Economic Impact Analysis of the Proposed

Stationary Combustion Turbines NSPS: Final

Report
 EPA-452/R-05-001

 February 2005

ECONOMIC IMPACT ANALYSIS (EIA) FOR THE PROPOSED STATIONARY

COMBUSTION TURBINES NSPS

Subcontract No. 265.001

EPA Contract No. 68-D-00-265

Work Assignment No. 4-37

Prepared for:

E.H. Pechan and Associates, Inc.

5528-B Hempstead Way

Springfield, VA 22151

For submittal to:

Darryl Weatherhead

U.S. Environmental Protection Agency

Research Triangle Park, NC 27711

Prepared by:

Michael Gallaher

Brooks Depro

RTI International*

Research Triangle Park, NC 27709

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Air Quality Strategies and Standards Division

Innovative Strategies and Economics Group

Research Triangle Park, NC

*RTI International is a trade name of Research Triangle Institute.
iii

TABLE OF CONTENTS

Section Page

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

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

1.2 Scope and Purpose ....................................... 1-2

1.3 Organization of the Report ................................. 1-2

2 Combustion Turbine Technologies and Costs ......................... 2-1

2.1 Simple-Cycle Combustion Turbine Technologies ................ 2-1

2.2 Combined-Cycle Combustion Turbines Technologies ............. 2-2

2.3 Capital and Installation Costs ............................... 2-4

2.4 O&M Costs Including Fuel ................................. 2-4

3 Background on Health Affects and Regulatory Alternatives .............. 3-1

3.1 Background ............................................ 3-1
iv

3.1.1 Summary of Proposed Stationary Combustion Turbines 

NSPS ........................................... 3-1

3.2 Health Effects Associated with NOx and SO2 Emissions from 

Stationary Combustion Turbines ............................. 3-7

3.2.1 Benefits of Reduced Nitrous Oxide Emissions ............. 3-7

3.2.2 Benefits of Sulfur Dioxide Reductions ................... 3-9

3.3 Emission Reductions from the Proposed NSPS ................. 3-10

3.4 Summary of the Rule .................................... 3-10

4 Projection of Units and Facilities in Affected Sectors ................... 4-1

4.1 Profile of Existing Combustion Turbine Units ................... 4-1

4.1.1 Distribution of Units and Facilities by Industry ............ 4-1

4.1.2 Technical Characteristics ............................. 4-1

4.2 Projected Growth of Combustion Turbines ..................... 4-5

4.3 Projected Number of Affected Stationary Combustion Turbines ..... 4-5

5 Profile of the Electric Utility Industry ............................... 5-1

5.1 Electric Utility Industry (NAICS 22111) ....................... 5-1

5.1.1 Market Structure of the Electric Power Industry ........... 5-1

5.1.1.1 The Evolution of the Electric Power Industry ..... 5-1

5.1.1.2 Structure of the Traditional Regulated Utility ..... 5-3

5.1.1.3 Current Electric Power Supply Chain ........... 5-5

5.1.1.4 Overview of Deregulation and the Potential Future

Structure of the Electricity Market ............ 5-13
v

5.1.2 Electricity Generation .............................. 5-15

5.1.2.1 Growth in Generation Capacity ............... 5-17

5.1.3 Electricity Consumption ............................ 5-19

6 Economic Analysis Methods ...................................... 6-1

6.1 Agency Requirements for Conducting an EIA ................... 6-1

6.2 Overview of Economic Modeling Approaches .................. 6-2

6.2.1 Modeling Dimension 1: Scope of Economic 

Decisionmaking .................................... 6-2

6.2.2 Modeling Dimension 2: Interaction Between Economic

Sectors .......................................... 6-3

6.3 Selected Modeling Approach Used for Combustion Turbine 

Analysis ............................................... 6-4

6.3.1 Electricity Markets ................................. 6-7

6.3.2 Other Energy Markets ............................... 6-7

6.3.3 Supply and Demand Elasticities for Energy Markets ........ 6-8

6.3.4 Final Product and Service Markets .................... 6-11

6.3.4.1 Modeling the Impact on the Industrial and 

Commercial Sectors ....................... 6-11

6.3.4.2 Impact on the Residential Sector and 

Transportation Sectors ..................... 6-13

6.3.4.3 Impact on the Government Sector ............. 6-13

6.4 Summary of the Economic Impact Model ..................... 6-13

6.4.1 Estimating Changes in Social Welfare .................. 6-16
vi

7 Economic Impact Analysis ....................................... 7-1

7.1 Engineering Control Cost Inputs ............................. 7-1

7.1.1 Computing Supply Shifts in the Electricity Market .......... 7-1

7.2 Market-Level Results ..................................... 7-2

7.3 Social Cost Estimates ..................................... 7-6

7.4 Energy Impact Analysis ................................... 7-8

8 Small Entity Impacts ........................................... 8-1

8.1 Identifying Small Businesses ................................ 8-2

8.2 Screening-Level Analysis .................................. 8-2

8.3 Assessment ............................................. 8-2

References ......................................................... R-1

Appendix A Overview of the Market Model .............................. A-1

Appendix B Assumptions and Sensitivity Analysis ......................... B-1
vii

LIST OF FIGURES

Number Page

2-1 Simple-Cycle Gas Turbine ....................................... 2-2

2-2 Combined-Cycle Gas Turbine ..................................... 2-3

4-1 Number of Units by MW Capacity ................................. 4-3

4-2 Number of Units by Annual MWh Output Equivalent ................... 4-4

5-1 Traditional Electric Power Industry Structure ......................... 5-4

5-2 Electric Utility Industry ......................................... 5-7

5-3 Utility and Nonutility Generation and Shares by Class, 1988 and 1998 ...... 5-9

5-4 Annual Electricity Sales by Sector ................................ 5-19

6-1 Links Between Energy and Final Product Markets ..................... 6-6

6-2 Electricity Market ............................................. 6-8

6-3 Potential Market Effects of the NSPS on Petroleum, Natural Gas, or Coal ... 6-9

6-4 Fuel Market Interactions with Facility-Level Production Decisions ........ 6-12

6-5 Operationalizing the Estimation of Economic Impact .................. 6-15

6-6 Changes in Economic Welfare with Regulation ....................... 6-17

7-1 Market for Baseload Electricity ................................... 7-4
viii

LIST OF TABLES

Number Page

2-1 Comparison of Emissions from Coal-Fired and Simple-Cycle Turbines and 

Combined-Cycle Turbines ....................................... 2-4

2-2 Overall Installation Costs ........................................ 2-5

2-3 Comparison of Percentage of Costs ................................ 2-5

4-1 Facilities With Units Having Capacities Above 1 MW by Industry 

Grouping and Government Sector ................................. 4-2

4-2 Stationary Combustion Turbine Projections .......................... 4-4

5-1 Total Expenditures in 1996 ($103) ................................. 5-6

5-2 Number of Electricity Suppliers in 1999 ............................. 5-8

5-3 Top Power Marketing Companies, First Quarter 1999 ................. 5-12

5-4 Industry Capability by Energy Source, 2000 ......................... 5-16

5-5 Installed Capacity at U.S. Nonutility Attributed to Major Industry Groups 

and Census Division, 1995 through 1999 (MW) ...................... 5-16

5-6 Existing Capacity at U.S. Electric Utilities by Prime Mover and Energy 

Source, as of January 1, 1998 .................................... 5-18

5-7 Key Parameters in the Cases ..................................... 5-20

5-8 Capacity Additions and Retirements at U.S. Electric Utilities by Energy 

Source, 1997 ................................................ 5-21

5-9 Fossil-Fueled Existing Capacity and Planned Capacity Additions at 

U.S. Electric Utilities by Prime Mover and Primary Energy Source, 

as of January 1, 1998 .......................................... 5-22

5-10 U.S. Electric Utility Retail Sales of Electricity by Sector, 1989 Through 
ix

July 1999 (Million kWh) ........................................ 5-23

6-1 Comparison of Modeling Approaches ............................... 6-3

6-2 Supply and Demand Elasticities .................................. 6-10

6-3 Fuel Price Elasticities .......................................... 6-10

6-4 Supply and Demand Elasticities for Industrial and Commercial Sectors ..... 6-14

7-1 Total Capital and Annual Cost of the Proposed NSPS in the Fifth Year ..... 7-2

7-2 Summary of Turbine Cost Information and Supply Shifts ................ 7-3

7-3 Market-Level Impacts of Stationary Combustion Turbines NSPS: 2010 .... 7-5

7-4 Changes in Market Shares for Electricity Suppliers ..................... 7-6

7-5 Distribution of Social Costs of Stationary Combustion Turbines NSPS: 2010 . 7-7
x

SELECT LIST OF ACRONYMS AND ABBREVIATIONS

CAA: Clean Air Act

CO: Carbon Monoxide

COPD: Chronic Obstructive Pulmonary Disease

CCCT: Combined-Cycle Combustion Turbine

C/S: Cost to Sales Ratio

DOE: Department of Energy

EO: Executive Order

EPA: Environmental Protection Agency

EWG: Exempt Wholesale Generators

GW: Gigawatt

HAP: Hazardous Air Pollutant

ICCR: Industrial Combustion Coordinated Rulemaking

IPP: Independent Power Producer

kWh: Kilowatt Hour

lb: Pound

mills/kWh: Mills per Kilowatt Hour

mmBTU: Millions of British Thermal Units

MACT: Maximum Achievable Control Technology

MW: Megawatts

Mwh: Megawatt Hours

NAAQS: National Ambient Air Quality Standards 

NAICS: North American Industrial Classification System

NESHAP: National Emission Standards for Hazardous Air Pollutants

NPR: Notice of Proposed Rulemaking
xi

NSPS: New Source Performance Standards

NSR: New Source Review

OMB: Office of Management and Budget

O&M: Operation and Maintenance

P/E: Partial Equilibrium

PM: Particulate Matter

ppbdv: Parts Per Billion, dry volume

ppm: Parts Per Million

PRA: Paperwork Reduction Act of 1995

RFA: Regulatory Flexibility Act

SAB: Science Advisory Board

SBA: Small Business Administration

SBREFA: Small Business Regulatory Enforcement Fairness Act of 1996

SCCT: Simple-Cycle Combustion Turbine

SIC: Standard Industrial Classification 

SOA: Secondary Organic Aerosols

TAC: Total Annual Cost

tpd: Tons Per Day

tpy: Tons Per Year

UMRA: Unfunded Mandates Reform Act

VOCs: Volatile Organic Compounds
1Office 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.

1-1

SECTION 1

INTRODUCTION

The U.S. Environmental Protection Agency (referred to as EPA or the Agency)

is developing regulations under Section 111 of the Clean Air Act (CAA) for new stationary

combustion turbines. The majority of stationary combustion turbines burn natural gas and

are used in the electric power and natural gas industries. The regulations are designed to

reduce emissions of nitrogen oxides (NOx) and sulfur dioxide (SO2) generated by the

combustion of fossil fuels in new combustion turbines. To inform this rulemaking, the

Innovative Strategies and Economics Group (ISEG) of EPA’s Office of Air Quality Planning

and Standards (OAQPS) has developed an economic impact analysis (EIA) to estimate the

potential social costs of the regulation. This report presents the results of this analysis in

which a market model was used to analyze the impacts of the air pollution rule on society.

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. In addition,

Executive Order (EO) 12866 requires a more comprehensive analysis of benefits and costs

for significant regulatory actions.1 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. Also, Executive Order 13211 requires EPA to

consider for particular rules the impacts on energy markets. 

1.2 Scope and Purpose

The CAA’s purpose is to protect and enhance the quality of the nation’s air

resources (Section 101(b)). Section 111 of the CAA establishes the authority of EPA to set

new source performance standards (NSPS) for criteria pollutants. This report evaluates the

economic impacts of pollution control requirements placed on stationary combustion

turbines under these amendments. These control requirements are designed to reduce

releases of NOx and SO2 from new sources into the atmosphere.

The regulation affects new stationary combustion turbines over 1 megawatt

(MW). To estimate the economic impacts associated with the regulation, new stationary

combustion turbines are projected through the fifth year after promulgation. 
1-2

1.3 Organization of the Report

The remainder of this report is divided into six sections that describe the

methodology and present results of this analysis:

C Section 2 provides background information on combustion turbine technologies

and compares the equipment, installation, and operating costs of simple-cycle

combustion turbines (SCCTs) and combined-cycle combustion turbines (CCCTs).

C Section 3 provides background information on the regulatory alternatives

examined, information on the emission reductions associated with the rule, and

health effects from exposure to the NOx emitted by combustion turbines.

C Section 4 provides projections of new stationary combustion turbines through the

fifth year after promulgation. This section also profiles the population of existing

turbines.

C Section 5 profiles the electric service industry (NAICS 221).

C Section 6 presents the methodology for assessing the economic impacts of the

NSPS and describes the computerized market model used to estimate the social

cost impacts and to disaggregate impacts into changes in producer and consumer

surplus.

C Section 7 presents the economic impact estimates for the NSPS . This section

also discusses the regulation’s impact on energy supply, distribution, and use. 

C Section 8 provides the Agency’s analysis of the regulation’s impact on small

entities.

In addition to these sections, Appendix A details the market model approach used to predict

the economic impacts of the NSPS. Appendix B describes the limitations of the data and

market model and presents sensitivity analyses associated with key assumptions.
2Combustion turbine technology used for aircraft engines is virtually the same except the energy is used to

generate thrust.

3

Spinning reserves are unloaded generating capacity that is synchronized to the grid that can begin to respond

immediately to correct for generation/load imbalances caused by generation and transmission outages and

that is fully available within 10 minutes. Black-start capacity refers to generating capacity that can be made

fully available within 30 to 60 minutes to back up operating reserves and for commercial purposes.

2-1

SECTION 2

COMBUSTION TURBINE TECHNOLOGIES AND COSTS

This section provides background information on combustion turbine

technologies. Included is a discussion of simple-cycle combustion turbines (SCCTs) and

combined-cycle combustion turbines (CCCTs), along with a comparison of fuel efficiency

and capital costs between the two classes of turbines. 

2.1 Simple-Cycle Combustion Turbine Technologies

Most stationary combustion turbines use natural gas to generate shaft power

that is converted into electricity.2

 Combustion turbines have four basic components, as

shown in Figure 2-1.

1. The compressor raises the air pressure up to thirty times atmospheric.

2. A fuel compressor is used to pressurize the fuel.

3. The compressed air is heated in the combustion chamber at which point fuel is

added and ignited.

4. The hot, high pressure gases are then expanded through a power turbine,

producing shaft power, which is used to drive the air and fluid compressors and a

generator or other mechanical drive device. Approximately one-third of the

power developed by the power turbine can be required by the compressors.

Electric utilities primarily use simple-cycle combustion turbines as peaking or backup units. 

Their relatively low capital costs and quick start-up capabilities make them ideal for partial

operation to generate power at periods of high demand or to provide ancillary services, such

as spinning reserves or black-start back-up capacity.3 The disadvantage of simple-cycle
2-2

systems is that they are relatively inefficient, thus making them less attractive as base load

generating units.

2.2 Combined-Cycle Combustion Turbines Technologies

The combined-cycle system incorporates two simple-cycle systems into one

generation unit to maximize energy efficiency. Energy is produced in the first cycle using a

gas turbine; then the heat that remains is used to create steam, which is run through a steam

turbine. Thus, two single units, gas and steam, are put together to minimize lost potential

energy.

The second cycle is a steam turbine. In a CCCT, the waste heat remaining from

the gas turbine cycle is used in a boiler to produce steam. The steam is then put through a

steam turbine, producing power. The remaining steam is recondensed and either returned to

the boiler where it is sent through the process again or sold to a nearby industrial site to be

used in a production process. Figure 2-2 shows a gas-fired CCCT.

Figure 2-1. Simple-Cycle Gas Turbine

Source: Hay, Nelson E., ed. 1988. Guide to Natural Gas Cogeneration. Lilburn, GA: The Fairmont Press,

Inc.
2-3

There are significant efficiency gains in using a combined-cycle turbine

compared to simple-cycle systems. With SCCTs, adding a second stage allows for heat that

otherwise would have been emitted and completely wasted to be used to create additional

power or steam for industrial purposes. For example, a SCCT with an efficiency of 38.5

percent, adding a second stage increases the efficiency to 58 percent, a 20 percent increase in

efficiency (Siemens, 1999). General Electric (1999) has recently developed a 480 MW

system that will operate at 60 percent net combined-cycle efficiency. 

In addition to energy efficiency gains, CCCTs also offer environmental

efficiency gains compared to existing coal plants. In addition, efficiency gains associated

with the CCCT lead to lower emissions compared to SCCTs. As Table 2-1 shows, the 58

percent efficiency turbine decreases NOx

 emissions by 14 percent over simple-cycle

combustion turbines and 89 percent over existing coal electricity generation plants. In

addition, CO2 emissions will be 5 percent lower than emissions from SCCTs and 64 percent

lower than existing coal plants.

Figure 2-2. Combined-Cycle Gas Turbine

Source: Siemens Westinghouse. August 31, 1999. Presentation. 
2-4

2.3 Capital and Installation Costs

CCCT capital and installation costs are approximately 30 percent less ($/MW)

than a conventional coal or oil steam power plant’s capital and installation costs, and CCCT

costs are likely to decrease over the next 10 years. Gas turbine combined-cycle plants range

from approximately $300 per kW installed for very large utility-scale plants to $1,000 per

kW ($1998) for small industrial cogeneration installation (GTW Handbook, 1999). However,

the prices of construction can vary as a result of local labor market conditions and the

geographic conditions of the site (GTW Handbook, 1999). SCCTs are approximately half the

cost of CCCT units.

Table 2-2 breaks down the budgeted construction costs of a gas-fired 107 MW

combined-cycle cogenerating station at John F. Kennedy International Airport that was

installed several years ago. As shown in Table 2-2, the construction price can range

dramatically. This job finished near the top of the budget, close to $133,600,000. According

to Gas Turbine World, the typical budget price for a 168 MW plant is $80,600,000,

($480/kW) for a plant with net efficiency of 50.9 percent (GTW Handbook, 1999).

2.4 O&M Costs Including Fuel

Fuel accounts for one-half to two-thirds of total production costs (annualized

capital, operation and maintenance, fuel costs) associated with generating power using

combustion turbines. Table 2-3 compares the percentage of costs spent on annualized

capital, operation and maintenance, and fuel for both simple turbines and CCCTs.

Table 2-1. Comparison of Emissions from Coal-Fired and Simple-Cycle Turbines and

Combined-Cycle Turbines

NOx

(lb/MW-hr)

CO2

(lb/MW-hr)

Coal electricity generation 5.7 2,190

Simple-cycle turbines 0.7 825

Combined-cycle turbines 0.6 780

Source: Siemens Westinghouse. August 31, 1999. Presentation.
2-5

The fuel costs may vary depending on the plant’s location. In areas where gas

costs are high, for a base-load CCCT power plant, fuel costs can account for up to 70 percent

of total plant costs—including acquisition, owning and operating costs, and debt service

Table 2-3. Comparison of Percentage of Costs

a

Simple Cycle Combined Cycle

% Capital costs 50 25

% Operation and maintenance 10 10

% Fuel 40 65

a Based on a review of marketing information from turbine manufacturers and the GTW Handbook.

Table 2-2. Overall Installation Costs

Construction costs can vary dramatically. This table shows the budgeted cost for a gas-fired

107 MW combined-cycle cogenerating station at John F. Kennedy International Airport in

Brooklyn, New York. The power plant uses two 40 MW Stewart & Stevenson LM6000 gas

turbine generators each exhausting into a triple pressure heat recovery steam generator raising

steam for processes and to power a nominal 27 MW steam turbine generator. Budgeted prices are

in 1995–1996 U.S. dollars.

Budget Equipment Pricing $ Amount

Gas turbine generators $24,000,000

Heat recovery steam generators 10,000,000

Steam turbine generator set 4,000,000

Condenser 300,000

Cooling towers 800,000

Transformer and switchgear 8,000,000

Balance of plant equipment 7,500,000

Subtotal, equipment $54,600,000

Budget Services and Labor

Mechanical and electrical construction $20-75,000,000

Engineering 4,000,000

Subtotal, services $24-79,000,000

Total Capital Cost $78,600,000-133,600,000

Source: 1998–99 GTW Handbook. “Turnkey Combined Cycle Plant Budget Price Levels.” Fairfield, CT: 

Pequot Pub. Pgs. 16–26.
2-6

(GTW Handbook, 1999). General Electric’s “H” design goals for future CCCT systems are

to reduce power plant operating costs by at least 10 percent compared to today’s technology

as a direct result of using less fuel. The higher efficiency allows more power to be generated

with the same amount of fuel, resulting in a substantial fuel cost savings for the plant owner

(General Electric, 1999).
3-1

SECTION 3

BACKGROUND ON HEALTH AFFECTS AND REGULATORY ALTERNATIVES

3.1 Background

Section 111 of the CAA requires EPA to establish NSPS for major and area

sources within various source categories.

3.1.1 Summary of the Proposed Stationary Combustion Turbines NSPS

Does the proposed rule apply to me?

The proposed standards would apply to new stationary combustion turbines

with a power output at peak load greater than or equal to 1 MW. The applicability of the

proposed rule is similar to that of existing 40 CFR part 60, subpart GG, except that the

proposed rule would apply to new stationary combustion turbines, and their associated heat

recovery steam generators (HRSG) and duct burners. A new stationary combustion turbine

is defined as any simple cycle combustion turbine, regenerative cycle combustion turbine, or

combined cycle steam/electric generating system that is not self propelled and that

commences construction, modification, or reconstruction after proposal. The new stationary

combustion turbines subject to the proposed standards are exempt from the requirements of

40 CFR part 60, subpart GG. Heat recovery steam generators and duct burners subject to the

proposed rule would be exempt from the requirements of 40 CFR part 60, subparts Da and

Db.

What pollutants would be regulated?

The pollutants to be regulated by the proposed standards are NOx

 and SO2

.

What is the affected source?

The affected source for the proposed stationary combustion turbine NSPS is

each stationary combustion turbine with a power output at peak load greater than or equal to

1 MW, that commences construction, modification, or reconstruction after proposal. 

Integrated gasification combined cycle (IGCC) combustion turbine facilities covered by

subpart Da of 40 CFR part 60 (the Utility NSPS) are exempt from the requirements of the

proposed rule.

What emission limits must I meet?

The format of the proposed standards for NOx is an output-based emission limit

in units of emissions mass per unit useful recovered energy, nanograms/Joule (ng/J) or

pounds per megawatt-hour (lb/MW-hr). There are four subcategories, and thus four separate

output-based NOx limits. These are presented in Table 3-1. The output of the turbine does
3-2

not include any steam turbine output and refers to the rating of the combustion turbine itself.

Table 3-1. NOx

 Emission Standards (ng/J)

Combustion Turbine Fuel

Type

Combustion Turbine Size

<30 MW >30 MW

Natural gas 132 (1.0 lb/MW-hr) 50 (0.39 lb/MW-hr)

Oil and other fuel 234 (1.9 lb/MW-hr) 146 (1.2 lb/MW-hr)

We have determined that it is appropriate to exempt emergency combustion

turbines from the NOx

 limit. We have defined these units as turbines that operate in

emergency situations. For example, turbines used to supply electric power when the local

utility service is interrupted are considered to fall under this definition. In addition, we are

proposing that combustion turbines used by manufacturers in research and development of

equipment for both combustion turbine emission control techniques and combustion turbine

efficiency improvements be exempted from the NOx

 limit. Given the small number of

turbines that are expected to fall under this category and since there is not one definition that

can provide an all-inclusive description of the type of research and development work that

qualifies for the exemption from the NOx limit, we have decided that it is appropriate to

make these exemption determinations on case by case basis only.

The proposed standard for SO2

 is the same for all turbines regardless of size

and fuel type. You may not cause to be discharged into the atmosphere from the subject

stationary combustion turbine any gases which contain SO2

 in excess of 73 ng/J (0.58

lb/MW-hr). You would be able to choose to comply with the SO2 limit itself or with a limit

on the sulfur content of the fuel. We are proposing this sulfur content limit to be 0.05

percent by weight (500 parts per million by weight (ppmw)).

If I modify or reconstruct my existing turbine, does the proposed rule apply to

me?

The proposed standards would apply to stationary combustion turbines that are

modified or reconstructed after proposal. The guidelines for determining whether a source is

modified or reconstructed are given in 40 CFR 60.14 and 60.15, respectively.

How do I demonstrate compliance?

In order to demonstrate compliance with the NOx limit, an initial performance

test is required. If you are using water or steam injection, you must continuously monitor

your water or steam to fuel ratio in order to demonstrate compliance and you are not required

to perform annual stack testing to demonstrate compliance. If you are not using water or

steam injection, you would conduct performance tests annually following the initial

performance test in order to demonstrate compliance. Alternatively, you may choose to

demonstrate continuous compliance with the use of a continuous emission monitoring system
3-3

(CEMS) or parametric monitoring; if you choose this option, you are not required to conduct

subsequent annual performance tests.

If you are using a NOx

 CEMS, the initial performance test required under 40

CFR 60.8 may, alternatively, coincide with the relative accuracy test audit (RATA). If you

choose this as your initial performance test, you must perform a minimum of nine reference

method runs, with a minimum time per run of 21 minutes, at a single load level, between 90

and 100 percent of peak (or the highest achievable) load. You must use the test data both to

demonstrate compliance with the applicable NOx emission limit and to provide the required

reference method data for the RATA of the CEMS. The requirement to test at three

additional load levels is waived. 

What monitoring requirements must I meet?

If you are using water or steam injection to control NOx emissions, you would

have to install and operate a continuous monitoring system to monitor and record the fuel

consumption and the ratio of water or steam to fuel being fired in the turbine. Alternatively,

you could use a CEMS consisting of NOx and oxygen (O2) or carbon dioxide (CO2)

monitors. During each full unit operating hour, each monitor would complete a minimum of

one cycle of operation for each 15-minute quadrant of the hour. For partial unit operating

hours, at least one valid data point would be obtained for each quadrant of the hour in which

the unit operates.

If you operate any new turbine which does not use water or steam injection to

control NOx emissions, you would have to perform annual stack testing to demonstrate

continuous compliance with the NOx limit. Alternatively, you could elect either to use a

NOx

 CEMS or perform continuous parameter monitoring as follows:

(1) For a diffusion flame turbine without add-on selective catalytic reduction

(SCR) controls, you would define at least four parameters indicative of the unit’s NOx

formation characteristics, and you would monitor these parameters continuously.

(2) For any lean premix stationary combustion turbine, you would continuously

monitor the appropriate parameters to determine whether the unit is operating in the lean

premixed combustion mode.

(3) For any turbine that uses SCR to reduce NOx

 emissions, you would

continuously monitor appropriate parameters to verify the proper operation of the emission

controls.

(4) For affected units that are also regulated under part 75 of this chapter, if

you elect to monitor the NOx emission rate using the methodology in appendix E to part 75

of this chapter, or the low mass emissions methodology in 40 CFR 75.19, the monitoring

requirements of the turbine NSPS may be met by performing the parametric monitoring

described in section 2.3 of appendix E of part 75 of this chapter or in 40 CFR

75.19(c)(1)(iv)(H). 
3-4

Alternatively, you could petition the Administrator for other acceptable

methods of monitoring your emissions. If you choose to use a CEMS or perform parameter

monitoring to demonstrate continuous compliance, annual stack testing is not required.

If you operate any stationary combustion turbine subject to the provisions of the

proposed rule, and you choose not to comply with the SO2

 stack limit, you would monitor

the total sulfur content of the fuel being fired in the turbine. There are several options for

determining the frequency of fuel sampling, consistent with appendix D to part 75 of this

chapter for fuel oil; and the sulfur content would be determined and recorded once per unit

operating day for gaseous fuel, unless a custom fuel sampling schedule is used. 

Alternatively, you could elect not to monitor the total sulfur content of the fuel combusted in

the turbine, if you demonstrate that the fuel does not to exceed a total sulfur content of 300

ppmw. This demonstration may be performed by using the fuel quality characteristics in a

current, valid purchase contract, tariff sheet, or transportation contract, or through

representative fuel sampling data which show that the sulfur content of the fuel does not

exceed 300 ppmw. 

If you choose to monitor combustion parameters or parameters indicative of

proper operation of NOx emission controls, the appropriate parameters would be

continuously monitored and recorded during each run of the initial performance test, to

establish acceptable operating ranges, for purposes of the parameter monitoring plan for the

affected unit. 

If you are required to periodically determine the sulfur content of the fuel

combusted in the turbine, a minimum of three fuel samples would be collected during the

performance test. For liquid fuels, the samples for the total sulfur content of the fuel must be

analyzed using American Society of Testing and Materials (ASTM) methods D129-00,

D2622-98, D4294-02, D1266-98, D5453-00 or D1552-01. For gaseous fuels, ASTM

D1072-90 (Reapproved 1999); D3246-96; D4468-85 (Reapproved 2000); or D6667-01 must

be used to analyze the total sulfur content of the fuel. 

The applicable ranges of some ASTM methods mentioned above are not

adequate to measure the levels of sulfur in some fuel gases. Dilution of samples before

analysis (with verification of the dilution ratio) may be used, subject to the approval of the

Administrator. 

What reports must I submit?

For each affected unit for which you continuously monitor parameters or

emissions, or periodically determine the fuel sulfur content under the proposed rule, you

would submit reports of excess emissions and monitor downtime, in accordance with 40 CFR

60.7(c). Excess emissions would be reported for all 4-hour rolling average periods of unit

operation, including startup, shutdown, and malfunctions where emissions exceed the

allowable emission limit or where one or more of the monitored process or control

parameters exceeds the acceptable range as determined in the monitoring plan. 
3-5

3.2 Health Effects Associated with NOx

 and SO2

 Emissions from Stationary

Combustion Turbines

3.2.1 Benefits of Reduced Nitrous Oxide Emissions

Emissions of NOx produce a wide variety of health and welfare effects. 

Nitrogen dioxide can irritate the lungs at high occupational levels and may lower resistance

to respiratory infection (such as influenza), although the research has been equivocal. NOx

emissions are an important precursor to acid rain and may affect both terrestrial and aquatic

ecosystems. Atmospheric deposition of nitrogen leads to excess nutrient enrichment

problems (“eutrophication”) in the Chesapeake Bay and several nationally important

estuaries along the East and Gulf Coasts. Eutrophication can produce multiple adverse

effects on water quality and the aquatic environment, including increased algal blooms,

excessive phytoplankton growth, and low or no dissolved oxygen in bottom waters. 

Eutrophication also reduces sunlight, causing losses in submerged aquatic vegetation critical

for healthy estuarine ecosystems. Deposition of nitrogen-containing compounds also affects

terrestrial ecosystems. Nitrogen fertilization can alter growth patterns and change the

balance of species in an ecosystem.

Nitrogen dioxide and airborne nitrate also contribute to pollutant haze (often

brown in color), which impairs visibility and can reduce residential property values and the

value placed on scenic views.

NOx in combination with volatile organic compounds (VOC) also serves as a

precursor to ozone. Based on a large number of recent studies, EPA has identified several

key health effects that may be associated with exposure to elevated levels of ozone. 

Exposures to high ambient ozone concentrations have been linked to increased hospital

admissions and emergency room visits for respiratory problems. Repeated exposure to

ozone may increase susceptibility to respiratory infection and lung inflammation and can

aggravate preexisting respiratory disease, such as asthma. Repeated prolonged exposures

(i.e., 6 to 8 hours) to ozone at levels between 0.08 and 0.12 ppb, over months to years may

lead to repeated inflammation of the lung, impairment of lung defense mechanisms, and

irreversible changes in lung structure, which could in turn lead to premature aging of the

lungs and/or chronic respiratory illnesses such as emphysema, chronic bronchitis, and

asthma.

Children have the highest exposures to ozone because they typically are active

outside playing and exercising, during the summer when ozone levels are highest. Further,

children are more at risk than adults from the effects of ozone exposure because their

respiratory systems are still developing. Adults who are outdoors and moderately active

during the summer months, such as construction workers and other outdoor workers, also are

among those with the highest exposures. These individuals, as well as people with

respiratory illnesses such as asthma, especially children with asthma, experience reduced

lung function and increased respiratory symptoms, such as chest pain and cough, when

exposed to relatively low ozone levels during periods of moderate exertion. In addition to

human health effects, ozone adversely affects crop yield, vegetation and forest growth, and

the durability of materials. Ozone causes noticeable foliar damage in many crops, trees, and
3-6

ornamental plants (i.e., grass, flowers, shrubs, and trees) and causes reduced growth in

plants. 

Particulate matter (PM) can also be formed from NOx

 emissions. Secondary

PM is formed in the atmosphere through a number of physical and chemical processes that

transform gases such as sulfur dioxide, NOx

, and VOC into particles. Scientific studies have

linked PM (alone or in combination with other air pollutants) with a series of health effects

(see Chapter 8 for a detailed discussion of studies used to evaluate health impacts of PM

emissions). Coarse particles can accumulate in the respiratory system and aggravate health

problems such as asthma. Fine particles can penetrate deep into the lungs and are more

likely than coarse particles to contribute to a number of the health effects. These health

effects include decreased lung function and alterations in lung tissue and structure and in

respiratory tract defense mechanisms which may be manifest in increased respiratory

symptoms and disease or in more severe cases, increased hospital admissions and emergency

room visits or premature death. Children, the elderly, and people with cardiopulmonary

disease, such as asthma, are most at risk from these health effects.

PM also causes a number of adverse effects on the environment. Fine PM is the

major cause of reduced visibility in parts of the United States, including many of our national

parks and wilderness areas. Other environmental impacts occur when particles deposit onto

soil, plants, water, or materials. For example, particles containing nitrogen and sulfur that

deposit onto land or water bodies may change the nutrient balance and acidity of those

environments, leading to changes in species composition and buffering capacity.

Particles that are deposited directly onto leaves of plants can, depending on

their chemical composition, corrode leaf surfaces or interfere with plant metabolism. 

Finally, PM causes soiling and erosion damage to materials.

Thus, reducing the emissions of NOx from stationary combustion turbines can

help to improve some of the effects mentioned above, either those directly related to NOx

emissions, or the effects of ozone and PM resulting from the combination of NOx

 with other

pollutants. 

3.2.2 Benefits of Sulfur Dioxide Reductions

Very high concentrations of sulfur dioxide (SO2) affect breathing and ambient

levels have been hypothesized to aggravate existing respiratory and cardiovascular disease. 

Potentially sensitive populations include asthmatics, individuals with bronchitis or

emphysema, children and the elderly. SO2 is also a primary contributor to acid deposition, or

acid rain, which causes acidification of lakes and streams and can damage trees, crops,

historic buildings and statues. In addition, sulfur compounds in the air contribute to visibility

impairment in large parts of the country. This is especially noticeable in national parks.

PM can also be formed from SO2 emissions. Secondary PM is formed in the

atmosphere through a number of physical and chemical processes that transform gases, such

as SO2, into particles. Overall, emissions of SO2 can lead to some of the effects discussed in

this section—either those directly related to SO2 emissions, or the effects of ozone and PM

resulting from the combination of SO2 with other pollutants. 
4-7

3.3 Emission Reductions from the Proposed NSPS

The reductions of NOx from this proposed NSPS for new stationary combustion

turbines will essentially be zero because the new turbines that may need to install add-on

controls to meet the NOx emissions limits will already be required to install these add-on

controls to meet NOx reduction requirements under the Prevention of Significant

Deterioration/New Source Review (PSD/NSR) programs. Therefore, we conclude that the

NOx reductions resulting from the proposed rule will essentially be zero. The expected SO2

reductions resulting from the proposed rule will be approximately 830 tons/year in the fifth

year after promulgation of the standards. 

3.4 Summary of the Rule

The EPA is planning to propose an output-based NOx emission standard for

natural gas-fired turbines, based on emissions of 15 ppm and the efficiency of a combined

cycle turbine (48 percent) for turbines larger than 30 MW. For natural gas-fired turbines

smaller than 30 MW, the proposed NOx standard will be based on emissions of 25 ppm and

an efficiency of 30 percent. For distillate oil-fired turbines, the proposed NOx standard will

be based on 42 ppm for all sizes of turbines, with the same efficiencies as the limits for

natural gas-fired units. The result of this NOx standard will likely be that a small number of

simple cycle turbines larger than 30 MW may need to install selective catalytic reduction

(SCR) in order to meet the standard. However, EPA expects that these turbines will already

be required to install add-on controls to reduce NOx emissions in order to comply with other

regulatory programs such as PSD/NSR.

The standard for SO2 will be the same for all turbines regardless of size and fuel

type. Owner/operators can choose to either meet an SO2 standard of 73 nanograms/Joule

(0.58 lb/MW-hr), or burn fuel in the turbine which contains total sulfur less than or equal to

0.05 percent by weight (500 ppmw).

SECTION 4

PROJECTION OF UNITS AND FACILITIES IN AFFECTED SECTORS
4-1

The regulation will affect new turbine units with capacity over 1 MW. As a

result, the economic impact estimates presented in Section 7 and the small entity screening

analysis presented in Section 8 are based on the population of existing units and the

projection of new combustion turbine units for the next 5 years. This section begins with a

review of the technical characteristics and industry distribution of existing combustion

turbines contained in the Agency’s Inventory Database. It presents projected growth

estimates for combustion turbines greater than 1 MW and describes trends in the electric

utility industry. It also presents (in Section 4.3) the estimated number of new combustion

turbines that will be affected by this rule.

4.1 Profile of Existing Combustion Turbine Units

4.1.1 Distribution of Units and Facilities by Industry

Table 4-1 presents the number of combustion turbines and facilities owning

turbines by NAICS code. Forty-seven percent of existing combustion turbines are in

Utilities (NAICS 221), 22 percent are in Pipeline Transportation, and 18 percent are in Oil

and Gas Extraction (NAICS 211). Section 4 presents industry profiles for the electric power,

natural gas pipelines, and oil and gas industries. The remaining units are primarily

distributed across the manufacturing sector and are concentrated in the chemical and

petroleum industries. 

4.1.2 Technical Characteristics

This section characterizes the population of 2,072 units by MW capacity, fuel

type, hours of operation, annual MWh produced (or equivalent), and simple or combined

cycle. 

C MW Capacity: Unit capacities in the population range between 1 and 368 MW. 

Although some units have large capacities in excess of 100 MW, about half

(1,000 units) have capacities between 1 and 10 MW (see Figure 4-1). Only

approximately 13 percent (278 units) have capacities greater than 100 MW. The

total estimated capacity of all the units in the population is 79,909 MW.
4-2

Table 4-1. Facilities With Units Having Capacities Above 1 MW by Industry Grouping

and Government Sector

NAICS Description # Units # Facilities

112 Animal Production 1 1

211 Oil and Gas Extraction 365 105

212 Mining (Except Oil and Gas) 3 3

221 Utilities 983 393

233 Building, Developing, and General Contracting 1 1

235 Special Trade Contractors 2 1

311 Food Manufacturing 18 11

321 Wood Products Manufacturing 3 2

322 Paper Manufacturing 17 11

324 Petroleum and Coal Products Manufacturing 34 11

325 Chemical Manufacturing 63 39

326 Plastics and Rubber Products Manufacturing 4 3

327 Nonmetallic Mineral Product Manufacturing 1 1

331 Primary Metal Manufacturing 13 4

332 Fabricated Metal Product Manufacturing 2 2

333 Machinery Manufacturing 2 2

334 Computer and Electronic Product Manufacturing 6 5

335 Electrical Equipment, Appliance, and Component

Manufacturing

1 1

336 Transportation Equipment Manufacturing 3 3

337 Furniture and Related Product Manufacturing 1 1

339 Miscellaneous Manufacturing 3 3

422 Wholesale Trade, Nondurable Goods 6 4

486 Pipeline Transportation 448 244

488 Support Activities for Transportation 1 1

513 Broadcasting and Telecommunications 1 1

522 Credit Intermediation and Related Activities 3 1

541 Professional, Scientific, and Technical Services 2 2

561 Administrative and Support Services 1 1

611 Educational Services 10 8

622 Hospitals 23 14

721 Accommodation 1 1

923 Administration of Human Resource Programs 1 1

926 Administration of Economic Programs 1 1

928 National Security and International Affairs 42 12

Unknown Industry Classification Unknown 6 5

Total 2,072 899

Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the

Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking

Federal Advisory Committee. EPA Docket Numbers A-94-63, II-K-4b2 through -4b5. Research

Triangle Park, North Carolina. September 16-17.
4-3

Figure 4-1. Number of Units by MW Capacity

C Fuel type: To determine the breakdown of turbines by fuel type, the EPA Region

4 spreadsheet of national combustion turbines permitted in the past few years was

used. According to the spreadsheet, 41 percent of turbines were dual fuel, 3

percent fired distillate oil only, and the remaining 56 percent fired natural gas

only. Many dual fuel turbines are permitted to operate up to 10 percent of the

time on distillate oil, so for purposes of this estimate it was assumed that dual fuel

turbines would operate 10 percent of the time on distillate oil. 

C Hours of Operation: The Combustion Turbine MACT EIA used assumptions that

new simple cycle stationary combustion turbines typically operate at a 20 percent

capacity factor (or 1,752 hours per year) and combined cycle turbines typically

operate at a 60 percent capacity factor (or 5,256 hours per year). These figures

are based on information submitted during the public comment period for the

proposed Stationary Combustion NESHAP. The same hours of operation are

used in this analysis.
4-4

Table 4-2. Stationary Combustion Turbine Projections

Total Number of New Units

Simple cycle 286

Combined cycle 69

Total in 5th year 355

Average per year 71

Figure 4-2. Number of Units by Annual MWh Output Equivalent

Note: Excludes 245 units for which information on annual hours of operation was unavailable.

C Annual MWh Equivalent: Figure 4-2 presents the distribution of units by the

estimated annual MWh equivalent produced by each unit. For units that are used

for compression or other functions, their likely MWh output was estimated using

their MW capacity and annual hours of operation. Annual MWh for 245 units

lacking annual hours of operation information was not calculated. Figure 4-3

includes data for the other 1,827 units, more than one-third of which have output

of between 10,000 and 50,000 MWh a year. 360 units have output of less than

5,000 MWh, and 217 units have output greater than 500,000 MWh.

C Simple vs. combined cycle: The Inventory Database did not distinguish between

simple and combined cycle turbines. In order to determine the breakdown
4-5

between simple and combined cycle units, the EPA’s RACT/BACT/LAER

Clearinghouse and the national list of combustion turbines maintained by EPA

Region 4 were consulted. Both of those sources showed that the vast majority of

turbines rated less than 30 MW are simple cycle. For turbines that are larger than

30 MW, approximately 40 percent were simple cycle and 60 percent were

combined cycle. 

4.2 Projected Growth of Combustion Turbines

The Agency estimates there will be a total of 355 new stationary turbines over

the next 5 years (see Table 4-2). This projection is based on a survey of gas turbine orders

for the period of June 2002 to May 2003 in the October 2003 Diesel & Gas Turbine

Worldwide (D>W) Power Generation Order Survey. The breakdown of turbines

classified as simple and combined cycle was estimated by using EPA’s RACT/BACT/LAER

Clearinghouse and the national list of combustion turbines maintained by EPA Region 4. 

4.3 Projected Number of Affected Stationary Combustion Turbines

We estimate that 10 of the new simple-cycle turbines in the 30 to 120 MW

range will install selective catalytic reduction (SCR) to meet the NOx emission standard for

the Gas Turbine NSPS. It is possible that some units could install a heat recovery steam

generator (HRSG). Although a HRSG is more expensive than SCR, it has the benefit of

increased power output and therefore may be a more attractive option. However, for

purposes of this estimate, it was assumed that SCR would be used to comply with the rule. 

Combined-cycle units and simple-cycle units less than 30 MW or greater than 120 MW will

not need to install a HRSG or SCR since turbines that do not exceed the NOx emissions

limits and meet the efficiency requirements are available. Existing sources are not required

to comply with emission requirements in the rule. 

Based on the projected estimates of simple-cycle units in the 30 to 60 MW and

60 to 120 MW ranges, a total of 10 units are expected to install an SCR. Two 30 to 60 MW

units and eight 60 to 120 MW units are expected to install SCR. 

It should be noted that these 10 new turbines will already be required to install

these add-on controls to meet NOx reduction requirements under the PSD/NSR programs. 

Thus, we conclude that the control costs resulting from the proposed NSPS will be

essentially zero. These sources and other affected sources are expected to follow monitoring,

record keeping, and reporting requirements, conduct fuel sampling, and conduct initial

performance testing. 
5-6

SECTION 5

PROFILE OF THE ELECTRIC UTILITY INDUSTRY

The Agency anticipates that all of the direct costs of the regulation will be borne

by the electric services (NAICS 22111) sector. The Agency projects that growth in new

combustion turbines that will be affected by the regulation will also be concentrated in the

electric services. This section contains background information on this industry to help

inform the regulatory process. 

5.1 Electric Utility Industry (NAICS 22111)

This profile of the U.S. electric power industry provides background

information on the evolution of the electricity industry, the composition of a traditional

regulated electric utility, the current market structure of the electric industry, and

deregulation trends and the potential future market structure of the electricity market. This
5-1

profile also discusses current industry characteristics and trends that will influence the future

generation and consumption of electricity.

5.1.1 Market Structure of the Electric Power Industry

The ongoing process of deregulation of wholesale and retail electric markets is

changing the structure of the electric power industry. Deregulation is leading to the

functional unbundling of generation, transmission, and distribution and to competition in the

generation segment of the industry. This section provides background on the current

structure of the industry and future deregulation trends. It begins with a brief overview of

the evolution of the electric power industry because the future market structure will, in large

part, be determined by the existing infrastructure and capital assets that have evolved over

the past decades.

5.1.1.1 The Evolution of the Electric Power Industry

The electric utility industry began as isolated local service systems with the first

electric companies evolving in densely populated metropolitan areas like New York and

Chicago. Prior to World War I, rural electrification was a piecemeal process. Only small,

isolated systems existed, typically serving a single town. The first high-voltage transmission

network was built in the Chicago area in 1911 (the Lake County experiment). This new

network connected the smaller systems surrounding Chicago and resulted in substantial

production economies, lower customer prices, and increased company profits.

In light of the success of the Lake County experiment, the 1910s and 1920s saw

increased consolidation and rapid growth in electricity usage. During this period, efficiency

gains and demand growth provided the financing for system expansions. Even though the

capacity costs (fixed costs per peak kW demanded) were typically twice as large with the

consolidated/interconnected supply systems, the fixed costs per unit of energy production

(kWh) were comparable to those of the old single-city system. This was the case because of

load factor improvements, which resulted from aggregating customer demand. 

Whereas the average fixed cost per customer was relatively unchanged as a

result of the move from single-city to consolidated supply systems, large savings were

realized from decreases in operating costs. In particular, fuel costs per kWh decreased

70 percent because of the improved combustion efficiency of larger plants and lower fuel

prices for purchases of large quantities. In addition, operation and maintenance costs

decreased 85 percent, primarily as a result of decreased labor intensity. 

During the 1920s, only a small part of the efficiency gains were passed on to

customers in the form of lower prices. Producers retained the bulk of the productivity
5-2

increases as profits. These profits provided the internal capital to finance system expansions

and to buy out smaller suppliers. Industry expansion and consolidation led to the

development of large utility holding companies whose assets were shares of common stock

in many different operating utilities. 

The speculative fever of the 1920s led to holding companies purchasing one

another, creating financial pyramids based on inflated estimates of company assets. With the

stock market crash in 1929, shareholders who had realized both real economic profits and

speculative gains lost large amounts of money. The financial collapse of the utility holding

companies led to new levels of utility regulation.

From the 1930s through the 1960s, the regulated mandate of electric utilities

was basically unchanged: to provide safe, adequate, and reliable service to all electricity

users. The majority of the state and federal laws regulating utilities in place during this era

had been written shortly after the Depression. The laws were primarily designed to prevent

“ruinous competition” through costly duplication of utility functions and to protect customers

against exploitation from a monopoly supplier.

During this period, most utilities were vertically integrated, controlling

everything from generation to distribution. Economies of scale in generation and the

inefficiency of duplicating transmission and distribution systems made the electric utility

industry a textbook example of a natural monopoly. Electricity was viewed as a

homogeneous good from which there were no product unbundling opportunities or unique

product offerings on which competition could get a foothold. In addition, the industry was

extremely capital-intensive, providing a sizable barrier to entry even if the monopoly status

of the utilities had not been protected. 

From the 1930s to the 1960s, the electric industry experienced almost

continuous growth in demand. In addition, there was a steady stream of technological

innovations in generation, transmission, and distribution operations. The increased

economies of scale, technological advances, and fast demand growth led to steadily declining

unit costs. However, in an environment of decreasing unit costs, there were few rate cases

and almost no pressure from customers to change the system. This period is often referred to

as the golden era for the electric utility industry.

5.1.1.2 Structure of the Traditional Regulated Utility

The utilities vary substantially in size, type, and function. Figure 5-1 illustrates

the typical structure of the electric utility market. Even with the technological and regulatory

changes in the 1970s and 1980s, at the beginning of the 1990s the structure of the electric
5-3

utility industry could still be characterized in terms of generation, transmission, and

distribution. Commercial and retail customers were in essence “captive,” and rates and

service quality were primarily determined by public utility commissions. 

The majority of utilities are interconnected and belong to a regional power pool. 

Pooling arrangements enable facilities to coordinate the economic dispatch of generation

facilities and manage transmission congestion. In addition, pooling diverse loads can

increase load factors and decrease costs by sharing reserve capacity.

Generation. Coal-fired plants have historically accounted for the bulk of

electricity generation in the United States. With abundant national coal reserves and

advances in pollution abatement technology, such as advanced scrubbers for pulverized coal

and flue gas-desulfurization systems, coal will likely remain the fuel of choice for most

existing generating facilities over the near term.

Natural gas accounts for approximately 10 percent of current generation

capacity but is expected to grow; advances in natural gas exploration and extraction

technologies and new coal gasification have contributed to the use of natural gas for power

generation.
5-4

Nuclear plants and renewable energy sources (e.g., hydroelectric, solar, wind)

provide approximately 20 percent and 10 percent of current generating capacity,

respectively. However, there are no plans for new nuclear facilities to be constructed, and

there is little additional growth forecasted in renewable energy.

Figure 5-1. Traditional Electric Power Industry Structure
4The electric power supply chain includes all generation, transmission, distribution, administrative, and market

activities needed to deliver electric power to consumers.

5-5

Transmission. Transmission refers to high voltage lines used to link generators

to substations where power is stepped down for local distribution. Transmission systems

have been traditionally characterized as a collection of independently operated networks or

grids interconnected by bulk transmission interfaces. 

Within a well-defined service territory, the regulated utility has historically had

responsibility for all aspects of developing, maintaining, and operating transmissions. These

responsibilities included

C system planning and expanding, 

C maintaining power quality and stability, and

C responding to failures. 

Isolated systems were connected primarily to increase (and lower the cost of) power

reliability. Most utilities maintained sufficient generating capacity to meet customer needs,

and bulk transactions were initially used only to support extreme demands or equipment

outages.

Distribution. Low-voltage distribution systems that deliver electricity to

customers comprise integrated networks of smaller wires and substations that take the higher

voltage and step it down to lower levels to match customers’ needs.

The distribution system is the classic example of a natural monopoly because it

is not practical to have more than one set of lines running through neighborhoods or from the

curb to the house.

5.1.1.3 Current Electric Power Supply Chain

This section provides background on existing activities and emerging

participants in the electric power supply chain.4

 Because the restructuring plans and time

tables are made at the state level, the issues of asset ownership and control throughout the

current supply chain in the electric power industry vary from state to state. However, the

activities conducted throughout the supply chain are generally the same.

Table 5-1 shows costs by utility ownership and by segment of the supply chain. 

Generation accounts for approximately 75 percent of the cost of delivered electric power.
5-6

Figure 5-2 provides an overview of the electric power supply chain,

highlighting a combination of activities and service providers. The activities/members of the

electric power supply chain are typically grouped into generation, transmission, and

distribution. These three segments are described in the following sections. 

Generation. As part of deregulation, the transmission and distribution of

electricity are being separated from the business of generating electricity, and a new

competitive market in electricity generation is evolving. As power generators prepare for the

competitive market, the share of electricity generation attributed to nonutilities and utilities is

shifting. 

More than 7,000 electricity suppliers currently operate in the U.S. market. As

shown in Table 5-2, approximately 42 percent of suppliers are utilities and 58 percent are

nonutilities. Utilities include investor-owned, cooperatives, and municipal systems. Of the

approximately 3,100 utilities operating in the United States, only about 700 generate electric

power. The majority of utilities distribute electricity that they have purchased from power

generators via their own distribution systems.

Table 5-1. Total Expenditures in 1996 ($103

)

Utility

Ownership Generation Transmission Distribution

Customer

Accounts

and Sales

Administration

and General

Expenses

Investorowned

80,891,644 2,216,113 6,124,443 6,204,229 13,820,059

Publicly

owned

12,495,324 840,931 1,017,646 486,195 1,360,111

Federal 3,685,719 327,443 1,435 55,536 443,809

Cooperatives 15,105,404 338,625 1,133,984 564,887 1,257,015

112,178,091 3,723,112 8,277,508 7,310,847 16,880,994

75.6% 2.5% 5.6% 4.9% 11.4%

148,370,552

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1998a. Financial Statistics of

Major Publicly Owned Electric Utilities, 1997. Washington, DC: U.S. Department of Energy.

U.S. Department of Energy, Energy Information Administration (EIA). 1997. Financial Statistics of

Major U.S. Investor-Owned Electric Utilities, 1996. Washington, DC: U.S. Department of Energy.
5-7

Utility and nonutility generators produced a total of 3,369 billion kWh in 1995. 

Although utilities generate the vast majority of electricity produced in the United States,

nonutility generators are quickly eroding utilities’ shares of the market. Nonutility

generators include private entities that generate power for their own use or to sell to utilities

or other end users. Between 1985 and 1995, nonutility generation increased from 98 billion

kWh (3.8 percent of total generation) to 374 billion kWh (11.1 percent). Figure 5-3

illustrates this shift in the share of utility and nonutility generation. 

Figure 5-2. Electric Utility Industry
5-8

Utilities. There are four categories of utilities: investor-owned utilities (IOUs),

publicly owned utilities, cooperative utilities, and federal utilities. Of the four, only IOUs

always generate electricity.

IOUs are increasingly selling off generation assets to nonutilities or converting

those assets into nonutilities (Haltmaier, 1998). To prepare for the competitive market, IOUs

have been lowering their operating costs, merging, and diversifying into nonutility

businesses. 

In 1995, utilities generated 89 percent of electricity, a decrease from 96 percent

in 1985. IOUs generate the majority of the electricity produced in the United States. IOUs

are either individual corporations or a holding company, in which a parent company operates

one or more utilities integrated with one another. IOUs account for approximately threequarters of utility generation, a percentage that held constant between 1985 and 1995. 

Utilities owned by the federal government accounted for about one-tenth of

generation in both 1985 and 1995. The federal government operated a small number of large

utilities in 1995 that supplied power to large industrial consumers or federal installations. 

The Tennessee Valley Authority is an example of a federal utility.

Table 5-2. Number of Electricity Suppliers in 1999

Electricity Suppliers Number Percent

Utilities 3,124 42%

Investor-owned utilities 222

Cooperatives 875

Municipal systems 1,885

Public power districts 73

State projects 55

Federal agencies 14

Nonutilities 4,247 58%

Nonutilities (excluding EWGs) 4,103

Exempt wholesale generators 144

Total 7,371 100%

Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999g. The Changing

Structure of the Electric Power Industry 1999: Mergers and Other Corporate Combinations. 

Washington, DC: U.S. Department of Energy.
5-9

a

Includes facilities classified in more th an one of the following FERC designated categories: cogenerator QF, small

power producer QF, or exempt wh olesale generator.

Cogen = Cogenerator.

EWG = Exempt wh olesale generator.

Other Non-QF = Nocogenerator N on-QF.

QF = Qualifying facility.

SPP = Small power producer.

Note: Sum of components may not equal total due to independent rounding. Classes for nonutility generation are

determined by the class of each generating unit. 

Sources: Utility data: U.S. Department of Energy, Energy Information Administration (EIA). 1996b. Electric Power

Annual 1995. Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC: U.S. Department of Energy; Table 8

(and previous issues); Nonutility data: Shares of generation estimated by EIA; total generation from Edison

Electric Institute (EEI). 1998. Statistical Yearbook of the Electric Utility Industry 1998. November. 

Washington, DC;

Figure 5-3. Utility and Nonutility Generation and Shares by Class, 1988 and 1998

Many states, municipalities, and other government organizations also own and

operate utilities, although the majority do not generate electricity. Those that do generate

electricity operate capacity to supply some or all of their customers’ needs. They tend to be

small, localized outfits and can be found in 47 states. These publicly owned utilities

accounted for about one-tenth of utility generation in 1985 and 1995. In a deregulated

market, these generators may be in direct competition with other utilities to service their

market. 
5-10

Rural electric cooperatives are the fourth category of utilities. They are formed

and owned by groups of residents in rural areas to supply power to those areas. Cooperatives

generally purchase from other utilities the energy that they sell to customers, but some

generate their own power. Cooperatives only produced 5 percent of utility generation in

1985 and only 6 percent in 1995.

Nonutilities. Nonutilities are private entities that generate power for their own

use or to sell to utilities or other establishments. Nonutilities are usually operated at mines

and manufacturing facilities, such as chemical plants and paper mills, or are operated by

electric and gas service companies (DOE, EIA, 1998b). More than 4,200 nonutilities operate

in the United States.

Between 1988 and 1998, nonutility generators increased their share of

electricity generation from 7 percent to 11 percent (see Figure 5-3). In 1978, the Public

Utilities Regulatory Policies Act (PURPA) stipulated that electric utilities must interconnect

with and purchase capacity and energy offered by any qualifying nonutility. In 1996, FERC

issued Orders 888 and 889 that opened transmission access to nonutilities and required

utilities to share information about available transmission capacity. These moves established

wholesale competition, spurring nonutilities to increase generation and firms to invest in

nonutility generation. 

Nonutilities are frequently categorized by their FERC classification and the type

of technology they employ. There are three categories of nonutilities: cogenerators, small

power producers (SPPs), and exempt wholesale generators (EWGs). 

Cogenerators are nonutilities that sequentially or simultaneously produce

electricity and another form of energy (such as heat or steam) using the same fuel source. At

cogeneration facilities, steam is used to drive a turbine to generate electricity. The waste

heat and steam from driving the turbine is then used as an input in an industrial or

commercial process. For a cogenerator to qualify or interconnect with utilities, it must meet

certain ownership, operating, and efficiency criteria specified by FERC. In 1985, about

55 percent of nonutility generation was produced by cogenerators that qualified or met

FERC’s specifications and sold power to utilities. By 1995 the percentage increased to

67 percent as the push for deregulation gathered momentum. At the same time, the

percentage that was produced by nonqualifying cogenerators decreased from 25 percent to

9 percent. 

SPPs typically generate power using renewable resources, such as biomass,

solar energy, wind, or water. However, increasingly SPPs include companies that selfgenerate power using combustion turbines and sell excess power back to the grid. As with
5-11

cogenerators, SPPs must fulfill a series of FERC requirements to interconnect with utilities. 

PURPA revisions enabled nonutility renewable electricity to grow significantly, and SPPs

have responded by improving technologies, decreasing costs, and increasing efficiency and

reliability (DOE, EIA, 1998b). Between 1985 and 1995, the percentage of SPP nonutility

generation nearly doubled to 13 percent.

EWGs produce electricity for the wholesale market. Also known as IPPs,

EWGs typically contract directly with large bulk customers, such as large industrial and

commercial facilities and utilities. They do not operate any transmission or distribution

facilities but pay tariffs to use facilities owned and operated by utilities. Unlike with

qualifying cogenerators and SPPs, utilities are not required to purchase energy produced by

EWGs, but they may do so at market-based prices. EWGs did not exist until the Energy

Policy Act created them in 1992, and by 1995 they generated about 2 percent of nonutility

electricity.

In 1995, about 4 percent of nonutility generation was produced by facilities that

were classified as any combination of cogenerator, SPP, and EWG. An additional 6 percent

was produced by facilities that generate electricity for their own consumption.

Transmission. Whereas the market for electricity generation is moving toward

a competitive structure, the transmission of electricity is currently (and will likely remain) a

regulated, monopoly operation. In areas where power markets are developing, generators

pay tariffs to distribute their electricity over established lines owned and maintained by

independent organizations. Independent service operators (ISOs) will most likely coordinate

transmission operations and generation dispatch over the bulk power system. 

The bulk power transmission system consists of three large regional networks,

which also encompass smaller groups. The three networks are geographically defined: the

Eastern Interconnect in the eastern two-thirds of the nation; the Western Interconnect in the

western portion; and the Texas Interconnect, which encompasses the majority of Texas. The

western and eastern networks are each fully integrated with Canada. The western is also

integrated with Mexico. Within each network, the electricity producers are connected by

extra high-voltage connections that allow them to transfer electrical energy from one part of

the network to the other.

The bulk power system makes it possible for electric power producers to engage

in wholesale trade. In 1995, utilities sold 1,283 billion kWh to other utilities. The amount of

energy sold by nonutilities has increased dramatically from 40 billion kWh in 1986 to 222

billion kWh in 1995, an average annual increase of 21 percent (DOE, EIA, 1996a). 

Distribution utilities and large industrial and commercial customers also have the option of
5-12

purchasing electricity in bulk at market prices from their local utility, a nonutility, or another

utility. The process of transmitting electricity between suppliers via a third party is known as

wholesale wheeling.

The wholesale trade for electricity is increasingly handled by power marketers

(brokers). Power marketers act as independent middlemen that buy and sell wholesale

electricity at market prices (EEI, 1999). Customers include large commercial and industrial

facilities in addition to utilities. Power marketers emerged in response to increased

competition. Brokers do not own generation facilities, transmissions systems, or distribution

assets, but they may be affiliated with a holding company that operates generation facilities. 

Currently, 570 power marketers operate in the United States. The amount of power sold by

marketers increased from 3 million MWh to 2.3 billion MWh between 1995 and 1998. This

is the equivalent of going from powering 1 million homes to powering 240 million homes

(EEI, 1999). Table 5-3 lists the top ten power marketers by sales for the first quarter of

1999.

Distribution. The local distribution system for electricity is expected to remain

a regulated monopoly operation. But power producers will soon be able to compete for retail

customers by paying tariffs to entities that distribute the power. Utilities may designate an

Table 5-3. Top Power Marketing Companies, First Quarter 1999

Company Total MWh Sold

Enron Power Marketing, Inc. 78,002,931

Southern Company Energy Marketing, L.P. 38,367,107

Aquila Power Corp. 29,083,612

PG&E Energy Trading-Power, L.P. 28,463,487

Duke Energy Trading & Marketing, L.L.C. 22,276,608

LG&E Energy Marketing, Inc. 15,468,749

Entergy Power Marketing Corp. 12,670,520

PacifiCorp Power Marketing, Inc. 11,800,263

Tractebel Energy Marketing, Inc. 10,041,039

NorAm Energy Services, Inc. 9,817,306

Source: Resource Data International. 1999. “PMA Online Top 25 Power Marketer Rankings.” Power

Marketers Online Magazine. <http://www.powermarketers.com/top25a.htm.> As obtained on

August 11, 1999.
5-13

ISO to operate the distribution system or continue to operate it themselves. If the utility

operates its own system, it is required by law to charge the same tariff to other power

producers that it charges producers within its own corporate umbrella. The sale of electricity

by a utility or other supplier to a customer in another utility’s retail service territory is known

as retail wheeling.

Supporters of retail wheeling claim that it will help lower the average price paid

for electricity. The states with the highest average prices for electricity are expected to be

the first to permit retail wheeling; wholesale wheeling is already permitted nationwide. In

1996, California, New England, and the Mid-Atlantic States had the highest average prices

for electricity, paying 3 cents or more per kilowatt-hour than the national average of

6.9 cents (DOE, EIA, 1998b). Open access to the electricity supply, coupled with a

proliferation of electricity suppliers, should combine to create falling electricity prices and

increasing usage. By 2002, the nationwide average price for electricity is projected to be

11 percent lower than in 1995, an average annual decline of roughly 2 percent (Haltmaier,

1998). 

The explosion in computer and other information technology usage in the

commercial sector is expected to offset energy efficiency gains in the residential and

industrial sectors and lead to a net increase in the demand for electricity. Retail wheeling has

the potential to allow customers to lower their costs per kilowatt-hour by purchasing

electricity from suppliers that best fit their usage profiles. Large commercial and industrial

customers engaged in self-generation or cogeneration will also be able to sell surplus

electricity in the wholesale market.

5.1.1.4 Overview of Deregulation and the Potential Future Structure of the Electricity

Market

Beginning in the latter part of the 19th century and continuing for about 100

years, the prevailing view of policymakers and the public was that the government should

use its power to require or prescribe the economic behavior of “natural monopolies” such as

electric utilities. The traditional argument is that it does not make economic sense for there

to be more than one supplier—running two sets of wires from generating facilities to end

users is more costly than one set. However, since monopoly supply is not generally regarded

as likely to provide a socially optimal allocation of resources, regulation of rates and other

economic variables was seen as a necessary feature of the system. 

Beginning in the 1970s, the public policy view shifted against traditional

regulatory approaches and in favor of deregulation for many important industries including
5-14

transportation, communications, finance, and energy. The major drivers for deregulation of

electric power included the following:

C existence of rate differentials across regions offering the promise of benefits from

more efficient use of existing generation resources if the power can be transmitted

across larger geographic areas than was typical in the era of industry regulation;

C the erosion of economies of scale in generation with advances in combustion

turbine technology;

C complexity of providing a regulated industry with the incentives to make socially

efficient investment choices;

C difficulty of providing a responsive regulatory process that can quickly adjust

rates and conditions of service in response to changing technological and market

conditions; and

C complexity of monitoring utilities’ cost of service and establishing cost-based

rates for various customer classes that promote economic efficiency while at the

same time addressing equity concerns of regulatory commissions.

Viewed from one perspective, not much changes in the electric industry with

restructuring. The same functions are being performed, essentially the same resources are

being used, and in a broad sense the same reliability criteria are being met. In other ways,

the very nature of restructuring, the harnessing of competitive forces to perform a previously

regulated function, changes almost everything. Each provider and each function become

separate competitive entities that must be judged on their own.

This move to market-based provision of generation services is not matched on

the transmission and distribution side. Network interactions on AC transmission systems

have made it impossible to have separate transmission paths compete. Hence, transmission

and distribution remain regulated. Transmission and generation heavily interact, however,

and transmission congestion can prevent specific generation from getting to market. 

Transmission expansion planning becomes an open process with many interested parties. 

This open process, coupled with frequent public opposition to transmission expansion, slows

transmission enhancement. The net result is greatly increased pressure on the transmission

system.

Restructuring of the electric power industry could result in any one of several

possible market structures. In fact, different parts of the country will probably use different

structures, as the current trend indicates. The eventual structure may be dominated by a

power exchange, bilateral contracts, or a combination. A strong Regional Transmission
5Nonutility power producers have approximately 10 percent of the capacity of utility power producers. 

5-15

Organization (RTO) may operate in the area, or a vertically integrated utility may continue to

operate a control area. In any case, several important characteristics will change: 

C Commercial provision of generation-based services (e.g., energy, regulation, load

following, voltage control, contingency reserves, backup supply) will replace

regulated service provision. This drastically changes how the service provider is

assessed. 

C Individual transactions will replace aggregated supply meeting aggregated

demand. It will be necessary to continuously assess each individual’s

performance. 

C Transaction sizes will shrink. Instead of dealing only in hundreds and thousands

of MW, it will be necessary to accommodate transactions of a few MW and less. 

C Supply flexibility will greatly increase. Instead of services coming from a fixed

fleet of generators, service provision will change dynamically among many

potential suppliers as market conditions change. 

5.1.2 Electricity Generation

Because of the uncertainties associated with the future course of deregulation,

forecasting deregulation’s impact on generation trends, and hence growth in combustion

turbines, is difficult. However, most industry experts believe that deregulation will lead to

increased competition in the wholesale (and eventually retail) power markets, driving out

high cost producers of electricity, and that there will be an increased reliance on distributed

generation to compensate for growing demands on the transmission system.

In 2000, the United States relied on fossil fuels to produce almost 74 percent of

its electricity. Table 5-4 shows a breakdown of generation by energy source.5 Whereas

natural gas seems to play a relatively minor role among utility producers, it represents 30

percent of capacity among nonutility producers. This is because nonutilities use coal and

petroleum to the same extent as the larger, traditionally regulated utility power producers.

Among nonutility producers, manufacturing facilities contain the largest

electricity-generating capacity. Table 5-5 illustrates that, from 1995 through 1997,

manufacturing 
5-16

Table 5-4. Industry Capacity by Energy Source, 2000

Energy Source

Utility Generators

(MW)

Nonutility

Generators (MW) Total (MW)

Fossil fuels 424,218 173,320 597,538

Coal 259,059 56,190 315,249

Natural gas 38,964 58,668 97,632

Petroleum 26,250 13,003 39,253

Duel-fired 99,945 45,549 145,494

Nuclear 85,519 12,038 97,557

Hydroelectric 91,590 7,478 99,068

Renewable/other 1,050 16,322 17,372

Total 602,377 209,248 811,625

Sources: U.S. Department of Energy, Energy Information Administration. 2000a. Electric Power Annual,

1999, Volume II. DOE/EIA-0348(99)/2. Washington, DC: U.S. Department of Energy. 

Table 5-5. Installed Capacity at U.S. Nonutility Attributed to Major Industry Groups

and Census Division, 1995 through 1999 (MW)

Year Manufacturing

Transportation

and Public

Utilities Services Mining

Public

Administration

Other

Industry

Groups Total

1995 47,606 15,124a

2,165 3,428 544 1,388a

70,254

1996 49,529 16,050 2,181 3,313 542 1,575 73,189

1997 49,791 16,559 2,223 3,306 616 1,510 74,004

1998 51,255 24,527 2,506 3,275 534 15,989 98,085

1999 52,430 78,419 2,342 5,123 536 28,506 167,357

a Revised data.

Notes: All data are for 1 MW and greater. Data for 1997 are preliminary; data for prior years are final. Totals

may not equal sum of components because of independent rounding.

Source: U.S. Department of Energy, Energy Information Administration (EIA). 2000a. Electric Power Annual

1999, Volume II. DOE/EIA-0348(99)/2. Washington, DC: U.S. Department of Energy.
5-17

facilities consistently had the capacity to produce over two-thirds of nonutility electricity

generation. However, manufacturing share fell to less than one half of nonutility capacity in

1998/1999.

In 1997 cogenerators produced energy totaling 146 billion kWh for their own

use. Cogenerators are expected to continue to increase their generation capabilities at a

slightly slower rate than utilities.

Table 5-6 further disaggregates capacity by prime mover and energy source at

electric utilities. As the table shows, hydroelectric and steam are the two prime movers with

the most units, while steam and nuclear generators have the greatest total capacity. 

Combustion turbines’ (including the second stage of CCCTs) generation represents

approximately 10 percent of total U.S. capacity.

Figure 5-4 shows the annual electricity sales by sector from 1970 with

projections through 2020.

The literature suggests that electricity consumption is relatively price inelastic. 

Consumers are generally unable or unwilling to forego a large amount of consumption as the

price increases. Numerous studies have investigated the short-run elasticity of demand for

electricity. Overall, the studies suggest that, for a 1 percent increase in the price of

electricity, demand will decrease by 0.15 percent. However, as Table 5-7 shows, elasticities

vary greatly, depending on the demand characteristics of end users and the price structure. 

Demand elasticities are estimated to range from a –0.05 percent elasticity of demand for a

“flat rates” case (i.e., no time-of-use assumption) up to a –0.50 percent demand elasticity for

a “high consumer response” case (DOE, EIA, 1999b).

5.1.2.1 Growth in Generation Capacity

The electric industry is continuing to grow and change. Throughout the

country, electric utility capacity additions are slightly outpacing capacity retirements. The

trend goes beyond an increasing capacity but also shows that coal units are slowly being

replaced by newer, more efficient methods of producing energy. In 1997, 71 electric utility

units were closed, decreasing capacity by 2,127 MW. Of those, six were coal facilities and

43 were petroleum facilities. However, of the 62 facility additions (2,918 MW), none were

coal powered, while 24 use petroleum. Gas installations slightly outpaced petroleum ones,

totaling 25 new units at electric utilities in 1997. Table 5-8 outlines capacity additions and

retirements at U.S. electric utilities by energy source.
5-18

Table 5-6. Existing Capacity at U.S. Electric Utilities by Prime Mover and Energy

Source, as of January 1, 1998

Prime Mover Energy Source Number of Units Generator Nameplate Capacity (MW)

U.S. Total 10,421 754,925

Steam 2,117 469,210

Coal only 911 276,895

Other solidsa15 334

Petroleum only 137 22,476

Gas only 117 10,840

Other solids/coala1 2

Solids/petroleumb72 10,796

Solids/gasb

232 36,763

Solids/petroleum/gasb1 558

Petroleum/gas 624 110,324

Internal Combustion 2,892 5,075

Petroleum only 1,799 2,671

Gas only 48 66

Petroleum/gas 1,044 2,335

Other solids onlya1 3

Combustion Turbine 1,549 63,131

Petroleum only 625 22,802

Gas only 179 5,776

Petroleum/gas 745 34,554

Second Stage of CCCTs 202 16,224

Petroleum only 11 470

Gas only 29 2,331

Coal/petroleum 1 326

Coal/gas 1 113

Petroleum/gas 100 8,852

Waste heat 60 4,130

Nuclear 107 107,632

Hydroelectric (conventional) 3,352 73,202

Hydroelectric (pumped storage) 141 18,669

Geothermal 27 1,746

Solar 11 5

Wind 19 14

a

Includes wood, wood waste, and nonwood waste.

b

Includes coal, wood, wood waste, and nonwood waste.

Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power Annual

1998. Volumes I and II. Washington, DC: U.S. Department of Energy.
5-19

Planned additions indicate a strong trend towards gas-powered

turbine/stationary combustion units. Three-quarters of the gas turbine/stationary combustion

units are expected to be gas-powered with the remaining quarter petroleum-powered. Based

on 1998 planned additions, it is likely that all additional petroleum-fueled units in the near

future will be gas turbine/stationary combustion units, not steam. Table 5-9 shows planned

capacity additions by prime mover and energy source.

5.1.3 Electricity Consumption

This section analyzes the growth projections for electricity consumption as well

as the price elasticity of demand for electricity. Growth in electricity consumption has

traditionally paralleled GDP growth. However, improved energy efficiency of electrical

equipment, such as high-efficiency motors, has slowed demand growth over the past few

decades. The magnitude of the relationship has been decreasing over time, from growth of 7

percent per year in the 1960s down to 1 percent in the 1980s. As a result, determining what 

Figure 5-4. Annual Electricity Sales by Sector
5-20

Table 5-7. Key Parameters in the Cases

Case Name

Key Assumptions

Cost Reduction

and Efficiency

Improvements

Short-Run

Elasticity

 of Demand

 (Percent)

Natural Gas

Prices

Capacity

Additions

AEO97 Reference Case AEO97 Reference

Case

— AEO97 Reference

Case

As needed

to meet demand

No Competition No change from

1995

— AEO97 Reference

Case

As needed

to meet demand

Flat Rates 

(no time-of-use rates)

AEO97 Reference

Case

–0.05 AEO97 Reference

Case

As needed

to meet demand

Moderate Consumer

Response

AEO97 Reference

Case

–0.15 AEO97 Reference

Case

As needed

to meet demand

High Consumer Response AEO97 Reference

Case

–0.50 AEO97 Reference

Case

As needed

to meet demand

High Efficiency Increased cost

savings and

efficiencies

–0.15 AEO97 Reference

Case

As needed

to meet demand

No Capacity Additions AEO97 Reference

Case

–0.15 AEO97 Low Oil

and Gas Supply

Technology Case

Not allowed

High Gas Price AEO97 Reference

Case

–0.15 AEO97 High Oil

and Gas Supply

Technology Case

As needed

to meet demand

Low Gas Price AEO97 Reference

Case

–0.15 AEO97 Reference

Case

As needed

to meet demand

High Value of Reliability AEO97 Reference

Case

–0.15 AEO97 Reference

Case

As needed

to meet demand

Half O&M AEO97 Reference

Case

–0.15 AEO97 Reference

Case

As needed

to meet demand

Intense Competition AEO97 Reference

Case

–0.15 AEO97 Reference

Case

As needed to meet

demand

— = not applicable.

Source: U.S. Department of Energy, Energy Information Administration, Office of Integrated Analysis and

Forecasting. “Competitive Electricity Price Projections.”

<http://www.eia.doe.gov/oiaf/elepri97/chap3.html>. As obtained on November 15, 1999b.
5-21

the future growth will be is difficult, although it is expected to be positive (DOE, EIA,

1999a). Table 5-10 shows consumption by sector of the economy over the past 10 years. 

The table shows that since 1989 electricity sales have increased at least 10 percent in all four

sectors. The commercial sector has experienced the largest increase, followed by residential

consumption.

In the future, residential demand is expected to be at the forefront of increased

electricity consumption. Between 1997 and 2020, residential demand is expected to increase

at 1.6 percent annually. Commercial growth in demand is expected to be approximately 1.4

percent, while industry is expected to increase demand by 1.1 percent (DOE, EIA, 1999a). 

Table 5-8. Capacity Additions and Retirements at U.S. Electric Utilities by Energy

Source, 1997

Primary Energy

Source

Additions Retirements

Number

of Units

Generator

Nameplate

Capacity (MW)

Number

of Units

Generator

Nameplate

Capacity (MW)

U.S. total 62 2,918 71 2127

Coal — — 6 281

Petroleum 24 199 43 445

Gas 25 2,475 18 405

Water

(pumped storage

hydroelectric)

— — — —

Nuclear — — 2 995

Waste heat 3 171 — —

Renewablea10 73 2 1

a

Includes conventional hydroelectric; geothermal; biomass (wood, wood waste, nonwood waste); solar; and

wind.

Note: Total may not equal the sum of components because of independent rounding.

Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power Annual

1998. Volumes I and II. Washington, DC: U.S. Department of Energy.
5-22

Table 5-9. Fossil-Fueled Existing Capacity and Planned Capacity Additions at U.S.

Electric Utilities by Prime Mover and Primary Energy Source, as of January 1, 1998

Planned Additionsa

Prime Mover Energy

Source Number of Units

Generator Nameplate

Capacity (MW)

U.S. Total 272 50,184

Steam 45 18,518

Coal 8 2,559

Petroleum — —

Gas 37 15,959

Gas Turbine/Internal

Combustion

226 31,663

Petroleum 52 1,444

Gas 174 30,219

a

Planned additions are for 1998 through 2007. Totals include one 2.9 MW fuel cell unit.

Notes: Total may not equal the sum of components because of independent rounding. The Form EIA-860

was revised during 1995 to collect data as of January 1 of the reporting year, where “reporting year” is

the calendar year in which the report is required to be filed with the Energy Information

Administration. These data reflect the status of electric plants/generators as of January 1; however,

dynamic data are based on occurrences in the previous calendar year (e.g., capabilities and energy

sources based on test and consumption in the previous year).

Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power

Annual 1998. Volumes I and II. Washington, DC: U.S. Department of Energy.
5-23

Table 5-10. U.S. Electric Utility Retail Sales of Electricity by Sector, 1989 Through

July 1999 (Million kWh)

Period Residential Commercial Industrial Othera All Sectors

1989 905,525 725,861 925,659 89,765 2,646,809

1990 924,019 751,027 945,522 91,988 2,712,555

1991 955,417 765,664 946,583 94,339 2,762,003

1992 935,939 761,271 972,714 93,442 2,763,365

1993 994,781 794,573 977,164 94,944 2,861,462

1994 1,008,482 820,269 1,007,981 97,830 2,934,563

1995 1,042,501 862,685 1,012,693 95,407 3,013,287

1996 1,082,491 887,425 1,030,356 97,539 3,097,810

1997 1,075,767 928,440 1,032,653 102,901 3,139,761

1998 1,124,004 948,904 1,047,346 99,868 3,220,121

Percentage

change

1989-1998

19% 24% 12% 10% 18%

a

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

and interdepartmental sales.

Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power

Annual 1998. Volumes I and II. Washington, DC: U.S. Department of Energy.

U.S. Department of Energy, Energy Information Administration (EIA). 1996b. Electric Power

Annual 1995. Volumes I and II. Washington, DC: U.S. Department of Energy.
6-1

SECTION 6

ECONOMIC ANALYSIS METHODS

This section presents the methodology for analyzing the economic impacts of

the NSPS. Implementation of this methodology will provide the economic data and

supporting information needed by EPA to support its regulatory determination. This analysis

is based on microeconomic theory and the methods developed for earlier EPA studies to

operationalize this theory. These methods are tailored to and extended for this analysis, as

appropriate, to meet EPA’s requirements for an economic impact analysis (EIA) of controls

placed on stationary combustion turbines. 

This methodology section includes a description of the Agency requirements for

conducting an EIA, background information on typical economic modeling approaches, the

conceptual approach selected for this EIA, and an overview of the computerized market

model used in the analysis. The focus of this section is on the approach for modeling the

electricity market and its interactions with other energy markets and final product markets. 

Appendix A contains additional detail on estimating changes is producer and consumer

surplus in the nonelectric utility markets included in the economic model. 

6.1 Agency Requirements for Conducting an EIA

The CAA provides the statutory authority under which all air quality regulations

and standards are implemented by OAQPS. The 1990 CAA Amendments require that EPA

establish emission standards for sources releasing any of the listed HAPs.

Congress and the Executive Office have imposed requirements for conducting

economic analyses to accompany regulatory actions. The Agency has published its

guidelines for developing an EIA (EPA, 1999a). Section 312 of the CAA specifically

requires a comprehensive analysis that considers benefits, costs, and other effects associated

with compliance. On the benefits side, it requires consideration of all the economic, public

health, and environmental benefits of compliance. On the cost side, it requires consideration

of the effects on employment, productivity, cost of living, economic growth, and the overall

economy. These effects are evaluated by measures of facility- and company-level

production impacts and societal-level producer and consumer welfare impacts. The RFA and

SBREFA require regulatory agencies to consider the economic impacts of regulatory actions

on small entities. Executive Order 12866 requires regulatory agencies to conduct an analysis

of the economic benefits and costs of all proposed regulatory actions with projected costs
6-2

greater than $100 million. Also, Executive Order 13211 requires EPA to consider for

particular rules the impacts on energy markets. The Agency’s draft Economic Analysis

Guidelines provide detailed instructions and expectations for economic analyses that support

rulemaking (EPA, 1999a). The EIA provides the data and information needed to comply

with the federal regulation, the executive order, and the guidance manual.

6.2 Overview of Economic Modeling Approaches

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:

C the scope of economic decisionmaking accounted for in the model and

C the scope of interaction between different segments of the economy.

Each of these dimensions was considered in recommending our approach. The advantages

and disadvantages of each are discussed below.

6.2.1 Modeling Dimension 1: Scope of Economic Decisionmaking

Models incorporating different levels of economic decisionmaking can

generally be categorized as with behavior responses and without behavior responses

(accounting approach). Table 6-1 provides a brief comparison of the two approaches. The

behavioral approach is grounded in economic theory related to producer and consumer

behavior in response to changes in market conditions. In essence, this approach models the

expected reallocation of society’s resources in response to a regulation. The behavioral

approach explicitly models the changes in market prices and production. Resulting changes

in price and quantity are key inputs into the determination of a number of important

phenomena in an EIA, such as changes in producer surplus, changes in consumer surplus,

and net social welfare effects. For example, a large price increase may imply that consumers

bear a large share of the regulatory burden, thereby mitigating the impact on producers’

profits and plant closures.

In contrast, the nonbehavioral/accounting approach essentially holds fixed all

interaction between facility production and market forces. In this approach, a simplifying

assumption is made that the firm absorbs all control costs, and discounted cash flow analysis

is used to evaluate the burden of the control costs. Typically, engineering control costs are

weighted by the number of affected units to develop “engineering” estimates of the total

annualized costs. These costs are then compared to company or industry sales to evaluate
6-3

the regulation’s impact.

6.2.2 Modeling Dimension 2: Interaction Between Economic Sectors

Because of the large number of markets potentially affected by the combustion

turbines regulation, an issue arises concerning the level of sectoral interaction to model. In

the broadest sense, all markets are directly or indirectly linked in the economy; thus, all

commodities and markets are to some extent affected by the regulation. For example, the

control costs on turbines may directly affect the market for aluminum if aluminum plants are

operating turbines for self-generation of electricity or generation of process steam. However,

control costs will also indirectly affect the market for aluminum because the cost of

electricity will increase. As a result, the increased price of aluminum production (due to

direct and indirect costs on the aluminum industry) may be passed onto consumers of

aluminum products. 

The appropriate level of market interactions to be included in the EIA is

determined by the scope of the regulation across industries and the ability of affected firms to

pass along the regulatory costs in the form of higher prices. Alternative approaches for

modeling interactions between economic sectors can generally be divided in three groups:

Table 6-1. Comparison of Modeling Approaches

EIA With Behavioral Responses

Incorporates control costs into production function

Includes change in quantity produced

Includes change in market price

Estimates impacts for

C affected producers

C unaffected producers

C consumers

C foreign trade

EIA Without Behavioral Responses

C Assumes firm absorbs all control costs

C Typically uses discounted cash flow analysis to evaluate burden of control costs

C Includes depreciation schedules and corporate tax implications

C Does not adjust for changes in market price 

C Does not adjust for changes in plant production
6-4

C Partial equilibrium model: Individual markets are modeled in isolation. The only

factor affecting the market is the cost of the regulation on facilities in the industry

being modeled. 

C General equilibrium model: All sectors of the economy are modeled together. 

General equilibrium models operationalize neoclassical microeconomic theory by

modeling not only the direct effects of control costs, but also potential input

substitution effects, changes in production levels associated with changes in

market prices across all sectors, and the associated changes in welfare

economywide. A disadvantage of general equilibrium modeling is that

substantial time and resources are required to develop a new model or tailor an

existing model for analyzing regulatory alternatives.

C Multiple-market partial equilibrium model: A subset of related markets are

modeled together, with intersectoral linkages explicitly specified. To account for

the relationships and links between different markets without employing a full

general equilibrium model, analysts can use an integrated partial equilibrium

model. In instances where separate markets are closely related and there are

strong interconnections, there are significant advantages to estimating market

adjustments in different markets simultaneously using an integrated market

modeling approach.

6.3 Selected Modeling Approach Used for Combustion Turbine Analysis

To conduct the analysis for the combustion turbine NSPS, the Agency used a

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

partial equilibrium model as described above. The majority of the regulation’s control costs

are projected to be associated with combustion turbines in the electricity market. These

control costs will increase the price of energy, affecting almost all sectors of the economy. 

Because the elasticity of demand for energy varies across fuel types, it is important to use a

market modeling approach to estimate the share of the burden borne by producers and

consumers. 

Multiple-market partial equilibrium analysis provides a manageable approach to

incorporate interactions between energy markets and final product markets into the EIA to

accurately estimate the impact of the regulation. The multiple-market partial equilibrium

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

approach and a full general equilibrium approach. This approach involves identifying and

modeling the most significant subset of market interactions using an integrated partial

equilibrium framework. In effect, the modeling technique is to link a series of standard

partial equilibrium models by specifying the interactions between supply functions and then

solving for all prices and quantities across all markets simultaneously.
6Technical changes are indirectly captured through the own-price and cross-price elasticities of demand used to

model fuel switching. These are discussed in Section 6.4.1.

6-5

Figure 6-1 presents an overview of the key market linkages included in the

economic impact modeling approach used to analyze the combustion turbines NSPS. The

focus of the analysis is on the energy supply chain, including the extraction and distribution

of natural gas and oil, the generation of electricity, and the consumption of energy by

producers of final products and services. As shown in Figure 6-1, wholesale electricity

generators consume natural gas and petroleum products to generate electricity that is then

used in the production of final products and services. In addition, the final product and

service markets also use natural gas and petroleum products as an input into their production

process. This analysis explicitly models the linkages between these market segments.

The control costs associated with the regulation will directly affect the cost of

the generation of wholesale electricity using combustion turbines. In addition to the direct

impact of control costs on entities installing new combustion turbines, indirect impacts are

passed along the energy supply chain through changes in prices. For example, the price of

natural gas will increase because of two effects: the higher price of electricity used in the

natural gas industry and increased demand for natural gas generated by fuel switching from

electricity to natural gas. Similarly, production costs for manufacturers of final products will

change as a result of price of electricity and natural gas.

Also included in the impact model is feedback on changes in outputs in final

product markets to the demand for Btus in the fuel markets. The change in facility output is

determined by the size of the Btu cost increase (typically variable cost per output), the

facility’s production function (slope of facility-level supply curve), and the characteristics of

the facility’s downstream market (other market suppliers and market demanders). For

example, if consumers’ demand for a product is not sensitive to price, then producers can

pass the cost of the regulation through to consumers and the facility output will not change. 

However, if only a small number of facilities in a market are affected, then competition will

prevent a facility from raising its prices.

One possible feedback pathway not explicitly modeled is technical changes in

manufacturing processes. For example, if the cost of Btus increases, a facility may use

measures to increase manufacturing efficiency or capture waste heat. These facility-level

responses are a form of pollution prevention. However, directly incorporating these

responses into the model is beyond the scope of our analysis.6
6-6

Figure 6-1. Links Between Energy and Final Product Markets
7The same controls are required for SCCTs and for CCCTs. But the relative costs are higher for SCCTs because

their equipment and installation costs are approximately 40 percent less compared to CCCTs. Control costs

are discussed in Section 6.1.

8A similar figure and analysis apply for peak load power with the exception that peak load supply is generally

less responsive to price changes at the margin (i.e., base load elasticity of supply > peak load elasticity of

supply).

6-7

The major market segments included in the model and the intermarket linkages

connecting the fuel markets and final product and service markets are described below. 

Because, as mentioned in Section 3, the overwhelming majority of combustion turbine units

are used to generate wholesale electric power, the discussion focuses on the electricity

market.

6.3.1 Electricity Markets

In this analysis, the market for base load energy and peak power are modeled

separately. As the industry deregulates, it is becoming increasingly common for separate

market prices to be determined for these two commodity attributes of electricity. In addition,

the growth of CCCTs is being driven primarily by growth in base load energy demand, and

the growth in SCCTs will be driven primarily by growth in peak demand. And because the

relative impact on the control costs is greater for SCCTs compared to CCCTs, economic

impacts will be different for base load energy and peak power.7

The base load energy and peak power market analyses compare the baseline

equilibrium (without the regulation) to the regulated market equilibrium. Figure 6-2a

presents a generalized market for the base load electricity that includes the installation of

new turbines to meet demand growth for base load power.

8

 Existing source supply is

characterized by an upward-sloping marginal cost (supply) curve. The supply of new base

load generation capacity is characterized by constant marginal costs and is modeled as a

horizontal supply curve through the current market price. Figure 6-2b shows that the control

costs associated with the rule will affect both existing and new sources of supply, shifting the

market supply curve and leading to an increase in price and decrease in quantity of base load

power consumed.

6.3.2 Other Energy Markets

The petroleum, natural gas, and coal markets are also included in the market

model. Because the overwhelming majority of the affected combustion turbines is projected

to be used in the electricity market, the other energy markets are assumed not to be directly

affected by the rule. However, these markets will be indirectly affected through changes in 
6-8

Figure 6-2. Electricity Market

input fuel prices (i.e., a supply shift) and changes in demand from final product and service

markets using these energy sources (i.e., a demand shift). The ultimate impact on market

price and quantities depends on the relative magnitudes of these shifts. Note the demand for

other fuels may increase (Figure 6-3a) as firms switch away from electricity to petroleum,

natural gas, or coal, or demand may decrease (Figure 6-3b) as the higher price for electricity

suppresses economic activity decreasing demand for all fuels. 

6.3.3 Supply and Demand Elasticities for Energy Markets

The market model incorporates behavioral changes based on the price

elasticities of supply and demand. The price elasticities used to estimate the economic

impacts presented in Section 6.3 are given in Table 6-2. Appendix B contains the sensitivity

analysis for the key supply and demand elasticity assumptions.

Because most of the direct cost impacts fall on the combustion turbines in

electricity markets, the price elasticities of supply in the electricity markets are important

factors influencing the size and distribution of the economic impacts associated with the

combustion turbine regulation. The elasticities of supply are intended to represent the

behavioral 
9The supply curve for new sources is assumed to be horizontal, reflecting a constant marginal cost of production

for new sources.

6-9

Figure 6-3. Potential Market Effects of the NSPS on Petroleum, Natural Gas, or Coal

responses from existing sources.9 However, in general, there is no consensus on estimates of

the price elasticity of supply for electricity. Estimates of the elasticity of supply for electric

power were unavailable. This is in part because, under traditional regulation, the electric

utility industry had a mandate to serve all its customers. In addition, utilities were

compensated on a rate-based rate of return. As a result, the market concept of supply

elasticity was not the driving force in utilities’ capital investment decisions. To

operationalize the model, a supply elasticity of 0.75 was assumed for the base load energy

market. We assumed that the peak power market was one-half of base load energy elasticity. 

Given the uncertainty surrounding these parameters, the Agency conducted a sensitivity

analysis for this value. The results of this sensitivity analysis are reported in Appendix B.

In contrast, many studies have been conducted on the elasticity of demand for

electricity, and it is generally agreed that, in the short run, the demand for electricity is

relatively inelastic. Most residential, commercial, and industrial electricity consumers do not

significantly adjust short-run behavior in response to changes in the price of electricity. The

elasticity of demand for electricity is primarily driven by long-run decisions regarding
6-10

equipment efficiency and fuel substitution. Table 6-3 shows the elasticities of demand used

for the commercial, residential, and transportation sectors.
6-11

Table 6-2. Supply and Demand Elasticities

Elasticity of Demand

Energy

Sectors

Elasticity of

Supply Manufacturing Commerciala Transportationa Residentiala

Electricity:

baseload

energy

0.75 Derived demand Derived

demand

–0.24 –0.23

Electricity:

peak power

0.375b Derived demand Derived

demand

–0.24 –0.23

Natural gas 0.41c Derived demand Derived

demand

–0.47 –0.26

Petroleum 0.58d Derived demand Derived

demand

–0.28 –0.28

Coal 1.0e Derived demand Derived

demand

–0.28 –0.28

a U.S. Department of Energy, Energy Information Administration. 2000b. “Issues in Midterm Analysis and

Forecasting 1999—Table 1.” <http://www.eia.doe.gov/oaif/issues/pricetbl1.html>. As obtained on May 8,

2000.

b Assumed to be one-half of baseload energy elasticity.

c Dahl, Carol A., and Thomas E. Duggan. 1996. “U.S. Energy Product Supply Elasticities: A Survey and

Application to the U.S. Oil Market.” Resource and Energy Economics18:243-263.

d Hogman, William W. 1989. “World Oil Price Projections: A Sensitivity Analysis.” Prepared pursuant to

the Harvard-Japan World Oil Market Study. Cambridge, MA: Energy Environmental Policy Center, John F.

Kennedy School of Government, Harvard University.

e Zimmerman, M.B. 1977. “Modeling Depletion in the Mineral Industry: The Case of Coal.” The Bell

Journal of Economics 8(2):41-65.

Table 6-3. Fuel Price Elasticities

Inputs

Own and Cross Elasticities in 2015

Electricity Natural Gas Coal Residual Distillate

Electricity –0.074 0.092 0.605 0.080 0.017

Natural Gas 0.496 –0.229 1.087 0.346 0.014

Steam Coal 0.021 0.061 –0.499 0.151 0.023

Residual 0.236 0.036 0.650 –0.587 0.012

Distillate 0.247 0.002 0.578 0.044 –0.055

Source: U.S. Department of Energy, Energy Information Administration (EIA). January 1998c. Model

Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System. 

DOE/EIA-M064(98). Washington, DC: U.S. Department of Energy.
6-12

Additional elasticity of demand parameters for the commercial, residential, and

transportation sectors, by fuel type (natural gas, petroleum and coal), were obtained from the

Energy Information Administration. The elasticity of demand in the energy market for the

manufacturing sector is not specified because the model calculates the derived demand for

each of the five energy markets modeled. In effect, adjustments in the final product markets

due to changes in production levels and fuel switching are used to estimate changes in

demand, eliminating the need for demand elasticity parameters in the energy markets. 

6.3.4 Final Product and Service Markets

Producers of final products and services are segmented into industrial,

commercial, transportation, and residential sectors. The industrial sector is further

partitioned into the 23 manufacturing, agricultural, and mining sectors. A partial equilibrium

analysis was conducted for each of these sectors. Changes in production levels and fuel

switching due to the regulation’s impact on the price of electricity are then linked back into

the energy markets.

6.3.4.1 Modeling the Impact on the Industrial and Commercial Sectors

The impact of the regulation on these sectors was modeled using changes in the

cost of Btus used in production processes. In this context, Btus refer to the generic energy

requirements that are used to generate process heat, process steam, or shaft power. As shown

in Figure 6-4, the regulation will increase the cost of Btu production indirectly through

increases in the price of Btus due to control costs on wholesale electricity generators. The

effect is similar to placing a tax on certain types of energy sources (i.e., on Btus generated by

combustion turbines). The firms’ reactions to the change in the cost of Btu production feeds

back into the energy markets in two ways (see Figure 6-4). The first feedback pathway is

through changing the fuel used in the production process. This can include fuel switching,

such as switching from gas turbines to power processes to diesel engines, and/or process

changes that increase energy efficiency and reduce the amount of Btus required per unit of

output. Fuel switching impacts are modeled using cross-price elasticities of demand between

energy sources and own-price elasticities.

EPA modeled fuel switching using secondary data developed by the U.S.

Department of Energy for the National Energy Modeling System (NEMS). Table 6-3

contains fuel price elasticities of demand for electricity, natural gas, petroleum products, and

coal. The diagonal elements in the table represent own-price elasticities. For example, the

table indicates that for steam coal, a 1 percent change in the price of coal will lead to a

0.499 percent decrease in the use of coal. The off diagonal elements are cross-price

elasticities and indicate fuel 
6-13

Figure 6-4. Fuel Market Interactions with Facility-Level Production Decisions

switching propensities. For example, for steam coal, the second column indicates that a

1 percent increase in the price of coal will lead to a 0.061 percent increase in the use of

natural gas.

The second feedback pathway to the energy markets is through the facility’s

change in output. Because Btus are an input into the production process, price increases

(8$/Btu) lead to an upward shift in the industry supply curve. In a perfectly competitive

market, the point where supply equals demand determines the market price and quantity. A

shift in the industry supply curve leads to a change in the equilibrium market price and

quantity. EPA assumed constant returns to scale in production so that the percentage change

in the equilibrium market quantity in each final product and service market equals the

percentage change in Btus consumed by industries.

The change in equilibrium supply and demand in each final industrial and

commercial sector was modeled using a partial equilibrium approach. The size of the

regulation-induced shifts in the final product supply curves is a function of the indirect fuel

costs (determined by the change in fuel prices and the fuel intensity) relative to variable

production costs in each manufacturing industry. 

It was assumed that the demand for final industrial and commercial products

and services is unchanged by the regulation. However, because the demand function

quantifies the change in quantity demanded in response to a change in price, the baseline

demand conditions are important in determining the regulation’s impact. Because prices

changes are anticipated to be small, the key demand parameters are the elasticity of demand
6-14

with respect to changes in the price of final products. Demand elasticities for each of the

sectors included in the analysis are reported in Table 6-4.

6.3.4.2 Impact on the Residential Sector and Transportation Sectors

The residential and transportation sector does not bear any direct costs

associated with the regulation because they do not own combustion turbines. However, they

bear indirect costs due to price increases. These sectors’ change in energy demand in

response to changes in energy prices is modeled as a series of demand curves parameterized

by elasticity of demand parameters (see Table 6-2).

6.3.4.3 Impact on the Government Sector

All combustion turbines projected to be installed by government entities will be

for local generation of electricity. These municipal generators are grouped into the

electricity energy market; thus the government sector is not explicitly included in the model.

6.4 Summary of the Economic Impact Model

We summarize the linkages used to operationalize the estimation of economic

impacts associated with the compliance costs in Figure 6-5.

Control costs on new turbines used for generators will shift the supply curve for

wholesale electricity. The new equilibrium price and quantity in the electricity market will

determine the distribution of impacts between producers (electricity generators) and

consumers. Changes in wholesale electricity generators’ demand for input fuels (due to

changes in the market quantity of electricity) feed back into the natural gas, coal, and

petroleum markets. 

Finally, manufacturers experience supply curve shifts due to changes in prices

for natural gas, petroleum, electricity, and coal. The share of these costs borne by producers

(manufactures) and consumers is determined by the new equilibrium price and quantity in

the final product and service markets. Changes in manufacturers’ Btu demands due to fuel

switching and changes in production levels feed back into the energy markets.

Adjustments in price and quantity in all energy and final product markets occur

simultaneously. A computer model was used to numerically simulate market adjustments by

iterating over commodity prices until equilibrium is reached (i.e., until supply equals demand

in all markets being modeled) and to estimate the economic impact of the regulation (change

in producer and consumer surplus) in the sectors of the economy being modeled.
6-15

Table 6-4. Supply and Demand Elasticities for Industrial and Commercial Sectors

NAICS Description Supply Demand

Industrial Sectors

311 Food 0.75 –1.00

312 Beverage and Tobacco Products 0.75 –1.30

313 Textile Mills 0.75 –1.50

314 Textile Product Mills 0.75 –1.50

315 Apparel 0.75 –1.10

316 Leather and Allied Products 0.75 –1.20

321 Wood Products 0.75 –1.00

322 Paper 0.75 –1.50

323 Printing and Related Support 0.75 –1.80

325 Chemicals 0.75 –1.80

326 Plastics and Rubber Products 0.75 –1.80

327 Nonmetallic Mineral Products 0.75 –1.00

331 Primary Metals 0.75 –1.00

332 Fabricated Metal Products 0.75 –0.20

333 Machinery 0.75 –0.50

334 Computer and Electronic Products 0.75 –0.30

335 Electrical Equip., Appliances, and

Components

0.75 –0.50

336 Transportation Equipment 0.75 –0.50

337 Furniture and Related Products 0.75 –1.80

339 Miscellaneous 0.75 –0.60

11 Agricultural Sector 0.75 –1.80

23 Construction Sector 0.75 –1.00

21 Other Mining Sector 0.75 –0.30

Commercial Sector (NAICS 42-45;51-56;61-72) 0.75 –1.00
6-16

Figure 6-5. Operationalizing the Estimation of Economic Impact
6-17

This model comprises a series of computer spreadsheet modules. The modules

integrate the engineering inputs and the market-level adjustment parameters to estimate the

regulation’s impact on the price and quantity in each market being analyzed. At the heart of

the model is a market-clearing algorithm that compares the total quantity supplied to the total

quantity demanded for each market commodity. Appendix A describes the computer model

in more detail.

6.4.1 Estimating Changes in Social Welfare

The combustion turbine regulation will impact almost every sector of the

economy either directly through control costs or indirectly through changes in the price of

energy and final products. For example, a share of control costs that originate in the energy

markets are passed through the final product markets and are borne by both the producers

and consumers of final products. To estimate the total change in social welfare without

double-counting impacts across the linked partial equilibrium markets being modeled, EPA

quantified social welfare changes for the following categories:

C change in producer surplus in the energy markets,

C change in producer surplus in the final product and service markets,

C change in consumer surplus in the final product and service markets, residential

and transportation energy markets.

Figure 6-6 illustrates the change in producer and consumer surplus in the intermediate energy

market and the final product markets. For example, assume a simple world with only one

energy market, wholesale electricity, and one final product market, pulp and paper. If the

regulation increased the cost of generating wholesale electricity, then part of the cost of the

regulation will be borne by the electricity producers as decreased producer surplus and part

of the costs will be passed on to the pulp and paper manufacturers. In Figure 6-6a, the pulp

and paper manufacturers are the consumers of electricity, so the change in consumer surplus

is displayed. This change in consumer surplus in the energy market is captured by the final

product market (because the consumer is the pulp and paper industry in this case), where it is

split between consumer surplus and producer surplus in those markets. Figure 6-6b shows

the change in producer surplus in the energy market.

As shown in Figures 6-6c and 6-6d, the cost affects the pulp and paper industry

by shifting up the supply curve in the pulp and paper market. These higher electricity prices

therefore lead to costs in the pulp and paper industry that are distributed between producers
6-18

Figure 6-6. Changes in Economic Welfare with Regulation

and consumers of paper products in the form of lower producer surplus and lower consumer

surplus. Note that the change in consumer surplus in the intermediate energy market must 
6-19

equal the total change in consumer and producer surplus in the final product market. Thus,

to avoid double-counting, the change in consumer surplus in the intermediate energy market

was not quantified; instead the total change in social welfare was calculated as

Change in Social Welfare = 3)PSE + 3)PSF + 3)CSF + 3)CSRT (6.1)

where 

)PSE = change in producer surplus in the energy markets,

)PSF = change in producer surplus in the final product markets,

)CSF = change in consumer surplus in the final product markets, and

)CSRT = change in consumer surplus residential and transportation energy

markets.

Appendix A contains the detailed equations used to calculate the change in producer and

consumer surplus in the appropriate intermediate and final product markets.
7-1

SECTION 7

ECONOMIC IMPACT ANALYSIS

Control measures implemented to comply with the NSPS will impose

regulatory costs on affected facilities in the energy, manufacturing, commercial, and

government sectors. These costs will be distributed between producers and consumers

through changes in energy prices and changes in prices of final products and services. This

section describes the compliance costs of the regulatory alternatives and presents the

economic impact estimates, including energy impacts, of the NSPS.

7.1 Engineering Control Cost Inputs

To calculate the total cost of the NOx emission standard by the fifth year after

promulgation, one calculated them based on the requirements of the NSPS. It has been noted

earlier in this EIA (Chapter 3) that the add-on controls that the ten new turbines would have

to apply to comply with this proposal will already be applied in response to Prevention of

Significant Deterioration/New Source Review (PSD/NSR) requirements. Thus, the total

capital cost of this proposal is essentially zero. The requirements of this NSPS are those for

inital performance testing, fuel sampling, monitoring and recordkeeping. Table 7-1 shows

the total annual cost associated with these requirements in the fifth year after promulgation

for each MW range. These annual costs total $3.4 million. As a result, the total annual cost

of the NSPS is $3.4 million (1998$).

7.1.1 Computing Supply Shifts in the Electricity Market

For the purpose of the market model, the electric services industry is broken

into two market sectors: base load energy and peak power. As shown in Section 4 (Table 4-

3), EPA estimates approximately two-thirds of new combustion turbine units are projected to

contribute to the base load energy market, and the remaining one-third are projected to

contribute to the peak power market. As a result, the control costs for the electricity are

distributed 67 percent to the electric base load energy market and 33 percent to the peak

power market. The relative shift in the supply curve for each segment is presented as the

percentage shift in the price of the marginal unit produced. The percentage shift is calculated
10Revenue in the electric utility industry was segmented into the base load and peak power markets assuming an

80/20 split, respectively. This ratio was estimated based on discussions with industry experts.

7-2

Table 7-1. Total Capital and Annual Cost of the Proposed NSPS in the Fifth Year

Total Capital Cost

Control cost $0

Total Annual Cost

Control cost $0

Initial performance testing $369,200

Fuel sampling $206,681

Monitoring and recordkeeping $2,393,730

Reporting $440,519

Total $3,410,130

Source: Alpha-Gamma Technologies, Inc. January _, 2005. “Cost Impact of Proposed NSPS for Stationary

Combustion Turbines.” Memorandum to Jaime Pagan, EPA OAQPS ESD Combustion Group from

Melanie Taylor, Alpha-Gamma Technologies, Inc.

as the ratio of compliance costs to the revenue of the affected portion of the industry10 (see

Table 7-2). Affected sources with performance testing, fuel sampling, monitoring and

recordkeeping, and reporting have shifts of 0.1 percent for base and peak load. The

remaining segments are unaffected (i.e., supply shift equals zero). 

Figure 7-1 illustrates the supply shifts and shows the with-regulation supply

curve S1. In this example, the regulation leads to an increased supply by unaffected units,

crowding out the new units with compliance costs. 

7.2 Market-Level Results

The model projects the NSPS standard will increase base load electricity price

by 0.03 percent and peak power prices by 0.04 percent (see Table 7-3). Domestic production

declines by 0.005 and 0.011 percent, respectively. 
7-3

Table 7-2. Summary of Turbine Cost Information and Supply Shifts

Share Units

of Market

(%)

Revenuea

($109

)

Control

Costsa

 ($106

)

Supply Shift

(%)

Base Load Energy

Existing 97.5% $173.29 — 0.0%

New affected: initial performance

testing, fuel sampling, monitoring and

recordkeeping, and reporting only

2.3% $4.17 $2.2 0.1%

Total 100.0% $177.64 $2.2 0.0%

Peak Power

Existing 97.5% $43.32 — 0.0%

New affected: initial performance

testing, fuel sampling, monitoring and

recordkeeping, and reporting only

2.3% $1.04 $1.2 0.1%

Total 100.0% $44.40 $3.4 0.0%

aRevenues and costs are in 1998$. 

The analysis also shows the impact on distribution of electricity supply (see

Table 7-4). The increase in the price of electricity will make it profitable for unaffected

sources to increase supply, displacing approximately 0.1 percent of affected new supply. 

This increase in supply implies that fewer older units may be retired as a result of the

regulation. The remaining change in quantity results from decreased consumer demand as

the prices of base load energy and peak power increase. However, all these effects are very

small.

In the natural gas and petroleum markets, both the price and quantity increase,

indicating that an increase in demand for the fuel (due to fuel switching) dominates the

upward shift in the supply curve (increased electricity costs as a fuel input). Price increases

in these markets are below 0.1 percent. Price and quantity decrease in the coal market,

reflecting the decreased demand for coal as electric utilities reduce output. Market-level

impacts on downstream product and service markets are essentially zero.
7-4

Figure 7-1. Market for Baseload Electricity

7.3 Social Cost Estimates

The social impact of a regulatory action is traditionally measured by the change

in economic welfare that it generates. The social costs of the rule will be distributed across

producers of energy and their customers. Producers experience welfare impacts resulting

from changes in profits corresponding with the changes in production levels and market

prices. Consumers experience welfare impacts due to changes in market prices and 
7-5

Table 7-3. Market-Level Impacts of Stationary Combustion Turbines NSPS Standard: 

2010

Percent Change

Energy Markets Price Quantity

Petroleum 0.002 0.001

Natural Gas 0.007 0.002

Base Electricity 0.028 –0.005

Peak Electricity 0.044 –0.011

Coal –0.001 –0.001

Industrial Sectors

NAICS Description Description

Percent Change

Price Quantity

311 Food 0.000 0.000

312 Beverage and Tobacco Products 0.000 0.000

313 Textile Mills 0.000 –0.000

314 Textile Product Mills 0.000 0.000

315 Apparel 0.000 0.000

316 Leather and Allied Products 0.000 0.000

321 Wood Products 0.000 0.000

322 Paper 0.000 –0.000

323 Printing and Related Support 0.000 0.000

325 Chemicals 0.000 –0.000

326 Plastics and Rubber Products 0.000 –0.000

327 Nonmetallic Mineral Products 0.000 –0.000

331 Primary Metals 0.000 –0.000

332 Fabricated Metal Products 0.000 0.000

333 Machinery 0.000 0.000

334 Computer and Electronic Products 0.000 0.000

335 Electrical Equipment, Appliances, and

Components

0.000 0.000

336 Transportation Equipment 0.000 0.000

337 Furniture and Related Products 0.000 0.000

339 Miscellaneous 0.000 0.000

11 Agricultural Sector 0.000 –0.000

23 Construction Sector 0.001 –0.001

21 Other Mining Sector 0.001 0.000

Commercial Sector 0.000 0.000

aActual value for all 0.000 entries for the various sectors is > –0.001 and < 0.
7-6

consumption levels. 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 to approximate the social

cost of the rule. The engineering analysis estimated annual costs of $3.4 million. In cases

where the engineering costs of compliance are used to estimate social cost, the burden of the

regulation is measured as falling solely on the affected producers, who 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, because no change in market

price is estimated. 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 conducted by the Agency accounts for

behavioral responses by producers and consumers to the regulation, as affected producers

shift costs to other economic agents. This approach results in a social cost estimate that may

differ from the engineering compliance cost estimate and also provides insights on how the

regulatory burden is distributed across stakeholders. As shown in Table 7-5, the economic

model estimates the total social cost of the rule to be $2 million. The social cost estimate is

slightly less than the estimated engineering costs as a result of behavioral changes of

producers and consumers. Therefore the social costs primarily reflect higher costs by

existing units to increase supply, and the deadweight loss to consumers as price increases and

quantity decreases. It should be noted that this social cost estimate does not account for the

benefits of emission reductions associated with this proposed NSPS and hence is not net of

these impacts to society. 

Table 7-4. Changes in Market Shares for Electricity Suppliers

Baseline Shares (%)

With Regulation Shares

(%)

Existing—unaffected 97.5 97.6

New—initial performance testing,

fuel sampling, monitoring and

recordkeeping, reporting only

2.3 2.3

New—controls, initial performance

testing, fuel sampling, monitoring and

recordkeeping, reporting 

0.1 0.0
7-7

Table 7-5. Distribution of Social Costs of Stationary Combustion Turbines NSPS: 2010

($1998 106

)

Change in:

Sectors/Markets

Producer

Surplus

Consumer

Surplus

Social

Welfare

Energy Sector

Petroleum (NAICS 32411, 4861) $7 NA NA

Natural Gas (NAICS 21111, 4862, 2212) $6 NA NA

Electricity (NAICS 22111, 221122, 221121) $68 NA NA

Coal (NAICS 2121) –$1 NA NA

Subtotal: $80 NA NA

Change in:

Industrial Sector 

NAICS Description

Producer

Surplus

Consumer

Surplus

Social

Welfare

311 Food –$1 –$0 –$1

312 Beverage and Tobacco Products $0 $0 $0

313 Textiles Mills –$0 $0 –$0

314 Textile Product Mills $0 $0 $0

315 Apparel $0 $0 $0

316 Leather and Allied Products $0 $0 $0

321 Wood Products $0 $0 –$0

322 Paper –$1 –$0 –$1

323 Printing and Related Support $0 $0 –$0

325 Chemicals –$2 –$1 –$3

326 Plastics and Rubber Products –$1 –$0 –$1

327 Nonmetallic Mineral Products –$1 –$0 –$1

331 Primary Metals –$2 –$1 –$3

332 Fabricated Metal Products $0 –$1 –$1

333 Machinery $0 –$0 –$0

334 Computer and Electronic Products $0 –$0 –$0

335 Electrical Equipment, Appliances, and

Components

$0 $0 –$0

336 Transportation Equipment –$1 –$0 –$1

337 Furniture and Related Products $0 $0 $0

339 Miscellaneous $0 $0 $0

11 Agricultural Sector –$1 –$1 –$2

23 Construction Sector –$8 –$6 –$14

21 Other Mining Sector $0 $1 –$1

Industrial Sector Subtotal: –$18 –$11 –$29

Commercial Sector –$14 –$10 –$24

Residential Sector NA –$23 –$26

Transportation Sector NA –$6 –$6

Subtotal –32 –$50 –$82

Grand Total $48 –$50 –$2
7-8

The analysis also shows important distributional impacts across stakeholders. 

For example, the model projects consumers will bear a burden of $50 million, as a result of

higher energy prices. In contrast, producer surplus increases by $48 million as energy

producers, particularly the electricity industry, become more profitable with higher prices.

7.4 Energy Impact Analysis

Executive Order 13211, “Actions Concerning Regulations That Significantly

Affect Energy Supply, Distribution, or Use” (66 Fed. Reg. 28355 [May 22, 2001]), requires

EPA to prepare and submit a Statement of Energy Effects to the Administrator of the Office

of Information and Regulatory Affairs, Office of Management and Budget, for certain

actions identified as “significant energy actions.” Section 4(b) of Executive Order 13211

defines “significant energy actions” as “any action by an agency (normally published in the

Federal Register) that promulgates or is expected to lead to the promulgation of a final rule

or regulation, including notices of inquiry, advance notices of proposed rulemaking, and

notices of proposed rulemaking:

C that is a significant regulatory action under Executive Order 12866 or any

successor order, and is likely to have a significant adverse effect on the supply,

distribution, or use of energy; or 

C that is designated by the Administrator of the Office of Information and

Regulatory Affairs as a significant energy action.” 

Although the proposed NSPS is considered to be a significant regulatory action

under Executive Order 12866, it is not a “significant energy action” because it is not likely to

have a significant adverse effect on the supply, distribution, or use of energy. No Statement

of Energy Effects is required for this proposed rule, but the following energy impact

estimates are included for informational purposes.

Energy Price Effects. As described in the market-level results section,

electricity prices are projected to increase by less than 0.1 percent. Petroleum and natural

gas prices are all projected to increase by less than 0.1 percent. The price of coal is projected

to decrease slightly.

Impacts on Electricity Supply, Distribution, and Use. We project the increased

compliance costs for the electricity market will result in an annual production decline of

approximately 0.2 billion kWh. Note these effects have been mitigated to some degree since

sectors previously using electricity in the baseline will switch to other energy sources (see

below).
7-9

Impacts on Petroleum, Natural Gas, and Coal Supply, Distribution, and Use. 

The rule will lead to higher electricity prices relative to other fuel types, resulting in fuel

switching. The model projects increases in petroleum production/consumption of

approximately 300 barrels per day. Similarly, natural gas production/consumption is

projected to increase by 2 million cubic feet per day. The model also projects decreases in

coal production/consumption of approximately 30 short tons per year. We expect that there

will be no discernable impact on the import of foreign energy supplies, and no other adverse

outcomes are expected to occur with regards to energy supplies. Also, the increase in cost of

energy production should be minimal given the very small increase in fuel consumption

resulting from back pressure related to operation of add-on control devices, such as SCR

emission control devices. All of the estimates presented above account for some passthrough

of costs to consumers as well as the direct cost impact to producers. 
8-1

SECTION 8

SMALL ENTITY IMPACTS

The regulatory costs imposed on domestic producers and government entities to

reduce air emissions from combustion turbines will have a direct impact on owners of

the affected facilities. Firms or individuals that own the facilities with combustion turbines

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

business decisions that affect the facility. The legal and financial responsibility for

compliance with a regulatory action ultimately rests with these owners, who must bear the

financial consequences of their decisions. Environmental regulations potentially affect all

sizes of businesses, but small businesses may have special problems relative to large

businesses in complying with such regulations.

The RFA of 1980 requires that special consideration be given to small entities

affected by federal regulations. The RFA was amended in 1996 by SBREFA to strengthen

the RFA’s analytical and procedural requirements. Prior to enactment of SBREFA, EPA

exceeded the requirements of the RFA by requiring the preparation of a regulatory flexibility

analysis for every rule that would have any impact, no matter how minor, on any number, no

matter how small, of small entities. Under SBREFA, however, the Agency decided to

implement the RFA as written and to require a regulatory flexibility analysis only for rules

that will have a significant impact on a substantial number of small entities. In practical

terms, the amount of analysis of impacts to small entities has not changed, for SBREFA

required EPA to increase involvement of small entities in the rulemaking process. 

This section investigates characteristics of businesses and government entities that

are likely to install new combustion turbines affected by this rule and provides a preliminary

screening-level analysis to assist in determining whether this rule is likely to impose a

significant impact on a substantial number of the small businesses within this industry. 

The screening-level analysis employed here is a “sales test,” which computes the

annualized compliance costs as a share of sales/revenue for existing companies/government

entities. Existing companies/government entities with combustion turbines are used to

provide insights into future companies/government entities that are likely to install new

turbines that are affected by the regulation. 
11Public and private electric service providers are defined as small if their annual generation is less than 4

million kWh. Local government entities that own combustion turbines are defined as small if the city

population is fewer than 50,000. In the manufacturing sector, companies are defined as small if the total

employment of the parent company is fewer than 500.

8-1

8.1 Identifying Small Businesses

As described in Section 3 of this report, the Agency has projected that approximately

355 new combustion turbines will begin operation during the next 5-years. Approximately

10 sources would be required to comply with the NOx emission standard for the Gas Turbine

NSPS by applying add-on controls, as mentioned earlier in this report (Chapter 3). However,

as also mentioned earlier in this report, these 10 new turbines will already be required to

install add-on controls to meet NOx reductions under the PSD/NSR programs. The only

requirements on them due to this NSPS will be initial performance testing, fuel sampling,

monitoring and recordkeeping, and reporting. No existing combustion turbines will be

affected by the regulation. However, because it is not possible to project specific companies

or government organizations that will purchase combustion turbines in the future, the small

entity screening analysis for the combustion turbine rule is based on the evaluation of

existing owners of combustion turbines. It is assumed that the existing size and ownership

distribution of combustion turbines contained in the Inventory Database is representative of

the future growth in new combustion turbines. The remainder of this section presents cost

and sales information on small companies and government organizations that own existing

combustion turbines of 1 MW or greater.

8.2 Screening-Level Analysis

Based on the Inventory Database and Small Business Administration (SBA)

definitions, 29 small entities own 51 units, which are located at 35 facilities.11 The 51 units

owned by small entities represent approximately 2.5 percent of the 2,072 units in the

Inventory Database with valid capacity information. This implies that approximately 1 out

of the 10 new affected units will be owned by a small entity. Based on our previous

research, the 29 small entities have an average revenue (sales) of approximately $80 million. 

We compared the average unit compliance costs ($3.4/10 = $0.34 million) with the average

sales value and for a typical small entities and calculated the cost to sales ratio for the

potentially affected small entity is 0.3 percent.
R-2

8.3 Assessment

The RFA generally requires an agency to prepare a regulatory flexibility analysis of

any rule subject to notice and comment rulemaking requirements under the Administrative

Procedure Act or any other statute unless the agency certifies that the rule will not have a

significant economic impact on a substantial number of small entities. Small entities include

small businesses, small organizations, and small governmental jurisdictions.

For purposes of assessing the impacts of today’s rule on small entities, small entity is

defined as:

C a small business whose parent company has fewer than 100 or 1,000 employees,

depending on size definition for the affected NAICS code, or fewer than 4 billion

kW-hr per year of electricity usage;

C a small governmental jurisdiction that is a government of a city, county, town,

school district, or special district with a population of fewer than 50,000; and

C a small organization that is any not-for-profit enterprise, which is independently

owned and operated and is not dominant in its field.

It should be noted that small entities in one three-digit NAICS codes are affected by this rule,

and the small business definition applied to this industry by NAICS code is that listed in the

SBA size standards (13 CFR 121). 

The economic impacts of the proposed NSPS are expected to be insignificant. In

addition, since there is only one small entity affected by this proposal, there is no significant

impact (economic) to a substantial number of small entities (or SISNOSE).

 

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A-1

APPENDIX A

OVERVIEW OF THE MARKET MODEL

To develop estimates of the economic impacts on society resulting from the

regulation, the Agency developed a computational model using a framework that is

consistent with economic analyses performed for other rules. This approach employs

standard microeconomic concepts to model behavioral responses expected to occur

with the regulation. This appendix describes the spreadsheet model in detail and

discusses how the Agency

C characterized the supply and demand in the energy markets,

C characterized supply and demand responses in industrial and commercial

markets,

C introduced a policy “shock” into the electricity market by using control

cost-induced shifts in the supply functions of affected supply segments

(new and existing sources),

C introduced indirect shifts in market supply functions resulting from

changes in energy prices

C used a solution algorithm to determine a new with-regulation equilibrium

in each market.

A.1 Energy Markets

The operational model includes five energy markets: coal, electricity (base load

energy), electricity (peak power), natural gas, and petroleum. The following sections

describe supply and demand equations the Agency developed to characterize these

markets. The data source for the price and quantity data used to calibrate the model

is the Department of Energy’s Supplemental Tables to the Annual Energy Outlook

2000 (DOE, EIA, 2001). 

A.1.1 Supply Side Modeling

The Agency modeled the existing market supply of energy markets (QSi) using a

single representative supplier with an upward-sloping supply curve. The CobbDouglas (CD) function specification is
A-2

(A.1)

(A.2)

where

= the supply of energy product i,

Ai = a parameter that calibrates the supply equation to replicate the

estimated 2005 level of production (Btu),

pi = the 2005 ($/Btu) market price for product i, and

ci = direct compliance costs (electricity markets only). Supply

shifts were computed and reported in Section 6, Table 6-2.

= indirect effects of changes in input prices, where is the fuel

share, i indexes the energy market. The fuel share is allowed

to vary using a fuel switching rule using cross-price elasticities

of demand between energy sources, as described in Section 5

of the report.

= the domestic supply elasticity for product i. 

For the electricity markets, new supply sources are characterized with a constant

marginal cost (supply) curve. In baseline, these units are willing to supply their

generation capacity at the baseline market price (P0i). With regulation, affected

sources are willing to supply their generation capacity if the new price (P1i) exceeds

costs (baseline + direct + indirect) :

A.1.2 Demand Side Modeling

Market demand in the energy markets (QDi) is expressed as the sum of the energy,

residential, transportation, industrial, and commercial sectors:
A-3

(A.3)

(A.4)

(A.5)

where i indexes the energy market and j indexes the consuming sector. The Agency modeled

the residential, and transportation sectors as single representative demanders using a

simple Cobb Douglas specification:

where p is the market price, is an assumed demand elasticity (actual values are presented in

Section 5, Table 5-2), and A is a demand parameter. In contrast, the energy,

industrial and commercial sectors demand is modeled as a derived demand resulting

from the production/consumption choices in agricultural, energy, mining,

manufacturing, and service industries. Changes in energy demand for these

industries respond to changes in output and fuel switching that occurs in response to

changes in relative energy prices projected in the energy markets. For each sector, 

energy demand is expressed as follows:

where qD is demand for energy, QD is output in the final product or service market, FSW is a

factor generated by the fuel switching algorithm, i indexes the energy market, j

indexes the market. The subscripts 0 and 1 represent baseline and with regulation

conditions, respectively.

A.2 Industrial and Commercial Markets

Given data limitations associated with the scope of potentially affected industrial and

commercial markets, EPA used an alternative approach to estimate the relative

changes in price and quantities. These measures are used to compute change in

economic welfare as described in Section A.4.

A.2.1 Compute Percentage Change in Market Price

First, we computed the change in production costs resulting from changes in the

market price of fuels (determined in the energy markets): 
12The fuel share is allowed to vary using a fuel switching rule using cross-price elasticities of demand between

energy sources, as described in Section 5. 

A-4

(A.6)

(A.7)

where is the fuel share,12 i indexes the energy market, and j indexes the industrial or

commercial market. We use the results from equation A.6 and the market supply and

demand elasticities to compute the change in market price:

A.2.2 Compute Percentage Change in Market Quantity

Using the percentage change in the price calculated in Equation A.7 and assumptions

regarding the market demand elasticity, the relative change in quantity was

computed. For example, in a market where the demand elasticity is assumed to be -1

(i.e., unitary), a 1 percent increase in price results in a 1 percent decrease in quantity. 

This change was then input into equation A.5 to determine energy demand. 

A.3 With-Regulation Market Equilibrium Determination

Market adjustments can be conceptualized as an interactive feedback process. Supply

segments face increased production costs as a result of the rule and are willing to

supply smaller quantities at the baseline price. This reduction in market supply leads

to an increase in the market price that all producers and consumers face, which leads

to further responses by producers and consumers and thus new market prices, and so

on. The new with-regulation equilibrium is the result of a series of iterations in

which price is adjusted and producers and consumers respond, until a set of stable

market prices arises where total market supply equals market demand (i.e., Qs = QD)

in each market. Market price adjustment takes place based on a price revision rule

that adjusts price upward (downward) by a given percentage in response to excess

demand (excess supply).

The algorithm for determining with-regulation equilibria can be summarized by

seven recursive steps:
A-5

1. Impose the control costs on electricity supply segments, thereby affecting

their supply decisions.

2. Recalculate the market supply in the energy markets. Excess demand

exists.

3. Determine the new energy prices via a price revision rule. 

4. Recalculate energy market supply.

5. Account for fuel switching given new energy prices. Solve for new

equilibrium in final product and service market.

6. Compute energy demand.

7. Compare supply and demand in energy markets. If equilibrium conditions

are not satisfied, go to Step 3, resulting in a new set of energy prices. 

Repeat until equilibrium conditions are satisfied (i.e., the ratio of supply to

demand is arbitrarily close to one).

A.4 Computing Social Costs

In the energy markets, consumers(residential and transportation) and producer

surplus were calculated using standard methods based on the price and quantity

before and after regulation. In the industrial and commercial markets, however, there

is no easily defined price or quantity due to the wide variety of products that fall

under each sector (i.e. NAICs code). Therefore, methods of calculating consumer

and producer surplus are defined based on relative changes in price and quantity and

total industry sales rather than on the price and quantity directly. The following

sections describe how we derive welfare estimates for these markets.

A.4.1 Change in Consumer Surplus 

If price and quantities were available, a linear approximation of the change in

consumer surplus can be calculated using the following formula:

)CS = –[( P) Q0 –0.5( Q) ( P)], (A.8)

where Q0 denotes the baseline quantity. Given the model only estimates relative changes in

price and quantity for each industrial/commercial market, changes in consumer

surplus were calculated using these data and total revenue by NAICS code as shown

below: 
13Multiplying price and quantity in an industry yields total industry revenue. The U.S. Census Bureau provides

shipment data for the NAICs codes included in the economic model.

A-6

CS = –[( P) Q1 – 0.5 ( Q) ( P)] (P1 Q1)/(P1 Q1)

)CS = –[%)P – 0.5 (%)P) (%)Q)] (P1

 Q1

). (A.9)

A.4.2 Change in Producer Surplus

If price and quantities were available, a linear approximation could also be used to

compute the change in producer surplus:

PS =–[((CC/Q1) – P)(Q1 – Q)]+ 0.5 [(CC/Q1 – P) ( Q)], (A.10)

where CC/Q1 equals the per-unit “cost-shifter” of the regulation. Again, we transform this

equation into one that relies only on percentage changes in price and quantity, total

revenue,

13 and compliance costs:

PS = – [((CC/Q1) – P)(Q1 – Q)]+ 0.5 [((CC/Q1) – P)( Q)](P1 Q1)/(P1 Q1)

PS = – [(% cost shift – % P)(1 – % Q)+ 0.5 (% cost shift – % P )(% Q)][P1 Q1]

PS = – [% cost shift – % P ][1 – 0.5(% Q)][TR], (A.11)
B-1

APPENDIX B

ASSUMPTIONS AND SENSITIVITY ANALYSIS

In developing the economic model to estimate the impacts of the stationary

combustion turbine NSPS, several assumptions were necessary to make the model

operational. This appendix lists and explains the major model assumptions and

describes their potential impact on the analysis results. Sensitivity analyses are

presented for numeric assumptions. 

Assumption: The domestic markets for energy are perfectly competitive.

Explanation: Assuming that the markets for energy are perfectly competitive implies that

individual producers are not capable of unilaterally affecting the prices they receive

for their products. Under perfect competition, firms that raise their price above the

competitive price are unable to sell at that higher price because they are a small share

of the market and consumers can easily buy from one of a multitude of other firms

that are selling at the competitive price level. Given the relatively homogeneous

nature of individual energy products (petroleum, coal, natural gas, electricity), the

assumption of perfect competition at the national level seems to be appropriate.

Possible Impact: If energy markets were in fact imperfectly competitive, implying that

individual producers can exercise market power and thus affect the prices they

receive for their products, then the economic model would understate possible

increases in the price of energy due to the regulation as well as the social costs of the

regulation. Under imperfect competition, energy producers would be able to pass

along more of the costs of the regulation to consumers; thus, consumer surplus losses

would be greater, and producer surplus losses would be smaller in the energy

markets.

Assumption: Base load energy and peak power represent 80 percent and 20 percent,

respectively, of the total cost of electricity production.

Explanation: With deregulation, it is increasingly common for base load energy and peak

power to be traded as different commodities. This economic model segments the

electricity market into these separate markets. However, no production cost or sales

data are currently available to partition the electricity market into base load and peak
B-2

power markets. The 80/20 percent was obtained from discussions with industry

experts. 

Sensitivity Analysis: Table B-1 shows how estimated economic impacts change as the share

of base load versus peak power costs varies.

Assumption: The elasticity of supply in the base load and peak power electricity

markets for existing sources is approximately 0.75 and 0.38, respectively. 

Explanation: The price elasticity of supply in the electricity markets represents the

behavioral responses from existing sources to changes in the price of electricity. 

However, there is no consensus on estimates of the price elasticity of supply for

electricity. This is in part because, under traditional regulation, the electric utility

industry had a mandate to serve all its customers and utilities were compensated on a

rate-based rate of return. As a result, the market concept of supply elasticity was not

the driving force in utilities’ capital investment decisions. This has changed under

deregulation. The market price for electricity has become the determining factor in

decisions to retire older units or to make higher cost units available to the market.

Sensitivity Analysis: Table B-2 shows how the economic impact estimates vary as the

elasticity of supply in the electricity markets varies.

Table B-1. Sensitivity Analysis: Base Load and Peak Power Markets’ Share of

Electricity Production Costs ($106)

Base Load = 70%

Peak = 30%

Base Load = 80%

Peak = 20%

Base Load = 90%

Peak = 10%

Change in producer

surplus

213 208 203

Change in consumer

surplus

–215 –209 –204

Change in social welfare –2 –2 –2
B-3

Assumption: The domestic markets for final products and services are all

perfectly competitive. 

Explanation: Assuming that these markets are perfectly competitive implies that the

producers of these products are unable to unilaterally affect the prices they receive for

their products. Because the industries used in this analysis are aggregated across a

large number of individual producers, it is a reasonable assumption that the individual

producers have a very small share of industry sales and cannot individually influence

the price of output from that industry. 

Possible Impact: If these product markets were in fact imperfectly competitive, implying

that individual producers can exercise market power and thus affect the prices they

receive for their products, then the economic model would understate possible

increases in the price of final products due to the regulation as well as the social costs

of the regulation. Under imperfect competition, producers would be able to pass

along more of the costs of the regulation to consumers; thus, consumer surplus losses

would be greater, and producer surplus losses would be smaller in the final product

markets. 

Assumption: The elasticity of supply in final product markets.

Explanation: The final product markets are modeled at the two-, and three-digit NAICS

codes level to operationalize the economic model. Because of the high level of

aggregation, elasticities of supply and demand estimates are not often available in the

literature. The elasticities of supply and demand in the final product markets

primarily determine the distribution of economic impacts between producers and

consumers.

Sensitivity Analysis: Table B-3 shows how the economic impact estimates vary as the

supply and demand elasticities in the final product markets vary.

Table B-2. Sensitivity Analysis: Elasticity of Supply in the Electricity Markets

ES = –25% Base Case ES = + 25%

Change in producer surplus 235 208 185

Change in consumer

surplus

–237 –209 –187

Change in social welfare –2 –2 –2
B-4

Table B-3. Sensitivity Analysis: Supply and Demand Elasticities in the Final Product

Markets

ES = –25%

ED = +25%

ES = Base Case

ED = Base Case

ES = +25%

ED = –25%

Change in producer surplus 185 208 231

Change in consumer surplus –187 –209 –233

Change in social welfare –2 –2 –2
B-5

Assumption: The amount of energy (in terms of Btus) required to produce a unit of

output in the final product markets remains constant as output changes and

prices.

Explanation: The importance of this assumption is that when output in the final product

markets changes as a result of a change in energy prices, it is assumed that the

amount of fuel used changes in the same proportion as output, although the

distribution of fuel usage among fuel types may change due to fuel switching. This

change in the demand for fuels feeds into the energy markets and affects the

equilibrium price and quantity in the energy markets.

Possible Impact: For example, fuel usage per unit output may change if the price of energy

increases because of increased energy efficiency. National energy-efficiency trends

are included in the model through projected Btu consumption (i.e., Btu consumption

is projected to grow more slowly than output). However, if the regulation leads to

increased energy efficiency because of higher fuel prices, this will result in a smaller

economic impact than the model results presented in Section 6 indicate. 

Assumption: Sensitivity to Fuel Switching.

Sensitivity Analysis: Table B-4 shows how the economic impact estimates vary as fuelswitching is turned on or off in the model. 

Table B-4. Sensitivity Analysis: Own- and Cross-Price Elasticities Used to Model Fuel

Switching

Base Case Without Fuel Switching

Change in producer surplus 208 207

Change in consumer surplus –209 –208

Change in social welfare –2 –2
B-6

United States Office of Air Quality Planning and Standards Publication No. EPA-452/R-05-001

Environmental Protection Agency Air Quality Strategies and Standards Division February 2005 

Research Triangle Park, NC