United States Office Of Air Quality

Environmental Protection Planning And Standards September 2002

Agency Research Triangle Park, NC 27711 FINAL REPORT

Air

Economic Impact Analysis of 

Final Coke Ovens NESHAP

Final Report
EPA 452/R-02-008

September 2002

Economic Impact Analysis of 

the Final Coke Ovens NESHAP

By: 

Michael P. Gallaher

Brooks M. Depro

Center for Regulatory Economics and Policy Research

RTI

Research Triangle Park, NC 27709

Prepared for:

Tyler J. Fox

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Innovative Strategies and Economics Group

(MD-C339-01)

Research Triangle Park, NC 27711

EPA Contract No. 68-D-99-024

RTI Project No. 7647.003.274

Steve Page, Director

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Office of Air and Radiation

Research Triangle Park, NC 27711
This report has been reviewed by the Emission Standards Division of the Office of Air Quality Planning

and Standards of the United States Environmental Protection Agency and approved for publication.

Mention of trade names or commercial products is not intended to constitute endorsement or

recommendation for use. Copies of this report are available through the Library Services (MD-C267-01),

U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, or from the National Technical

Information Services 5285 Port Royal Road, Springfield, VA 22161.
iii

CONTENTS

Section Page

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.1 Agency Requirements for an EIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.2 Overview of Coke, Iron and Steel, and Foundry Industries . . . . . . . . . . 1-2

1.3 Summary of EIA Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-4

1.4 Organization of this Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-5

2 Industry Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.1 Production Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.1.1 By-Product Coke Production Process . . . . . . . . . . . . . . . . . . . . 2-2

2.1.2 Types of Coke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3

2.2 Industry Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

2.2.1 Manufacturing Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

2.2.2 Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11

2.2.3 Industry Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-13

2.2.4 Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-15

2.3 Market Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

3 Engineering Cost Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.1 Overview of Emissions from Coke Batteries . . . . . . . . . . . . . . . . . . . . . 3-1

3.2 Approach for Estimating Compliance Costs . . . . . . . . . . . . . . . . . . . . . 3-2
iv

CONTENTS (CONTINUED)

Section Page

3.3 Costs for MACT Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

3.3.1 Costs for the Baseline Program . . . . . . . . . . . . . . . . . . . . . . . . . 3-4

3.3.2 Major Repairs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4

3.3.3 Quenching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5

3.3.4 Monitoring Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5

3.3.5 Capital Recovery Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6

3.4 Estimates of Nationwide Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6

4 Economic Impact Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1 EIA Data Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1.1 Producer Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1.2 Market Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.1.3 Regulatory Control Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4

4.2 EIA Methodology Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

4.3 Economic Impact Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-8

4.3.1 Market-Level Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-9

4.3.2 Industry-Level Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-9

4.3.2.1 Changes in Profitability . . . . . . . . . . . . . . . . . . . . . . 4-12

4.3.2.2 Facility Closures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-15

4.3.2.3 Changes in Employment . . . . . . . . . . . . . . . . . . . . . . 4-15

4.3.3 Social Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-15

5 Small Business Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1 Identifying Small Businesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.2 Screening-Level Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

5.3 Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.4 Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4
v

CONTENTS (CONTINUED)

Section Page

Appendices

A Economic Impact Analysis Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1

B Development of Coke Battery Cost Functions . . . . . . . . . . . . . . . . . . . . . . . . . . B-1

C Economic Estimation of the Demand Elasticity for Steel Mill Products . . . . . . C-1

D Economic Estimation of the Demand Elasticity for Iron Castings . . . . . . . . . D-1

E Joint Economic Impact Analysis of the Integrated Iron and Steel

MACT Standard with the Coke MACT Standard . . . . . . . . . . . . . . . . . . . . . . . E-1

F Foreign Imports Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F-1
vi

LIST OF FIGURES

Number Page

1-1 Summary of Interactions Between Producers and Commodities in the

Iron and Steel Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

2-1 The By-Product Coke Production Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3

2-2 A Schematic of a By-Product Coke Battery . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

2-3 Distribution of U.S. Coke Production by Type: 2000 . . . . . . . . . . . . . . . . . . . . 2-5

2-4 Location of Coke Manufacturing Plants by Type of Producer: 1997 . . . . . . . . 2-9

2-5 Distribution of Affected U.S. Companies by Size: 2000 . . . . . . . . . . . . . . . . 2-13

2-6 Price Trends for Coke: 1992–2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-19

4-1 Market Linkages Modeled in the Economic Impact Analysis . . . . . . . . . . . . . . 4-3

4-2 Market Equilibrium without and with Regulation . . . . . . . . . . . . . . . . . . . . . . . 4-7
vii

LIST OF TABLES

Number Page

2-1 Air Emissions from U.S. Coke Manufacturing Plants by Emission Point . . . . . 2-4

2-2 Summary Data for Coke Manufacturing Plants: 1997 . . . . . . . . . . . . . . . . . . . 2-6

2-3 Coke Industry Summary Data by Type of Producer: 1997 . . . . . . . . . . . . . . . 2-10

2-4 Summary of Companies Owning Potentially Affected Coke

Manufacturing Plants: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12

2-5 U.S. Production, Foreign Trade, and Apparent Consumption of Coke: 

1980–1997 (103 short tons) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-17

2-6 Domestic Coke Production by Type: 1998-2000 . . . . . . . . . . . . . . . . . . . . . . 2-18

2-7 Foreign Trade Concentration for Coke Production . . . . . . . . . . . . . . . . . . . . . 2-18

3-1 Repair Categories and Assignment of Batteries . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3-2 Capital Recovery Factors (at 7 percent interest) . . . . . . . . . . . . . . . . . . . . . . . . 3-6

3-3 Capital Costs for Battery Repairs and Baseline Program ($1,000) . . . . . . . . . . 3-7

3-4 Total Annual Costs for Battery Repairs and Baseline Program ($1,000) . . . . . 3-8

3-5 Estimated Nationwide Compliance Costs for Coke Batteries Associated with the

MACT Floor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-9

4-1 Baseline Characterization of U.S. Iron and Steel Markets: 2000 . . . . . . . . . . . 4-5

4-2 Market-Level Impacts of the Final Coke MACT: 2000 . . . . . . . . . . . . . . . . . 4-10

4-3 National-Level Industry Impacts of the Final Coke MACT: 2000 . . . . . . . . . 4-11

4-4 Distribution Impacts of the Final Coke MACT Across Directly Affected

Producers: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14

4-5 Distribution of the Social Costs of the Final Coke MACT: 2000 . . . . . . . . . . 4-16

5-1 Summary Statistics for SBREFA Screening Analysis: 2000 . . . . . . . . . . . . . . 5-3

5-2 Small Business Impacts of the Final Coke MACT: 2000 . . . . . . . . . . . . . . . . . 5-5
1

In addition, Executive Order (EO) 12866 requires a more comprehensive analysis of benefits and costs for

proposed significant regulatory actions. 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. Other statutory and administrative requirements include

examination of the composition and distribution of benefits and costs. For example, the Regulatory

Flexibility Act (RFA), as amended by the Small Business Regulatory Enforcement and Fairness Act of 1996

(SBREFA), requires EPA to consider the economic impacts of regulatory actions on small entities. 

1-1

SECTION 1

INTRODUCTION

The U.S. Environmental Protection Agency (EPA) has developed a maximum

achievable control technology (MACT) standard to reduce hazardous air pollutants (HAPs)

from the coke ovens: pushing, quenching, and battery stacks source category. To support

this rulemaking, EPA’s Innovative Strategies and Economics Group (ISEG) has conducted

an economic impact analysis (EIA) to assess the potential costs of the rule. This report

documents the methods and results of this EIA. These final standards will implement

Section 112(d) of the Clean Air Act (CAA) by requiring all major sources to meet HAP

emission standards reflecting the application of the MACT. The HAPs emitted by this

source category include coke oven emissions, polycyclic organic matter, and volatile organic

compounds such as benzene and toluene.

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 the cost and economic impacts for

specific regulations and standards proposed under the authority of the Act.1

 ISEG’s

Economic Analysis Resource Document provides detailed guidelines and expectations for

economic analyses that support MACT rulemaking (EPA, 1999). In the case of the coke

MACT, these requirements are fulfilled by examining the following:

 facility-level impacts (e.g., changes in output rates, profitability, and facility

closures),
1-2

 market-level impacts (e.g., changes in market prices, domestic production, and

imports),

 industry-level impacts (e.g., changes in revenue, costs, and employment), and

 societal-level impacts (e.g., estimates of the consumer burden as a result of higher

prices and reduced consumption levels and changes in domestic and foreign

profitability).

1.2 Overview of Coke, Iron and Steel, and Foundry Industries

In the United States, furnace and foundry coke are produced by two producing

sectors—integrated producers and merchant producers. Integrated producers are part of

integrated iron and steel mills and primarily produce furnace coke for captive use in blast

furnaces. In 2000, integrated producers accounted for approximately three-fourths of U.S.

coke capacity, and merchant producers accounted for the remaining one-fourth. Merchant

producers sell furnace and foundry coke on the open market to integrated steel producers

(i.e., furnace coke) and iron foundries (i.e., foundry coke). Some merchant producers sell

both furnace and foundry coke, while others specialize in only one. 

Figure 1-1 summarizes the interactions between source categories and markets within

the broader iron and steel industry. As shown, captive coke plants are colocated at integrated

iron and steel mills providing furnace coke for its blast furnaces, while merchant coke plants

supply the remaining demand for furnace coke at integrated iron and steel mills and supply

the entire demand for foundry coke at iron foundries. These integrated mills compete with

nonintegrated mills (i.e., minimills) and foreign imports in the markets for these steel

products typically consumed by the automotive, construction, and other durable goods

producers. Alternatively, iron foundries use foundry coke, pig iron, and scrap in their

ironmaking furnaces (cupolas) to produce iron castings, and steel foundries use pig iron and

scrap in their steelmaking furnaces (electric arc and electric induction) to produce steel

castings. The markets for iron and steel castings are distinct with different product

characteristics and end users.

The EIA models the specific links between these models. The analysis to support the

coke EIA focuses on four specific markets:

 furnace coke,

 foundry coke, 
1-3

Foreign

(Exports) and

Other

Industries

Ironmaking

Furnaces

Nonintegrated Steel

Mills (including

minimills) Finishing Mills Foreign (Imports)

Blast Furnace

Merchant

Coke Plants

Foreign

(Imports)

Foreign

(Imports)

Steelmaking

Furnace

Furnace

Coke

Pig Iron

Scrap

Foundry Coke

Other Coke

Molten

Steel

Markets for Finished Steel Products

Furnace

Coke

Markets for

Iron Castings Markets for Steel Castings

Steelmaking

Furnaces

Integrated Iron and

Steel Mills

Scrap

Steel Castings Iron

Castings

Iron

Foundries

Steel

Foundries

Finished Steel Products

Furnace, Foundry, and Other

Coke Markets

Scrap

Captive

Coke Plants

Figure 1-1. Summary of Interactions Between Producers and Commodities in the

Iron and Steel Industry
2

All costs were adjusted to $2000 dollars (base year of the economic analysis). 

1-4

 steel mill products, and

 iron castings.

Changes in price and quantity in these markets are used to estimate the facility, market,

industry, and social impacts of the coke regulation.

1.3 Summary of EIA Results

The rule requires coke manufacturers to implement good management practices and

ongoing maintenance that will increase the costs of producing furnace and foundry coke at

affected facilities. The increased production costs will lead to economic impacts in the form

of increases in market prices and decreases in domestic furnace coke production. The

impacts of these price increases will be borne by integrated producers of steel mill products

as well as consumers of steel mill products. Nonintegrated steel mills and foreign producers

of furnace coke will earn higher profits. Key results of the EIA for the coke MACT are as

follows:

 Engineering Costs: The engineering analysis estimates annual costs for existing

sources of $20.2 million.2

 Sales Test: A simple “sales test,” in which the annualized compliance costs are

computed as a share of sales for affected companies that own coke batteries,

shows that thirteen of the fourteen companies are affected by less than 3 percent

of sales. The cost-to-sales ratio (CSR) for the median company is 0.13 percent.

 Price and Quantity Impacts: The EIA model predicts the following:

— The market price for furnace coke is projected to increase by 2.7 percent

($3.00/short ton), and domestic furnace coke production is projected to

decrease by 3.9 percent (348,000 tons/year). 

— The market price and domestic foundry coke production for foundry coke are

projected to remain unchanged. 

— The market price for steel mill products is projected to increase by 0.03

percent ($0.14/short ton), and domestic production of steel mill products is

projected to decrease by 0.18 percent (192,000 tons/year). 

— The market price and production for iron castings are projected to remain

unchanged.
1-5

 Plant Closures: Two furnace coke batteries are projected to close.

 Small Businesses: The Agency identified three small companies that own and

operate coke batteries, or 21 percent of the total. The average CSR for these

firms is 2.0 percent. One small business is projected to have a CSR between 1

and 3 percent. One small business is projected to have a CSR greater than

3 percent. No facilities or batteries owned by a small business are projected to

close as a result of the regulation.

 Social Costs: The annual social costs are projected to be $18.6 million.

— The consumer burden as a result of higher prices and reduced consumption

levels is $20.9 million annually.

— The aggregate producer profit gain is expected to increase by $2.3 million. 

 The profit losses are $10.3 million annually for domestic producers. 

 Foreign producer profits increase by $12.6 million due to higher prices

and level of impacts. 

1.4 Organization of this Report

The remainder of this report supports and details the methodology and the results of

the EIA of the coke MACT.

 Section 2 presents a profile of the coke industry.

 Section 3 describes the regulatory controls and presents engineering cost

estimates for the regulation.

 Section 4 reports market-, industry-, and societal-level impacts.

 Section 5 contains the small business screening analysis. 

 Appendix A describes the EIA methodology. 

 Appendix B describes the development of the coke battery cost functions.

 Appendixes C and D include the econometric estimation of the demand elasticity

for steel mill products and iron castings.

 Appendix E reports the results of the joint economic impacts of the Iron and Steel

and Coke MACTs.

 Appendix F reports the results of foreign coke import elasticity sensitivity

analysis. 
2-1

SECTION 2

INDUSTRY PROFILE

Coke is metallurgical coal that has been baked into a charcoal-like substance that

burns more evenly and has more structural strength than coal. Coke manufacture is included

under Standard Industrial Classification (SIC) code 3312—Blast Furnaces and Steel Mills;

however, coke production is a small fraction of this industry. In 2000, the U.S. produced

20.8 million short tons of coke. Coke is primarily used as an input for producing steel in

blast furnaces at integrated iron and steel mills (i.e., furnace coke) and as an input for gray,

ductile, and malleable iron castings in cupolas at iron foundries (i.e., foundry coke). 

Therefore, the demand for coke is a derived demand that is largely dependent on production

of steel from blast furnaces and iron castings.

In the remainder of this section, we provide a summary profile of the coke industry in

the United States, including the technical and economic aspects of the industry that must be

addressed in the economic impact analysis. Section 2.1 provides an overview of the

production processes and the resulting types of coke. Section 2.2 summarizes the

organization of the U.S. coke industry, including a description of U.S. manufacturing plants

and batteries, the companies that own these plants, and the markets for coke products. 

Finally, Section 2.3 presents historical data on the coke industry, including U.S. production

and consumption and foreign trade.

2.1 Production Overview

This section provides an overview of the by-product coke manufacturing process and

types of coke produced in the United States. Although not discussed in this section, several

substitute technologies for by-product cokemaking have been developed in the United States

and abroad, including nonrecovery cokemaking, formcoke, and jumbo coking ovens. Of

these alternatives to by-product coke batteries, the nonrecovery method is the only substitute

in terms of current market share in the United States.
2-2

2.1.1 By-Product Coke Production Process

Cokemaking involves heating coal in the absence of air resulting in the separation of

the non-carbon elements of the coal from the product (i.e., coke). The process essentially

bakes the coal into a charcoal-like substance for use as fuel in blast furnaces at integrated

iron and steel mills and cupolas at iron foundries. Figure 2-1 summarizes the multi-step

production process for by-product cokemaking, which includes the following steps:

 coal preparation and charging,

 coking and pushing,

 quenching, and

 by-product recovery.

In by-product cokemaking, coal is converted to coke in long, narrow by-product coke ovens

that are constructed in groups with common side walls, called batteries (typically consisting

of 10 to 100 coke ovens). 

Figure 2-2 provides a schematic of a by-product coke battery. Metallurgical coal is

pulverized and fed into the oven (or charged) through ports at the top of the oven, which are

then covered with lids. The coal undergoes destructive distillation in the oven at 1,650°F to

2,000°F for 15 to 30 hours. A slight positive back-pressure maintained on the oven prevents

air from entering the oven during the coking process. After coking, the incandescent or

“hot” coke is then pushed from the coke oven into a special railroad car and transported to a

quench tower at the end of the battery where it is cooled with water and screened to a

uniform size. During this process, raw coke oven gas is removed through an offtake system,

by-products such as benzene, toluene, and xylene are recovered, and the cleaned gas is used

to underfire the coke ovens and for fuel elsewhere in the plant. 

As shown in Table 2-1, pollutants may be emitted into the atmosphere from several

sources during by-product cokemaking. For the final MACT standards, the sources of

environmental concern to EPA are the pushing of coke from the ovens, the quenching of 

incandescent coke, and battery stacks. Coke pushing results in fugitive particulate emissions,

which may include volatile organic compounds (VOCs), while coke quenching results in

particulate emissions with traces of organic compounds. EPA will focus on these three areas

of emissions as HAP-emitting source categories to be regulated. 
2-3

Other

By-Products

To Blast Furnace or

Foundry Cupola

By-Product

Recovery Quenching

Coking and Pushing

Coal Preparation

and Charging

Metallurgical Coal

Recycled

Coke

Oven Gas

By-Products

All Other Inputs

“Hot” Coke

Coke

All Other Inputs

Figure 2-1. The By-Product Coke Production Process

2.1.2 Types of Coke

The particular mix of high- and low-volatile coals used and the length of time the

coal is heated (i.e., coking time) determine the type of coke produced: (1) furnace coke,

which is used in blast furnaces as part of the traditional steelmaking process, or (2) foundry

coke, which is used in the cupolas of foundries in making gray, ductile, or malleable iron

castings. Furnace coke is produced by baking a coal mix of 10 to 30 percent low-volatile

coal for 16 to 18 hours at oven temperatures of 2,200°F. Most blast furnace operators prefer

coke sized between 0.75 inches and 3 inches. Alternatively, foundry coke is produced by

baking a mix of 50 percent or more low-volatile coal for 27 to 30 hours at oven temperatures

of 1,800°F. Coke size requirements in foundry cupolas are a function of the cupola diameter

(usually based on a 10:1 ratio of cupola diameter to coke size) with foundry coke ranging in 
2-4

Figure 2-2. A Schematic of a By-Product Coke Battery

Source: U.S. International Trade Commission. 1994. Metallurgical Coke: Baseline Analysis of the U.S.

Industry and Imports. Publication No. 2745. Washington, DC: U.S. International Trade Commission.

Table 2-1. Air Emissions from U.S. Coke Manufacturing Plants by Emission Point

Emission Point Example Pollutants

Oven charging and leaks from doors, lids, and

offtakesa

Polycyclic organic matter (e.g., benzo(a)pyrene and

many others), volatile organic compounds (e.g.,

benzene, toluene), and particulate matter

Coke pushing, coke quenching, and battery stacks

(oven underfiring)b

By-product recovery plantc Benzene, toluene, zylene, napthalene, and other

volatile organic compounds

a

 A NESHAP was promulgated for these emission points in 1993—see 40 CFR Part 63, Subpart L.

b

 The final MACT standard evaluated in this economic analysis will address hazardous pollutants from these

emission points and is scheduled for promulgation in 2001 in 40 CFR Part 63, Subpart CCCCC.

c

 A NESHAP for the by-product recovery plant was promulgated in 1989 in 40 CFR Part 61, Subpart L.
2-5

U.S. Coke Production

20.8 million short tons

Furnace Coke

85%

Foundry Coke

6%

Industrial Coke and

Coke Breeze

9%

Figure 2-3. Distribution of U.S. Coke Production by Type: 2000

size from 4 inches to 9 inches (Lankford et al., 1985). Because the longer coking times and

lower temperatures required for foundry coke are more favorable for long-term production,

foundry coke batteries typically remain in acceptable working condition longer than furnace

coke batteries (Hogan and Koelble, 1996). 

As shown in Figure 2-3, furnace coke accounts for the vast majority of coke produced

in the United States. In 2000, furnace coke production was roughly 17.7 million short tons,

or 85 percent of total U.S. coke production, while foundry coke production was only

1.3 million short tons. Integrated iron and steel producers that use furnace coke in their blast

furnaces may either produce this coke on-site (i.e., captive coke producers) or purchase it on

the market from merchant coke producers. As shown in Table 2-2, almost 76 percent of U.S.

furnace coke capacity in 1997 was from captive operations at integrated steel producers. 

Alternatively, there are no captive coke operations at U.S. iron foundries so these producers

purchase all foundry coke on the market from merchant coke producers. In summary,

captive coke production occurs at large integrated iron and steel mills and accounts for the

vast majority of domestic furnace coke production, while merchant coke production occurs at

smaller merchant plants and accounts for a small share of furnace coke production and all of

the foundry coke produced in the United States.
2-6

Table 2-2. Summary Data for Coke Manufacturing Plants: 1997

Plant Name Location

Number

of

Batteries

Number

of Coke

Ovens

Total Coke

Capacity

(short

tons/yr)

Coke Production by Type (short tons/yr)

Furnace Foundry Other Total

Integrated Producers

Acme Steela Chicago, IL 2 100 500,000 493,552 0 19,988 513,538

AK Steel Ashland, KY 2 146 1,000,000 942,986 0 0 942,986AK Steel Middletown, OH 1 76 429,901 410,000 0 0 410,000Bethlehem Steel Burns Harbor, IN 2 164 1,877,000 1,672,701 0 82,848 1,755,549Bethlehem Steela Lackawanna, NY 2 152 750,000 747,686 0 0 747,686Geneva Steela Provo, UT 4 252 800,000 700,002 0 16,320 716,322Gulf States Steela Gadsden, AL 2 130 500,000 521,000 0 0 521,000LTV Steela Chicago, IL 1 60 615,000 590,250 0 0 590,250LTV Steel Warren, OH 1 85 549,000 543,156 0 0 543,156National Steel Ecorse, MI 1 85 924,839 908,733 0 0 908,733National Steel Granite City, IL 2 90 601,862 570,654 0 0 570,654U.S. Steel Clairton, PA 12 816 5,573,185 4,854,111 0 0 4,854,111U.S. Steel Gary, IN 4 268 2,249,860 1,813,483 0 0 1,813,483WheelingPittsburgh Follansbee, WV 4 224 1,247,000 1,249,501 0 36,247 1,285,748Total, Integrated Producers 40 2,648 17,617,647 16,017,815 0 155,403 16,173,216

(continued)
2-7

Table 2-2. Summary Data for Coke Manufacturing Plants: 1997 (Continued)

Plant Name Location

Number

of

Batteries

Number

of Coke

Ovens

Total Coke

Capacity

(short

tons/yr)

Coke Production by Type (short tons/yr)

Furnace Foundry Other Total

Merchant Producers

ABC Coke Tarrant, AL 3 132 699,967 25,806 727,720 0 753,526Citizens Gas Indianapolis, IN 3 160 634,931 173,470 367,798 93,936 635,204Empire Coke Holt, AL 2 60 162,039 0 142,872 0 142,872Erie Coke Erie, PA 2 58 214,951 0 122,139 19,013 141,152Indiana Harbor Cokeb,c East Chicago, IN 4 268 1,300,000 0 0 0 0

Jewell Coke and Coalb Vansant, VA 4 142 649,000 649,000 0 0 649,000

Koppers Monessen, PA 2 56 372,581 358,105 0 0 358,105New Boston Cokea Portsmouth, OH 1 70 346,126 317,777 0 4,692 322,469

Shenango, Inc. Pittsburgh, PA 1 56 514,779 354,137 0 0 354,137Sloss Industries Birmingham, AL 3 120 451,948 268,304 131,270 33,500 433,074Tonawanda Buffalo, NY 1 60 268,964 0 136,225 63,822 200,047Total, Merchant Producers 26 1,182 5,615,286 2,146,599 1,628,024 214,963 3,989,586

Total, All Producers 66 3,830 23,232,933 18,164,414 1,628,024 370,366 20,162,802

a Closed since 1997. b Operates nonrecovery coke batteries not subject to the regulations.c Newly built coke operations coming on-line during 1998.

Sources: U.S. Environmental Protection Agency. 1998. Coke Industry Responses to Information Collection Request (ICR) Survey. Database

prepared for EPA’s Office of Air Quality Planning and Standards. Research Triangle Park, NC.Association of Iron and Steel Engineers (AISE). 1998. “1998 Directory of Iron and Steel Plants: Volume 1 Plants and Facilities.” 

Pittsburgh, PA: AISE.
2-8

Co-products of the by-product coke production process are (1) coke breeze, the fine

screenings that result from the crushing of coke; and (2) “other coke,” the coke that does not

meet size requirements of steel producers that is sold as a fuel source to non-steel producers. 

In addition, the by-product cokemaking process results in the recovery of some salable crude

materials such as coke oven gas, ammonia liquor, tar, and light oil. The cleaned coke oven

gas is used to underfire the coke ovens with excess gas used as fuel in other parts of the plant

or sold. The remaining crude by-products may be further processed and separated into

secondary products such as anhydrous ammonia, phenol, ortho cresol, and toluene. In the

past, coke plants were a major source of these products (sometimes referred to as coal

chemicals); however, today their output is overshadowed by chemicals produced from

petroleum manufacturing (DOE, 1996). 

2.2 Industry Organization

In order to inform the economic impact analysis, we provide an overview of the U.S.

coke industry based on survey data collected by the Agency for 1997. Note, however, six

coke plants have closed since the survey was completed (see Table 2-2). We also have

provided selected updated information that reflects current trends in the industry (i.e.,

company and market data). 

2.2.1 Manufacturing Plants

Figure 2-4 identifies the location of U.S. coke manufacturing plants by type of

producer (i.e., integrated and merchant). As of 1997 (see Table 2-2), there were

14 integrated plants operating 40 coke batteries with 2,648 coke ovens. Total coke capacity

at these plants was 17.6 million short tons with production devoted entirely to furnace coke. 

Large integrated steel companies owned and operated these plants and accounted for

80 percent of total U.S. coke production in 1997 (all furnace coke). U.S. Steel was the

largest integrated producer, operating two coke manufacturing plants in Clairton,

Pennsylvania and Gary, Indiana. The Clairton facility was the largest single coke plant in the

United States, accounting for roughly 24 percent of U.S. cokemaking capacity. Together, the

two U.S. Steel plants accounted for roughly 40 percent of all coke batteries and ovens at

integrated plants. As shown in Table 2-3, integrated coke plants had an average of 2.9 coke

batteries, 189 coke ovens, and coke capacity of 1.26 million short tons per plant. These

plants produced an average of 1.14 million short tons of furnace coke and accounted for 88

percent of the 18.2 million short tons of furnace coke produced in 1997. 
2-9

Figure 2-4. Location of Coke Manufacturing Plants by Type of Producer: 1997

Source: U.S. Environmental Protection Agency. 1998. Coke Industry Responses to Information Collection

Request (ICR) Survey. Database prepared for EPA’s Office of Air Quality Planning and Standards. 

Research Triangle Park, NC.

As of 1997, there were 11 merchant plants operating 26 coke batteries with

1,182 coke ovens. Total coke capacity at these plants was 5.6 million short tons with

production split between furnace and foundry coke. Merchant coke plants are typically

owned by smaller, independent companies that rely solely on the sale of coke and coke byproducts to generate revenue. These plants accounted for 20 percent of total U.S. coke

production in 1997. Sun Coal and Coke is the largest merchant furnace producer, operating

Jewell Coke and Coal in Vansant, Virginia and newly constructed operations at Indiana

Harbor Coke in East Chicago, Illinois (both plants employ the nonrecovery cokemaking

processes). Although listed as a merchant producer, the Indiana Harbor Coke plant is colocated with Inland Steel’s integrated plant in East Chicago, Illinois and has an agreement to 
2-10

Table 2-3. Coke Industry Summary Data by Type of Producer: 1997

Item

Integrated Producers Merchant Producers

Total Total Share Total Share

Coke Plants (#) 14 56.0% 11 44.0% 25 

Coke Batteries (#)

Total number 40 60.6% 26 39.4% 66 

Average per plant 2.86 2.36 2.64

Coke Ovens (#)

Total number 2,648 69.1% 1,182 30.9% 3,830 

Average per plant 189.1 107.5 153.2 

Coke Capacity (short tons/yr)

Total capacity 17,617,647 75.8% 5,615,286 24.2% 23,232,933 

Average per plant 1,258,403 510,481 929,317 

Coke Production (short

tons/yr)

Total production

 Furnace 16,017,815 88.2% 2,146,599 11.8% 18,164,414 

Foundry 0 0.0% 1,628,024 100.0% 1,628,024 

Other 155,403 42.0% 214,963 58.0% 370,366 

Total 16,173,218 80.2% 3,989,586 19.8% 20,162,804 

Average per Plant

Furnace 1,144,130 195,145 726,577 

Foundry 0 148,002 65,121 

Other 11,100 19,542 14,815 

Total 1,155,230 362,690 806,512 

Sources: U.S. Environmental Protection Agency. 1998. Coke Industry Responses to Information Collection

Request (ICR) Survey. Database prepared for EPA’s Office of Air Quality Planning and Standards. 

Research Triangle Park, NC.

Association of Iron and Steel Engineers (AISE). 1998. “1998 Directory of Iron and Steel Plants:

Volume 1 Plants and Facilities.” Pittsburgh, PA: AISE.
2-11

supply 1.2 million short tons of coke to Inland and sell the residual furnace coke production

(Ninneman, 1997). As shown in Table 2-3, merchant coke plants are smaller than integrated

plants with an average of 2.4 coke batteries, 108 coke ovens, and coke capacity of only

0.5 million short tons per plant. In 1997, these plants produced an average of 195,000 short

tons of furnace coke and 148,000 short tons of foundry coke per plant, accounting for

12 percent of U.S. furnace coke and 100 percent of foundry coke produced.

2.2.2 Companies

The final MACT will potentially affect business entities that own coke manufacturing

facilities. Facilities comprise a land site with plant and equipment that combine inputs (raw

materials, energy, labor) to produce outputs (coke). Companies that own these facilities are

legal business entities that have capacity to conduct business transactions and make business

decisions that affect the facility. The terms facility, establishment, plant, and mill are

synonymous in this analysis and refer to the physical location where products are

manufactured. Likewise, the terms company and firm are synonymous and refer to the legal

business entity that owns one or more facilities.

As shown in Table 2-4, 14 companies currently operate U.S. coke manufacturing

coke batteries. These companies ranged from small, single-facility merchant coke producers

to large integrated steel producers. As shown, integrated producers are large, publicly owned

integrated steel companies such as USX Corporation and Bethlehem Steel Corporation. 

Alternatively, merchant producers are smaller, typically privately owned and operated

companies including Koppers Industries, Drummond Company (which owns ABC Coke),

McWane Incorporated (which owns Empire Coke), and Citizens Gas and Coke. These

potentially affected parent companies range in size from 200 to over 50,000 employees. 

Companies are grouped into small and large categories using Small Business

Administration (SBA) general size standard definitions for North American Industry

Classification System (NAICS) codes. Under these guidelines, SBA establishes 1,000 or

fewer employees as the small business threshold for Iron and Steel Mills (i.e., NAICS

331111), while coke ovens not integrated with steel mills are classified under All Other

Petroleum and Coal Products Manufacturing (i.e., NAICS 324199) with a threshold of 500. 

Figure 2-5 illustrates the distribution of affected U.S. companies by size based on reported

employment data. As shown, three companies (all merchant producers), or 21 percent, are

categorized as small, and 11 companies, or 79 percent, are categorized as large. As expected,

the companies owning integrated coke plants are generally larger than the companies owning 
2-12

Table 2-4. Summary of Companies Owning Potentially Affected Coke

Manufacturing Plants: 2000

Company Name

Legal Form of

Organization

Producer

Type

Total Sales

($106)

Total

Employment

Small

Business

Bethlehem Steel Corporation Public Integrated 4,197 14,700 No

Citizens Gas and Coke Private Merchant 339 1,000 Yes

Drummond Company Inc.a Private Merchant 615 2,800 No

International Steel Groupb NA Integrated 4,934 16,500 No

Koppers Industries Inc. Private Merchant 724 2,085 No

McWane Inc.c Private Merchant 755 5,170 No

NKK Corporation NA Foreign Integrated 14,148 39,875 No

Shenango Groupd Holding company Merchant 49 200 Yes

Sunacoe Public Merchant 12,426 14,200 No

Tonawanda Coke

Corporationf

NA Merchant 47 260 Yes

USX Corporation Public Integrated 39,914 49,679 No

Walter Industries Inc.g Public Merchant 1,185 6,535 No

WHX Corporationh Public Integrated 1,745 6,991 No

a Owns ABC Coke.

b Owns LTV Corporation. Data presented is for LTV Corporation. 

c Owns Empire Coke.

d Owns Shenango Inc.

e Owns Indiana Harbor Coke Company and Jewell Coke and Coal Company, which are not subject to final

regulations.

f Owns Erie Coke Corporation.

g Owns Sloss Industries Corporation.

h Owns Wheeling-Pittsburgh Corporation.

Source: Hoover’s Online and selected 10-K and Annual Reports. 

merchant coke plants. None of the nine companies owning integrated operations have fewer

than 1,000 employees or are classified as small businesses. Alternatively, three of the

companies owning merchant operations have fewer than 1,000 employees and are classified

as small businesses. However, not all companies owning merchant coke plants are small; for

example, the Sun Company is one of the largest companies with over 10,000 employees.
2-13

Large

79%

Small

21%

Figure 2-5. Distribution of Affected U.S. Companies by Size: 2000

2.2.3 Industry Trends

During the 1970s and 1980s, integrated steelmakers shut down blast furnaces in

response to reduced demand for steel, thereby reducing the demand for furnace coke. During

the same period, many coke batteries were also shut down, thereby reducing the supply of

coke. During the 1990s, the improved U.S. economy has produced strong demand for steel,

and domestic coke consumption currently exceeds production. This deficit may increase

because many domestic furnace coke batteries are approaching their life expectancies and

may be shut down rather than rebuilt. However, no new coke batteries have been built and

only two coke oven batteries have been rebuilt since 1990—National Steel in Ecorse,

Michigan and Bethlehem Steel in Burns Harbor, Indiana (Agarwal et al., 1996). Most recent

investments in new cokemaking have been made in non-recovery, rather than by-product

recovery, coke batteries. In fact, LTV Steel Corporation and the U.S. Steelworkers Union

are reportedly exploring the possibility of locating a non-recovery coke facility on the site of

LTV’s current coke plant in Pittsburgh (American Metal Market, 1998). LTV closed this

coke plant at the end of 1997 because its operating and environmental performance

deteriorated to the point that it was unable to meet CAA requirements without prohibitive

investments of between $400 and $500 million (New Steel, 1997a).
2-14

Faced with the prospect of spending hundreds of millions of dollars to rebuild aging

coke batteries, many integrated steelmakers have totally abandoned their captive cokemaking

operations and now rely on outside suppliers. As of 1997, five integrated steel companies 

did not produce their own coke and had to purchase this input from merchant plants, foreign

sources, or other integrated producers with coke surpluses. These integrated steel

companies—Inland Steel, Rouge Steel, USS/Kobe Steel, WCI Steel, and Weirton Steel—had

an estimated aggregate coke demand of 5.8 million short tons (Hogan and Koelble, 1996). In

addition, four other integrated producers currently have coke deficits. However, there are

few integrated producers with coke surpluses to take up the slack. Hogan and Koelble

(1996) reported that only four integrated steelmakers had coke surpluses as of 1995. This

number is now down to three with the March 1998 closing of Bethlehem Steel’s coke

operations in Bethlehem, Pennsylvania (New Steel, 1998b). These recent closures by LTV

and Bethlehem removed 2.4 million short tons, or 10.5 percent, of U.S. coke capacity (New

Steel, 1998b).

Furthermore, several integrated firms have sold some or all of their coke batteries to

merchant companies, which then sell the majority of the coke they produce to the steel

company at which the battery is located. Some of these are existing coke batteries, and

others are newly rebuilt batteries, including some that use the non-recovery cokemaking

process. An example is the Indiana Harbor Coke Company’s coke batteries located at Inland

Steel’s Indiana Harbor Works in East Chicago, Indiana. Both National Steel and Bethlehem

Steel have recently sold coke batteries to DTE Energy Company (New Steel, 1998a; New

Steel, 1997b). Both steel companies will continue to operate the batteries and will buy the

majority of the coke produced by the batteries from DTE at market value (National Steel,

1998). 

These recent trends should have the following future impacts on the U.S. coke

industry:

 Reduce the share of furnace coke produced by integrated producers, thereby

increasing reliance on merchant producers and foreign sources.

 Increase the furnace coke share of merchant production as these producers

respond to expected increases in market prices for furnace coke, which also has

lower production cost than foundry coke. 

 Increase the volume of foreign imports of furnace and foundry coke as domestic

demand continues to exceed domestic supply.
2-15

In 2000 and 2001, representatives from the coke industry (furnace and foundry) filed

separate petitions alleging that the industry was materially injured or threatened with

material injury from imports being sold at less than fair value (LTFV). After Commission

investigations, the U.S. International Trade Commission found “no reasonable” indication

the blast furnace coke industry was materially injured from these imports. In contrast, the

Commission did find that foundry coke was sold in the United States at LTFV. As a result,

the Secretary of Commerce issued an antidumping duty order on September 17, 2001 which

assessed antidumping duties on foundry coke from China.

2.2.4 Markets

The U.S. coke industry has two primary product markets (i.e., furnace and foundry

coke) that are supplied by two producing sectors—integrated producers and merchant

producers. Integrated producers are part of integrated iron and steel mills and only produce

furnace coke for captive use in blast furnaces. Therefore, much of the furnace coke is

produced and consumed by the same integrated producer and never passes through a market. 

However, some integrated steel producers have closed their coke batteries over the past

decade and must purchase their coke supply from merchant producers or foreign sources. In

addition, a small number of integrated steelmakers produce more furnace coke than they

need and sell their surplus to other integrated steelmakers. As of 1997, integrated producers

accounted for roughly 76 percent of U.S. coke capacity with merchant producers accounting

for the remaining 23 percent. These merchant producers sell furnace and foundry coke on

the open market to integrated steel producers (i.e., furnace coke) and iron foundries (i.e.,

foundry coke). Some merchant producers sell both furnace and foundry coke, while others

specialize in only one.

Although captive consumption currently dominates the U.S. furnace coke market,

open market sales of furnace coke are increasing (USITC, 1994). Because of higher

production costs, U.S. integrated steel producers have been increasing their consumption of

furnace coke from merchant coke producers, foreign imports, and other integrated steel

producers with coke surpluses. Although concentration ratios indicate that the U.S. furnace

market is slightly concentrated, it is expected to be competitive at the national level after

factoring in competition from foreign imports and integrated producers with coke surpluses.

Merchant coke producers account for a small share of U.S. furnace coke production

(about 12 percent in 1997); however, they account for 100 percent of U.S. foundry coke

production. The U.S. foundry market appears to be fairly concentrated with two companies

currently accounting for almost 68 percent of U.S. production—Drummond Company
2-16

Incorporated with 45 percent and Citizens Gas and Coke with 22.6 percent. The remaining

four merchant producers each account for between 7.5 and 8.8 percent of the market. 

However, these producers do not produce a differentiated product and are limited to selling

only to iron foundries, and these factors limit their ability to influence prices. In addition, the

strategic location of these manufacturers would appear to promote competition within the

southeastern and north-central United States and, perhaps, across regions given access to

water transportation. Thus, the U.S. market for foundry coke is also expected to be

competitive at the national level.

2.3 Market Data

The average annual production growth rate for furnace and foundry coke declined

approximately 2.6 percent for the period 1990 and 2001 (see Table 2-5). Production fell

significantly between 2000 and 2001 (9.0 percent) as a result of declining economic

conditions in the United States and high volumes of Chinese imports. In 2000, 17.7 million

short tons of furnace coke and 1.3 million short tons of foundry coke were produced

domestically (see Table 2-6). 

Apparent consumption of coke declined by almost 2 percent between 1990 and 2001,

while levels have fluctuated in recent years. In 2001, coke consumption fell to its lowest

level in over 2 decades. This follows trends in the integrated iron and steel sector, the

primary consumer of domestic coke. The steel industry has faced strong import competition

and declining national economic conditions during this period. 

Export ratios indicate that 5.5 percent of domestic production was sold overseas in

2000 (see Table 2-7). This ratio has more than doubled over the past 10 years, from an

initial level of 2.1 percent in 1990. The imports have also grown throughout the decade, and

comprised over 16 percent of U.S. consumption in 2000. China and Japan are particularly

strong suppliers to U.S. markets. 

The average price per ton for coke has fluctuated moderately during the past decade. 

Price volatility was greatest during the latter part of the 1990s, with 1999–2000 exhibiting

the largest variation in prices, a drop of nearly 8 percent (see Figure 2-6). From the fourth

quarter of 1999 to the second quarter of 2001, the price of furnace coke fluctuated modestly

between $109 and $112 per short ton (USITC, 2001c). Between the third quarter of 1998

and the first quarter of 2000, foundry coke prices declined steadily, falling from $165 to 

$161 per short ton (USITC, 2001b). Substantially lower import prices on coke put

downward pressure on domestic prices throughout this period, according to the ITC. 
2-17

Table 2-5. U.S. Production, Foreign Trade, and Apparent Consumption of Coke: 

1980-1997 (103

 short tons)

Year

U.S.

Production Exports Imports

Changes in

Inventories

Apparent

Consumptiona

1980 46,132 2,071 659 3,442 41,278

1981 42,786 1,170 527 –1,903 44,046

1982 28,115 993 120 1,466 25,776

1983 25,808 665 35 –4,672 29,850

1984 30,561 1,045 582 198 29,900

1985 28,651 1,122 578 –1,163 29,270

1986 25,540 1,004 329 –487 25,352

1987 26,304 574 922 –1,012 27,664

1988 28,945 1,093 2,688 529 30,011

1989 28,045 1,085 2,311 336 28,935

1990 27,617 572 1,078 –1 28,124

1991 24,046 740 1,185 189 24,302

1992 23,410 642 2,098 –224 25,090

1993 23,182 835 2,155 –422 24,924

1994 22,686 660 3,338 –525 25,889

1995 23,749 750 3,820 366 26,453

1996 23,075 1,121 2,543 21 24,476

1997 22,115 832 3,185 3 24,465

1998 20,041 1129 3,834 –361 23,107

1999 20,016 898 3,224 –81 22,423

2000 20,808 1146 3,781 202 23,241

2001 18,949 1069 2,340 –73 20,293

Average Annual Growth Rates

1980–2001 –2.9% –0.9% 14.6% –2.2%

1980–1989 –4.6% –4.7% 24.0% –3.7%

1990–2001 –2.6% 5.5% 8.5% –1.9%

a Apparent consumption is equal to U.S. production minus exports plus imports minus changes in

inventories.

Sources: U.S. Department of Energy. “AER Database: Coke Overview, 1949-1997.” 

<http://tonto.eia.doe.gov/aer/aer-toc-d.cfm>. Washington, DC: Energy Information

Administration. As obtained on September 14, 1998a.

Hogan, William T., and Frank T. Koelble. 1996. “Steel’s Coke Deficit: 5.6 Million Tons and

Growing.” New Steel 12(12):50-59.

U.S. International Trade Commission. Trade Database: Version 1.7.1. 

<http://205.197.120.17/scripts/user_set.asp> As obtained in September 1998.

U.S. Department of Energy, Energy Information Administration. 2002. Quarterly Coal Report: 

January–March 2002. Washington, DC: U.S. Department of Energy. 

<http://www.eia.doe.gov/cneaf/coal/quarterly/qcr_sum.html>. 
2-18

Table 2-6. Domestic Coke Production by Type: 1998-2000

Year Furnace Share Foundry Share Other Share Total

1998 17,637 88.0% 1,364 6.8% 1,040 5.2% 20,041

1999 16,976 84.8% 1,376 6.9% 1,665 8.3% 20,016

2000 17,747 85.3% 1,257 6.0% 1,804 8.7% 20,808

Sources: U.S. International Trade Commission. July 2000. “Foundry Coke: A Review of the Industries in

the United States and China.” <http://www.usitc.gov/sec/I0917W1.htm>.

U.S. Department of Energy, Energy Information Administration. 2002. Quarterly Coal Report: 

January–March 2002. Washington, DC: U.S. Department of Energy. 

<http://www.eia.doe.gov/cneaf/coal/quarterly/qcr_sum.html>. 

U.S. International Trade Commission (USITC). 2001c. “Blast Furnace Coke from China and

Japan.” Investigations Nos. 731-TA-951-952 (Preliminary) Publication 3444; August 2001. 

<http://www.usitc.gov/wais/reports/arc/w3449.htm>. 

Table 2-7. Foreign Trade Concentration for Coke Production

Year Export Ratio Import Ratio

1990 2.1% 3.8%

1991 3.1% 4.9%

1992 2.7% 8.4%

1993 3.6% 8.6%

1994 2.9% 12.9%

1995 3.2% 14.4%

1996 4.9% 10.4%

1997 3.8% 13.0%

1998 5.6% 16.6%

1999 4.5% 14.4%

2000 5.5% 16.3%

Sources: U.S. Department of Energy, Energy Information Administration. 2002. Quarterly Coal Report: 

January–March 2002. Washington, DC: U.S. Department of Energy. 

<http://www.eia.doe.gov/cneaf/coal/quarterly/qcr_sum.html>.
2-19

40

60

80

100

120

140

160

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Price Index: 1992=100

Figure 2-6. Price Trends for Coke: 1992–2001
3-1

SECTION 3

ENGINEERING COST ANALYSIS

Control measures implemented to comply with the MACT standard will impose

regulatory costs on coke batteries. This section presents compliance costs for representative

“model” batteries and the estimate of national compliance costs associated with the rule. 

These engineering costs are defined as the initial capital and annual operating costs assuming

no behavioral market adjustment by producers or consumers. For input to the EIA,

engineering costs are expressed per unit of coke production and used to shift the coke supply

functions in the market model.

The final MACT will cover the “Coke Ovens: Pushing, Quenching, and Battery

Stacks” source category. It will affect all 46 by-product coke oven batteries at 17 coke

plants. The processes covered by the regulation include pushing the coke from the coke

oven, quenching the incandescent coke with water in a quench tower, and the battery stack

which is the discharge point for the underfiring system. Capital, operating, and monitoring

costs were estimated for representative model batteries. Model battery costs were linked to

the existing population of coke batteries to estimate the national costs of the regulation.

3.1 Overview of Emissions from Coke Batteries

The listed HAP of concern is “coke oven emissions,” which includes hundreds of

organic compounds formed when volatiles are thermally distilled from the coal during the

coking process. Traditionally, benzene-soluble organics and methylene chloride-soluble

organics have been used as surrogate measures of coke oven emissions. The primary

constituents of concern are polynuclear aromatic hydrocarbons. Other constituents include

benzene, toluene, and xylene. 

Coke oven emissions occur from pushing and quenching when the coal has not been

fully coked, which is called a “green” push. A green push produces a dense cloud of coke

oven emissions that is not captured and controlled by the emission control systems used for

particulate matter. Coke oven emissions occur from battery stacks when raw coke oven gas

leaks through the oven walls, enters the flues of the underfiring system, and is discharged

through the stack. Coke oven emissions from these sources are controlled by pollution
3-2

prevention activities, diagnostic procedures, and corrective actions. One component of the

control technology is good systematic operation and maintenance of the battery to prevent

green pushes and stack emissions.

Based on limited test data and best engineering judgment, the final standards are

expected to reduce coke oven emissions from pushing, quenching, and battery stacks by

about 50 percent. There is uncertainty in estimates of emissions and emission reductions

because the emissions are fugitive in nature. For example, the emissions from green coke

during pushing and quenching are not enclosed or captured in a conveyance, which makes

accurate measurement of concentrations and flow rates very difficult (or impossible). 

3.2 Approach for Estimating Compliance Costs

The costs for individual batteries to achieve the MACT level of control will vary

depending on the battery condition and control equipment in place. There is uncertainty in

determining exactly what costs will be incurred by each battery. Consequently, several

model batteries were developed to represent the range of battery types and conditions to

place bounds on the probable costs. Several repair categories were developed, and after

review by the Coke Oven Environmental Task Force (COETF) of the American Coke and

Coal Chemicals Institute (ACCCI), the number of categories was expanded. The repair

categories recommended by COETF are given in Table 3-1. Costs estimates for each type of

repair and any lost production associated with them were also provided by COETF based on

the experience of coke plant operators. These cost estimates were then applied to each repair

category to estimate the costs for model batteries.

Actual batteries were assigned to model batteries based on opacity data, discussions

with plant operators, information from site visits, conversations with inspectors from state

agencies, and best judgment based on battery age and repair history. The battery

assignments to specific repair categories are given in Table 3-1. The most uncertainty in the

assignment to model batteries is for those batteries for which the least information is

available. These batteries were assigned to the more extensive repair groups. Consequently,

the costs to be incurred by these batteries may be overstated because they may not require

the extensive repairs that were assumed. In addition, some of these batteries may have

required repairs to continue operating even without the MACT standard.
3-3

Table 3-1. Repair Categories and Assignment of Batteries

Repair Category Batteries Assigned

A—Battery in good condition and can already

meet the emission limits

USS Clairton Works (12 batteries)

USS Gary Works (4 batteries)

Bethlehem Steel—Burns Harbor (2 batteries)

Citizen’s Gas Battery 1

B—Needs a baseline program (includes special

program for tall batteries; coal quality

assurance/quality control, inspection

procedures, extensive oven patching and

welding for all batteries) 

ABC Coke 1, 5, and 6 plus all batteries listed

below in other categories

C—Needs baseline program plus end flue

repair for 25 percent of the ovens

AK Steel (KY) 3 and 4

AK Steel (OH) 3

ISG - Warren 4 

Shenango 1

Sloss 5

Tonawanda 2

Koppers 1 and 2 

Citizens Gas E and H

Empire 1 and 2 

Wheeling-Pittsburgh 1, 2, and 3

National Granite City A and B

D—Needs baseline program, 1 through wall, 5

end flue repairs

Erie Coke A and B

Sloss 3 and 4

E—Tall battery that needs baseline program National Steel, Ecorse 5

F—Tall battery that needs baseline program

plus end flue repair for 25 percent of the ovens

Wheeling-Pittsburgh 8

3.3 Costs for MACT Performance

The MACT standard involves a routine program of good systematic operation and

maintenance and oven repairs to control emissions from battery stacks and pushing. In

addition, batteries in poor condition may have to rebuild oven walls and end flues. An

important element of this routine program for battery stacks is the use of continuous opacity

monitors (COM). In addition, control of quenching emissions will require the installation of

baffles in three quench towers that do not have them. 
3-4

3.3.1 Costs for the Baseline Program

The baseline program includes routine oven patching, coal quality control, and other

measures that are used by the best controlled batteries. The cost elements for the baseline

program were provided by COETF and are discussed below.

a. Oven patching: Add one patcher, include extensive ceramic welding repairs to two

ovens per year, and account for lost production while welding and patching. The

estimated costs in $/yr per oven are $2,917 for a short foundry coke battery, $2,933

for a short furnace coke battery, and $3,083 for a tall furnace coke battery.

b. Coal testing program: Implement a quality assurance/quality control program for

coal, including bulk density, size, blend composition, and moisture. Estimate a

capital cost of $10,000 ($167/oven) to develop a statistical sampling program and an

operating cost of $72,000/yr ($1,200/yr per oven) for one lab technician.

c. Inspections: Capital cost of $6,000 ($100/oven) to develop procedures for hard

pushes. Estimate the operating cost for periodic refractory inspection, documentation

and specifications for pressure and contraction as $4,000/yr or $67/yr per oven.

d. Special testing and procedures for tall batteries: Capital costs include an initial

structural evaluation to determine acceptable wall pressure ($40,000 or $667/oven),

testing equipment for coal ($263,000 for testing equipment or $4,383/oven), and

equipment for field tests of coking pressures ($10,000 for testing equipment or

$167/oven). Operating costs include testing moisture and bulk density of the coal

($20,000/yr or $333/yr per oven), test all coal for “Go/No Go” status ($168,000/yr for

2.4 lab technicians, $10,000/yr for maintenance, or $2,970/yr per oven), one “No Go”

per year with 6 hours lost production ($31,000/yr or $517/yr per oven), and periodic

field tests of coking pressures ($12,000/yr for labor or $200/yr per oven). This

results in a total operating cost for a tall 60-oven battery of $241,000/yr or $4,017/yr

per oven.

3.3.2 Major Repairs

Some batteries may incur a one-time capital expense to rebuild oven walls and end

flues to achieve the level of control associated with the best performing batteries. Cost

estimates for these major repairs were provided by COETF based on the experience of coke

plant operators.

a. End flue repairs: For Category C and F batteries, assume 25 percent of the ovens

need end flue repairs. For the small Category D foundry batteries (less than 50

ovens), assume 5 ovens need end flue repairs. Estimate the cost as $175,000 per oven

for short batteries and $245,000 per oven for tall batteries. For lost coke production

during the repair, add $78,000 per oven for short foundry batteries, $130,000 for
3-5

short furnace batteries, and $220,000 for tall batteries. (The cost of lost production is

based on $62/ton for furnace coke and $73/ton for foundry coke.)

b. Through wall repairs: For Category D batteries, COETF recommended using one

through wall repair for small batteries (less than 50 ovens). Estimate the cost as

$800,000 per through wall. For lost coke production during the repair, add $113,000

per through wall for short foundry batteries.

c. Oven patching: Include a capital cost for one-time patching for all ovens for

batteries in Categories C, D, and F at $525/oven.

3.3.3 Quenching

Three quench towers at two coke plants will require the installation of baffles: one

quench tower at Erie Coke and two quench towers at Tonawanda Coke. The capital cost for

installing baffles with a water spray cleaning system in quench towers is $140,000 (based on

responses to EPA’s cost survey).

3.3.4 Monitoring Costs

The following monitoring costs are included.

a. The capital cost for installing a continuous opacity monitor (COM) is $37,000 and

the operating cost is $8,000/yr (based on responses to EPA’s cost survey). A total of

18 stacks will require new COM.

b. The capital cost for installing a bag leak detection system is $9,000 and the operating

cost is $500/yr. There are 18 baghouses applied to pushing emissions.

c. Method 9 observations of 4 pushes per battery per day have an annual cost of $11,000

times the number of batteries (approximately one hour per day per battery for

observations) plus $22,000 per coke plant (2 hours per day for travel time and data

entry). These costs will be incurred by batteries that are not currently making

Method 9 observations (38 batteries at 17 plants, adjusting for cases in which two

small batteries are operated as a single battery).

d. Other costs include the startup, shutdown, and malfunction plan (assume 40 hrs every

5 years or 8 hrs/yr), operation and maintenance plan (assume 40 hrs every 5 years or

8 hrs/yr), Method 5 testing (80 hrs every 2.5 years or 32 hrs/yr), monthly inspections

of control equipment (2 hrs/month or 24 hrs/yr), and notifications and records (40

hrs/yr) for a total of 112 hrs/yr. Using a typical labor rate of $50/hr, these costs total

$5,600/yr.
3-6

Table 3-2. Capital Recovery Factors (at 7 percent interest)

Life

(years)

Capital Recovery

Factor Capital Items

5 0.244 • Initial structural evaluation to determine acceptable wall

pressure

• Develop a coal QA/QC program

• Develop procedures for tracking and addressing sticker

pushes

• Equipment for field tests of coking pressure

10 0.142 • End flue repairs

• Continuous opacity monitor

• Bag leak detector

15 0.110 • Testing equipment for coal

20 0.094 • Through wall repairs

• Baffles for quench towers

3.3.5 Capital Recovery Factors

Capital recovery factors are used to annualize the cost of capital to estimate total

annual cost. The equipment lifetimes and capital recovery factors (based on 7 percent

interest) are given in Table 3-2.

3.4 Estimates of Nationwide Costs

Tables 3-3 and 3-4 illustrate the development of nationwide costs for the baseline

program and for major repairs. The cost functions discussed earlier in $/oven were applied

to the appropriate categories of model batteries, and the cost elements were summed to get a

total cost for each model battery. Nationwide costs were estimated by multiplying the model

battery cost by the number of actual batteries associated with each model battery. The tables

show a total capital cost of $88 million and a total annual cost of $19 million/yr for the

baseline program and major repairs.

Other costs associated with MACT include installing baffles in quench towers,

monitoring, reporting, and recordkeeping. Table 3-5 presents the nationwide costs for these

additional items as well battery repair costs. The total nationwide capital cost is estimated as

$89.5 million with a total annualized cost of $20.2 million/yr.
3-7

Table 3-3. Capital Costs for Battery Repairs and Baseline Program ($1,000)a

Baseline Program Only Baseline plus Repair 25 Percent of End Flues Baseline, End Flues, through Walls

Category B B E C C C C C F DShort/Tall Short Short Tall Short Short Short Short Short Tall ShortCoke type Foundry Foundry Furnace Foundry Foundry Furnace Furnace Furnace Furnace FoundryNo. of ovens 76 37 76 64 37 37 64 76 76 37Actual batteriesrepresented

1 2 1 544141 4

Cost for baseline program:Structural evaluation 51 51Coal testing 333 333Pressure testing 13 13Develop procedures forsticker pushes

8 4 8 644688 4

Coal QA/QC 13 6 13 11 6 6 11 13 13 6Total for baseline 20 10 417 17 10 10 17 20 417 10Endflue repairs 2,800 1,619 1,619 2,800 3,325 4,655 875Lost production 1,248 722 1,203 2,080 2,470 4,180 390Through wall repairs 800Lost production 113Patch all ovens 34 19 19 34 40 40 19Cost per model battery 20 10 417 4,099 2,370 2,851 4,931 5,855 9,292 2,207Nationwide costb 20 20 417 20,493 9,478 11,402 4,931 23,421 9,292 8,829

Total nationwide capital cost = $88.3 million 

a All costs are in 2001 dollars.b Cost per model battery times the number of actual batteries represented.
3-8

Table 3-4. Total Annual Costs for Battery Repairs and Baseline Program ($1,000)a

Baseline Program Only Baseline Program plus Repair 25 Percent of End Flues

Baseline, End

Flues, through

Walls

Group B B E C C C C C F DShort/Tall Short Short Tall Short Short Short Short Short Tall ShortCoke type Foundry Furnace Furnace Foundry Foundry Furnace Furnace Furnace Furnace FoundryNo. of ovens 76 37 76 64 37 37 64 76 76 37Actual batteriesrepresented

12 1 5 4 4 1 4 1 4

Capital recovery,baseline program

2.9 1.4 48.5 2.4 1.4 1.4 2.4 2.9 48.5 1.4

Tall battery coke/coaltesting

305.3 305.3

Baseline patch/weld 221.7 108.5 234.3 186.7 107.9 108.5 187.7 222.9 234.3 107.9Coal QA/QC 91.2 44.4 91.2 76.8 44.4 44.4 76.8 91.2 91.2 44.4Inspect/procedures 5.1 2.5 5.1 4.3 2.5 2.5 4.3 5.1 5.1 2.5Total baseline/battery 320.8 156.8 684.3 270.2 156.2 156.8 271.2 322.1 684.3 156.2

Capital recovery, endflues 

— — — 399 231 231 399 473 663 125

Capital recovery,through walls 

— — — — — — — — — 76

Capital recovery, lostproduction for repairs 

— — — 178 103 171 296 352 595 66

Capital recovery,patching all ovens 

— — — 4.8 2.8 2.8 4.8 5.7 5.7 2.8

Cost per model battery 321 157 684 851 492 561 971 1,153 1,948 425Nationwide costb 321 314 684 4,257 1,969 2,245 971 4,612 1,948 1,701

Total nationwide annual cost = $19 million/yr

a All costs are in 2001 dollars.b Cost per model battery times the number of actual batteries represented.
3-9

Table 3-5. Estimated Nationwide Compliance Costs for Coke Batteries Associated with

the MACT Floora

Cost Element

Capital Cost 

($106)

Total Annualized Cost

($106/yr)

Baseline repair program 1.2 6.8

Major repairs (end flues, through walls,

oven patching)

87.1 12.0

Baffles, continuous opacity monitors, bag

leak detectors, daily Method 9 observations,

and reporting, recordkeeping.

1.2 1.4

Total 89.5 20.2

a All costs are in 2001 dollars.

These costs estimates are expected to be upper bound costs for several reasons. If

some batteries are in a serious state of disrepair as indicated by the model battery categories,

they could incur these expenses in the future simply to keep operating even in the absence of

the MACT standard. In addition, the repairs will help to maintain production and extend

battery life; consequently, the true cost of lost coke production while the repairs are being

made are overstated. Although we know which batteries can achieve MACT without any

significant repairs, we have much less information on those that may not achieve it and what

repairs would be required. Some of these batteries may implement more cost effective

approaches than the extensive repairs assumed in this cost analysis.
4-1

SECTION 4

ECONOMIC IMPACT ANALYSIS

The final rule to control the release of HAPs from coke pushing and quenching

operations will directly (through imposition of compliance costs) or indirectly (through

changes in market prices) affect the entire U.S. iron and steel industry. Implementation of

the final rule will increase the costs of producing furnace and foundry coke at affected

facilities. As described in Section 3, these costs will vary across facilities and their coke

batteries depending upon their physical characteristics and baseline controls. The response

by these producers to these additional costs will determine the economic impacts of the

regulation. Specifically, the impacts will be distributed across producers and consumers of

coke, steel mill products, and iron castings through changes in prices and quantities in the

affected markets. This section presents estimates of the economic impacts of the coke

MACT using an economic model that captures the linkages between the furnace coke and

steel mill products, and foundry coke and iron castings markets.

This section describes the data and approach used to estimate the economic impacts

of this final rule for the baseline year of 2000. Section 4.1 presents the inputs for the

economic analysis, including characterization of producers, markets, and the costs of

compliance. Section 4.2 summarizes the conceptual approach to estimating the economic

impacts on the affected industries. A fully detailed description of the economic impact

methodology is provided in Appendix A. Lastly, Section 4.3 provides the results of the

economic impact analysis.

4.1 EIA Data Inputs

Inputs to the economic analysis are a baseline characterization of directly and

indirectly affected producers, their markets, and the estimated costs of complying with the

final rule.

4.1.1 Producer Characterization

As detailed in Section 2, the baseline characterization of integrated and merchant

manufacturing plants is based on the facility responses to EPA’s industry survey and industry

data sources for 1997. In order to develop a baseline data set for coke batteries consistent
4-2

with the year 2000, EPA collected aggregate production and shipment data for furnace and

foundry coke reported in recent USITC publications (USITC, 2001a,b,c). These reports

distinguished the data by type of coke (furnace, foundry) and use (captive and merchant). 

Using this data, EPA applied factors to individual coke battery production data collected

from the 1997 survey (see Table 2-2) that result in a data set that is consistent with aggregate

baseline production values reported by USITC. Coke-specific cost equations were developed

using the 1993 Coke Ovens MACT methodology (as described fully in Appendix B).

Plant-specific data on existing integrated steel producers were supplemented with

secondary information from company 10K, 10K–405, and annual reports; the 1998 Directory

of Iron and Steel Plants published by the Association of Iron and Steel Engineers; World

Cokemaking Capacity published by the International Iron and Steel Institute. 

4.1.2 Market Characterization

Figure 4-1 summarizes the market interactions included in the Agency’s EIA

modeling approach. Changes in the equilibrium price and quantity due to control costs on

coke batteries were estimated simultaneously in four linked markets:

 market for furnace coke,

 market for foundry coke, 

 market for steel mill products, and

 market for iron castings.

As described in Section 2, many captive coke plants supply their excess coke to the

furnace coke market. Merchant coke plants and foreign imports account for the remaining

supply to the furnace coke market. Furnace coke produced at captive coke plants and

shipped directly to integrated iron and steel mills owned by their parent companies does not

directly enter the market for furnace coke. However, compliance costs incurred by captive,

or “in-house”, furnace coke batteries indirectly affect the furnace coke market through price

and output changes in the steel mill products market. 

The market demand for furnace coke is derived from integrated mills producing steel

mill products. Integrated iron and steel mills that need more coke than their captive batteries

can produce purchase furnace coke from the market. Integrated mills’ market (and captive)

demand for furnace coke depends on their production levels as influenced by the market for

steel mill products. Steel mill products are supplied by three general groups: integrated iron 
4-3

Merchant Coke Plants

• Finishing Mills

• Steelmaking Furnace

• Blast Furnace

Captive Coke Plants

Market for

Foundry Coke

Consumers of Steel

Mill Products

Imports

Imports

Exports

Integrated Iron

and Steel Mills

Exports

Market for

Furnace Coke

Electric

Furnaces

Consumers of

Iron Castings

Cupola Furnaces

Control Costs

Market for

Steel

Mill Products

Nonintegrated

Steel Mills

(including

minimills)

Market for

Iron Castings

Imports

Exports

Figure 4-1. Market Linkages Modeled in the Economic Impact Analysis
1

Other coke, frequently grouped with foundry coke, is purchased as a fuel input by cement plants, chemical

plants, and nonferrous smelters. For simplicity, supply and demand for other coke are assumed to be

unaffected by the final coke regulation and are not included in the market model.

2

 EPA used the chemical engineering plant cost index with the following values: 

4-4

and steel mills, nonintegrated steel mills (primarily minimills), and imports. Domestic

consumers of steel mill products and exports account for the market demand.

As described in Section 2, domestic and foreign merchant plants are the suppliers of

foundry coke to the market. Consumers of foundry coke include foundries with cupolas that

produce iron castings, and they are modeled using aggregate market demand curves.1

 

Table 4-1 provides the 2000 data on the U.S. furnace and foundry coke, steel mill

products, and iron castings markets for use in this analysis. Coke prices were obtained from

USITC reports (USITC, 2000b, 2000c). The market price for steel mill products was

obtained from Current Industrial Reports (CIR) and reflects the production-weighted average

across all product types. The market price for iron castings was also obtained from CIR and

reflects the production-weighted average across iron castings (ductile, gray, and malleable). 

Domestic production from affected facilities reflects the aggregate of the plant-specific data

developed from survey and secondary data sources, while unaffected domestic production is

derived either directly from secondary sources or as the difference between observed total

U.S. production and the aggregate production from affected facilities. Foreign trade data

were obtained from industry and government statistical publications supplemented by survey

data. Market volumes for each product are then computed as the sum of U.S. production and

foreign imports. 

4.1.3 Regulatory Control Costs

As shown in Section 3, the Agency developed compliance cost estimates for model

plants that may be mapped to each of the coke manufacturing facilities affected by the final

rule. These estimates reflect the “most-reasonable” scenario for this industry. To be

consistent with the 2000 baseline industry characterization of the economic model, the

Agency adjusted the nationwide compliance cost estimate of $20.2 expressed in 2001 dollars

(Table 3-5) to be $20.1 million as expressed in 2000 dollars using an engineering cost index.2

These cost estimates serve as inputs to the economic analysis and affect the operating

decisions for each affected facility and thereby the markets that are served by these facilities.
4-5

Table 4-1. Baseline Characterization of U.S. Iron and Steel Markets: 2000

Baseline

Furnace Coke

Market price ($/short ton) $112.00

Market output (103

 tpy) 12,004

Domestic productiona 8,904

Imports 3,100

Foundry Coke

Market price ($/short ton) $161.00

Market output (103

 tpy) 1,385

Domestic production 1,238

Imports 147

Steel Mill Products

Market price ($/short ton) $489.45

Market output (103

 tpy) 147,007

Domestic production 109,050

Integrated producers 57,153

Nonintegrated steel millsb 51,897

Imports 37,957

Iron Castings

Market price ($/short ton) $1,028.50

Market output (103

 tpy) 8,793

Domestic productiona 8,692

Cupola furnaces 5,210

Electric furnacesc 3,482

Imports 101

a Includes minimills. b Excludes captive production. c Includes electric arc or electric induction furnaces. 
4-6

4.2 EIA Methodology Summary

In general, the EIA methodology needs to allow EPA to consider the effect of the

different regulatory alternatives. Several types of economic impact modeling approaches

have been developed to support regulatory development. These approaches can be viewed as

varying along two modeling dimensions:

 the scope of economic decision making accounted for in the model, and

 the scope of interaction between different segments of the economy.

Each of these dimensions was considered in selecting the approach used to model the

economic impact of the final coke regulation. 

To conduct the analysis for the final coke regulation, the Agency used a market

modeling approach that incorporates behavioral responses in a multiple-market partial

equilibrium model. Multiple-market partial equilibrium analysis provides a manageable

approach to incorporate interactions between coke, steel mill product, and iron castings

markets into the EIA to better estimate the final regulation’s impact. The multiple-market

partial equilibrium approach represents an intermediate step between a simple, single-market

partial equilibrium approach and a full general equilibrium approach. The modeling

technique is to link a series of standard partial equilibrium models by specifying the

interactions between the supply and demand for products and then solving for changes in

prices and quantities across all markets simultaneously. The EIA methodology is fully

detailed in Appendix A.

The Agency’s methodology is soundly based on standard microeconomic theory

relying heavily on previous economic analyses, employs a comparative static approach, and

assumes certainty in relevant markets. For this analysis, prices and quantities are determined

in perfectly competitive markets for furnace coke, foundry coke, finished steel mill products,

and iron castings. The competitive model of price formation, as shown in Figure 4-2 (a),

posits that market prices and quantities are determined by the intersection of market supply

and demand curves. Under the baseline scenario, a market price and quantity (P, Q) are

determined by the downward-sloping market demand curve (DM) and the upward-sloping

market supply curve (SM) that reflects the horizontal summation of the individual supply

curves of directly affected and indirectly affected facilities that produce a given product.
4-7

p

Sa

qa qu Q

Affected Facilities

Su SM

DM

+ = p p

Unaffected Facilities Market

a) Baseline Equilibrium

p

q′

a qu Q′

Affected Facilities

Su SM′

DM

+ = p p

Unaffected Facilities Market

b) With-Regulation Equilibrium

p′

Sa

qa q′

u Q

SM

p′ p′

S′

a

Figure 4-2. Market Equilibrium without and with Regulation
4-8

With the regulation, the cost of production increases for directly affected producers. 

The imposition of the compliance costs is represented as an upward shift in the supply curve

for each affected facility from Sa to Sa. As a result, the market supply curve to shift upward

to SMas shown in Figure 4-2(b) reflecting the increased costs of production at these

facilities. In the baseline scenario without the final standards, the industry would produce

total output, Q, at the price, P, with affected facilities producing the amount qa and

unaffected facilities accounting for Q minus qa, or qu. At the new equilibrium with the

regulation, the market price increases from P to Pand market output (as determined from

the market demand curve, DM) declines from Q to Q. This reduction in market output is the

net result from reductions at affected facilities and increases at unaffected facilities.

4.3 Economic Impact Results

Based on the simple analytics presented above, when faced with higher costs of coke

production, producers will attempt to mitigate the impacts by making adjustments to shift as

much of the burden on other economic agents as market conditions allow. The adjustments

available to facility operators include changing production processes, changing inputs,

changing output rates, or even closing the facility. This analysis focuses on the last two

options because they appear to be the most viable for coke manufacturing facilities, at least

in the near-term. A large segment of the furnace and foundry coke market is affected by the

regulation so we would expect upward pressure on prices as producers reduce output rates in

response to higher costs. Higher prices reduce quantity demanded and output for each

market product, leading to changes in profitability of batteries, facilities, and firms. These

market and industry adjustments will also determine the social costs of the regulation and its

distribution across stakeholders (producers and consumers). 

To estimate these impacts, the economic modeling approach described in Appendix A

was operationalized in a multiple spreadsheet model. This model characterizes those

producers and consumers identified in Figure 4-1 and their behavioral responses to the

imposition of the regulatory compliance costs. These costs are expressed per ton of furnace

or foundry coke and serve as the input to the economic model, or “cost-shifters” of the

baseline supply curves at affected facilities. Given these costs, the model determines a new

equilibrium solution in a comparative static approach. The following sections provide the

Agency’s estimates of the resulting economic impacts for the final rule. 
4-9

4.3.1 Market-Level Impacts

The increased cost of coke production due to the regulation is expected to increase

the price of furnace coke and steel mill products and reduce their production and

consumption from 2000 baseline levels. As shown in Table 4-2, the regulation is projected

to increase the price of furnace coke by 2.6 percent, or $3.00 per short ton. The increased

captive production costs and higher market price associated with furnace coke are projected

to increase steel mill product prices by less than 0.1 percent, or $0.14 per ton. As expected,

directly affected output declines across all producers, while supply from domestic and

foreign producers not subject to the regulation increases. Although the resulting net declines

are slight across all products (i.e., less than 1 percent decline in market output) the change in

domestic production is typically higher than 0.1 percent. This is especially true for furnace

coke where domestic production declines by 3.9 percent.

In contrast, the regulation showed no impact on price or quantity in the foundry coke

market. This is due to the capacity constraints on domestic producers and the role of foreign

imports. The supply of foundry coke is characterized by a domestic step supply function

augmented by foreign supply, with foreign suppliers being the high cost producers in the

market. Because foreign suppliers are the high cost producers, they determine the market

price and an upward shift in the domestic supply curve does not affect the equilibrium price

or quantity. This implies that domestic foundry coke producers are not able to pass along

any of the cost of the regulation. In addition, because there is no price change in the foundry

coke market, the production of iron castings in unaffected by the regulation. 

4.3.2 Industry-Level Impacts

Industry revenue, costs, and profitability change as prices and production levels

adjust to increased production costs. As shown in Table 4-3, the economic model projects

that profits for directly affected integrated iron and steel producers will decrease by $22.4

million, or 3.0 percent. However, because the price increase exceeds the average cost

increase, industry-level profits for U.S. merchant furnace coke producers are expected to

increase by $9.7 million, or 8.3 percent. In contrast, industry-level profits for U.S. merchant

foundry coke producers are expected to decline by $5.0 million, or 5.0 percent. These

producers cannot pass along any of the control costs of the regulation because there is no

price increase. Those domestic suppliers not subject to the regulation experience windfall

gains with non-integrated steel mills (i.e., minimills) increasing profits by $7.4 million. 
4-10

Table 4-2. Market-Level Impacts of the Final Coke MACT: 2000

Baseline

Changes From Baseline

Absolute Percent

Furnace Coke

Market price ($/short ton) $112.00 $3.00 2.68%

Market output (103

 tpy) 12,004 –91.8 –0.76%

Domestic productiona 8,904 –347.9 –3.91%

Imports 3,100 256.1 8.26%

Foundry Coke

Market price ($/short ton) $161.00 0.0 0.00%

Market output (103

 tpy) 1,385 0.0 0.00%

Domestic production 1,238 0.0 0.00%

Imports 147 0.0 0.00%

Steel Mill Products

Market price ($/short ton) $489.45 $0.14 0.03%

Market output (103

 tpy) 147,007 –26.4 –0.02%

Domestic production 109,050 –191.9 –0.18%

Integrated producers 57,153 –244.6 –0.43%

Nonintegrated steel millsb 51,897 52.7 0.10%

Imports 37,957 165.5 0.44%

Iron Castings

Market price ($/short ton) $1,028.50 $0.00 0.00%

Market output (103

 tpy) 8,793 0.0 0.00%

Domestic productiona 8,692 0.0 0.00%

Cupola furnaces 5,210 0.0 0.00%

Electric furnacesc 3,482 0.0 0.00%

Imports 101 0.0 0.00%

a Includes minimills. b Excludes captive production. c Includes electric arc or electric induction furnaces.
4-11

Table 4-3. National-Level Industry Impacts of the Final Coke MACT: 2000

Baseline

Changes From Baseline

Absolute Percent

Integrated Iron and Steel Mills

Total revenues ($106

/yr) $28,430.5 –$99.9 –0.35%

Steel mill products $27,973.6 –$111.62 –0.40%

Market coke operations $456.9 $12.44 2.72%

Total costs ($106

/yr) $27,690.8 –$76.81 –0.28%

Control costs $0.0 $9.91 NA

Steel production $0.0 $0.00 NA

Captive coke production $0.0 $7.43 NA

Market coke production $0.0 $2.48 NA

Production costs $27,690.8 –$86.72 –0.315

Steel production $25,327.3 –$110.43 –0.44%

Captive coke production $746.6 –$0.06 –0.01%

Market coke consumption $1,249.5 $23.71 1.90%

Market coke production $367.4 $0.06 0.02%

Operating profits ($106

/yr) $739.7 –$22.38 –3.02%

Iron and steel facilities (#) 20 0 0.00%

Coke batteries (#) 37 0 0.00%

Employment (FTEs) 66,603 –323 –0.48%

Coke Producers (Merchant Only)

Furnace

Revenues ($106

/yr) $521.8 –$28.76 –5.51%

Costs ($106

/yr) $404.5 –$38.45 –9.51%

Control costs $0.0 $3.13 NA

Production costs $404.5 –$41.57 –10.28%

Operating profits ($106

/yr) $117.4 $9.68 8.25%

Coke batteries (#) 17 –2 –11.76%

Employment (FTEs) 774 –193 –34.94%

Foundry

Revenues ($106

/yr) $245.5 $0.56 0.23%

Costs ($106

/yr) $148.7 $5.54 3.73%

Control costs $0.0 $5.54 NA

Production costs $148.7 $0.00 0.00%

Operating profits ($106

/yr) $96.8 –$4.98 –5.15%

Coke batteries (#) 12 0 0.00%

Employment (FTEs) 2,486 0 0.00%

(continued)
4-12

Table 4-3. National-Level Industry Impacts of the Final Coke MACT: 2000

(continued)

Baseline

Changes From Baseline

Absolute Percent

Nonintegrated Steel Millsa

Operating profits ($106/yr) NA $7.4 NA

Cupola Furnaces

Operating profits ($106/yr) NA $0.0 NA

Captive NA $0.0 NA

Merchant NA $0.0 NA

Affected NA $0.0 NA

Unaffected NA $0.0 NA

Electric Furnacesb

Operating profits ($106/yr) NA $0.0 NA

Captive NA $0.0 NA

Merchant NA $0.0 NA

Affected NA $0.0 NA

Unaffected NA $0.0 NA

a Includes minimills. b Includes iron foundries that use electric arc or electric induction furnaces.

4.3.2.1 Changes in Profitability

For integrated steel mills, operating profits decline by $22 million. This is the net

result of three effects: 

 Net decrease in revenue ($99 million): Steel mill product revenue decreases as a

result of reductions in output. However, these losses were mitigated by increased

revenues from furnace coke supplied to the market as a result of higher prices.

 Net decrease in production costs ($87 million): Reduction in steel mill and

market coke production costs occur as output declines. However, producers also

experience increases in costs associated with the higher price of inputs (i.e.,

furnace coke). 

 Increase in control costs ($10 million): The costs of captive production of

furnace coke increase as a result of regulatory controls.

Industry-wide profits for merchant furnace coke producers increase by $10 million as

a result of the following:
4-13

 Decreases in revenue ($29 million): Reductions in output outweigh revenue

increases as a result of higher market prices.

 Reduction in production costs ($42 million): Reduction in coke production costs

occurs as output declines. 

 Increased control costs ($3 million): The cost of producing furnace coke

increases as a result of regulatory controls.

Industry-wide profits for merchant foundry coke producers fall by $5 million under

the regulation:

 Increase in revenue ($0.5 million): Given that we project no price changes for

foundry coke, foundry coke revenue remains unchanged. However, small

revenue increases occur because some batteries also produce small amounts of

furnace coke. 

 Reduction in production costs ($0 million): No change in coke production costs

occur as output remains unchanged. 

 Increased control costs ($5.6 million): The cost of producing foundry coke

increases as a result of regulatory controls.

Lastly, domestic producers that are not subject to the regulation benefit from higher

prices without additional control costs. As mentioned above, profits increase are projected

for nonintegrated steel mills. 

Additional distributional impacts of the rule within each producer segment are not

necessarily apparent from the reported decline or increase in their aggregate operating

profits. The regulation creates both gainers and losers within each industry segment based

on the distribution of compliance costs across facilities. As shown in Table 4-4, a substantial

subset of the merchant coke facilities are projected to experience profit increases (i.e., 13

furnace coke batteries and 1 foundry coke battery, or 62 percent). However, two merchant

batteries are projected to cease market operations as they are the highest-cost coke batteries

with the additional regulatory costs.

A majority of directly affected integrated iron and steel facilities (i.e., 16 plants, or 80

percent) are projected to become less profitable with the regulation with a total loss of $33.9

million. However, four integrated mills are projected to benefit from higher prices and

experience a total profit gain of $11.5 million. These mills typically own furnace coke

batteries with low production costs and lower per-unit compliance costs. In addition, a high

proportion of their coke inputs are supplied internally. 
4-14

Table 4-4. Distribution Impacts of the Final Coke MACT Across Directly Affected

Producers: 2000

With Regulation

Increased

Profits

Decreased

Profits Closure Total

Integrated Iron and Steel Mills

Facilities (#) 4 16 0 20

Steel production

Total (103

 tpy) 6,232 50,922 0 57,153

Average (tons/facility) 1,558 3,183 0 2,858

Steel compliance costs

Total ($106/yr) $0.00 $0.00 $0.00 $0.00

Average ($/ton) $0.00 $0.00 $0.00 $0.00

Coke production

Total (103

 tpy) 5,729 6,915 0 12,644

Average (tons/facility) 1,432 432 0 632

Coke compliance costs

Total ($106

/yr) $0.17 $9.74 $0.00 $9.91

Average ($/ton) $0.03 $1.41 $0.00 $0.78

Change in operating profit ($106

/yr) $11.47 –$33.85 $0.00 –$22.38

Coke Plants (Merchant Only)

Furnace

Batteries (#) 13 2 2 17

Production (103

 tpy)

Total (103

 tpy) 3,979 391 267 4,637

Average (tons/facility) 306 196 134 273

Compliance costs

Total ($106

/yr) $2.1 $1.3 $1.340 $4.738

Average ($/ton) $0.52 $3.42 $5.01 $1.02

Change in operating profit ($106

/yr) $9.89 –$0.16 –$0.04 $9.68

Foundry

Batteries (#) 1 11 0 12

Production

Total (103

 tpy) 476 1,181 0 1,657

Average (tons/facility) 476 107 0 138

Compliance costs

Total ($106

/yr) $0.021 $5.524 $0.00 $5.545

Average $0.04 $4.68 $0.00 $3.35

Change in operating profit ($106

/yr) $0.54 –$5.52 $0.00 –$4.98
4-15

4.3.2.2 Facility Closures

EPA estimates two merchant batteries supplying furnace coke are likely to

prematurely close as a result of the regulation. In this case, these batteries are the highestcost producers of furnace coke with the regulation. 

4.3.2.3 Changes in Employment

As a result of decreased output levels, industry employment is projected to decrease

by less than 1 percent, or 516 full-time equivalents (FTEs), with the regulation. This is the

net result of employment losses for integrated iron and steel mills totaling 323 FTEs and

merchant coke plants of 193 FTEs. Although EPA projects increases in output for producers

not subject to the rule, which would likely lead to increases in employment, the Agency did

not develop quantitative estimates for this analysis.

4.3.3 Social Cost

The social impact of a regulatory action is traditionally measured by the change in

economic welfare that it generates. The social costs of the final rule will be distributed

across consumers and producers alike. Consumers experience welfare impacts due to

changes in market prices and consumption levels associated with the rule. Producers

experience welfare impacts resulting from changes in profits corresponding with the changes

in production levels and market prices. However, it is important to emphasize that this

measure does not include benefits that occur outside the market, that is, the value of reduced

levels of air pollution with the regulation.

The national compliance cost estimates are often used as an approximation of the

social cost of the rule. The engineering analysis estimated annual costs of $20.1 million. In

this case, the burden of the regulation falls solely on the affected facilities that experience a

profit loss exactly equal to these cost estimates. Thus, the entire loss is a change in producer

surplus with no change (by assumption) in consumer surplus. This is typically referred to as

a “full-cost absorption” scenario in which all factors of production are assumed to be fixed

and firms are unable to adjust their output levels when faced with additional costs.

In contrast, the economic analysis accounts for behavioral responses by producers

and consumers to the regulation (i.e., shifting costs to other economic agents). This

approach results in a social cost estimate that differs from the engineering estimate and also

provides insights on how the regulatory burden is distributed across stakeholders. As shown

in Table 4-5, the economic model estimates the total social cost of the rule to be 
4-16

Table 4-5. Distribution of the Social Costs of the Final Coke MACT: 2000

Change in Consumer Surplus ($106/yr) –$20.87

Steel mill product consumers –$20.87

Domestic –$19.94

Foreign –$0.93

Iron casting consumers $0.00

Domestic $0.00

Foreign $0.00

Change in Producer Surplus ($106

/yr) $2.25

Domestic producers –$10.31

Integrated iron and steel mills –$22.38

Nonintegrated steel millsa $7.37

Cupola furnaces $0.00

Electric furnacesb $0.00

Furnace coke (merchant only) $9.68

Foundry coke (merchant only) –$4.98

Foreign producers $12.56

Iron and steel $2.86

Castings $0.00

Furnace coke $9.69

Foundry coke $0.00

Change in Total Social Surplus ($106

/yr)c –$18.62

a Includes minimills.

b Includes electric arc or electric induction furnaces. c The negative change in total social surplus indicates the social cost of the regulation is $18.62 million

$18.6 million. This difference occurs because society reallocates resources through the

predicted market adjustments that result from the regulation-induced increase in coke

production costs. 

In the final product markets, higher market prices lead to consumers of steel mill

products experiencing losses of $20.9 million. Although integrated iron and steel producers

are able to pass on a limited amount of cost increases to their final consumers, e.g.,

automotive manufactures and construction industry, the increased costs result in a net decline

in profits at integrated mills of $22.4 million. 
4-17

In the coke industry, low-cost merchant producers of furnace coke benefit at the

expense of consumers and higher-cost coke batteries resulting in an industry-wide increase in

profits. Furnace coke profits at merchant plants increase in aggregate by $9.7 million. In

contrast, foundry coke profits at merchant plants decline in aggregate by $5 million. 

Lastly, domestic producers not subject to the regulation (i.e., nonintegrated steel mills

and electric furnaces) as well as foreign producers experience unambiguous gains because

they benefit from increases in market price under both alternatives. 
5-1

SECTION 5

SMALL BUSINESS IMPACTS

This regulatory action will potentially affect the economic welfare of owners of coke

batteries. These individuals may be owners/operators who directly conduct the business of

the firm or, more commonly, investors or stockholders who employ others to conduct the

business of the firm on their behalf through privately held or publicly traded corporations. 

The legal and financial responsibility for compliance with a regulatory action ultimately rests

with plant managers, but the owners must bear the financial consequences of the decisions.

Although environmental regulations can affect all businesses, small businesses may have

special problems complying with such regulations.

The Regulatory Flexibility Act (RFA) of 1980 requires that special consideration be

given to small entities affected by federal regulations. The RFA was amended in 1996 by the

Small Business Regulatory Enforcement Fairness Act (SBREFA) to strengthen its analytical

and procedural requirements. Under SBREFA, the Agency must perform a regulatory

flexibility analysis for rules that will have a significant impact on a substantial number of

small entities.

This section focuses on the compliance burden of the small businesses with the coke

manufacturing industry and provides a screening analysis to determine whether this final rule

is likely to impose a significant impact on a substantial number of the small entities

(SISNOSE) within this industry. The screening analysis employed here is a “sales test” that

computes the annualized compliance costs as a share of sales for each company. In addition,

it provides information about the impacts on small businesses after accounting for producer

responses to the final rule and the resulting changes in market prices and output.

5.1 Identifying Small Businesses

The SBA released guidelines effective October 2000 that provide small business

thresholds based on NAICS codes that replace the previous thresholds based on SIC codes. 

Under these new guidelines, SBA establishes 1,000 or fewer employees as the small business

threshold for Iron and Steel Mills (i.e., NAICS 331111), while coke ovens not integrated

with steel mills are classified under All Other Petroleum and Coal Products Manufacturing
1

Annualized capital costs include purchased equipment costs (PEC), direct costs for installation (DCI), and

indirect costs for installation (ICI) related to engineering and start up. Operating and maintenance costs

include direct annual costs (DAC), such as catalysis replacement, increased utilities, and increased labor,

and indirect annual costs (IAC), such as costs due to tax, overhead, insurance, and administrative burdens.

5-2

(i.e., NAICS 324199) with a threshold of 500. Based on these SBA size definitions for the

affected industries and reported sales and employment data, as described in Section 2, the

Agency has identified three of the 14 companies as small businesses (i.e., 21 percent). The

following businesses were identified as small for the purpose of this analysis: 

 Citizen’s Gas and Coke,

 Shenango Group, Inc., and

 Tonawanda Coke Corporation. 

Each of these small companies owned and operated a coke plant with a total of seven coke

batteries, or roughly 14 percent of all the coke batteries operated in 2002. 

5.2 Screening-Level Analysis

To assess the potential impact of this rule on small businesses, the Agency calculated

the share of annual compliance costs relative to baseline sales for each company. When a

company owns more than one affected facility, EPA combined the costs for each facility for

the numerator of the test ratio. Annual compliance costs include annualized capital costs and

operating and maintenance costs imposed on these companies.1

 They do not include changes

in production or market adjustments. 

Small businesses represent 21 percent of the companies within the source category

and are expected to incur 19 percent of the total industry compliance costs of $20.2 million

(see Table 5-1). The average total annual compliance cost is projected to be $1.3 million per

small company, while the average for large companies is projected to be $1.5 million per

company. The mean (median) cost-to-sales ratio for small businesses is 2.0 percent (1.8

percent), with a range of 0.3 to 5.0 percent. EPA estimates that one of the two small

businesses may experience an impact between 1 percent and 3 percent of sales, and one small

business will experience an impact greater than 3 percent of sales. In contrast, all of the

large companies are affected at less than 1 percent of sales.
5-3

Table 5-1. Summary Statistics for SBREFA Screening Analysis: 2000

Small Large All Companies

Total Number of Companies 3 11 14Total Annual Compliance Costs (TACC)($106/yr)

$3.8 $16.4 $20.2

Average TACC per company ($106/yr) $1.3 $1.5 $1.4

Compliance Cost-to-Sales Ratios

Average 2.04% 0.09% 0.51%Median 1.83% 0.08% 0.13%Minimum 0.31% <0.01% <0.01%Maximum 4.97% 0.25% 3.97%

Number Share Number Share Number Share

Compliance costs are <1% of sales 1 33% 11 100% 12 86%Compliance costs are 1 to 3% of sales 1 33% 0 0% 1 7%

Compliance costs are 3% of sales 1 33% 0 0% 1 7%

Note: Assumes no market responses (i.e., price and output adjustments) by regulated entities.
2

Furthermore, the QFR reports that companies within the iron and steel industry of less than $25 million in

assets reported an average return to sales ranging from 6.8 to 9.8 percent.

5-4

5.3 Economic Analysis

The Agency also analyzed the economic impacts on small businesses under withregulation conditions expected to result from implementing the MACT. Unlike the screening

analysis, this approach examines small business impacts in light of the behavioral responses

of producers and consumers to the regulation. As shown in Table 5-2, the economic model

projects operating profits increase by $0.3 million for the furnace coke plant operated by a

small business. For this plant, furnace coke price increases outweigh the additional costs

associated with the MACT. In contrast, the model projects operating profits decrease by

$2.4 million for foundry coke plants operated by small firms. In this case, foundry coke

plants fully absorb additional control costs. No batteries (furnace or foundry) are projected

to prematurely close as a result of the additional control costs associated with the regulation.

5.4 Assessment

Based on the Quarterly Financial Report (QFR) from the U.S. Bureau of the Census,

the average return to sales for all reporting companies within the iron and steel industry

ranged from 3.2 to 4.6 percent (U.S. Bureau of the Census, 1998).2

 In addition, Dun &

Bradstreet reports the median return on sales as 3.7 percent for SIC 3312—Steel Works,

Blast Furnaces (including Coke Ovens), and Rolling Mills (Dun & Bradstreet, 1997). 

Although this industry is typically characterized by average profit margins, the Agency’s

analysis indicated that none of the coke manufacturing facilities owned by small businesses

are at risk of closure because of the final rule. In fact, the furnace coke plant is projected to

become more profitable in profits because of market feedbacks related to higher costs

incurred by competitors, while the six plants manufacturing foundry coke are projected to

experience a decline in profits of slightly less than 5 percent. In summary, this analysis

supports certification under the RFA because, while a few small firms may experience initial

impacts greater than 1 percent of sales, the Agency’s economic analysis indicates no

significant impacts on their viability to continue operations and remain profitable. 
5-5

Table 5-2. Small Business Impacts of the Final Coke MACT: 2000

Baseline

Changes From Baseline

Absolute Percent

Coke Plants (Merchant Only)

Furnace

Revenues ($106

/yr) $42.7 $1.1 2.7%

Costs ($106

/yr) $40.9 $0.9 2.2%

Control costs $0.0 $0.9 NA

Production costs $40.9 $0.0 0.0%

Operating profits ($106

/yr) $1.8 $0.3 13.9%

Coke batteries (#) 1 0 0.0%

Employment (FTEs) 175 0 0.0%

Foundry

Revenues ($106

/yr) $139.3 $0.6 0.4%

Costs ($106

/yr) $86.8 $2.9 3.4%

Control costs $0.0 $2.9 NA

Production costs $86.8 $0.0 0.0%

Operating profits ($106

/yr) $52.4 –$2.4 –4.5%

Coke batteries (#) 6 0 0.0%

Employment (FTEs) 1,760 0 0.0%

Total

Revenues ($106

/yr) $182.0 $1.7 0.9%

Costs ($106

/yr) $127.7 $3.8 3.0%

Control costs $0.0 $3.8 NA

Production costs $127.7 $0.0 0.0%

Operating profits ($106

/yr) $54.3 –$2.1 –3.9%

Coke batteries (#) 7 0 0.0%

Employment (FTEs) 1,935 0 0.0%
R-1

REFERENCES

Agarwal, Jay, Francis Brown, David Chin, Gregory Stevens, Richard Clark, and David

Smith. 1996. “The Future Supply of Coke.” New Steel 12(3):88.

Association of Iron and Steel Engineers (AISE). 1998. “1998 Directory of Iron and Steel

Plants: Volume 1 Plants and Facilities.” Pittsburgh, PA: AISE.

American Metal Market. 1998. “LTV, USW Eye Coke Plant Site.” 106(37):3.

Bingham, T.H., and T.J. Fox. 1999. “Model Complexity and Scope for Policy Analysis.” 

Public Administration Quarterly 23(3). 

Dun & Bradstreet. 1997. Industry Norms & Key Business Ratios: Desk-Top Edition 1996-

97. Murray Hill, NJ: Dun & Bradstreet.

Engineering and Mining Journal. 1997. “A New U.S. Trend? No Leftovers—No

Problems.” 198(10):WW15.

Graham, Paul, Sally Thorpe, and Lindsay Hogan. 1999. “Non-competitive Market Behavior

in the International Coking Coal Market.” Energy Economics 21:195-212.

Ho, M., and D. Jorgenson. 1998. “Modeling Trade Policies and U.S. Growth: Some

Methodological Issues.” Presented at USITC Conference on Evaluating APEC Trade

Liberalization: Tariff and Nontariff Barriers. September 11-12, 1997. 

Hogan, William T., and Frank T. Koelble. 1996. “Steel’s Coke Deficit: 5.6 Million Tons

and Growing.” New Steel 12(12):50-59.

Lankford, William T., Norman L. Samways, Robert F. Craven, and Harold E. McGannon,

eds. 1985. The Making, Shaping and Treating of Steel. Pittsburgh: United States

Steel, Herbick & Held.

National Steel. Web homepage. <http://www.nationalsteel.com/>. As obtained in

September 1998.

New Steel. August 1997a. “LTV will Close Pittsburgh Coke Plant.”

New Steel. June 1997b. “National will Sell Ecorse Coke Battery.”

New Steel. August 10, 1998a. “ Bethlehem Sells Coke Battery.”

New Steel. January 1998b. “Bethlehem will Shut Down Coke Division.”

Ninneman, Patrick. 1997. “Less Coke and More Coal in the Blast Furnace.” New Steel

13(7):38-45.
R-2

U.S. Bureau of the Census. 1998. Quarterly Financial Report for Manufacturing, Mining,

and Trade Corporations. First Quarter, Series QFR 98-1. Washington, DC: 

Government Printing Office. 

U.S. Department of Energy. 1996. Coal Industry Annual 1995. Washington, DC: Energy

Information Administration.

U.S. Department of Energy. “AER Database: Coke Overview, 1949-1997.” Washington,

DC: Energy Information Administration. <http://tonto.eia.doe.gov/aer/

aer-toc-d.cfm>. As obtained on September 14, 1998a.

U.S. Department of Energy, Energy Information Administration. 2001. Electric Power

Annual 2000. 

U.S. Department of Energy, Energy Information Administration. 2002. Quarterly Coal

Report: January–March 2002. Washington, DC: U.S. Department of Energy. 

<http://www.eia.doe.gov/cneaf/coal/quarterly/qcr_sum.html>. 

U.S. Department of Labor, Bureau of Labor Statistics. BLS LABSTAT Database: 

Employment and Earnings, SIC 33. <http://www.bls.gov>. Obtained in September

1998.

U.S. Environmental Protection Agency. 1979. Technical Approach for a Coke Production

Cost Model. Prepared by Research Triangle Institute, Research Triangle Park, N.C. 

U.S. Environmental Protection Agency. 1988. Benzene Emissions form Coke By-Product

Recovery Plants-BackGround Information for Proposed Standards. Office of Air

Quality Planning and Standards, Research Triangle Park, NC.

U.S. Environmental Protection Agency. 1991. Controlling Emissions from By-Product

Coke Oven Charging, Door Leaks, and Topside Leaks: An Economic Impacts

Analysis. Prepared by Research Triangle Institute, Research Triangle Park, NC.

U.S. Environmental Protection Agency. 1998. Coke Industry Responses to Information

Collection Request (ICR) Survey. Database prepared for EPA’s Office of Air Quality

Planning and Standards. Research Triangle Park, NC.

U.S. Environmental Protection Agency (EPA). 1999. OAQPS Economic Analysis Resource

Document. Durham, NC: Innovative Strategies and Economics Group.

U.S. International Trade Commission. 1994. Metallurgical Coke: Baseline Analysis of the

U.S. Industry and Imports. Publication No. 2745. Washington, DC: U.S.

International Trade Commission.

U.S. International Trade Commission (USITC). July 2000. “Foundry Coke: A Review of

the Industries in the United States and China.”

<http://www.usitc.gov/sec/I0917W1.htm>.
R-3

U.S. International Trade Commission (USITC). 2001a. Memorandum to the Commission

from Craig Thomsen, John Giamalua, John Benedetto, Joshual Levy, International

Economists. Investigation No. TA-201-73: STEEL—Remedy Memorandum. 

November 21, 2001. 

U.S. International Trade Commission (USITC). 2001b. “Foundry Coke from China.” 

Investigation No. 731-ta-891 (Final) Publication 3449; September 2001. 

<http://www.usitc.gov/wais/reports/arc/w3449.htm>. 

U.S. International Trade Commission (USITC). 2001c. “Blast Furnace Coke from China

and Japan.” Investigations Nos. 731-TA-951-952 (Preliminary) Publication 3444;

August 2001. <http://www.usitc.gov/wais/reports/arc/w3449.htm>. 
A-1

APPENDIX A

ECONOMIC IMPACT ANALYSIS METHODOLOGY

This appendix provides the methodology for analyzing the economic impacts of the 

coke ovens, integrated iron and steel MACT, and iron foundry MACT standards to ensure

consistency across the EIAs for each of these MACT standards. Implementation of this

methodology provided the economic data and supporting information that EPA requires to

support its regulatory determination. This approach is firmly rooted in microeconomic

theory and the methods developed for earlier EPA studies to operationalize this theory. The

Agency employed a computerized market model of the coke, steel mill products, and iron

castings industries to estimate the behavioral responses to the imposition of regulatory costs

and, thus, the economic impacts of the standard. The market model captures the linkages

between these industries through changes in equilibrium prices and quantities. 

This methodology section describes the conceptual approach selected for this EIA. 

For each product market included in the analysis, EPA derived facility-level supply functions

and demand functions that are able to account for the behavioral response and market

implications of the regulatory costs. Finally, this appendix presents an overview of the

specific functional forms that constitute the Agency’s computerized market model.

A.1 Overview of Economic Modeling Approach

In general, the EIA methodology needs to allow EPA to consider the effect of the

different regulatory alternatives. Several types of economic impact modeling approaches

have been developed to support regulatory development. These approaches can be viewed as

varying along two modeling dimensions:

 the scope of economic decision making accounted for in the model, and

 the scope of interaction between different segments of the economy.

Each of these dimensions was considered in selecting the approach used to model the

economic impact of the regulation. Bingham and Fox (1999) provide a useful summary of

these dimensions as they relate to modeling the outcomes of environmental regulations.
A-2

For this analysis, prices and quantities are determined in perfectly competitive

markets for furnace coke, foundry coke, steel mill products, and iron castings. The Agency

analyzed the impact of the regulation using a market modeling approach that incorporates

behavioral responses in a multiple-market partial equilibrium model. Multiple-market partial

equilibrium analysis accounts for the interactions between coke, steel mill product, and iron

castings markets into the EIA to better estimate the regulation’s impact. The modeling

technique is to link a series of standard partial equilibrium models by specifying the

interactions between the supply and demand for products and then solving for changes in

prices and quantities across all markets simultaneously. 

Figure A-1 summarizes the market interactions included in the Agency’s EIA

modeling approach. Changes in the equilibrium price and quantity due to control costs

associated with individual MACTs were estimated simultaneously in four linked markets:

 market for furnace coke,

 market for foundry coke, 

 market for steel mill products, and

 market for iron castings.

As described in Section 2 of this EIA report, many captive coke plants supply their

excess furnace coke to the market. Merchant coke plants and foreign imports account for the

remaining supply to the furnace coke market. Furnace coke produced at captive coke plants

and shipped directly to integrated iron and steel mills owned by their parent companies does

not directly enter the market for furnace coke. However, compliance costs incurred by these

captive, or “in-house,” furnace coke batteries indirectly affect the furnace coke market

through price and output changes in the steel mill products market. 

The market demand for furnace coke is derived from integrated mills producing steel

mill products. Integrated iron and steel mills that need more coke than their captive batteries

can produce will purchase furnace coke from the market. Integrated mills’ market demand

for furnace coke depends on their production levels as influenced by the market for steel mill

products. Steel mill products are supplied by three sources: integrated iron and steel mills,

nonintegrated steel mills (primarily minimills), and imports. Domestic consumers of steel

mill products and exports account for the market demand.
A-3

Merchant Coke Plants

• Finishing Mills

• Steelmaking Furnace

• Blast Furnace

Captive Coke Plants

Market for

Foundry Coke

Consumers of Steel

Mill Products

Imports

Imports

Exports

Integrated Iron

and Steel Mills

Exports

Market for

Furnace Coke

Electric

Furnaces

Consumers of

Iron Castings

Cupola Furnaces

Control Costs

Coke MACT

Market for

Steel

Mill Products

Nonintegrated

Steel Mills

(including

minimills)

Market for

Iron Castings

Imports

Exports

Control Costs

Iron and Steel

Foundry MACT

Control Costs

Integrated Iron

and Steel MACT

Figure A-1. Market Linkages Modeled in the Economic Impact Analysis

Domestic merchant plants are the primary suppliers of foundry coke to the market. 

However, the U.S. International Trade Commission (2000) has documented an increasing

trend in foreign imports of foundry coke from China. Therefore, we have included a single

import supply curve to characterize this supply segment. 

In addition to furnace and foundry coke, merchant and captive coke plants sell a byproduct referred to as “other coke” that is purchased as a fuel input by cement plants,

chemical plants, and nonferrous smelters. Because “other coke” is a by-product and

represented only 2 percent of U.S. coke production in 1997 it is not formally characterized

by supply and demand in the market model. Revenues from this product are accounted for

by assuming its volume is a constant proportion of the total amount of coke produced by a

battery and sold at a constant price.
A-4

A.2 Conceptual Market Modeling Approach

This section examines the impact of the regulations on the production costs for

affected facilities, both merchant and captive. It provides an overview of the basic economic

theory of the effect of regulations on facility production decisions and the concomitant effect

on market outcomes. Following the OAQPS Economic Analysis Resource Document (EPA,

1999), we employed standard concepts in microeconomics to model the supply of affected

products and the impacts of the regulations on production costs and the operating decisions. 

The approach relies heavily on previous economic analyses, employs a comparative static

approach, and assumes certainty in relevant markets. The three main elements of the

analysis are regulatory effects on the manufacturing facility, market responses, and

facility–market interactions. The remainder of this section describes each of these main

elements.

A.2.1 Facility-level Responses to Control Costs 

Individual plant-level production decisions were modeled to develop the market

supply and demand for key industry segments in the analysis. Production decisions were

modeled as intermediate-run decisions, assuming that the plant size, equipment, and

technologies are fixed. For example, the production decision typically involves (1) whether

a firm with plant and equipment already in place purchases inputs to produce output and (2)

at what capacity utilization the plant should operate. A profit-maximizing firm will operate

existing capital as long as the market price for its output exceeds its per-unit variable

production costs, since the facility will cover not only the cost of its variable inputs but also

part of its capital costs. Thus, in the short run, a profit-maximizing firm will not pass up an

opportunity to recover even part of its fixed investment in plant and equipment. 

The existence of fixed production factors gives rise to diminishing returns to those

fixed factors and, along with the terms under which variable inputs are purchased, defines

the upward-sloping form of the marginal cost (supply) curve employed for this analysis. 

Figure A-2 illustrates this derivation of the supply function at an individual mill based on the

classical U-shaped cost structure. The MC curve is the marginal cost of production, which

intersects the facility’s average variable (avoidable) cost curve (AVC) and its average total

cost curve (ATC) at their respective minimum points. The supply function is that portion of

the marginal cost curve bounded by the minimum economically feasible production rate (qm)

and the technical capacity (qM). A profit-maximizing producer will select the output rate

where marginal revenue equals price, that is, at [P*, q*]. If market price falls below ATC, 
A-5

AVC

ATC

$/q

q q/t m qM q

P

MC

Figure A-2. Product Supply Function at Facility

then the firm’s best response is to cease production because total revenue does not cover total

costs of production. 

Now consider the effect of the regulation and the associated compliance costs. 

These fall into one of two categories: avoidable variable and avoidable nonvariable. These

final costs are characterized as avoidable because a firm can choose to cease operation of the

facility and, thus, avoid incurring the costs of compliance. The variable control costs include

the operating and maintenance costs of the controls, while the nonvariable costs include

compliance capital equipment. Figure A-3 illustrates the effect of these additional costs on

the facility supply function. The facility’s AVC and MC curves shift upward (to AVCand

MC) by the per-unit variable compliance costs. In addition, the nonvariable compliance

costs increase total avoidable costs and, thus, the vertical distance between ATCand AVC. 

The facility’s supply curve shifts upward with marginal costs and the new (higher) minimum

operating level (q) is determined by a new (higher) ps.

Next consider the effect of compliance costs on the derived demand for inputs at the

regulated facility. Integrated iron and steel mills are market demanders of furnace coke,

while foundries with cupola furnaces are market demanders of foundry coke. We employ

similar neoclassical analysis to that above to demonstrate the effect of the regulation on the

demand for market coke inputs, both furnace and foundry. Figure A-4 illustrates the derived
A-6

q m

$/q

MC

q M

P m

q m′

MC′

P m′

q/t

ATC′

AVC′

ATC

AVC

Figure A-3. Effect of Compliance Costs on Product Supply Function at Facility

demand curve for coke inputs. Each point on the derived demand curve equals the

willingness to pay for the corresponding marginal input. This is typically referred to as the

input’s value of marginal product (VMP), which is equal to the price of the output (P) less

the per-unit compliance cost (c) times the input’s “marginal physical product” (MPP), which

is the incremental output attributable to the incremental inputs. If, as assumed in this

analysis, the input-output relationship between the market coke input and the final product

(steel mill products or iron castings) is strictly fixed, then the VMP of the market coke is

constant and the derived demand curve is horizontal with the constant VMP as the vertical

intercept, as shown in Figure A-4. Ignoring any effect on the output price for now, an

increase in regulatory costs will lower the VMP of all inputs leading to a downward shift in

the derived demand in Figure A-4 from Dy to .
A-7

1 Dy

$/qy

q/ty

Dy

Figure A-4. Derived Demand Curve for Coke Inputs

A.2.2 Market Effects

To evaluate the market impacts, the economic analysis assumes that prices and

quantities are determined in a competitive market (i.e., individual facilities have negligible

power over the market price and thus take the price as “given” by the market). As shown in

Figure A-5(a), under perfect competition, market prices and quantities are determined by the

intersection of market supply and demand curves. The initial baseline scenario consists of a

market price and quantity (P, Q) that is determined by the downward-sloping market demand

curve (DM) and the upward-sloping market supply curve (SM) that reflects the horizontal

summation of the individual producers’ supply curves.

Now consider the effect of the regulation on the baseline scenario as shown in

Figure A-5(b). In the baseline scenario without the standards, at the projected price, P, the

industry would produce total output, Q, with affected facilities producing the amount qa and

unaffected facilities accounting for Q minus qa, or qu. The regulation raises the production

costs at affected facilities, causing their supply curves to shift upward from Sa to Saand the

market supply curve to shift upward to SM. At the new with-regulation equilibrium with the

regulation, the market price increases from P to Pand market output 
A-8

p

Sa

qa qu Q

Affected Facilities

Su SM

DM

+ = p p

Unaffected Facilities Market

a) Baseline Equilibrium

p

q′

a qu Q′

Affected Facilities

Su SM′

DM

+ = p p

Unaffected Facilities Market

b) With-Regulation Equilibrium

p′

Sa

qa q′

u Q

SM

p′ p′

S′

a

Figure A-5. Market Equilibrium without and with Regulation
A-9

(as determined from the market demand curve, DM) declines from Q to Q. This reduction in

market output is the net result from reductions at affected facilities and increases at

unaffected facilities. Unaffected facilities do not incur the increased costs due to regulation

so their response to higher product prices is to increase production. Foreign suppliers (i.e.,

imports), which also do not face higher costs, will respond in the same manner as these

unaffected producers.

The above description is typical of the expected market effects for final product

markets. The regulations would potentially affect the costs of producing steel mill products

through additional control costs and increases in the market price of furnace coke and the

cost of producing captive furnace coke. The increase in control costs, the market price, and

captive production costs for furnace coke result in an upward shift in the supply functions of

integrated iron and steel mills, while nonintegrated and foreign suppliers are unaffected. 

Additionally, the regulations would potentially affect the costs of producing iron castings

through additional control costs and changes in the market price of foundry coke. This

results in an upward shift in supply functions of foundries operating cupola furnaces, while

foundries operating electric furnaces are only affected to the extent they are subject to

additional control costs.

However, there are additional impacts on the furnace and foundry coke markets

related to their derived demand as inputs to either the production of steel mill products or

iron castings. Figure A-6 illustrates, under perfect competition, the baseline scenario where

the market quantity and price of the final steel mill product or iron casting, Qx(Qx0, Px0), are

determined by the intersection of the market demand curve (Dx) and the market supply curve

(Sx), and the market quantity and price of furnace or foundry coke, Qy(Qy0, Py0), are

determined by the intersection of the market demand curve (Dy) and market supply curve

(Sy). Given the derived demand for coke, the demanders of coke, Qy, are the individual

facilities that purchase coke for producing their final products (i.e., integrated steel mills in

the case of furnace coke or foundries with cupola furnaces in the case of foundry coke).

Imposing the regulations increases the costs of producing coke and, thus, the final

product, shifting the market supply functions for both commodities upward to Sxand Sy,

respectively. The supply shift in the final product market causes the market quantity to fall

to Qx1 and the market price to rise to Px1 in the new equilibrium. In the market for coke, the

reduced production of the final product causes a downward shift in the demand curve (Dy)

with an unambiguous reduction in coke production, but the direction of the change in market 
A-10

(a) Market for single steel mill product or iron casting, Qx

(b) Market for coke input, Qy

$/Qx

Px1

Px0

Qx1 Qx0 Qx/t

Dx

Sx

Sx′

$/Qy Sy

′

Dy

Sy

Qy1 Qy3 Qy2 Qy0 Qy/t

Dy′′

Dy

′

Dy′′′

Py1

Py2

Py3 = Py0

Figure A-6. Market Equilibria With and Without Compliance Costs
A-11

price is determined by the relative magnitude of the demand and supply shift. If the

downward demand effect dominates, the price will fall (e.g., Py1); however, if the upward

supply effect dominates, the price will rise (e.g., Py2). Otherwise, if the effects just offset

each other, the price remains unchanged (e.g., Py3 = Py0).

A.2.3 Facility-Level Responses to Compliance Costs and New Market Prices

In evaluating the market effects, we must distinguish between the initial effect of the

regulations and the net effect after all markets have adjusted. The profit-maximizing

behavior of firms, as described above, may lead to changes in output that, when aggregated

across all producers, lead to changes in the market-clearing price and feedback on the firms

to alter their decisions. These adjustments are characterized as a simultaneous interaction of

producers, consumers, and markets. Thus, to evaluate the facility-market outcomes, the

analysis must go beyond the initial effect of the regulation and estimate the net effect after

markets have fully adjusted.

Given changes in the market prices and costs, each facility will elect to either

 continue to operate, adjusting production and input use based on new revenues

and costs, or

 cease production at the facility if total revenues do not exceed total costs.

This decision can be extended to those facilities with multiple product lines or operations

(e.g., coke batteries, blast furnaces, cupolas). If product revenues are less than productspecific costs, then these product-lines or operations may be closed.

Therefore, after accounting for the facility-market interaction, the operating decisions

at each individual facility can be derived. These operating decisions include whether to

continue to operate the facility (i.e., closure) and, if so, the optimal production level based on

compliance costs and new market prices. The approach to modeling the facility closure

decision is based on conventional microeconomic theory. This approach compares the

ATC—which includes all cost components that fall to zero when production

discontinues—to the expected post-regulatory price. Figure A-3 illustrates this comparison. 

If price falls below the ATC, total revenue would be less than the total costs. In this

situation, the owner’s cost-minimizing response is to close the facility. Therefore, as long as

there is some return to the fixed factors of production— that is, some positive level of

profits— the firm is expected to continue to operate the facility.
A-12

If the firm decides to continue operations, then the facility’s decision turns to the

optimal output rate. Facility and product-line closures, of course, directly translate into

reductions in output. However, the output of facilities that continue to operate will also

change depending on the relative impact of compliance costs and higher market prices. 

Increases in costs will tend to reduce producers’ output rates; however, some of this effect is

mitigated when prices are increased. If the market price increase more than offsets the

increase in unit costs, then even some affected facilities could respond by increasing their

production. Similarly, supply from unaffected domestic producers and foreign sources will

respond positively to changes in market prices.

A.3 Operational Economic Model

Implementation of the MACT standards will affect the costs of production for plants

across the United States subject to the rule. Responses at the facility-level to these additional

costs will collectively determine the market impacts of the rule. Specifically, the cost of the

regulation may induce some facilities to alter their current level of production or to cease

operations. These choices affect and, in turn are affected by, the market price of each

product. As described above, the Agency has employed standard microeconomic concepts to

model the supply and demand of each product and the impacts of the regulation on

production costs and the output decisions of facilities. The main elements of the analysis are

to

 characterize production of each product at the individual supplier and market

levels,

 characterize the demand for each product, and

 develop the solution algorithm to determine the new with-regulation equilibrium.

The following sections provide the supply and demand specifications for each product

market as implemented in the EIA model and summarize the model’s solution algorithm. 

Supply and demand elasticities used in the model are presented in Table A-1.

A.3.1 Furnace Coke Market

The market for furnace coke consists of supply from domestic coke plants, both

merchant and captive, and foreign imports and of demand from integrated steel mills and

foreign exports. The domestic supply for furnace coke is modeled as a stepwise supply

function developed from the marginal cost of production at individual furnace coke batteries. 

The domestic demand is derived from iron and steel production at integrated mills as 
A-13

Table A-1. Supply and Demand Elasticities Used in Analysis

Market Supply Elasticity Demand Elasticity

Furnace Coke

Domestic 2.1a Derived demand

Foreign 3.0b –0.3b

Foundry Coke

Domestic 1.1a Derived demand

Foreign 3.0b –0.3b

Steel Mill Products

Domestic 3.5c –0.59d

Foreign 1.5c –1.25e

Iron Castings

Domestic 1.0f –0.58d

Foreign 1.0f –1.0f

a Estimate based on individual battery production costs and output. b Graham, Thorpe, and Hogan (1999). c U.S. International Trade Commission (USITC). 2001a. Memorandum to the Commission from Craig

Thomsen, John Giamalua, John Benedetto, and Joshua Level, International Economists. Investigation

No. TA-201-73: STEEL—Remedy Memorandum. November 21, 2001. d Econometric analysis (see Appendixes C and D for details). e Ho, M., and D. Jorgenson. 1998. “Modeling Trade Policies and U.S. Growth: Some Methodological

Issues.” Presented at USITC Conference on Evaluating APEC Trade Liberalization: Tariff and Nontariff

Barriers. September 11-12, 1997. f Assumed value.

(A.1)

determined through the market for steel mill products and coking rates for individual

batteries. The following section details the market supply and demand components for this

analysis.

A.3.1.1 Market Supply of Furnace Coke

The market supply for furnace coke, QSc, is the sum of coke production from

merchant facilities, excess production from captive facilities (coke produced at captive

batteries less coke consumed for internal production on steel mill products), and foreign

imports, i.e., 
A-14

(A.2)

(A.3)

where

= furnace coke supply from merchant plants,

= furnace coke supply from integrated steel mills, and

= furnace coke supply from foreign sources (imports).

Supply from Merchant and Captive Coke Plants. The domestic supply of furnace

coke is composed of the supply from merchant and captive coke plants reflecting plant-level

production decisions for individual coke batteries. For merchant coke plants the supply is

characterized as

where

= supply of foundry coke from coke battery (j) at merchant plant (l).

Alternatively, for captive coke plants the supply is characterized as the furnace coke

production remaining after internal coke requirements are satisfied for production of final

steel mill products, i.e, 

where

= the furnace coke production from captive battery (j) at integrated steel

mill (l);
1

The furnace coke rate for each integrated steel mill is taken from Hogan and Koelble (1996). The coke rate is

assumed to be constant with respect to the quantity of finished steel products produced at a given mill. A

constant coke rate at each integrated mill implies a constant efficiency of use at all output levels and

substitution possibilities do not exist given the technology in place at integrated mills. Furthermore, the

initial captive share of each integrated mill’s coke requirement is based on the baseline data from the EPA

estimates.

A-15

= the coke rate for integrated steel mill (l), which specifies the amount of

furnace coke input per unit of final steel mill product;1 and

= supply of steel mill product from integrated mill (l). 

The MAX function in Eq. (A.3) indicates that if the total captive production of furnace coke

at an integrated mill is greater than the amount of furnace coke consumption required to

produce steel mill products, then supply to the furnace coke market will equal the difference;

otherwise, the mill’s supply to the furnace coke market will be zero (i.e., it only satisfies

internal requirements from its captive operations).

As stated above, the domestic supply of furnace coke is developed from plant-level

production decisions for individual coke batteries. For an individual coke battery the

marginal cost was assumed to be constant. Thus, merchant batteries supply 100 percent of a

battery’s capacity to the market if the battery’s marginal cost (MC) is below the market price

for furnace coke (pc), or zero if MC exceeds pc. Captive batteries first supply the furnace

coke demanded by their internal steelmaking requirements. Any excess capacity will then

supply the furnace coke market if the remaining captive battery’s MC is below the market

price. 

Marginal cost curves were developed for all furnace coke batteries at merchant and

captive plants in the United States as detailed in Appendix B. Production costs for a single

battery are characterized by constant marginal cost throughout the capacity range of the

battery. This yields the inverted L-shaped supply function shown in Figure A-7(a). In this

case, marginal cost (MC) equals average variable cost (AVC) and is constant up to the

production capacity given by q. The supply function becomes vertical at q because

increasing production beyond this point is not possible. The minimum economically

achievable price level is equal to p*. Below this price level, p* is less than AVC, and the

supplier would choose to shut down rather than to continue to produce coke. 
A-16

(a) Inverted L-Shaped Supply Function at Single-Battery Plant

(b) Inverted L-Shaped Supply Functions at Multibattery Plant

$/q

S

AVC = MC

q/t q

$/q

S

MC battery 1

q/t q

(c) Stepwise Market Supply Curve

q

$/q

MC battery 2

p*

Figure A-7. Facility-Level Supply Functions for Coke
A-17

(A.4)

(A.5)

A stepwise supply function can be created for each facility with multiple batteries by

ordering production from least to highest MC batteries (see Figure A-7[b]). For captive coke

plants, the lowest cost batteries are assumed to supply internal demand, leaving the higher

cost battery(ies) to supply the market if MC<P for the appropriate battery(ies). Similarly, a

stepwise aggregate domestic supply function can be created by ordering production from

least to highest MC batteries (see Figure A-7(c)). Based on this characterization of domestic

supply, a decrease in demand for furnace coke would then sequentially close batteries

beginning with the highest MC battery.

Foreign Supply of Furnace Coke. Foreign supply of furnace coke ( ) is expressed

as

where

= multiplicative parameter for the foreign furnace coke supply equation, and

= foreign supply elasticity for furnace coke.

The multiplicative parameter ( ) calibrates the foreign coke supply equation to replicate

the observed 2000 level of furnace coke imports based on the market price and the foreign

supply elasticity. 

A.3.1.2 Market Demand for Furnace Coke

Market demand for furnace coke (QDc) is the sum of domestic demand from

integrated steel mills and foreign demand (exports), i.e.,

where

= derived demand of furnace coke from integrated steel mills, and 
A-18

(A.6)

= foreign demand of furnace coke (exports).

Domestic Demand for Furnace Coke. Integrated steel mills use furnace coke as an

input to the production of finished steel products. Furnace coke demand is derived from the

final product supply decisions at the integrated steel mills. Once these final production

decisions of integrated producers have been made, the mill-specific coke input rate will

determine their individual coke requirements. Integrated steel mills satisfy their internal

requirements first through captive operations and second through market purchases. Thus,

the derived demand for furnace coke is the difference between total furnace coke required

and the captive capacity at integrated plants, i.e., 

= the coke rate for integrated steel mill (l), which specifies the amount of

furnace coke input per unit of final steel mill product;

= supply of steel mill product from integrated mill (l); and

= the furnace coke production from captive battery (j) at integrated steel mill

(l).

The MAX function in Eq. (A.3) indicates that if the amount of furnace coke consumption

required by an integrated mill to produce steel mill products is greater than its total captive

production, then demand from the furnace coke market will equal the difference; otherwise,

the mill’s demand from the furnace coke market will be zero (i.e., it fully satisfies internal

requirements from its captive operations). 

Increases in the price for furnace coke will increase the per-unit costs of final steel

products and thereby shift upward the integrated mill’s supply curve for steel mill products. 

The shift in the supply curve decreases the market quantity of finished steel products

produced, which subsequently reduces the quantity of furnace coke consumed at integrated

mills and shifts their demand curve downward in the furnace coke market.

Foreign Demand for Furnace Coke (Exports). Foreign demand for furnace coke is

expressed as
A-19

(A.7)

(A.8)

where

= multiplicative demand parameter for the foreign furnace coke demand

equation, and

= foreign demand elasticity for furnace coke.

The multiplicative demand parameter, , calibrates the foreign coke demand equation to

replicate the observed 2000 level of foreign exports based on the market price and the

foreign demand elasticity. 

A.3.2 Market for Steel Mill Products

The market for steel mill products consists of supply from domestic mills and foreign

imports and of demand from domestic and foreign consumers. Steel mill products are

modeled as a single commodity market. The domestic supply for steel mill products includes

production from integrated mills operating blast furnaces that require furnace coke and from

nonintegrated mills that operate electric arc furnaces that do not. The coke oven NESHAP is

expected to increase the cost of furnace coke inputs. In addition, the integrated iron and steel

NESHAP will also increase the costs of production leading to similar impacts. This will

increase the cost of production at integrated mills and thereby shift their supply curves

upward and increase the price of steel mill products. 

A.3.2.1 Market Supply of Steel Mill Products

The market supply for steel mill products (QSs) is defined as the sum of the supply

from integrated iron and steel mills, nonintegrated mills, and foreign imports, i.e.,

where

= supply of steel mill products from integrated mills;

= supply of steel mill products from the nonintegrated steel mills; and
A-20

(A.9)

(A.10)

= supply of steel mill products from foreign suppliers (imports).

Supply from Integrated Mills. Supply of steel mill products from integrated iron and

steel mills is the sum of individual mill production, i.e., 

where

= quantity of steel mill products produced at an individual integrated mill (l).

Integrated producers of steel mill products vary output as production costs change. 

As described above, upward-sloping supply curves were used to model integrated mills’

responses. For this analysis, the generalized Leontief technology is assumed to characterize

the production of steel mill products at each facility. This technology is appropriate, given

the fixed-proportion material input of coke and the variable-proportion inputs of labor,

energy, and raw materials. The generalized Leontief supply function is

where ps is the market price for the steel product, l

 and are model parameters, and l

indexes affected integrated mills. The theoretical restrictions on the model parameters that

ensure upward-sloping supply curves are l > 0 and < 0.

Figure A-8 illustrates the theoretical supply function of Eq. (A.6). As shown, the

upward-sloping supply curve is specified over a productive range with a lower bound of zero

that corresponds with a shutdown price equal to and an upper bound given by the

productive capacity of qM

l that is approximated by the supply parameter l

. The curvature of

the supply function is determined by the parameter. 

To specify the supply function of Eq. (A.6) for this analysis, the parameter was

computed by substituting a market supply elasticity for the product (), the market price of

the product (p), and the average annual production level across mills (q) into the following

equation:
A-21

$/q

q*

l  q/ t i

 = qM

i

p*

s

2

l

2

4

Figure A-8. Theoretical Supply Function for Integrated Facilities and Foundries

(A.11)

The parameter was calculated by incorporating market price and elasticity of supply values

into Eq. (A.11). 

The intercept of the supply function, l, approximates the productive capacity and

varies across products at each facility. This parameter does not influence the facility’s

production responsiveness to price changes as does the parameter. Thus, the parameter l

is used to calibrate the economic model so that each individual facility’s supply equation

matches its baseline production data from 2000.

Modeling the Impact of Compliance Costs. The effect of coke oven NESHAP is to

increase the MC of producing furnace coke by the compliance costs. These costs include the

variable component consisting of the operating and maintenance costs and the nonvariable

component consisting of the control equipment required for the regulatory option. 

Regulatory control costs will shift the supply curve upward for each affected facility by the
A-22

[ ] ( )

q

Ss

I

p r

s

I c pc

l

s

c

c l

( ) s

( )

1 2

1

1 11 1 1

= +

− +− −

























γ β

α α ∆ ∆

(A.12)

annualized compliance cost (operating and maintenance plus annualized capital) expressed

per unit of coke production. Computing the supply shift in this way treats compliance costs

as the conceptual equivalent of a unit tax on output. For coke facilities, the horizontal

portion of its supply curve will rise by the per-unit total compliance costs. In this case, the

MC curve will shift by this amount to allow the new higher reservation price for the coke

battery to appropriately reflect the fixed costs of compliance in the operating decision. At a

multiple-battery facility, the change in each battery’s MC may cause a reordering of the steps

because the compliance costs vary due to the technology, age, and existing controls of

individual batteries.

Compliance costs on captive furnace coke batteries will directly affect production

decisions at integrated mills, while compliance costs on merchant furnace coke batteries will

indirectly affect these decisions through the change in the market price of furnace coke. In

addition, direct compliance costs associated with the integrated iron and steel NESHAP will

directly affect production decisions at these mills. Both of these impacts were modeled as

reducing the net price integrated mills receive for steel mill products. Returning to the

integrated mill’s supply function presented in Eq. (A.10), the mill’s production quantity with

compliance costs is expressed as 

where

= the coke rate for integrated steel mill (l), which specifies the amount of

furnace coke input per unit of steel mill product; 

l = the share of integrated steel mill l’s furnace coke provided by captive

batteries;

∆c = change in per-unit cost of captive coke production at integrated steel mill l; l

c

(1–l) = share of integrated steel mill l’s furnace coke provided by the market; 

pc = change in the market price for furnace coke; and
2

The captive versus market furnace coke weights are endogenous in the model because integrated mills exhaust

their captive supply of coke first; hence, changes in coke consumption typically come from changes in

market purchases, while captive consumption remains relatively constant.

A-23

(A.13)

(A.14)

∆c = change in per-unit compliance cost at integrated steel mill l. l

s

The bracketed term in the denominator represents the increased costs due to the coke ovens

NESHAP and integrated iron and steel NESHAP, i.e., both the direct and indirect effects. 

The coke oven NESHAP compliance costs, and pc ∆c , are expressed per ton of furnace l

c

coke and weighted to reflect each integrated mill’s reliance on captive versus market furnace

coke.2

 The change in the cost per ton of furnace coke due to the regulation is then multiplied

by the mill’s coke rate to obtain the change in the cost per ton of steel mill product. The

integrated iron and steel NESHAP compliance costs are also expressed in cost per ton ∆cl

s

of steel mill product. These changes in the cost per ton of steel mill product correspond to the

shift in the affected facility supply curve shown in Figure A-5b.

Supply from Nonintegrated Mills. The supply of steel mill products from domestic

nonintegrated mills is specified as

where

= multiplicative parameter for nonintegrated mill supply equation, and 

= the nonintegrated mill supply elasticity for finished steel products. 

The multiplicative supply parameter is determined by backsolving Eq. (A.8), given baseline

values of the market price, supply elasticities, and quantities supplied by nonintegrated mills

and foreign mills.

Foreign Supply (Imports). The supply of steel mill products from foreign suppliers

(imports) is specified as
A-24

(A.15)

(A.16)

where

= multiplicative parameter for foreign supply equation, and 

= the foreign supply elasticity for finished steel products (assumed value = 1). 

The multiplicative supply parameters are determined by backsolving Eq. (A.8), given

baseline values of the market price, supply elasticity, and level of imports.

A.3.2.2 Market Demand for Steel Mill Products

The market demand for steel mill products, QDs, is the sum of domestic and foreign

demand, i.e., 

where

= domestic demand for steel mill products, and

= foreign demand for steel mill products (exports).

Domestic Demand for Steel Mill Products. The domestic demand for steel mill

products is expressed as

where

= multiplicative parameter for domestic steel mill products demand equation,

and

= domestic demand elasticity for steel mill products.

The multiplicative demand parameter calibrates the domestic demand equation given

baseline data on price and demand elasticity to replicate the observed 2000 level of domestic

consumption.
A-25

(A.17)

Q q q

Merchant q q sk M

Sk

F

Sk

l j Mlj

Sk

F

Sk = + =∑ ∑ (,) + (A.18)

Foreign Demand for Steel Mill Products (Exports). Foreign demand (exports) for 

steel mill products is expressed as

where

= multiplicative demand parameter for foreign steel mill products’ demand

equation, and

= foreign (export) demand elasticity for steel mill products.

The multiplicative demand parameter calibrates the foreign demand equation given data on

price and demand elasticities to replicate the observed 2000 level of foreign exports. 

A.3.3 Market for Foundry Coke

The market for furnace coke consists of supply from domestic merchant coke plants

and imports and demand from foundries operating cupola furnaces. The domestic supply for

foundry coke is modeled as a stepwise supply function developed from the marginal cost of

production at individual foundry coke batteries. Imports are modeled using a representative

supply curve. The domestic demand is derived from iron castings production at foundries

operating cupola furnaces (domestic and foreign) as determined through the market for iron

castings and coking rates. The following section details the market supply and demand

components for this analysis. 

A.3.3.1 Market Supply of Foundry Coke

The market supply of foundry coke, QSk, is composed of the supply from domestic

merchant plants reflecting plant-level production decisions for individual merchant coke

batteries, and a single representative foreign supply curve, i.e., 

where

l = plants
A-26

(A.19)

j = batteries

= supply of foundry coke from coke battery (j) at merchant plant (l)

q = foundry coke supply from imports F

Sk

As was the case for furnace coke batteries, the marginal cost for an individual foundry coke

battery is assumed to be constant reflecting a fixed-coefficient technology. Marginal cost

curves were developed for all foundry coke batteries at merchant plants in the United States

as detailed in Appendix B. 

Foundry coke production decisions are based on the same approach used to model

furnace coke production decisions. Thus, as illustrated previously in Figure A-7, the

production decision is determined by an inverted L-shaped supply curve that is perfectly

elastic to the capacity level of production and perfectly inelastic thereafter. Foundry coke

batteries will supply 100 percent of capacity if its marginal cost is less than market price;

otherwise, it will cease production. The regulatory costs shift each affected battery’s

marginal cost upward, affecting facilities’ decision to operate or shut down individual

batteries. 

Foreign Supply of Foundry Coke. Foreign supply of foundry coke ( ) is expressed

as

where

= multiplicative parameter for the foreign foundry coke supply equation, and

= foreign supply elasticity for foundry coke.

The multiplicative parameter ( ) calibrates the foreign coke supply equation to replicate

the observed 2000 level of foundry coke imports based on the market price and the foreign

supply elasticity. 
A-27

Q q q r q q Dk

CF

Dk

CFF

Dk

CF

i

CF

Si

CFF

Dk =+ = + (A.20)

(A.21)

A.3.3.2 Market Demand for Foundry Coke

The market demand for foundry coke, QDk, is composed of domestic and foreign

demand by foundries operating cupola furnaces. Therefore, the foundry coke demand is

derived from the production of iron castings from cupola furnaces. Increases in the price of

foundry coke due to the regulation will lead to decreases in production of iron castings at

foundries operating cupola furnaces. The demand function for foundry coke is expressed as

follows:

where

= derived demand for foundry coke from domestic cupola foundries;

q = demand for foundry coke from foreign cupola foundries; CFF

Dk

= the coke rate for cupola foundries, which specifies the amount of foundry

coke input per unit output; and

= quantity of iron castings produced at domestic cupola foundries;

Changes in production at foundries using electric arc and electric induction furnaces to

produce iron castings do not affect the demand for foundry coke. 

Foreign Demand for Foundry Coke (Exports). Foreign demand for foundry coke is

expressed as

where

= multiplicative demand parameter for the foreign foundry coke demand

equation, and

= foreign demand elasticity for foundry coke.
A-28

(A.22)

The multiplicative demand parameter, , calibrates the foreign coke demand equation to

replicate the observed 2000 level of foreign exports based on the market price and the

foreign demand elasticity. 

A.3.4 Market for Iron Castings

The market for iron castings consists of supply from domestic foundries and foreign

imports and of demand from domestic and foreign consumers. Iron castings are modeled as

a single commodity market. The domestic supply for iron castings includes production from

foundries operating cupola furnaces that require foundry coke and from foundries that

operate electric furnaces that do not. The rule is expected to increase production costs for

selected cupola and electric foundries and thereby shift their supply curves upward and

increase the price of iron castings.

A.3.4.1 Market Supply of Iron Castings

The market supply for iron castings, QSi, is defined as the sum of the supply from

domestic and foreign foundries. Domestic foundries are further segmented into operations

using foundry coke (referred to as cupola foundries) and operations using electric furnaces

(referred to as electric foundries). Supply is expressed as a function of the market price for

castings:

where

= quantity of iron castings produced at domestic cupola foundries,

= supply from domestic electric foundries, and

= supply from foreign foundries.

Domestic Foundries with Cupola Furnaces. The Agency used a simple supply

function to characterize the production of iron castings. Compliance costs on foundry coke

will directly affect cupola foundries’ production decisions and indirectly affect these

decisions through the changes in the market price of foundry coke. This impact is modeled

as reducing the net revenue cupola foundries receive for the sales of iron castings. Each

directly affected cupola foundry’s supply function is expressed as 
A-29

(A.23)

(A.24)

where

= multiplicative supply parameter for foundry l’s supply equation,

= share of foundry l’s iron castings produced using cupola furnaces,

= the coke rate for cupola furnaces, which specifies the amount of foundry

coke input per unit output (0.2493),

= change in the market price for foundry coke,

= change in per-unit cost of iron casting production, and

= supply elasticity for iron castings.

The multiplicative supply parameter, , is determined by backsolving Eq. (A.23), given

baseline values of the market price, supply elasticity, and quantity supplied. Unaffected iron

casting output produced with cupola furnaces are modeled as a single representative cupola

foundry. 

Domestic Electric Furnace Foundries. The functional form of the supply curve for

directly affected domestic foundries with electric arc or induction furnaces is specified as

where

= multiplicative parameter for electric foundries supply equation, and 

= change in per-unit cost of iron casting production, and

= electric foundries supply elasticity for iron castings.
A-30

(A.25)

(A.26)

(A.27)

The multiplicative supply parameter, , is determined by backsolving Eq. (A.24), given

baseline values of the market price, supply elasticity, and quantity supplied from electric

foundries. Unaffected iron casting output produced with electric furnaces are modeled as a

single representative electric foundry. 

Foreign Supply (Imports). The functional form of the foreign supply curve for iron

castings is specified as

where

= multiplicative parameter for foreign iron castings supply equation, and

= foreign supply elasticity for iron castings. 

The multiplicative supply parameter, , is determined by backsolving Eq. (A.25), given

baseline values of the market price, supply elasticity, and level of imports.

A.3.4.2 Market Demand for Iron Castings

The market demand for iron castings (QDi) is the sum of domestic and foreign

demand, and it is expressed as a function of the price of iron castings:

where

= domestic demand for iron castings, and

= foreign demand (exports) for iron castings.

Domestic Demand for Iron Castings. The domestic demand for iron castings is

expressed as
A-31

(A.28)

where

= multiplicative parameter for domestic iron castings’ demand equation, and

= domestic demand elasticity for iron castings.

The multiplicative demand parameter calibrates the domestic demand equation given

baseline data on price and demand elasticity to replicate the observed 2000 level of domestic

consumption.

Foreign Demand for Iron Castings. Foreign demand (exports) for iron castings is

expressed as

where

= multiplicative demand parameter for foreign iron castings’ demand equation,

and

= foreign (export) demand elasticity for iron castings.

The multiplicative demand parameter is determined by backsolving Eq. (A.28), given

baseline values of market price, demand elasticity, and level of exports.

A.3.5 Post-regulatory Market Equilibrium Determination

Integrated steel mills and iron foundries with cupola furnaces must determine output

given the market prices for their finished products, which in turn determines their furnace

and foundry coke requirements. The optimal output of steel mill products at integrated mills

also depends on the cost of producing captive furnace coke and the market price of furnace

coke; whereas iron foundries with cupolas depend on only the market price of foundry coke

because they have no captive operations. Excess production of captive furnace coke at

integrated mills will spill over into the furnace coke market; whereas an excess demand will

cause the mill to demand furnace coke from the market. For merchant coke plants, the

optimal market supply of furnace and/or foundry coke will be determined by the market

price of each coke product. 
A-32

Facility responses and market adjustments can be conceptualized as an interactive

feedback process. Facilities face increased costs from the regulation, which initially reduce

output. The cumulative effect of these individual changes leads to an increase in the market

price that all producers (affected and unaffected) and consumers face, which leads to further

responses by producers (affected and unaffected) as well as consumers and thus new market

prices, and so on. The new equilibrium after imposing the regulation is the result of a series

of iterations between producer and consumer responses and market adjustments until a stable

market price arises where market supply equals market demand for each product, i.e., QS =

QD.

The Agency employed a Walrasian auctioneer process to determine equilibrium price

(and output) associated with the increased production costs of the regulation. The auctioneer

calls out a market price for each product and evaluates the reactions by all participants

(producers and consumers), comparing total quantities supplied and demanded to determine

the next price that will guide the market closer to equilibrium (i.e., where market supply

equals market demand). Decision rules are established to ensure that the process will

converge to an equilibrium, in addition to specifying the conditions for equilibrium. The

result of this approach is a vector of prices with the regulation that equilibrates supply and

demand for each product.

The algorithm for deriving the with-regulation equilibria in all markets can be

generalized to five recursive steps:

1. Impose the control costs for each affected facility, thereby affecting their supply

decisions.

2. Recalculate the production decisions for coke products and both final steel mill

products and iron castings across all affected facilities. The adjusted production

of steel mill products from integrated steel mills and iron castings from foundries

with cupola furnaces determines the derived demand for furnace and foundry

coke through the input ratios. Therefore, the domestic demand for furnace and

foundry coke is simultaneously determined with the domestic supply of final steel

mill products and iron castings from these suppliers. After accounting for these

adjustments, recalculate the market supply of all products by aggregating across

all producers, affected and unaffected.

3. Determine the new prices via a price revision rule for all product markets.

4. Recalculate the supply functions of all facilities with the new prices, resulting in a

new market supply of each product, in addition to derived (domestic) demand for

furnace and foundry coke. Evaluate domestic demand for final steel mill products
A-33

and iron castings, as well as import supply and export demand for appropriate

products given the new prices.

5. Go to Step #3, resulting in new prices for each product. Repeat until equilibrium

conditions are satisfied in all markets (i.e., the ratio of supply to demand is

approximately one for each and every product).

A.3.6 Economic Welfare Impacts

The economic welfare implications of the market price and output changes with the

regulation can be examined using two slightly different tactics, each giving a somewhat

different insight but the same implications: changes in the net benefits of consumers and

producers based on the price changes and changes in the total benefits and costs of these

products based on the quantity changes. This analysis focuses on the first measure—the

changes in the net benefits of consumers and producers. Figure A-9 depicts the change in

economic welfare by first measuring the change in consumer surplus and then the change in

producer surplus. In essence, the demand and supply curves previously used as predictive

devices are now being used as a valuation tool.

This method of estimating the change in economic welfare with the regulation

divides society into consumers and producers. In a market environment, consumers and

producers of the good or service derive welfare from a market transaction. The difference

between the maximum price consumers are willing to pay for a good and the price they

actually pay is referred to as “consumer surplus.” Consumer surplus is measured as the area

under the demand curve and above the price of the product. Similarly, the difference

between the minimum price producers are willing to accept for a good and the price they

actually receive is referred to as “producer surplus” or profits. Producer surplus is measured

as the area above the supply curve and below the price of the product. These areas can be

thought of as consumers’ net benefits of consumption and producers’ net benefits of

production, respectively.

In Figure A-9, baseline equilibrium occurs at the intersection of the demand curve, D,

and supply curve, S. Price is Pl

 with quantity Ql. The increased cost of production with the

regulation will cause the market supply curve to shift upward to S. The new equilibrium

price of the product is P2. With a higher price for the product, there is less consumer welfare,

all else being unchanged as real incomes are reduced. In Figure A-9(a), area A represents the

dollar value of the annual net loss in consumers’ benefits with the increased price. The

rectangular portion represents the loss in consumer surplus on the quantity still consumed, 
A-34

S

S′

D

Q/t

$/Q

(a) Change in Consumer Surplus with Regulation

(b) Change in Producer Surplus with Regulation

(c) Net Change in Economic Welfare with Regulation

A

B

C

D

P2

P1

Q2 Q1

S

S′

D

$/Q

P2

P1

Q Q/t 2 Q1

S

S′

D

$/Q

P2

P1

Q Q/t 2 Q1

Figure A-9. Economic Welfare Changes with Regulation: Consumer and Producer

Surplus
A-35

Q2, while the triangular area represents the foregone surplus resulting from the reduced

quantity consumed, Ql

–Q2.

In addition to the changes in consumer welfare, producer welfare also changes with

the regulation. With the increase in market price, producers receive higher revenues on the

quantity still purchased, Q2. In Figure A-9(b), area B represents the increase in revenues due

to this increase in price. The difference in the area under the supply curve up to the original

market price, area C, measures the loss in producer surplus, which includes the loss

associated with the quantity no longer produced. The net change in producer welfare is

represented by area B–C.

The change in economic welfare attributable to the compliance costs of the regulation

is the sum of consumer and producer surplus changes, that is, – (A) + (B–C). Figure A-9(c)

shows the net (negative) change in economic welfare associated with the regulation as area

D. However, this analysis does not include the benefits that occur outside the market (i.e.,

the value of the reduced levels of air pollution with the regulation). Including this benefit

may reduce the net cost of the regulation or even make it positive.
B-1

APPENDIX B

DEVELOPMENT OF COKE BATTERY COST FUNCTIONS

This appendix outlines EPA’s method for estimating 2000 baseline production costs

for coke batteries. The Agency used a coke production cost model developed in support of

the 1993 MACT on coke ovens. EPA’s Technical Approach for a Coke Production Cost

Model (EPA, 1979) provides a more detailed description of this model. For this analysis, the

model was updated with reported technical characteristics of coke batteries from the

Information Collection Request (ICR) survey responses and available price data (see

Table B-1). In addition, the Agency incorporated estimates of MACT pollution abatement

costs developed for the 1993 MACT on coke ovens (EPA, 1991).

B.1 Variable Costs

Coke batteries use four variable inputs during the manufacturing process—

metallurgical coal, labor, energy, and other materials/supplies. Metallurgical coal is

essentially the only raw material used in the production of coke. Labor transports and

delivers the raw materials as well as final products. Coke ovens and auxiliary equipment

consume energy and supplies during the production process and periodic maintenance and

repair of the coke batteries. 

Coke production requires a fixed amount of each variable input per ton of coke, and

these inputs are not substitutable. Accordingly, the total variable cost function is linear in the

output and input prices, or, in other words, the average variable cost function is independent

of output. Therefore, the average variable cost function (expressed in dollars per short ton of

coke) can be written as

AVC = AV_CIPc + AV_LIw + AV_EIPe + AV_OIPo (B.1)

where AV_CI, AV_LI, AV_EI, and AV_OI are the fixed requirements per ton of coke of

metallurgical coal, labor, energy, and other material and supplies. Pc, w, Pe, and Po are the

prices of each variable input, respectively. As shown above, the contribution of each

variable input to the per-unit coke cost is equal to the average variable input (fixed

requirement of the input per ton of coke) times the price of the input. For example, the
B-2

Table B-1. Key Parameter Updates for Coke Production Cost Model: 2000a

Variable Description Units 2000

R1 Steam Cost $/1,000 lb steam 8.97

R2 Cooling Water $/1,000 gal 0.26

R3 Electricity $/kWh Varies by state

R4 Underfire Gas $/103 cft 1.06

R7 Calcium Hydroxide $/ton 74.00

R8 Sulfuric Acid $/ton 79.00

R9 Sodium Carbonate $/ton 537.00

R10 Sodium Hydroxide $/ton 315.00

R11 Coal Tar Credit $/gal 0.82

R12 Crude Light Oil $/gal 1.27

R13 BTX Credit $/gal 0.94

R14 Ammonium Sulfate Credit $/ton 40.04

R14* Anhydrous Ammonia Credit $/ton 239.21

R15 Elemental Sulfur Credit $/ton 287.48

R16 Sodium Phenolate Credit $/ton 864.12

R17 Benzene Credit $/gal 1.21

R18 Toluene Credit $/gal 0.85

R19 Xylene Credit $/gal 0.75

R20 Naphalene Credit $/lb 0.27

R21 Coke Breeze Credit $/ton 45.62

R22 Solvent Naptha Credit $/gal 0.88

R23 Wash Oil Cost $/gal 1.29

R25 Phosphoric Acid (commercial) $/ton 711.31

Industrial Coke Price $/ton 112.00

a

This table provides price update for the coke production cost model (EPA, 1979, Table 2–3). 

contribution of labor to the cost per ton of coke (AV_LI) is equal to the labor requirement

per ton of coke times the price of labor (w). 

The variable costs above include those costs associated with by- and co-product

recovery operations associated with the coke battery. To more accurately reflect the costs

specific to coke production, the Agency subtracted by- and co-product revenues/credits from

Eq. (B.1). By-products include tar and coke oven gas among others, while co-products

include coke breeze and other industrial coke. Following the same fixed coefficient
B-3

Table B-2. Metallurgical Coal Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average $61.23 $57.98 $60.22

Minimum $56.21 $52.17 $52.17

Maximum $71.98 $68.39 $71.98

approach, these revenues or credits (expressed per ton of coke) are derived for each

recovered product at the coke battery by multiplying the appropriate yield (recovered product

per ton of coke) by its price or value. The variable cost components and by-/co-product

credits are identified below.

B.1.1 Metallurgical Coal (AVCI, Pc)

The ICR survey responses provided the fixed input requirement for metallurgical coal

at each battery. Based on the responses from the survey, U.S. coke producers require an

average of 1.36 tons of coal per ton of coke produced. This fixed input varies by type of

producer. Integrated, or captive, producers require an average of 1.38 tons of coal per ton of

coke produced, while merchant producers require an average of 1.31 tons of coal per ton of

coke produced. The U.S. Department of Energy provides state-level coal price data for

metallurgical coal. For each coke battery, EPA computed the cost of coal per short ton of

coke by multiplying its input ratio times the appropriate state or regional price. As shown in

Table B-2, the average cost of metallurgical coal per ton of coke in 2000 was $61.23 for

captive producers and $57.98 for merchant producers.

B.1.2 Labor (AVLI, w)

The cost model provides an estimate of the fixed labor requirement for operation,

maintenance, and supervision labor at each battery. The Agency used these estimates to

derive the average variable labor cost for each individual battery given its technical

characteristics and the appropriate state-level wage rates obtained from the U.S. Bureau of

Labor Statistics (2002). As shown in Table B-3, average labor costs per ton of coke are

significantly lower for captive producers (e.g., $17.18 per ton of coke) relative to merchant 
B-4

Table B-3. Labor Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average $17.18 $28.95 $20.83

Minimum $9.19 $11.07 $9.19

Maximum $38.35 $44.63 $44.63

Table B-4. Energy Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average $5.51 $6.34 $5.77

Minimum $3.91 $4.31 $3.91

Maximum $16.11 $15.41 $16.11

producers (e.g., $28.95 per ton of coke). Captive batteries are typically larger capacity

batteries and therefore require fewer person-hours per ton of coke.

B.1.3 Energy (AVEI, Pe)

The cost model estimates the fixed energy requirements (i.e., electricity, steam, and

water) for each battery. These estimates are used to derive the energy costs per ton of coke

for each battery. Captive producers have a lower electricity requirement (i.e., 47.58 kWh per

ton of coke) relative to merchant producers (i.e., 50.96 kWh per ton of coke). As shown in

Table B-4, the average energy cost per ton of coke across all coke batteries is $5.77. 

Average energy costs per ton of coke are lower for captive producers (e.g., $5.51 per ton of

coke) relative to merchant producers (e.g., $6.34 per ton of coke). This difference reflects

lower state/regional electricity prices in regions where captive batteries produce coke.
B-5

Table B-5. Other Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average $4.42 $5.53 $4.76

Minimum $3.27 $3.26 $3.26

Maximum $7.69 $7.42 $7.69

B.1.4 Other Materials and Supplies (AVOI, Po)

The fixed requirements for other materials and supplies associated with the

production of coke include

 chemicals,

 maintenance materials, 

 safety and clothing, and

 laboratory and miscellaneous supplies.

As shown in Table B-5, the cost model estimates the average cost for these items across all

coke batteries is $4.76 per short ton of coke, ranging from $3.26 to $7.69 per ton of coke. 

These costs vary by producer type, with merchant producers averaging $5.53 per ton of coke

versus captive producers who average $4.42 per ton of coke.

B.1.5 By- and Co-product Credits

In addition to the variable cost inputs described above, by- and co-products are

associated with the manufacture of coke products. Therefore, the Agency modified Eq. (B.1)

by subtracting (1) revenues generated from the sale of by-/co-products and (2) credits

associated with using of coke oven gas as an energy input in the production process. The

following cost function adjustments were made to the engineering model to incorporate byand co-products into the cokemaking cost function: 

 Coke breeze—ICR survey responses provided coke breeze output per ton of coke

for each battery. 
1

The Agency estimated costs for the LAER control level using two scenarios. The first (LAER-MIN) assumed

all batteries will require new doors and jambs. The second (LAER-MAX) also assumed all batteries will

require new doors and jambs and in addition assumed batteries with the most serious door leak problems

would be rebuilt. This analysis reports cost estimates for the LAER-MIN scenario.

B-6

Table B-6. By-/Co-Product Credits by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average $19.54 $24.05 $20.94

Minimum $16.09 $10.69 $10.69

Maximum $35.99 $51.78 $51.78

 Other industrial coke—ICR survey responses provided other industrial coke

output per ton of coke for each battery. 

 Coke oven gas—Based on secondary sources and discussions with engineers,

furnace coke producers were assumed to produce 8,500 ft3

 per ton of coal, and

foundry producers were assumed to produce 11,700 ft3 per ton of coal (Lankford

et al., 1985; EPA, 1988).

As shown in Table B-6, the average by-/co-product credit is $19.54 per ton of coke for

captive producers and $24.05 per ton of coke for merchant producers.

B.2 MACT/LAER Pollution Abatement Costs

The 1990 Clean Air Act Amendments mandated two levels of control for emissions

from coke ovens. The first control level, referred to as MACT, specified limits for leaking

doors, lids, offtakes, and time of charge. This level of control was to be attained by 1995. 

The second level of control, Lowest Achievable Emissions Rate (LAER), specified more

stringent limits for leaking doors and offtakes. Estimates of the MACT and LAER costs

associated with these controls were developed for EPA’s Controlling Emissions from ByProduct Coke Oven Charging, Door Leaks, and Topside Leaks: An Economic Impacts

Analysis (EPA, 1991).1

 Table B-7 provides summary statistics for the projected costs

associated with each level of control. However, the Agency determined that industry actions

undertaken in the interim period to comply with the MACT limits have enabled them to also

meet the LAER limits. Therefore, only the MACT-related pollution abatement costs have 
B-7

Table B-7. Pollution Abatement Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

MACT

Average $0.83 $2.34 $1.30

Minimum $0.00 $0.00 $0.00

Maximum $2.59 $11.14 $11.14

LAER

Average $1.64 $2.44 $1.88

Minimum $0.07 $0.94 $0.07

Maximum $2.63 $6.07 $6.07

been incorporated to determine the appropriate baseline costs for the 2000 economic model. 

As shown in Table B-7, the average MACT pollution abatement cost across all coke batteries

is $1.30 per short ton of coke. The projected costs for captive producers range from zero to

$2.59 per ton of coke, while projected costs for merchant producers range from zero to

$11.14 per ton of coke.

B.3 Fixed Costs

Production of coke requires the combination of variable inputs outlined above with

fixed capital equipment (e.g., coke ovens and auxiliary equipment). It also includes other

overhead and administrative expenses. For each coke battery, the average fixed costs per ton

of coke can be obtained by dividing the total fixed costs (TFC) estimated by the coke model

by total battery coke production. Therefore, the average fixed cost function (expressed in

dollars per ton of coke) can be written as

AFC = (PTI + ASE +PYOH+ PLOH)/Q (B.2)

where

 property taxes and insurance (PTI) = (0.02)($225Coke Capacity). This category

accounts for the fixed costs associated with property taxes and insurance for the

battery. The cost model estimates this component as 2 percent of capital cost. 

Capital costs are estimated to be $225 per annual short ton of capacity based on

reported estimates of capital investment cost of a rebuilt by-product coke-making

facility (USITC, 1994). As shown in Table B-8, the average PTI cost across all

batteries is $4.47 per ton of coke.
B-8

Table B-8. Average Fixed Costs by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Property taxes and insurance

Average $4.41 $4.58 $4.47

Minimum $3.20 $3.55 $3.20

Maximum $6.78 $6.11 $6.78

Administrative and sales expense

Average $4.96 $5.16 $5.02

Minimum $3.60 $4.00 $3.60

Maximum $7.63 $6.87 $7.63

Payroll overhead 

Average $3.44 $5.79 $4.17

Minimum $1.84 $2.21 $1.84

Maximum $7.67 $8.93 $8.93

Plant overhead

Average $10.18 $18.91 $12.89

Minimum $5.73 $7.92 $5.73

Maximum $21.83 $28.62 $28.62

 administration and sales expense (ASE) = (0.02)($225Coke capacity). This

category accounts for the fixed costs associated with administrative and sales

expenses for the coke battery. The cost model also calculates this component as 2

percent of capital cost. As shown in Table B-8, the average cost across all coke

batteries for ASE is $5.02 per ton of coke.

 payroll overhead (PYOH) = (0.2)(Total labor costs). Payroll overhead is

modified as 20 percent of total labor costs. Payroll overhead is used to capture

fringe benefits because wage rates obtained from the Bureau of Labor Statistics

exclude fringe benefits. As shown in Table B-8, the average payroll overhead is

$3.44 per ton of coke for captive producers and $5.79 per ton of coke for

merchant producers, reflecting the different labor requirements by producer type. 

 plant overhead (PLOH) = (0.5)(Total payroll + Total other expenses). The cost

model computes plant overhead as 50 percent of total payroll and total other

expenses by producer type. As shown in Table B-8, the average plant overhead

cost is $10.18 for captive producers and $18.91 for merchant producers. As with
B-9

payroll overhead, this difference reflects differences in labor requirements for

captive and merchant producers. 

B.4 Summary of Results

Table B-9 summarizes each cost component and aggregates them to estimate the

average total costs per ton of coke by producer type. As shown, the average total cost (ATC)

across all coke batteries is $98.49 per short ton of coke. The ATC for captive producers is

$92.62 per short ton of coke and is significantly lower than the ATC for merchant producers

at $111.52. This difference reflects both economies of scale and lower production costs

associated with the production of furnace coke. These differences are also consistent with

observed market prices for furnace coke $112 (produced mainly by captive producers) and

for foundry coke $161 (produced solely by merchant producers with some furnace coke)

(USITC, 2001b, 2001c). A correlation analysis of these cost estimates shows that ATC is

negatively correlated with coke battery capacity (correlation coefficient of -0.70) and

start/rebuild date (correlation coefficient of -0.63). Therefore, average total costs are lower

for larger coke batteries and those that are new or recently rebuilt. Tables B-10 and B-11

present cost estimates for individual captive and merchant coke batteries, respectively.

B.5 Nonrecovery Cokemaking

Several substitute technologies for by-product cokemaking have been developed in

the United States and abroad. In the United States, the nonrecovery method is the only

substitute that has a significant share of the coke market. This technology is relatively new,

and, as a result, the original coke production cost model did not include estimates for these

types of coke-making batteries. The nonrecovery process is less costly than the by-product

process because of the absence of recovery operations and a lower labor input requirement

per ton of coke. Therefore, the Agency modified the model to reflect these cost advantages

in the following manner:

 No expenses/credits associated with by- and co-product recovery.

 Reduced labor input—labor requirement estimates generated by the model were

multiplied by a factor of 0.11, which represents the ratio of employment per ton

of coke at merchant batteries to employment per ton of coke at nonrecovery

batteries.
B-10

Table B-9. Cost Summary by Producer Type: 2000 ($/ton of coke)

Captive Merchant All Coke Batteries

Number of batteries 40 18 58

Average variable costa

Average $68.80 $74.74 $70.64

Minimum $57.95 $39.80 $39.80

Maximum $82.94 $91.00 $91.00

MACT

Average $0.83 $2.34 $1.30

Minimum $0.00 $0.00 $0.00

Maximum $2.59 $11.14 $11.14

Average fixed cost

Average $22.99 $34.44 $26.55

Minimum $15.61 $17.91 $15.61

Maximum $43.91 $48.34 $48.34

Average total cost

Average $92.62 $111.52 $98.49

Minimum $73.87 $69.92 $69.92

Maximum $127.07 $141.84 $141.84

a

Includes by-/co-product credits.

 Exceed current standards of pollution abatement (Engineering and Mining

Journal, 1997)—MACT compliance costs were excluded.

As shown in Table B-12, the ATC for nonrecovery coke-making facilities is $69.25 per ton

of coke, which is significantly lower than the average ATC of captive and merchant

producers. These costs vary slightly across these batteries ranging from $67.51 to $70.12 per

ton of coke. Table B-13 presents cost estimates for individual nonrecovery cokemaking

batteries.
B-11

Table B-10. Cost Data Summary for Captive Coke Batteries: 2000

Facility Name Location

Producer

Typea

Coke

Typeb

Capacity

(short

tons/yr)

Start/

Rebuild

Date

AVCc

($/short

ton)

MACT

($/short

ton)

AFC

($/short

ton)

ATC

($/short

ton)

Acme Steel Chicago, IL C 1 250,000 1979 $74.41 $1.02 $20.69 $96.13Acme Steel Chicago, IL C 1 250,000 1978 $74.26 $1.02 $20.69 $95.97AK Steel Ashland, KY C 1 634,000 1978 $66.88 $1.28 $18.88 $87.05AK Steel Ashland, KY C 1 366,000 1953 $69.25 $1.02 $21.15 $91.42AK Steel Middletown, OH C 1 429,901 1952 $74.42 $1.23 $23.62 $99.27Bethlehem Steel Burns Harbor, IN C 1 948,000 1972 $58.99 $0.72 $18.11 $77.82Bethlehem Steel Burns Harbor, IN C 1 929,000 1983 $59.27 $0.71 $18.68 $78.66Bethlehem Steel Lackawanna, NY C 1 375,000 1962 $65.66 $1.78 $21.41 $88.86Bethlehem Steel Lackawanna, NY C 1 375,000 1952 $65.65 $1.83 $21.23 $88.71Geneva Steel Provo, UT C 1 200,000 1944 $77.49 $0.27 $28.62 $106.38Geneva Steel Provo, UT C 1 200,000 1944 $78.44 $0.27 $30.92 $109.62Geneva Steel Provo, UT C 1 200,000 1944 $78.41 $0.22 $26.47 $105.10Geneva Steel Provo, UT C 1 200,000 1944 $82.94 $0.22 $43.91 $127.07Gulf States Steel Gadsden, AL C 1 250,000 1942 $75.28 $1.71 $27.56 $104.55Gulf States Steel Gadsden, AL C 1 250,000 1965 $74.47 $2.59 $19.44 $96.51LTV Steel Chicago, IL C 1 615,000 1982 $63.79 $0.36 $18.38 $82.52LTV Steel Warren, OH C 1 549,000 1979 $69.00 $0.04 $22.18 $91.22National Steel Ecorse, MI C 1 924,839 1992 $78.68 $0.27 $17.44 $96.38National Steel Granite City, IL C 1 300,931 1982 $69.93 $0.68 $21.26 $91.87National Steel Granite City, IL C 1 300,931 1980 $69.93 $0.68 $21.26 $91.88

(continued)
B-12

Table B-10. Cost Data Summary for Captive Coke Batteries: 2000 (continued)

Facility Name Location

Producer

Typea

Coke

Typeb

Capacity

(short

tons/yr)

Start/

Rebuild

Date

AVCc

($/short

ton)

MACT

($/short

ton)

AFC

($/short

ton)

ATC

($/short

ton)

USX Clairton, PA C 1 844,610 1982 $59.24 $0.72 $15.75 $75.71USX Clairton, PA C 1 668,680 1976 $60.62 $0.00 $20.32 $80.94USX Clairton, PA C 1 668,680 1978 $60.62 $0.00 $20.32 $80.94USX Clairton, PA C 1 373,395 1989 $63.33 $0.00 $21.71 $85.03USX Clairton, PA C 1 373,395 1989 $63.33 $0.00 $21.71 $85.03USX Clairton, PA C 1 373,395 1979 $63.33 $1.04 $21.71 $86.07USX Clairton, PA C 1 378,505 1955 $65.43 $1.04 $22.73 $89.20USX Clairton, PA C 1 378,505 1955 $65.43 $1.09 $22.73 $89.25USX Clairton, PA C 1 378,505 1955 $65.43 $1.09 $22.73 $89.25USX Clairton, PA C 1 378,505 1954 $66.39 $1.09 $22.46 $89.94USX Clairton, PA C 1 378,505 1954 $66.39 $1.04 $22.46 $89.89USX Clairton, PA C 1 378,505 1954 $66.39 $0.00 $22.46 $88.85USX Gary, IN C 1 827,820 1976 $65.47 $0.65 $23.24 $89.36USX Gary, IN C 1 827,820 1975 $66.41 $0.65 $22.60 $89.67USX Gary, IN C 1 297,110 1954 $72.99 $1.51 $24.76 $99.26USX Gary, IN C 1 297,110 1954 $73.22 $1.51 $25.94 $100.67Wheeling-Pitt Follansbee, WV C 1 782,000 1977 $57.95 $0.31 $15.61 $73.87Wheeling-Pitt Follansbee, WV C 1 163,000 1964 $73.58 $1.36 $30.00 $104.93Wheeling-Pitt Follansbee, WV C 1 151,000 1955 $74.69 $1.11 $29.28 $105.07Wheeling-Pitt Follansbee, WV C 1 151,000 1953 $74.69 $1.11 $29.28 $105.07

aC = Captive; M = Merchant.b1 = Furnace; 2 = Foundry; 3 = Both.
B-13

Table B-11. Cost Data Summary for Merchant Coke Batteries: 2000

Facility Name Location

Producer

Typea

Coke

Typeb

Capacity

(short

tons/yr)

Start/

Rebuild

Date

AVCc

($/short

ton)

MACT

($/short

ton)

AFC

($/short

ton)

ATC

($/short

ton)

ABC Coke Tarrant, AL M 2 490,528 1968 $66.46 $1.22 $17.91 $85.59ABC Coke Tarrant, AL M 3 112,477 1951 $81.68 $2.69 $32.48 $116.85ABC Coke Tarrant, AL M 3 96,962 1941 $86.10 $2.56 $36.12 $124.78Citizens Gas Indianapolis, IN M 3 389,116 1979 $47.46 $1.05 $21.41 $69.92Citizens Gas Indianapolis, IN M 2 128,970 1946 $79.85 $2.02 $43.85 $125.72Citizens Gas Indianapolis, IN M 2 116,845 1941 $84.51 $2.13 $48.34 $134.98Empire Coke Holt, AL M 2 108,026 1978 $88.52 $7.38 $38.11 $134.01Empire Coke Holt, AL M 2 54,013 1978 $90.09 $11.14 $40.61 $141.84Erie Coke Erie, PA M 2 130,073 1943 $73.99 $1.73 $46.76 $122.48Erie Coke Erie, PA M 2 84,878 1952 $75.12 $1.48 $48.19 $124.78Koppers Monessen, PA M 1 245,815 1981 $79.25 $0.12 $30.25 $109.63Koppers Monessen, PA M 1 126,766 1980 $91.00 $0.36 $39.67 $131.03New Boston Portsmouth, OH M 1 346,126 1964 $78.73 $1.35 $27.76 $107.84Shenango Pittsburgh, PA M 1 514,779 1983 $78.87 $0.00 $28.29 $107.16Sloss Industries Birmingham, AL M 3 184,086 1959 $44.32 $1.61 $25.59 $71.52Sloss Industries Birmingham, AL M 1 133,931 1952 $79.78 $1.61 $30.30 $111.69Sloss Industries Birmingham, AL M 1 133,931 1956 $79.78 $1.61 $30.30 $111.69Tonawanda Buffalo, NY M 2 268,964 1962 $39.80 $2.03 $34.09 $75.92

aC = Captive; M = Merchant.b1 = Furnace; 2 = Foundry; 3 = Both.
B-14

Table B-12. Cost Summary for Nonrecovery Coke Batteries: 2000 ($/ton of coke)

Nonrecovery

Number of batteries 8

Metallurgical coal

Average $47.58

Minimum $46.95

Maximum $48.21

Labor

Average $2.07

Minimum $1.47

Maximum $2.68

Energy

Average $6.45

Minimum $6.25

Maximum $6.71

Other

Average $2.53

Minimum $2.44

Maximum $2.66

Average fixed cost

Average $10.62

Minimum $10.07

Maximum $11.13

Average total cost

Average $69.25

Minimum $67.51

Maximum $70.12
B-15

Table B-13. Cost Data Summary for Nonrecovery Coke Batteries: 1997

Facility Name Location

Producer

Typea

Coke

Typeb

Capacity

(short

tons/yr)

Start/

Rebuild

Date

AVCc

($/short

ton)

MACT

($/short

ton)

AFC

($/short

ton)

ATC

($/short

ton)

Jewell Cokeand Coal

Vansant, VA M 1 197,000 1966 $58.59 $0.00 $9.90 $68.49

Jewell Cokeand Coal

Vansant, VA M 1 164,000 1983 $59.31 $0.00 $10.38 $69.69

Jewell Cokeand Coal

Vansant, VA M 1 124,000 1989 $59.98 $0.00 $10.85 $70.83

Jewell Cokeand Coal

Vansant, VA M 1 164,000 1990 $59.31 $0.00 $10.38 $69.69

Indiana HarborCoke Co

East Chicago, IN M 1 325,000 1998 $62.36 $0.00 $10.52 $72.88

Indiana HarborCoke Co

East Chicago, IN M 1 325,000 1998 $62.36 $0.00 $10.52 $72.88

Indiana HarborCoke Co

East Chicago, IN M 1 325,000 1998 $62.36 $0.00 $10.52 $72.88

Indiana HarborCoke Co

East Chicago, IN M 1 325,000 1998 $62.36 $0.00 $10.52 $72.88

aC = Captive; M = Merchant.b1 = Furnace; 2 = Foundry; 3 = Both.cIncludes by-/co-product credits.
C-1

APPENDIX C

ECONOMETRIC ESTIMATION OF THE DEMAND ELASTICITY FOR

STEEL MILL PRODUCTS

This appendix summarizes EPA’s estimation of the demand elasticities for steel mill

products. These estimates are based on national-level data from 1987 through 1997 as

obtained from the AISI, U.S. Bureau of the Census, U.S. Bureau of Labor Statistics, and

other government sources. The following sections summarize the econometric procedure

and present the estimates of the demand elasticity for the following nine steel mill products:

 semi-finished products

 structural shapes and plates

 rails and track accessories

 bars

 tool steel

 pipe and tubing

 wire

 tin mill

 sheet and strip

C.1 Econometric Model

A partial equilibrium market supply/demand model is specified as a system of

interdependent equations in which the price and output of a product are simultaneously

determined by the interaction of producers and consumers in the market. In simultaneous

equation models, where variables in one equation feed back into variables in other equations,

the error terms are correlated with the endogenous variables (price and output). In this case,

single-equation ordinary least squares (OLS) estimation of individual equations will lead to

biased and inconsistent parameter estimates. Thus, simultaneous estimation of this system to
C-2

obtain elasticity estimates requires that each equation be identified through the inclusion of

exogenous variables to control for shifts in the supply and demand curves over time.

Exogenous variables influencing the demand for steel mill products include measures

of economic activity such as U.S. gross national and domestic production and the value of

construction activity, and the price of substitute products such as aluminum, plastics and

other nonferrous materials and building materials like cement/concrete (typically proxied by

the appropriate producer price indices). Exogenous variables influencing the level of supply

include measures of the change in the costs of iron and steel production caused by changes in

prices of key inputs like raw materials, fuel, and labor (typically proxied by the producer

price index for iron ore, coke, metallurgical coal, as well as the average hourly earnings for

the industry’s production workers).

The supply/demand system for a particular steel mill product over time (t) is defined

as follows:

Qt

d

 = f(Pt,Zt) + ut (C.1)

Qt

s

 = g(Pt,Wt) + vt (C.2)

Qt

d

 = Qt

s

 (C.3)

Eq. (C.1) shows quantity demanded in year t as a function of price, Pt, an array of demand

factors, Zt (e.g., measures of economic activity and substitute prices), and an error term, ut.

Eq. (C.2) represents quantity supplied in year t as a function of price and other supply

factors, Wt (e.g., input prices), and an error term, vt, while Eq. (C.3) specifies the equilibrium

condition that quantity supplied equals quantity demanded in year t, creating a system of

three equations in three variables. The interaction of the specified market forces solves this

system, generating equilibrium values for the variables Pt

*

 and Qt

*

=Qt

d*=Qts*.

Since the objective is to generate estimates of the demand elasticities for use in the

economic model, EPA employed the two-stage least squares (2SLS) regression procedure to

estimate only the parameters of the demand equation. This 2SLS approach is preferred to the

three-stage least squares approach because the number of observations limits the degrees of

freedom for use in the estimation procedure. EPA specified the logarithm of the quantity

demanded as a linear function of the logarithm of the price so that the coefficient on the price

variable yields the estimate of the constant elasticity of demand for steel mill product. All

prices employed in the estimation process were deflated by the gross domestic product

(GDP) implicit price deflator to reflect real rather than nominal prices. The first stage of the
C-3

2SLS procedure involves regressing the observed price against the supply and demand

“shifter” variables that are exogenous to the system. This first stage produces fitted (or

predicted) values for the price variable that are, by definition, highly correlated with the true

endogenous variable, the observed price, and uncorrelated with the error term. In the second

stage, these fitted values are then employed as observations of the right-hand side price

variable in the demand function. This fitted value is uncorrelated with the error term by

construction and thus does not incur the endogeneity bias.

C.2 Econometric Results

Table C-1 provides the results of the econometric estimation for each steel mill

product demand equation. The coefficients of the price variables represent the demand

elasticity estimates for each of the nine steel mill products. As economic theory predicts, all

of these estimates are negative, reflecting reductions in quantity demanded as price increases. 

The elasticities range from –0.16 for semi-finished products to –2.17 for rails and track

accessories, with a shipments weighted average elasticity for all products of –0.59. As

shown, three of the nine elasticity estimates are significant at a 90 percent confidence level. 

As expected, the estimated coefficients for the demand growth variables (GDP and

value of new construction) are all positive with the exception of the equation for steel wire

drawn products. However, this estimate is not statistically significant. The regression

coefficient results generally show that the price of aluminum, nonferrous metals’ producer

price index (PPI), and plastics’ PPI are substitutes for the majority of the steel mill products. 

Prices increases for these products result in increases in quantity demand for steel mill

products. The coefficient for the primary copper PPI is negative in the wire equation

indicating that it is a complement. A price increase for this product decreases wire

consumption. Copper and steel are both used in electric appliances; therefore, this is

consistent with these results. The regressions also show a negative coefficient for the price

of aluminum in the semi-finished products equation, the nonferrous metals’ PPI in the tin

mill products equation, and the concrete products’ PPI in the structural shapes and plates

equation suggesting these products are also complement products. Although these products

may be substitutes in specific applications, they are often complement products in the

production of final goods (i.e., building construction).

As a result of these econometric findings, the market model used the weighted

average demand elasticity of –0.59.
C-4

Table C-1. Two Stage Least Squares Regression Estimation of Steel Mill Products Demand Equations

Dependent Variables (ln Qd)

Independent Variables

Semifinished

Products

Structural

Shapes

and Plates

Rails and

Track

Accessories Bars Tool Steel

Pipe and

Tubing Wire

Tin Mill

Products

Sheet and

Strip

Constant 3.42

(1.47)

11.24

(1.93)

1.26

(0.27)

6.56

(1.71)

2.06

(0.31)

14.41

(1.11)

22.5

(1.14)

3.66

(0.61)

6.14

(0.61)

ln(price)a –0.16

(–1.39)

–0.17

(–0.71)

–2.17

(–1.95)*

–0.66

(–1.17)

–0.47

(–2.02)*

–1.62

(–2.14)*

–0.73

(–2.05)

–0.28

(–1.61)

–0.65

(–1.90)

ln(gdp) 1.52

(4.64)***

1.20

(4.00)**

2.95

(4.96)***

1.61

(6.08)***

— — –1.13

(–0.55)

1.41

(2.32)*

1.92

(2.59)**

ln(value_new_construct) — — — — 0.98

(1.84)

0.13

(0.18)

———

ln(alum_price) –0.20

(–2.75)**

— 0.08

(0.69)

0.27

(2.67)**

0.09

(0.52)

— — — 0.12

(1.18)

ln(PPI_nonferrmetals) — 0.69

(1.66)

— — — — –0.15

(–1.59)

—

ln(PPI_plast_parts_mfg) — — — — — — — 0.39

(1.23)

–0.26

(–0.29)

ln(PPI_plast_sh_rd_tube) — — — — — 2.09

(0.90)

———

ln(PPI_copper_prim) — — — — — — –0.50

(–2.90)**

— —

ln(PPI_conc_prod) — –1.59

(–1.25)

— — —— — — —

ln(PPI_plast_prod) — — — — — — 1.78

(2.46)*

— —

Time trend squared — — — — — — –0.002

(–0.54)

–0.002

(–2.37)*

—

(continued)
C-5

Table C-1. Two Stage Least Squares Regression Estimation of Steel Mill Products Demand Equations (Continued)

Dependent Variables (ln Qd)

Independent Variables

Semifinished

Products

Structural

Shapes

and Plates

Rails and

Track

Accessories Bars Tool Steel

Pipe and

Tubing Wire

Tin Mill

Products

Sheet and

Strip

R-Squared 0.90 0.81 0.82 0.84 0.44 0.51 0.98 0.57 0.93Adjusted R-Squared 0.86 0.65 0.75 0.77 0.20 0.30 0.96 0.14 0.88F value 21.44*** 5.26** 10.87*** 12.32*** 1.85 2.41 42.23*** 1.31 17.47***Observations 11 10 11 11 11 11 10 11 10Degrees of Freedom 7 5 7 7 7 7 4 5 5

Note: T-statistics of parameter estimates are in parenthesis. The F test analyzes the usefulness of the model. Asterisks indicate significance levels for these tests asfollows:

* = 90%, ** = 95%, *** = 99%

aPrice of corresponding steel mill product.

Variable Descriptions:ln(gdp) real gross domestic productln(value_new_construct) real value of construction put in placeln(alum_price) real price of aluminum ln(PPI_nonferrmetals) real producer price index for nonferrous metalsln(PPI_plast_parts_mfg) real producer price index for plastic parts and components for manufacturing

ln(PPI_plast_sh_rd_tube) real producer price index for laminated plastic sheets, rods, and tubesln(PPI_copper_prim) real producer price index for primary copperln(PPI_conc_prod) real producer price index for concrete productsln(PPI_plast_prod) real producer price index for plastic productstime trend squared time trend squared
D-1

APPENDIX D

ECONOMETRIC ESTIMATION OF THE DEMAND ELASTICITY FOR

IRON CASTINGS

In this appendix, we summarize the econometric procedure used to estimate demand

elasticities and present demand elasticity estimates for iron castings. Elasticity estimates are

based on national-level annual sales and price data. In addition, individual demand elasticity

estimates are developed for three subcategories of iron castings:

 Gray iron castings

 Ductile iron castings

 Malleable iron castings

D.1 Econometric Model

A partial equilibrium market supply/demand model is used to simulate the interaction

of producers and consumers in the iron and steel casting markets. The model consists of a

system of interdependent equations in which the price and output of a product are

simultaneously determined. This class of model is referred to as a simultaneous equation

model.

In simultaneous equation models, where variables in one equation feed back into

variables in another equation, the error terms in each equation are correlated with the

endogenous variables (price and output). In this case, single-equation ordinary least squares

(OLS) estimation of individual equations will lead to biased and inconsistent parameter

estimates. 

We therefore use a two-stage least squares (2SLS) approach to correct for the

correlation between the error term and the endogenous variables. The 2SLS approach

requires that each equation be identified through the inclusion of exogenous variables to

control for shifts in the supply and demand curves over time. 

Exogenous variables influencing the demand for iron castings include measures of

economic activity such as U.S. gross domestic production, the number of motor vehicle
1

The 2SLS approach was selected over the three-stage least squares (3SLS) approach because of the limited

number of observations available for the regression analysis. The 3SLS approach requires more degrees of

freedom for the estimation procedure. 

D-2

sales, and the price of substitute products such as plastics, nonferrous castings and forgings,

and steel mill products (typically proxied by the appropriate producer price indices). 

Exogenous variables influencing the level of supply include measures of the change in the

costs of iron and steel castings production caused by changes in prices of key inputs such as

raw materials, fuel, and labor (typically proxied by the producer price index for iron ore,

coke, fuel, and electricity as well as the average hourly earnings for the industry’s production

workers).

The supply/demand system for a particular iron or steel casting over time (t) is

defined as follows:

Qt

d

 = f(Pt,Zt) + ut (D.1)

Qt

s

 = g(Pt,Wt) + vt (D.2)

Qt

d

 = Qt

s

 (D.3)

Eq. (D.1) represents quantity demanded, Qt

d

 in year t as a function of price, Pt, and other

demand factors, Zt (e.g., measures of economic activity and prices of substitute products),

and an error term, ut

. Equation D.2 represents quantity supplied, Qt

s

, in year t as a function

of price and other supply factors, Wt (e.g., wage rate and other input prices), and an error

term, vt. Eq. (D.3) specifies the equilibrium condition, where quantity supplied equals

quantity demanded in year t. Equation D.3 creates a system of three equations in three

variables. Solving the system generates equilibrium values for the variables Pt

*

 and

Qt

*

=Qt

d*=Qts*.

We use a 2SLS regression procedure to estimate the parameters and obtain the

demand elasticities.1 In the first stage of the 2SLS procedure, the observed price is regressed

against the supply and demand “shifter” variables that are exogenous to the system. The first

stage produces fitted (or imputed) values for the price variable that are, by definition, highly

correlated with the true endogenous variable (the observed price) and uncorrelated with the

error term. In the second stage, these fitted values are then employed as explanatory

variables of the right-hand side in the demand function. The imputed value is uncorrelated

with the error term by construction and thus does not incur the endogeneity bias.
D-3

The logarithm of the quantity demanded is modeled as a linear function of the

logarithm of the commodity price. This specification enables us to interpret the price

variable coefficient as a constant elasticity of demand. 

D.2 Econometric Results

Demand elasticities for iron castings—and for the subcategories gray, ductile, and

malleable iron castings—are estimated based on commodity data from the U.S. Department

of Commerce, U.S. Bureau of Labor Statistics, and other government sources. The average

prices for iron and steel commodities are calculated based on value of shipments data from

1987 through 1997. Prior to estimating demand elasticities, all prices are deflated by the

gross domestic product (GDP) implicit price deflator to reflect real rather than nominal

prices. 

Table D-1 provides demand elasticity estimates for iron castings. The coefficients on

the price variables, ln (price), are the estimates of the demand elasticity. Demand elasticity

reflects how responsive consumers are to changes in the price of a product. For normal

goods, consumption decreases as price increases, and this negative relationship is shown by a

negative price variable coefficient. As economic theory predicts, our estimated coefficients

on the price variables are negative. 

As shown in Table D-1, all of the individual elasticity estimates are inelastic,

implying that a 1 percent increase in price results in a less than 1 percent decrease in

consumption. Individual demand elasticity estimates for the iron casting subcategories range

from –0.41 for malleable iron castings to –0.67 for gray iron castings. As shown in

Table D-1, the econometrically determined demand elasticity for all iron castings was –0.58.

The estimated coefficients for the demand growth variables (GDP and motor vehicle

production volume) are all positive, with the coefficient for steel castings significant at the

95 percent level and the coefficient for iron castings significant at the 99 percent level. The

coefficients for plastic manufacturing parts and steel pipe and tube products are negative in

the ductile iron castings equation indicating that these are complements. Price increases for

these products are therefore expected to decrease consumption of ductile iron castings. 

However, neither of these coefficients is significant at the 90 percent confidence level. 
D-4

Table D-1. Two Stage Least Squares Regression Estimation of Iron and Steel Castings Demand Equations

Dependent Variables

Iron Castings

Independent Variables Gray Iron Ductile Iron Malleable Iron All IronConstant .81

(.43)

.82

(.20)

–3.12

(–1.04)

–42.90

(–8.15)***

ln(price) –.67

(–2.80)**

–.42

(–1.89)*

–.41

(–1.51)

–.58

(–2.52)**

ln(gdpd) — — — 5.17

(11.10)***

ln(motor) .91

(9.97)***

1.01

(4.62)***

.61

(3.79)***

—

ln(PPI_plast_parts_trans) .09

(.26)

— ——

ln(PPI_nonferr_forge) .50

(1.37)

— .04

(.07)

–2.57

(–6.33)***

ln(PPI_nonferr_foundry) — 1.83

(1.88)*

— —

ln(PPI_plast_parts_mfg) — –.90

(–1.22)

1.07

(3.48)***

4.58

 (7.97)***

ln(pipe_price)a .16

 (.76)

–.57

(–.95)

.14

(.41)

.23

 (.95)

R-Squared .97 .92 .89 .97Adjusted R-Squared .94 .87 .81 .94F Value 33.90*** 17.08*** 11.49*** 38.46***Observations 12 13 13 12Degrees of Freedom 5 5 5 5

Note: T-statistics of parameter estimates are in parentheses. The F test analyzes the usefulness of the model. Asterisks indicate significance levels for these tests asfollows: * = 90%, ** = 95%, *** = 99%

aPrice of corresponding casting.

Variable Descriptions:ln(gdp) real gross domestic productln(motor) U.S. motor vehicle productionln(PPI_plast_parts_trans) real producer price index for

plastic parts for transportation

ln(PPI_nonferr_forge) real producer price index for nonferrous metal forge shop productsln(PPI_plast_parts_mfg) real producer price index for parts and components for manufacturingln(pipe_price) real producer of steel mill pipe and tube productsln(PPI_nonferr_foundry) real producer price index for nonferrous foundry shop products
D-5

D.3 Summary

Based on the econometric findings, we use the following demand elasticity estimate

for iron castings in the market model:

 Iron castings = –0.58 (significant at the 95 percent level).

This value is similar to the 1997 production weighted average of the individual product

elasticity estimates presented in Table D-1 (–0.52).
E-1

APPENDIX E

JOINT ECONOMIC IMPACT ANALYSIS OF THE INTEGRATED IRON AND

STEEL MACT STANDARD WITH THE COKE MACT STANDARD

For this analysis, the Agency also considered the national-level economic impacts of

joint implementation of the integrated iron and steel MACT standard with the coke MACT

standard. The measures of economic impacts presented in this appendix are the result of

incorporating the costs of compliance for each affected integrated iron and steel mill under

the integrated iron and steel MACT into market models developed by the Agency to analyze

the economic impacts of the coke MACT standard. The engineering analysis estimates

annual costs for existing sources are $15.5 million under the integrated iron and steel MACT

and $20.1 million under the coke MACT. Therefore, the total national estimate for existing

sources under joint implementation are $35.6 million.

E.1 Market-Level Impacts

The increased cost of coke production due to the regulation is expected to increase

the price of furnace coke and steel mill products and reduce their production and

consumption from 2000 baseline levels. As shown in Table E-1, the regulation is projected

to increase the price of furnace coke by 2.9 percent, or $3.26 per short ton. The increased

captive production costs and higher market price associated with furnace coke are projected

to increase steel mill product prices by less than 0.1 percent, or $0.19 per ton. As expected,

directly affected output declines across all producers, while supply from domestic and

foreign producers not subject to the regulation increases. Although the results show net

declines across all products (i.e., less than 1 percent decline in market output) the change in

domestic production is typically higher. This is especially true for furnace coke where

domestic production declines by 4.5 percent.

In contrast, the regulation showed no impact on price or quantity in the foundry coke

market. This is due to the capacity constraints on domestic producers and the role of foreign

imports. The supply of foundry coke is characterized by a domestic step supply function

augmented by foreign supply, with foreign suppliers being the high cost producers in the

market. Because foreign suppliers are the high cost producers, they determine the market 
E-2

Table E-1. Market-Level Impacts of the Joint Implementation of the Integrated Iron

and Steel MACT and Coke MACT: 2000

Baseline

Changes From Baseline

Absolute Percent

Furnace Coke

Market price ($/short ton) $112.00 $3.26 2.91%

Market output (103

 tpy) 12,004 –120.9 –1.01%

Domestic productiona 8,904 –399.7 –4.49%

Imports 3,100 278.8 8.99%

Foundry Coke

Market price ($/short ton) $161.00 — 0.00%

Market output (103

 tpy) 1,385 0.0 0.00%

Domestic production 1,238 0.0 0.00%

Imports 147 0.0 0.00%

Steel Mill Products

Market price ($/short ton) $489.45 $0.19 0.04%

Market output (103

 tpy) 147,007 –36.1 –0.02%

Domestic production 109,050 –262.3 –0.24%

Integrated producers 57,153 –334.3 –0.58%

Nonintegrated steel millsb 51,897 72.0 0.14%

Imports 37,957 226.3 0.60%

Iron Castings

Market price ($/short ton) $1,028.50 $0.00 0.00%

Market output (103

 tpy) 8,793 0.0 0.00%

Domestic productiona 8,692 0.0 0.00%

Cupola furnaces 5,210 0.0 0.00%

Electric furnacesc 3,482 0.0 0.00%

Imports 101 0.0 0.00%

a Includes minimills. b Excludes captive production. c Includes electric arc or electric induction furnaces.
E-3

price and an upward shift in the domestic supply curve does not affect the equilibrium price

or quantity. This implies that domestic foundry coke producers are not able to pass along

any of the cost of the regulation. In addition, because there is no price change in the foundry

coke market, the production of iron castings in unaffected by the regulation. 

E.2 Industry-Level Impacts

Industry revenue, costs, and profitability change as prices and production levels

adjust to increased production costs. As shown in Table E-2, the economic model projects

that profits for directly affected integrated iron and steel producers will decrease by $36

million, or 4.9 percent. However, because the price increase exceeds the average cost

increase, industry-level profits for U.S. merchant furnace coke producers are expected to

increase by $11.0 million, or 9.0 percent. In contrast, industry-level profits for U.S.

merchant foundry coke producers are expected to decline by $5.0 million, or 5.0 percent. 

These producers cannot pass along any of the control costs of the regulation because there is

no price increase. Those domestic suppliers not subject to the regulation experience windfall

gains with non-integrated steel mills (i.e., minimills) increasing profits by $10 million. 

E.2.1 Changes in Profitability

For integrated steel mills, operating profits decline by $36 million. This is the net

result of three effects: 

 Net decrease in revenue ($139 million): Steel mill product revenue decreases as a

result of reductions in output. However, these losses were mitigated by increased

revenues from furnace coke supplied to the market as a result of higher prices.

 Net decrease in production costs ($128 million): Reduction in steel mill and

market coke production costs occur as output declines. However, producers also

experience increases in costs associated with the higher price of inputs (i.e.,

furnace coke). 

 Increase in control costs ($25 million): The costs of captive production of

furnace coke increase as a result of regulatory controls.

Industry-wide profits for merchant furnace coke producers increase by $10 million as

a result of the following:

 Decreases in revenue ($34 million): Reductions in output outweigh revenue

increases as a result of higher market prices.
E-4

Table E-2. National-Level Industry Impacts of the Joint Implementation of the

Integrated Iron and Steel MACT and Coke MACT: 2000

Baseline

Changes From Baseline

Absolute Percent

Integrated Iron and Steel Mills

Total revenues ($106

/yr) $28,430.5 –$138.87 –0.49%

Steel mill products $27,973.6 –$152.62 –0.55%

Market coke operations $456.9 $13.75 3.01%

Total costs ($106

/yr) $27,690.8 –$102.49 –0.37%

Control costs $0.0 $25.29 NA

Steel production $0.0 $15.39 NA

Captive coke production $0.0 $7.42 NA

Market coke production $0.0 $2.49 NA

Production costs $27,690.8 –$127.78 –0.46

Steel production $25,327.3 –$151.06 –0.60%

Captive coke production $746.6 –$0.20 –0.03%

Market coke consumption $1,249.5 $23.28 1.86%

Market coke production $367.4 $0.20 0.05%

Operating profits ($106

/yr) $739.7 –$36.39 –4.92%

Iron and steel facilities (#) 20 0 0.00%

Coke batteries (#) 37 0 0.00%

Employment (FTEs) 66,603 –455 –0.68%

Coke Producers (Merchant Only)

Furnace

Revenues ($106

/yr) $521.8 –$33.88 –6.49%

Costs ($106

/yr) $404.5 –$44.65 –11.04%

Control costs $0.0 $2.95 NA

Production costs $404.5 –$47.60 –11.77%

Operating profits ($106

/yr) $117.4 $10.78 9.18%

Coke batteries (#) 17 –3 –17.65%

Employment (FTEs) 774 –236 –30.49%

Foundry

Revenues ($106

/yr) $245.5 $0.61 0.25%

Costs ($106

/yr) $148.7 $5.54 3.73%

Control costs $0.0 $5.54 NA

Production costs $148.7 $0.00 0.00%

Operating profits ($106

/yr) $96.8 –$4.93 –5.10%

Coke batteries (#) 12 0 0.00%

Employment (FTEs) 2,486 0 0.00%

(continued)
E-5

Table E-2. National-Level Industry Impacts of the Joint Implementation of the

Integrated Iron and Steel MACT and Coke MACT: 2000 (continued)

Baseline

Changes From Baseline

Absolute Percent

Nonintegrated Steel Millsa

Operating profits ($106/yr) NA $10.1 NA

Cupola Furnaces

Operating profits ($106

/yr) NA $0.00 NA

Captive NA $0.00 NA

Merchant NA $0.00 NA

Affected NA $0.00 NA

Unaffected NA $0.00 NA

Electric Furnacesb

Operating profits ($106/yr) NA $0.00 NA

Captive NA $0.00 NA

Merchant NA $0.00 NA

Affected NA $0.00 NA

Unaffected NA $0.00 NA

a Includes minimills. b Includes iron foundries that use electric arc or electric induction furnaces.

 Reduction in production costs ($48 million): Reduction in coke production costs

occurs as output declines. 

 Increased control costs ($3 million): The cost of producing furnace coke

increases as a result of regulatory controls.

Industry-wide profits for merchant foundry coke producers fall by $5 million under

the regulation:

 Increase in revenue ($0.6 million): Given that we project no price changes for

foundry coke, foundry coke revenue remains unchanged. However, small

revenue increases occur for batteries that also produce small amounts of furnace

coke. 

 Reduction in production costs ($0 million): No change in coke production costs

occur as output remains unchanged. 

 Increased control costs ($5.6 million): The cost of producing foundry coke

increases as a result of regulatory controls.
E-6

Lastly, domestic producers that are not subject to the regulation benefit from higher

prices without additional control costs. As mentioned above, profits increase are projected

for nonintegrated steel mills. 

Additional distributional impacts of the rule within each producer segment are not

necessarily apparent from the reported decline or increase in their aggregate operating

profits. The regulation creates both gainers and losers within each industry segment based

on the distribution of compliance costs across facilities. As shown in Table E-3, a substantial

subset of the merchant coke facilities are projected to experience profit increases (i.e., 13

furnace coke batteries and 1 foundry coke battery that also produces furnace coke, or

62 percent). However, two merchant batteries are projected to cease market operations as

they are the highest-cost coke batteries with the additional regulatory costs.

A majority of directly affected integrated iron and steel facilities (i.e., 16 plants, or 80

percent) are projected to become less profitable with the regulation with a total loss of $49

million. However, four integrated mills are projected to benefit from higher coke prices and

experience a total profit gain of $13 million. These mills typically own furnace coke

batteries with low production costs and lower per-unit compliance costs. In addition, a high

proportion of their coke inputs are supplied internally. 

E.2.2 Facility Closures

EPA estimates three merchant batteries supplying furnace coke are likely to

prematurely close as a result of the regulation. In this case, these batteries are the highestcost producers of furnace coke with the regulation. 

E.2.3 Changes in Employment

As a result of decreased output levels, industry employment is projected to decrease

by less than 1 percent, or 691 full-time equivalents (FTEs), with the regulation. This is the

net result of employment losses for integrated iron and steel mills totaling 455 FTEs and

merchant coke plants of 236 FTEs. Although EPA projects increases in output for producers

not subject to the rule, which would likely lead to increases in employment, the Agency did

not develop quantitative estimates for this analysis.

E.3 Social Cost

The social impact of a regulatory action is traditionally measured by the change in

economic welfare that it generates. The social costs of the final rule will be distributed

across consumers and producers alike. Consumers experience welfare impacts due to
E-7

Table E-3. Distribution Impacts of the Joint Implementation of the Integrated Iron and

Steel MACT and Coke MACT Across Directly Affected Producers: 2000

With Regulation

Increased

Profits

Decreased

Profits Closure Total

Integrated Iron and Steel Mills

Facilities (#) 4 16 0 20

Steel production

Total (103

 tpy) 6,232 50,922 0 57,153

Average (tons/facility) 1,558 3,183 0 2,858

Steel compliance costs

Total ($106/yr) $0.08 $15.46 $0.00 $15.54

Average ($/ton) $0.01 $0.30 $0.00 $0.27

Coke production

Total (103

 tpy) 5,729 6,915 0 12,644

Average (tons/facility) 1,432 432 0 632

Coke compliance costs

Total ($106

/yr) $0.17 $9.74 $0.00 $9.91

Average ($/ton) $0.03 $1.41 $0.00 $0.78

Change in operating profit ($106

/yr) $12.62 –$49.01 $0.00 –$36.39

Coke Plants (Merchant Only)

Furnace

Batteries (#) 13 1 3 17

Production (103

 tpy)

Total (103

 tpy) 3,979 255 404 4,637

Average (tons/facility) 306 255 135 273

Compliance costs

Total ($106

/yr) $2.1 $0.9 $1.791 $4.738

Average ($/ton) $0.52 $3.48 $4.44 $1.02

Change in operating profit ($106

/yr) $10.92 –$0.06 –$0.08 $10.78

Foundry

Batteries (#) 1 11 0 12

Production

Total (103

 tpy) 476 1,181 0 1,657

Average (tons/facility) 476 107 0 138

Compliance costs

Total ($106

/yr) $0.021 $5.524 $0.00 $5.545

Average $0.04 $4.68 $0.00 $3.35

Change in operating profit ($106

/yr) $0.59 –$5.52 $0.00 –$4.93
E-8

changes in market prices and consumption levels associated with the rule. Producers

experience welfare impacts resulting from changes in profits corresponding with the changes

in production levels and market prices. However, it is important to emphasize that this

measure does not include benefits that occur outside the market, that is, the value of reduced

levels of air pollution with the regulation.

The national compliance cost estimates are often used as an approximation of the

social cost of the rule. The engineering analysis estimated annual costs of $35.6 million. In

this case, the burden of the regulation falls solely on the affected facilities that experience a

profit loss exactly equal to these cost estimates. Thus, the entire loss is a change in producer

surplus with no change (by assumption) in consumer surplus. This is typically referred to as

a “full-cost absorption” scenario in which all factors of production are assumed to be fixed

and firms are unable to adjust their output levels when faced with additional costs.

In contrast, the economic analysis accounts for behavioral responses by producers

and consumers to the regulation (i.e., shifting costs to other economic agents). This

approach results in a social cost estimate that differs from the engineering estimate and also

provides insights on how the regulatory burden is distributed across stakeholders. As shown

in Table E-4, the economic model estimates the total social cost of the rule to be $34 million. 

This difference occurs because society reallocates resources as a result of the increased cost

of coke production. 

In the final product markets, higher market prices lead to consumers of steel mill

products experiencing losses of $28.5 million. Although integrated iron and steel producers

are able to pass on a limited amount of cost increases to their final consumers, e.g.,

automotive manufactures and construction industry, the increased costs result in a net decline

in profits at integrated mills of $36.4 million. 

In the coke industry, low-cost merchant producers of furnace coke benefit at the

expense of consumers and higher-cost coke batteries resulting in an industry-wide increase in

profits. Furnace coke profits at merchant plants increase in aggregate by $10.8 million. In

contrast, foundry coke profits at merchant plants declines in aggregate by $5 million. 

Lastly, domestic producers not subject to the regulation (i.e., nonintegrated steel mills

and electric furnaces) as well as foreign producers experience unambiguous gains because

they benefit from increases in market price under both alternatives. 
E-9

Table E-4. Distribution of the Social Costs of the Joint Implementation of the

Integrated Iron and Steel MACT and Coke MACT: 2000

Change in Consumer Surplus ($106

/yr) –$28.52

Steel mill product consumers –$28.52

Domestic –$27.25

Foreign –$1.27

Iron casting consumers $0.00

Domestic $0.00

Foreign $0.00

Change in Producer Surplus ($106/yr) $5.27

Domestic producers –$20.47

Integrated iron and steel mills –$36.39

Nonintegrated steel millsa $10.07

Cupola furnaces $0.00

Electric furnacesb $0.00

Furnace coke (merchant only) $10.78

Foundry coke (merchant only) –$4.93

Foreign producers $15.20

Iron and steel $4.63

Castings $0.00

Furnace coke $10.57

Foundry coke $0.00

Change In Total Social Surplusc ($106/yr) –$33.79

a Includes minimills. b Includes electric arc or electric induction furnaces. c The negative change in total social surplus indicates that the social cost of the regulation is $33.79 million.
F-1

Table F-1. Market-Level Impacts of the Final Coke MACT: 2000

Imports

 = 3.0

Imports

 = 10

Furnace Coke

Market price (percent change) 2.7% 1.1%

Market output (percent change) –0.8% –0.4%

Domestic production –3.9% –4.5%

Imports 8.3% 11.4%

Closures (# batteries) 2 3

APPENDIX F

FOREIGN IMPORTS SENSITIVITY ANALYSIS

The purpose of this appendix is to investigate the sensitivity of economic impact

estimates to changes in the blast furnace coke import supply elasticity parameter. To model

imports, we used a simple constant elasticity functional form to develop a supply curve for a

single foreign supplier. Graham, Thorpe, and Hogan (1999) use values of 3 and 10 in their

simulation analysis although they consider a value of 3 as being the most likely (page 204). 

Therefore, the Agency used a value of 3 for the base case scenario. However, we conducted

additional sensitivity analysis for the foreign supply elasticity using an even more elastic

value of 10.

F.1 Sensitivity Analysis Results

As shown in Table F-1, the market price increase falls from 2.7 to 1.1 percent and the

change in domestic market output increases from –3.9 percent to –4.5 percent, an additional

decrease of 51,000 short tons. In addition, one additional furnace coke battery is projected to

close. Foreign imports increase from 8.3 percent to 11.4 percent under this elasticity

assumption.
F-2

In contrast the shows no market impact differences on price or quantity in the

foundry coke market. As discussed in Section 4, this is due to the capacity constraints on

domestic producers and the role of foreign imports. The supply of foundry coke is

characterized by a domestic step supply function augmented by foreign supply, with foreign

suppliers being the high cost producers in the market. Because foreign suppliers are the high

cost producers, they determine the market price and an upward shift in the domestic supply

curve does not affect the equilibrium price or quantity. This implies that domestic foundry

coke producers are not able to pass along any of the cost of the regulation. In addition,

because there is no price change in the foundry coke market, the production of iron castings

in unaffected by the regulation. 
TECHNICAL REPORT DATA

(Please read Instructions on reverse before completing)

1. REPORT NO.

 EPA-452/R-02-008

2. 3. RECIPIENT’S ACCESSION NO.

4. TITLE AND SUBTITLE

Economic Impact Analysis of Final Coke Ovens NESHAP 

5. REPORT DATE

 September 2002

6. PERFORMING ORGANIZATION CODE

7. AUTHOR(S)

 Michael P. Gallaher and Brooks M. Depro, RTI

 

8. PERFORMING ORGANIZATION REPORT NO.

RTI Project Number 7647.003.274

9. PERFORMING ORGANIZATION NAME AND ADDRESS

 Research Triangle Institute (RTI)

 Center for Economics Research, Hobbs Bldg.

 Research Triangle Park, NC 27709

10. PROGRAM ELEMENT NO.

11. CONTRACT/GRANT NO.

68-D-99-024

 

12. SPONSORING AGENCY NAME AND ADDRESS

 Steve Page, Director

 Office of Air Quality Planning and Standards

 Office of Air and Radiation

 U.S. Environmental Protection Agency

 Research Triangle Park, NC 27711

13. TYPE OF REPORT AND PERIOD COVERED

Final

14. SPONSORING AGENCY CODE

EPA/200/04

15. SUPPLEMENTARY NOTES

16. ABSTRACT

This report evaluates the economic impacts of the final NESHAP for pushing and quenching operations at

coke plants. The social costs of the rule are estimated by incorporating the expected costs of compliance to a

partial equilibrium model of the U.S. iron and steel industry and projecting the market impacts for furnace

and foundry coke. 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

18. DISTRIBUTION STATEMENT

 Release Unlimited

19. SECURITY CLASS (Report)

 Unclassified

21. NO. OF PAGES

139

20. SECURITY CLASS (Page)

 Unclassified

22. PRICE

EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION IS OBSOLETE
United States Office of Air Quality Planning and Standards Publication No. EPA 452/R-02-008

Environmental Protection Air Quality Strategies and Standards Division September 2002Agency Research Triangle Park, NC