early 45 percent. Materials co sts matched the increase in shipments over this same period. Industry grow th also fed new capital investments, which averaged $191.2 million a year in the late 1980s and $515.6 million a year in the early to mid1990s.
SIC 2834’s costs of production and employ ment for 1987 to 1996 are presented in Table 4-15. The number of people employe d by the industry ranged between 123,000 and 144,000; employment peaked in 1990 before declining by 21,000 jobs by the end of 1992. During this 10-year period, the cost of materials rose 42.1 percent. The increase is associated with increased product shipments and the develo pment of new, more expensive medications (Haltmaier, 1998). New capital invest ment averaged $2.3 billion a year.4-18 Table 4-14. Inputs for Medicinal Chemic als and Botanical Products Industry (SIC 2833/NAICS 32451), 1987–1996

Labor

Year Quantity (10 3 ) Payroll ($10 6 ) Materials ($10 6 ) New Capital Investment ($10 6 ) 1987 11.6 520.2 2,229.3 158.2 1988 11.3 494.4 2,658.8 194.9 1989 11.4 504.9 3,118.4 263.4 1990 10.9 476.4 2,902.4 218.9 1991 12.5 568.6 3,368.2 512.9 1992 13.0 587.1 3,245.9 550.5 1993 13.0 584.3 2,638.4 470.0 1994 13.9 572.6 2,755.2 480.3 1995 14.1 625.0 3,006.0 356.2 1996 16.8 752.1 3,793.9 752.1
Sources: U.S. Department of Commer ce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures, [Multiple Years] . Washington, DC: Government Printing Office. Table 4-15. Inputs for the Pharmaceutical Pr eparations Industry (SIC 2834/NAICS 32451), 1987–1996

Labor

Year Quantity (10 3 ) Payroll ($10 6 ) Materials ($10 6 ) New Capital Investment ($10 6 ) 1987 131.6 5,759.2 11,693.7 2,032.7 1988 133.4 5,447.2 12,634.8 2,234.0 1989 141.8 6,177.5 12,874.2 2,321.4 1990 143.8 6,223.9 13,237.6 2,035.3 1991 129.1 5,275.8 13,546.6 1,864.7 1992 122.8 4,949.4 13,542.5 2,450.0 1993 128.2 5,184.2 13,508.7 2,385.2 1994 134.2 5,368.4 13,526.1 2,531.9 1995 143.0 5,712.4 15,333.6 2,856.1 1996 136.9 5,547.3 16,611.1 2,317.0
Sources: U.S. Department of Commer ce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures, [Multiple Years] . Washington, DC: Government Printing Office.4-19 4.5.1.5 Capacity Utilization Table 4-16 presents the trend in these rati os from 1991 to 1996 for both industries. The varying capacity ratios reflect adjusting production volumes a nd new production facilities and capacity going both on- and off-line. In 1996, the capacity utilization ratios for SICs 2833 and 2834 were 84 and 67, respectively. Table 4-16. Capacity Utilization Ratios fo r the Medicinal Chemicals and Botanical Products (SIC 2833/NAICS 32451) and Pharmaceutical Preparations (SIC 2834/NAICS 32451) Industries, 1991–1996

1991 1992 1993 1994 1995 1996 SIC 2833/NAICS 32451 84 86 89 80 90 84 SIC 2834/NAICS 32451 76 74 70 67 63 67 Note: Capacity utilization ratio is the ratio of the actual production level to the full production level. All values are percentages. Source: U.S. Department of Commer ce, Bureau of the Census. 1998. Survey of Plant Capacity: 1996 . Washington, DC: Government Printing Office.
4.5.2 Demand Side of the Industry New product introductions and improvements on older medications by the drug industry have greatly improved the heal th and well-being of the U.S. population (Haltmaier, 1998). Products help alleviate or reduce physical, mental , and emotional ailments or reduce the severity of symptoms associated with disease, age, and degenerative conditions. Dietary supplements, such as vitamins and herbal remedies, ensure th at consumers receive nutrients of which they may not ordinarily consume enough. Products are available in a range of dosage types, such as tablets and liquids.
Although prescription medications are increasingl y distributed through th ird parties, such as hospitals and health maintenance organizations , the general population remains the end user of pharmaceutical products. As the average age of the U.S. population adjusts to reflect large numbers of older people, the variety and num ber of drugs consumed increases. An older population will generally consume more medications to maintain and improve quality of life (Haltmaier, 1998).

4.5.3 Organization of the Industry In 1992, 208 companies produced medicinal chemicals and botanical products and operated 225 facilities (see Table 4-17). The number of companies and facilities in 1992 was the same as that of 1987, although shipment values incr eased almost 40 percent. The average facility employed more people in 1992 than in 1987. In fact , the number of facilities employing 50 or4-20 Table 4-17. Size of Establishments and Valu e of Shipments for the Medicinal Chemicals and Botanical Products (SIC 2833/NAICS 32451) and Pharmaceutical Preparations (SIC 2834/NAICS 32451) Industries

1987 1992

Number of Employees in Establishment Number of Facilities Value of Shipments ($10 6 ) Number of Facilities Value of Shipments ($10 6 ) SIC 2833/NAICS 32451 1 to 4 employees 61 20.7 62 23.8 5 to 9 employees 34 38.6 42 58.3 10 to 19 employees 46 237.0 47 357.1 20 to 49 employees 47 287.3 29 182.0 50 to 99 employees 15 273.6 25 653.9 100 to 249 employees 12 520.6 10 5,163.4 250 to 499 employees 5 753.0 4 (D) 500 to 999 employees 4 2478.2 3 (D) 1,000 to 2,499 employees 1 (D) 3 (D) Total 225 4629.1 225 6,438.5
SIC 2834/NAICS 32451 1 to 4 employees 158 58.7 152 115.6 5 to 9 employees 108 178.8 73 105.4 10 to 19 employees 102 320.3 101 284.6 20 to 49 employees 117 932.5 110 815.7 50 to 99 employees 66 1231.0 65 1,966.8 100 to 249 employees 76 3596.0 77 2,912.4 250 to 499 employees 50 9239.7 56 11,394.6 500 to 999 employees 23 4946.9 30 10,077.7 1,000 to 2,499 employees 24 15,100.9 21 14,525.7 2,500 employees or more 8 8740.9 6 8,219.4 Total 732 44,345.7 691 50,417.9 (D) = undisclosed Sources: U.S. Department of Commer ce, Bureau of the Census. 1990a. 1987 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office.
more people grew from 37 to 45. These facilities accounted for the lion’s share of the industry’s shipments. According to the Small Business Administration, companies in this SIC code are considered small if they employ fewer than 750 em ployees. It is unclear what percentage of the facilities listed in Table 4-17 are small companies.4-21 In 1992, 585 companies manufactured pharmaceu tical preparations and operated 691 facilities. By way of comparison, 640 compan ies operated 732 facilities in 1987. Although the number of facilities declined by 41, no particular category lost or gained an exceptional number of facilities. The biggest movement was in the five to nine employees category, which lost 35 facilities. In both years, facilities with more than 50 employees accounted for at least 95 percent of the industry’s shipments.
Table 4-18 presents the measures of market concentration for both industries. For the medicinals and botanicals industry, the CR4 was 76 in 1992, and the CR8 was 84 (U.S. Department of Commerce, 1995b). The highly concen trated nature of the market is further indicated by an HHI of 2,999 (DOJ, 1992). Accordi ng to the Department of Justice’s Horizontal Merger Guidelines, industries with HHIs above 1,800 are less competitive.

Table 4-18. Measures of Market Concentration for the Medicinal Chemicals and Botanical Products (SIC 2833/NAICS 32451) and Pharma ceutical Preparations (SIC 2834/NAICS 32451) Industries

SIC NAICS Industry CR4 CR8 HHI Number of Companies Number of Facilities 2833 32451 Medicinal Chemicals and Botanical Products 76 84 2,999 208 225

2834 32451 Pharmaceutical Preparations 26 42 341 585 691

Sources: U.S. Department of Commer ce, Bureau of the Census. 1995d. 1992 Concentration Ratios in Manufacturing . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office.
The pharmaceuticals preparations industry is less concentrated than the medicinal chemicals and botanical produc ts industry. For SIC 2834, the CR4 and CR8 were 26 and 42, respectively, in 1992. The industry’s HHI was 341, indicating a competitive market.

4.5.4 Markets and Trends According to the Department of Commerce, global growth in the consumption of pharmaceuticals is projected to accelerate over th e coming decade as populations in developed countries age and those in devel oping nations gain wider access to health care. Currently, the United States remains the largest market for dr ugs, medicinals, and botanicals and produces more new products than any other country (Haltmaier, 1998). But, n early two-fifths of American producers’ sales are generated abroad. Top mark ets for American exports are China, Canada,4-22 Mexico, Australia, and Japan. Most imports originate in Canada, Russia, Mexico, Trinidad and Tobago, and Norway.

4.6 Industrial Organic Chemicals Industry (SIC 2869/NAICS 3251) The industrial organic chemicals (n ot elsewhere classified) industry (SIC 2869/NAICS 3251) produces orga nic chemicals for end-use app lications and for inputs into numerous other chemical manufacturing industries. In nominal terms, it was the single largest segment of the $367 billion chemical and allied products industry (SIC 28) in 1996, accounting for approximately 17 percent of the industry’s shipments.
All organic chemicals are, by definition, car bon-based and are divide d into two general categories: commodity and specialty. Commodity chemical manufacturers compete on price and produce large volumes of staple chemicals using continuous manufacturing processes. Specialty chemicals cater to custom markets, using ba tch processes to produ ce a diverse range of chemicals. Specialty chemicals generally require more technical expertise and research and development than the more standardized commodity chemicals industry (EPA, 1995c). Consequently, specialty chemical manufacturers have a greater value added to their products. End products for all industrial organic chemical producers are as varied as synthetic perfumes, flavoring chemicals, gly cerin, and plasticizers.
Table 4-19 presents the shipments of industr ial organic chemicals from 1987 to 1996. In real terms, the industry’s shipments rose in the late 1980s to a high of $54.9 billion before declining in the early 1990s as the U.S. economy went into recession. By the mid-1990s, the industry recovered, as product values reached record highs (Haltmaier, 1998). Between 1993 and 1996, the industry’s shipments grew 7.3 percent to $57.7 billion.

4.6.1 Supply Side of the Industry

4.6.1.1 Production Processes Processes used to manufacture industrial orga nic chemicals are as varied as the endproducts themselves. There are thousands of po ssible ingredients and hund reds of processes. Therefore, the discussion that follows is a ge neral description of the ingredients and stages involved in a typical manufacturing process.4-23 Table 4-19. Value of Shipments for the Industr ial Organic Chemicals, N.E.C. Industry (SIC 2869/NAICS 3251), 1987–1996

Year Value of Shipments (1992 $10 6 ) 1987 48,581.7 1988 53,434.7 1989 54,962.9 1990 53,238.8 1991 51,795.6 1992 54,254.2 1993 53,805.2 1994 57,357.1 1995 59,484.3 1996 57,743.3

Sources: U.S. Department of Commer ce, Bureau of the Census. 1995b. 1992 Census of Manufactures, Industry Series: Industrial Organic Chemicals . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures, Multiple Years . Washington, DC: Government Printing Office.
Essentially a set of ingredient s (feedstocks) is combined in a series of reactions to produce end products and intermediates (EPA, 1995c). The typical chemical synthesis processes incorporate multiple feedstocks in a series of chemical reactions. Commodity chemicals are produced in a continuous reactor, and specialty chemicals are produced in batches. Specialty chemicals may undergo a series of reaction step s, as opposed to commodity chemicals’ one continuous reaction because a fi nite amount of ingredients are prepared and used in the production process. Reactions usually take place at high temperatures, with one or two additional components being intermittently added. As th e production advances, by-products are removed using separation, distillation, or refrigeration techniques. The final product may undergo a drying or pelletizing stage to form a more manageable substance.

4.6.1.2 Types of Output Miscellaneous industrial organi c chemicals comprise nine ge neral categories of products:

 aliphitic and other acyclic organic chemical s (ethylene); acetic, chloroaceptic, adipic, formic, oxalic, and tartaric acids and thei r metallic salts; chloral, formaldehyde, and methylamine;

 solvents (ethyl alcohol etc.); methano l; amyl, butyl, and ethyl acetates; ethers; acetone, carbon disulfide and chlorinated solvents;

 polyhydric alcohols (synthet ic glycerin, etc.);4-24  synthetic perfume and flavoring materi als (citral, methyl , oinone, etc.);

 rubber processing chemicals, both accelerat ors and antioxidants (cyclic and acyclic);

 cyclic and acyclic plasticize rs (phosphoric acid, etc.);

 synthetic tanning agents;

 chemical warfare gases; and

 esters, amines, etc., of polyhydric alcohols and fatty and other acids.

4.6.1.3 Major By-Products and Co-Products Co-products, by-products, and emissions vary according to the ingred ients, processes, maintenance practices, and equipment used (EPA, 1997b). Frequently, residuals from the reaction process that are separated from the end product are resold or possibly reused in the manufacturing process. A by-product from one pr ocess may be another’s input. The industry is strictly regulated because it emits chemicals thro ugh many types of media, including discharges to air, land, and water, and because of the volume and composition of these emissions.

4.6.1.4 Costs of Production Of all the factors of production, employment in industrial organic chemicals fluctuated most often between 1987 and 1996 (see Table 4-20). During that time, employment fell 8.18 percent to 92,100, after a high of 101,000 in 1991. Most jobs lost were at the production level (Haltmaier, 1998). Facilities became far more computerized, incorporating advanced technologies into the production process. Even with the drop in employment, payroll was $200 million more in 1995 than in 1987. The cost of ma terials fluctuated between $29 and $36 billion for these years, and new capital investment averaged $3,646 million a year.

4.6.1.5 Capacity Utilization Table 4-21 presents the trend in capacity utilization ratios from 1991 to 1996 for the industrial organic chemicals industry. The varyin g capacity utilization rati os reflect changes in production volumes and new production facilities and capacities going on- and off-line. The capacity utilization ratio for the industry averaged 85.3 over the 6-year period presented.4-25 Table 4-20. Inputs for the Industrial Organic Chemicals Industry (SIC 2869/NAICS 3251), 1987–1996

Labor Year Quantity (10 3 ) Payroll (1992 $10 6 ) Materials (1992 $10 6 ) New Capital Investment (1992 $10 6 ) 1987 100.3 4,295.8 28,147.7 2,307.4 1988 97.1 4,045.1 29,492.8 2,996.5 1989 97.9 3,977.4 29,676.4 3,513.0 1990 100.3 4,144.6 29,579.2 4,085.5 1991 101.0 4,297.3 29,335.2 4,428.7 1992 100.1 4,504.2 31,860.6 4,216.6 1993 97.8 4,540.2 30,920.1 3,386.1 1994 89.8 4,476.5 33,267.4 2,942.8 1995 92.1 4,510.4 33,163.9 3,791.0 1996 100.3 5,144.8 36,068.9 4,794.7
Sources: U.S. Department of Commer ce, Bureau of the Census. 1995b. 1992 Census of Manufactures . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990–1998. Annual Survey of Manufactures

. Washington, DC: Government Printing Office. Table 4-21. Capacity Utilization Ratios for th e Industrial Organic Chemicals Industry (SIC 2869/NAICS 3251), 1991–1996

1991 1992 1993 1994 1995 1996 SIC 2869/NAICS 3251 86 81 91 89 84 84 Note: The capacity utilization ratio is the ratio of the actual production level to the full production level. All values are percentages. Source: U.S. Department of Commer ce, Bureau of the Census. 1998. Survey of Plant Capacity: 1996. Washington, DC: Government Printing Office.
4.6.2 Demand Side of the Industry Industrial organic chemicals are components of many chemical products. Most of the chemical sectors (classified under SIC 28) are do wnstream users of organic chemicals. These sectors either purchase commodity chemicals or enter into contracts w ith industrial organic chemical producers to obtain specialty chemical s. Consumers include inorganic chemicals (SIC 281), plastics and synthetics (SIC 282), drugs (283), soaps and cleaners (SIC 284), paints and allied products (SIC 286), and misce llaneous chemical products (SIC 289).

4.6.3 Organization of the Industry Although the industry’s value of shipments increased nearly 12 percent between 1987 and 1992, the number of facilities producing industrial organic chemicals only increased by 64-26 percent. Facilities with 100 or more employees continued to account for the majority of the industry’s shipment values. For example, in 199 2, 28 percent of all faci lities had 100 or more employees (see Table 4-22), and these facilities produced 89 percent of the industry’s shipment values. The average number of facilities per firm was 1.4 in both years. According to the Small Business Administration, an industrial organic ch emicals company is considered small if the total number of employees does not exceed 500. It is unclear what percentage of facilities are owned by small businesses.

Table 4-22. Size of Establishments and Valu e of Shipments for the Industrial Organic Chemicals Industry (SIC 2869/NAICS 3251)

1987 1992 Number of Employees in Establishment Number of Facilities Value of Shipments (1992 $10 6 ) Number of Facilities Value of Shipments (1992 $10 6 ) 1 to 4 employees 97 552.8 100 102.6 5 to 9 employees 80 200.9 80 208.7 10 to 19 employees 91 484.7 97 533.9 20 to 49 employees 137 1,749.9 125 1,701.5 50 to 99 employees 99 2556.3 106 3,460.9 100 to 249 employees 110 10,361.2 111 8,855.9 250 to 499 employees 41 17,156.9 41 9,971.1 500 to 999 employees 27 9,615.5 30 13,755.0 1,000 to 2,499 employees 11 9,184.6 10 9,051.0 2,500 or more employees 6 7,156.9 5 6,613.5
Sources: U.S. Department of Commer ce, Bureau of the Census. 1995b. 1992 Census of Manufactures, Industry Series: Industrial Organic Chemicals . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990b. 1987 Census of Manufactures, Industry Series, Paints and Allied Products . Washington, DC: Government Printing Office.
The industrial organic chemicals (not elsewh ere classified) industr y is unconcentrated and competitive. The CR4 was 29 and the CR8 43; the industry’s HHI was 336.

4.6.4 Markets and Trends The U.S. industrial organic chemical industr y is expected to ex pand through 2002 at an annual rate of 1.4 percent (Haltmaier, 1998). U.S. producers face increasing competition domestically and abroad as ch emical industries in developing nations gain market share and increase exports to the United States. American producers will, however, benefit from decreasing costs for raw materials and en ergy and productivity gains.4-27 4.7 Electric Services (SIC 4911/NAICS 22111) The ongoing process of deregula tion of wholesale and retail el ectric markets is changing the structure of the electric power industry. De regulation is leading to the functional unbundling of generation, transmission, and distribution and to competition in the generation segment of the industry. This profile provides background informa tion on the U.S. electric power industry and discusses current industry characteristics and trends that will influence the future generation and consumption of electricity. It is important to note that through out th is report the te rms “boilers,” “process heaters,” and “units” are synonymous w ith “ICI boilers” and “process heaters.” Boilers primarily engaged in the generati on of electricity are not covere d by the NESHAP under analysis and are therefore excluded from this analysis. Utility sources are not affected by this NESHAP except for a small number of nonfo ssil fuel units within this industry. Those un its in this industry that are affected may be engaged in activiti es such as heating and mechanized work.

4.7.1 Electricity Production Figure 4-1 illustrates the typica l structure of the electric ut ility market. Even with the technological and regulatory changes in the 1970s and 1980s, at the beginning of the 1990s the structure of the electric utility industry could still be charac terized in terms of generation, transmission, and distribution. Co mmercial and retail customers we re in essence “captive,” and rates and service quality were primarily determined by public utility commissions.
The majority of utilities are interconnected and belong to a regional power pool. Pooling arrangements enable facilities to coordinate th e economic dispatch of ge neration facilities and manage transmission congestion. In addition, pooli ng diverse loads can increase load factors and decrease costs by sharing reserve capacity.

4.7.1.1 Generation As shown in Table 4-23, coal-fired plants ha ve historically accounted for the bulk of electricity generation in the United States. With abundant national coal reserves and advances in pollution abatement technology, suchas advanced scrubbers for pulverized coal and flue gasdesulfurization systems, coal will likely remain the fuel of choice for most existing generating facilities over the near term.
Natural gas accounts for approximately 10 perc ent of current generation capacity but is expected to grow; advances in natural gas explorati on and extraction techno logies and new coal gasification have contribute d to the use of natural gas for power generation.4-28 Large C/I Customers Small C/I Customers Residential Customers Transformer Generation Electricity

Distribution High Voltage LinesTransmission Power Plants

Figure 4-1. Traditional Electri c Power Industry Structure
Nuclear plants and renewable energy sources (e.g., hydroelectric, solar, wind) provide approximately 20 percent and 10 percent of curren t generating capacity, respectively. However, there are no plans for new nuclear fa cilities to be constructed, and there is little additional growth forecasted in renewable energy.

4.7.1.2 Transmission Transmission refers to high voltage lines used to link generators to substations where power is stepped down for local distribution. Tr ansmission systems have been traditionally characterized as a collection of independently op erated networks or grids interconnected by bulk transmission interfaces.4-29 Table 4-23. Net Generation by Energy Source, 1995

Energy Source Utility Generators (MWh) Nonutility Generators (MWh) Total (MWh) Fossil fuels 2,021,064 287,696 2,308,760 Coal 1,652,914 63,440 Natural gas 307,306 213,437 Petroleum 60,844 3,957 Nuclear 673,402 — 673,402 Hydroelectric 293,653 14,515 308,168 Renewable/other 6,409 98,295 104,704 Total 2,994,582 400,505 3,395,033
Sources: U.S. Department of Energy, Energy Information Administration. 1996. Electric Power Annual, 1995 . Vol. 1. DOE/EIA-0348(95/1). Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Information Administration. 1999b. The Changing Structure of the Electric Power Industry 1999: Mergers and Other Corporate Combinations . Washington, DC: U.S. Department of Energy.
Within a well-defined service territory, th e regulated utility ha s historically had responsibility for all aspects of developing, maintaining, and operating transmissions. These responsibilities included

 system planning and expanding,

 maintaining power quality and stability, and

 responding to failures. Isolated systems were connected primarily to in crease (and lower the cost of) power reliability. Most utilities maintained sufficient generating capacity to meet customer needs, and bulk transactions were initially used only to support extreme demands or equipment outages.

4.7.1.3 Distribution Low-voltage distribution systems that deliver el ectricity to customers comprise integrated networks of smaller wires and substations that ta ke the higher voltage a nd step it down to lower levels to match customers’ needs.
The distribution system is the classic exam ple of a natural monopoly because it is not practical to have more than one set of lines running through neighborhoods or from the curb to the house.4-30 4.7.2 Cost of Production Table 4-24 shows total industry expenditu res by production activ ities. Generation accounts for approximately 75.6 percent of the cost of delivered el ectric power in 1996. Transmission and distribution accounted for 2.5 pe rcent and 5.6 percent, re spectively. Customer accounts and sales and administrativ e costs accounted for the rema ining 16.3 percent of the cost of delivered power. Table 4-24. Total Expenditures in 1996 ($10 3 )

Utility Ownership Generation Transmission Distribution Customer Accounts and Sales Administration and General

Expenses Investor-owned 80,891,644 2,216,113 6,124,443 6,204,229 13,820,059 Publicly owned 12,495,324 840,931 1,017,646 486,195 1,360,111 Federal 3,685,719 327,443 1,435 55,536 443,809 Cooperatives 15,105,404 338,625 1,133,984 564,887 1,257,015 112,178,091 3,723,112 8,277,508 7,310,847 16,880,994
75.6% 2.5% 5.6% 4.9% 11.4% 148,370,552
Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1998b. Financial Statistics of Major Publicly Owned Electric Utilities, 1997 . Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Information Administration (EIA). 1997. Financial Statistics of Major U.S. Investor-Owned Electric Utilities, 1996 . Washington, DC: U.S. Department of Energy.
4.7.3 Organization of the Industry Because the restructuring plans and time tables are made at the state level, the issues of asset ownership and control thr oughout the current supply chain in the electric power industry vary from state to state. However, the act ivities conducted throughout the supply chain are generally the same. This section focuses on the ge neration segment of the market because all the boilers affected by the regulati on are involved in generation.
As part of deregulation, the transmission and distribution of el ectricity are being separated from the business of generating electricit y, and a new competitive market in electricity generation is evolving. As power generators pr epare for the competitive market, the share of electricity generation attributed to no nutilities and utilit ies is shifting.4-31 More than 7,000 electricity suppl iers currently oper ate in the U.S. market. As shown in Table 4-25, approximately 42 percen t of suppliers are utilities and 58 percent are nonutilities. Utilities include investor-owned, cooperatives, and municipal systems. Of the approximately 3,100 utilities operating in the United States, only about 700 generate electric power. The majority of utilities distribute electricity that they have purchased from power generators via their own distri bution systems. Table 4-25. Number of Electricity Suppliers in 1999

Electricity Suppliers Number Percent Utilities 3,124 42% Investor-owned utilities 222 Cooperatives 875 Municipal systems 1,885 Public power districts 73 State projects 55 Federal agencies 14 Nonutilities 4,247 58% Nonutilities (excluding EWGs) 4,103 Exempt wholesale generators 144 Total 7,371 100% Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999b. The Changing Structure of the Electric Power Industry 1999: Mergers and Other Corporate Combinations . Washington, DC: U.S. Department of Energy.
Utility and nonutility generators produced a total of 3,369 billion kWh in 1995. Although utilities generate the vast majority of elec tricity produced in the United States, nonutility generators are quickly eroding utilities’ shares of the market. Nonutility generators include private entities that generate power for their own use or to sell to utili ties or other end users. Between 1985 and 1995, nonutility generation increas ed from 98 billion kWh (3.8 percent of total generation) to 374 billion kWh (11.1 percent). Figure 4-2 illustrates this shift in the share of utility and nonutility generation.

4.7.3.1 Utilities There are four categories of utilities: investor-owned uti lities (IOUs), publicly owned utilities, cooperative utilities, and federal utilities. Of the four, only IOUs always generate electricity.4-32 a Includes facilities classified in more than one of the following FERC designated categories: cogenerator QF, small

power producer QF, or exempt wholesale generator. Cogen = Cogenerator. EWG = Exempt wholesale generator. Other Non-QF = Noncogenerator Non-QF. QF = Qualifying facility. SPP = Small power producer. Note: Sum of components may not equal total due to independent rounding. Classes for nonutility generation are determined by the class of each generating unit. Sources: Utility data: U.S. Department of Energy, Energy Information Administration ( EIA). 1996. Electric Power Annual 1995 . Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC: U.S. Department of Energy; Table 8 (and previous issues); 1985 nonutility data: Shares of generation estimated by EIA; total generation from Edison Electric Institute ( EEI). 1998. Statistical Yearbook of the Electric Utility Industry 1998 . November. Washington, DC; 1995 nonutility data: U.S. Department of Energy, Energy Information Administration ( EIA). 1996. Electric Power Annual 1995 . Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC: U.S. Department of Energy. Figure 4-2. Utility and Nonutility Genera tion and Shares by Class, 1988 and 19984-33 IOUs are increasingly selling off generation assets to nonutilities or converting those assets into nonutilities (Haltmaier, 1998). To prep are for the competitive market, IOUs have been lowering their operating costs, merging, a nd diversifying into nonutility businesses.
In 1995, utilities generated 89 percent of elect ricity, a decrease from 96 percent in 1985. IOUs generate the majority of the electricity produced in the United St ates. IOUs are either individual corporations or a holding company, in which a parent company operates one or more utilities integrated with one a nother. IOUs account for approxim ately three-quarters of utility generation, a percentage that he ld constant between 1985 and 1995.
Many states, municipalities, and other government organiza tions also own and operate utilities, although the ma jority do not generate electricity. Those that do generate electricity operate capacity to supply some or all of their cust omers’ needs. They tend to be small, localized outfits and can be found in 47 states. These publ icly owned utilities accounted for about onetenth of utility generation in 1985 and 1995. In a de regulated market, these generators may be in direct competition with other u tilities to service their market.
Rural electric cooperatives are formed and owned by groups of residents in rural areas to supply power to those areas. Cooperatives generally purchase from other u tilities the energy that they sell to customers, but some generate thei r own power. Cooperatives only produced 5 percent of utility generation in 1985 and only 6 percent in 1995.
Utilities owned by the federal government accoun ted for about one-tenth of generation in both 1985 and 1995. The federal government operate d a small number of large utilities in 1995 that supplied power to large i ndustrial consumers or federal in stallations. The Tennessee Valley Authority is an example of a federal utility.

4.7.3.2 Nonutilities Nonutilities are private en tities that generate power for thei r own use or to sell to utilities or other establishments. Nonutilities are usually operated at mines and manufacturing facilities, such as chemical plants and paper mills, or ar e operated by electric and gas service companies (DOE, EIA, 1998a). More than 4,200 nonu tilities operate in the United States.

4.7.4 Demand Side of the Industry

4.7.4.1 Electricity Consumption This section analyzes the growth projections for electricity consumption as well as the price elasticity of demand for el ectricity. Growth in electricity consumption has traditionally4-34 paralleled gross domestic product growth. Howeve r, improved energy efficiency of electrical equipment, such as high-efficiency motors, has slowed demand growth over the past few decades. The magnitude of the relationship has been decreasing over time, from growth of 7 percent per year in the 1960s dow n to 1 percent in the 1980s. As a result, determining what the future growth will be is difficult, although it is expected to be positive ( DOE, EIA, 1999a). Table 4-26 shows consumption by s ector of the economy over the pa st 10 years. The table shows that since 1989 electricity sales have increased at least 10 percent in all four sectors. The commercial sector has experien ced the largest incr ease, followed by residential consumption. Table 4-26. U.S. Electric Utility Retail Sales of Electricity by S ector, 1989 Through 1998 (10 6 kWh)

Period Residential Commercial Industrial Other a All Sectors 1989 905,525 725,861 925,659 89,765 2,646,809 1990 924,019 751,027 945,522 91,988 2,712,555 1991 955,417 765,664 946,583 94,339 2,762,003 1992 935,939 761,271 972,714 93,442 2,763,365 1993 994,781 794,573 977,164 94,944 2,861,462 1994 1,008,482 820,269 1,007,981 97,830 2,934,563 1995 1,042,501 862,685 1,012,693 95,407 3,013,287 1996 1,082,491 887,425 1,030,356 97,539 3,097,810 1997 1,075,767 928,440 1,032,653 102,901 3,139,761 1998 1,124,004 948,904 1,047,346 99,868 3,220,121 Percentage change 1989–1998 19% 24% 12% 10% 18%

a Includes public street and highway lighting, other sales to public authorities, sales to railroads and railways, and

interdepartmental sales. Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1999d. Electric Power Annual 1998 . Volumes I and II. Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Information Administration (EIA). 1996. Electric Power Annual 1995

. Volumes I and II. Washington, DC: U.S. Department of Energy.
In the future, residential demand is expected to be at the forefront of increased electricity consumption. Between 1997 and 2020, residential demand is expected to increase at 1.6 percent annually. Commercial growth in demand is expect ed to be approximately 1.4 percent, while industry is expected to increase demand by 1.1 pe rcent (DOE, EIA, 1999a). Figure 4-3 shows the annual electricity sales by sector from 1970 with projections through 2020.4-35 Figure 4-3. Annual Electrici ty Sales by Sector
The literature suggests that electricity consumption is relatively price inelastic. Consumers are generally unable or unwilling to forego a large amount of consumption as the price increases. Numerous studies have investigated the shor t-run elasticity of demand for electricity. Overall, the studies suggest that, for a 1 percent increase in the price of electricity, demand will decrease by 0.15 percen t. However, as Table 4-27 s hows, elasticitie s vary greatly, depending on the demand characteristics of end us ers and the price structure. Demand elasticities are estimated to range from a –0.05 percent elastici ty of demand for a “fla t rates” case (i.e., no time-of-use assumption) up to a –0.50 percent de mand elasticity for a “high consumer response” case (DOE, EIA, 1999c).

4.7.4.2 Trends in the Electricity Market Beginning in the latter part of the 19th centu ry and continuing for about 100 years, the prevailing view of policymakers and the public wa s that the government should use its power to require or prescribe the economic be havior of “natural monopolies” su ch as electric utilities. The traditional argument is that it does not make economic sense for there to be more than one supplier—running two sets of wire s from generating facilities to e nd users is more costly than one set. However, since monopoly supply is not gene rally regarded as likely to provide a socially optimal allocation of resources, regulation of rates and other ec onomic variables was seen as a necessary feature of the system.4-36 Table 4-27. Key Parameters in the Cases

Key Assumptions

Case Name Cost Reduction and Efficiency Improvements Short-Run Elasticity of Demand (Percent) Natural Gas Prices Capacity Additions
AEO97 Reference Case AEO97 Reference Case — AEO97 Reference Case As needed to meet demand No Competition No change from 1995 — AEO97 Reference Case As needed to meet demand
Flat Rates (no time-of-use rates) AEO97 Reference Case –0.05 AEO97 Reference Case As needed to meet demand
Moderate Consumer Response AEO97 Reference Case –0.15 AEO97 Reference Case As needed to meet demand High Consumer Response AEO97 Reference Case –0.50 AEO97 Reference Case As needed to meet demand High Efficiency Increased cost savings and efficiencies –0.15 AEO97 Reference Case As needed to meet demand

No Capacity Additions AEO97 Reference Case –0.15 AEO97 Low Oil and Gas Supply Technology Case Not allowed

High Gas Price AEO97 Reference Case –0.15 AEO97 High Oil and Gas Supply Technology Case As needed to meet demand

Low Gas Price AEO97 Reference Case –0.15 AEO97 Reference Case As needed to meet demand High Value of Reliability AEO97 Reference Case –0.15 AEO97 Reference Case As needed to meet demand
Half O&M AEO97 Reference Case –0.15 AEO97 Reference Case As needed to meet demand Intense Competition AEO97 Reference Case –0.15 AEO97 Reference Case As needed to meet demand
— = not applicable. Source: U.S. Department of Energy, Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. “Competitive Elect ricity Price Projections.” <http://www.eia.doe.gov/oiaf/elepri97/chap3.html>. As obtained on November 15, 1999c.4-37 Beginning in the 1970s, the public policy view shifted against traditional regulatory approaches and in favor of de regulation for many important i ndustries including transportation, communications, finance, and energy. The majo r drivers for deregulation of electric power included the following:

 existence of rate differentials across regions offering the promise of benefits from more efficient use of existing generation resources if the power can be transmitted across larger geographic areas than was typical in the era of industry regulation;

 the erosion of economies of scale in gene ration with advances in combustion turbine technology;

 complexity of providing a regulated industr y with the incentives to make socially efficient investment choices;

 difficulty of providing a res ponsive regulatory process that can quickly adjust rates and conditions of service in response to changing technological and market conditions; and

 complexity of monitoring utilities’ cost of service and establishing cost-based rates for various customer classes that promote economic efficiency while at the same time addressing equity concerns of regulatory commissions. Viewed from one perspective, not much changes in the electric industry with restructuring. The same functions are being perf ormed, essentially the same resources are being used, and in a broad sense the same reliability cr iteria are being met. In other ways, the very nature of restructuring, the harnessing of comp etitive forces to perform a previously regulated function, changes almost everything. Each pr ovider and each functi on become separate competitive entities that must be judged on their own.
This move to market-based provision of generation services is not matched on the transmission and distribution side. Network inte ractions on AC transmission systems have made it impossible to have separate transmission path s compete. Hence, transmission and distribution remain regulated. Transmission and generation heavily interact, however, and transmission congestion can prevent specific generation from getting to market. Transmission expansion planning becomes an open process with many interest ed parties. This open process, coupled with frequent public opposition to tr ansmission expansion, slows transmission enhancement. The net result is greatly increased pre ssure on the transmission system.
Restructuring of the electric power industry could result in any one of several possible market structures. In fact, different parts of the country will probably use different structures, as the current trend indicates. The eventual stru cture may be dominated by a power exchange, bilateral contracts, or a co mbination. A strong Regional Tran smission Organization (RTO) may4-38 operate in the area, or a vertically integrated util ity may continue to operate a control area. In any case, several important characteristics will change:

 Commercial provision of generation-base d services (e.g., ener gy, regulation, load following, voltage control, contingency reserves, backup supply) will replace regulated service provision. This drastically changes how the se rvice provider is assessed.

 Individual transactions will replace aggreg ated supply meeting aggregated demand. It will be necessary to continuously a ssess each individual’s performance.

 Transaction sizes will shrink. Instead of dealing only in hundreds and thousands of MW, it will be necessary to accommodate transactions of a few MW and less.

 Supply flexibility will greatly increase. Inst ead of services coming from a fixed fleet of generators, service provision will change dynamically among many potential suppliers as market conditions change.5-1 SECTION 5 ECONOMIC ANALYSIS METHODOLOGY

The final rule to control emissions of HAPs from industrial, commer cial, and institutional boilers and process heaters will affect almost all sectors of the U.S. economy. Several markets will bear the direct compliance costs. In additi on, sectors that consume energy will also bear indirect costs through higher prices for energy. Fi nally, consumers of goods and services will experience impacts from higher market prices.
This section presents the methodology for analyzing the economic impacts of the NESHAP. This economic analysis provides th e economic data and supporting information needed by EPA to support its regulatory de termination. The methodology is based on microeconomic theory and the methods develope d for earlier EPA studies. These methods are tailored to and extended for this analysis, as ap propriate, to meet EPA’s requirements for an EIA of controls placed on boilers and process heaters.
This methodology section includes bac kground information on typical economic modeling approaches, the conceptual approach se lected for this EIA, and an overview of the computerized market model used in the anal ysis with emphasis on th e links between energy markets and the markets for goods and services . Appendix A includes a description of the model’s baseline data set and specification.

5.1 Background on Economic Modeling Approaches In general, the EIA methodology needs to al low EPA to consider the effects of the different regulatory alternatives. Several type s of economic impact modeling approaches have been developed to support regula tory development. These approach es can be viewed as varying along two modeling dimensions:

 the scope of economic decisionmaking accounted for in the model and

 the scope of interaction between di fferent segments of the economy.
Each of these dimensions was considered in determining the approach for this study. The advantages and disadvantages of different modeling approaches are discussed below.

5.1.1 Modeling Dimension 1: Scope of Economic Decisionmaking Models incorporating different levels of economic decisionmaking can generally be categorized as with behavior responses and without behavior responses (accounting approach). Table 5-1 provides a brief comparison of the two approaches. The nonbehavioral approach5-2 Table 5-1. Comparison of Modeling Approaches

EIA With Behavioral Responses

• Incorporates control costs into production function • Includes change in quantity produced • Includes change in market price • Estimates impacts for T affected producers T unaffected producers T consumers T foreign trade EIA Without Behavioral Responses

• Assumes firm absorbs all control costs • Typically uses discounted cash flow analysis to evaluate burden of control costs • Includes depreciation schedules and corporate tax implications
• Does not adjust for changes in market price
• Does not adjust for changes in plant production

essentially holds fixed all interactions between fa cility production and mark et forces. It assumes that firms absorb all control costs and consum ers do not face any of the costs of regulation. Typically, engineering control co sts are weighted by the number of affected units to develop “engineering” estimates of the to tal annualized costs. These costs are then compared to company or industry sales to determ ine the regulation’s impact.
In contrast, the behavioral approach is grounded in economic theory related to producer and consumer behavior in response to changes in market conditions. Owners of affected facilities are economic agents that can, and presumably will, make adjustments such as changing production rates or altering input mixes that will generally affect the market environment in which they operate. As producers change their be havior in response to regulation, consumers are typically faced with changes in prices that cause them to alter the quantity that they are willing to purchase. In essence, this approach models the expected reallocation of society’s resources in response to a regulation. The ch anges in price and production fr om the market-level impacts are used to estimate the distribution of soci al costs between consumers and producers.5-3 5.1.2 Modeling Dimension 2: Interact ion Between Economic Sectors Because of the large number of markets poten tially affected by the regulation on boilers and process heaters, an issue aris es concerning the level of sectoral interaction to model. In the broadest sense, all markets are directly or indirectly linked in the economy; thus, the regulation affects all commodities and markets to some extent. For example, controls on boilers and process heaters may indirectly affect almost all market s for goods and services to some extent because the cost of fuel (an input in the provision of mo st goods and services) is likely to increase with the regulation in effect. However, the impact of rising fuel prices will differ greatly between different markets depending on how important fuel is as an input in that market.
The appropriate level of market interactions to be included in the EIA is determined by the scope of the regulation across industries a nd the ability of affected firms to pass along the regulatory costs in the form of higher prices. Al ternative approaches for modeling interactions between economic sectors can genera lly be divided into three groups:

 Partial equilibrium model: Individual ma rkets are modeled in isolation. The only factor affecting the market is the cost of the regulation on faci lities in the industry being modeled.

 General equilibrium model: All sectors of the economy are modeled together. General equilibrium models operationalize neoclass ical microeconomic theory by modeling not only the direct effects of control costs, but also potenti al input subst itution effects, changes in production levels associated w ith changes in market prices across all sectors, and the associated changes in welfare economywide. A disadvantage of general equilibrium modeling is that substa ntial time and resources are required to develop a new model or tailor an existing m odel for analyzing regulatory alternatives.

 Multiple-market partial equilibrium model: A subset of related markets are modeled together, with intersectoral linkages e xplicitly specified. To account for the relationships and links between different markets without employing a full general equilibrium model, analysts can use an in tegrated partial equilibrium model. The multiple-market partial equilibrium approach represents an intermediate step between a simple, single-market partial equilibrium approach and a full general equilibrium approach. This approach involves identif ying and modeling the most significant subset of market interactions using an in tegrated partial equilibrium framework. In effect, the modeling technique is to link a series of st andard partial equilibrium models by specifying the interactions betw een supply functions and then solving for prices and quantities across all markets si multaneously. In instances where separate markets are closely related and there are st rong interconnections, there are significant advantages to estimating market adjustme nts in different markets simultaneously using an integrated market modeling approach.5-4 5.2 Selected Modeling Approach for Boil ers and Process Heaters Analysis To conduct the analysis for the boilers and process heaters MACT, the Agency used a market modeling approach that incorporates behavioral responses in a multiple-market partial equilibrium model as described above. This appr oach allows for a more realistic assessment of the distribution of impacts across different groups than the nonbehavioral approach, which may be especially important in accurately assessi ng the impacts of a significant rule affecting numerous industries. Because of the size and complexity of this regulation, it is important to use a behavioral model to examine the distribution of costs across society. Because the regulations on boilers and process heaters pr imarily affect energy costs, an input into many production processes, complex market interactions need to be captured to provide an accurate picture of the distribution of regulatory costs. Because of the large number of affected industries under this MACT, an appropriate model should include mu ltiple markets and the interactions between them. Multiple-market partial equilibrium an alysis provides a manageable approach to incorporate interactions between energy market s and final product markets into the EIA to accurately estimate the regulation’s impact.
The model used for this analysis include s energy, agriculture, manufacturing, mining, commercial, and transportation markets affected by the controls placed on boilers and process heaters. 6 The energy markets are divided into natural gas, petroleum products, coal, and electricity. The residential sector is treated as a single representative demander in the energy markets.
Figure 5-1 presents an overview of the ke y market linkages included in the economic impact model used for analyzing the boilers a nd process heaters MACT. The analysis’ emphasis is on the energy supply chain and the consumpti on of energy by producers of goods and services. The industries most directly affected by the boile rs and process heaters MACT are the electric power industry, chemical industry and pulp a nd paper industry. However, changes in the equilibrium prices and quantitie s of energy and goods and services affect all sectors of the economy. (See Figure 5-1.) This analysis explicitl y models the linkages between these market segments to capture both the direct costs of comp liance and the indirect co sts due to changes in prices. For example, production costs will increase for chemical companies using boilers and process heaters as a result of the capital investments and mon itoring costs, as well as the resulting increase in the price of electricity used as an energy input in the production process.

6 These markets are defined at the two- and three-digit NAI CS code level. This allows for a fairly disaggregated examination of the regulation’s impact on producers. Howeve r, if the costs of the regul ation are concentrated on a particular subset of one of these ma rkets, then treating the cost as if it fell on the entire NAICS code may still underestimate the impacts on the subset of producers affected by the regulation.5-5ΣdemandoilOilSupplyExogenousDemandEndogenousΣdemandNGGasΣdemandcoalCoalIndustry ABtuProductionManufacturingProcessIndustry BRegulatoryCostsEnergy ConsumptionFuel MarketsΣsupplyproduct AProduct ASupplyEndogenousDemandExogenousIntermediate orFinal Product MarketsIndustry ZResidential HouseholdsCommercial BusinessesΣdemandelecElectricityElectricity MarketSupplyExogenousDemandEndogenous•••

Figure 5-1. Links Between Energy and Goods and Services Markets5-6 The economic model also captures behavioral changes of producers of goods and services that feedback into the energy markets. Changes in production levels and fuel switching in the manufacturing process affect the demand for Btus in fuel market s. The change in output is determined by the size of the cost increase per Btu (typically variable cost per output), the facility’s production function (sl ope of supply curve), and the demand characteristics of the facility’s downstream market (other market s uppliers and market demanders). For example, if consumers’ demand for a product is not very se nsitive to price, then producers can pass the majority of the cost of th e regulation through to consumer s and output may not change appreciably. However, if only a small proporti on of market output is produced by producers affected by the regulation, then competition will pr event the affected producers from raising their prices significantly.
One possible feedback pathwa y that this analysis does not model is technical changes in the manufacturing process. For example, if the cost of Btus increases, a facility may use measures to increase manufacturing efficiency or capture waste heat. Facilities could also possibly change the input mix that they use, substituting other input s for fuel. These facility-level responses will also act to reduce pollution, but including these responses is beyond the scope of this analysis.

5.2.1 Directly Affected Markets Markets where boilers and process heaters are used as an input to production are considered to be directly affected. As outlined in Section 2, facilities using several types of boilers or process heaters will be required to add controls. In addition, a larger population of boilers and process heaters will in cur monitoring costs to comply with the regulation. Therefore, the regulation will increase their production cost s and cause these directly affected firms to reduce the quantity that they are wi lling to supply at any given price.

5.2.1.1 Electricity Market Boilers are used to generate power throughout the electric power industry. Even though utility boilers are not covered under this regulation, the Agency estimates over 300 industrial, commercial, and institutiona l boilers involved in pr oviding electric services (SIC 4911/NAICS22111) will be affected. Most of these are owned by munici pal electric service providers.
For this study, the electricity market was m odeled as a nationally competitive market. The direct costs of compliance on affected boilers lead to an upward shift in the total market supply for electricity. Figure 5-2 illustrates the sh ifts in the supply curv e for a representative5-7 P 1

P 0

Q 11 Q 10
(a) Producers bearing control costs (affected) S 11

S 10 $

Quantity $ $

Quantity Q 20 Q 21
(b) Producers bearing no control costs (unaffected) S 20

Quantity

(c) Total Market Q T1 Q T0 D S T0 S T1

P 0 = market price without regulation P 1 = market price with regulation S 10 = supply function for affect ed firms without regulation S 11 = supply function for affect ed firms with regulation Q 10 = quantity sold for affect ed firms without regulation Q 11 = quantity sold for affected firms with regulation S 20 = supply function for unaffected firm s both with and without regulation Q 20 = quantity sold for unaffect ed firms without regulation Q 21 = quantity sold for unaffected firms with regulation S T0 = total market supply function without regulation S T1 = total market supply function with regulation Q T0 = total market quantity sold without regulation Q T1 = total market quantity sold with regulation Figure 5-2. Market Effects of Regulation-Induced Costs
energy market. In addition to the direct costs, th e market for electricity w ill also be indirectly affected through changes in fuel prices. Electric ity generators are extremely large consumers of coal, natural gas, and petroleum products. For exam ple, some of the impact of control costs on the petroleum industry will be on th e electricity industry in the fo rm of higher prices. Indirect costs will also lead to an upward shift in the supply curve.
The demand for electricity is derived by aggregating across th e goods and services markets and the residential sector. Because of direct compliance costs on the goods and services markets, the demand curve for electricity wi ll shift downward. Therefore, it is ambiguous whether equilibrium quantity will rise or fall. The changes in the price and quantity are determined by the relative magnitude of the shif ts in the price elastic ities of the supply and demand curves.

5.2.1.2 Petroleum Market Control costs associated with boilers and proce ss heaters will increase the cost of refining petroleum products. The supply curve for petroleum products will shift upward by the proportional increase in total pr oduction costs caused by the contro l costs on boilers and process5-8 heaters. For petroleum products, a single co mposite product was used to model market adjustment because boilers and process heaters ar e used throughout the refinement process, from distillation to reformulation. As a result, assigning costs to specifi c end products, such as fuel oil #2 or reformulated gasoline, is difficult. The us e of a composite product tends to understate the impacts for petroleum products where compliance costs as a percentage of production costs are greater than average and overstate impacts for products where co mpliance costs as a percentage of production costs are less than average.

5.2.1.3 Goods and Services Markets: Agricultu re, Manufacturing, Mining, Commercial, and Transportation Many manufacturing facilities use boilers and process he aters in their production processes to generate steam and process heat. Commercial entities use boilers for space heating and to generate supplementary el ectricity. In addition to the dir ect costs of the regulation, goods and services markets are indirectly affected through price increases in the energy markets.
Directly affected producers are segmented into sectors defined at th e two- or three-digit NAICS code level. A partial equilibrium analys is was conducted for each sector to model the supply and demand. Changes in production levels and fuel switching due to the regulation’s impact on the price of Btus were then linked back into the energy markets.
The impact of the regulation on producers in these sectors was modeled as an increase in the cost of Btus used in the production process. In this context, Btus refer to the generic energy requirements used to generate process heat, pr ocess steam, or shaft power. Compliance costs associated with the regulation will increase the cost of Btu production in the manufacturing sectors. The cost of Btu producti on for industry increases because of both direct control costs on boilers and process heaters owned by manufacturers, and increases in the price of fuels. Because Btus are an input into the producti on process, these price increases lead to an upward shift in the facility (and industry) supply curves as show n in Figure 5-2, leading to a change in the equilibrium market price and quantity.
The changes in equilibrium supply and demand in each market are modeled to estimate the regulation’s impact on each sector. In a perfectly competitive market, the point where supply equals demand determines the market price a nd quantity, so market price and quantity are determined by solving the model for the price where the quantity supplied and the quantity demanded are equal. The size of th e regulation-induced shifts in th e supply curve is a function of the total direct control costs associated with boilers and process heaters and the indirect fuel costs (determined by the change in fuel price an d intensity of use) in each goods and services5-9 market. The proportional shift in th e supply curve is determined by th e ratio of total control costs (both direct and indir ect) to total revenue.
This impact on the price of Btus facing industr ial users feeds back to the fuel market in two ways (see Figure 5-3). The first is thr ough the company’s input decision concerning the fuel(s) that will be used for its manufacturing pro cess. As the cost of Btus increases, firms may switch fuels and/or change produc tion processes to increase energy efficiency and reduce the number of Btus required per unit of output. Fuel switching imp acts were modeled using crossprice elasticities of demand betw een energy sources. For example, a cross-price elasticity of demand between natural gas and electricity of 0.5 imp lies that a 1 percent incr ease in the price of electricity will lead to a 0.5 per cent increase in the demand for na tural gas. Own-price elasticities of demand are used to estimate the change in the use of fuel by demanders. For example, a demand elasticity of –0.175 for electri city implies that a 1 percen t increase in the price of electricity will lead to a 0.175 percent decrease in the quant ity of electricity demanded.

Btu Production

Decision Output Market

Δ Fuel Use

Δ Output Δ

$/Btu Production Decision $/Btu Δ $/Btu

Fuel Markets Compliance Costs

Figure 5-3. Fuel Market Interactions with Facility-Level Production Decisions
The second feedback pathway to the energy mark ets is through the f acility’s change in output. Because Btus are an input into the producti on process, energy price increases lead to an upward shift in the facility supply curves (not modeled individually). Th is leads to an upward shift in the industry supply curv e when the shifts at the facil ity level are aggregated across facilities. A shift in the industry supply curve leads to a change in the equilibrium market price and quantity. In a perfectly competitive ma rket, the point where supply equals demand determines the new market price and quantity. Th e Agency modeled the feedback into the energy market by assuming that the percentage change in output in the manufactur ing sectors translates into a equivalent percentage change in the demand for energy (Btus). This implies that there are5-10 constant returns to scale from energy inputs in the manufacturing process over the relevant range of output and time period of analysis. This is an appropriate assumption fo r this analysis because the output changes in these sectors being modeled are relatively small (always less than 1 percent) and reflect shor t-run production decisions. 7
The Agency assumed that the demand curves for goods and services in all sectors are unchanged by the regulation. However, because the demand function quantifies the change in quantity demanded in response to a change in price, the baseline demand conditions are important in determining the regulation’s impact . The key demand paramete rs are the elasticities of demand with respect to changes in the pri ce of goods and services. For these markets, a “reasonable” range of elasticity values is assigned based on estimates from similar commodities. Because price changes are anticipated to be small, the point elasticities at the original price and quantity should be applicable th roughout the relevant ra nge of prices and qua ntities examined in this model.

5.2.2 Indirectly Affected Markets In addition to the many markets that are dire ctly affected by the re gulation on boilers and process heaters, some markets feel the regul ation’s impacts despite having no direct costs resulting from the regulation. Firms in these ma rkets generally face changes in the price of energy that affect th eir production decisions.

5.2.2.1 Market for Coal The coal market is not directly affected by the regulation, but it has the potential to be significantly affected through indirect costs. Although boilers and pr ocess heaters are not commonly used in the production or transportation of coal, the supply of coal will be affected by the price of energy used in coal production. Ho wever, the indirect impacts on coal production costs are relatively small compared to the direct impacts on the production co sts in the electricity and petroleum markets; thus, the “relative” price of coal (per Btu) will decrease compared with other energy sources.

The demand for coal from the industrial se ctors will be affected by differences in compliance costs by fuel type applied to boilers and process heaters in the industrial sectors. Because compliance costs are hi gh for coal-fired units, manufact urers will switch away from coal units toward natural gas units with lower compliance costs. However, the overall impact on the demand for coal is ambiguous because the relati ve increase in the cost of producing Btus by

7 Long-run production decisions of fuel switching and increas ed energy efficiency are ca ptured by the cross- and own-price elasticities in the energy markets.5-11 burning coal will be offset by the relative decrease in the price of coal. Similarly, the demand for coal by utility generators will be affected through changes in the relative price of alternative (noncoal) energy sources and di rect costs on coal boilers.

5.2.2.2 Natural Gas Market The natural gas market is incl uded in the economic model to complete coverage of the energy markets. EPA projects that there are no direct and minimal indirect impacts on the production costs of natural gas. However, the dema nd for natural gas will increase because of the relative decrease in the price of natural gas and the lower relative compliance costs for gas-fired boilers and process heaters.

5.2.2.3 Goods and Services Markets Some goods and services markets do not include any boilers or pro cess heaters and are therefore not directly affected by the regulation. However, these markets will still be affected indirectly because of the change s in energy prices that they will face following the regulation. There will be a tendency for these users to shif t away from electricity and petroleum products and towards natural gas and coal.

5.2.2.4 Impact on Residential Sector The residential sector does not bear any di rect costs associated with the regulation because this sector does not own boilers or pro cess heaters. However, they bear indirect costs due to price increases. The residential sector is a significant consumer of electricity, natural gas, and petroleum products used for heating, cooling, and lighting, as well as many other end uses. The change in the quantity of energy demanded by these consumers in response to changes in energy prices is modeled as a single demand curve parameterized by demand elasticities for residential consumers obtain ed from the literature.

5.3 Operationalizing the Economic Impact Model Figure 5-4 illustrates the li nkages used to operationalize the estimation of economic impacts associated with the compliance costs. Compliance costs placed on boilers and process heaters shift the supply curve for electricity and petroleum products. Adjustments in the electricity and petroleum energy ma rkets determine the share of the cost increases that producers (electric service providers a nd petroleum companies) and co nsumers (product manufacturers, commercial business, and re sidential households) bear.5-12ΣdemandelecElectricityElectricity MarketΣdemandoilOilAssumeSupplyModelDemandΣdemandNGGasΣdemandcoalCoalIndustry ABtuProductionManufacturingProcessIndustry ZIndustry BRegulatory Costs( ΔFuel Prices)⇒PΔQQEnergy Consumption Final Product MarketsFuel MarketsFuel PricesFuel PricesFuel PricesFuel Prices ΔProduction Process(Fuel Switching) ΔProduction LevelsProduct SupplyProduct PriceP = market price of finaloutputQ = quantity sold of finaloutput•••Residential HouseholdsCommercial BusinessesFuel Prices

Regulatory Costs Figure 5-4. Operationalizing the Es timation of Economic Impact5-13 The supply and demand relationships between the energy markets are fully modeled. For example, changes in electricity production feed back and affect the demand for coal, natural gas and petroleum products. Similar ch anges in refinery production a ffect the petroleum industry’s demand for electricity.
Manufacturers experience supply curve shifts due to control costs on affected boilers and process heaters they operate and changes in prices for natural ga s, petroleum, electricity, and coal. The share of these costs borne by produ cers and consumers is determined by the new equilibrium price and quantity in the goods and services markets. Changes in manufacturers’ Btu demands due to fuel switching and changes in production levels feed back into the energy markets.
Adjustments in price and quantity in all markets occur simultaneously. A computer model was used to numerically simulate market adjustments by iterating over commodity prices until equilibrium is reached (i.e., until the quantit y supplied equals the quantity demanded in all markets being modeled). Using the results pr ovided by the model, economic impacts of the regulation (changes in consumer and producer surplus) were estim ated for all sectors of the economy being modeled.

5.3.1 Computer Model The computer model comprises a series of computer spreadsheet modules. The modules integrate the engineering cost inputs and the mark et-level adjustment parameters to estimate the regulation’s impact on the price and quantity in e ach market being analyzed. At the heart of the model is a market-clearing algorithm that compares the total quantity supplied to the total quantity demanded for each market commodity.
Current prices and production le vels are used to calibrate th e baseline scenario (without regulation) for the model. Then, the complian ce costs associated with the regulation are introduced as a “shock” to the system, and the supply and demand for market commodities are allowed to adjust to account for the increased production costs resulting from the regulation. Using an iterative process, if the supply does not equal demand in all markets, a new set of prices is “called out” and sent back to producers and consumers to “ask” what quantities they would supply and demand based on these new prices. This technique is referred to as an auctioneer approach because new prices are continually called out until an equilibrium set of prices is determined (i.e., where supply equals demand for all markets).5-14 Supply and demand quantities are computed at each price iteration. The market supply for each market is obtained by using a mathemati cal specification of th e supply function, and the key parameter is the point elasticity of supply at the baseline condition. Ta ble 5-2 lists the supply elasticities for the markets used in the model. Table 5-2. Supply and De mand Elasticities

Demand Elasticities Supply Elasticities Industrial Residential a Transportation Commercial Petroleum 0.58b Derived –0.28 Derived Derived Natural Gas 0.41 b Derived –0.26 Derived Derived Electricity 0.75 c Derived –0.23 Derived Derived Coal 1.00 b Derived –0.26 Derived Derived NAICS Description Supply d Demand d

311 Food 0.75 c –0.30 312 Beverage and Tobacco Products 0.75 c –1.30 313 Textile Mills 0.37 e –0.85 e 314 Textile Product Mills 0.37 e –0.85 e 315 Apparel 0.75 c –1.80 316 Leather and Allied Products 0.75 c –1.20 321 Wood Products 0.75 d –0.20 322 Paper 1.20 c –1.09 323 Printing and Related Support 0.75 c –1.80 325 Chemicals 0.75 c –1.50 326 Plastics and Rubber Products 0.75 c –1.80 327 Nonmetallic Mineral Products 0.75 c –0.90 331 Primary Metals 3.50 f –0.80 332 Fabricated Metal Products 0.75 c –0.20 333 Machinery 0.75 c –0.50 334 Computer and Electronic Products 0.75 c –0.30 335 Electrical Equipment, Appliances, and Components 0.75 c –0.50 336 Transportation Equipment 0.75 c –1.00 c 337 Furniture and Related Products 0.75 c –3.40 339 Miscellaneous 0.75 c –0.60 11 Agricultural Sector 0.75 c –1.80 23 Construction Sector 0.75 c –1.00 c (continued)5-15 Table 5-2. Supply and Demand El asticities (continued)

NAICS Description Supply d Demand d

21 Other Mining Sector 0.43 –0.30 48 Transportation 0.75 c –0.70 Commercial Commercial 0.75 c –1.00 c

a U.S. Department of Energy, Energy Information Administration (EIA). “Issues in Midterm Analysis and

Forecasting 1999—Table 1.” <http ://www.eia.doe.gov/oaif/issues/pricetbl1.ht ml>. As obtained on May 8, 2000a.
b Dahl, Carol A., and Thomas E. Duggan. 1996. “U.S . Energy Product Supply Elasticities: A Survey and

Application to the U.S. Oil Market.” Resource and Energy Economics 18:243-263.

c Assumed value.
d E.H. Pechan & Associates, Inc. 1997. Qualitative Market Impact Analysis for Implementation of the Selected Ozone and PM NAAQS. Appendix B. Prepared for the U.S. Environmental Protection Agency.

e Warfield, et al. 2001. “Multifiber Arrangement Phaseou t: Implications for the U.S. Fibers/Textiles/Fabricated

Products Complex.” www.fibronet.com.tw/mirron/ncs/9312/mar.html> As obtained September 19, 2001.
f U.S. International Trade Commission (USITC). November 21, 2001. Memorandum to the Commission from

Craig Thomsen, John Giamalua, John Benedetto, Joshua Levy, International Economists. Investigation No. TA201-73: STEEL-Remedy Memorandum.
The demand curves for the energy markets are the sum of demand responses across all markets. The demand for energy in the manufact uring sectors is a derived demand calculated using baseline energy usage and changes associat ed with fuel switching and changes in output levels. Similarly, the energy demand in resident ial sectors is obtained through mathematical specification of a demand function (see Appendix A).
The demand for goods and service in the two- and three-digit NAICS code manufacturing sectors is obtained by using a mathematical spec ification of the demand function. Table 5-2 lists the demand elasticities for the markets used in the model.
EPA modeled fuel switching using secondary da ta developed by the U.S. Department of Energy for the National Energy Modeling System (NEMS). Table 5-3 contains fuel price elasticities of demand for electr icity, natural gas, petroleum products, and coal. The diagonal elements in the table represent own-price elasticit ies. For example, the table indicates that for steam coal, a 1 percent change in the price of co al will lead to a 0.499 percent decrease in the use of coal. The off diagonal elements are cross-pr ice elasticities and indicate fuel switching propensities. For example, for st eam coal, the second column indica tes that a 1 percent increase in the price of coal will l ead to a 0.061 percent increase in the use of natural gas.5-16 Table 5-3. Fuel Price Elasticities

Own and Cross Elasticities Inputs Electricity Natural Gas Coal Residual Distillate Electricity –0.074 0.092 0.605 0.080 0.017 Natural Gas 0.496 –0.229 1.087 0.346 0.014 Steam Coal 0.021 0.061 –0.499 0.151 0.023 Residual 0.236 0.036 0.650 –0.587 0.012 Distillate 0.247 0.002 0.578 0.044 –0.055 Source: U.S. Department of Energy, Energy Information Administration (EIA). January 2000b. Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System

. DOE/EIA-M064(2000). Washington, DC: U.S. Department of Energy.
5.3.2 Calculating Changes in Social Welfare The boilers and process heaters MACT will im pact almost every sector of the economy, either directly through control cost s or indirectly through changes in the price of energy and final products. For example, a share of control costs that originate in the energy markets is passed through the goods and services markets and borne by both the producers and consumers of their products. To estimate the total change in soci al welfare without double-counting impacts across the linked partial equilibrium markets being mode led, EPA quantified social welfare changes for the following categories:

 change in producer surplus in the energy markets;

 change in producer surplus in th e goods and services markets;

 change in consumer surplus in th e goods and services markets; and

 change in consumer surplus in the residential sector. Figure 5-5 illustrates the change in producer a nd consumer surplus in the intermediate energy market and the goods and services markets. For example, assume a simple world with only one energy market, wholesale electricity, and one pr oduct market, pulp and pa per. If the regulation increases the cost of generating w holesale electricity, then part of the cost of the regulation will be borne by the electricity producer s as decreased producer surplus, and part of the costs will be passed on to the pulp and paper manufacturer s. In Figure 5-5(a), the pulp and paper manufacturers are the consumers of electricity, so the change in consumer surplus is displayed. This change in consumer surplus in the en ergy market is captured by the product market (because the consumer is the pulp and paper indust ry in this case), where it is split between consumer surplus and producer surplus in those markets. Figure 5-5(b) shows the change in producer surplus in the energy market, where B repr esents an increase in producer surplus and C represents a decrease.5-17 S

D S ′

D (a) Change in Consumer Surplus in the Energy Market

(c) Change in Consumer Surplus in Final Product Markets (b) Change in Producer Surplus in the Energy Market

(d) Change in Producer Surplus in Final Product Markets P

P 2

Q P 1

Q 2 Q 1 S

D S ′

P

P B

Q P A

Q B Q A S

D S ′ P

P B

Q P A

Q B Q A P

P 2

Q P 1

Q 2 Q 1 S

D S ′

A B

C

E

F

Figure 5-5. Changes in Economic Welfare with Regulation
As shown in Figures 5-5(c) and 5-5(d), the cost affects the pulp and paper industry by shifting up the supply curve in the pulp and pa per market. These highe r electricity prices therefore lead to costs in the pulp and paper i ndustry that are distribut ed between producers and consumers of paper products in the form of lo wer producer surplus and lower consumer surplus. Note that the change in consumer surplus in th e intermediate energy market must equal the total change in consumer and producer surplus in the product market. Thus, to avoid double-counting, the change in consumer surplus in the intermedia te energy market was not quantified; instead the total change in social welfare was calculated as

Change in Social Welfare = 3 Δ PSE + 3 Δ PSF + 3 Δ CSF + 3 Δ CSR (5.1)5-18 where

Δ PSE = change in producer surplus in the energy markets; Δ PSF = change in producer surplus in the goods and services markets; Δ CSF = change in consumer surplus in the goods and services markets; and Δ CSR = change in consumer surplus in the commercial, residential, and transportation energy markets. Appendix A contains the mathemati cal algorithms used to calculat e the change in producer and consumer surplus in the appropriate markets. Th e market analysis is conducted for the year 2005 and incorporates both growth in supply and demand. As a result, both new and existing sources are evaluated using the same analysis approach.
The engineering control costs presented in Se ction 3.3 are inputs (regulatory “shocks”) in the market model approach. The magnitude and distribution of the regul atory costs’ impact on the economy depend on the relative size of the impact on individual markets (r elative shift of the market supply curves) and the behavioral respon ses of producers and consumers in each market (measured by the price elasticities of supply and demand).6-1 SECTION 6 ECONOMIC IMPACT ANALYSIS RESULTS
The underlying objective of the EIA is to eval uate the effect of the regulation on the welfare of affected stakeholders and society in general. Altho ugh the engineering cost analysis presented in Section 3 does represent an estimate of the resources requir ed to comply with the rule under baseline economic conditions, the anal ysis does not account for the fact that the regulations may cause the economic conditions to change. For instance, producers may reduce production in the face of higher production costs, thereby reducing market supply. Moreover, the control costs may be passed along to other parties through various economic exchanges. Therefore, EPA developed an analytical stru cture and economic model to measure and track these effects (described in detail in Secti on 5 and Appendix A). In this section, we report quantitative estimates of these welfare impacts and their dist ribution across stakeholders.
Note that EPA requested RTI to update model unit costs, which had the effect of lowering the economic impacts pres ented in this section. The revi sed scenario is presented in Appendix D of this report.

6.1 Social Cost Estimates Under the final rule, EPA estimates the tota l change in social welfare is $862.9 million (see Table 6-1). This estimate is slightly smaller (less than $0.3 million) than the estimated baseline engineering costs as a result of beha vior changes by producers and consumers. Possible behavior responses include cha nges in consumption and produc tion patterns and fuel switching. Table 6-1. Social Cost Estimates ($1998 10 6 ): Final Rule

Change in Social Welfare

Baseline engineering costs $863.0 Social costs with mark et adjustments $862.9 Difference between engineerin g and social costs $0.1

EPA also estimated the distribution of soci al costs between producers and consumers and report the distribution of impacts across sector s/markets in Table 6-2. The market analysis estimates that consumers will bear $414.3 million, or 48 percent of the total social cost as a result of higher prices and lower consumption levels. Producer surplus is projected to decrease by $448.7 million, or 52 percent of the total social cost as result of direct control costs, higher energy costs, and reductions in output.6-2 Table 6-2. Distribution of Social Costs by Sector/Market: Final Rule ($1998 10 6 )

Change in:

Sectors/Markets Producer Surplus Consumer Surplus Social Welfare Energy Markets Petroleum –$1.9 Natural gas $4.1 Electricity –$33.7 Coal –$2.7 Subtotal –$34.2 NAICS Code SIC Code Description 311 20 (pt) Food –$28.2 –$11.3 –$39.4 312 20 (pt); 21 Beverage and Tob acco Products –$ 2.4 –$4. 1 –$6.5 313 22 (pt) Textile Mills –$22.7 –$52.0 –$74.7 314 22 (pt) Textile Product Mills –$0.1 –$0.1 –$0.2 315 23 Apparel –$0.4 –$1.1 –$1.5 316 31 Leather and Allied Products –$0.3 –$0.4 –$0.7 321 24 Wood Products –$39.1 –$10.4 –$49.5 322 26 Paper –$66.1 –$60.0 –$126.1 323 27 Printing and Related Support –$0.2 –$0.4 –$0.6 325 28 Chemicals –$40.9 –$81.8 –$122.8 326 30 Plastics and Rubber Products –$2.2 –$5.4 –$7.6 327 32 Nonmetallic Mineral Products –$3.4 –$4.0 –$7.4 331 33 Primary Metals –$25.2 –$5.7 –$30.9 332 34 Fabricated Metal Products –$8.5 –$2.3 –$10.8 333 35 Machinery –$7.3 –$4.9 –$12.2 334 36 (pt) Computer and Electronic Products –$3.6 –$1.4 –$5.0 335 36 (pt) Electrical Equipment, Appliances, and Components –$2.5 –$1.6 –$4.1
336 37 Transportation Equipment –$24.6 –$32.8 –$57.3 337 25 Furniture and Related Products –$5.4 –$24.6 –$30.1 339 39 Miscellaneous –$0.8 –$0.7 –$1.5 11 01-08 Agricultural Sector –$0.6 –$1.3 –$1.9 23 15-17 Construction Sector –$0.8 –$1.1 –$1.9 21 10; 14 Other Mining Sector –$10.1 –$7.0 –$17.2 48 40-47 (pt) Transportation –$4.7 –$4.3 –$9.0 42; 44-45; 49; 51-56;

61-62; 71-72; 81 40-48 (pt); 50-99 Commercial –$71.6 –$95.5 –$167.1

Residential NA –$42.7 –$42.7 Grand Total –$414.3 –$448.7 –$862.9 NA = Not applicable. pt = Part.6-3 With exception of the natural gas market, en ergy producers are expect ed to experience producer surplus losses. Under the final rule, electricity, petroleum, and coal producer surplus is projected to decline by approximately $35 million. In contrast, natural gas producer surplus is projected to increase by $4 million as they be nefit from increased demand from industries switching from petroleum and electricity.
The majority welfare impacts fall on the agriculture, manufacturing, and mining industries. EPA estimates total welfare losses of $609.8 million for these sectors. Manufacturing industries with large number of boilers and process heaters and i ndustries that consume electricity experience the majority these losses (e.g., chemicals a nd allied products, paper, textile mill products, and food). Consumers in these indu stries experience loss es of $295.2 million and producers bear $314.6 million. The cost of this rule to producers as a percentage of baseline 2005 shipments is less th an 0.5 percent.
EPA also examined the impact on the commerci al, transportation and residential sectors. The total welfare loss for the commercial sector is estimated to be $167.1 million. Therefore, the regulatory burden associated with the MACT is estimated as 0.001 percent of total 2005 commercial sector revenues. Consumers in this sector bear approxi mately $71.6 million and producers bear $95.5 million of these impacts. In contrast, the total welfare loss for the transportation sector is estimated to be $9.0 m illion. The regulatory burden associated with the rule is estimated as 0.003 per cent of total 2005 transportation se ctor revenues. Transportation consumers bear approximately $4.7 million and pr oducers bear $4.3 million of these impacts. Finally, the social cost burden to residentia l consumers of energy, $42.7 million, is 0.037 percent of annual residential en ergy expenditures in 2005.

6.2 National Market-Level Impacts Increases in the costs of production in the energy and final product markets due to the regulation are expected to result in changes in prices, production, and consumption from baseline levels. As shown in Table 6-3, the electricity market price increases by 0.050 percent, while production/consumption decreases by 0.011 percent as a result of additional control costs. A significant share of electricity is produced in the United States using coal as a primary input. Therefore, projected reductions in electricity production also lead to a decrease in demand for coal. As a result, the price a nd quantities of coal are project ed to fall by 0.007 percent and 0.010 percent, respectively. In the petroleum market, the model projects small price and quantity effects (i.e., less than 0.01 per cent). In the natural gas market, the model projects the market price will rise in response to increased demand (0 .005 percent). The price increase is the result of additional control costs and increased dema nd. Production and consumption quantities also increase in this market (0.002) as a result of increased demand.6-4 Table 6-3. Market-Level Impacts: Final Rule

Percent Change
Sectors/Markets Price Quantity Energy Markets Petroleum 0.002% 0.000% Natural gas 0.005% 0.002% Electricity 0.050% –0.011% Coal –0.007% –0.010%

NAICS Code SIC Code Description 311 20 (pt) Food 0.006% –0.002% 312 20 (pt); 21 Beverage and Tobacco Products 0.003% –0.004% 313 22 (pt) Textile Mills 0.025% –0.021% 314 22 (pt) Textile Product Mills 0.000% 0.000% 315 23 Apparel 0.000% –0.001% 316 31 Leather and Allied Products 0.002% –0.003% 321 24 Wood Products 0.041% –0.008% 322 26 Paper 0.026% –0.028% 323 27 Printing and Related Support 0.000% 0.000% 325 28 Chemicals 0.009% –0.013% 326 30 Plastics and Rubber Products 0.001% –0.002% 327 32 Nonmetallic Mineral Products 0.003% –0.003% 331 33 Primary Metals 0.011% –0.009% 332 34 Fabricated Metal Products 0.003% –0.001% 333 35 Machinery 0.002% –0.001% 334 36 (pt) Computer and Electronic Products 0.001% 0.000% 335 36 (pt) Electrical Equipment, Appliances, and Components 0.002% –0.001%

336 37 Transportation Equipment 0.004% –0.004% 337 25 Furniture and Related Products 0.008% –0.026% 339 39 Miscellaneous 0.001% 0.000% 11 01-08 Agricultural Sector 0.000% 0.000% 23 15-17 Construction Sector 0.000% 0.000% 21 10; 14 Other Mining Sector 0.012% –0.004% 48 40-47 (pt) Transportation 0.001% –0.001% 42; 44-45; 49; 51-56; 61- 62; 71-72; 81 40-48 (pt); 50-99 Commercial 0.000% 0.000%

pt = Part.6-5 Additional control costs and hi gher energy costs associated w ith the regulation lead to higher goods and services prices in all markets and a decline in output. However, the changes are generally very small. Under the MACT Floor, thr ee markets have price increases greater than or equal to 0.02 percent—Wood Pr oducts (NAICS 321), Paper (NAI CS 322), and Textile Mills (NAICS 313). The producers in these sectors are expected to face higher per-unit control costs relative to other indus tries. In addition, th ese industries are al so electricity-inte nsive; therefore, costs of production also in crease as a result of hi gher electricity prices.
Although the impacts on price and quantity in the goods and services markets are estimated to be small, one possible effect of modeling market impacts at the two and three digit NAICS code level is that fuel-intensive industr ies within the larger NAICS code definition may be affected more significantly than the average industry for that NAICS code. Thus, the changes in price and quantity should be interpreted as an average for the whole NAICS code, not necessarily for each disaggregated industry within that NAICS code.

6.3 Executive Order 13211 (Energy Effects) Executive Order 13211, “Actions Concerning Re gulations That Significantly Affect Energy Supply, Distribution, or Use” (66 Fe d. Reg. 28355 [May 22, 2001]), requires EPA to prepare and submit a Statement of Energy Eff ects to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, for certain actions identified as “significant energy actions.” Section 4(b) of Executive Order 13211 defines “significant energy actions” as “any action by an agency (normally published in the Federal Register ) that promulgates or is expect ed to lead to the promulgation of a final rule or regulation, including notices of inquiry, advance notices of rulemaking, and notices of rulemaking:

 that is a significant regulatory action under Executive Order 12866 or any successor order, and is likely to have a significant adve rse effect on the supply, distribution, or use of energy; or

 that is designated by the Ad ministrator of the Office of Information and Regulatory Affairs as a significant energy action.” EPA has provided additional information on th e impacts of the final rule on affected energy markets below. 8

8 Conversion factors for heat rates were obtained from AEO 2002, Appendix H. These factors vary by year to year; 2010 values are reported in this Appendix.6-6 Energy Price Effects . As described in the market-level results section, electricity prices are projected to increase by less than 1 percent. Pe troleum and natural gas pr ices are all projected to increase by less than 0.1 percent. The price of coal is projected to decrease slightly.
Impacts on Electricity S upply, Distribution, and Use . We project the increased compliance costs for the electricity market w ill result in an annual production decline of approximately 415 million kWh under the MACT floor.
Impacts on Petroleum, Natural Gas, and Coal Supply, Distribution, and Use . The model projects decreases in petrol eum production/consumption of a pproximately 68 barrels per day under the MACT floor. In contrast, natural gas pr oduction/consumption is projected to increase by 1.1 million cubic feet per day under the MACT fl oor. This is the result of fuel switching in response to relative price changes. Finally, the model also projects less than a 1,000 tons per day decrease in coal production/cons umption in response to reduced out put from the electricity sector (a significant consumer of coal).

6.4 Conclusions The decrease in social surplus estimated using the market analysis is $862.9 million. This estimate is slightly smaller than the estimated baseline engineering costs because the market model accounts for behavioral changes of produ cers and consumers. Although the rule affects boilers and process heaters used in energy indus tries, energy producers only incur less than 6 percent of the total social cost of the regulation. This burden is spread across numerous markets because the price of energy increases slightly as a result of the regulation, which increases the cost of production for all markets that use en ergy as part of their production process.
The remaining share of the social cost is mostly borne by the manufacturing sectors which operate the majority of the boilers a nd process heaters aff ected by the regulation. Manufacturing industries bearing the largest social costs in clude percent—Wood Products (NAICS 321), Paper (NAICS 322) , and Textile Mills (NAICS 313) . However, the market model predicts that changes in th ese industries’ price and quantity do not exceed 0.02 percent.
Because of the minimal changes in price and quantity estimated for most of the affected markets, EPA expects that there would be no di scernable impact on inte rnational trade. Although an increase in the price of U.S. products relative to those of fo reign producers is expected to decrease exports and increase imports, the chan ges in price due to th e industrial boilers and process heaters MACT are genera lly too small to significantly in fluence trade patterns. There may also be a small decrease in employment, but because the impact of th e regulation is spread across so many industries and the decreases in market quantities are so small, it is unlikely that any particular industry will face a significant decrease in employment.7-1 SECTION 7 SMALL ENTITY IMPACTS
This section investigates the potential impact the regulation will have on small entities. The Agency has identified 187 small entities that will be affected by the final rule for the ICI boilers and process heaters NESHAP . For these entities, the averag e cost-to-sales ratio (CSR) is 0.52 percent and the average annual control co st is $149,000. Eight entities will incur annual costs that are greater than or equal to 3 percent of their annual sales (see Table 7-1). Table 7-1. Summary of Small Entity Impacts

February 2004 Report Final Rule Number of small entities 185 187 Total number of entities 576 576 Average annual control cost per small entity (10 3 ) $199 $149 Average control cost/sal es ratio 0.78% 0.52% Number of small entities with cost-to-sales ratios $ 1 percent 34 23 Number of small entities with cost-to-sales ratios $ 3 percent 10 8

This report corrects errors in the Februa ry 2004 report and reflects revised model unit cost estimates and corrected characterizations of size status. The net incr ease in small entities affected by the final rule was 2 entities. However, lower model unit control costs lowered the average annual control cost per small entity, wh ich had the effect of lowering the average costto-sales ratio and the number of small entities with cost-to-sales ratios greater than 1 percent. The lower model unit cost estimates were prepared as part of revisions to the costs for the final MACT standard issued in 2004, but were not in corporated in the February 2004 report due to lack of time and resources. These lower model un it costs do not reflect the risk-based compliance alternatives included in th e final MACT standard.

7.1 Background on Small Entity Screenings The regulatory costs imposed on domestic pr oducers and government entities to reduce air emissions from boilers and process heaters will ha ve a direct impact on owners of the affected facilities. Firms, individuals, or governmental juri sdictions that own the f acilities with boilers and process heaters are typically business entities that have the capacity to conduct business transactions and make business decisions that affect the faci lity. The legal and financial responsibility for compliance with a regulatory action ultimately rests with these owners, who7-2 must bear the financial conseque nces of their decisions. Enviro nmental regulations potentially affect all sizes of businesses, but small busines ses may have special prob lems relative to large businesses in complying with such regulations.
The Regulatory Flexibility Act (RFA) gene rally requires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the Administrative Procedure Act or any other statute unless the agency certifies that the rule will not have a signifi cant economic impact on a substantial number of small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions.
For purposes of assessing the impacts of toda y’s rule on small entiti es, small entity is defined as: (1) a small business according to Small Business Administration (SBA) size standards by the Standard Industrial Cla ssification (SIC) category of the owning entity. The range of small business size standards for the 40 affected industries ranges from 500 to 1,000 employees, except for petroleum refining a nd electric utilitie s. In these latter two industries, the size standard is 1, 500 employees and a mass throughput of 75,000 barrels/day or less, and 4 million megawatt- hours of production or less, respectively. (2) a small governmental jurisdiction that is a government of a city, county, town, school district or special district with a population of less than 50,000; and (3) a small organization that is any not-fo r-profit enterprise which is independently owned and operated and is not dominant in its field. This section investigates ch aracteristics of businesses a nd government entities that own existing boilers and process heaters affected by this rule and provides a preliminary screeninglevel analysis to assist in determining whether this rule is likely to impose a significant impact on a substantial number of the small businesses with in this industry. The sc reening-level analysis employed here is a “sales test,” which computes the annualized compliance costs as a share of sales/revenue for existing companies/government entities.

7.2 Identifying Small Entities with Affect ed Sources in the Inventory Database As discussed in Section 3.2, EPA identified 2,186 boilers and process heaters located at commercial, industrial, and government facilities that would be affected by the regulation. The population of boilers and process heaters was de veloped from the EPA I CCR Inventory Database version 4.1. 9 The list of boilers and process heaters c ontained in these databases was developed

9 The ICCR Inventory Database contains data for boilers, pr ocess heaters, incinerators, landfill gas flares, turbines, and internal combustion engines.7-3 from information in the AIRS and OTAG databa ses, state and local permit records, and the combustion source ICR conducted by the Agenc y. Industry and environmental stakeholders reviewed the units contained in these databases as part of the ICCR FACA process. In addition, stakeholders contributed to the databases by identifying and including omitted units. Information was extracted from the ICCR databases to support the ICI boilers and pr ocess heaters NESHAP. This modified database containi ng information on only boilers and process heaters is referred to as the Inventory Database.
The ICCR Inventory Database provided inform ation on thousands of facilities at which units were located. Using DUNS num bers, plant names, and ownershi p records, each facility’s ultimate parent entity was identified. The parent company was added to the Inventory Database to facilitate the SBREFA scr eening. Next, revenue, employment , and, if applicable, population and nameplate capacity data were ob tained for all parent entities:

 Parent company data were gathered from Dun & Bradstreet, Standard & Poor’s, and American Business Information. The refere nce years for this data are 1999 to 2000.

 Electric utility and nonutility data were taken from the Energy Information Administration. The reference ye ar for this data is 1999.

 Population data were obtained from the U. S. Census Bureau, and the reference year of the data is 2000. These revenue, employment, capacity, and populati on data were used to characterize each entity as either small or large using SBA small business size standards. The initial screening for this analysis was done before widespread adopti on of NAICS. All data sources still used the SIC system, and accordingly the Agency used the ultimate parent’s 4-digit SIC code when characterizing each entity as large or small.
In some instances, a facility’s 4-digit SIC code did not match the 4-digit SIC code for its parent’s primary economic activity. The size standa rd for the parent’s primary economic activity was used for the SBREFA screening; however, the f acility SIC code was left as reported so that all tables listing unit, facility, and company count s accurately reflect the economic activity of the affected boiler or process heater. For example, a government owning an electric generating unit was characterized as small if it had fewer than 50,000 residents, but the unit, facility, and parent is presented in the tables as a constituent member of SIC 49.
The sum of each parent’s affected unit contro l costs was compared with its revenue to calculate the parent’s cost-to-sa les ratio (CSR). The CSR presents the total annual control costs as a percentage of estimated annual revenue. This measure is used to determine the extent to7-4 which the proposed rule will affect the parent financially. Sections 7.3 and 7.4 present summary descriptive statistics on parent entity sales and employment, as well as th e distribution of CSRs among small and large entities.
The small entities screening analysis for the regulation is based on the evaluation of existing owners of boilers and process heaters for which information was available. It is assumed that the size and ownership distribu tion of units in the Inventory Data base is representative of the entire estimated population of exis ting boilers and process heaters. In addition, it is assumed that new sources included in the 2005 population will also be repr esentative of the Inventory Database. However, because our analysis is base d on a subset of the total population of boilers and process heaters, the number of entities identified as highly aff ected in this analysis may not be identical to the actual impact of the regula tion on small entities. The remainder of this section presents cost and sales information on small co mpanies and government organizations that own existing boilers and process heaters.

7.3 Analysis of Facility-Level and Parent-Level Data The 2,186 units in the Inventory Database with full information were linked to 1,214 existing facilities. As shown in Table 7-2, thes e 1,214 facilities are owne d by 576 parent entities. The average number of facilities per entity is appr oximately 2.0; however, as is also illustrated in Table 7-2, several large entities in the health services industr y and government sectors own many facilities with boilers and process heaters.
Employment and sales are typically used as measures of business size. Employment, sales, population, and tax revenue data (when appli cable) were collected for the 576 parent companies and government entities. 10 Figure 7-1 shows the distribu tion of employees by parent company for the final rule. Employment fo r parent companies ranges from 5 to 608,000 employees. 178 or more of the firms have fewer than 500 employees, and 55 companies have more than 25,000 employees.
Sales provide another measure of business size. Figure 7-2 pr esents the sales or revenue distribution for affected parent entities. The median sales figure for affected companies is $300 million ($200 million), and the average sales figure is $4.1 billion ($3.5 billion) (excluding the federal government). As shown in Figure 7-2, reve nue and sales figures va ry greatly across the

10 Total annualized cost is compared to tax revenue to asse ss the relative impact on local governments. This metric for estimating impacts on government entities is consistent with the 1999 Interim Final RFA and SBREFA Guidance prepared by EPA and issued in March 1999.7-5 Table 7-2. Facility-Level and Parent-Level Data by Industry

SIC Code NAICS Code Description Number of Units Number of Facilities Number of Parent Entities Avg. Number of Facilities Per Parent Entity 01 111 Agriculture—Crops 3 3 3 1.0 02 112 Agriculture—Livestock — — — — 07 115 Agricultural Services — — — — 10 212 Metal Mining 9 4 2 2.0 12 212 Coal Mining 2 1 — — 13 211 Oil and Gas Extraction — — — — 14 212 Mining/Quarrying—Nonmetallic Minerals 8 4 3 1.3 17 235 Construction—Special Trade — — — — 20 311 Food and Kindred Products 138 60 32 1.9 21 312 Tobacco Products 11 7 4 1.8 22 313 Textile Mill Products 135 71 33 2.2 23 315 Apparel & Other Products from Fabrics 2 2 1 2.0 24 321 Lumber and Wood Products 360 262 122 2.1 25 337 Furniture and Fixtures 234 154 67 2.3 26 322 Paper and Allied Products 321 194 68 2.9 27 511 Printing, Publishing, and Related Industries — — — — 28 325 Chemicals and Allied Products 174 70 41 1.7 29 324 Petroleum Refining and Re lated Industries 11 8 9 0.9 30 326 Rubber and Misc. Plastics Products 17 13 9 1.4 31 316 Leather and Leather Products 1 1 1 1.0 32 327 Stone, Clay, Glass, and Concrete Products 9 7 4 1.8 33 331 Primary Metal Industries 41 16 10 1.6 34 332 Fabricated Metal Products 16 10 7 1.4 35 333 Industrial Machinery and Computer Equip. 23 12 9 1.3 36 335 Electronic and Electrical Equipment 5 5 3 1.7 37 336 Transportation Equipment 102 41 12 3.4 38 334 Scientific, Optical, and Photographic Equipment 8 4 3 1.3
39 339 Misc. Manufacturing Industries 2 2 2 1.0 40 482 Railroad Transportation 4 1 1 1.0 42 484 Motor Freight and Warehousing 5 1 1 1.0 46 486 Pipelines, Except Natural Gas — — — — 49 221 Electric, Gas, and Sani tary Services 318 160 80 2.0 50 421 Wholesale Trade—Durable Goods 3 2 1 2.0 51 422 Wholesale Trade—Nondurable Goods 2 1 1 1.0 55 441 Automotive Dealers and Gasoline Service Stations — — — —
58 722 Eating and Drinking Places — — — — 59 445–454 Miscellaneous Retail — — — — 60 522 Depository Institutions — — — — (continued)7-6 Table 7-2. Facility-Level and Parent-Level Data by Industry (continued)

SIC Code NAICS Code Description Number of Units Number of Facilities Number of Parent Entities Avg. Number of Facilities Per Parent Entity 70 721 Hotels and Other Lodging Places 1 1 1 1.0 72 812 Personal Services — — — — 76 811 Misc. Repair Services 2 1 — — 80 621 Health Services 37 18 2 9.0 81 541 Legal Services — — — — 82 611 Educational Services 105 45 30 1.5 83 624 Social Services 2 1 — — 86 813 Membership Organizations — — — — 87 541 Engineering, Accounting, Research, Management and Re lated Services 2 2 1 2.0

89 711/514 Services, N.E.C. 2 1 — — 91 921 Executive, Legislative, and General Administration 1 1 — —

92 922 Justice, Public Orde r, and Safety 29 9 — — 94 923 Administration of Human Resources 1 1 — — 96 926 Administration of Economic Programs 4 3 1 3.0 97 928 National Security and International Affairs 29 11 2 5.5 NA SIC Information Not Available 7 4 — — State Parent is a state government — — 10 —

Total 2,186 1,214 576 2.0 Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.

10 12 31 125

52 121 141

55

0 50 100 150 200

<25 25 to 49 50 to 99 100 to 499 500 to 999 1,000 to 4,999 5,000 to 24,999 >25,000

Parent EmploymentNumber of Parents

Figure 7-1. Parent Size by Employment Range7-7 7 18 128

56 110

51 133

20 33 17
0 50 100 150 200

<5 5 to 9 10 to 49 50 to 99 100 to 499 500 to 999 1,000 to 4,999 5,000 to 9,999 10,000 to 24,999 >25,000
Parent Sales ($10 6 )Number of Parents

Figure 7-2. Number of Parents by Sales Range *Excludes 3 parent entities for which sales or revenue information was unavailable.
population: 209 firms and governments affected by the final rule ha ve annual revenues less than $100 million per year. These figures include all sa les associated with the parent company, not just facilities affected by the re gulation (i.e., facilities with boilers or process heaters).
Based on SBA guidelines, 187 of the entitie s were identified as small businesses. 11 Small businesses by business type are presented in Table 7-3. The lumber a nd wood products industry contains the largest number of the small busines ses with 84, followed by furniture and fixtures with 28, electric services with 28, and paper a nd allied products with 13. The remaining small businesses are distributed across 40 different two-digit SIC code groupings. This corrected report identified 2 additional small entities in SIC 49, cha nged one entity in SIC 80 from small to large, and corrected one SIC 82 entity from large to small.

11 Small business guidelines typically define small businesses based on employment, and the threshold varies from industry to industry. For example, in the paints and a llied products industry, a business with fewer than 500 employees is considered a small business; whereas in the industrial gases industry, a business with fewer than 1,000 employees is considered small. However, for a fe w industries, usually services, sales are used as the criterion. For example, in the veterinary hospital industry, companies with less than $5 million in annual sales are defined as small businesses.7-8 Table 7-3. Small Parent Entities by Industry

SIC Code NAICS Code Description Number of Parent Entities February 2004 Report Number of Small

Parent Entities Final Rule Number of Small

Parent Entities 01 111 Agriculture—Crops 3 — — 02 112 Agriculture—Livestock — — — 07 115 Agricultural Services — — — 10 212 Metal Mining 2 2 2 12 212 Coal Mining — — — 13 211 Oil and Gas Extraction — — — 14 212 Mining/Quarrying—Nonmetallic Minerals 3 — — 17 235 Construction—Special Trade Contractors — — — 20 311 Food and Kindred Products 32 12 12 21 312 Tobacco Products 4 — — 22 313 Textile Mill Products 33 5 5 23 315 Apparel and Other Products from Fabrics 1 — — 24 321 Lumber and Wood Products 122 84 84 25 337 Furniture and Fixtures 67 28 28 26 322 Paper and Allied Products 68 13 13 27 511 Printing, Publishing, and Related Industries — — — 28 325 Chemicals and Allied Products 41 4 4 29 324 Petroleum Refining and Related Industries 9 2 2 30 326 Rubber and Misc. Plastics Products 9 1 1 31 316 Leather and Leather Products 1 1 1 32 327 Stone, Clay, Glass, a nd Concrete Products 4 — — 33 331 Primary Metal Industries 10 1 1 34 332 Fabricated Metal Products 7 3 3 35 333 Industrial Machinery and Computer Equip. 9 1 1 36 335 Electronic and Electrical Equipment 3 — — 37 336 Transportation Equipment 12 1 1 38 334 Scientific, Optical, and Photographic Equip. 3 — — 39 339 Miscellaneous Manufacturing Industries 2 — — 40 482 Railroad Transportation 1 — — 42 484 Motor Freight and Warehousing 1 — — 46 486 Pipelines, Except Natural Gas — — — 49 221 Electric, Gas, and Sa nitary Services 80 26 28 50 421 Wholesale Trade—Durable Goods 1 — — 51 422 Wholesale Trade—Nondurable Goods 1 — — 55 441 Automotive Dealers and Gasoline Stations — — — 58 722 Eating and Drinking Places — — — 59 445–454 Miscellaneous Retail — — — 60 522 Depository Institutions — — — (continued)7-9 Table 7-3. Small Parent Entiti es by Industry (continued)

SIC Code NAICS Code Description Number of Parent Entities February 2004 Report Number of Small

Parent Entities Final Rule Number of Small

Parent Entities 70 721 Hotels and Other Lodging Places 1 — — 72 812 Personal Services — — 76 811 Misc. Repair Services — — 80 621 Health Services 2 1 — 81 541 Legal Services — — — 82 611 Educational Services 30 — 1 83 624 Social Services — — — 86 813 Membership Organizations — — — 87 541 Engineering, Accounting, Research, Management and Re lated Services 1 — —

89 711/514 Services, N.E.C. — — — 91 921 Executive, Legislative, and General Administration — — —
92 922 Justice, Public Or der, and Safety — — — 94 923 Administration of Human Resources — — — 96 926 Administration of Economic Programs 1 — — 97 928 National Security and International Affairs 2 — — NA SIC Information Not Available — — — State Parent is a State Government 10 — —

Total 576 185 187 Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.
7.4 Small Entity Impacts Table 7-4 presents a summary of the ratio of control costs to sales for affected large and small entities. The average CSR is 0.10 percen t for large entities (excluding the federal government) and 0.52 percent for small entities. In all, 23 small parents had CSRs greater than 1 percent, assuming add-on cont rol is employed to meet the standard. For these 23 parent companies, the CSRs ranged from 1.00 percent to 7.83 percent. Eight entities had CSRs ratios greater than 3 percent. The Febr uary 2004 report identified 44 sm all entities, 10 of which were impacted at the greater than 3 percent cost-to-sales ratio level.7-10 Table 7-4. Summary Statistics fo r SBREFA Screening Analysis

February 2004 Report Final Rule

Total Number of Small Entities 185 187 Average Annual Compliance Cost per Small Entity ($10 3 ) $199 $149
Entities with Sales/Revenue Data Compliance costs are <1% of sales 141 164 Compliance costs are $ 1 to 3% of sales 34 15 Compliance costs are $ 3% of sales 10 8 Compliance Cost-to-Sales/Revenue Ratios Average 0.78 0.52 Median 0.50 0.16 Maximum 7.83 7.83 Minimum 0.01 0.01

7.5 Affected Government Enti ties: Supplemental Analysis Of the 187 small entities identified, 14 were small governmental jurisdictions that own and operate public utilities with affected boilers. The Regulator y Flexibility Act as amended by the Small Business Regulatory Enforcement Fairness Act provides the following standard definition of “small governmental jurisdiction”: a city, county, town, township, village, school district, or special dist rict with a population of less than 50,000. For this analys is, public power producers are defined as nonprofit pu blicly owned utilitie s operated by munici palities, counties, and states or other publicly owned bodies such as public utility districts. This excludes rural electric cooperatives.
As illustrated in Table 7-5, the vast majority of small municipal systems with affected boilers are located in the Midwest (10 systems or 71 percent). Four of the 10 municipal systems are located in Minnesota and two are in Indiana. The February 2004 report incorrectly identified 13 small government entities; the third column of Table 7-5 includes one additional entity in both Pennsylvania and Georgia, but removes a Mich igan municipality incorrectly categorized as small.
Historically municipal utilitie s were created to provide residents of a community with reliable energy. For example, the residential sector accounts for mo re than two-thirds of total consumers in all cases (see Table 7-6). However, the residential sector ge nerally represents the smallest group in terms of to tal energy consumption. The indus trial and commercial sectors7-11 Table 7-5. Regional Distribut ion of Municipal Systems

Regional Distribution February 2004 Report Number of Facilities Final Rule Number of Facilities East

Pennsylvania

— 1 Vermont 1 1 Midwest

Indiana 2 2 Iowa 1 1 Michigan 2 1 Minnesota 4 4 Ohio 1 1 Wisconsin 1 1 South

Georgia

— 1 West

California 1 1 Total 13 14

consume approximately 70 percent of total energy supplied. Power not consumed by the residential, commercial, or i ndustrial sector is sold into the wholesale energy market.
Public power producers do not pay state or local taxes. Howeve r, they typically are under agreement to make annual contributions to st ate and local government operating funds. In addition, they are not guaranteed a rate of return (as regulated pub lic utilities are); however, their rates are set by agreement with lo cal councils, and these rates are typically adjusted to reflect changes in operating costs.
Municipal utilities can genera te capital by issuing tax-ex empt municipal bonds. These municipal bonds are exempt from federal income taxes, permitting publicly owned utilities to finance capital projects at a more affordable rate. Additionally, the local governments investing in municipal utilities generally issue revenue bonds rather than genera l obligation bonds. This ensures that the debt can be paid back through revenues from generating electricity and does not obligate the local government or community tax base.7-12Table 7-6. Selected Municipal Utilities’ Capacity, Usage, and Consumer TypesDistribution of Energy Usage by CustomerTypeDistribution of CustomersRowIDCapacity(MW)Energy Usage(kWh/y)ResidentialCommercialIndustrialTotalConsumersResidentialCommercialIndustrial1 50.5 332,524,000 27% NA NA 19,313 82% 15% 3.7%2 115 371,823,000 36% 28% 16% 15,615 87% 11% 0.3%3 24.3 388,066,000 19% 10% 70% 9,082 84% 14% 1.0%4 22.2 185,191,000 26% 14% 58% 6,235 86% 13% 1.6%5 34.5 147,335,000 26% 27% 44% 5,955 86% 14% 0.3%6 23 573,003,000 8% NA NA 7,207 90% 7% 1.0%7 35 338,903,000 38% 8% 51% 13,247 87% 11% 1.3%8 46 194,753,000 22% NA NA 6,890 85% 13% 0.1%9 103.1 837,175,000 NA NA NA NA NA NA NA10 32 218,208,000 40% 3% 55% 10,829 88% 3% 8.4%11 26 267,201,000 16% NA NA 9,471 75% 24% 0.3%12 34 95,642,000 33% 67% NA 5,747 83% 17% 0.3%13 31.5 363,989,000 39% NA NA 11,650 79% 19% 0.6%Source: Giles, Ellen F. 2000. Platt’s Directory of Electric Power Producers and Distributors, 109th Edition of the Electrical World Directory. New York:McGraw Hill.Note: One impacted municipality’s boiler is employed by its city school district; the unit is not an electric generating unit.This corrected report includes amunicipal utility system (Row 13) that was incorrectlycategorized as large in the February 2004 report.7-13 As shown in Table 7-7, the average total a nnual compliance costs per entity are $258,654 under the final rule. The median cost-to-revenue ra tio is 0.90 percent, and ratios range from less than 0.5 percent to 8 percent. Three of the a ffected small governments have cost-to-revenue ratios at or above 3 percent. The average a nnual control cost for impacted small governments increased in the corrected versi on of the report becau se the total annual co ntrol costs for the corrected subset of muni cipal entities increased. Table 7-7. Comparison of Screening Analysis Re sults for Small Governmental Jurisdictions

February 2004 Report Final Rule

Total Number of Small Entities 13 14 Average Total Annual Compliance Cost (TACC) per Small Entity ($10 3 ) $223 $259
Entities with Sales/Revenue Data Compliance costs are <1% of revenue 7 7 Compliance costs are $ 1 to 3% of revenue 3 4 Compliance costs are $ 3% of revenue 3 3 Compliance Cost-to-Sales/Revenue Ratios Average 1.67 1.51 Median 0.94 0.90 Maximum 7.83 7.83 Minimum 0.02 0.02

7.6 Small Utility and Nonutility Entities: Data and Screening Analysis Results
EPA identified 14 small commercial utilities and nonutilities in addition to the 14 small municipal utility systems. The commercial entities consisted of 11 small electric power generators (SIC 4911). One facility is a cogenera tion plant at a sugar cane processing facility. The remaining two entities are small local privat e utility services that provide steam services within a limited service territory (see Table 7-8).
As shown in Table 7-9, the average total a nnual compliance costs per entity are $270,428 under the final rule. The median cost-to-revenue ra tio is 0.24 percent, and ratios range from less than 0.02 percent to 1.02 percent. Only 1 of these 14 affected enti ties has a cost-to-revenue ratio at or above 1 percent.7-14 Table 7-8. Industry Distribution of Small Co mmercial Electric Utility and Nonutility Entities

Parent SIC Code Parent Industry Final Rule Number of Entities SBA Size Standard 2062 Sugar Cane Producers 1 750 employees 4911 Electric Generation 11 4 million megawatt hours 4931 Electricity and Other Services Combined 1 $5 million annual revenue 4961 Steam and Air Conditioning Supply 1 $9 million annual revenue Total 14

Table 7-9. Supplemental Screening Analysis fo r Small Governmental Jurisdictions

Final Rule Total Number of Small Entities 14 Average Total Annual Compliance Cost (TACC) per Small Entity ($10 3 ) $270
Entities with Sales/Revenue Data Compliance costs are <1% of revenue 13 Compliance costs are $ 1 to 3% of revenue 1 Compliance costs are $ 3% of revenue 0 Compliance Cost-to-Sales/Revenue Ratios Average 0.33 Median 0.24 Maximum 1.02 Minimum 0.02

7.7 Assessment of SBREFA Screening This analysis indicates that over two-thirds of the entities aff ected by the industrial boilers and process heat ers standard are large. 12 The relatively small proportion of small entities affected by the regulation at the MACT floor is due in part to the exclusion of ICI boilers and process heaters with less than 10 MMBtu input capacity that also us e a fossil fuel liquid or gas as primary fuel. As a result, a large share of small boilers and process heaters, which are presumably owned disproportionately by smaller en tities, will not incur compliance costs. The Agency estimates that approximately 57 percent of the U.S. population are less than 10 MMBtus or are emergency units and, hence, are excluded from the regulation.

12 Based on SBA guidelines for determining small entities.7-15 Of the small entities affected by the final rule, the majority are in the lumber and wood products, furniture and fixtures, paper and allied pr oducts, and electric, gas and sanitary services sectors. As shown in Table 7-10, the median profit margin for thes e four sectors is approximately 3 percent. Table 7-10 also shows the profit margins for the other industry sectors with affected small businesses. All profit margins of industry se ctors with affected small businesses are above 2 percent. Table 7-10. Profit Margins for Industry Sectors with Affected Small Businesses

SIC Code NAICS Code Description Median Profit Margin 20 311 Food and Kindred Products 3.6% 22 313 Textile Mill Products 2.1% 24 321 Lumber and Wood Products 3.0% 25 337 Furniture and Fixtures 3.0% 26 322 Paper and Allied Products 3.3% 28 325 Chemicals and Allied Products 2.7% 49 221 Electric, Gas, and Sanitary Services 7.5%

Source: Dun & Bradstreet. 1997. Industry Norms & Key Business Ratios . Desktop Edition 1996-97. Murray Hill, NJ: Dun & Bradstreet, Inc.
After considering the economic impact of the final rule on small entities, EPA certifies that this action will not have a significant imp act on a substantial number of small entities. In accordance with the RFA, as amended by the SBREFA, 5 U.S.C. 601, et. seq., EPA conducted an assessment of the standard on small businesse s within the industries affected by the rule. Based on SBA size definitions a nd reported sales and employment data, the Agency identified 187 entities, or 32 percent.
Although small entities represent 32 percent of the SBREFA screening population, they are expected to incur only 7.5 percent of the screening popula tion’s compliance costs of $370.4 million (1998$). Only 8 small entities have complianc e costs equal to or greater than 3 percent of their sales. In addition, only 15 small entities have CSRs between 1 and 3 percent. Additional analysis of small governmental jurisdictions show s 3 of 14 have CSRs greater than 3 percent, and 4 have CSRs between 1 and 3 percent.
An EIA was performed to estimate the change s in product price and production quantities for this rule. As mentioned in the summary of economic impacts earlier in this report, the estimated changes in prices and output for aff ected firms (including small firms) are no more than 0.04 percent. It should be noted that we di d not use median profit margin data in drawing any conclusions on the size of the small en tity impacts estimated for this report.7-16 This rule will not have a significant economic impact on a substantial number of small entities as a result of several decisions EPA ma de regarding the development of this rulemaking which resulted in limiting the impact of this rule on small entities. First, as mentioned earlier, EPA identified small units (heat input of 10 MMBtu /hr or less) and limited-use boilers (operate less than 10 percent of the time) as separate subcategories from large units. Many small and limited-use units are located at small entities. As also discussed earlier, th e result of the MACT floor analysis for these subcategories of exis ting sources was that no MACT floor could be identified except for the limited-use solid fuel subcategory, which is less stringent than the MACT floor for large units. Furthermore, the resu lts of the above-the-flo or analysis for these subcategories indicated that the costs would be too high to be c onsidered feasible. Consequently, this rule contains no emission limitations for any of the existing small and limited-use subcategories except the existing limited-use soli d fuel subcategory. In addition, the alternative metals emission limit resulted in minimizing the impacts on small entities because some of the potential entities burning a fuel containi ng very little metals are small entities.R-1 REFERENCES

American Public Power Association (APPA). 2002. Straight Answers to False Charges about Public Power . Washington, DC: APPA. <http:// www.appanet.org/about/publicpower/ index.cfm>. As obtained on November 13, 2003. Dahl, Carol A., and Thomas E. Duggan. 1996. “U.S. Energy Product Supply Elasticities: A Survey and Application to the U.S. Oil Market.” Resource and Energy Economics 18:243- 263.

Dun & Bradstreet. 1997. Industry Norms & Key Business Ratios . Desktop Edition 1996-97. Murray Hill, NJ: Dun & Bradstreet, Inc. Eastern Research Group. Memorandum to Jim E ddinger, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Development of the Population Database for the Industrial/Commercial/ Institutional Boiler and Indi rect-Fired Process Heater National Emission Standard for Hazar dous Air Pollutants (NESHAP). May 18, 2000. Eastern Research Group. Memorandum to Jim E ddinger, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standard s. Development of Model Units for the Industrial/Commercial/Institutio nal Boiler and Indirect-Fired Process Heater National Emission Standard for Hazardous Ai r Pollutants (NESHAP). July, 2000.

Edison Electric Inst itute (EEI). 1998. Statistical Yearbook of the Electric Utility Industry 1997. November. Washington, DC. E.H. Pechan & Associates, Inc. 1997. Qualitative Market Impact Analysis for Implementation of the Selected Ozone and PM NAAQS. Appendix B. Prepared for the U.S. Environmental Protection Agency. Fleming, Ian. 1992. “Just How Clean is your Steam?: Minimizing Risk of Product Contamination and Prol onging Filter Life.” Manufacturing Chemist 63(10):37-39. Giles, Ellen F. 2000. Platt’s Directory of Electric Po wer Producers and Distributors, 109th Edition of the Electrical World Directory . New York: McGraw Hill. Haltmaier, Susan. 1998. “Electric ity Production and Sales.” In U.S. Industry & Trade Outlook ‘98 , DRI/McGraw-Hill, Standard & P oor’s, and U.S. Department of Commerce/international Trade Administrati on. New York: McGraw-Hill. pp. 5-1 to 5-9.

Industrial Combustion Coordinated Rulemaki ng (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A-94-63, II-K-4b2 through -4b5. Research Triangle Pa rk, North Carolina. September 16-17. Lemm, Jamie. 2000. “Household Furniture.” In U.S. Industry & Trade Outlook 2000 . New York: DRI/McGraw-Hill, Standard & Poor’s, and U.S. Department of Commerce/International Trade Administration.R-2 Plant Engineering . 1991. “Boiler Systems.” Plant Engineering 45(14):92-94. Texas Utilities (TXU). 2000. “Generating Electri city: Steam Turbines.” As obtained in September 2000. <http://www.txu.com/knowle dge/energy_lib/generating01.html>. U.S. Bureau of Economic Analysis. 1997. Re gional Economic Information System: 1969-1995 on CD-ROM [machine-readable data file s]/prepared by the Bureau of Economic Analysis, U.S. Department of Commerce. Washington, DC: The Bureau of Economic Analysis [producer and distributor], 1997. <h ttp://govinfo.kerr.orst.edu/ reis-stateis.html>. As obtained February 2002. U.S. Environmental Protection Agency. July 19 99: “Draft Revised Guidelines for Carcinogen Risk Assessment.” NCEA-F-0644. USEPA, Risk Assessment Forum. Pp 3-9ff. Http://www.epa.gov/ncea/raf/pdfs/cancer_gls.pdf. U.S. Department of Agriculture, National Ag riculture Statistics Service. 1997 Census of Agriculture. <http://govinfo.library.orst.edu/ cgi-bin/ag-list?02-sta te.usa>. As obtained February 2002. U.S. Department of Commerce, Bureau of the Census. 1990-1998. Annual Survey of Manufactures [Multiple Years] . Washington, DC: Govern ment Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990a. 1987 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990b. 1987 Census of Manufactures, Industry Series, Paints and Allied Products . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1990c. 1987 Census of Manufactures, Industry Series: Pulp, Paper, and Board Mills . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1991. 1987 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995a. 1992 Census of Manufactures, Industry Series: Drug Industry . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995b. 1992 Census of Manufactures, Industry Series: Industrial Organic Chemicals . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1995c. 1992 Census of Manufactures, Industry Series: Pulp, Paper, and Board Mills . Washington, DC: Government Printing Office.R-3 U.S. Department of Commerce, Bureau of the Census. 1995d. 1992 Concentration Ratios in Manufacturing . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1996. 1992 Census of Manufactures, Subject Series: General Summary . Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. 1998. Survey of Plant Capacity: 1996. Washington, DC: Government Printing Office. U.S. Department of Commerce, Bureau of the Census. Economy-Wide Key Statistics: 1997. <http://factfinder.census.gov/servlet/datasetma inpageservlet?_program=ecn&_ lang=en>. As obtained February 2001. U.S. Department of Commerce, Bureau of the Census. 2001. “1997 Economic Census—United States.” As obtained on March 13, 2001. <http://www.census.gov/epcd/ec97/us/US000_31.HTM>. U.S. Department of Energy, Energy In formation Administration (EIA). 1996. Electric Power Annual 1995. Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy In formation Administration (EIA). 1997. Financial Statistics of Major U.S. Investo r-Owned Electric Utilities, 1996. Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Info rmation Administration (EIA). 1998a. The Changing Structure of the Electric Power Industry: Selected Issues, 1998 . DOE/EIA-0562(98). Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy In formation Administration (EIA). 1998b. Financial Statistics of Major Publicly Owned Electric Utilities, 1997 . Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Informati on Administration (EIA). “Annual Energy Outlook 1999—Market Trend—Electricity.” <http://www.eia.doe.gov/oiaf/aeo99/electric ity.html>. As accessed November 15, 1999a. U.S. Department of Energy, Energy In formation Administration (EIA). 1999b. The Changing Structure of the Electric Power I ndustry 1999: Mergers and Other Corporate Combinations . Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. “Competitive Electricity Price Projections.” <http://www.eia.doe.gov/oia/elepri97/chap3.ht ml>. As obtained on November 15, 1999c. U.S. Department of Energy, Energy In formation Administration (EIA). 1999d. Electric Power Annual, 1998 . Volumes I and II. Washington, DC: U.S. Department of Energy.R-4 U.S. Department of Energy, Energy Informati on Administration (EIA). “Issues in Midterm Analysis and Forecasting 1999—T able 1.” <http://www.eia.doe.gov/ oaif/issues/pricetb l1.html>. As obtained on May 8, 2000a. U.S. Department of Energy, Energy Inform ation Administration (EIA). January 2000b. Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System . DOE/EIA-M064(2000). Washington, DC: U.S. Department of Energy. U.S. Department of Energy, Energy Informati on Administrations (EIA). 2002. “Annual Energy Outlook 2002.” <http://www.eia.doe.gov/oiaf/aeo /index.html>. As obtained on February 12, 2002. U.S. Department of Justice. 1992. Horizontal Merger Guidelines . Washington, DC: U.S. Department of Justice. U.S. Environmental Protection Agency (EPA). 1993. Alternative Control Techniques Document– NO x Emissions from Process Heaters (Revised) . Washington, DC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA), Office of Compliance Sector Notebook Project. 1995a. Profile of the Lumber and Wood Products Industry . Washington, DC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA), Office of Compliance Sector Notebook Project. 1995b. Profile of the Pulp and Paper Industry . Washington, DC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA), Office of Compliance Sector Notebook Project. 1995c. Profile of the Organic Chemical Industry . Washington, DC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA). 1997a. EPA Office of Compliance Sector Notebook Project: Profile of the Ph armaceutical Manufacturing Industry . Washington, DC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA). 1997b. Regulatory Impact Analysis of Air Pollution Regulations: Util ity and Industrial Boilers . Research Triangle Park, NC: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Industrial Combustion Coordinated Rulemaking, Inve ntory Database V4—Process Heaters. November 13, 1998. U.S. Environmental Protection Agency (EPA). 1999. OAQPS Economic Analysis Resource Document . Durham, NC: Innovative St rategies and Economics Group.R-5 U.S. Environmental Protection Agency (EPA). July 1999. “Draft Revised Guidelines for Carcinogen Risk Assessment.” NCEA-F-0644. USEPA, Risk Assessment Forum. pp 3- 9ff. http://www.epa.gov/ncea/raf/pdfs/cancer_gls.pdf. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Industrial Combustion Coordinated Rulemaking, Invent ory Database V4.1-Boilers. February 26, 1999. U.S. International Trade Commission (USI TC). November 21, 2001. Memorandum to the Commission from Craig Thomsen, John Gi amalva, John Benedetto, Joshua Levy, International Economists. Investigation No. TA-201-73: STEEL-Remedy Memorandum. Warfield, et al. 2001. “Multifiber Arrangement Phaseout: Implications for the U.S. Fibers/Textiles/Fabricat ed Products Complex.” <www.fibronet.com.tw/mirron/ncs/9312/ma r.html>. As obtained September 19, 2001.A-1 APPENDIX A: ECONOMIC MODEL OF MARKETS A FFECTED BY THE BOILERS AND PROCESS HEATERS MACT
The primary purpose of the EIA for the rule is to describe and quantify the economic impacts associated with the rule. The Agency us ed a basic framework that is consistent with economic theory and the analyses performed fo r other rules to develop estimates of these impacts. This approach employs standard mi croeconomic concepts to model behavioral responses expected to occur with regulation. Th is appendix describes th e spreadsheet model in more detail and discusses how the Agency

 collected the baseline data set from the Annual Energy Outlook 2002 (DOE, EIA, 2002), U.S. Census Bureau (U.S. Depa rtment of Commerce, 2001), and U.S. Department of Agriculture (USDA, 2002).

 characterized market supply and demand for each market and specified links between the energy and agricultural, manufactur ing, mining, and commercial markets.

 introduced a policy “shock” into the model by using control cost-induced shifts in the supply functions, and

 used a solution algorithm to determine a new with-regulation equilibrium for each market.

A.1 Baseline Data Set EPA collected the following data to characterize the baseline year, 2005:

 Energy Market Data —The Department of Energy’s Supplemental Tables to the Annual Energy Outlook 2002 report forecasts of price, quantity, and fuel intensities used to calibrate the model.

 Agriculture, Mining, Manufac turing, Commercial Sectors —EPA obtained shipment data from the 1997 Economic Census and 1997 Agriculture Census. We then used annual growth rates reported by the Bur eau of Economic Analysis (BEA, 1997) to estimate baseline shipment data for 2005. The Agency selected units for output such that the price in each market equals one. We computed energy demand using fuel intensity data reported in the AEO 2002.

 Supply and Demand Elasticities —The supply and demand elasticity values used in the market model are reported in Table 5-2 of this report. Give n the uncertainties regarding these parameters, EPA also c onducted several sensitivity analyses and report these results in Appendix B.A-2 A.2 Multi-Market Model The model includes four energy markets (coal, electricity, natural gas, and petroleum) and 24 goods and service markets. The following s ections describe model equations the Agency developed to characterize these markets and esti mate welfare changes resulting from the rule. A.1.1 Supply Side Modeling EPA estimated the change in quantity supplied as follows:

Δ q S = q 0 S • ε S • 0 n

1 j j j

p p c p 

# ∑

= Δ α

− − Δ (A.1)

where q 0 S is the baseline quantity, ε S is the domestic supply elasticity, the term 

## ∑

= Δ α

− − Δ n

1 j j j p c p is the change in the producer’s net price, and p 0 is the baseline price. The
change in net price is composed of the change in baseline price resulting from the regulation, the direct shift in the supply function resulting from compliance costs, and the indirect shift in the supply function resulting from changes in input pr ices in energy market (j). The fuel share is allowed to vary using a fuel switching rule rely ing on cross-price elasticit ies of demand between
energy sources. A.1.1.1 Producer Welfare Measurement EPA approximated the change in producer surplus with the following equation:

Δ PS = q 1 • ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ Δ α

− − Δ 

## ∑

= n

1 j j j p c p – 0.5 • Δ q • ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ Δ α

− − Δ 

## ∑

= n

1 j j j p c p (A.2)

Increased control costs, higher energy input costs, and output declines have a negative effect on domestic producer surplus. However, these losses are mitigated to some degree as a result of higher market prices. A.1.2 Energy Demand Side Modeling Market demand in the energy markets is expressed as the sum of the energy, residential, agriculture, manufacturing, mining, commercial, and transportation sectors:

Q Dj = 

## ∑

= n

1 i q Dji , (A.3)A-3 where j indexes the energy market and i indexes the consuming sect or. The change in residential quantity demanded of energy market j can be approximated as follows:

Δ q D j = q 0 D j • η D j • 0 j j p p Δ (A.4)

where q 0 D j is baseline consumption, η Dj is the residential demand elasticity and ( Δ p) is the change in the market price.
In contrast, energy demand from energy, agricultural, manufacturing, mining, commercial, and transportation sectors is m odeled as a derived demand resulting from the production and consumption choices in these industries. Energy demand responds to changes in sector output and fuel switching th at occurs in response to change s in relative energy prices. For each of these sectors, energy demand is expressed as follows:

BTU ji1 = 0 i ji q BTU • FSW • q i1 (A.5)

where BTU is demand for energy market j from sect or i, q is sector i’ s output, and FSW is a factor generated by the fuel sw itching algorithm. The subscripts 0 and 1 represent baseline and with regulation conditi ons, respectively. A.1.3 Agriculture, Manufacturing, Mining, Comme rcial, and Transportation Demand Side Modeling The change in quantity demanded in these markets can be approximated as follows:

Δ q D i = q 0 D i • η D i • 0 i i p p Δ (A.6)

where q 0 D i is baseline output, η D is the demand elasticity of the respective market (i) and ( Δ p i ) is the change in the market price.
The change in consumer surplus in markets is approximated as follows:

Δ CS =~ q 1 • Δ p + 0.5 • Δ q • Δ p (A.7)
As shown, higher market prices and reduced cons umption lead to welfare losses for consumers.A-4 A.2 With-Regulation Market Equilibrium Determination Market adjustments can be c onceptualized as an interact ive feedback process. Supply segments face increased production costs as a result of the rule and are will ing to supply smaller quantities at the baseline pri ce. This reduction in market supply leads to an increase in the market price that all producers and cons umers face, which leads to further responses by producers and consumers and thus new market prices. The new with-regulation equilibrium is the result of a series of iterations in which price is adjusted and producers and consumers respond, until a set of stable market prices arises where total ma rket supply equals market demand (i.e., Q s = Q D ) in each market. Market price adjustment takes place ba sed on a price revision rule that adjusts price upward (downward) by a given percentage in response to excess demand (excess supply).
The algorithm for determining with-regulati on equilibria can be summarized by seven recursive steps: 1. Impose the control costs on affected suppl y segments, thereby affecting their supply decisions. 2. Recalculate the market supply in each market. Excess demand currently exists. 3. Determine the new prices via a price revision rule. 4. Recalculate market supply with new pr ices, accounting for fuel switching choices associated with new energy prices. 5. Compute market demand in each market. 6. Compare supply and demand in each mark ets. If equilibrium conditions are not satisfied, go to Step 3, resulting in a new set of market prices. Repeat until equilibrium conditions are sati sfied (i.e., the ratio of suppl y to demand is arbitrarily close to one).B-1 APPENDIX B: ASSUMPTIONS AND SENSITIVITY ANALYSIS
In developing the economic model to estimat e the impacts of the industrial/commercial/ institutional boilers and proce ss heaters NESHAP, several assump tions were necessary to make the model operational. This appendix lists a nd explains the major model assumptions and describes their potential impact on the analysis results. Sensitivity analyses are presented for numeric assumptions.
Assumption: The domestic mark ets for goods and services a re all perfectly competitive.
Explanation : Assuming that these markets are perfectly competitive implies that the producers of these products are unable to unilaterally aff ect the prices they rece ive for their products. Because the industries used in th is analysis are aggregated acro ss a large number of individual producers, it is a reasonable assu mption that the individual producer s have a very small share of industry sales and cannot indivi dually influence the price of output from that industry.
Possible Impact: If these product markets we re in fact imperfectly competitive, implying that individual producers can exercise market power and thus affect th e prices they receive for their products, then the economic mode l would understate possible incr eases in the price of final products due to the regulation as well as the social costs of the regulation. Under imperfect competition, producers would be able to pass al ong more of the costs of the regulation to consumers; thus, consumer surplus losses would be greater, and producer surplus losses would be smaller in the final product markets.
Assumption: Market Supply and Demand Elasticity Uncertainty
Explanation: The goods and service markets are modeled at the two or three-digit NAICS code level to operationalize the econom ic model. Because of the hi gh level of aggregation, only limited data on elasticities of supply and dema nd estimates are available. However, these elasticities strongly influence the distribution of economic impacts between producers and

consumers.
Sensitivity Analysis: Tables B-1a and Table B-1b show how the economic impact estimates vary as the supply and demand el asticities for goods and servic es change by 25 percent.B-2 Table B-1a. Sensitivity Analysis : Supply and Demand Elasticities in the Goods and Services Markets

Change Supply Demand Constant 25% Decrease Elasticities Reported in Section 6 25% Increase Change in consumer surplus –367.8 –414.3 –450.5 Change in producer surplus –495.2 –448.7 –412.4 Change in social welfar e –862.9 –862.9 –862.9

Table B-1b. Sensitivity Analysis : Supply and Demand Elasticities in the Goods and Services Markets

Supply Constant Demand Change 25% Decrease Elasticities Reported in Section 6 25% Increase Change in consumer surplus –462.7 –414.3 –364.4 Change in producer surplus –400.2 –448.7 –498.5 Change in social welfar e –862.9 –862.9 –862.9

Assumption: Cross-price elasticities of demand for fuels are based on 2015 NEMS projections.
Explanation: Cross- and own-price elasti cities of demand from NEMS we re used to capture fuel switching in the manufacturing sect ors in the economic model. As shown in Table 5-2, allowing manufacturers to switch fuels in response to ch anges in relative ener gy prices decreases the change in social welfare by approximately 10 pe rcent. However, the NEMS projection reflects aggregate behavioral responses in the year 2015. Because this is a longer window of analysis compared to the baseline year 2005, this analysis may overestimate firms’ ability to switch fuels in the short run.
Sensitivity Analysis: Table B-2 shows how the economic impact estimates vary as the own- and cross-price elasticities used in the EIA are reduced by 50 percent and 75 percent.B-3 Table B-2. Sensitivity Analysis: Own- and Cro ss-Price Elasticities Used to Model Fuel Switching

Fuel Price Elasticities Presented in Table 5-2 Reduced by 50 Percent Reduced by 75 Percent Change in consumer surplus –414.3 –414.6 –414.9 Change in producer surplus –448.7 –448.4 –448.0 Change in social welfar e –862.9 –862.9 –862.9

Assumption: The domestic markets fo r energy are perfectly competitive.
Explanation: Assuming that the markets for energy ar e perfectly competitive implies that individual producers are not capable of unilaterally affecting the prices they receive for their products. Under perfect competition, firms that ra ise their price above the competitive price are unable to sell at that higher price because they are a small share of the market and consumers can easily buy from one of a multitude of other firms th at are selling at the competitive price level. Given the relatively homogeneous nature of indi vidual energy products (p etroleum, coal, natural gas, electricity), the assumption of perfect competition at the national level seems to be appropriate.
Possible Impact: If energy markets were in fact imperfectly competitive, implying that individual producers can exercise market power and thus affect th e prices they receive for their products, then the economic mode l would understate possible increases in the price of energy due to the regulation as well as the social cost s of the regulation. Under imperfect competition, energy producers would be able to pass along more of the costs of the regulation to consumers; thus, consumer surplus losses would be greater, and producer surplus losses would be smaller in the energy markets.
Assumption: The elasticity of supply in the electricity market for existing sources is approximately 0.75.
Explanation: The price elasticity of supply in the elec tricity markets repres ents the behavioral responses from existing sources to changes in the price of elect ricity. However, there is no consensus on estimates of the pr ice elasticity of supply for electri city. This is in part because, under traditional regulation, the el ectric utility industry had a mandate to serve all its customers and utilities were compensated on a rate-based rate of return. As a result, the market concept of supply elasticity was not the driving force in uti lities’ capital investment decisions. This hasB-4 changed under deregulation. The market price for electricity has become the determining factor in decisions to retire older units or to make higher cost units available to the market.
Sensitivity Analysis : Table B-3 shows how the economic impact estimates vary as the elasticity of supply in the electricity markets varies. Table B-3. Sensitivity Analysis: Elasticity of Supply in the El ectricity Markets

ES = 0.5 ES = 0.75 ES = 1.0 Change in consumer surplus –405.0 –414.3 –419.6 Change in producer surplus –457.9 –448.7 –443.4 Change in social welfar e –862.9 –862.9 –862.9C-1 APPENDIX C: ECONOMIC ANALYSIS OF REGULATO RY ALTERNATIVE: OPTION 1A

EPA examined one above-the-floor alternative referred to in this appendix as Option 1A. Option 1A broadens the scope of affected units to include those fueled by residual fuel oil and units of covered fuel types with input capacitie s less than 10 million Btus. In this appendix, we describe the engineering compliance costs associat ed with this option, estimate the size and distribution of social cost, and report the re sults of the small entity screening analysis C.1 Engineering Cost Analysis: Aff ected Population and Cost Estimates The entire Inventory Database contains more than 58,000 ICI boilers and process heaters. The number of units included in the profile was 3,580 for Option 1A. As shown in Table C-1, the industries with the largest number of potentially affected units are the furniture, paper, lumber, and electrical services industries. These four industries al one account for nearly 60 percent of affected units. Almost all the process heaters are in the lumber industry. The remaining units are primarily distributed across the manufacturing sect or and service industri es. The distribution of units affected by the Option 1A alternative is similar to the final ru le, although both the number of units and the number of facilities is greater for Option 1A.

We describe the technical ch aracteristics of existing boile rs affected under Option 1A below (see Figure C-1). These characteristics in clude capacity range, fuel type, and level of preexisting controls.

 Capacity Range: About half of the 3,580 units affected by this a lternative have input capacities between 10 and 100 MMBtu/hr. Twen ty percent have capacities between 100 and 250, 16 percent have capacities gr eater than 250, and 13 percent have capacities less than 10 MMBtu/hr.

 Fuel Type: Coal and residual fuel oil are the primary fuel types each accounting for slightly less than one-third of the units. The remaining third primarily consists of units that consume wood or some other type of biomass fuel.

 Control Level: Forty-one percent have no existing pollution control equipment installed. Typical contro l devices include fabric filters, wet scrubbers, and electrostatic precipitators.

 Fuel Type: This alternative includes those units affected under Option 1A, as well as a large number of natural gas units that were not affect ed under Option 1A. The vast majority of the 78 percent of the total number of potentially affected units are fueled by natural gas.

 Control Level: Eighty-eight pe rcent of the affected units have no preexisting control equipment.C-2 Table C-1. Units and Facilities Affected by the Option 1A Alternative by Industry a

SIC Code NAICS Code Description Boilers Heaters Total Units Facilities 01 111 Agriculture—Crops 6 0 6 6 02 112 Agriculture—Livestock 0 0 0 0 07 115 Agricultural Services 0 0 0 0 10 212 Metal Mining 10 1 11 5 12 212 Coal Mining 2 0 2 1
13 211 Oil and Gas Extraction 8 10 18 4 14 212 Mining/Quarrying—Nonmetallic Minerals 10 0 10 5 17 235 Construction—Special Trade Contractors 2 0 2 1
20 311 Food and Kindred Products 163 0 163 72
21 312 Tobacco Products 22 0 22 11
22 313 Textile Mill Products 247 3 250 134 23 315 Apparel and Other Products from Fabrics 4 0 4 4
24 321 Lumber and Wood Products 434 28 462 337
25 337 Furniture and Fixtures 310 0 310 209 26 322 Paper and Allied Products 503 0 503 272 27 511 Printing, Publishing, and Related Industries 8 0 8 6
28 325 Chemicals and Allied Products 332 101 433 163 29 324 Petroleum Refining and Related Industries 54 108 162 50
30 326 Rubber and Miscellaneous Plastics Products 56 0 56 37
31 316 Leather and Leather Products 22 0 22 12 32 327 Stone, Clay, Glass, and Concrete Products 40 2 42 25 33 331 Primary Metal Industries 83 2 85 33
34 332 Fabricated Metal Products 44 0 44 28 35 333 Industrial Machinery and Computer Equipment 46 0 46 25 36 335 Electronic and Electrical Equipment 45 0 45 29 37 336 Transportation Equipment 158 0 158 61 38 334 Scientific, Optical, and Photographic Equip. 33 0 33 16 39 339 Miscellaneous Manufacturing Industries 14 0 14 10 40 482 Railroad Transportation 4 0 4 1 42 484 Motor Freight and Warehousing 5 2 7 3 46 486 Pipelines, Except Natural Gas 3 3 6 5 49 221 Electric, Gas, and Sanitary Services 371 1 372 185
50 421 Wholesale Trade—Durable Goods 3 0 3 2 (continued)C-3 Table C-1. Units and Facilities Affected by the Option 1A Alternative by Industry a (continued)

SIC Code NAICS Code Description Boilers Heaters Total Units Facilities
51 422 Wholesale Trade—Nondurable Goods 2 0 2 1
55 441 Automotive Dealers and Gasoline Service Stations 0 1 1 1 58 722 Eating and Drinking Places 0 0 0 0 60 522 Depository Institutions 0 0 0 0
59 445–454 Miscellaneous Retail 1 0 1 1 70 721 Hotels and Other Lodging Places 1 0 1 1
72 812 Personal Services 0 0 0 0 76 811 Miscellaneous Repair Services 2 0 2 1
80 621 Health Services 40 0 40 19 81 541 Legal Services 0 0 0 0
82 611 Educational Services 114 0 114 50
83 624 Social Services 3 0 3 2 86 813 Membership Organizations 0 0 0 0 87 541 Engineering, Accounting, Research, Management and Related Services 6 0 6 5

89 711/514 Services, N.E.C. 2 0 2 1 91 921 Executive, Legislative, and General Administration 2 0 2 2

92 922 Justice, Public Order, and Safety 33 0 33 10
94 923 Administration of Human Resources 1 0 1 1 96 926 Administration of Economic Programs 4 0 4 3 97 928 National Security and International Affairs 41 0 41 13
NA SIC Information Not Available 24 0 24 18 3,318 262 3,580 1,881

a Based on the Inventory Database.
The Agency estimates that in 2005, 9,163 units (existing units and new units) may be affected by the Option 1A. These populations were used to estimate nationa l engineering costs. As shown in Table C-2, the cost of controls for Option 1A is $1,995.8 million, with an average per-unit cost of $218,000.C-4 Input Capacity

(million Btu) Preexisting Control Technology Fuel Type Coal 31%

Coal and

Wood

5% Wood 18% Other

3% Other Biomass 9% Bagasse 2% Option 1A Alternative (n=3,580)

>250 16% 10 to 100 51%

100 to 250 20% 0 to 10 13%

Cyclone 26%

No Control 41%

Wet Scrubber 8% Fabric Filter 10% ESP 15% Residual Fuel Oil

32%

Figure C-1. Characteristics of Units Affected Table C-2. Unit Cost and Population Esti mates for the Option 1A by Industry, 2005

Total Units Total Cost
SIC Code NAICS Code Description Option 1A Units Percent Option 1A Costs (by Unit) Percent 01 111 Agriculture—Crops 11 0.12% $1,633,841 0.08% 02 112 Agriculture—Livestock — 0.00% — 0.00% 07 115 Agricultural Services — 0.00% — 0.00% 10 212 Metal Mining 34 0.37% $8,952,098 0.45% 12 212 Coal Mining 6 0.06% $683,026 0.03% 13 211 Oil and Gas Extraction 137 1.50% $6,070,001 0.30% 14 212 Mining/Quarrying—Nonmetallic Minerals 31 0.34% $17,958,177 0.90% 17 235 Construction—Special Trade Contractors 2 0.03% $230,525 0.01% 20 311 Food and Kindred Products 376 4.10% $122,487,346 6.14% 21 312 Tobacco Products 56 0.61% $13,685,614 0.69% 22 313 Textile Mill Products 673 7.34% $147,094,726 7.37% 23 315 Apparel and Other Products fro m Fabrics 10 0.11% $1,213,586 0.06% 24 321 Lumber and Wood Products 620 6.77% $89,961,854 4.51% 25 337 Furniture and Fixtures 421 4.60% $50,045,573 2.51% 26 322 Paper and Allied Produc ts 1,050 11.46% $323,736,302 16.22% 27 511 Printing, Publishing, and Rela ted Industries 37 0.40% $1,824,933 0.09% 28 325 Chemicals and Allied Produc ts 1,359 14.83% $293,027,205 14.68% 29 324 Petroleum Refining and Relate d Industries 677 7.38% $73,172,001 3.67% 30 326 Rubber and Miscellaneous Plasti cs Products 178 1.94% $18,100,195 0.91% 31 316 Leather and Leather Pr oducts 66 0.72% $6,924,480 0.35% 32 327 Stone, Clay, Glass, and Concre te Products 154 1.68% $17,509,996 0.88% 33 331 Primary Metal Industries 271 2.95% $65,174,064 3.27% (continued)C-5 Table C-2. Unit Cost and Population Esti mates for the Option 1A by Industry, 2005 (continued)

Total Units Total Cost

SIC Code NAICS Code Description Option 1A Units Percent Option 1A Costs (by Unit) Percent 34 332 Fabricated Metal Produc ts 165 1.80% $22,066,661 1.11% 35 333 Industrial Machinery and Comput er Equipment 151 1.65% $26,418,385 1.32% 36 335 Electronic and Electrical Equipment 167 1.82% $18,770,867 0.94% 37 336 Transportation Equipment 453 4.95% $107,402,909 5.38% 38 334 Scientific, Optical, and Photogr aphic Equipment 104 1.13% $13,638,983 0.68% 39 339 Miscellaneous Manufacturing Industries 37 0.41% $4,222,427 0.21% 40 482 Railroad Transportation 9 0.10% $2,240,871 0.11% 42 484 Motor Freight and Warehousing 19 0.21% $3,475,610 0.17% 46 486 Pipelines, Except Natural Gas 19 0.21% $1,959,589 0.10% 49 221 Electric, Gas, an d Sanitary Services 865 9.44% $331,479,389 16.61% 50 421 Wholesale Trade—Durable Goods 6 0.07% $2,675,296 0.13% 51 422 Wholesale Trade—Nondurable Goods 4 0.04% $2,693,380 0.13% 55 441 Automotive Dealers and Gasoline Service Stations 2 0.02% $195,421 0.01%

58 722 Eating and Drinking Places — 0.00% — 0.00% 59 445–454 Miscellaneous Retail 3 0.03% $259,585 0.01% 60 522 Depository Institutions — 0.00% — 0.00% 70 721 Hotels and Other Lodging Places 2 0.02% $849,114 0.04% 72 812 Personal Services 1 0.01% $7,840 0.00% 76 811 Miscellaneous Repair Se rvices 4 0.05% $1,120,435 0.06% 80 621 Health Services 93 1.01% $22,545,605 1.13% 81 541 Legal Services — 0.00% — 0.00% 82 611 Educational Services 273 2.98% $91,770,778 4.60% 83 624 Social Services 8 0.08% $1,448,405 0.07% 86 813 Membership Organizations — 0.00% — 0.00% 87 541 Engineering, Accounting, Research, Management and Related Services 49 0.54% $5,016,627 0.25%

89 711/514 Services, N.E.C. 2 0.02% $1,211,582 0.06% 91 921 Executive, Legislative, and General Administration 5 0.06% $845,423 0.04%

92 922 Justice, Public Order, a nd Safety 77 0.85% $21,308,885 1.07% 94 923 Administration of Human Resources 2 0.02% $314,316 0.02% 96 926 Administration of Economic Programs 8 0.09% $4,200,975 0.21% 97 928 National Security and Interna tional Affairs 96 1.05% $36,080,306 1.81% NA SIC Information Not Available 368 4.01% $12,099,975 0.61% State Parent is a state government — 0.00% — 0.00%

9,163 $1,995,805,181C-6 C.2 Economic Impact Analysis Results As shown in Table C-3, EPA estimates the we lfare impacts are over twice as high as the MACT floor ($1,995.5 million). The market an alysis shows that consumers will bear $955.3 million, or 48 percent of the total social cost as a result of higher prices and lower consumption levels. Producer surplus is project ed to decrease by $1,040.2 million, or 52 of the total social cost as result of direct control costs, higher energy costs, and reductions in output. Table C-3. Social Cost Estimates ($1998 10 6 )

Change in Social Welfare, MACT Floor Change in Social Welfare, Option 1A Baseline engineering co sts $863.0 $1,995.8 Social costs with market ad justments $862.9 $1,995.5 Difference between engineering and social costs $0.1 $0.3

With exception of the natural gas market, en ergy producers are expect ed to experience producer surplus losses. Electricity, petroleum, and coal producer surplus is projected to decline by approximately $113 million under Option 1A. In contrast, natural gas producer surplus is projected to increase by $2 million as they be nefit from increased demand from industries switching from petroleum and electricity (Table C-4).
The majority welfare impacts fall on the agriculture, manufacturing, and mining industries and EPA estimates losses of $1,444.3 million for these sectors. Manufacturing industries with large number of boilers and process heaters and i ndustries that consume electricity experience the majority these losses (e.g., chemical s and allied products, paper, textile mill products, and food). Consumers in these indu stries experience losses of $709.9 million and producers bear $734.4 million.
EPA also examined the impact on the commerci al, transportation and residential sectors. We project the commercial sector has the high est welfare losses among the three ($302 million) with commercial customers bearing approximate ly 42 percent of these losses, or $129 million. EPA estimates similar consumer surplus loss ($92 million) for residential energy consumers. Finally, the total welfare loss for the transportation sector is es timated to be $46.5 million, with transportation customers bearing slightly more than half of these losses (51 percent). However, all of these losses (consumer or producer) for these sectors repr esent less than 0.05 percent of baseline value of consumption or shipments.C-7 Table C-4. Distribution of Social Costs by Sector/Market: Option 1A ($1998 10 6 )

Change in:

Sectors/Markets Producer Surplus Consumer Surplus Social Welfare Energy Markets Petroleum –$27.3 Natural gas $2.4 Electricity –$79.5 Coal –$6.4 Subtotal –$110.8 NAICS Code SIC Code Description 311 20 (pt) Food –$90.0 –$36.0 –$126.0 312 20 (pt); 21 Beverage and Tob acco Products –$5. 4 –$9.3 –$14.7 313 22 (pt) Textile Mills –$45.0 –$103.2 –$148.2 314 22 (pt) Textile Product Mills –$0.1 –$0.3 –$0.4 315 23 Apparel –$0.9 –$2.1 –$3.0 316 31 Leather and Allied Products –$2.7 –$4.3 –$7.1 321 24 Wood Products –$72.0 –$19.2 –$91.2 322 26 Paper –$173.1 –$157.2 –$330.3 323 27 Printing and Related Support –$0.4 –$1.0 –$1.4 325 28 Chemicals –$102.4 –$204.7 –$307.1 326 30 Plastics and Rubber Products –$6.1 –$14.6 –$20.7 327 32 Nonmetallic Mineral Products –$9.1 –$10.9 –$20.0 331 33 Primary Metals –$59.5 –$13.6 –$73.1 332 34 Fabricated Metal Products –$18.6 –$5.0 –$23.6 333 35 Machinery –$17.1 –$11.4 –$28.5 334 36 (pt) Computer and Electronic Products –$12.0 –$4.8 –$16.8
335 36 (pt) Electrical Equipment, Appliances, and Components –$11.7 –$7.8 –$19.6
336 37 Transportation Equipment –$47.8 –$63.7 –$111.4 337 25 Furniture and Related Products –$9.2 –$41.8 –$51.0 339 39 Miscellaneous –$3.2 –$2.5 –$5.7 11 01-08 Agricultural Sector –$1.5 –$3.6 –$5.1 23 15-17 Construction Sector –$3.2 –$4.3 –$7.5 21 10; 14 Other Mining Sector –$18.9 –$13.1 –$32.0 48 40-47 (pt) Transportation –$24.1 –$22.5 –$46.5 42; 44-45; 49; 51-56;

61-62; 71-72; 81 40-48 (pt); 50- 99 Commercial –$129.3 –$172.5 –$301.8

Residential NA –$92.0 –$92.0 Grand Total –$955.3 –$1,040.2 –$1,995.5 NA = Not applicable. pt = PartC-8 C.2.1 Market-Level Impacts Increases in the costs of production in the energy and final product markets due to the regulation are expected to result in changes in prices, production, and consumption from baseline levels. As shown in Table C-5, the electricity market price increases by 0.11 percent, while production/consumption decreases by 0.03 percent as a result of additional control costs. A significant share of electricity is produced in the United States using coal as a primary input. Therefore, projected reductions in electricity production also lead to a decrease in demand for coal. As a result, the price and quantities of co al are projected to fall by 0.02 percent and 0.02 percent, respectively. In the petroleum market, the model projects small price and quantity effects (i.e., less than 0.02 percent). In the natural gas market, the model projects the market price will rise in response to increased demand (0 .01 percent). The price increase is the result of additional control costs and increased demand. Production and consumption quantities also slightly increase in this market as a result of increased demand.

Additional control costs and hi gher energy costs associated with the regulation lead to higher goods and services prices in all markets and a decline in output. However, the changes are generally very small. Under Option 1A, three mark ets have price increases greater than or equal to 0.05 percent—Wood Products (NAICS 321), Pa per (NAICS 322), and Textile Mills (NAICS 313). The producers in these sectors are expected to face higher per-unit c ontrol costs relative to other industries. In addition, these industries ar e also electricity-intensi ve; therefore, costs of production also increase as a resu lt of higher electricity prices. C.2.2 Executive Order 13211 (Energy Effects) EPA has provided additional information on the impacts of the rule on affected energy markets below. 13
Energy Price Effects . As described in the market-level results section, electricity prices are projected to increase by less than 1 percent. Pe troleum and natural gas pr ices are all projected to increase by less than 0.1 percent. The price of coal is projected to decrease slightly.
Impacts on Electricity S upply, Distribution, and Use . We project the increased compliance costs for the electricity market w ill result in an annual production decline of approximately 980 million kWh under Option 1A.

13 Conversion factors for heat rates were obtained from AEO 2002, Appendix H. These factors vary by year to year; 2010 values are reported in this appendix.C-9 Table C-5. Market-Level Impacts: Option 1A

Option 1A Percent Change Sectors/Markets Price Quantity Energy Markets Petroleum 0.019% –0.005% Natural gas 0.005% 0.001% Electricity 0.108% –0.026% Coal –0.020% –0.024% NAICS Code SIC Code Description 311 20 (pt) Food 0.019% –0.006% 312 20 (pt); 21 Beverage and To bacco Products 0.007% –0.009% 313 22 (pt) Textile Mills 0.050% –0.043% 314 22 (pt) Textile Product Mills 0.000% 0.000% 315 23 Apparel 0.001% –0.001% 316 31 Leather and Allied Products 0.025% –0.030% 321 24 Wood Products 0.075% –0.015% 322 26 Paper 0.068% –0.074% 323 27 Printing and Related Support 0.000% –0.001% 325 28 Chemicals 0.021% –0.032% 326 30 Plastics and Rubber Products 0.003% –0.005% 327 32 Nonmetallic Mineral Products 0.009% –0.008% 331 33 Primary Metals 0.026% –0.021% 332 34 Fabricated Metal Products 0.007% –0.001% 333 35 Machinery 0.005% –0.002% 334 36 (pt) Computer and Electronic Products 0.002% –0.001% 335 36 (pt) Electrical Equipment, Appliances, and Components 0.009% –0.004% 336 37 Transportation Equipment 0.007% –0.007% 337 25 Furniture and Related Products 0.013% –0.044% 339 39 Miscellaneous 0.003% –0.002% 11 01-08 Agricultural Sector 0.001% –0.001% 23 15-17 Construction Sector 0.000% 0.000% 21 10; 14 Other Mining Sector 0.023% –0.007% 48 40-47 (pt) Transportation 0.007% –0.005% 42; 44-45; 49; 51- 56; 61-62; 71-72; 81 40-48 (pt); 50-99 Commercial 0.001% –0.001%

pt = Part.C-10 Impacts on Petroleum, Natural Gas, and Coal Supply, Distribution, and Use . The model projects decreases in petrol eum production/consumption of a pproximately 975 barrels per day under Option 1A. In contrast, natural gas produc tion/consumption is projected to increase by 600,000 cubic feet per day under Option 1A. This is the result of fuel sw itching in response to relative price changes. Finally, the model also pr ojects less than a 1,000 t ons per day decrease in coal production/consumption in response to re duced output from the electricity sector (a significant consumer of coal). C.3 Small Entity Screening The 3,580 units in the Inventory Database with full information were linked to 1,881 existing facilities. As shown in Table C-6, th ese are facilities owned by 969 parent companies. The average number of faciliti es per company is approximately 2.2; however, several large entities in the health se rvices industry and govern ment sectors own many f acilities with boilers and process heaters.
Based on SBA guidelines, 372 of the companie s were identified as small businesses. 14 The lumber and wood products industry contains th e largest number of the small businesses with 134, followed by furniture and fixtures with 55, el ectric services with 33, and paper and allied products with 30. The remaining small businesse s are distributed across 40 different two-digit SIC code groupings (Table C-7).

14 Small business guidelines typically define small businesses based on employment, and the threshold varies from industry to industry. For example, in the paints and a llied products industry, a business with fewer than 500 employees is considered a small business; whereas in the industrial gases industry, a business with fewer than 1,000 employees is considered small. However, for a fe w industries, usually services, sales are used as the criterion. For example, in the veterinary hospital industry, companies with less than $5 million in annual sales are defined as small businesses.C-11 Table C-6. Facility-Level and Parent-Level Data by Industry

SIC Code NAICS Code Description Number of Units Number of Facilities Number of Parent Companies Avg. Number of Facilities Per Parent Entity 01 111 Agriculture—Crops 6 6 6 1.0 02 112 Agriculture—Livestock — — — — 07 115 Agricultural Services — — — — 10 212 Metal Mining 11 5 2 2.5 12 212 Coal Mining 2 1 — —
13 211 Oil and Gas Extraction 18 4 2 4.0 14 212 Mining/Quarrying—Nonmetallic Minerals 10 5 4 1.3 17 235 Construction—Special Trade 2 1 1 1.0
20 311 Food and Kindred Products 163 72 38 1.9
21 312 Tobacco Products 22 11 6 1.8
22 313 Textile Mill Products 250 134 73 1.8 23 315 Apparel & Other Products from Fabrics 4 4 3 1.3
24 321 Lumber and Wood Products 462 337 175 1.9
25 337 Furniture and Fixtures 310 209 100 2.1 26 322 Paper and Allied Products 503 272 100 2.7 27 511 Printing, Publishing, and Related Industries 8 6 3 2.0
28 325 Chemicals and Allied Products 433 163 91 1.8 29 324 Petroleum Refining and Re lated Industries 162 50 32 1.6
30 326 Rubber and Misc. Plastics Products 56 37 24 1.5
31 316 Leather and Leather Products 22 12 8 1.5 32 327 Stone, Clay, Glass, and Concrete Products 42 25 15 1.7 33 331 Primary Metal Industries 85 33 22 1.5
34 332 Fabricated Metal Products 44 28 19 1.6 35 333 Industrial Machinery and Computer Equip. 46 25 20 1.3 36 335 Electronic and Electrical Equipment 45 29 19 1.5 37 336 Transportation Equipment 158 61 26 2.3 38 334 Scientific, Optical, and Photographic Equipment 33 16 9 1.8

39 339 Misc. Manufacturing Industries 14 10 9 1.1 40 482 Railroad Transportation 4 1 1 1.0 42 484 Motor Freight and Warehousing 7 3 3 1.0 46 486 Pipelines, Except Natural Gas 6 5 1 5.0 49 221 Electric, Gas, and Sani tary Services 372 185 95 1.9
50 421 Wholesale Trade—Durable Goods 3 2 1 2.0 (continued)C-12 Table C-6. Facility-Level and Parent-Level Data by Industry (continued)

SIC Code NAICS Code Description Number of Units Number of Facilities Number of Parent Companies Avg. Number of Facilities Per Parent Entity
51 422 Wholesale Trade—Nondurable Goods 2 1 1 1.0
55 441 Automotive Dealers and Gasoline Service Stations 1 1 1 1.0

58 722 Eating and Drinking Places — — — —
59 445–454 Miscellaneous Retail 1 1 1 1.0 60 522 Depository Institutions — — — — 70 721 Hotels and Other Lodging Places 1 1 1 1.0
72 812 Personal Services — — — — 76 811 Misc. Repair Services 2 1 — —
80 621 Health Services 40 19 3 6.3 81 541 Legal Services — — — —
82 611 Educational Services 114 50 35 1.4
83 624 Social Services 3 2 1 2.0 86 813 Membership Organizations — — — — 87 541 Engineering, Accounting, Research, Management and Re lated Services 6 5 2 2.5

89 711/514 Services, N.E.C. 2 1 — — 91 921 Executive, Legislative, and General Administration 2 2 1 2.0

92 922 Justice, Public Orde r, and Safety 33 10 — —
94 923 Administration of Human Resources 1 1 — — 96 926 Administration of Economic Programs 4 3 1 3.0 97 928 National Security and International Affairs 41 13 2 6.5
NA SIC Information Not Available 24 18 2 9.0 State Parent is a state government — — 11 —

Total 3,580 1,881 969 2.2 Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.C-13 Table C-7. Small Parent Companies by Industry

SIC Code NAICS Code Description Number of Parent Companies Number of Small Parent Companies 01 111 Agriculture—Crops 6 1 02 112 Agriculture—Livestock — — 07 115 Agricultural Services — — 10 212 Metal Mining 2 2 12 212 Coal Mining — — 13 211 Oil and Gas Extraction 2 1 14 212 Mining/Quarrying—Nonmetallic Minerals 4 — 17 235 Construction—Special Trade Contractors 1 1 20 311 Food and Kindred Products 38 15 21 312 Tobacco Products 6 — 22 313 Textile Mill Products 73 27 23 315 Apparel and Other Products from Fabrics 3 2 24 321 Lumber and Wood Products 175 134 25 337 Furniture and Fixtures 100 55 26 322 Paper and Allied Products 100 30 27 511 Printing, Publishing, and Related Industries 3 2 28 325 Chemicals and Allied Products 91 19 29 324 Petroleum Refining and Related Industries 32 9 30 326 Rubber and Misc. Plastics Products 24 4 31 316 Leather and Leather Products 8 4 32 327 Stone, Clay, Glass, and Concrete Products 15 3 33 331 Primary Metal Industries 22 3 34 332 Fabricated Metal Products 18 5 35 333 Industrial Machinery and Computer Equip. 20 5 36 335 Electronic and Electrical Equipment 19 — 37 336 Transportation Equipment 26 5 38 334 Scientific, Optical, and Photographic Equip. 9 1 39 339 Miscellaneous Manufacturing Industries 9 1 40 482 Railroad Transportation 1 — 42 484 Motor Freight and Warehousing 3 1 46 486 Pipelines, Except Natural Gas 1 — 49 221 Electric, Gas, and Sanitary Services 95 33 (continued)C-14 Table C-7. Small Parent Companies by Industry (continued)

SIC Code NAICS Code Description Number of Parent Companies Number of Small Parent Companies
50 421 Wholesale Trade—Durable Goods 1 — 51 422 Wholesale Trade—Nondurable Goods 1 — 55 441 Automotive Dealers and Gasoline Service Stations 1 1

58 722 Eating and Drinking Places — — 59 445–454 Miscellaneous Retail 1 1 60 522 Depository Institutions — — 70 721 Hotels and Other Lodging Places 1 — 72 812 Personal Services — — 76 811 Misc. Repair Services — — 80 621 Health Services 3 1 81 541 Legal Services — — 82 611 Educational Services 35 4 83 624 Social Services 1 — 86 813 Membership Organizations — — 87 541 Engineering, Accounting, Research, Management and Related Services 2 —

89 711/514 Services, N.E.C. — — 91 921 Executive, Legislative, and General Administration 1 —

92 922 Justice, Public Order, and Safety — — 94 923 Administration of Human Resources — — 96 926 Administration of Economic Programs 1 — 97 928 National Security and International Affairs 2 — NA SIC Information Not Available 2 2 State Parent is a State Government 11 —
Total 969 372
Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers A- 94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina. September 16-17.C-15 C.3.1 Small Entity Screening Results As shown in Table C-8, the average cost per entity is $280,000. The median cost-to-sales ratio is 0.8 percent, and ratios range from 0.01 to 39 percent. Forty-se ven of the 372 affected small businesses have CSRs at or above 3 percent. Table C-8. Summary Statistics fo r SBREFA Screening Analysis

Option 1A Total Number of Small Entities 372 Average Annual Compliance Cost per Small Entity ($10 3 ) $280
Entities with Sales/Revenue Data Compliance costs are <1% of sales 151 Compliance costs are $ 1 to 3% of sales 104 Compliance costs are $ 3% of sales 47 Compliance Cost-to-Sales/Revenue Ratios Average 1.744 Median 0.77 Maximum 38.83 Minimum 0.01

C.3.2 Affected Government Entit ies: Supplemental Analysis As shown in Table C-9, the average total a nnual compliance costs per entity are $559,000 for Option 1A. The median cost-to-revenue ratio is 1.7 percent, and ratios range from less than 0.5 percent to 16 percent. Five of the 15 affected small government s have cost-to-revenue ratios at or above 3 percent.C-16 Table C-9. Supplemental Screening Analysis fo r Small Governmental Jurisdictions

Option 1A Total Number of Small Entities 15 Average Total Annual Compliance Cost (TACC) per Small Entity ($) $559
Entities with Sales/Revenue Data Compliance costs are <1% of revenue 13 Compliance costs are $ 1 to 3% of revenue 8 Compliance costs are $ 3% of revenue 5 Compliance Cost-to-Sales/Revenue Ratios Average 3.65 Median 1.68 Maximum 16.30 Minimum 0.02

Source: American Public Powe r Association (APPA). 2002. Straight Answers to False Charges about Public Power . Washington, DC: APPA. <http://www.appanet.org/about/publicpower/index.cfm>. As obtained on November 13, 2003.D-1 APPENDIX D: IMPACTS FROM APPLICATION OF RISK-BASED ALTERNATIVES
As an alternative to the requirement for each large solid fuel-fired boiler to demonstrate compliance with the HC1 emission limit in the final rule, the source may demonstrate compliance with a health-based facility-wide HC 1 equivalent allowable emission limit. The procedures for complying with this compliance a lternative are in Appendix A of the final rule. Also, in lieu of complying with the emission stan dard for what are called total selected metals (TSM) in subpart DDDDD of part 63 based on the sum of emissions for metals (such as arsenic, cadmium, chromium, mercury, manganese, nickel, a nd lead facilities may de monstrate eligibility for complying with the TSM standard base d on excluding manganese emissions from the summation of TSM emissions fo r the affected source unit.
The impacts discussed below reflect the e ffects of compliance with both risk-based alternatives to the final rule.
Per technical direction received February 5, 2004, RTI performed an economic and small entity sensitivity analysis of a modified emission control scen ario under the Industrial Boilers and Process Heaters MACT. The key elements of the sensitivity scenario are as follows:

 Exempt controls for HCL emissions for coal-fired units—(model plants 2d, 3e, 6d, and 7e).

 Exempt controls for manganese emissions for wood-fired units (model plants 30a, 30b, 34a, 34b, and 34d).

 Monitoring, record-keeping, a nd reporting costs for units lin ked to these model plants remain unchanged. This appendix highlights the ke y results of these analyses.

 Social Cost Estimates —The social cost estimates fall from $863 billion to $746 billion, or approximately 14 percent (see Ta ble D-1). The sensitivity analysis does not show significant changes in the distribu tion of these costs across sectors and stakeholders (see Table D-2).

 Market-Level Impacts —A comparison of the relative price and quantity changes shows the sensitivity scenario moderates price and quantity effects, but the differences are very small (see Table D-3).D-2 Table D-1. Social Cost Estimates ($1998 10 6 )

Change in Social Welfare

Baseline engineering costs $746.49 Social costs with mark et adjustments $746.44 Difference between engineering and social cost estimates $.04

 Energy Effects —Energy impacts are small in both an alyses. However, electricity and natural gas production/consumption impact s in the sensitiv ity scenario are approximately half the values projected under the MACT floor. Annual electricity production declines by 246 million kWh compared to 415 kWh. Natural gas production/consumption declines by 230,000 c ubic feet per day compared to 1.1 million cubic feet per day. Petroleum and coal sector effects do not significantly change.

 Small Entity Impacts —The average annual control costs fall from $199K to $142K under the sensitivity scenario (see Table D-4) . Similarly, the average (median) costto-sales ratio (CSR) falls from 0.78 per cent (0.50 percent) to 0.52 percent (0.16 percent) (see Table D-5). Twenty-two enti ties have CSRs greater than 1 percent under the sensitivity scenario compared with 34 entities under the MACT floor. Eight entities have CSRs that are 3 percent or higher compared to 10 entities under the MACT floor.

 Affected Government Entities: Supplemental Analysis —The average annual control costs fall from $223K to $217K under the se nsitivity scenario(see Table D-6). CSRs remain essentially unchanged (e.g., the aver age [median] CSR falls from 1.67 percent [0.94 percent] to 1.66 percent [0.94 percen t]). As a result, there is no change in projections of the number of government entitie s affected at the 1 or 3 percent level.D-3 Table D-2. Distribution of Social Costs by Sector/Market: ($1998 10 6 )

Change in:

Sectors/Markets Producer Surplus Consumer Surplus Social Welfare Energy Markets Petroleum –$2.4 Natural gas $0.9 Electricity –$32.3 Coal –$2.6 Subtotal –$36.3 NAICS Code SIC Code Description 311 20 (pt) Food –$21.4 –$8.6 –$30.0 312 20 (pt); 21 Beverage and Tob acco Products –$ 2.1 –$3. 7 –$5.8 313 22 (pt) Textile Mills –$20.8 –$47.6 –$68.4 314 22 (pt) Textile Product Mills –$0.1 –$0.1 –$0.2 315 23 Apparel –$0.3 –$0.8 –$1.2 316 31 Leather and Allied Products –$0.3 –$0.4 –$0.7 321 24 Wood Products –$25.2 –$6.7 –$31.9 322 26 Paper –$63.3 –$57.5 –$120.8 323 27 Printing and Related Support –$0.2 –$0.4 –$0.5 325 28 Chemicals –$35.5 –$71.0 –$106.5 326 30 Plastics and Rubber Products –$2.1 –$5.0 –$7.0 327 32 Nonmetallic Mineral Products –$2.6 –$3.1 –$5.7 331 33 Primary Metals –$21.6 –$4.9 –$26.6 332 34 Fabricated Metal Products –$6.3 –$1.7 –$8.0 333 35 Machinery –$6.3 –$4.2 –$10.5 334 36 (pt) Computer and Electronic Products –$3.2 –$1.3 –$4.5 335 36 (pt) Electrical Equipment, Appliances, and Components –$2.4 –$1.6 –$4.1
336 37 Transportation Equipment –$19.9 –$26.6 –$46.5 337 25 Furniture and Related Products –$3.3 –$14.8 –$18.1 339 39 Miscellaneous –$0.8 –$0.6 –$1.4 11 01-08 Agricultural Sector –$0.5 –$1.2 –$1.7 23 15-17 Construction Sector –$0.7 –$0.9 –$1.6 21 10; 14 Other Mining Sector –$9.9 –$6.9 –$16.8 48 40-47 (pt) Transportation –$3.5 –$3.2 –$6.7 42; 44-45; 49; 51-56;

61-62; 71-72; 81 40-48 (pt); 50-99 Commercial –$63.7 –$84.9 –$148.6

Residential NA –$36.3 –$36.3 Grand Total –$352.3 –$394.2 –$746.4 NA = Not applicable. pt = Part.D-4 Table D-3. Market-Level Impacts: Final Rule

Percent Change Sectors/Markets Price Quantity Energy Markets Petroleum 0.001% 0.000% Natural gas 0.002% 0.000% Electricity 0.044% –0.010% Coal –0.008% –0.010% NAICS Code SIC Code Description 311 20 (pt) Food 0.004% –0.001% 312 20 (pt); 21 Beverage and Tobacco Products 0.003% –0.004% 313 22 (pt) Textile Mills 0.023% –0.020% 314 22 (pt) Textile Product Mills 0.000% 0.000% 315 23 Apparel 0.000% –0.001% 316 31 Leather and Allied Products 0.002% –0.003% 321 24 Wood Products 0.026% –0.005% 322 26 Paper 0.025% –0.027% 323 27 Printing and Related Support 0.000% 0.000% 325 28 Chemicals 0.007% –0.011% 326 30 Plastics and Rubber Products 0.001% –0.002% 327 32 Nonmetallic Mineral Products 0.003% –0.002% 331 33 Primary Metals 0.009% –0.007% 332 34 Fabricated Metal Products 0.002% –0.000% 333 35 Machinery 0.002% –0.001% 334 36 (pt) Computer and Electronic Products 0.001% 0.000% 335 36 (pt) Electrical Equipment, Appliances, and Components 0.002% –0.001%
336 37 Transportation Equipment 0.003% –0.003% 337 25 Furniture and Related Products 0.005% –0.015% 339 39 Miscellaneous 0.001% 0.000% 11 01-08 Agricultural Sector 0.000% 0.000% 23 15-17 Construction Sector 0.000% 0.000% 21 10; 14 Other Mining Sector 0.012% –0.004% 48 40-47 (pt) Transportation 0.001% –0.001% 42; 44-45; 49; 51-56; 61- 62; 71-72; 81 40-48 (pt); 50-99 Commercial 0.000% 0.000%

pt = Part.D-5 Table D-4. Summary of Small Entity Impacts

Final Rule

Number of small entities 187 Total number of entities 576 Average annual control cost per small entity (10 3 ) $149 Average control cost/sales ratio 0.52% Number of small entities with cost-to-sales ratios $ 1 percent 23 Number of small entities with cost-to-sales ratios $ 3 percent 8

Table D-5. Summary Statistics fo r SBREFA Screening Analysis

Final Rule Total Number of Small Entities 187 Average Annual Compliance Cost per Small Entity ($10 3 ) $149 Entities with Sales/Revenue Data Compliance costs are <1% of sales 164 Compliance costs are $ 1 to 3% of sales 15 Compliance costs are $ 3% of sales 8 Compliance Cost-to-Sales/Revenue Ratios Average 0.52 Median 0.16 Maximum 7.83 Minimum 0.01D-6 Table D-6. Supplemental Screening Analysis fo r Small Governmental Jurisdictions

Final Rule Total Number of Small Entities 14 Average Total Annual Compliance Co st (TACC) per Small Entity ($10 3 ) $259 Entities with Sales/Revenue Data Compliance costs are <1% of revenue 7 Compliance costs are $ 1 to 3% of revenue 4 Compliance costs are $ 3% of revenue 3 Compliance Cost-to-Sales/Revenue Ratios Average 1.51 Median 0.90 Maximum 7.83 Minimum 0.02

Source: American Public Powe r Association (APPA). 2002. Straight Answers to False Charges about Public Power . Washington, DC: APPA. <http://www.appanet.org/about/publicpower/index.cfm>. As obtained on November 13, 2003.June 2007Office of Air Quality Planning and StandardsAir Quality Strategies and Standards DivisionResearch Triangle Park, NCUnited StatesEnvironmental ProtectionAgencyTECHNICAL REPORT DATA (Please read Instructions on reverse before completing) 1. REPORT NO. EPA-452/R-04-001 2. 3. RECIPIENT’S ACCESSION NO.

5. REPORT DATE June 2007 4. TITLE AND SUBTITLE Economic Impact Analysis of th e Industrial Boilers and Process Heaters NESHAP 6. PERFORMING ORGANIZATION CODE

7. AUTHOR(S)

Mike Gallaher, Alan O’Connor, Brooks Depro 8. PERFORMING ORGANIZATION REPORT NO. RTI Project Number 0209897-001- 029
10. PROGRAM ELEMENT NO. 9. PERFORMING ORGANIZATION NAME AND ADDRESS

RTI International Center for Regulatory Economics and Policy Research, Hobbs Bldg. Research Triangle Park, NC 27709 11. CONTRACT/GRANT NO. 68-D-99-024

13. TYPE OF REPORT AND PERIOD COVERED 12. SPONSORING AGENC Y NAME AND ADDRESS

Director Office of Air Quality Planning and Standards Office of Air and Radiation U.S. Environmental Protection Agency Research Triangle Park, NC 27711 14. SPONSORING AGENCY CODE EPA/200/04

15. SUPPLEMENTARY NOTES

16. ABSTRACT This report evaluates the economic impacts of the Industrial Boilers and Process Heaters NESHAP . The social costs of the rule are estimated by in corporating the expected costs of compliance in a partial equilibrium model and projecting the market imp acts. The report also provides the screening analysis for small business impacts.

17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b. IDENTIFIERS/OPEN ENDED TERMS c. COSATI Field/Group economic impacts small business impacts social costs Air Pollution Control Economic Impact Analysis Regulatory Flexibility Analysis

19. SECURITY CLASS (Report)

Unclassified 21. NO. OF PAGES 191 18. DISTRIBUTION STATEMENT

Release Unlimited 20. SECURITY CLASS (Page) Unclassified 22. PRICE

EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDIT ION IS OBSOLETE